Reviewer #2 (Public Review):

Summary:<br /> The study provides valuable and compelling evidence that while activation of the mTOR cascade confers some similarities in alterations in cell size, mTOR pathway activation, cortical lamination, baseline firing properties, and synaptic activity, there are distinctions that could account for clinical differences in seizure and epilepsy phenotypes in patients harboring these mutations. These findings could have important implications going forward as we design clinical therapeutic strategies to modulate mTOR activity in these individuals to treat seizures.

This study presents a valuable finding on the role that distinct mTOR pathway genes play in altered cell shape, cortical laminar migration, and cellular excitability in the mouse medial prefrontal cortex (mPFC). The evidence supporting the claims of the authors is solid, although analysis of the role of the mTORC2 pathway and consideration of distinct metabolic states i.e., amino acid levels would have strengthened the study. The work will be of interest to neuroscientists working on human epilepsy. These genes have each been assayed in previous independent studies and thus the direct comparison is what provides the innovation and interest.

The manuscript by Nguyen and colleagues attempts to define both the common and differential roles of mTOR pathway genes, both by gene knockout (KO) and activation, on cortical neuronal size, cortical lamination, and excitability. They focused on 5 genes that have been linked to human malformations of cortical development (MCD) and epilepsy: RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO. The RhebY35L, mTORS2215Y are known and pathogenic human gain-of-function variants. Each of these genes is known to modulate the activity of mTORC1 and either KO or activation will lead to abnormal and persistent hyperactivation of mTOR activity. Using in utero electroporation they transfected plasmids containing these gene constructs into fetal mouse brains at E15.5 and then assessed neuronal shape and size, laminar positioning, spontaneous activity, synaptic activity, and expression of a novel voltage-gated potassium channel (HCN4) at varying time postnatally e.g., P7-9 (neonates) and P28-43 (young adults).

The study clearly achieves its stated aims i.e., that disruption of each of five distinct mTOR pathway genes, Rheb, mTOR, Depdc5, Pten, and Tsc1, individually impacts pyramidal neuron development and electrophysiological function in the mouse mPFC. The data from each of the 5 genes provides strong support to the notion that mTOR pathway gene mutations yield the unifying clinical parcellation of mTORopathies, likely as a consequence of mTOR pathway activation. The data also provide interesting evidence that subtle or even overt differences in clinical phenotypes between RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO in humans could be due to effects of these genes either on mTOR or on yet to be defined alternative pathways. Assuredly follow-up studies to examine how Rheb, mTOR, Dedpdc5, Pten, and Tsc1 engage with other protein binding partners or other pathways will be warranted in future studies.

Strengths:<br /> The investigators demonstrate that gene KO or activation leads to common changes in cell size (enlargement) though with different effects across each gene subtype suggesting distinct genetic effects despite a common effect on mTOR signaling. The major effect was seen in forebrain neurons expressing mTORS2215Y. They also report gene-specific effects of each mTOR pathway gene on cortical lamination. For example, while RhebY35L, mTORS2215Y, Dedpdc5KO, and Tsc1KO significantly disrupted laminar positioning of neurons in layer 2/3, PtenKO had minimal effects on laminar positioning. This finding is intriguing since it means that simply activating mTOR during fetal brain development will not necessarily alter cortical lamination and that an increase in cell size by itself doesn't disrupt laminar fidelity. To verify that the expression of plasmids led to mTORC1 hyperactivation, phosphorylated levels of S6 (i.e., p-S6), a downstream substrate of mTORC1, were assayed by immunohistochemistry in P28-43 mice. Expression of the RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO plasmids all led to significantly increased p-S6 staining intensity, supporting that the expression of each of these plasmids leads to increased mTORC1 signaling.

Whole-cell current- and voltage-clamp recordings were performed in P25-P51 mice in acute brain slice preparations. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to decreased depolarization-induced excitability, but only RhebY35L, mTORS2215Y, and Tsc1KO expression led to depolarized resting membrane potentials. Interestingly, expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to the abnormal presence of HCN4 channels with variations in functional expression suggesting a common cellular mechanism that could confer excitability. Treatment with rapamycin, an mTOR inhibitor, reversed the expression changes in HCN4. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to different impacts on sEPSC properties. Effects of treatment with the selective HCN channel blocker zatebradine on hyperpolarization-induced inward currents in mTORS2215Y neurons confirmed the identity of ΔI as Ih.

Overall the data presented provides a convincing and compelling direct comparison of the roles that select mTOR pathway genes play on brain development and network excitability. It is critical to directly compare these gene effects in mouse models because although these genes are part of the mTOR pathway and clearly cause augmentation of mTOR activation, there are mechanistic differences in how these gees modify mTOR and how they interact with other proteins and phenotypic differences in humans harboring mutations in these same genes.

Weaknesses:<br /> There are a few limitations to an otherwise solid study. First, the authors postulate that all the findings are dependent on mTORC1-related effects but don't assess whether some of the differences could be due to effects on mTORC2 signaling. mTORC2 is an important and poorly understood alternative isoform of mTOR (due to rictor binding) that has effects on distinct cell signaling pathways and in particular actin polymerization. This doesn't diminish the effects of the current analysis of mTORC1 but could explain genotypic differences in each variable. A few prior studies have assessed the role of mTORC2 in epileptogenesis and Cortical malformations (Chen et al., 2019)

Second, the slice recordings were performed in the usual recording aCSF buffer conditions but there is no assessment of the role of amino acids or nutrients in the bath. While it is clear that valuable and viable acute slice recordings can be made in aCSF, the role of the mTOR pathway is to modulate cell growth in response to nutrient conditions. Thus, one variable that could be manipulated and assessed currently in this study is the levels of amino acids i.e., leucine and arginine added to the bath since DEPDC5 and TSC1 are responsive to ambient amino acid levels.

Third, the analysis concedes that the role of somatic mutations in cortical malformations may depend not only on genotypic effects but also on allelic load and cellular subtype affected by the mutation. Thus, it would interesting to see if electroporation either at E14 or E16, thereby affecting a distinct pool of progenitors, would mitigate or accentuate differences between mTOR pathway genes.

Treatment with rapamycin and zatebradine in each condition would have added to the strength of the findings to determine the mTOR-dependence and reversibility of HCN4 effects.

Reviewer #1 (Public Review):

Summary:

The authors study the appearance of oscillations in motifs of linear threshold systems, coupled in specific topologies. They derive analytical conditions for the appearance of oscillations, in the context of excitatory and inhibitory links. They also emphasize the higher importance of the topology, compared to the strength of the links. Finally, the results are confirmed with WC oscillators, which are also linear. The findings are to some extent confirmed with spiking neurons, though here results are less clear, and they are not even mentioned in the Discussion.

Overall, the results are sound from a theoretical perspective, but I still find it hard to believe that they are of significant relevance for biological networks, or in particular for the oscillations of BG-thalamus-cortex loop in PD. I find motifs in general to be too simplistic for multiscale and generally large networks as is the case in the brain. Moreover, the division of regions is more or less arbitrary by definition, and having such a strong dependence on an odd/even number of inhibitory links is far from reality. Another limitation is the fact that the cortex is considered a single node. Similarly, decomposing even such a coarse network in all possible (238 in this case) motifs doesn't seem of much relevance, when I assume that the emergence of pathological rhythms is more of an emergent phenomenon.

Strengths:

From the point of view of nonlinear dynamics, the results are solid, and the intuition behind the proofs of the theorems is well explained.

Weaknesses:

As stated in the summary, I find the work to be too theoretical without a real application in biological systems or the brain, where the networks are generally very large. It is not the problem in the simplicity of the model or of the topology, it is often the case that the phenomena are explained by very reduced systems, but the problem is that the applicability of the finding cannot be extended. E.g. the Kuramoto model uses all-to-all coupling, or similar with QIF neurons which also need to follow a Lorentzian distribution in order to derive a mean field. But in those cases, relaxing the strict conditions that were necessary for the derivations, still conserves the main findings of the analysis, which I don't see being the case here. The odd/even number rule is too strict, and talking about a fixed and definite number of cycles in the actual brain seems too simplistic.

Being linear is another strong assumption, and it is not clear how much of the results are preserved for spiking neurons, even though there is such an analysis, or maybe for other nonlinear types of neuronal masses.

Delays are also mentioned, and their impact on the oscillatory networks is as expected: it reduces the amplitude, but there is no link to the literature, where this is an established phenomenon during synchronization. Finally, the authors should also discuss the time-delays as a known phenomenon to cause or amplify oscillations at different frequencies in a network of coupled oscillators, e.g Petkoski & Jirsa Network Neuroscience 2022, Tewarie et al. NeuroImage 2019, Davis et al. Nat Commun 2021.

Reviewer #2 (Public Review):

Summary:

The authors present here a mathematical and computational study of the topological/graph theory requirements to obtain sustained oscillations in neural network models. A first approach mathematically demonstrates that, a given network of interconnected neural populations (understood in the sense of dynamical systems) requires an odd number of inhibitory populations to sustain oscillations. The authors extend this result via numerical simulations of (i) a simplified set of Wilson-Cowan networks, (ii) a simplified circuit of the cortico-basal ganglia network, and (iii) a more complex, spike-based neural network of basal ganglia network, which provides insight on experimental findings regarding abnormal synchrony levels in Parkinson's Disease (PD).

Strengths:

The work elegantly and effectively combines solid mathematical proof with careful numerical simulations at different levels of description, which is uncommon and provides additional layers of confidence to the study. Furthermore, the authors included detailed sections to provide intuition about the mathematical proof, which will be helpful for readers less inclined to the perusal of mathematical derivations. Its insightful and well-informed connection with a practical neuroscience problem, the presence of strong beta rhythms in PD, elevates the potential influence of the study and provides testable predictions.

Weaknesses:

In its current form, the study lacks a more careful consideration of the role of delays in the emergence of oscillations. Although they are addressed at certain points during the second part of the study, there are sections in which this could have been done more carefully, perhaps with additional simulations to solidify the authors' claims. Furthermore, there are several results reported in the main figures which are not explained in the main text. From what I can infer, these are interesting and relevant results and should be covered. Finally, the text would significantly benefit from a revision of the grammar, to improve the general readability at certain sections. I consider that all these issues are solvable and this would make the study more complete.

Reviewer #2 (Public Review):

This is a very interesting paper about the coupling of Slack and Nav1.6 and the insight this brings to the effects of quinidine to treat some epilepsy syndromes.

Slack is a sodium-activated potassium channel that is important to hyperpolarization of neurons after an action potential. Slack is encoded by KNCT1 which has mutations in some epilepsy syndromes. These types of epilepsy are treated with quinidine but this is an atypical antiseizure drug, not used for other types of epilepsy. For sufficient sodium to activate Slack, Slack needs to be close to a channel that allows robust sodium entry, like Nav channels or AMPA receptors. but more mechanistic information is not available. Of particular interest to the authors is what allows quinidine to be effective in reducing Slack.

In the manuscript, the authors show that Nav, not AMPA receptors, are responsible for Slack's sensitization to quinidine blockade, at least in cultured neurons (HeK293, primary cortical neurons). Most of the paper focuses on the evidence that Nav1.6 promotes Slack sensitivity to quinidine.

Reviewer #3 (Public Review):

Yuan et al., set out to examine the role of functional and structural interaction between Slack and NaVs on the Slack sensitivity to quinidine. Through pharmacological and genetic means they identify NaV1.6 as the privileged NaV isoform in sensitizing Slack to quinidine. Through biochemical assays, they then determine that the C-terminus of Slack physically interacts with the N- and C-termini of NaV1.6. Using the information gleaned from the in vitro experiments the authors then show that virally-mediated transduction of Slack's C-terminus lessens the extent of SlackG269S-induced seizures. These data uncover a previously unrecognized interaction between a sodium and a potassium channel, which contributes to the latter's sensitivity to quinidine.

Reviewer #2 (Public Review):

Summary:

This work by Kadeřábková et al. demonstrates the importance of a specific protein folding system to effectively folding β-lactamase proteins, which are responsible for resistance to β-lactam antibiotics, and shows that inhibition of this system sensitize multidrug-resistant pathogens to β-lactam treatment. In addition, the authors extend these observations to a two-species co-culture model where β-lactamases provided by one pathogen can protect another, sensitive pathogen from β-lactam treatment. In this model, disrupting the protein folding system also disrupted protection of the sensitive pathogen from antibiotic killing. Overall, the data presented provide a solid foundation for subsequent investigations and development of inhibitors for β-lactamases and other resistance determinants. This and similar strategies may have particular application to polymicrobial contexts, but the present state of knowledge regarding the existence and clinical effects of microbial interactions in disease, both specifically regarding S. maltophilia and P. aeruginosa as well as generally, is significantly overstated.

Strengths:

The authors use clear and reliable molecular biology strategies to show that β-lactamase proteins from P. aeruginosa and Burkholderia species, expressed in E. coli in the absence of the dsbA protein folding system, are variably less capable of resisting the effects of different β-lactam antibiotics compared to the dsbA-competent parent strain (Figure 1). The appropriate control is included in the supplemental materials to demonstrate that this effect is specifically dependent on dsbA, since complementing the mutant with an intact dsbA gene restores antibiotic resistance (Figure S1). The authors subsequently show that this lack of activity can be explained by significantly reduced protein levels and loss-of-function protein misfolding in the dsbA mutant background (Figure 2). These data support the importance of this protein folding mechanism in the activity of multiple clinically relevant β-lactamases.

Native bacterial species are used for subsequent experiments, and the authors provide important context for their antibiotic choices and concentrations by referencing the breakpoints that guide clinical practice. In Figure 4, the authors show that loss of the DsbA system in P. aeruginosa significantly sensitizes clinical isolates expressing different classes of β-lactamases to clinically relevant antibiotics. The appropriate control showing that the dsbA1 mutation does not result in sensitivity to a non-β-lactam antibiotic is included in Figure S2. The authors further show, using an in vivo model for antibiotic treatment, that treatment of a dsbA1 mutant results in moderate and near-complete survival of the infected organisms. The importance of this system in S. maltophilia is then investigated similarly (Figure 5), showing that a dsbA dsbL mutant is also sensitive to β-lactams and colistin, another antibiotic whose resistance mechanism is dependent on the DsbA protein folding system. Importantly, the authors show that a small-molecule inhibitor that disrupts the DsbA system, rather than genetic mutations, is also capable of sensitizing S. maltophilia to these antibiotics. It should be noted that while the sensitization is less pronounced, this molecule has not been optimized for S. maltophilia and would be expected to increase in efficacy once this is done. Together, the data support that interference with the DsbA system in native hosts can sensitize otherwise resistant pathogens to clinically relevant antibiotic therapy.

Finally, the authors investigate the effects of co-culturing S. maltophilia and P. aeruginosa (Figure 5E). These assays are performed in synthetic cystic fibrosis sputum medium (SCFM), which provides a nutritional context similar to that in CF but without the presence of more complex components such as mucin. The authors show that while P. aeruginosa alone is sensitive to the antibiotic, it can survive moderate concentrations in the presence of S. maltophilia and even grow in higher concentrations where S. maltophilia appears to overproduce its β-lactamases. However, this protection is lost in S. maltophilia without the DsbA protein folding system, showing that the protective effect depends on functional production of β-lactamase. The data support a protective role for DsbA-dependent β-lactamase under these co-culture conditions.

Weaknesses:

While Figure 5E demonstrates a protective effect of DsbA-dependent β-lactamase, the omission of CFU data for S. maltophilia makes it difficult to assess the applicability of the polymicrobial strategy. Since S. maltophilia is pre-cultured prior to the addition of P. aeruginosa and antibiotics, it is unclear whether the protective effect is dependent on high S. maltophilia CFU. It is also unclear what the fate of the S. maltophilia dsbA dsbL mutant is under these conditions. If DsbA-deficient S. maltophilia CFU is not impacted, then this treatment will result in the eradication of only one of the pathogens of interest. If the mutant is lost during treatment, then it is not clear whether the loss of protection is due specifically to the production of non-functional β-lactamase or simply the absence of S. maltophilia.

The alleged clinical relevance and immediate, theoretical application of this approach should be properly contextualized. At multiple junctures, the authors state or suggest that interactions between S. maltophilia and P. aeruginosa are known to occur in disease or have known clinical relevance related to treatment failure and disease states. For instance, the citations provided for S. maltophilia protection of P. aeruginosa in the CF lung environment both describe simplified laboratory experiments rather than clinical or in vivo observations. Similarly, the citations provided for both the role of S. maltophilia in treatment failure and CF disease severity do not support either claim. The role of S. maltophilia in CF is currently unsettled, with more recent work reporting conflicting results that support S. maltophilia as a marker, rather than cause, of severe disease. These citations also do not support the suggestion that S. maltophilia specifically contributes to treatment failure. While it is reasonable to pursue these ideas as a hypothesis or potential concern, there is no evidence provided that these specific interactions occur in vivo or that they have clinical relevance.

Reviewer #2 (Public Review):

In this study, Dietmar Funck and colleagues have made a significant breakthrough by identifying three isoforms of plant 2-oxoglutarate-dependent dioxygenases (2-ODD-C23) as homo/arginine-6-hydroxylases, catalyzing the degradation of 6-hydroxyhomoarginine into 2-aminoadipate-6-semialdehyde (AASA) and guanidine. This discovery marks the very first confirmation of plant or eukaryotic enzymes capable of guanidine production.

The authors selected three plant 2-ODD-C23 enzymes with the highest sequence similarity to bacterial guanidine-producing (EFE) enzymes. They proceeded to clone and express the recombinant enzymes in E coli, demonstrating capacity of all three Arabidopsis isoforms to produce guanidine. Additionally, by precise biochemical experiments, the authors established these three 2-ODD-C23 enzymes as homoarginine-6-hydroxylases (and arginine-hydroxylase for one of them). Furthermore, the authors utilized transgenic plants expressing GFP fusion proteins to show the cytoplasmic localization of all three 2-ODD-C23 enzymes. Most notably, using T-DNA mutant lines and CRISPR/Cas9-generated lines, along with combinations of them, they demonstrate the guanidine-producing capacity of each enzyme isoform in planta. These results provide robust evidence that these three 2-ODD-C23 Arabidopsis isoforms are indeed homoarginine-6-hydroxylases responsible for guanidine generation.<br /> The findings presented in this manuscript are a significant contribution for our understanding of plant biology, particularly given that this work is the first demonstration of enzymatic guanidine production in eukaryotic cells. However, there are a couple of concerns and potential ways for further investigation that the authors should (consider) incorporate.

Firstly, the observation of cytoplasmic and nuclear GFP signals in the transgenic plants may also indicate cleaved GFP from the fusion proteins. Thus, the authors should perform Western blot analysis to confirm the correct size of the 2-ODD-C23 fusion proteins in the transgenic protoplasts.

Secondly, it may be worth measuring pipecolate (and proline?) levels under biotic stress conditions (particularly those that induce transcript changes of these enzymes, Fig S8). Given the results suggesting a potential regulation of the pathway by biotic stress conditions (eg. meJA), these experiments could provide valuable insights into the physiological role of guanidine-producing enzymes in plants. This additional analysis may give a significance of these enzymes in plant defense mechanisms.

Reviewer #1 (Public Review):

Summary:<br /> The Drosophila wing disc is an epithelial tissue, the study of which has provided many insights into the genetic regulation of organ patterning and growth. One fundamental aspect of wing development is the positioning of the wing primordia, which occurs at the confluence of two developmental boundaries, the anterior-posterior and the dorsal-ventral. The dorsal-ventral boundary is determined by the domain of expression of the gene apterous, which is set early in the development of the wing disc. For this reason, the regulation of apterous expression is a fundamental aspect of wing formation.

In this manuscript, the authors used state-of-the-art genomic engineering and a bottom-up approach to analyze the contribution of a 463 base pair fragment of apterous regulatory DNA. They find compelling evidence about the inner structure of this regulatory DNA and the upstream transcription factors that likely bind to this DNA to regulate apterous early expression in the Drosophila wing disc.

Strengths:<br /> This manuscript has several strengths concerning both the experimental techniques used to address the problem of gene regulation and the relevance of the subject. To identify the mode of operation of the 463 bp enhancer, the authors use a balanced combination of different experimental approaches. First, they use bioinformatic analysis (sequence conservation and identification of transcription factors binding sites) to identify individual modules within the 463 bp enhancer. Second, they identify the functional modules through genetic analysis by generating Drosophila strains with individual deletions. Each deletion is characterized by looking at the resulting adult phenotype and also by monitoring apterous expression in the mutant wing discs. They then use a clever method to interfere in a more dynamic manner with the function of the enhancer, by directing the expression of catalytically inactive Cas9 to specific regions of this DNA. Finally, they recur to a more classical genetic approach to uncover the relevance of candidate transcription factors, some of them previously known and others suggested by the bioinformatic analysis of the 463 bp sequence. This workflow is clearly reflected in the manuscript, and constitutes a great example of how to proceed experimentally in the analysis of regulatory DNA.

Weaknesses:<br /> There are several caveats with the data that might be constructed as weaknesses, some of them are intrinsic to this detailed analysis or to the experimental difficulties of dealing with the wing disc in its earliest stages, and others are more conceptual and are offered here in case the authors may wish to consider them.

1) The primordium of the wing region of the wing imaginal disc is defined by the expression of the gen vestigial, which is regulated by inputs coming from the dorsal-ventral boundary (Notch and wg) and from the anterior-posterior boundary (Dpp). Having such a principal role in wing primordium specification and expansion, I am surprised that this manuscript does not mention this gene in the main text and only contains indirect references to it. I consider that the manuscript would have benefited a lot by including vestigial in the analysis, at least as a marker of early wing primordium. This might allow us to visualize directly the positioning of the primordium in the apterous mutants generated in this study, adding more verisimilitude to the interpretations that place this domain based on indirect evidence.

2) The authors place some emphasis on the idea that their work addresses possible coordination between setting the D/V boundary and the A/P boundary:

Abstract: "Thus, the correct establishment of ap expression pattern with respect to en must be tightly controlled", "...challenging the mechanism by which apE miss-regulation leads to AP defects." "Detailed mutational analyses using CRISPR/Cas revealed a role of apE in positioning the DV boundary with respect to the AP boundary"<br /> Introduction: "However, little is known about how the expression pattern of ap is set up with respect that of en. In other words, how is the DV boundary positioned with respect to the AP boundary?"<br /> "How such interaction between ap and the AP specification program arises is unknown."<br /> Results: "Some of these phenotypes are reminiscent of those reported for apBlot (Whittle, 1979) and point towards a yet undescribed crosstalk between ap early expression and the AP specification program."

At the same time, they express the notion, with which this reviewer agrees, that all defects observed in A/P patterning arising as a result of apterous miss-regulation are due to the fact that in their mutants, apterous expression is lost mainly in the posterior dorsal compartment, bringing novel confrontations between the A/P and the D/V boundaries.

To me, the key point is why the expression of apterous in different mutants of the OR463 enhancer affects only the posterior compartment. This should be discussed because it is far from obvious that apterous expression has different regulatory requirements in the anterior and posterior compartments.

3) The description of gene expression in the wing disc of novel apterous mutants is only carried out in late third instar discs (Figs. 2, 3, 5, and 7). This is understandable given the technical difficulties of dealing with early discs, as those shown in the analysis of candidate apterous regulatory transcription factors (Fig. 4F, Fig. 6 C-D). However, because the effects of the mutants on apterous expression are expected to occur much earlier than the time of expression analysis, this fact should be discussed.

Reviewer #2 (Public Review):

In their manuscript, "Transcriptional control of compartmental boundary positioning during Drosophila wing development," Aguilar and colleagues do an exceptional job of exploring how tissue axes are established across Drosophila development. The authors perform a series of functional perturbations using mutational analyses at the native locus of apterous (ap), and perform tissue-specific enhancer disruption via dCas9 expression. This innovative approach allowed them to explore the spatio-temporal requirements of an apterous enhancer. Combining these techniques allowed the authors to explore the molecular basis of apterous expression, connecting the genotypes to the phenotypical effects of enhancer perturbations. To me, this paper was a beautiful example of what can be done using modern drosophila genetics to understand classic questions in developmental biology and transcriptional regulation.

In sum, this was a rigorous paper bridging scales from the molecular to phenotypes, with new insight into how enhancers control compartmental boundary positioning during Drosophila wing development.

Reviewer #3 (Public Review):

In this manuscript, authors use the Drosophila wing as a model system and combine state-of-the-art genetic engineering to identify and validate the molecular players mediating the activity of one of the cis-regulatory enhancers of the apterous gene involved in the regulation of its expression domain in the dorsal compartment of the wing primordium during larval development.

(1) The authors raise two very important questions in the Introduction: (1) who is locating the relative position of the AP and DV boundaries in the developing wing, and (2) who is responsible for the maintenance of the apterous expression domain late in larval development. None of these two questions have been responded to and, indeed, the summary of the work (as stated in the conclusions of the last paragraph of the Introduction) does not resolve any of these questions.

(2) The authors have identified two different regions whose deletions give very interesting phenotypes in the adult wing (AP identify change & outgrowths, and loss of wing), and have bioinformatically identified and functionally verified 4 TFs that mediate the activity of these regions by their capacity to phenocopy the wing phenotype. While identification of the 2 TFs acting on the m1 is incremental with respect to previous work on the identification of the enhancer responsible for the early expression of Ap, identification of Antp and Grn does not explain the loss of function phenotype of the m3 enhancer. Does any of these results shed any light on the first two Qs? Do these results explain the compartment boundary position in the wing as stated in the title? Expression of lacZ reporter assays is fundamental to demonstrate their model of Figure 8. The reduction of the PD compartment is difficult to understand by the sole reduction in ap expression in this region (which has not been demonstrated).

(3) The authors state in one of the sections "Spatio-temporal analysis of apE via dCas9 ". No temporal manipulation of gene activity is shown. The authors should combine GAL4/UAs with the Gal80ts to demonstrate the temporal requirements of Antp/Grn and Pnt/Hth as depicted in their model of Figure 8.

(4) The authors have not managed to explain the AP phenotype. Thus, this work opens many unresolved questions and does not resolve the title, which is a big overstatement. Thus, strengths (technically excellent), weakness (there is not much to learn about wing development and apterous regulation from these results besides the incremental identification of 4 additional TFs mediating the regulation of ap expression by their ability to phenocopy regulatory mutations of the apterous gene).

Joint Public Review:

In this work Wu, J., et al., highlight the importance of a previously overlooked region on kinases: the αC-β4 loop. Using PKA as a model system, the authors extensively describe the conserved regulatory elements within a kinase and how the αC-β4 loop region integrates with these important regulatory elements. Previous biochemical work on a mutation within the αC-β4 loop region, F100A showed that this region is important for the synergistic high affinity binding of ATP and the pseudo substrate inhibitor PKI. In the current manuscript, the authors assess the importance of the αC-β4 loop region using computational methods such as Local Spatial Pattern Alignment (LSP) and MD simulations. LSP analysis of the F100A mutant showed decreased values for degree centrality and betweenness centrality for several key regulatory elements within the kinase which suggests a loss in stability/connectivity in the mutant protein as compared to the WT. Additionally, based on MD simulation data, the side chain of K105, another residue within the αC-β4 loop region had altered dynamics in the F100A mutant as compared to the WT protein. While these changes in the αC-β4 loop region seem to be consistent with the previous biochemical data, the results are preliminary and the manuscript can be strengthened (as the authors themselves acknowledge) with additional experiments. Specific comments/concerns are listed below.

1. MD simulations were carried out using a binary complex of the catalytic subunit of PKA and ATP/Mg and not the ternary complex of PKA, ATP/Mg and PKI. MD simulations carried out using the ternary complex instead of the binary complex would be more informative, especially on the role of the αC-β3 loop region in the synergistic binding of ATP/Mg and PKI.

2. The LSP analysis shows a decrease in degree centrality for the αC-β4 loop region in the F100A mutant compared to the WT protein which suggests a gain in stability in this region for the F100A mutant (Fig. 8A). These results seem to be contradictory to the MD simulation data which shows the side chain dynamics of K105 destabilizes the αC-β4 loop region in the F100A mutant (Fig. 10B). It would be helpful if the authors could clarify this apparent discrepancy.

3. The foundation for the experiments carried out in this paper are based on previous NMR and computational data for the F100A mutant. However, the specific results and conclusions from these previous experiments are not clearly described.

Reviewer #1 (Public Review):

Summary:<br /> This work seeks to isolate the specific effects of phosphoinositide 3-kinase (PI3K) on the trafficking of the ion channel TRPV1, distinct from other receptor tyrosine kinase-activated effectors. It builds on earlier studies by the same group (Stein et al. 2006; Stratiievska et al. 2018), which described the regulatory relationship between PI3K, nerve growth factor (NGF), and TRPV1 trafficking. A central theme of this study is the development of methods that precisely measure the influence of PI3K on TRPV1 trafficking and vice versa. The authors employ a range of innovative methodologies to explore the dynamics between TRPV1 and PI3K trafficking.

Strengths:<br /> A major strength of this study is the application of innovative methods to understand the interaction between PI3K and TRPV1 trafficking. The key techniques presented include:

1) The optogenetic trafficking system based on phytochrome B, introduced in this research. Its interaction mechanism, dependent on reversible light activation, is comprehensively explained in Figures 1 and 2, with the system's efficacy demonstrated in Figure 3.

2) An extracellular labeling method using click chemistry, which although not exclusive to this study, introduces specific reagents engineered for membrane impermeability.

The central biological insight presented here is the sufficiency of PI3K activation to guide TRPV1 trafficking to the plasma membrane. An additional notable discovery is the potential regulation of insulin receptors via this mechanism.

The paper's strengths are anchored in its innovative methodologies and the valuable collaboration between groups specializing in distinct areas of research.

Weaknesses:<br /> The paper might benefit from a more streamlined structure and a clearer emphasis on its findings. A possible way to enhance its impact might be to focus more on its methodological aspects. The methodological facets stand out as both innovative and impactful. These experiments are well-executed and align with biological expectations. It's evident how these techniques could be tailored for many protein trafficking studies, a sentiment echoed in the manuscript (lines 287-288). When seen through a purely biological lens, some findings, like those concerning the PI3K-TRPV1 interaction, are very similar to previous work (Stratiievska et al. 2018). A biological focus demands further characterization of this interaction through mutagenesis. Also, the incorporation of insights on the insulin receptor feels somewhat tangential. A cohesive approach could be to reshape the manuscript with a primary focus on methodology, using TRPV1 and InsR as illustrative examples.

Reviewer #2 (Public Review):

Summary:<br /> The authors hypothesized that the interaction between TRPV1 and PI3K directly influenced PI3K activity along with increasing TRPV1 trafficking to the membrane. Previous results showed that PI3K could interact with one of the ankyrin repeat domains, however it was unclear whether the direct interaction influenced PI3K activity.

Strengths:<br /> A major strength of the paper is the innovative combination of techniques. The first technique used the optogenetic PhyB/PIF system. They anchored PhyB to the membrane and fused PIF with the interSH2 domain from PI3K. This allowed them to use 650nm light to induce an interaction between the PhyB and PIF resulting in a recruitment of the endogenous PI3K to the membrane through the iSH2 domain without actual activation of an RTK. This allowed them to dissect out one function, just PI3K recruitment/activation from the vast number of RTK downstream cascades.

The second technique was the development of a new non-canonical amino acid that is cell-impermeant. The authors synthesized the sTSO-sulfa-Cy5 compound that will react with the Tet3 ncAA through click chemistry. They showed that the sulfa-Cy5 did not cross the membrane and would be used to track protein production over time, though the reaction rates were slow as noted by the authors. The comparison of the sulfa-Cy5 data with the standard GFP with TIRF showed a clear difference indicating the useful information that is gained with the ncAA.

Weaknesses:<br /> To monitor the phosphatidylinositol-3,4,5-trisphosphates, the pleckstrin homology (PH) domain from Akt was used. This PH domain is not specific for just PI(3,4,5)P3 as stated by the authors. The Akt PH domain also binds PI(3,4)P2. The observed PI3K localization increase will also increase PI(3,4)P2 concentrations so the observed responses may not be solely because of PI(3,4,5)P3.

The data in Figure 4 supplement was confusing to interpret since it is unclear whether a membrane protein with the Tet3 is being expressed at the same time as the ncAA for labeling or if the observed labeling is endogenous. If the observed labeling in Figure 4 supplement D is endogenous, then significant concerns come up regarding the background labeling of the sTCO-sulfo-Cy5 used in the rest of the experiments.

Even with the weaknesses, I believe the authors did achieve their goal of investigating the reciprocity between TRPV1 and PI3K. Their results support their conclusions and will help understand how TRPV1 is regulated by signals other than the traditional channel activators. The tools developed in the article will be of use to the broader cell biology and biophysics community, not just the channel community. The opto control of the PhyB/PIF system makes it more convenient than other systems since it does not take the typical wavelengths needed for fluorescence. The cell-impermeant ncAA will also be a great tool for those studying membrane proteins, protein trafficking and protein dynamics.

Reviewer #3 (Public Review):

Summary: In this manuscript, Koh, Stratiievska, and their colleagues investigate the mechanism by which TRPV1 channels are delivered to the plasma membrane following the activation of receptor tyrosine kinases, specifically focusing on the NGF receptor. They demonstrate that the activation of the NGF receptor's PI3K pathway alone is sufficient to increase the levels of TRPV1 at the plasma membrane.

Strengths: The authors employ cutting-edge optogenetic, imaging, and chemical-biology techniques to achieve their research goals. They ingeniously use optogenetics to selectively activate the PI3K pathway without affecting other NGF pathways. Additionally, they develop a novel, membrane-impermeable fluorescent probe for labeling cell-surface proteins through click-chemistry.

Weaknesses: Previous research, including work by the authors themselves, has already established that PI3K activation is required for NGF-induced TRPV1 trafficking to the plasma membrane. Moreover, the paper suffers from issues such as subpar writing quality, a lack of statistical analysis, and insufficient control experiments, which dampen the reviewer's enthusiasm.

Reviewer #1 (Public Review):

• A summary of what the authors were trying to achieve.

The authors cultured pre- and Post-vaccine PBMCs with overlapping peptides encoding S protein in the presence of IL-2, IL-7, and IL-15 for 10 days, and extensively analyzed the T cells expanded during the culture; by including scRNAseq, scTCRseq, and examination of reporter cell lines expressing the dominant TCRs. They were able to identify 78 S epitopes with HLA restrictions (by itself represents a major achievement) together with their subset, based on their transcriptional profiling. By comparing T cell clonotypes between pre- and post-vaccination samples, they showed that a majority of pre-existing S-reactive CD4+ T cell clones did not expand by vaccinations. Thus, the authors concluded that highly-responding S-reactive T cells were established by vaccination from rare clonotypes.

• An account of the major strengths and weaknesses of the methods and results.

Strengths<br /> • Selection of 4 "Ab sustainers" and 4 "Ab decliners" from 43 subjects who received two shots of mRNA vaccinations.<br /> • Identification of S epitopes of T cells together with their transcriptional profiling. This allowed the authors to compare the dominant subsets between sustainers and decliners.

Weaknesses<br /> • Fig. 3 provides the epitopes, and the type of T cells, yet the composition of subsets per subject was not provided. It is possible that only one subject out of 4 sustainers expressed many Tfh clonotypes and explained the majority of Tfh clonotypes in the sustainer group. To exclude this possibility, the data on the composition of the T cell subset per subject (all 8 subjects) should be provided.<br /> • S-specific T cells were obtained after a 10-day culture with peptides in the presence of multiple cytokines. This strategy tends to increase a background unrelated to S protein. Another shortcoming of this strategy is the selection of only T cells amenable to cell proliferation. This strategy will miss anergic or less-responsive T cells and thus create a bias in the assessment of S-reactive T cell subsets. This limitation should be described in the Discussion.<br /> • Fig. 5 shows the epitopes and the type of T cells present at baseline. Do they react to HCoV-derived peptides? I guess not, as it is not clearly described. If the authors have the data, it should be provided.<br /> • As the authors discussed (L172), pre-existing S-reactive T cells were of low affinity. The raw flow data, as shown in Fig. S3, for pre-existing T cells may help discuss this aspect.

Reviewer #2 (Public Review):

Summary: A short-term comparison of durability of S antibody levels after 2-dose vaccination, showing that better or more poorly sustained responses correlate with the presence of Tfh cells.

Strengths:<br /> Novelty of approach in expanding, sequencing and expressing TCRs for functional studies from the implicated populations.

Weaknesses:<br /> Somewhat outdated question, short timeline, small numbers, over-interpretation of sequence homology data.

Reviewer #1 (Public Review):

Drawing on insights from preceding studies, the researchers pinpointed mutations within the spag7 gene that correlate with metabolic aberrations in mice. The precise function of spag7 has not been fully described yet, thereby the primary objective of this investigation is to unravel its pivotal role in the development of obesity and metabolic disease in mice. First, they generated a mice model lacking spag7 and observed that KO mice exhibited diminished birth size, which subsequently progressed to manifest obesity and impaired glucose tolerance upon reaching adulthood. This behaviour was primarily attributed to a reduction in energy expenditure. In fact, KO animals demonstrated compromised exercise endurance and muscle functionality, stemming from a deterioration in mitochondrial activity. Intriguingly, none of these effects was observed when using a tamoxifen-induced KO mouse model, implying that Spag7's influence is predominantly confined to the embryonic developmental phase. Explorations within placental tissue unveiled that mice afflicted by Spag7 deficiency experienced placental insufficiency, likely due to aberrant development of the placental junctional zone, a phenomenon that could impede optimal nutrient conveyance to the developing fetus. Overall, the authors assert that Spag7 emerges as a crucial determinant orchestrating accurate embryogenesis and subsequent energy balance in the later stages of life.

The study boasts several noteworthy strengths. Notably, it employs a combination of animal models and a thorough analysis of metabolic and exercise parameters, underscoring a meticulous approach. Furthermore, the investigation encompasses a comprehensive evaluation of fetal loss across distinct pregnancy stages, alongside a transcriptomic analysis of skeletal muscle, thereby imparting substantial value. However, a pivotal weakness of the study centres on its translational applicability. While the authors claim that "SPAG7 is well-conserved with 97% of the amino acid sequence being identical in humans and mice", the precise role of spag7 in the human context remains enigmatic. This limitation hampers a direct extrapolation of findings to human scenarios. Additionally, the study's elucidation of the molecular underpinnings behind the spag7-mediated anomalous development of the placental junction zone remains incomplete. Finally, the hypothesis positing a reduction in nutrient availability to the fetus, though intriguing, requires further substantiation, leaving an aspect of the mechanism unexplored.

Hence, in order to fortify the solidity of their conclusions, these concerns necessitate meticulous attention and resolution in the forthcoming version of the manuscript. Upon the comprehensive addressing of these aspects, the study is poised to exert a substantial influence on the field, its significance reverberating significantly. The methodologies and data presented undoubtedly hold the potential to facilitate the community's deeper understanding of the ramifications stemming from disruptions during pregnancy, shedding light on their enduring impact on the metabolic well-being of subsequent generations.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Flaherty III S.E. et al identified SPAG7 gene in their forward mutagenetic screening and created the germline knockout and inducible knockout mice. The authors reported that the SPAG7 germline knockout mice had lower birth weight likely due to intrauterine growth restriction and placental insufficiency. The SPAG7 KO mice later developed obesity phenotype as a result of reduced energy expenditure. However, the inducible SPAG7 knockout mice had normal body weight and composition.

Strengths:<br /> In this reviewer's opinion, this study has high significance in the field of metabolic research for the following reasons.<br /> (1) The authors' findings are significant in the field of obesity research, especially from the perspective of maternal-fetal medicine. The authors created and analyzed the SPAG7 KO mice and found that the KO mice had a "thrifty phenotype" and developed obesity.<br /> (2) SPAG7 gene function hasn't been thoroughly studied. The reported phenotype will fill the gap of knowledge.<br /> Overall, the authors have presented their results in a clear and logically organized structure, clearly stated the key question to be addressed, used the appropriate methodology, produced significant and innovative main findings.

Weaknesses:<br /> The manuscript can be further strengthened with more clarification on the following points.<br /> 1. The germline whole-body KO mice were female mice (Line293), however the inducible knockout mice were male mice (Line549). Sexual dimorphism is often observed in metabolic studies, therefore the metabolic phenotype of both female and male mice needs to be reported for the germline and inducible knockouts in order to make the justified conclusion.<br /> 2. SPAG7 has an NLS. Does this protein function in gene expression? Whether the overall metabolic phenotype is the direct cause of SPAG7 ablation is unclear. For example, the Hsd17b10 gene was downregulated in all tissues in the KO mice. Could this have been coincidentally selected for and thus be the cause of the developmental issues and adulthood obesity? Do the iSpag7 mice demonstrate reduced expression of Hsd17b10?<br /> 3. Figure 2c should display the energy expenditure normalized to body weight (or lean body mass).<br /> 4. Please provide more information for the figure legend, including the statistical test that was conducted for each data set, animal numbers for each genotype and sexes.<br /> 5. The authors should report how long after treatment the data was collected for figures 4F-M.<br /> 6. The authors should justify ending the data collection after 8 weeks for the iSPAG7 mice in Figures 4C-E. In the WT vs germline KO mice, there was no clear difference in body weight or lean mass at 15 weeks of age.

Reviewer #1 (Public Review):

The authors start from the premise that neural circuits exhibit "representational drift" -- i.e., slow and spontaneous changes in neural tuning despite constant network performance. While the extent to which biological systems exhibit drift is an active area of study and debate (as the authors acknowledge), there is enough interest in this topic to justify the development of theoretical models of drift.

The contribution of this paper is to claim that drift can reflect a mixture of "directed random motion" as well as "steady state null drift." Thus far, most work within the computational neuroscience literature has focused on the latter. That is, drift is often viewed to be a harmless byproduct of continual learning under noise. In this view, drift does not affect the performance of the circuit nor does it change the nature of the network's solution or representation of the environment. The authors aim to challenge the latter viewpoint by showing that the statistics of neural representations can change (e.g. increase in sparsity) during early stages of drift. Further, they interpret this directed form of drift as "implicit regularization" on the network.

The evidence presented in favor of these claims is concise. Nevertheless, on balance, I find their evidence persuasive on a theoretical level -- i.e., I am convinced that implicit regularization of noisy learning rules is a feature of most artificial network models. This paper does not seem to make strong claims about real biological systems. The authors do cite circumstantial experimental evidence in line with the expectations of their model (Khatib et al. 2022), but those experimental data are not carefully and quantitatively related to the authors' model.

To establish the possibility of implicit regularization in artificial networks, the authors cite convincing work from the machine-learning community (Blanc et al. 2020, Li et al., 2021). Here the authors make an important contribution by translating these findings into more biologically plausible models and showing that their core assumptions remain plausible. The authors also develop helpful intuition in Figure 4 by showing a minimal model that captures the essence of their result.

In Figure 2, the authors show a convincing example of the gradual sparsification of tuning curves during the early stages of drift in a model of 1D navigation. However, the evidence presented in Figure 3 could be improved. In particular, 3A shows a histogram displaying the fraction of active units over 1117 simulations. Although there is a spike near zero, a sizeable portion of simulations have greater than 60% active units at the end of the training, and critically the authors do not characterize the time course of the active fraction for every network, so it is difficult to evaluate their claim that "all [networks] demonstrated... [a] phase of directed random motion with the low-loss space." It would be useful to revise the manuscript to unpack these results more carefully. For example, a histogram of log(tau) computed in panel B on a subset of simulations may be more informative than the current histogram in panel A.

Reviewer #2 (Public Review):

Summary:

In the manuscript "Representational drift as a result of implicit regularization" the authors study the phenomenon of representational drift (RD) in the context of an artificial network that is trained in a predictive coding framework. When trained on a task for spatial navigation on a linear track, they found that a stochastic gradient descent algorithm led to a fast initial convergence to spatially tuned units, but then to a second very slow, yet directed drift which sparsified the representation while increasing the spatial information. They finally show that this separation of timescales is a robust phenomenon and occurs for a number of distinct learning rules.

Strengths:

This is a very clearly written and insightful paper, and I think people in the community will benefit from understanding how RD can emerge in such artificial networks. The mechanism underlying RD in these models is clearly laid out and the explanation given is convincing.

Weaknesses:

It is unclear how this mechanism may account for the learning of multiple environments. The process of RD through this mechanism also appears highly non-stationary, in contrast to what is seen in familiar environments in the hippocampus, for example.

Reviewer #3 (Public Review):

Summary:

Single-unit neural activity tuned to environmental or behavioral variables gradually changes over time. This phenomenon, called representational drift, occurs even when all external variables remain constant, and challenges the idea that stable neural activity supports the performance of well-learned behaviors. While a number of studies have described representational drift across multiple brain regions, our understanding of the underlying mechanism driving drift is limited. Ratzon et al. propose that implicit regularization - which occurs when machine learning networks continue to reconfigure after reaching an optimal solution - could provide insights into why and how drift occurs in neurons. To test this theory, Ratzon et al. trained a Feedforward Network to perform the oft-utilized linear track behavioral paradigm and compare the changes in hidden layer units to those observed in hippocampal place cells recorded in awake, behaving animals.

Ratzon et al. clearly demonstrate that hidden layer units in their model undergo consistent changes even after the task is well-learned, mirroring representational drift observed in real hippocampal neurons. They show that the drift occurs across three separate measures: the active proportion of units (referred to as sparsification), spatial information of units, and correlation of spatial activity. They continue to address the conditions and parameters under which drift occurs in their model to assess the generalizability of their findings. However, the generalizability results are presented primarily in written form: additional figures are warranted to aid in reproducibility. Last, they investigate the mechanism through which sparsification occurs, showing that the flatness of the manifold near the solution can influence how the network reconfigures. The authors suggest that their findings indicate a three-stage learning process: 1) fast initial learning followed by 2) directed motion along a manifold which transitions to 3) undirected motion along a manifold.

Overall, the authors' results support the main conclusion that implicit regularization in machine learning networks mirrors representational drift observed in hippocampal place cells. However, additional figures/analyses are needed to clearly demonstrate how different parameters used in their model qualitatively and quantitatively influence drift. Finally, the authors need to clearly identify how their data supports the three-stage learning model they suggest. Their findings promise to open new fields of inquiry into the connection between machine learning and representational drift and generate testable predictions for neural data.

Strengths:

1) Ratzon et al. make an insightful connection between well-known phenomena in two separate fields: implicit regularization in machine learning and representational drift in the brain. They demonstrate that changes in a Feedforward Network mirror those observed in the brain, which opens a number of interesting questions for future investigation.

2) The authors do an admirable job of writing to a large audience and make efforts to provide examples to make machine learning ideas accessible to a neuroscience audience and vice versa. This is no small feat and aids in broadening the impact of their work.

3) This paper promises to generate testable hypotheses to examine in real neural data, e.g., that drift rate should plateau over long timescales (now testable with the ability to track single-unit neural activity across long time scales with calcium imaging and flexible silicon probes). Additionally, it provides another set of tools for the neuroscience community at large to use when analyzing the increasingly high-dimensional data sets collected today.

Weaknesses:

1) Neural representational drift and directed/undirected random walks along a manifold in ML are well described. However, outside of the first section of the main text, the analysis focuses primarily on the connection between manifold exploration and sparsification without addressing the other two drift metrics: spatial information and place field correlations. It is therefore unclear if the results from Figures 3 and 4 are specific to sparseness or extend to the other two metrics. For example, are these other metrics of drift also insensitive to most of the parameters as shown in Figure 3 and the related text? These concerns could be addressed with panels analogous to Figures 3a-c and 4b for the other metrics and will increase the reproducibility of this work.

2) Many caveats/exceptions to the generality of findings are mentioned only in the main text without any supporting figures, e.g., "For label noise, the dynamics were qualitatively different, the fraction of active units did not reduce, but the activity of the units did sparsify" (lines 116-117). Supporting figures are warranted to illustrate which findings are "qualitatively different" from the main model, which are not different from the main model, and which of the many parameters mentioned are important for reproducing the findings.

3) Key details of the model used by the authors are not listed in the methods. While they are mentioned in reference 30 (Recanatesi et al., 2021), they need to be explicitly defined in the methods section to ensure future reproducibility.

4) How different states of drift correspond to the three learning stages outlined by the authors is unclear. Specifically, it is not clear where the second stage ends, and the third stage begins, either in real neural data or in the figures. This is compounded by the fact that the third stage - of undirected, random manifold exploration - is only discussed in relation to the introductory Figure 1 and is never connected to the neural network data or actual brain data presented by the authors. Are both stages meant to represent drift? Or is only the second stage meant to mirror drift, while undirected random motion along a manifold is a prediction that could be tested in real neural data? Identifying where each stage occurs in Figures 2C and E, for example, would clearly illustrate which attributes of drift in hidden layer neurons and real hippocampal neurons correspond to each stage.

Reviewer #1 (Public Review):

C. elegans is a pre-eminent model for developmental genetics, and its invariant lineage makes it possible in theory to define molecular features such as gene expression comprehensively and at single cell resolution across the organism.

Previously published single-cell RNA-seq studies have mapped gene expression across the lineage through the 16-cell stage (Tintori et al 2017, Hashimshony et al 2016), and at later stages (Packer et al 2019, with good coverage starting at the 100-cell stage and some coverage at the ~50-cell stage). This left the critical period around gastrulation (~28-cell and ~50-cell) without comprehensive transcriptome data. This study covers this gap with a heroic effort involving the manual isolation and analysis of over 800 cells from embryos of known stage, combined with painstaking curation using known markers from small scale studies and larger imaging-based expression atlases. Importantly, the dataset overlaps at early and late stages with data prior studies.

The data quality and overlap with Tintori and Packer datasets both appear high, but to make this inference required additional analysis from Supplemental Table 6 by this reviewer as it is not explored or described in the manuscript. Analyses demonstrating continuity with these datasets would greatly increase the value of the resource.

The authors show that specific lineages and stages preferentially express TFs with different classes of DNA binding domains. This extends previous work implicating homeodomains as preferentially involved in nervous system patterning and as enriched in neural and muscle progenitors in mid-stage embryos.

They also show that C. elegans homologs of Drosophila early embryonic regulators (which function based on spatial position in that system) tend to also be patterned in early C. elegans embryos, but with lineage-specific patterns. This conserved use of regulators would be fairly remarkable given the dramatically different developmental modes in these two species, although this observation is not backed up by quantitative analyses.

Finally, there is an argument that combinations of TFs expressed in lineage-specific patterns give rise to "stripe" patterns. This section is also not based on statistical analyses but suggests the possibility that lineage and positional regulation may be more convoluted than was previously thought.

Reviewer #2 (Public Review):

The C. elegans embryo has been model system of study for more than 30 years because of the ease of doing forward and reverse genetics, coupled with its nearly invariant lineage which allows a description of development at high resolution. 4D time lapse imaging coupled with spatially resolved gene expression has enabled identification of transcriptional signatures of cells in space and time, and in the past decade this has been advanced with single-cell transcriptomics methods, using individually isolated embryonic cells (which can retain their identity) or by deconvolving complex mixtures of early cells. Recent work using these methods has resolved spatiotemporal expression patterns for many genes, defining cells up to gastrulation stage, but then changing to more tissue-specific patterns during morphogenesis. A key paradigm of specification in C. elegans and other systems is that early maternal factors initiate or restrict patterns of transcription factor expression from the zygotic genome. Combinatorial expression patterns and some symmetries broken by autonomous or extrinsic cell inductions ultimately program lineages towards their fates. To date, only simple networks have been elucidated, as the increasing complexity of these networks and the high level of redundancy has made functional dissection of such pathways difficult. Hence, almost all of the work in recent years has been descriptive.

In this work the authors fill a knowledge gap from the early embryo (~16 cells) to the ~100-cell stage and describe new patterns of gene expression. They reconcile their findings with that of others who have defined expression patterns using other methods, such as scRNA-Seq from complex mixtures of cells, and from transcription factor expression analyses. The resulting description of embryonic develop is the most precise to date, and offers a potentially useful resource for other researchers.

The authors attempt to use their results to find patterns of gene expression that could hint at phylogenetic conservation of specification mechanisms. They find some supporting evidence that expression of homeobox genes occurs in anterior-posterior stripes, which recalls the elaborate A/P patterning system elucidated in the Drosophila embryo, which belongs to the sister phylum Arthropoda in the Ecdysozoan clade of molting animals. It felt as if the authors chose the Hox genes they need to support this conclusion.

Some caveats exist to the work. The expression patterns seem to be well-validated, and following prior work from the Yanai group are likely to be strongly correlated with expression in living embryos. When cells are separated, they could lose some expression patterns that require cell-cell interactions, so it is expected that there might be a small minority of expression patterns that are more complex than what has been documented here.

A major caveat is the idea of the stripes of Hox expression. I just did not find these arguments to be compelling. Seeing these 'stripes' requires organizing the data in a way that maximizes their appearance, for one. Since there is not a lot of movement of cells away from their birth in the early embryo, the AB descendants are anterior to those of MS, anterior to those of E, anterior to those of C, D, and P4. Lineage-specific expression will just naturally fall into 'stripes'. Second, the conservation of Hox expression patterns typically comes with collinearity of the genes along the length of a chromosome (i.e. the so-called Hox clusters) with expression along the body axis, as well as posterior-to-anterior fate transformations when Hox specification is disrupted.

A minor note is the detection of an enrichment of GATA factors in the early E lineage. This has now been found to be a derived condition even within the genus (see Broitman-Maduro et al. Development 149 (21): dev200984, as other species like C. angaria show only a simpler network of elt-3 -> elt-2. This suggests that many of the other patterns of gene expression, particularly in the early embryo, could be highly derived as well; some caution is warranted in generalizing the results as being conserved with arthropods as some of this could be convergent.

Given what the authors are proposing about Hox stripes, some omissions of prior work were surprising (or maybe I missed them). For example, a comprehensive study of Hox genes in C. elegans by Hench et al. (2015) (PLoS One 10(5): e0126947) evaluated all the homeobox genes and examined their genomic locations and expression patterns in the embryo at high spatiotemporal resolution. Work from the Hobert lab (Nature 2020, 584(7822):595-601) showed how homeobox codes specify classes of C. elegans neurons, and the Murray lab (PLoS Genet. 18(5):e1010187) examined Hox control of posterior lineage specification at high resolution, with functional assays.

The Discussion section of the paper is brief, consistent with the descriptive nature of the work overall, but it would have been nice to see the findings related to other published studies as indicated above.

Reviewer #3 (Public Review):

The authors claim that this dataset covers a timepoint of embryogenesis that is not well covered in the other published single cell datasets (Tintori et al 2016 and Packer et al 2019). The Tintori data indeed do not cover the 28-102-cell stages sufficiently, but it is unclear how the data presented here compare to the Packer et al data. It is true that the Packer et al data have fewer cells at earlier timepoints than at later ones, but given that they sequenced tens of thousands of cells, they report that they still have ~10,000 cells <210 min of embryogenesis. It seems that if the authors want to make any claims about how their data enables exploration of a stage that was previously not accessible, this would require a better comparison to the available data.

The authors provide thorough support for how they assigned cell identities in their data. It is surprising though that at the 102-cell stage they only identify 37 unique cell identities. They suggest that this is because there are many equivalence groups at this stage. However, I would strongly encourage the authors to perform a similar analysis or otherwise compare their obtained identities with the data from Packer et al. 2019. It seems possible that given the low number of cells in this dataset, the authors are missing certain identities and it would be important to know this.

The main analysis the authors perform is to look at expression patterns of various classes of TFs and ask whether they are enriched in particular lineages or at specific timepoints. This analysis is interesting but would be more informative if the authors provided in Figure 3d the numbers of each class of TFs. The authors then focus on the homeodomain class of TFs as they display interesting lineage-specific expression patterns, which when mapped on the embryo form stripes. The stripe pattern however is not that obvious, at least not as shown in Figure 4b. Perhaps separate embryo schematics showing the different TF expression patterns would show this more clearly. Moreover, given the relatively small number of cell identities found in this dataset (particularly at the 102-cell stage), a similar analysis using the Packer data would provide further support to these patterns. The localization of cells with shared expression patterns does show a stripe pattern at the 28-cell stage, but also not so clearly beyond this timepoint.

I am also unsure about the validity/value of the comparison of the stripes to Drosophila and the centrality of homeodomain TFs to anterior-posterior positional identity. First, it would be important to map other TFs, very likely there are several other TFs that correlate with positional identity. Also, even if the expression of the homeodomain TFs in C. elegans form stripes, there are still several cells within that stripe that do not express these TFs, it is thus unclear whether these TFs encode positional information or the identity of cells with different positions in the embryo.

Reviewer #4 (Public Review):

This is an admirable piece of work. The authors build on a previous dataset they assembled, but expand it to include all stages of early development in the nematode Caenorhabditis elegans. Cell collection was done manually, which is very impressive, and is clearly far better than pooled unidentified cells. I will not comment on the specific sequencing and analysis, since this is not my expertise, but will comment on the general conclusions and comparative framework in which the authors place their results.

While the Introduction and Discussion sections are actually fairly short, much of the presentation of the results is based on a certain comparative framework, which is explicitly a comparison between C. elegans and Drosophila melanogaster. This is an important perspective, but I feel the authors' interpretation is in some places exaggerated and in other places almost trivial.

Drosophila and C. elegans are two of the main models for developmental biology. However, it has been clear for over two decades that both species are highly derived and specialized and therefore, treating them as representative for their taxa is problematic. Much of the authors' discussion hinges on the question of comparing syncytial and lineage-dependent development. The syncytial early development of Drosophila is very specific and is clearly a recent innovation within a restricted group of flies. The canonical Drosophila segmentation cascade is mostly a novelty and most elements within the cascade are recent. Specifically, the expression of gap genes in regional stripes is not found very broadly. Conversely, the polarizing role of Caudal is very ancient and is probably found in all Bilateria. When making comparisons with a distantly related species, it is important to keep this in mind. Not as much is known about development of other nematodes, but the little that is known indicates that C. elegans is also unusual, and specifically the eutelic development (conserved cell lineages in development) is not found in all nematodes.

The authors suggest that regional expression of transcription factors in stripes is a conserved characteristic of development. This is true for Hox genes and has been known for decades. The regional expression they show for other genes is not convincing as "stripes". It is no surprise that developmental transcription factors are regionalized, but linking this to the stripes of Drosophila gap genes and even more so to Drosophila pair-rule and segment-polarity genes is a bit far-fetched. Yes, many genes are expressed in restricted domains along the A-P axis, but that is all that can be said based on the data. Calling them "Drosophila-like" is unfounded.

Reviewer #2 (Public Review):

There are reports that patients experience hematologic improvement after treatment with iron chelators but the mechanism of this improvement and the specific patient category that benefits are not known. This article uses a mouse model of MDS to explore the mechanism by which chelator therapy may lead to improved erythropoiesis. Although many changes were seen in the MDS mouse model treated with deferiprone, a causal mechanism was not demonstrated.

The authors provide solid evidence for the following:<br /> 1. The NUP98-HOXD13 mouse model of MDS recapitulates spontaneous (non-transfusion related) iron overload seen in some subtypes of MDS<br /> 2. In this model, iron chelation with deferiprone (DFP) improves not only iron overload but also improves anemia, decreases splenomegaly, decreases erythropoietin concentrations and makes erythropoiesis more effective<br /> 3. DFP treatment does not change hepcidin mRNA but increases it relative to the iron load. Consistently, DFP treatment also lowers the expression of erythroferrone mRNA in erythroblasts.<br /> 4. DFP lowers erythroblast reactive oxygen species

The authors identify a number of changes that result from iron chelation in their model but do not causally link them to the improvements in iron overload, anemia or ineffective erythropoiesis:<br /> 5. DFP alters the expression of GATA-1, Bcl-XI, EpoR, TfR1 but not TfR2, as well as intracellular iron chaperone Pcbp1, and the cargo receptor Ncoa4<br /> 6. Analyses of the same genes in human CD34+ selected bone marrow samples from unclassified MDS patients are shown but no conclusion or comparison is (or can be) made to the mouse data.<br /> 7. The data therefore do not provide a mechanistic explanation of the effect of DFP on anemia and ineffective erythropoiesis

The manuscript has significant strengths and several substantial weaknesses. The strengths include the establishment of a mouse MDS model that manifests anemia, ineffective erythropoiesis and non-transfusional iron overload, with increased erythroferrone and inadequate hepcidin response to iron overload, features that improve after treatment with deferiprone. The main structural weakness is that the many changes in erythroid pathways documented in the manuscript do not establish the mechanism by which deferiprone mediates these beneficial effects.

Reviewer #1 (Public Review):

Myelodysplastic syndrome (MDS) represents as a rather complex and serious hematologic malignancy that affects the production of normal blood cells in the bone marrow. Some types of MDS could stay mild for years and other types of MDS could be more serious and progressed into AML. Tremendous efforts have been made to investigate the pathogenesis and treatment of MDS. For instance, a pile of papers has found that iron chelation therapy could benefit the overall survival in low risk MDS patients. Yet, the risk and benefit of this therapy remain in much debate. The authors demonstrated that erythrocyte precursors could re-gain EPO responsiveness after DFP chelation therapy. In addition, the authors investigated iron trafficking in erythroblasts using the MDS mouse model. The paper is rather interesting as it discussed the biological effects and underlying mechanisms of DFP for the treatment of low-risk MDS. More importantly, the paper adds practical values and theoretical evidences for chelation therapy towards low-risk MDS. The paper is overall well-written.

Reviewer #3 (Public Review):

Myelodysplastic syndrome (MDS) is a heterogenous, clonal hematopoietic stem cell disorder characterized by morphological dysplasia in one or more hematopoietic lineages, cytopenias (most frequently anemia), and ineffective hematopoiesis. In patients with MDS, transfusion therapy treatment causes clinical iron overload; however it has been unclear if treatment with iron chelation yields clinical benefits. In the present study, the authors use a transgenic mouse model of MDS, NUP98-HOXD13 (referred to here as "MDS mice") to investigate this area. Starting at 5 months of age (before MDS mice progress to acute leukemia), the authors administered DFP in the drinking water for 4 weeks, and compared parameters to untreated MDS mice and WT controls.

The authors first show that MDS mice exhibit systemic iron overload and macrocytic anemia that is improved by treatment with the iron chelator deferiprone (DFP). They then perform a detailed characterization the effects of DFP treatment on erythroid differentiation and various parameters related to iron transport and trafficking in MDS erythroblasts. Strengths of the work are the use of a well-characterized mouse model of MDS with appropriate animal group sizes and detailed analyses of systemic iron parameters and erythroid subpopulations. A remediable weakness is that in certain areas of the Results and Discussion, the authors overinterpret their findings by inferring causation when they have only shown a correlation. Additionally, when drawing conclusions based on changes in erythroblast mRNA expression levels between groups, the authors should consider that translation efficiency may be altered in MDS and that the NUP98 fusion protein itself, by acting as a chimeric transcription factor, may also impact gene expression profiles. Given that the application of chelators for treatment of MDS remains controversial, this work will be of interest to scientists focused on erythroid maturation and iron dysregulation in MDS, as well as clinicians caring for patients with this disorder.

Major Comments

1. The authors define the stages of erythroblast differentiation using the CD44-FSC method, which assumes that CD44 expression levels during the stages of erythroid differentiation are not altered by MDS itself. Are morphologically abnormal erythroblasts, such as bi-nucleate forms, captured in this analysis, and if so, are they classified in the appropriate subset? The percentage of erythroblasts in the bone marrow of MDS mice in this current study is lower than that reported by Suragani et al (Nat Med 2014), who employed a different strategy to define erythroid precursors. While representative erythroblast gating is presented as Supplemental Figure 17, it would be important to present representative gating from all 3 animal groups: WT, MDS, and MDS+DFP mice.

2. Methods, "Statistical analysis." The authors state that all comparisons were done with 2-tailed student paired t test, which would not be appropriate for comparisons being made between independent animals groups (i.e. when groups are not "paired").

3. The Results (p.7) indicates that both sexes showed similar responses to DFP; however, the figure legends do not indicate sex. Given that systemic iron metabolism in mice shows sex-related differences, sex should be specified.

Reviewer #1 (Public Review):

In this manuscript, the authors have performed extensive imaging analysis of six human histone H1 variants, their enrichment and localization, their differential dynamics during interphase and mitosis, and their association with lamina-associated domains (LADs) or nucleolus-associated domains. The manuscript is well-written with high-quality confocal and super-resolution images. Various interesting observations are made on distribution patterns of H1 variants. H1.2, H1.3, and H1.5 are shown to be universally enriched at the nuclear periphery whereas H1.4 and H1X are found to be distributed throughout the nucleus. Interestingly, H1X was the only H1 variant found to be abundant in nucleoli. Depletion of H1 variants has been shown to affect chromatin structure in a variant-specific manner, with H1.2 knock-down resulting in global chromatin decompaction. Overall, the study presents several interesting insights on H1 variants conducted in a large number of cell lines.

Major Comments:<br /> 1) Though the co-immunostaining of a nucleolar marker (NPM1) is performed with H1X, it would be interesting to explore the localization of H1 variants with respect to some of the proteins critically involved in chromatin organization such as PC4 or HP1alpha. Since the phosphorylated form of PC4 has been shown to interact with H1, which variants specifically interact with PC4 and how their dynamic changes in interphase and mitosis would be worth exploring.

2) The manuscript would be a complete study if any physiological significance with the H1 variant distribution could be shown.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Salinas-Pena et. al examines the distribution of a subgroup of histone H1 variants primarily with the use of high-resolution microscopy. The authors find that while some H1s have a universal distribution pattern, some display a preference for discrete regions within the nuclear landscape namely, the periphery, the center, or the nucleolus. They also show that using the various H1s within a cell did not colocalize significantly with each other, rather, they occupy discrete 'nanodomains' throughout the nucleus which is visualized as a punctate signal.

The authors present evidence relating to a long-standing question in the field regarding the spatial distribution of the different H1 variants. Since reliable, specific antibodies toward the variants were unavailable, this question was unable to elicit a definitive answer. This study uses more recently available antibodies against endogenous H1s to put together a systematic and comprehensive view of a group of H1 variant distribution inside a nucleus and ties it with previously generated genome-wide data to demonstrate localization and some functional heterogeneity.

Strengths of the study.<br /> 1. First systematic, high-resolution view of H1 variants providing a significant advance towards the long hypothesized functional differences between H1 variants.<br /> 2. The use of endogenous antibodies allows the authors to bypass the need to use tagged proteins or overexpression strategies to study H1 distribution.<br /> 3. The availability of genome-wide H1 distribution data for the variants using the endogenous H1 antibodies to strengthen the presented visual data.

Weakness of the study.<br /> One of the major reasons for slow progress in deciphering variant-specific function has been the dearth of quality, specific, antibodies. This study is heavily dependent on the antibody function and its ability to accurately report on the distribution. However, appropriate controls to confirm the specificity were not included. Commercially available antibodies are equally susceptible to quality issues.

Impact:<br /> This study sets the stage for an exciting avenue of H1 study where variant-specific cellular functions can be explored which has otherwise been severely understudied.

Reviewer #3 (Public Review):

Summary:<br /> This paper uses indirect immunofluorescence, superresolution fluorescence microscopy, and X-ChIP to demonstrate radial distribution profiles of all histone H1 somatic variants with the exception of histone H1.1. The results support earlier work from chromatin immunoprecipitation experiments that revealed biases for active versus repressed states of chromatin. The previous studies provided some support for the subtle sequence variation found primarily within the C-terminus of histone H1 variants conferred preferences in the type of DNA (e.g. methylated DNA) or chromatin-bound. The current study significantly strengthens that argument. Importantly, this was shown across multiple cell lines and reveals conserved properties of localization of histone H1 variants.

Strengths:<br /> The strength of the manuscript is the combined use of quantitative analysis of indirect immunofluorescence and X-ChIP. The results generally support the polar organization of the genome and a corresponding distribution of histone H1 variants that reflect this polar organization. AT-rich chromatin is positioned near the lamina and is found to be enriched in H1.2, H1.3, and H1.5. H1.4 and H1.X were more biased towards the GC-rich intranuclear chromatin.

There is emerging functional evidence for variant-specific properties to histone H1 subtypes. This work provides an important building block in understanding how different histone H1 variants may have specific functional consequences. The histone H1 variant that is most abundant in most cell types, H1.2, was found to decrease the area of the immunofluorescent slice that was chromatin-free when depleted, suggesting a more important role in global chromatin organization.

Weaknesses:<br /> While histone H1 variants may show biases in their distributions, it is unlikely that these are more than biases. That is, it is unlikely that specific H1 variants are unable to bind to nucleosomes in regions where they are depleted. Fluorescence recovery after photobleaching experiments has demonstrated differences in binding affinity but the capacity to bind a range of chromatin structures, including highly acetylated chromatin, for histone H1 variants. Thus, it is critical in assessing this data to have accurate quantitative information on the relative abundance of the different histone variants amongst the cell lines tested here. The paper relies upon quantification by immunoblotting.

Another uncertainty in both the ChIP and immunofluorescence datasets is the accessibility of the epitope. This weakness is highlighted by the apparent loss of H1.2 and H1.4 in mitotic chromosomes which is revealed to be false by the detection of the phosphorylated species. The distributions relative to the surface of chromosomes in mitosis and the depletion of H1.2, H1.3, and H1.5 from the central regions of interphase nuclei reveal an unusual dissipation of the staining that is suggestive of antibody accessibility or potentially overstaining and quenching of the fluorescence in the center of highly stained structures. The overall image quality of the immunofluorescence images is poor.

Reviewer #1 Public Review

Summary<br /> This paper presents a new, but simple and low-cost technique for multimodal EM imaging that combines the strengths of both volume scanning electron microscopy (SEM) and electron microscopic tomography. The novel ATUM-Tomo approach enables the consecutive inspection of selected areas of interest by correlated serial SEM and TEM, optionally in combination with CLEM, as demonstrated here. The most important feature of ATUM-Tomo, particularly of correlative ATUM-Tomo, is that it can bridge scales, from the cellular to the high-resolution subcellular scale, from micrometer to low nanometer resolution. This is particularly important for ultrastructural analyses of biological regions of interest, which is demonstrated here for focal pathologies or rare cellular and subcellular events. Both imaging modalities are non-destructive, thus allowing re-imaging and hierarchical imaging at the SEM and TEM levels. This is particularly important for precious samples, including human biopsies and samples from complex CLEM experiments. Beyond the demonstrated neuropathology-related application, further use in investigating normal and pathologically altered brains, including human brain tissue samples that require high-resolution SEM and TEM in combination with immunohistochemistry, and virus or tracer injections, would be possible. Thus, ATUM-Tomo provides new possibilities in multimodal volume EM imaging for diverse areas of biological research.

Strengths<br /> This paper is a very nice piece of work, bringing together modern high-end state-of-the-art technology that will allow us to investigate diverse biological questions in different areas of interest and at different scales. The paper is clear and well-written, although some additions are necessary to the methods section and the scientific results as exemplified by investigations of the blood-brain barrier. The discussion would benefit from an expansion of the part dealing with the scientific results. The paper is accompanied by excellent figures, supplemental information, and colored 3D-reconstructions, which makes it easy for the reader to follow the experimental procedure and the scientific context. The authors may consider moving the supplemental figures into the main body of the paper, which would then still contain 'only' eight figures.

Weaknesses<br /> There is some imbalance between the description of the state-of-the-art methodology and the scientific context.

Reviewer #2 Public Review

Summary<br /> Kislinger et al. present a method permitting a targeted, multiscale ultrastructural imaging approach to bridge the resolution gap between large-scale scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The key methodological development consists of an approach to recover sections of resin-embedded material produced by Automated Tape Collecting Ultramicrotomy (ATUM), thereby permitting regions of interest identified by serial section SEM (ATUM-SEM) screening to be subsequently re-examined at higher resolution by TEM tomography (ATUM-Tomo). The study shows that both formvar and permanent marker coatings are in principle compatible with the solvent-based release of pre-screened sections from ATUM tape (carbon nanotubule or Kapton tape). However, a comparative analysis of potential limitations and artifacts introduced by these respective coatings revealed permanent marker to provide a superior coating; permanent marker coatings are more easily and reliably applied to tape with only minor contaminants affecting the recovered section-tape interface with negligible influence on tomogram interpretation. Proof-of-principle is provided by integrating this novel ATUMTomo technique into a technically impressive correlated light and electron microscopy (CLEM) approach specifically tailored to investigate ultrastructural manifestations of trauma-induced changes in blood-brain barrier permeability (Khalin et al., 2022).

Strengths<br /> Schematics and well-constructed figures clearly illustrate the general workflow, light and electron microscope image data are of excellent quality, and the efficacy of the ATUM-Tomo approach is documented by qualitative assessment of ATUM-SEM performance using coated tape variants and a convincing correlation between scanning and transmission electron microscopy imaging modalities. Potential ultrastructural artifacts induced via solvent exposure and any subsequent mechanical stress incurred during section detachment were systematically investigated using appropriate methods and transparently reported. In summary, the presented data are consistent with the study's claims. A major strength of this work includes its general applicability to a broad range of biological questions and ultrastructural targets demanding resolutions exceeding that obtained via serial section and block-face imaging approaches alone. Importantly, this relatively simple and cost-effective technique is widely adopted by electron microscopy laboratories. Its integration into existing ATUM-SEM workflows supports a versatile and non-destructive imaging regime enabling high-resolution details of targeted structures to be interpreted within anatomical and subcellular contexts.

Weaknesses<br /> Given the identified importance of glow-discharge treatment of precoated tape to the flat deposition of sections during ATUM, a corresponding schematic or appropriate reference(s) providing more information about the custom-built tape plasma device would likely be a prerequisite for effective reproduction of this technique in other laboratories.

Reviewer #1 (Public Review):

Sun and co-authors have determined the crystal structures of EHEP with/without phlorotannin analog, TNA, and akuBGL. Using the akuBGL apo structure, they also constructed model structures of akuBGL with phlorotannins (inhibitor) and laminarins (substrate) by docking calculation. They clearly showed the effects of TNA on akuBGL activity with/without EHEP and resolubilization of the EHEP-phlorotannin (eckol) precipitate under alkaline conditions (pH >8). Based on this knowledge, they propose the molecular mechanism of the akuBGL-phlorotannin/laminarin-EHEP system at the atomic level. Their proposed mechanism is useful for further understanding of the defensive-offensive association between algae and herbivores.

Reviewer #2 (Public Review):

In this study the authors try to understand the interaction of a 110 kDa ß-glucosidase from the mollusk Aplysia kurodai, named akuBGL, with its substrate, laminarin, the main storage polysaccharide in brown algae. On the other hand, brown algae produce phlorotannin, a secondary metabolite that inhibits akuBGL. The authors study the interaction of phlorotannin with the protein EHEP, which protects akuBGL from phlorotannin by sequestering it in an insoluble complex.

The strongest aspect of this study is the outstanding crystallographic structures they obtained, including akuBGL (TNA soaked crystal) structure at 2.7 Å resolution, EHEP structure at 1.15 Å resolution, EHEP-TNA complex at 1.9 Å resolution, and phloroglucinol soaked EHEP structure at 1.4 Å resolution. EHEP structure is a new protein fold, constituting the major contribution of the study.

The drawback on EHEP structure is that protein purification, crystallization, phasing and initial model building were published somewhere else by the authors, so this structure represents incremental research.

One concern remains unanswered to me. If the mechanism of action of EHEP is to precipitate together with TNA in a 1:1 insoluble complex, then it does not matter if there are multiple mechanisms involved in the activity assay, the protection of 4uM EHEP against 40uM TNA simply requires a different stoichiometry.

Reviewer #3 (Public Review):

The manuscript by Sun et al. reveals several crystal structures that help underpin the offensive-defensive relationship between the sea slug Aplysia kurodai and algae. These centre on TNA (a algal glycosyl hydrolase inhibitor), EHEP (a slug protein that protects against TNA and like compounds) and BGL (a glycosyl hydrolase that helps digest algae). The hypotheses generated from the crystal structures herein are supported by biochemical assays.

The crystal structures of apo and TNA-bound EHEP reveals the binding (and thus protection) mechanism. The authors then demonstrate that the precipitated EHEP-TNA complex can be resolubilised at an alkaline pH, potentially highlighting a mechanism for EHEP recycling in the A. kurodai midgut. The authors also present the crystal structures of akuBGL, a beta-glucosidase utilised by Aplysia kurodai to digest laminarin in algae into glucose. The structure revealed that akuBGL is composed of two GH1 domains, with only one GH1 domain having the necessary residue arrangement for catalytic activity, which was confirmed via hydrolytic activity assays. Docking was used to assess binding of the substrate laminaritetraose and the inhibitors TNA, eckol and phloroglucinol to akuBGL. The docking studies revealed that the inhibitors bound akuBGL at the glycone-binding suggesting a competitive inhibition mechanism. Overall, most of the claims made in this work are supported by the data presented.

Reviewer #1 (Public Review):

Gambelli et al. provide a structural study of the SlaA/SlaB S-layer of the archaeon Sulfolobus acidocaldarius. S-layers form an essential component of most archaeal cell envelopes, where their self-assembling properties and activity as cell envelope support structures have raised substantial interest, both from researchers seeking to understand the fundamental biology of archaea, as well as researchers seeking to exploit the biomaterial properties of S-layers in biotechnological applications. Both interests are hampered by the paucity of structural information on archaeal S-layer assembly, structure, and function to date, in large part due to technical difficulties in their study.

In this study, Gambelli and coworkers overcome these difficulties and report the high-resolution 3D cryoEM structures of the purified SlaA monomers at three different pH, as well as the medium resolution 3D cryoET structures of the SlaA/SlyB lattices determined from S-layer fragments isolated from the Sulfolobus cells.

The structural work is generally well executed, although lacks in detail in places to allow a proper review, particularly in the cryoET. A further drawback of the current manuscript is that the structural work remains rather descriptive and speculative, with little validation of the proposed models.

The authors run a plethora of representation, analyses, prediction, and simulation software on their structures resulting in an abundance of Figures that risk overloading the reader and in several cases bring little new insight beyond unsubstantiated speculation.

The structural description of the S. acidocaldarius S-layer will be of high general interest and the authors have made a substantial leap forward, but the current manuscript would benefit from a better validation and basic atomic description of the SlaA/SlaB S-layer.

Specific points.

- It is not possible to review the quality of the SlaA and SlaA/SlaB models in the cryoET reconstruction. No detailed fits of the map and model are shown, and no correlation statistics are given (the latter is also true for the higher resolution 3D reconstructions at pH4, 7, and 10). To be of use to the community, the S-layer model and cryoET maps should also be deposited in PDB and EMDB, and an autodep report and ideally the cryoET maps should be available.

- The authors spend a great deal on the MD simulation of the SlaA glycans and the description of the 'glycan shield' and its possible role in subunit electrostatics and intersubunit contacts. This does not result in testable hypotheses, however, and does not bring much more than vague speculation on the role of the glycans or the subunits contacts in S-layer assembly and stability. For the primary description of the SlaA/B S-layer, more important would be a detailed atomic description and validation of the intermolecular contacts in the proposed lattice model. Given the low resolution of the cryoET, this would require MD simulation of the contacts. Lattice stability during MD simulation and/or the confirmation of lattice contacts by cross-linking mass spectrometry would go a great way in validating the proposed lattice model.

- The discussion of the subunit electrostatics and the role they could play in subunit assembly/disassembly remains superficial and speculative. No real model or hypothesis is put forward, let alone validated.

- The authors solve the cryoEM structure of SlaA released and purified form S. acidocaldarius S-layers by an alkaline pH shift. When shifted back to acidic pH, does this native material self-assemble in vitro? If not, do the authors have an explanation for this? Are components missing or could the solved structures represent SlaA conformations that are no longer assembly competent?

Reviewer #2 (Public Review):

Gambelli et al. investigated the surface layer (S-layer) of Sulfolobus acidocaldarius by using combined single particle cryo-electron microscopy (cryoEM), cryo-electron tomography (cryoET), and Alphafold2 predictions to generate an atomic model of this outermost cell envelope structure. As known from previous studies, the two-dimensional lattice comprises two distinct S-layer glycoproteins (SLPs) termed SlaA, the outer component interacting with the harsh living environment of this archaeon, and SlaB, comprising a dominant hydrophobic domain, which anchors this SLP in the cytoplasmic membrane, respectively. The interwoven S-layer lattice of S. acidocaldarius shows a hexagonal lattice symmetry with a p3 topography. It is built very complex as the unit cell constitutes of one SlaB trimer and three SlaA dimers (SlaB3/3SlaA2). Despite the complexity of this distinct proteinaceous S-layer lattice, the authors not only investigated the SLP structures but also considered the glycans in their structure predictions.

The strengths of this study are that it was possible, and the first approach taken, to divide the Y-shaped SlaA SLP, starting from the N-terminus into six domains, D1 to D6. As previous studies revealed that SlaA assembly and disassembly are pH-sensitive processes, the structure of SlaA was investigated at different pH conditions. This approach led to the striking result that the cryoEM maps of SlaA D1 to D4 are virtually identical at the three pH conditions, demonstrating remarkable pH stability of these protein domains. For SlaA at low pH, however, the domains D5 and D6 were too flexible to be resolved in the cryoEM maps. Nevertheless, the authors were able to hypothesize that jackknife-like conformational changes of a link between domains D4 and D5, as well as pH-induced alterations in the surface charge of SlaA play important roles in S-layer assembly.<br /> This study showed in addition, that the surface charges of SlaA shift significantly from positive at acidic pH to negative at basic pH. A comparison of the surface charge between glycosylated and non-glycosylated SlaA showed that the glycans contribute considerably to the negative charge of the protein at higher pH values. This change in electrostatic surface potential may therefore be a key factor in disrupting protein-protein interactions within the S-layer, causing its disassembly as it is highly desired for new practical applications in biomolecular nanotechnology and synthetic biology.<br /> An excellent approach was to use exosomes to determine the structure of the entire S-layer structure comprising of SlaA and SlaB. By this approach, effectively two zones in the SlaA assembly could be distinguished: an outer zone constituted by D1 to D4, and one inner zone formed by D5 and D6. Moreover, for the first time, deeper insights into how SlaA forms the hexagonal and triangular pores within the S-layer lattice of S. acidocaldarius are provided. Very interesting are the found SlaA dimers, which are suggested to be formed by two SlaA monomers through the D6 domains, with each SlaA dimer spanning two adjacent hexagonal pores.

The weaknesses in this work are in the introduction, where the citation is incomplete. In the comparisons drawn between archaeal and bacterial S-layers, basic citations are missing for the latter. One gets the impression that there is a deliberate avoidance of citing individual prominent S-layer research groups here. The same is true for citations of glycosylation of archaeal S-layer proteins and Sulfolobus mutants lacking SlaB.<br /> The authors show many pictures and schematic drawings of high quality. In the main text, these illustrations should be briefly commented on if there is any ambiguity. For example, it is somewhat difficult to understand that in one schematic drawing the angle between the SlaA longitudinal axis and the membrane plane is 28 degrees and at the same time in another schema, the angle of the longitudinal axes in SlaA dimers is given as 160 degrees.<br /> The authors argue that by a pH shift to 10, SlaA disassembles and exists exclusively as a single molecule. The presence of exclusively single SlaA proteins and the purity of the fractions were assessed by SDS/PAGE analysis and cryoEM micrographs. However, one can doubt that, due to the strong denaturing effect of SDS and the subsequent dissociation of protein complexes, SlaA dimers or oligomers could have been determined with SDS/PAGE. Moreover, the shown representative micrographs (supplementary figure 2, a-c) show a heterogeneous structure and thus, do not support the exclusive presence of disassembled SlaA monomers.<br /> An interesting finding is SlaA dimerization. SlaA dimers can obviously be found in co-existence with SlaA-only S-layer as shown in supplementary figure 15. A short discussion on whether dimers are an intermediate structure in the process of S-layer lattice formation from monomeric SlaA or if this structure was just a coincident observation could help the reader to better understand the meaning of these dimeric structures and at which stage they are formed.

Reviewer #1 (Public Review):

The manuscript by Royall et al. builds on previous work in the mouse that indicates that neural progenitor cells (NPCs) undergo asymmetric inheritance of centrosomes and provides evidence that a similar process occurs in human NPCs, which was previously unknown.

The authors use hESC-derived forebrain organoids and develop a novel recombination tag-induced genetic tool to birthdate and track the segregation of centrosomes in NPCs over multiple divisions. The thoughtful experiments yield data that are concise and well-controlled, and the data support the asymmetric segregation of centrosomes in NPCs. These data indicate that at least apical NPCs in humans undergo asymmetric centrosome inheritance. The authors attempt to disrupt the process and present some data that there may be differences in cell fate, but this conclusion would be better supported by a better assessment of the fate of these different NPCs (e.g. NPCs versus new neurons) and would support the conclusion that younger centriole is inherited by new neurons.

Reviewer #2 (Public Review):

Royall et al. examine the asymmetric inheritance of centrosomes during human brain development. In agreement with previous studies in mice, their data suggest that the older centrosome is inherited by the self-renewing daughter cell, whereas the younger centrosome is inherited by the differentiating daughter cell. The key importance of this study is to show that this phenomenon takes place during human brain development, which the authors achieved by utilizing forebrain organoids as a model system and applying the recombination-induced tag exchange (RITE) technology to birthdate and track the centrosomes.

Overall, the study is well executed and brings new insights of general interest for cell and developmental biology with particular relevance to developmental neurobiology. The Discussion is excellent, it brings this study into the context of previous work and proposes very appealing suggestions on the evolutionary relevance and underlying mechanisms of the asymmetric inheritance of centrosomes. The main weakness of the study is that it tackles asymmetric inheritance only using fixed organoid samples. Although the authors developed a reasonable mode to assign the clonal relationships in their images, this study would be much stronger if the authors could apply time-lapse microscopy to show the asymmetric inheritance of centrosomes.

Reviewer #3 (Public Review):

In this manuscript, the authors report that human cortical radial glia asymmetrically segregates newly produced or old centrosomes after mitosis, depending on the fate of the daughter cell, similar to what was previously demonstrated for mouse neocortical radial glia (Wang et al. 2009). To do this, the authors develop a novel centrosome labelling strategy in human ESCs that allows recombination-dependent switching of tagged fluorescent reporters from old to newly produced centrosome protein, centriolin. The authors then generate human cortical organoids from these hESCs to show that radial glia in the ventricular zone retains older centrosomes whereas differentiated cells, i.e. neurons, inherit the newly produced centrosome after mitosis. The authors then knock down a critical regulator of asymmetric centrosome inheritance called Ninein, which leads to a randomization of this process, similar to what was observed in mouse cortical radial glia.

A major strength of the study is the combined use of the centrosome labelling strategy with human cortical organoids to address an important biological question in human tissue. This study is similarly presented as the one performed in mice (Wang et al. 2009) and the existence of the asymmetric inheritance mechanism of centrosomes in another species grants strength to the main claim proposed by the authors. It is a well-written, concise article, and the experiments are well-designed. The authors achieve the aims they set out in the beginning, and this is one of the perfect examples of the right use of human cortical organoids to study an important phenomenon. However, there are some key controls that would elevate the main conclusions considerably.

1) The lack of clonal resolution or timelapse imaging makes it hard to assess whether the inheritance of centrosomes occurs as the authors claim. The authors show that there is an increase in newly made non-ventricular centrosomes at a population level but without labelling clones and demonstrating that a new or old centrosome is inherited asymmetrically in a dividing radial glia would grant additional credence to the central conclusion of the paper. These experiments will put away any doubt about the existence of this mechanism in human radial glia, especially if it is demonstrated using timelapse imaging. Additionally, knowing the proportions of symmetric vs asymmetrically dividing cells generating old/new centrosomes will provide important insights pertinent to the conclusions of the paper. Alternatively, the authors could soften their conclusions, especially for Fig 2.<br /> 2) Some critical controls are missing. In Fig. 1B, there is a green dot that does not colocalize with Pericentrin. This is worrying and providing rigorous quantifications of the number of green and tdTom dots with Pericentrin would be very helpful to validate the labelling strategy. Quantifications would put these doubts to rest. Additionally, an example pericentrin staining with the GFP/TdTom signal in figure 4 would also give confidence to the reader. For figure 4, having a control for the retroviral infection is important. Although the authors show a convincing phenotype, the effect might be underestimated due to the incomplete infection of all the analyzed cells.<br /> 3) It would be helpful if the authors expand on the presence of old centrosomes in apical radial glia vs outer radial glia. Currently, in figure 3, the authors only focus on Sox2+ cells but this could be complemented with the inclusion of markers for outer radial glia and whether older centrosomes are also inherited by oRGCs. This would have important implications on whether symmetric/asymmetric division influences the segregation of new/old centrosomes.

Reviewer #1 (Public Review):

In this manuscript, Kim et al. investigate the molecular basis for hindbrain segmentation by performing combined single cell nucleus RNAseq and ATACseq (scMultiome) on zebrafish embryonic hindbrain tissue. Hindbrain segmentation is fundamental to head development in vertebrate species. Decades of research have provided many insights into the gene regulatory cascades that control the progressive subdivision of the hindbrain territory into segments (rhombomeres). These studies have enabled the formulation of gene regulatory network (GRN) models that depict these regulatory interactions. However, many aspects of the GRN need further clarification, including the early steps of pre-rhombomeric patterning, and the factors that respond to axial signaling pathways such as RA and FGF. The dataset in this study provides a comprehensive view of gene expression and chromatin states during hindbrain segmentation, thus it is a valuable resource for characterizing the underlying GRN. The authors demonstrate the utility of this data by comparing the molecular profiles between different rhombomeres and tracing when and how these profiles arise during development.

Four main findings are presented:

1. Each rhombomere has a unique molecular profile.<br /> 2. There is no clear molecular signature for odd versus even rhombomeres, nor any overt repeating two-segment molecular identities.<br /> 3. The mature rhombomeres emerge through the subdivision of three mixed-identity 'primary hindbrain progenitor domains' (PHPDs) that correspond to r2/r3, r4, and r5/r6, respectively.<br /> 4. RA and FGF signaling control formation of the primary hindbrain progenitor domains.

These findings are well supported by the data but in my opinion they mainly confirm what was already known and do not significantly advance our mechanistic understanding of rhombomere formation, which is the aim of the paper.

Strengths:<br /> This comprehensive dataset will be very valuable to researchers in the field. The authors successfully demonstrate its utility by resolving unique molecular profiles for each rhombomere and identifying some novel markers.

The authors make excellent use of HCR to validate their findings, such as the co-expression of vgll3 and egr2b in r2/r3 cells at 10hpf, which implies mixed identities of PHPD cells.

The performance of scMultiome analysis on tissue from DEAB-treated embryos (depleted RA signaling) is exciting and holds much promise for identifying RA-dependent gene regulatory cascades that govern caudal hindbrain patterning. Assessing the contribution of control versus DEAB-treated cells to the various UMAP clusters is a very nice way to identify the altered cell states in the RA-depleted hindbrain. This confirms a complete absence of r5 and r6 in the DEAB-treated embryos at this developmental stage, as was inferred from in-situ approaches in earlier studies.

Weaknesses:<br /> The major weakness of this work is that it only provides an incremental mechanistic advance to our current understanding of the molecular basis for rhombomere formation. The descriptions of gene expression are useful but for the most part they are rather shallow lines of enquiry that confirm what was already known from previous, less comprehensive studies of gene expression. For example, regarding the identification of PHPDs, it has long been known that r5/r6 share a progenitor domain that is demarcated by mafba expression. Similarly, RA and Fgf signaling have already been shown to be required for anterior-posterior patterning in the pre-rhombomeric hindbrain. The identification of mixed-identity progenitors in PHPDs, and the characterisation of the changes in transcription and chromatin state in response to RA signaling perturbation are really exciting starting points for deeper analysis of the underlying GRN. However, it is a shame that no effort is made to glean mechanistic insights from this dataset by computational GRN inference.

Reviewer #2 (Public Review):

The hindbrain is one of three primary anatomical domains of the developing brain, and is thought to be important for motor activity, respiratory rhythm, and sleep and wake behavior. The purpose of this study was to analyse spatiotemporal changes in gene expression during early development of the hindbrain. The authors used single cell RNA sequencing and ATAC sequencing at three developmental stages of zebrafish embryo development to characterize the transcriptomic changes that occur as the hindbrain neuroepithelium resolves into rhombomeres and the expression of a small number of genes was validated by in situ hybridization. The bulk of the "omic" dataset potentially provides a resource for the field to functionally analyze, but otherwise only incrementally advances our understanding of hindbrain rhombomere development and patterning. The primary conclusion from the work is that hindbrain progenitor domains contain mixed identity progenitors that eventually resolve into individual mature rhombomeres. This concept has been known historically for quite some time based on the expression of many genes of the Hox and other gene families, despite the authors describing this at higher resolution through analyses of whole genome expression. Unfortunately, the paper is largely a descriptive resource of transcriptomic data which in the absence of functional experimentation tells us very little that's new about the fundamental development or function of rhombomeres.

Reviewer #3 (Public Review):

Rhombomeres are key organizational structures for building cell type and even functional diversity in the brainstem. How these rhombmeres ultimately arise from a broad neuro-epithilium remains unclear. While genetic, cellular, tissue, and morphogen manipulations have revealed key processes in rhombomere development the hierarchical organization of neuron-epithelium into individual rhombomeres was less well understood. For example it is thought that rhombomeres are organized in an even odd fashion where two base identities i.e. even or odd where laminated with paired identifies i.e. rhombomeres 1 and 2 being paired and so on. However, there are many exceptions to these organizing constructs at the gene expression levels.

To further interrogate early development of the hindbrain neuro-epithelium and gain insight as to how rhombomere identities emerge at the earliest stages, Kim et al used ATACseq and RNAseq to query chromatin landscapes and gene expression for single nuclei at different developmental stages of zebrafish hindbrain development. The goal of the two pronged approach termed scMultiome analysis was to gain additional insight beyond either method individually for characterizing early events in rhombomere differentiation.

Using scMultiome, three stages of zebrafish hindbrain development were examined at 10hpf(whole embryos), 13hpf, and 16hpf. In the early hindbrain, the data shows that at 13hpf early rhombomere identities can be resolved but that the typical markers seen later are not fully expressed or resolved. At 10hpf clear rhombomere identities are not present. Rather at very early stages, the analysis suggests that three domains for pre-rhombomeres encompassing HB1 - r2+r3 (possibly r1, but this remains to be resolved); HB2 - r5+r6; and HB3 - 4 are present. These clusters or PHPDs are mixed populations that presumably resolve later as the embryo matures. They are shown to be responsive to developmental signals that pattern the neuroepithelium supporting the premise that these are rhombomeric organization structures.

Altogether the use of two methods of transcriptional interrogation i.e. ATACseq and RNA seq are strengths for the presented work to offer increased resolution of cell type characterization. The data analysis is reasonably supported by expression studies using in situ Hybridization Chain Reaction (HCR) to show mixed markers in the early stages. the PHPDs are also responsive to perturbation in retinoid acid, supporting the overall premise.

Overall, the work is well executed and analyzed. The impact in the field largely resides in bringing increasing resolution to earlier stages of rhombomere development and re-examining long held paradigms about when and potentially how rhombomere periodicity and pairing are established at the earliest stages. The premise that pre-rhombomeres may first establish large domains that sort or otherwise resolve themselves into rhombomeres is the most notable outcome from the work and will be seen as impactful in the field.

Reviewer #1 (Public Review):

This manuscript by Proskurin, Manakov, and Karpova, posits a unique role for the anterior cingulate cortex (ACC) in the flexible control of learned sequences of motor actions. The authors marshall evidence from behavioral-electrophysiological analyses in support of two major claims: 1) that action encoding by ACC ensembles tracks 1) the current "context", i.e., which behavioral sequence is rewarded, and 2) the "prevalence", i.e., number of repetitions of one specific sequence. An important aspect of this later point is that the authors propose prevalence encoding is not strictly dependent on trial-by-trial reward receipt.

In this work, the authors wish to focus on self-initiated behavior when the correct behavioral sequence, out of four or fewer (mostly two it appears), changes across blocks in an unsignaled manner. Rats learn to enter a left and right nose poke in a sequence of three responses, with a required entry into a central port prior to each intra-sequence response, with correct sequence completion reinforced by a sucrose delivery in the relevant side nose poke port. Extracellular spike activity is acquired from well-trained rats performing this task. The authors' analyses of the behavior of well-trained rats show rats adjust their behavior when the block switches to a different one of the sequences in the known 'library'. The rats also perform non-reinforced responses/sequences within a given block which the authors suggest is exploration likely not triggered by changes in reinforcement in contrast to behavior change after a block switch.

The authors next provide a very rich set of analyses to examine the encoding of responses and sequences by ACC neural activity. Overall, these data provide intriguing support for ACC's integral contributions to flexible behavioral control. However, some of the individual analyses are a bit difficult to follow and could be clarified with greater detail within the results section of the paper, permitting an easier evaluation of the quality of the supporting data. Second, there are some proposals that could be strengthened by fuller analysis, in particular the authors' suggestion that "prevalence" encoding is distinct from reward encoding and/or is not impacted by reward presence or omission. Given the likely rich data set in hand, the authors could do more to demonstrate how "prevalence" encoding interacts with reinforcement parameters or perhaps be more specific in their word choice. More importantly, I was left unclear on how "prevalence" encoding intersects with the decision to repeat the same behavioral sequence on the next trial or not. These issues aside, this work provides further information on the physiology of ACC during flexible behavior and will add importance to this field.

Below are specific issues:

1. Some greater attention to the behavioral parameters could be helpful, especially regarding the impact of reward rate on behavior. For example, looking at some of the figures of individual rat behavior, exploratory sequences seemed triggered by reward omission. Is this just a chance for the examples chosen or is there something systematic here? Upon block switch, how exactly does the switch in sequences emitted by the rat track with reinforcement history? The authors mention that reinforcement probability differed across sessions, and one would thus expect switching behavior would as well. Because of the interesting existence of sometimes quite long 'tails' of performance of the original sequence after a block switch, I am wondering how the length of such tails relates to reinforcement rate parameters.

2. The authors provide strong data indicating that a given L or R response is associated with distinct ACC activity depending on which sequence that response is embedded within, a finding reminiscent of other reports in multiple brain regions. While not a criticism per se, I was interested in the center port responses, also embedded within unique sequences, yet never preceding reward. A key difference in the performance of a given R or L response is that it is sometimes the terminal response, and thus the rat knows a given R or L response to be sometimes reinforced in one of the contexts, but not the other, in each of these comparisons. I wonder if there was an opportunity to cleanly demonstrate the context dependence of a given individual action by comparing center port responses across distinct sequences.

3. In analyzing neural activity accompanying the behavioral persistence of the dominant sequence after a block change, the authors find that the ACC ensemble firing pattern is closer to the original dominant sequence pattern during reinforcement and less like this pattern during exploration. This makes sense and must be the case, as, in the example shown in the figure, the rat does not "know" the block has switched since no reward has yet been delivered that would signal that switch. (As an aside, it would be interesting to know, given a specific reward schedule in a given session, what would be the maximum number of unrewarded trials within the block, and how might that impact the performance/reward expectation during the tails?)<br /> As time, and trials, progress the rat is approaching the point at which it explores another strategy. The authors find strengthened "prevalence" encoding with increasing sequence repetition, but if this parameter is related to behavioral change/flexibility, this was not clear to me. Might there be something unique about the last trials in a tail "predicting" an upcoming switch? Can the authors please expand?<br /> Relatedly, if the prediction of upcoming behavioral change is not observed in the neural activity from sequence steps 2-6, it is notable that these are the steps 'within' the sequence, that leaves out the initiation (first center poke) and termination (reward/reward omission). Thus one could imagine this information is "missed" in the current analysis given that both the reward period and the initiation of a trial at the center are not analyzed. This does lead me to suggest a softening of some claims made of identifying "unifying principles" of ACC function, as the authors state, based on the analyses included in the current report, since the neural activity related to the full unit of behavior is not considered. (I appreciate the motivation behind this focus on within-sequence behavior - the wish to compare time periods with similar movement parameters .)

4. The variance in neural activity explained by the prevalence models is on average quite low. However, the authors find that the variance explained differs quite dramatically by anatomical coordinate within ACC. Would it make sense to focus the control analyses (vigor, reward history, and so on) on those sessions/ensembles with greater variance explained, ie, perhaps there might be greater sensitivity to detecting interactions among variables within ensembles recorded more rostrally?

5. A very intriguing aspect of this work is the position that (from the abstract): "Prevalence encoding in the ACC is ...independent of reward delivery." This is a novel aspect of the current work. However, I am wondering if the authors can refine and expand upon this. I find it difficult to disentangle prevalence encoding and impacts of reward in the way the data and interpretation are presented in some areas of the text. While neural encoding may not reflect trial-by-trial reward receipt, clearly the rat's decision to repeat a given sequence or initiate a new sequence is impacted by reinforcement parameters and reward expectation. Thus being very exact in the interpretation would be helpful.

Reviewer #2 (Public Review):

Correctly keeping track of behavioral strategies allows for flexible context-appropriate behaviors. Several brain regions, including the anterior cingulate cortex (ACC), have been proposed to be involved in this process. But its neural correlates and computation principles still need to be uncovered, especially at the neural population level.

In this manuscript, to find such neural correlates, the authors create a behavioral task in which rats must discover a strategy and use it to obtain a reward. Specifically, the authors train rats to perform a self-initiated nose-poking task in which, within every 250-500 trials, rats performing a target '3-step action sequence' leads to sucrose reward delivery. The target action sequence is viewed as 'latent' because it is un-signaled, and rats have to infer it based on past choices and outcomes. Behavioral analyses show that rats' actions comply with the target action sequence after training. However, even at the expert level, rats sometimes show deviations from choosing the target action sequence and instead choose the alternative action sequence. Based on several criteria, the authors identify most of these deviations to reflect an 'exploratory' nature of the rats' behavior in this task. Tetrode recordings in these trained rats show that most ACC neurons encode 'strategy prevalence,' basically, a signal telling which strategy dominates rats' sequential nose-poking actions. Such representation is not restricted to ACC and is also found in M2 and SMC, though with less pronounced correlations. Beyond encoding such a 'global' strategy, the ACC neurons also show activity related to 'local' fluctuations in rats' choices, which the authors argue cannot be explained by several commonly considered behavioral variables, including movement kinematics and vigor and reward expectation. Interestingly, the strategy prevalence is decodable across sequence execution time with a weight-fixed decoder, even though most neurons show transient selectivity to strategy prevalence at the single-cell level, showing the importance of neural population representation.

The behavioral task design is complicated yet appealing. In this task, rats must constantly adjust their behavioral strategy to align with the un-signaled target sequence changes. The task design and the following neural data analyses represent a technical strength of the current study. After controlling for many confounding factors, the ACC neural activities distinguish between 'dominant' vs. 'exploratory' sequence prevalence and contain the specific sequence identities. Building upon their previous work, in this study, the authors reveal more detailed neural dynamics mechanisms for the involvement of ACC in signaling subjective behavioral strategy other than the actual task rule. These findings are conceptually important and would greatly draw the attention of many interested in the neural mechanisms of higher-order brain functions at the systems level.

The primary weakness of the study, however, is that the behavioral and data analyses cannot eliminate all the confounding factors, although, in certain conditions, such influences can be minimized to an acceptable level. That said, the current analyses only partially support the authors' conclusions. Nevertheless, despite these limitations, this study aiming at isolating neural correlates of the 'strategy prevalence' has substantial value in its methodology and proposed hypothesis on ACC behavioral functions and would likely have a significant impact on the field. The innovative data analysis methods implemented in the study can be helpful for related behavioral electrophysiological and imaging studies. Besides, mapping the putative SMC and ACC area to primate SMC and 32D helps to connect the research in rodents and primates.

Reviewer #3 (Public Review):

Proskurin and colleagues aim to test if neurons in rat medial prefrontal cortex encode strategy in a serial choice task. They recorded neural activity as rats performed a nose-poke task for reward. Rats were required to discover, without explicit instruction, which of the possible 3-action sequences were rewarded. One of several possible sequences remained the target (thereby triggering reward delivery) over a block of trials, before switching to an alternate sequence. The authors then used analysis of single neurons and ensembles of neural activity to determine if neural activity reflected whether a sequence was the dominant strategy in a block or an explorative test.

The strengths of the work include the timely and important hypothesis, and the use of appropriate methodologies to test it.

I commend the authors for endeavouring to tackle this challenging topic. The weaknesses of the work derive from the difficulties of studying such a challenging topic. It is extremely difficult to ascribe the variance of neural activity to a latent variable such as strategy, particularly in freely-moving animals motivated by reward. This is because of the plethora of potential confounders. For instance, the authors compare the encoding of one action (L) in two sequences (RLL and LLR). However, the analyzed action occurs in different local contexts. In the first, it is the middle action, and in the second it is the first action following a reward omission. Even though the reward is withheld, the rat presumably has some reward expectation. Because strategy is a latent variable, the evidentiary threshold is high, and alternate explanations of neural variance needed to be rejected. This is particularly important given the neural structures under investigation are involved in regulating motor output, suggesting that differences in response speed, body position, and related variables may explain considerable variance in neural activity. Other potential explanatory variables are rule certainty, position in the sequence, side chosen, preceding choice, and changes in firing rate as the session progresses due to changes in motivation, fatigue, or drift in the signal. The authors attempt to address some of these, but this is done in a very condensed presentation near the end of the results. This needs to be unpacked (and visualized) in order for readers to evaluate whether the strategy is the most likely explanation of neural variance, as proposed by the authors. The paper would benefit from analyses, such as multiple regression over all possible predictive variables, to evaluate the relative amount of neural signal variance attributable to strategy dominance compared to other information.

An additional weakness of the manuscript is the absence of some fundamental checks on data quality, particularly for bias in animal behavior, stability of neural activity during sessions, and bias in data sampling for classifier sampling.

In sum, the experimental methodology appears sufficient to address the authors' aim of evaluating the encoding of strategy by neurons in the medial prefrontal cortex. Alternate interpretations of the data, however, are not sufficiently ruled out by the analysis to strongly support the claim that the exploration of strategy is the primary driver of altered neural signalling. The data and methodologies are valuable to behavioral and systems neuroscientists. The task and the finding that rats appear to spontaneously explore alternate strategies are elegant, and a very nice paradigm for studying the neural mechanisms of strategy shifting. Moreover, the finding that many neurons in the medial prefrontal cortex change their firing rate during the task is an important new contribution. Future analysis and experiments will undoubtedly better resolve the information encoded by these changes in firing rate.

Reviewer #1 (Public Review):

Summary:

Fox, Dan, and Loewenstein investigated how people explored six maze-like environments. They show that roughly one-third of their participants make choices now that increase the potential for future information gain and also temporally discount potential information gain based on how far in the future potential gains might be. The authors argue that rather than valuing exploration in its own right, participant behavior is most consistent with using exploration as a way to reduce uncertainty. They then propose a reinforcement learning (RL) model in which agents estimate an "exploration value" (the expected cumulative information gained by taking a given action in a given state) using standard RL techniques for estimating value (expected cumulative reward). They find that this model exhibits several qualitative similarities with human behavior and that it best captures the temporal dynamics of human exploration when propagating information through the entire history of a behavioral episode (as opposed to merely propagating it in a single step as some of the simplest RL models do).

While the core insight and basic method of the paper are compelling, the way in which both the behavioral experiment and computational modeling were conducted raise concerns that mean that, in their present form, the results do not fully justify the conclusions. After resolving these issues, the work would demonstrate how human exploration is sensitive to long-range dependencies in information gain, as well as valuable insights about how best to characterize this behavior computationally. I am not particularly well-versed in the literature on exploration so cannot comment on novelty here.

Strengths:<br /> The entire paper is logically well-motivated. It builds on a valuable basic insight, namely that while bandit tasks are an ideally minimal platform for testing certain questions about decision-making and exploration, richer paradigms are needed to capture the long-range informational dependencies distinguishing between various approaches to exploration.

Even so, the maze navigation paradigm explored here remains simple. Participants navigate a maze with two main branches which are identical save for minimal, theoretically motivated differences. Moreover, the tested differences are designed to clearly and explicitly test well-identified questions. The task, and really the entire paper, is clearly organized, and each component is logically connected to a larger argument.

The proposed model is also simple, clearly presented, and a clever way of applying ideas typically used to reason about reward-motivated behavior to reason here about information-motivated behavior.

One other strength of this work is that it combines behavioral experiments with computational modeling. This approach pairs a detailed and objectively specified theory (i.e. the model) with novel data specifically designed to test that theory and thus in principle presents a particularly strong test of the authors' hypotheses.

Weaknesses:<br /> Despite many strengths in the underlying logic of the paper, the presented evidence does not provide compelling support for the conclusions. In particular:

- The main claims are based on the behavior of 452 participants classed as good explorers, out of 1,052 participants included in the analyses and 1,336 participants who completed the study. That is, the authors' broad claims about human exploration are based on a third of their total sample; the other two-thirds displayed very different behavior, including 20% who performed at or below chance levels. That is, while a significant sub-population may demonstrate the claimed abilities, it is far from clear that they are universal.

- While the experimental manipulations are elegant, the behavioral study seems underpowered. In each of the primary manipulations, key theoretical predictions are not statistically validated. For example, in Experiment 1, the preference for the right door increases from the 4:3 condition to the 5:2 condition, but not when moving from the 5:2 condition to the 6:1 condition, as predicted (Figure 1c). Similar results can be seen for other analyses in Figures 3b and 4b. Relatedly, the experiments comprised just 20 episodes, and it is unclear whether that was sufficiently long for participants to demonstrate asymptotic behavior (e.g. Figure 5b). Either more participants or greater differences between conditions (e.g. testing 9:8, 12:5, and 15:2 conditions in a revised Experiment 1), as well as running a greater number of total episodes, would be needed to resolve this concern.

- The model is presented after the behavioral results, giving the impression that it was perhaps constructed to fit the data. No attempt is made to fit the model to a subset of the data and then validate the rest or give any clear indication as to how the model parameters were set. Moreover, as noted, even where the model is successful, it only explains the behavior of a minority of the total participants. No modeling work is done to explain the behavior of the other two-thirds of the participants.

- The authors helpfully discuss several meaningful alternative models of exploration, such as visit-counting and incorporating an objective function sensitive to information gain. They do not, however, compare their model against these or any other meaningful baselines. Moreover, the comparison between model and human participants is qualitative rather than quantitative. These issues could be resolved by introducing a more rigorous analysis quantitatively comparing a variety of theoretically relevant models as quantitative explanations of the human data.

Reviewer #2 (Public Review):

Summary:<br /> In this article, the authors develop an algorithm for exploration inspired by the classic, state-action-reward-state-action (SARSA) reinforcement learning algorithm. Designed to account for exploration in multi-state environments, this algorithm computes the expected discounted return from selecting an action in a state and uses that value to update the cached value of taking a given action in a given state. The value represents the uncertainty in a given state, and the backed-up value is computed from the discounted future return plus the immediate reduction in uncertainty regarding the state.

Strengths:<br /> The article is ambitious and seeks to characterize human exploration in a novel task using zero rewards. That characterization is useful.

Weaknesses:<br /> The paper suffers from many problems. Here, I will mention three. First, the algorithm is very poorly motivated-exploration is central to many behaviors, but the algorithm computes the value of exploration independent of any long-run considerations of exploitation. Second, the article attempts to recover the observed exploratory behavior in two different multi-state choice tasks. But the algorithm does not explain that behavior, and there is no performance metric on the model, nor a comparison to other models. Third, the article frames the algorithm in terms of uncertainty, but there is no measure of uncertainty.

In short, in many ways this manuscript is 'half an article', and the authors have much work to do. They could decide to dive into the convergence proofs and other theoretical properties of the model. However, as far as I understand the model, it is literally an optimistic SARSA, whose characteristics are well-understood. Or, they could compare the model's performance to a number of other exploration models (UCB, Thompson sampling, infomax, infotaxis-there are so many!). However the authors need to choose one or the other. I urge the authors to properly compare their model to other models.

1. Motivation<br /> The algorithm is poorly motivated. Exploration is valuable for a time but quickly becomes less valued as more is learned about the environment. The algorithm attempts to account for this by the ad hoc nature of the backup: the immediate outcome is -E(s,a), which represents a reduction in uncertainty. So in the long run, the exploratory value will decrease to zero. But this is ad hoc; why not add E(s,a)? In addition, exploration values are set to 1. But this is also ad hoc; why should E(s,a) start at 1? They have cherry-picked their starting values and the nature of the back-up to yield exploratory behavior.

2. Performance<br /> The authors wish to compare the model's performance to observed exploration behavior. However, their model does a poor job of explaining the behavior. What's confusing is that the authors note the ways the model deviates. There are two principal deviations. First, the model exhibits an exploratory transient, but it is too wide to match the humans. Second, the model fails to exhibit the low-level persistent exploration characteristic of humans in their task.

The next natural step would be to augment the model in different ways to attempt to describe the behavior. The authors do attempt to import td-λ aspects into their exploration model. They determine that importation fails to capture the observed behavior. But why stop there? Why not continue? Why not follow through and change the model in a way that can capture the dynamics of exploration?

In addition, a natural complement would be to compare the model's ability to describe human performance to other models. This would require model fitting, recovery, and validation. However the authors don't engage in that model fitting exercise.

They note that a model-based learning strategy could account for the speed of learning in humans. However they don't comment generally on how model-based strategies could explain their findings nor how they relate to their model. They should comment on this. In particular, the participants are likely learning a model of their environment, and this can be done using non-parametric Bayesian inference (along the lines of Gershman or Collins's work). The authors should model their task using these models and compare this to their algorithm.

The authors state that there was no reward. Were subjects paid for their time? Also, the lack of a reward is unusual, and even if unconsciously, participants may have been engaged in reward-seeking. The authors should try to model the behavior with a pseudo-reward to see how that accounts for their findings. This is especially true from the perspective of computational RL. On that theory, the only object 'in' the agent is the policy; everything else is considered 'in' the environment. This means that rewards in RL need not be from environmental returns but could also be from inside the organism (even if modeled as 'outside' the agent in the RL framework). So they need to model the behavior using 'pseudorewards' to see if that can account for their findings. Finally, though trivially, a reward of 0 is technically a reward, and the model's exploratory drive comes from settling on the true values of the states (i.e., 0).

3. Uncertainty<br /> The authors frame their model in terms of uncertainty, but their model does not measure uncertainty at all. The model makes choices on the basis of optimistic initial Q-values and then searches on that basis, backing up the 0 rewards until the true values are more or less hit upon. But that is not a measure of uncertainty in any sense; rather, it is an optimistic Q-value bias that drives exploration. However, I may simply fail to understand their model.

Reviewer #3 (Public Review):

Summary:<br /> In this article, Fox and colleagues describe the results of a novel and innovative task, coupled with a modified computational model, to explore pure directed exploration (not quite a pun, but intended nonetheless). In their task, participants make a series of discrete choices, importantly with no reward feedback, to navigate a nested series of rooms in a virtual environment. The initial 2-door choice is used as the primary probe and the complexity of the series of rooms behind each choice is used as the critical independent variable. The authors find that, as the number of follow-up options behind a door increases, "good" participants are more likely to choose the door that leads to the more complex choices. As the depth of the search increased (i.e. the room with the most doors was presented "farther" down the search), these same participants were less likely to choose the door leading to the more complex route. Finally, these same "good" participants showed an initial boost in preference towards the more complex exploration option after a few learning episodes that settled down after about 10 episodes, with a modest reliable preference towards the more complex route. This reflected the fact that information value decays over time in stable situations. Using an adaptation of standard Q-learning, with a proxy of information value being substituted for reward value, the authors show how their model can qualitatively capture most of the observed experimental effects, although with some critical differences in the temporal dynamics of learning, suggesting that the memory horizon for humans is longer than in the adapted Q-learning model.

Strengths:<br /> 1. Clever experimental design<br /> The novel task is really clever and gets around many of the limitations for understanding directed exploration that have plagued prior research (which typically involve some use of reward feedback). Finding a way to provide direct information that can be experimentally manipulated, without needing to provide any explicit reward feedback, makes this one of the few pure exploration tasks that I am aware of.

2. Compelling results<br /> The effect of manipulating choice complexity and depth on initial choice probability for "good" directed learners seems fairly strong, as do the learning dynamics. The heterogeneity in exploration style across participants is also interesting and brings up more questions that are useful for follow-up research.

3. Simple model<br /> The computational model used is a simple adaptation of standard reinforcement learning models, specifically Q-learning models. This is elegant as it doesn't require major changes in the dynamics of learning, simply a revision of the variables going into the update. The simplicity of this change, coupled with the ability to capture the results of the "good" directed explorers makes a strong case that information seeking and reward-seeking may share common underlying mechanisms (as shown previously by Kobayashi, K., & Hsu, M. (2019). Common neural code for reward and information value. Proceedings of the National Academy of Sciences, 116(26), 13061-13066.).

Weaknesses:

1. "Good" vs. "poor"<br /> There is an odd circularity, and implicit value judgment, in the classification of participants into "good" and "poor" directed explorers. The logic, based on the visit-counter model of directed exploration, is that the probability of repeating a choice (at the initial decision trial) should be low for directed explorers vs. random explorers. Doing the median split on repetition probability seems intuitively fine here, but it does bring up two issues. First, the labels "good" vs. "poor" seem arbitrarily judgemental, after all random exploration is a viable exploration strategy in many contexts. Would "directed" vs. "random" be more appropriate labels based on how the decision was made to categorize participants? Second, how much of the "good" participant performance is driven by the extreme non-repeaters? For example, if a tertiary split was performed instead of a binary median split, would the middle group show a weaker version of the effects seen in the "good" group or appear more like the "poor" group?

2. Characterization of information value<br /> The authors discuss primarily methods that can be summarized by visit counters as a description for all directed exploration models. However, that doesn't seem to be a good summary of the overall literature in this space. There are also entropy-based approaches, that quantify information value based on the statistics of the feedback. For example, in machine learning methods like the KL divergence are often used to represent the information value of a channel. A few such papers are highlighted below. Now it is entirely possible that these approaches can be extrapolated to simple visit-count approaches, but I am unaware of anything showing this. I think it would be good to broaden the discussion on directed exploration models beyond visit-counter methods like UCB, highlighting the other methods used to promote directed exploration.

Houthooft, R., Chen, X., Duan, Y., Schulman, J., De Turck, F., & Abbeel, P. (2016). Vime: Variational information maximizing exploration. Advances in neural information processing systems, 29.

Eysenbach, B., Gupta, A., Ibarz, J., & Levine, S. (2018). Diversity is all you need: Learning skills without a reward function. arXiv preprint arXiv:1802.06070.

Hazan, E., Kakade, S., Singh, K., & Van Soest, A. (2019, May). Provably efficient maximum entropy exploration. In International Conference on Machine Learning (pp. 2681-2691). PMLR.

3. Model vetting<br /> The model used to simulate the behavioral results is interesting and intuitive. However, there seem to be some things left on the table and unresolved. First, the definition of information value (E) that is maximized is assumed to satisfy the same constraints as typical reward does in the Bellman solution for reinforcement learning. This is the only way it can be substituted into the typical Q-learning method. Is that true here?

Second, the advantage of these simpler computational-level models is that they can be effectively fit to behavior. The model outlined in the paper has only a few free parameters (some of which can be fixed for convenience purposes). Was there an attempt to fit each participant's data into the model? This would be a powerful way of highlighting where exactly the differences between the "good" and "bad" participants arise.

Reviewer #2 (Public Review):

Summary: This work presented by Kudo and colleagues is of great importance to strengthen our understanding of electrophysiological changes in the course of AD. Although the main conclusions regarding functional connectivity and spectral power change through the course of the disease are not new and have been largely studied and theorised on, this article offers an innovative approach that certainly consolidates previous knowledge on the topic. Not only that, this article also broadens our knowledge presenting useful and important details on the specificity of frequency and cortical distribution of these early alterations. The main take-home message of this work is the early disruption of electrophysiological signatures that precedes detectable alterations in other more commonly used pathology markers (i.e. gray matter atrophy and cognitive impairment). More specifically, these signatures include long-range connectivity in the alpha and beta bands, and local synchrony (spectral power) in the same frequency bands.

Strengths: The present work has some major strengths that make it paramount for the advance of our understanding of AD electrophysiology. It is a very well written manuscript that, despite the complexity of the analyses employed, runs the reader through the different steps of the analysis in a pedagogic and clever way, making the points raised by the results easy to grasp. The methodology itself is carefully chosen and appropriate to the nature of the question posed by the researchers, as event-based models are well-suited for cross-sectional data.

The quality of the figures is outstanding; not only are they aesthetic but, more importantly, the figures convey information exceptionally well and facilitate comprehension of the main results.<br /> The conclusions of the paper are, in general, well described and discussed, and consider the state-of-the-art works of AD electrophysiology. Furthermore, even though the conclusions themselves are not groundbreaking at all (synaptic damage preceding structural and cognitive impairment is one of the epitomes of the pathological cascading model proposed by Jack in 2010), this article is innovative and groundbreaking in the way they address with clever analyses in a relatively large sample for neuroimaging standards.

Weaknesses: The main limitation of the work revolves around sample definition and inclusion criteria that are somewhat confusing obscuring some of the points of the analyses. Firstly it is not clear why the purely clinical approach is employed to diagnose the "probable Alzheimer´s Disease" for the 78 participants in the "AD group". In the same paragraph, it is stated that 67 out of the 78 participants show biomarker positivity, thus allowing a more biologically guided diagnosis that is preferred according to current NIA-AA criteria. This would avoid highly possible mixing of different subtypes of dementia etiologies. One might wonder, why would those 11 participants be included if we have strong indications that their symptoms are not due to AD? Furthermore, the real pathological status of the control group is somewhat questionable. The authors do not specify whether common AD biomarkers are available for this subgroup. In that case, it would have highly increased the clarity and interpretability of the results if this group was subdivided in a preclinical and completely healthy control group. This would be particularly interesting since a significant proportion of the control group is labeled as belonging to stages 2,3,4 (MCI) and even 5 (mild dementia). This raises the question of whether these participants are true healthy controls mislabeled by the EBM model, or actual cognitive controls with actual underlying AD pathology well identified by the model proposed. On this note, Figure 2 (C and D) and Figure 3 (C, G and K) show a cortical surface depicting the mean difference of each stage vs the control group, which again, is formed by subjects that can be included (and in fact, are included) in all of those stages, obscuring the meaning and interpretability of these cortical distributions.

Reviewer #1 (Public Review):

Summary:<br /> The authors aimed to infer the trajectories of long range and local neuronal synchrony across the Alzheimer's disease continuum, relative to neurodegeneration and cognitive decline. The trajectories are inferred using event-based models, which infer a set of data-driven disease stages from a given dataset. The authors develop an adapted event-based modelling approach, in which they characterise each stage as a particular biomarker increasing by a particular z-score deviation from controls. Fitting infers the optimal set of z-scores to use for each biomarker and the order in which each biomarker reaches each z-score. The authors apply this approach to data from 148 individuals (70 cognitively unimpaired older adults and 78 individual with mild cognitive impairment or Alzheimer's disease), identifying trajectories in which long-range (amplitude-envolope correlation) and local (regional spectral power) neuronal synchrony in the alpha and beta bands becomes abnormal prior to neurodegeneration (measured as the volume of the parahippocampal gyrus) and cognitive decline (measured using the mini-mental state examination).

Strengths:<br /> - The main strength is that the authors assess two models. In the first they derive a staging system based only on the volume of the parahippocampal gyrus and mini-mental state examination score. They then investigate how neuronal synchrony metrics change compared to this staging system. In the second they derive a staging system that also includes an average (combined long-range and local) neuronal synchrony metric and investigate how long-range and local synchrony metrics change relative to this staging system. This is a strength as the first model provides confidence that there is not overfitting to the neuronal synchrony data, and the second provides more detailed insights into the dynamics of the early neuronal synchrony changes.<br /> - Another strength is that the authors automatically infer the optimal z-scores to choose, rather than having to pre-select them manually, as in previous approaches.

Weaknesses:<br /> - The dataset is small and no external validation is performed.<br /> - A high proportion of the data is from controls (nearly 50%) with no biomarker evidence of Alzheimer's disease, and so the changes may be driven by aging or other non-Alzheimer's effects.<br /> - Inferring the optimal z-scores is a strength, however as different sets of z-scores are allowed per biomarker, there is a concern that the changes reflected are mainly driven by the choice of z-score, rather than the markers themselves (e.g. if lower z-scores are selected for one marker than another, then changes in that marker will appear to be detected earlier, even if both markers change at the same time).<br /> - In equation 2 it is unclear why the gaussian is measured based on a sum over I. The more obvious choice would be to use a multivariate gaussian with no covariance, which would mean taking the product rather than the sum over I.<br /> - In the original event-based model, k is a hidden variable. Presumably that is also the case here, however the notation k=stage(j) makes it seem like each subject is assigned a stage during the sequence optimisation.<br /> - Typically for event-based modelling, positional variance diagrams are created from the markov chain monte carlo samples of the event sequence, enabling visualisation of the uncertainty in the sequence, but these are not included in the study.<br /> - Many of the figures in the manuscript (e.g. Figure 1E/G, Figure 2A/B, Figure 3A/B/E/F/I/J, Figure 4 A/B/E/F/I/J) are based on averages in both the x and the y axis. In the x dimension, individuals have a weighted contribution to the value on the y axis, depending on their stage probability. In the y dimension, the values are averages across those individuals, and the error bars represent the standard error rather than the standard deviation. Whilst the trajectories themselves are interesting, they may not be discriminative at the individual level and may be more heterogeneous than it appears.<br /> - The bootstrapped statistical analyses comparing metrics between the stages do not consider the variability in the sequence.

Reviewer #3 (Public Review):

This study examines how the correlation structure of a perceptual decision-making task influences history biases in responding. By manipulating whether stimuli were more likely to be repetitive or alternating, they found evidence from both behavior and a neural signal of decision formation that history biases are flexibly adapted to the environment. On the whole, these findings are supported across an impressive range of detailed behavioral and neural analyses. The methods and data from this study will likely be of interest to cognitive neuroscience and psychology researchers. The results provide new insights into the mechanisms of perceptual decision-making.

The behavioral analyses are thorough and convincing, supported by a large number of experimental trials (~600 in each of 3 environmental contexts) in 38 participants. The psychometric curves provide clear evidence of adaptive history biases. The paper then goes on to model the effect of history biases at the single trial level, using an elegant cross-validation approach to perform model selection and fitting. The results support the idea that, with trial-by-trial accuracy feedback, the participants adjusted their history biases due to the previous stimulus category, depending on the task structure in a way that contributed to performance.

The paper then examines MEG signatures of decision formation, to try to identify neural signatures of these adaptive biases. Looking specifically at motor beta lateralization, they found no evidence that starting-level bias due to the previous trial differed depending on the task context. This suggests that the adaptive bias unfolds in the dynamic part of the decision process, rather than reflecting a starting level bias. This is supported by analysis of lateralization relative to the chosen hand as a proxy for a decision variable (DV), whose slope is shown to be influenced by these adaptive biases.

Reviewer #1 (Public Review):

This paper aims to study the effects of choice history on action-selective beta band signals in human MEG data during a sensory evidence accumulation task. It does so by placing participants in three different stochastic environments, where the outcome of each trial is either random, likely to repeat, or likely to alternate across trials. The authors provide good behavioural evidence that subjects have learnt these statistics (even though they are not explicitly told about them) and that they influence their decision-making, especially on the most difficult trials (low motion coherence). They then show that the primary effect of choice history on lateralised beta-band activity, which is well-established to be linked to evidence accumulation processes in decision-making, is on the slope of evidence accumulation rather than on the baseline level of lateralised beta.

The strengths of the paper are that it is: (i) very well analysed, with compelling evidence in support of its primary conclusions; (ii) a well-designed study, allowing the authors to investigate the effects of choice history in different stochastic environments.

There are no major weaknesses to the study. On the other hand, investigating the effects of choice/outcome history on evidence integration is a fairly well-established problem in the field. As such, I think that this provides a valuable contribution to the field, rather than being a landmark study that will transform our understanding of the problem.

The authors have achieved their primary aims and I think that the results support their main conclusions. One outstanding question in the analysis is the extent to which the source-reconstructed patches in Figure 2 are truly independent of one another (as often there is 'leakage' from one source location into another, and many of the different ROIs have quite similar overall patterns of synchronisation/desynchronisation.). A possible way to investigate this further would be to explore the correlation structure of the LCMV beamformer weights for these different patches, to ask how similar/dissimilar the spatial filters are for the different reconstructed patches.

The revised paper now states explicitly how source-reconstructed patches are indeed affected by leakage, but also why the focus of the authors on differences (rather than similarities) between patches leaves their findings and conclusions essentially unaffected by this intrinsic limitation of cortical source reconstruction from surface MEG data.

Reviewer #2 (Public Review):

In this work, the authors use computational modeling and human neurophysiology (MEG) to uncover behavioral and neural signatures of choice history biases during sequential perceptual decision-making. In line with previous work, they see neural signatures reflecting choice planning during perceptual evidence accumulation in motor-related regions, and further show that the rate of accumulation responds to structured, predictable environments suggesting that statistical learning of environment structure in decision-making can adaptively bias the rate of perceptual evidence accumulation via neural signatures of action planning. The data and evidence show subtle but clear effects, and are consistent with a large body of work on decision-making and action planning.

Overall, the authors achieved what they set out to do in this nice study, and the results, while somewhat subtle in places, support the main conclusions. This work will have an impact within the fields of decision-making and motor planning, linking statistical learning of structured sequential effects in sense data to evidence accumulation and action planning.

Strengths:

- The study is elegantly designed, and the methods are clear and generally state-of-the-art<br /> - The background leading up to the study is well described, and the study itself conjoins two bodies of work - the dynamics of action-planning processes during perceptual evidence accumulation, and the statistical learning of sequential structure in incoming sense data<br /> - Careful analyses effectively deal with potential confounds (e.g., baseline beta biases)

Weaknesses (after revision):

- The treatment of "awareness" of task structure is left as a somewhat open, potentially important question.

Reviewer #1 (Public Review):

In this study, the authors utilise different chemical inhibitors and celular markers to examine the roles of macropinocytosis in WNT signalling activation in development (Xenopus), cell culture (3T3 cells) and cancer (CRC sections). Furthermore, they investigate the effect of the inflammation inducer Phorbol-12-myristate-13-acetate (PMA) in WNT signalling activation through macropinocytosis. The authors show 1) that PMA induces macropinocytosis-dependent WNT signalling activation, and 2) that CRC development correlates with increased levels and co-localisation of macropinocytosis components and b-catenin.

I found the analyses and conclusions compelling. Additional epistatic analyses could be done in the future to further disentangle the roles of macropinocytosis during WNT signalling activation, especially upon oncogenic alterations (e.g. in APC). The studies on CRC samples open interesting questions for specialists in tumour progression.

Reviewer #2 (Public Review):

Tejeda Muñoz et al. investigate the intersection of Wnt signaling, macropinocytosis, lysosomes, focal adhesions and membrane trafficking in embryogenesis and cancer. Following up on their previous papers, the authors present evidence that PMA enhances Wnt signaling and embryonic patterning through macropinocytosis. Strikingly, PMA and Wnt ligand act synergistically to trigger macropinocytosis in fibroblasts. Proteins that are associated with the endo-lysosomal pathway and Wnt signaling are co-increased in colorectal cancer samples, consistent with their pro-tumorigenic action. The function of macropinocytosis is not well understood in most physiological contexts, and its role in Wnt signaling is intriguing. The authors use a wide range of models - Xenopus embryos, cancer cells in culture and in xenografts and patient samples to investigate several endolysosomal processes that appear to act upstream or downstream of Wnt. This broad approach has the downside that results are often validated only in a subset of biological systems and that experiments tend to lack of mechanistic depth. The connections between PMA, Wnt signaling, Rac stabilization, FAK signaling and macropinocytosis remain unclear. Nevertheless, the results provide intriguing insights into a novel connection of the tumor promoting agent PMA and Wnt signaling in development and cancer.

The authors demonstrate striking, additive effects of Wnt3a and PMA in inducing macropinocytosis in 3T3 cells (Fig. 1 K-P). In the APC-mutant colorectal cancer line SW480, the authors show that PMA treatment increases macropinocytosis (Fig. S1). While these data provide additional confirmation that PMA can trigger macropinocytosis, they do not address the role of Wnt signaling directly. This could be done by restoring APC function in SW480 cells, or by ectopically activating Wnt signaling in a CRC cell line that lacks activating mutations in the Wnt pathway. These experiments would help to strengthen the cancer angle and validate the connection between Wnt signaling and PMA in macropinocytosis induction in additional cell lines.

The authors conclude that PMA enhances Wnt signaling based on experiments in Xenopus embryos where co-treatment with PMA and the Wnt activator LiCl increases Wnt target gene expression. This is an interesting observation, but large parts of the paper focus on mammalian cells / cancer cells. It would be important to demonstrate the ability of PMA to enhance Wnt signaling in these contexts as well.

Reviewer #3 (Public Review):

In this improved version of the manuscript, Chang et al set out to find direct interactions with the Eph-B2 receptor, as our knowledge of its function/regulation is still incomplete. Using proteomic analysis of Hela cells expressing EPHB2, they identified MYCBP2 a potential binder, which they then confirm using extensive biochemical analyses, an interaction that seems to be negatively affected by binding of ephrin-B2 (but not B1). Furthermore, they find that FBXO45, a known MYCBP2 interaction, strongly facilitates its binding to EPHB2. Intriguingly, these interactions depend on the extracellular domains of EPHB2, suggesting the involvement of additional proteins as MYCBP2 is thought to be a cytoplasmic protein. Finally, they find that, in contrast to what could be expected given the known function of MYCBP2 as a ubiquitin E3 ligase, it actually positively regulates EPHB2 protein stability, and function.

The strength of this manuscript is the extensive biochemical analysis of the EPHB2/MYCBP2/FBXO43 interactions. The vast majority of the conclusions supported by the data.

The attempt to extend the study to an in vivo animal using the worm is important, however the additive insight is, unfortunately, minimal.

Reviewer #1 (Public Review):

The Eph receptor tyrosine kinase family plays a critical function in multiple physiological and pathophysiological processes. Hence, understating the regulation of these receptors is highly important question. Through extensive experiments in cell lines and cultured neurons Chang et.al show that the signaling hub protein, MYCBP2 positively regulates the overall stability of a specific member of the family, EPHB2, and by that the cellular response to ephrinBs.<br /> Overall, this work sheds light on the divergent in the regulatory mechanisms of the Eph receptors family. Although the physiological importance of this new regularly mechanism in mammals awaits to be discovered, the authors provide genetic evidence using C.elegans that it is evolutionarily conserved.

Reviewer #2 (Public Review):

Members of the EphB family of tyrosine kinase receptors are involved in a multitude of diverse cellular functions, ranging from the control of axon growth to angiogenesis and synaptic plasticity. In order to provide these diverse functions, it is expected that these receptors interact in a cell-type specific manner with a diverse variety of downstream signalling molecules.

The authors have used proteomics approaches to characterise some of these molecules in further detail. This molecule, myc-binding protein 2 (MYCBP2) is also known as highwire, has been identified in the context of establishment of neural connectivity. Another molecule coming up on this screen was identified as FBXO45.

The authors use classical methods of co-IP to show a kinase-independent binding of MYCBP2 to EphB2. They further showed that FBXO45 within a ternary complex increased the stability of the EphB2/MYCBP2 complex.

To define the interacting domains, they used clearly designed swapping experiments to show that the extracellular and transmembrane domains are necessary and sufficient for the formation of the ternary complex.

Using a cellular contraction assay, the authors showed the necessity of MYCBP2 in mediating the cytoskeletal response of EphB2 forward signalling. Furthermore, they used the technically challenging stripe assay of alternating lanes of ephrinB-Fc and Fc to show that also in this migration-based essay MYCBP2 is required for EphB mediated differential migration pattern.

MYCBP2 in addition is necessary to stabilize EphB2, that is in the absence of MYCBP2, EphB2 is degraded in the lysosomal pathway.

Interestingly, the third protein in this complex, Fbxo45, was further characterized by overexpression of the domain of MYCBP2, known to interact with Fbxo45. Here the authors showed that this approach led to the disruption of the EphB2 / MYCBP2 complex, and also abolished the ephrinB mediated activation of EphB2 receptors and their differential outgrowth on ephrinB2-Fc / Fc stripes.

Finally, the authors demonstrated an in vivo function of this complex using another model system, C elegans where they were able to show a genetic interaction.

Data show in a nice set of experiments a novel level of EphB2 forward signalling where a ternary complex of this receptor with multifunctional MYCBP2 and Fbxo45 controls the activity of EphB2, allowing a further complex regulation of this important receptors. Additionally, the authors challenge pre-existing concepts of the function of MYCBP2 which might open up novel ways to think about this protein.<br /> Of interest is this work also in terms of development of the retinotectal projection in zebrafish where MYCBP2/highwire plays a crucial role, and thus might lead to a better understanding of patterning along the DV axis, for which it is known that EphB family members are crucial.

Overall, the experiments are classical experiments of co-immunoprecipitations, swapping experiments, collapse assays, and stripe assays which all are well carried out and are convincing.

Reviewer #1 (Public Review):

Summary:<br /> Ngoune et al. present compelling evidence that Slender cells are challenged to infect tsetse flies. They explore the experimental context of a recent important paper in the field, Schuster et al., that presents evidence suggesting the proliferative Slender bloodstream T.brucei can infect juvenile tsetse flies. Schuster et al. were disruptive to the widely accepted paradigm that the Stumpy bloodstream-form is solely responsible for tsetse infection and T.brucei transmission potential.

Evidence presented here shows that in all cases, Stumpy form parasites are exponentially more capable of infecting tsetse flies. They further show that Slender cells do not infect mature flies.

However, they raise questions of immature tsetse immunological potential and field transmission potential that their experiments do not address. Specifically, they do not show that teneral tsetse flies are immunocompromised, that tsetse flies must be immunocompromised for Slender infection nor that younger teneral tsetse infection is not pertinent to field transmission.

Strengths:<br /> Experimental Design is precise and elegant, outcomes are convincing. Discussion is compelling and important to the field. This is a timely piece that adds important data to a critical discussion of host: parasite interactions, of relevance to all parasite transmission.

Weaknesses:<br /> As above, the authors dispute the biological relevance of teneral tsetse infection in the wild, without offering evidence to the contrary. Statements need to be softened for claims regarding immunological competence or relevance to field transmission.

Reviewer #2 (Public Review):

Summary:<br /> Contrary to findings recently reported by Schuster S et al., this short paper shows evidence that the stumpy form of T. brucei is probably the most pre-adapted form to progress with the life cycle of this parasite in the tsetse vector.

Strengths:<br /> One of the most important pieces of experimental evidence is that they conduct all fly infection experiments in the absence of metabolites like GlcNAc or S-glutathione; by doing so, the infection rates in flies infected with slender trypanosomes seem very low or nonexistent. This, on its own, is a piece of important experimental evidence that the Schuster S et al findings may need to be revisited.

Weaknesses:<br /> I consider that the authors should have included their own experiments demonstrating that the addition of these chemicals enhances the infection rates in flies receiving bloodmeals containing slender trypanosomes.

Reviewer #3 (Public Review):

The dogma in the Trypanosome field is that transmission by Tsetse flies is ensured by stumpy forms. This has been recently challenged by the Engstler lab (Schuster et al. ), which showed that slender forms can also be transmitted by teneral flies. In this work, the authors aimed to test whether transmission by slender forms is possible and frequent.

For this, the authors repeated Tsetse transmission experiments but with some key critical differences relative to Schuster et al. First, they infected teneral and adult flies. Second, their infective meals lacked two components (N-acetylglucosamine and glutathione), which could have boosted the infection rates in the Schuster et al. work. In these conditions, the authors observed that most stumpy form infections with teneral and adult flies were successful while only 1 out of 24 slender-form infections was successful. Adult flies showed a lower infection rate, which is probably because their immune system is more developed.

Given that in Tsetse-infested areas most transmission is likely ensured by adult flies, the authors conclude that the parasite stage that will have a significant epidemiologic impact on transmission is the stumpy form.

Strengths:<br /> • This work tackles an important question in the field.<br /> • The Rotureau laboratory has well-known expertise in Tsetse fly transmission experiments.<br /> • Experimental setup is robust and data is solid.<br /> • The paper is concise and clearly written.

Weaknesses:<br /> • The reason(s) for why this work has lower infection rates with slender forms than Schuster et al. remain unknown. The authors suggested it could be because of the absence of N-acetylglucosamine and/or glutathione, but this was not formally tested. Could another source of variation be the clone of EATRO1125 AnTat1.1 (Paris versus Munich origin)? To reduce the workload, such additional experiments could be done with just one dose of parasites.<br /> • The characterization of what is slender and stumpy is critical. The authors used PAD1 protein expression as the sole reporter. While this is a robust assay to confirm stumpy, an analysis of the cell cycle would have been helpful to confirm that slender forms have not initiated differentiation (Larcombe S et al. 2023, preprint).<br /> • Statistical analysis is missing. Is the difference between adult and teneral infections statistically significant?

Reviewer #1 (Public Review):

DeKraker et al. propose a new method for hippocampal registration using a novel surface-based approach that preserves the topology of the curvature of the hippocampus and boundaries of hippocampal subfields. The surface-based registration method proved to be more precise and resulted in better alignment compared to traditional volumetric-based registration. Moreover, the authors demonstrated that this method can be performed across image modalities by testing the method with seven different histological samples. This work has the potential to be a powerful new registration technique that can enable precise hippocampal registration and alignment across subjects, datasets, and image modalities.

Reviewer #2 (Public Review):

Summary:

In the current manuscript, Dekraker and colleagues have demonstrated the ability to align hippocampal subfield parcellations across disparate 3D histology samples that differ in contrast, resolution, and processing/staining methods. In doing so, they validated the previously generated Big-Brain atlas by comparing across seven different ground-truth subfield definitions. This is an impressive effort that provides important groundwork for future in vivo multi-atlas methods.

Strengths:

DeKraker and colleagues have provided novel evidence for the tremendously complicated curvature/gyrification of the hippocampus. This work underscores the challenge that this complicated anatomy presents in our ability to co-register other types of hippocampal data (e.g. MRI data) to appropriately align and study a structure in which the curvature varies considerably across individuals.

This paper is also important in that it highlights the utility of using post-mortem histological datasets, where ground truth histology is available, to inform our rigorous study of the in vivo brain.

This work may encourage readers to consider the limitations of the current methods that they currently use to co-register and normalize their MRI data and to question whether these methods are adequate for the examination of subfield activity, microstructure, or perfusion in the hippocampal head, for example. Thus the implications of this work could have a broad impact on the study of hippocampal subfield function in humans.

Weaknesses:

As the authors are well aware, hippocampal subfield definitions vary considerably across laboratories. For example, some neuroanatomists (Ding, Palomero-Gallagher, Augustinack) recognize that the prosubiculum is a distinct region from subiculum and CA1 but others (e.g. Insausti, Duvernoy) do not include this as a distinct subregion. Readers should be aware that there is no universal consensus about the definition of certain subfields and that there is still disagreement about some of the boundaries even among the agreed upon regions.

Reviewer #1 (Public Review):

Summary:<br /> Van der Heijden et al perform an ambitious analysis of single-unit activity in the interposed nuclei of multiple mouse models of cerebellar dysfunction. Based on these recordings, they develop a classifier to predict the behavioral phenotype (ataxic, dystonic, or tremor) of each model, suggesting that highly regular spiking is associated with ataxia, irregular spiking is associated with dystonia and rhythmic spiking is associated with tremor. After developing this classifier, they show that activating Purkinje neurons in different patterns that evoke interposed nuclear activity similar to their "ataxic", "dystonic", and "tremor" firing patterns induce similar behaviors in healthy mice. These results show convincingly that specific patterns of cerebellar output are sufficient to cause specific movement abnormalities. The extent to which cerebellar nuclear firing patterns are solely responsible for phenotypes in human disease remains to be established, however.

Strengths:<br /> Major strengths are the recordings across multiple phenotypic models including genetic and pharmacologic manipulations, and the robust phenotypes elicited by Purkinje neuron stimulation.

Weaknesses:<br /> The number of units recorded was small for each model (on the order of 20), limiting the conclusions that can be drawn from the recording/classifier experiments.

Reviewer #2 (Public Review):

Cerebellar diseases can manifest as various behavioral phenotypes, such as ataxia, dystonia, and tremor. In this study, Heijden and colleagues aim to understand whether these differing behavioral phenotypes are associated with disease-specific changes in the firing patterns of cerebellar output neurons in the cerebellar nuclei (CN). The authors effectively demonstrate that across different mouse models of cerebellar disease, there are distinct changes in the firing properties of CN neurons. They take a crucial step further by attempting to replicate disease-specific firing patterns in the cerebellar output neurons of healthy (control) mice using optogenetics. When Purkinje cells are stimulated in a manner that results in similar firing properties in CN neurons, the authors observe a variety of atypical behavioral responses, many of which align with the behavioral phenotypes observed in mouse models of the respective diseases.

Overall, the primary results are quite convincing. Specifically, they show that (1) different mouse models of cerebellar disease exhibit different statistics of firing in CN neurons, and (2) driving CN neurons in a time-varying manner that mimics the statistics measured in disease models results in behavioral phenomena reminiscent of the disease states. These findings suggest that aberrant activity in the CN can originate from various sources (e.g., developmental circuit deficits, abnormal plasticity, insult), but ultimately, these changes are funneled through the CN neurons, whose firing rates are affected, and this, in turn, drives aberrant behavior. This is a noteworthy observation that underscores the potential of targeting these output neurons in the treatment of cerebellar disease. Moreover, this manuscript provides valuable insights into the firing patterns associated with the most common cerebellar-dependent disease phenotypes.

However, the paper falls short in terms of the classifier model itself. The current implementation of this classifier appears to be rather weak. For instance, the cross-validated performance on the same disease line mouse model for tremor is only 56%. While I understand that the classifier aims to simplify a high-dimensional dataset into a more manageable decision tree, its rather poor performance undermines the authors' main objectives. In a similar vein, although focusing on three primary features of spiking statistics identified by the decision tree model (CV, CV2, and median ISI) is useful for understanding the primary differences between the firing statistics of different mouse models, it results in an overly simplistic view of this complex data. The classifier and its reliance on the reduced feature set are the weakest points of the paper and could benefit from further analysis and a different classification architecture. Nevertheless, it is commendable that the authors have collected high-quality data to validate their classifier. Particularly impressive is their inclusion of data from multiple mouse models of ataxia, dystonia, and tremor, enabling a true test of the classifier's generalizability.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript looks at the single-cell spike signatures taken from in vivo cerebellar nuclear neurons from awake mice suffering from 3 distinct diseases and uses a sophisticated classifier model to predict disease based on a number of different parameters about the spiking patterns, rather than just one or two. Single read-outs of spike firing patterns did not show significant differences between all 4 groups meaning that you need to analyze multiple parameters of the spike trains to get this information. The results are really satisfying and intriguing, with some diseases separating very well, and others having more overlap. It also represents a significant advancement for the rigor and creativity used for analyzing cerebellar output spike patterns. I really like this paper, it's a clever idea and has been done very well.

The authors examine multiple distinct forms of different diseases, including different types of ataxia, dystonia, and tremor. While some of the interpretation of this work remains unclear to this reviewer (in particular Figure 2, with ataxia models), I applaud the rigor and sharing of complex data that is not always straightforward to understand.

Strengths:<br /> The work is technically impressive and the analysis pushes the envelope of how cerebellar dysfunction is classified, which makes it an important paper for the field. It's well written. The approach it is taking is clever. The analysis is thorough, and the authors examine a wide array of different disease models, which is time-consuming, costly, and very challenging to do. It's a very strong manuscript.

Weaknesses:<br /> Weaknesses are few and quite minor. Some rewriting could be done to make certain sections clearer.

Joint Public Review:

Summary<br /> This is a very meticulous and precise anatomical description of the external sensory organs (sensillia) in Drosophila larvae. Extending on their previous study (Rist and Thum 2017) that analyzed the anatomy of the terminal organ, a major external taste organ of fruit fly larva, the authors examined the anatomy of the remaining head sensory organs - the dorsal organ, the ventral organ, and the labial organ-also described the sensory organs of the thoracic and abdominal segments. Improved serial electron microscopy and digital modeling are used to the fullest to provide a definitive and clear picture of the sensory organs, the sensillia, and adjacent ganglia, providing an integral and accurate map, which is dearly needed in the field. The authors revise all the data for the abdominal and thoracic segments and describe in detail, for the first time, the head and tail segments and construct a complete structural and neuronal map of the external larval sensilla.

Strengths<br /> It is a very thorough anatomical description of the external sensory organs of the genetically amenable fruitfly. This study represents a very useful tool for the research community that will definitely use it as a reference paper. In addition to the classification and nomenclature of the different types of sensilla throughout the larval body, the wealth of data presented here will be valuable to the scientific community. It will allow for investigating sensory processing in depth. Serial electron microscopy and digital modeling are used to the fullest to provide a comprehensive, definitive, and clear picture of the sensory organs. The discussion places the anatomical data into a functional and developmental frame. The study offers fundamental anatomical insights, which will be helpful for future functional studies and to understand the sensory strategies of Drosophila larvae in response to the external environment. By analyzing different larval stages (L1 and L3), this work offers some insights into the developmental aspects of the larval sense organs and their corresponding sensory cells.

Weaknesses<br /> There are no apparent weaknesses, although it is not a complete novel anatomical study. It revisits many data that already existed, adding new information. However, the repetitiveness of some data and prior studies may be avoided for easy readability.

Reviewer #1 (Public Review):

In this manuscript, Lee et al. compared encoding of odor identity and value by calcium signaling from neurons in the ventral pallidum (VP) in comparison to D1 and D2 neurons in the olfactory tubercle (OT).

Strengths: They utilize a strong comparative approach, which allows the comparison of signals in two directly connected regions. First, they demonstrate that both D1 and D2 OT neurons project strongly to the VP, but not the VTA or other examined regions, in contrast to accumbal D1 neurons which project strongly to the VTA as well as the VP. They examine single unit calcium activity in a robust olfactory cue conditioning paradigm that allows them to differentiate encoding of olfactory identity versus value, by incorporating two different sucrose, neutral and air puff cues with different chemical characteristics. They then use multiple analytical approaches to demonstrate strong, low-dimensional encoding of cue value in the VP, and more robust, high-dimensional encoding of odor identity by both D1 and D2 OT neurons, though D1 OT neurons are still somewhat modulated by reward contingency/value. Finally, they utilize a modified conditioning paradigm that dissociates reward probability and lick vigor to demonstrate that VP encoding of cue value is not dependent on encoding of lick vigor during sucrose cues, and that separable populations of VP neurons encode cue value/sucrose probability and lick vigor.

Weaknesses: The conclusions of the data are mostly well supported by the analyses, but the statistical analysis is somewhat limited and needs to be clarified and extended.

1) The manuscript includes limited direct statistical comparison of the neural populations, and many of the comparisons between the subregions are descriptive, including descriptions of the percentage of neurons having specific response types, or differences in effect sizes or differing "levels" of significance. An additional direct comparison of data from each subpopulation would help to confirm whether the differences reported are statistically meaningful.

2) When hypothesis tests are conducted between the neural populations, it is not clear whether the authors have accounted for the random effect of the subject, or whether individual units were treated as fully independent. For instance, pairwise differences are reported in Figures 4I, 5G/I/L, and others, but the statistical methods are unclear. Assessment of the statistics is further limited by the lack of reporting of degrees of freedom.

Reviewer #2 (Public Review):

Summary:<br /> This work is interesting since the authors provide an in vivo analysis into how odor-associations may change as represented at the level of olfactory tubercle (presynaptic) and next at the level of the ventral pallidum (postsynaptic). First the authors start-off with a seemingly careful characterization of the anterograde and retrograde connectivity of dopamine 1 receptor (D1) and dopamine 2 receptor (D2) expressing medium spiny neurons in the olfactory tubercle and neurons in the ventral pallidum. From this work they claim that regardless of D1 or D2 expression, tubercle neurons mainly project to the lateral portion of the ventral pallidum. Next, to compare how odor-associated neuronal activity in the ventral pallidum and the olfactory tubercle (D1 vs D2 MSNs) transforms across association learning, the authors performed 2-photon calcium imaging while mice engaged in a lick / no-lick task wherein two odors are associated with reward, two odors are associated with no outcome, and two odors are associated with an air puff.

This manuscript builds off of prior work by several groups indicating that the olfactory tubercle neurons form flexible learned associations to odors by looking at outputs into the pallidum (but without looking specifically at palladial neurons that truly get input from tubercle I should highlight) and with that, this work is novel. We appreciated the use of a straight-forward odor-outcome behavioral paradigm and the careful computational methods and analyses utilized to disentangle the contributions of single neurons vs population level responses to behavior. With one exception from the Murthy lab, 2P imaging in the tubercle is a new frontier and that is appreciated - as is the 2P imaging in the pallidum which was well-supported by the histology. The anatomical work is also well presented.

Overall the approach and methods are superb. The issues come when considering how the authors present the story and what conclusions are made from these data. Several key points before going into specifics about each are: 1) The authors can not conclude that their results are contradictory to prior results, 2) The authors over-interpret the results and do not discuss several key methodological issues. We were concerned with the ability to make strong claims regarding the circuitry presented, especially given how much the presented claims contradict prior work. There were also issues with the interpretability of neuronal encoding of value vs valence based on the present behavior (in which a distinction between the air puff and neutral trial types was not clear) and the imaging methodology (in which the neuronal populations analyzed were not clearly defined). In addition to toning down and rectifying some of the language and interpretations, we suggest including a study limitations section where these methodological and interpretation issues are discussed. Over-interpreting and playing up the significance of this work is unnecessary. Readers should be given a sufficiently detailed and nuanced presentation of these thought-provoking results, and from there allowed to interpret the results as they want.

Strengths:<br /> State-of-the-art approaches (as detailed above)

Possible conceptual innovation in terms of looking into output from the olfactory tubercle which has yet to be investigated in this avenue.

Weaknesses:<br /> On the first point regarding the authors repeated and unsupported claims that their results are contradictory. There are papers by numerous groups, in respected journals including this one, all together which used 5 different methods (cfos, photometry, 2P, units, fMRI), in animals ranging from humans to mice, which support that tubercle neurons reflect the emotional association of an odor, whether spontaneous or learned. With that, it is on the authors to not claim that their results contradict as if the other papers are suspect, but instead, from our standpoint it is on the authors to explain how and why their results differ from these other papers versus just simply saying they found something different [which at present is framed in a way that is 'correct' due to primacy if nothing else].

Second, onto the points of interpretation of results, there are several specific areas where this should be rectified. As is, the authors overinterpret their results and draw too far-reaching conclusions. This needs to be corrected.

In particular, the claims that D1 and D2 neurons of the olfactory tubercle nearly exclusively send projections to the ventral pallidum must be interpreted with caution given that the authors injected an anterograde AAV into the anteromedial olfactory tubercle, and did not examine the projections from either the posterior or lateral portions of the olfactory tubercle. This is especially significant since the retrograde tracing performed from the ventral pallidum indicates that the lateral olfactory tubercle, not the medial olfactory tubercle, primarily projects to the ventral pallidum (Fig 1D-F), however this may be due to leakage into the nucleus accumbens, as seen in the supplementary figure, S1G. The same caution must be advised when interpreting the retrograde tracing performed in Fig 1G-I, since the neuronal tracer used and the laterality and rostral-caudal injection site within the VTA could result in different projection patterns and under- or over-labelling. Additionally, the metric used, %Fiber Density (Figure 1C), as in the percentage of 16-bit pixels within the region of interest with an intensity greater than 200, is semi-quantitative, and is more applicable for examining axonal fibers that pass through a region rather than the synaptic terminals (like with a synaptophysin fusion protein-based tracing paradigm) found within a region (puncta). The statements made in contrast to prior studies should therefore be softened, and these concerns should be addressed in the introduction, discussion, and the limitations section if added.

The other major concern is whether the behavioral data generated is indicative of the full spectrum of valence. The authors appropriately state that the mice "perceive" the air puff, yet based on their data the mice did not clearly experience the puff-associated odor as emotionally aversive (viz., negative valence). The way the authors describe these results, it seems they agree with this. With that, the authors can't say the puff is aversive without data to show such - that is an assumption which, while seemingly intuitive, is not supported by the data unfortunately. To elaborate more since this is important to the messaging of the paper: The authors utilized a simple behavioral design, wherein two molecular classes of odors were included in either a sucrose rewarded, neutral no outcome, or air puff punished trial type. The odor-outcome pairs were switched after three days, allowing the authors to compare neuronal responses on the basis of odor identity and the later associated outcome. While the mice showed clear learning of the rewarded trial types by an increase in anticipatory licking during the odor, they did not show any significant changes in behavior that indicated learning of the air puff trial type (change in running velocity or % maximal eye size), especially in contrast to the neutral trial type. This brings up the concern that either the odor-air puff aversive associations (to odors) were not learned, or that the neutral trial types, in which a reward was omitted, were just as aversive as the air puff to the rear, despite the lack of startle response - perhaps due to stimulus generalization between neutral and air puff odor. The possibility of lack of learning is addressed in the paragraph starting at line 578, but does not account for the possibility that the lack of reward is also sufficiently punishing. The authors also address the possibility that laterality in the VP contributed to the lack of neural responsivity observed, but should also include a statement regarding laterality in the olfactory tubercle, as described in https://doi.org/10.7554/eLife.25423 and https://doi.org/10.1523/JNEUROSCI.0073-15.2015, since the effects of modulating the lateral portion of the olfactory tubercle are not yet reported. Lastly, use of the term "reward processing" should be avoided/omitted since the authors did not specifically study the processing of reinforcers.

Also, I would appreciate justification of the term "value". How specifically does the assay used assess value versus a more simplistic learned association which influences perceived hedonics or valence of the odors.

More information is needed regarding how neurons are identified day-to-day, both in textual additions to the Methods and also in terms of elaborating more in the results and/or figure legends about what neurons are included:<br /> a) The ROI maps for identifying/indicating cells in the FOVs are nice to see and at the same time raise some concerns about how cells are identified and/or borders for those specific ROIs drawn. For instance, Figure 4, A & D, ROI #13 (cell #13) between those two panels is VERY different in shape/size. Also see ROIs 15 and 4. Why was an ROI map not made on day 1 and then that same map applied and registered to frames from consecutive imaging days in that same mouse? As it is new ROIs are drawn, smaller for some "cells" and larger for others. And at least in ROI #13 above, one ROI is about twice as large as the other. This inconsistency in the work flow and definition of the ROIs is needing to be addressed in Methods. Also, the authors should address if and how this could possibly impact their results.<br /> b) Also, more details are needed in results and/or figure legends regarding the changes in cell numbers over days that are directly compared in the results. Some days there are 10% or more or less cells. Why? It is not the same population being compared in this case and so some Discussion of this is needed.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript describes a study of the olfactory tubercle in the context of reward representation in the brain. The authors do so by studying the responses of OT neurons to odors with various reward contingencies and compare systematically to the ventral pallidum. Through careful tracing, they present convincing anatomical evidence that the projection from the olfactory tubercle is restricted to the lateral portion of the ventral pallidum.

Using a clever behavioral paradigm, the authors then investigate how D1 receptor- vs. D2 receptor-expressing neurons of the OT respond to odors as mice learn different contingencies. The authors find that, while the D1-expressing OT neurons are modulated marginally more by the rewarded odor than the D2-expressing OT neurons as mice learn the contingencies, this modulation is significantly less than is observed for the ventral pallidum. In addition, neither of the OT neuron classes shows significant modulation by the reward itself. In contrast, the OT neurons contained information that could distinguish odor identities. These observations have led the authors to conclude that the primary feature represented in the OT is not reward.

Strengths:<br /> The highly localized projection pattern from olfactory tubercle to ventral pallidum is a valuable finding and suggests that studying this connection may give unique insights into the transformation of odor by reward association.

Comparison of olfactory tubercle vs. ventral pallidum is a good strategy to further clarify the olfactory tubercle's position in value representation in the brain.

Weaknesses:

The authors' interpretation of the physiologic results - that a novel framework is needed to interpret the OT's role - requires more careful treatment.

Reviewer #2 (Public Review):

The authors applied two visual working memory tasks, a memory-guided localization (MGL), examining short-term memory of the location of an item over a brief interval, and an N-back task, examining orientation of a centrally presented item, in order to test working memory performance in patients with multiple sclerosis (including a subgroup with relapsing-remitting and one with secondary progressive MS), compared with healthy control subjects. The authors used an approach in testing and statistically modelling visual working memory paradigm previously developed by Paul Bays, Masud Husain and colleagues. Such continuous measure approaches make it possible to quantify the precision, or resolution, of working memory, as opposed to measuring working memory using discretised, all-or-none measures. This represents an advance beyond prior work in this area.

The authors of the present study found that both MS subgroups performed worse than controls on the N-back task and that only the secondary progressive MS subgroup was significantly impaired on the MGL task. The underlying sources of error including incorrect association of an object's identity with its location or serial order, were also examined.

The application of more precise psychophysiological methods to test visual working memory in multiple sclerosis should be applauded. It has the potential to lead to more sensitive and specific tests which could potentially be used as useful outcome measures in clinical trials of disease-modifying drugs, for example.

The present study does not compare the continuous-report testing with a discrete measure task so it is unclear whether the former is more sensitive, or more feasible in this patient group, although this may not have been the purpose of the study.

Comments on the revised submission: My previous comments have been answered to the extent that is possible with the data available.

Reviewer #1 (Public Review):

This study compares visuospatial working (VWM) memory performance between patients with MS and healthy controls, assessed using analog report tasks that provide continuous measures of recall error. The aim is to advance on previous studies of VWM in MS that have used binary (correct/incorrect) measures of recall, such as from change detection tasks, that are not sensitive to the resolution with which features can be recalled, and to use mixture modelling to disentangle different contributions to overall performance. The results identify a specific decrease in the precision of VWM recall in MS, although the possibility that visual and/or motor impairments contribute to performance decrements on the memory task cannot be ruled out.

Reviewer #1 (Public Review):

Summary:<br /> Ever-improving techniques allow the detailed capture of brain morphology and function to the point where individual brain anatomy becomes an important factor. This study investigated detailed sulcal morphology in the parieto-occipital junction. Using cutting-edge methods, it provides important insights into local anatomy, individual variability, and local brain function. The presented work advances the field and will stimulate future research into this important area.

Strengths:<br /> Detailed, very thorough methodology. Multiple raters mapped detailed sulci in a large cohort. The identified sulcal features and their functional and behavioural relevance are then studied using various complementary methods. The results provide compelling evidence for the importance of the described sulcal features and their proposed relationship to cortical brain function.

Weaknesses:<br /> A detailed description/depiction of the various sulcal patterns is missing. A possible relationship between sucal morphology and individual demographics might provide more insight into anatomical variability. The unique dataset offers to opportunity to provide insights into laterality effects that should be explored.

Reviewer #2 (Public Review):

Summary: After manually labelling 144 human adult hemispheres in the lateral parieto-occipital junction (LPOJ), the authors 1) propose a nomenclature for 4 previously unnamed highly variable sulci located between the temporal and parietal or occipital lobes, 2) focus on one of these newly named sulci, namely the ventral supralateral occipital sulcus (slocs-v) and compare it to neighbouring sulci to demonstrate its specificity (in terms of depth, surface area, gray matter thickness, myelination, and connectivity), 3) relate the morphology of a subgroup of sulci from the region including the slocs-v to the performance in a spatial orientation task, demonstrating behavioural and morphological specificity. In addition to these results, the authors propose an extended reflection on the relationship between these newly named landmarks and previous anatomical studies, a reflection about the slocs-v related to functional and cytoarchitectonic parcellations as well as anatomic connectivity and an insight about potential anatomical mechanisms relating sulcation and behaviour.

Strengths:<br /> - To my knowledge, this is the first study addressing the variable tertiary sulci located between the superior temporal sulcus (STS) and intra-parietal sulcus (IPS).<br /> - This is a very comprehensive study addressing altogether anatomical, architectural, functional and cognitive aspects.<br /> - The definition of highly variable yet highly reproducible sulci such as the slocs-v feeds the community with new anatomo-functional landmarks (which is emphasized by the provision of a probability map in supp. mat., which in my opinion should be proposed in the main body).<br /> - The comparison of different features between the slocs-v and similar sulci is useful to demonstrate their difference.<br /> - The detailed comparison of the present study with state of the art contextualises and strengthens the novel findings.<br /> - The functional study complements the anatomical description and points towards cognitive specificity related to a subset of sulci from the LPOJ<br /> - The discussion offers a proposition of theoretical interpretation of the findings<br /> - The data and code are mostly available online (raw data made available upon request).

Weaknesses:<br /> - While three independent raters labelled all hemispheres, one single expert finalized the decision. Because no information is reported on the inter-rater variability, this somehow equates to a single expert labelling the whole cohort, which could result in biased labellings and therefore affect the reproducibility of the new labels.<br /> - 3 out of the 4 newly labelled sulci are only described in the very first part and never reused. This should be emphasized as it is far from obvious at first glance of the article.<br /> - The tone of the article suggests a discovery of these 4 sulci when some of them have already been reported (as rightfully highlighted in the article), though not named nor studied specifically. This is slightly misleading as I interpret the first part of the article as a proposition of nomenclature rather than a discovery of sulci.<br /> - The article never mentions the concept of merging of sulcal elements and the potential effect it could have on the labelling of the newly named variable sulci.<br /> - The definition of the new sulci is solely based on their localization relative to other sulci which are themselves variable (e.g. the 3rd branch of the STS can show different locations and different orientation, potentially affecting the definition of the slocs-v). This is not addressed in the discussion.<br /> - The new sulci are only defined in terms of localization relative to other sulci, and no other property is described (general length, depth, orientation, shape...), making it hard for a new observer to take labelling decisions in case of conflict.<br /> - The very assertive tone of the article conveys the idea that these sulci are identifiable certainly in most cases, when by definition these highly variable tertiary sulci are sometimes very difficult to take decisions on.<br /> - I am not absolutely convinced with the labelling proposed of a previously reported sulcus, namely the posterior intermediate parietal sulcus.

Assuming that the labelling of all sulci reported in the article is reproducible, the different results are convincing and in general, this study achieves its aims in defining more precisely the sulcation of the LPOJ and looking into its functional/cognitive value. This work clearly offers a finer understanding of sulcal pattern in this region, and lacks only little for the new markers to be convincingly demonstrated. An overall coherence of the labelling can still be inferred from the supplementary material which support the results and therefore the conclusions, yet, addressing some of the weaknesses listed above would greatly enhance the impact of this work. This work is important to the understanding of sulcal variability and its implications on functional and cognitive aspects.

Reviewer #3 (Public Review):

Summary: 72 subjects, and 144 hemispheres, from the Human Connectome Project had their parietal sulci manually traced. This identified the presence of previously undescribed shallow sulci. One of these sulci, the ventral supralateral occipital sulcus (slocs-v), was then demonstrated to have functional specificity in spatial orientation. The discussion furthermore provides an eloquent overview of our understanding of the anatomy of the parietal cortex, situating their new work into the broader field. Finally, this paper stimulates further debate about the relative value of detailed manual anatomy, inherently limited in participant numbers and areas of the brain covered, against fully automated processing that can cover thousands of participants but easily misses the kinds of anatomical details described here.

Strengths:<br /> - This is the first paper describing the tertiary sulci of the parietal cortex with this level of detail, identifying novel shallow sulci and mapping them to behaviour and function.<br /> - It is a very elegantly written paper, situating the current work into the broader field.<br /> - The combination of detailed anatomy and function and behaviour is superb.

Weaknesses:<br /> - the numbers of subjects are inherently limited both in number as well as in being typically developing young adults.<br /> - while the paper begins by describing four new sulci, only one is explored further in greater detail.<br /> - there is some tension between calling the discovered sulci new vs acknowledging they have already been reported, but not named.<br /> - the anatomy of the sulci, as opposed to their relation to other sulci, could be described in greater detail.

Overall, to summarize, I greatly enjoyed this paper and believe it to be a highly valued contribution to the field.

Reviewer #1 (Public Review):

Summary:<br /> The authors provide very compelling evidence that the lateral septum (LS) engages in theta cycle skipping.

Strengths:<br /> The data and analysis are highly compelling regarding the existence of cycle skipping.

Weaknesses:<br /> The manuscript falls short on describing the behavioral or physiological importance of the witnessed theta cycle skipping, and there is a lack of attention to detail with some of the findings and figures:

More/any description is needed in the article text to explain the switching task and the behavioral paradigm generally. This should be moved from only being in methods as it is essential for understanding the study.

An explanation is needed as to how a cell can be theta skipping if it is not theta rhythmic.

The most interesting result, in my opinion, is the last paragraph of the entire results section, where there is more switching in the alternation task, but the reader is kind of left hanging as to how this relates to other findings. How does this relate to differences in decoding of relative arms (the correct or incorrect arm) during those theta cycles or to the animal's actual choice? Similarly, how does it relate to the animal's actual choice? Is this phenomenon actually behaviorally or physiologically meaningful at all? Does it contribute at all to any sort of planning or decision-making?

The authors state that there is more cycle skipping in the alternation task than in the switching task, and that this switching occurs in the lead-up to the choice point. Then they say there is a higher peak at ~125 in the alternation task, which is consistent. However, in the final sentence, the authors note that "This result indicates that the representations of the goal arms alternate more strongly ahead of the choice point when animals performed a task in which either goal arm potentially leads to reward." Doesn't either arm potentially lead to a reward (but different amounts) in the switching task, not the alternation task? Yet switching is stronger in the alternation task, which is not constant and contradicts this last sentence.

Additionally, regarding the same sentence - "representations of the goal arms alternate more strongly ahead of the choice point when the animals performed a task in which either goal arm potentially leads to reward." - is this actually what is going on? Is there any reason at all to think this has anything to do with reward versus just a navigational choice?

Similarly, the authors mention several times that the LS links the HPC to 'reward' regions in the brain, and it has been found that the LS represents rewarded locations comparatively more than the hippocampus. How does this relate to their finding?

Reviewer #2 (Public Review):

Summary<br /> Recent evidence indicates that cells of the navigation system representing different directions and whole spatial routes fire in a rhythmic alternation during 5-10 Hz (theta) network oscillation (Brandon et al., 2013, Kay et al., 2020). This phenomenon of theta cycle skipping was also reported in broader circuitry connecting the navigation system with the cognitive control regions (Jankowski et al., 2014, Tang et al., 2021). Yet nothing was known about the translation of these temporally separate representations to midbrain regions involved in reward processing as well as the hypothalamic regions, which integrate metabolic, visceral, and sensory signals with the descending signals from the forebrain to ensure adaptive control of innate behaviors (Carus-Cadavieco et al., 2017). The present work aimed to investigate theta cycle skipping and alternating representations of trajectories in the lateral septum, neurons of which receive inputs from a large number of CA1 and nearly all CA3 pyramidal cells (Risold and Swanson, 1995). While spatial firing has been reported in the lateral septum before (Leutgeb and Mizumori, 2002, Wirtshafter and Wilson, 2019), its dynamic aspects have remained elusive. The present study replicates the previous findings of theta-rhythmic neuronal activity in the lateral septum and reports a temporal alternation of spatial representations in this region, thus filling an important knowledge gap and significantly extending the understanding of the processing of spatial information in the brain. The lateral septum thus propagates the representations of alternative spatial behaviors to its efferent regions. The results can instruct further research of neural mechanisms supporting learning during goal-oriented navigation and decision-making in the behaviourally crucial circuits entailing the lateral septum.

Strengths<br /> To this end, cutting-edge approaches for high-density monitoring of neuronal activity in freely behaving rodents and neural decoding were applied. Strengths of this work include comparisons of different anatomically and probably functionally distinct compartments of the lateral septum, innervated by different hippocampal domains and projecting to different parts of the hypothalamus; large neuronal datasets including many sessions with simultaneously recorded neurons; consequently, the rhythmic aspects of the spatial code could be directly revealed from the analysis of multiple spike trains, which were also used for decoding of spatial trajectories; and comparisons of the spatial coding between the two differently reinforced tasks.

Weaknesses<br /> Possible in principle, with the present data across sessions, longitudinal analysis of the spatial coding during learning the task was not performed. Without using perturbation techniques, the present approach could not identify the aspects of the spatial code actually influencing the generation of behaviors by downstream regions.

Reviewer #3 (Public Review):

Summary:<br /> Bzymek and Kloosterman carried out a complex experiment to determine the temporal spike dynamics of cells in the dorsal and intermediate lateral septum during the performance of a Y-maze spatial task. In this descriptive study, the authors aim to determine if inputting spatial and temporal dynamics of hippocampal cells carry over to the lateral septum, thereby presenting the possibility that this information could then be conveyed to other interconnected subcortical circuits. The authors are successful in these aims, demonstrating that the phenomenon of theta cycle skipping is present in cells of the lateral septum. This finding is a significant contribution to the field as it indicates the phenomenon is present in neocortex, hippocampus, and the subcortical hub of the lateral septal circuit. In effect, this discovery closes the circuit loop on theta cycle skipping between the interconnected regions of the entorhinal cortex, hippocampus, and lateral septum. Moreover, the authors make 2 additional findings: 1) There are differences in the degree of theta modulation and theta cycle skipping as a function of depth, between the dorsal and intermediate lateral septum; and 2) The significant proportion of lateral septum cells that exhibit theta cycle skipping, predominantly do so during 'non-local' spatial processing.

Strengths: The major strength of the study lies in its design, with 2 behavioral tasks within the Y-maze and a battery of established analyses drawn from prior studies that have established spatial and temporal firing patterns of entorhinal and hippocampal cells during these tasks. Primary among these analyses, is the ability to decode the animal's position relative to locations of increased spatial cognitive demand, such as the choice point before the goal arms. The presence of theta cycle skipping cells in the lateral septum is robust and has significant implications for the ability to dissect the generation and transfer of spatial routes to goals within and between the neocortex and subcortical neural circuits.

Weaknesses: There are no major discernable weaknesses in the study, yet the scope and mechanism of the theta cycle phenomenon remain to be placed in the context of other phenomena indicative of spatial processing independent of the animal's current position. An example of this would be the ensemble-level 'scan ahead' activity of hippocampal place cells (Gupta et al., 2012; Johnson & Redish, 2007). Given the extensive analytical demands of the study, it is understandable that the authors chose to limit the analyses to the spatial and burst firing dynamics of the septal cells rather than the phasic firing of septal action potentials relative to local theta oscillations or CA1 theta oscillations. Yet, one would ideally be able to link, rather than parse the phenomena of temporal dynamics. For example, Tingley et al recently showed that there was significant phase coding of action potentials in lateral septum cells relative to spatial location (Tingley & Buzsaki, 2018). This begs the question as to whether the non-uniform distribution of septal cell activity within the Y-maze may have a phasic firing component, as well as a theta cycle skipping component. If so, these phenomena could represent another means of information transfer within the spatial circuit during cognitive demands. Alternatively, these phenomena could be part of the same process, ultimately representing the coherent input of information from one region to another. Future experiments will therefore have to sort out whether theta cycle skipping, is a feature of either rate or phase coding, or perhaps both, depending on circuit and cognitive demands.

The authors have achieved their aims of describing the temporal dynamics of the lateral septum, at both the dorsal extreme and the intermediate region. All conclusions are warranted.

Reviewer #1 (Public Review):

Summary:

This manuscript describes the development of an oral THC consumption model in mice where THC is added to a chocolate flavored gelatin. The authors compared the effects of THC consumed in this highly palatable gelatin (termed E-gel) to THC dissolved in a less palatable gelatin (CTR-gel), and to i.p. injections of multiple doses of THC, on the classic triad of CB1R dependent behaviors (hypolocomotion, antinociception, and body temperature).

The authors found that they could achieve consumption of higher concentrations of THC in the E-gel than the CTR-gel, and that this led to larger total dose exposure and decreases in locomotor activity, antinociception, and body temperature reductions similar to 3-4 mg/kg THC when tested after 2 hour consumption and roughly 10 mg/kg if tested immediately after 1 hour consumption. The majority of THC E-gel consumption was found to occur in the first hour on the first exposure day. THC E-gel consumption was lower than VEH E-gel consumption and this persisted on a subsequent consumption day, suggesting that the animals may form a taste aversion and that THC at the dose consumed likely has aversive properties, consistent with the literature on i.p. dosing. The authors also report the pharmacokinetics in brain and plasma of THC and metabolites after 1 or 2 hour consumption, finding high levels of THC in the brain that begins to dissipate at 2.5 hours is gone 24 hours later. Finally, the authors tested THC effects on the acoustic startle response and found an inverted dose response that was more pronounced in males than females after i.p. dosing and a greater startle response in males after E-gel dosing.

Overall, the authors find that voluntary oral consumption of THC can achieve levels of intake that are consistent with the present and prior reported literature on i.p. dosing.

Strengths:

The strengths of the article include a direct comparison of voluntary oral THC consumption to noncontingent i.p. administration, the use of multiple THC doses and oral THC formulations, the inclusion of multiple assays of cannabinoid agonist effects, and the inclusion of males and females. Additional strengths include monitoring intake over 10 minute intervals and validating that effects are CB1R dependent via antagonist studies.

Weaknesses:

1. The abstract does not discuss the reduction of E-gel consumption that occurs after multiple days of exposure to the THC formulation, but rather implies that a new model for chronic oral self-administration has been developed. Given that only two days of consumption was assessed, it is not clear if the model will be useful to determine THC effects beyond the acute measures presented here. The abstract should clarify that there was evidence of reduced consumption/aversive effects with repeated exposures.<br /> 2. In the results section, the authors sometimes describe effects in terms of the concentration of gel as opposed to the dose consumed in mg/kg, which can make interpretation difficult. For example, the text describing Figure 1i states that significant effects on body temperature were achieved at 4 mg CTR-gel and 5 mg THC-gel, but were essentially equivalent doses consumed? It would be helpful to describe what average dose of THC produced effects given that consumption varied within each group of mice assigned to a particular concentration.<br /> 3. The description of the PK data in Figure 3 did not specify if sex differences were examined. Prior studies have found that males and females can exhibit stark differences in brain and plasma levels of THC and metabolites, even when behavioral effects are similar. However, this does depend on species, route, timing of tissue collection. It would be helpful to describe the PK profile of males and females separately.<br /> 4. In Figure 5, it is unclear how the predicted i.p. THC dose could be 30 mg/kg when 30 mg/kg was not tested by the i.p. route according to the figure, and if it had been it would have likely been almost zero acoustic startle, not the increased startle that was observed in the 2 hr gel group. It seems more likely that it would be equivalent to 3 mg/kg i.p. Could there be an error in the modeling, or was it based on the model used for the triad effects? This should be clarified.

Reviewer #2 (Public Review):

Summary:<br /> The work fruitfully adds to the tools to study cannabinoid action and pharmacology specifically, but also this method is applicable to other drugs, in particular, if lipophilic in nature.

Strengths:<br /> The addition of chocolate flavor overcomes aversive reactions which are often experienced in pharmacological treatments, leading to possible caveats in the interpretation of the behavioral outcomes.

Weaknesses:<br /> Certainly, more THC mediated behavioral outcomes could have been tested, but the work presents a proof-of-concept study to investigate acute THC treatment.<br /> It would have been interesting if this application form is also possible for chronic treatment regimen

Reviewer #3 (Public Review):

Summary: This manuscript explores the development of a rodent voluntary oral THC consumption model. The authors use the model to demonstrate that similar effect levels of THC can be observed to what has previously been described for i.p. THC administration.

Strengths: Overall this is an interesting study with compelling data presented. There is a growing need within the field of cannabinoid research to explore more 'realistic' routes of cannabinoid administration, such as oral consumption or inhalation. The evidence presented here shows the utility of this oral administration model.

Weaknesses: The main weaknesses of the manuscript revolve around clarification of the Methods section. All of these weaknesses are described in the "Recommendations to authors" section. Revising the manuscript would account for many of these weaknesses.

Reviewer #1 (Public Review):

Prior research demonstrated that vocal learning is sexually dimorphic in zebra finches; female song nuclei atrophy and fail to develop, but can be rescued with exogenous 17-𝛃-estradiol (E2) treatment. In previous research, the authors treated both male and female birds with exogenous E2. They laser-captured dissected tissue samples from the E2-treated individuals as well as untreated controls. They then extracted RNA and used RNA-seq to characterize the transcriptomes within and adjacent to four major song nuclei (HVC, LMAN, RA, Area X) in these birds. In this study, Davenport et al. remapped this massive amount of transcriptome data (n=3 birds per sex/treatment group) to fully resolve the genomic location of differentially expressed genes, which they assigned to several modules based on co-expression. Adequate read mapping to all chromosomes was previously impossible with zebra finch genome assemblies lacking W chromosome data. Using the high-quality zebra finch genome assembly with Z and W chromosomes (bTaeGut2.pat.W.v2), the authors were able to demonstrate the enrichment of certain modules on certain chromosomes; most interestingly, Z chromosome gene expression was increased in E2-treated females. This research greatly improves our understanding of the ontology and location of genes involved in song development in E2-treated females, providing insight into the development of vocal learning in the zebra finch.

The authors' main conclusions on the importance of certain gene modules in the vocal learning process are well warranted by their excellent data and thorough analyses, but should not be too broadly interpreted as necessarily applying to the gene expression involved in vocal learning in other species. While the data here further supports convergent evolution in vocal learning genes in humans and zebra finches, vocal learning is unusually sexually dimorphic in zebra finches compared to most other vocal learners.

The authors note the possibility of female haploinsufficiency of Z-linked genes such as the growth hormone receptor (GHR) and also imply there are potential effects of the fission of the ancestral chromosome into passerine chromosomes 1 and 1A impacting the typical development of male zebra finch song and the lack thereof in females. These thoughts are intriguing and should prompt further transcriptomic research in avian species with the same genomic features (ZW females, split 1 and 1A chromosomes) where females also learn song, i.e. female-singing passerine species. Currently, it is impossible to say if female-singing species are, as is likely with the E2-treated zebra finch females, using estrogen signaling pathways to regulate an increase in dosage of these genes. Alternately, these female-singing birds may be using different gene modules, which is also worthy of investigation. This research excels at elucidating the genomic underpinnings of vocal learning in a model organism; further research will demonstrate how broadly applicable these authors' findings are across other species.

Reviewer #2 (Public Review):

This work tried to identify genes involved in the song learning of zebra finches by looking at gene expression from individuals who could learn to sing (males and E2-treated females) or not learn to sing (untreated females). They use extensive RNAseq data from one of their previous publications, but this time align the reads to a female genome (from another of their previous publications). Here they use traditional Weighted Gene Correlation Network Analysis (WGCNA) to identify modules (sets of genes whose expression co-varies across all samples) and then find how these sets of genes collectively differ between brain regions involved in song learning and the surrounding tissues not involved in song learning. This approach identified modules that were significantly different in expression between males and females, and the authors interpret this as sex chromosomes being involved in song learning. However, this approach is highly skewed by unrelated patterns of gene expression from the sex chromosomes due to a lack of dosage compensation in birds. In short, by generating WGCNA modules from males and females, all sex chromosome genes will be expected to be artificially pulled into one module due to methodological artifacts and not true biologically relevant differences.

Strengths:<br /> It's nice to see large datasets being reevaluated with updated genomes.

Weaknesses:<br /> Zebra finches (like all birds) do not have XX/XY sex determination, but instead have ZZ/ZW, which means that males have two copies of the Z chromosome and females have one copy of the Z and one copy of the W. This is important because it means that if males and females express all their genes at the same rate, then expression of Z genes will always be twice as high in males relative to females. [While mammals have mechanisms to equalize expression of X chromosome genes between males and females (aka. dosage compensation), birds do not have such chromosome-scale mechanisms.] Therefore, the expression of genes on the sex chromosomes of birds will always differ dramatically between males and females, without necessarily indicating any biologically meaningful difference. WGCNA-based approaches (such as those used here) form modules based on differences in gene expression across all samples. Since this manuscript used all samples to generate their WGCNA modules then all (or nearly all) of the expressed genes on the sex chromosomes would be expected to be pulled into the same module - which is precisely what happened: the reported 'module E' contained 904 genes, while there are only 1,078 genes annotated on the Z chromosome of the reference genome used. Some of these genes may 'belong' in other modules if there are regional differences, but the dosage-driven-differences between sexes across all regions will overwhelm these signals. Therefore great care needs to be taken when interpreting the results of this study until such time as independent analyses can verify these results.

Reviewer #3 (Public Review):

Summary:<br /> Davenport et al have investigated how the administration of a masculinizing dose of estrogen changes the transcriptomes of several key song nuclei song and adjacent brain areas in juvenile zebra finches of both sexes. Only male zebra finches sing, learn song, and normally have a fully developed song control circuitry, so the study was aimed at further understanding how genetic and hormonal factors contribute to the dimorphism in song behavior and related brain circuitry in this species. Using WGCNA and follow-up correlations to re-analyze published transcriptome datasets, the authors provide evidence that the main variance of several identified gene co-expression modules shows significant correlations with one or some of the factors examined, including sex, estrogen treatment, regional neuroanatomy, or occurrence of vocal learning.

Strengths:<br /> Among the main strengths are the thorough gene co-expression module and correlation analyses, and the inclusion of both song nuclei and adjacent areas, the latter serving as sort of controls for areas that are not dimorphic and likely broadly present in birds in general. The most relevant finding is arguably the identification of some modules where gene expression variation within song nuclei correlates with hormonal effects and/or gene location on sex chromosomes, which are present at different dosages between sexes. The study also shows how a published RNA-seq dataset can be reanalyzed in novel and informative ways.

Weaknesses:<br /> Among its main weaknesses, the study relies entirely on one set of transcriptomic data and lacks effort to validate the inferred direction of regulation in the identified co-expression modules using other molecular methods or approaches on independent samples. The study shows that some representative and/or highly significant genes in some of the main modules that correlate with anatomical, sex, or hormone treatment group comparisons indeed differ in expression when comparing song nuclei vs surroundings, male vs female, or E2- vs VEH-treated tissues in independent samples by qPCR or in situ hybridization would provide important validation and enhance experimental rigor for the analyses presented. In the absence of this further validation, the WGCNA data need to be interpreted with caution.

The findings related to ex-chromosome genes (i.e. module E) are a significant strength of the study. Two points, however, need to be taken into account more closely. First, sex differences in gene expression in areas that are not song nuclei are likely related to functions other than song behavior or vocal learning, thus not related to the main question posed by the study. Furthermore, an alternative interpretation with regard to sex chromosome gene expression is that the higher male expression for a large number of Z chromosome genes may not significantly or fundamentally affect brain cell function and can be tolerated, thus not requiring active compensation. This alternative interpretation (mentioned for song nucleus RA in Friedrich et al, Cell Reports, 2022) suggesting that the higher male dosage of many of these genes might not affect or contribute to sex differences in brain function, cannot at present be discarded, and should at least be acknowledged.

Friedrich et al, Cell Reports, 2022 (Table S3 ) presented an extensive manual curation of W chromosome genes in zebra finches. BLAST alignments showed that a large proportion of W chromosome genes are also on the Z, noting that only a small subset of these are annotated as Z:W pairs. The genes that are truly W-specific and present at a higher dosage in females are thus only a fraction of W-chromosome genes. This creates a complication when examining the mapping of RNA-seq reads to sex chromosomes: to conclude about higher expression of W genes in female tissue samples one needs to take into account reads that may also map to the homologous genes on the Z, if that gene is present as a W:Z pair. Because Friedrich et al mapped reads to a male genome assembly, W genes were not assessed, thus the present study provides novel info. However, the issues above need to be acknowledged and taken into account to accurately assess sex differences in W chromosome gene expression.

Reviewer #1 (Public Review):

Summary:<br /> This paper presents an innovative decoding approach for brain-computer interfaces (BCIs), introducing a new method named MINT. The authors develop a trajectory-centric approach to decode behaviors across several different datasets, including eight empirical datasets from the Neural Latents Benchmark. Overall, the paper is well written and their method shows impressive performance compared to more traditional decoding approaches that use a simpler approach. While there are some concerns (see below), the paper's strengths, particularly its emphasis on a trajectory-centric approach and the simplicity of MINT, provide a compelling contribution to the field.

Strengths:<br /> The adoption of a trajectory-centric approach that utilizes statistical constraints presents a substantial shift in methodology, potentially revolutionizing the way BCIs interpret and predict neural behaviour. This is one of the strongest aspects of the paper.

The thorough evaluation of the method across various datasets serves as an assurance that the superior performance of MINT is not a result of overfitting. The comparative simplicity of the method in contrast to many neural network approaches is refreshing and should facilitate broader applicability.

Weaknesses:<br /> Scope: Despite the impressive performance of MINT across multiple datasets, it seems predominantly applicable to M1/S1 data. Only one of the eight empirical datasets comes from an area outside the motor/somatosensory cortex. It would be beneficial if the authors could expand further on how the method might perform with other brain regions that do not exhibit low tangling or do not have a clear trial structure (e.g. decoding of position or head direction from hippocampus)

When comparing methods, the neural trajectories of MINT are based on averaged trials, while the comparison methods are trained on single trials. An additional analysis might help in disentangling the effect of the trial averaging. For this, the authors could average the input across trials for all decoders, establishing a baseline for averaged trials. Note that inference should still be done on single trials. Performance can then be visualized across different values of N, which denotes the number of averaged trials used for training.

Reviewer #2 (Public Review):

Summary:<br /> The goal of this paper is to present a new method, termed MINT, for decoding behavioral states from neural spiking data. MINT is a statistical method which, in addition to outputting a decoded behavioral state, also provides soft information regarding the likelihood of that behavioral state based on the neural data. The innovation in this approach is neural states are assumed to come from sparsely distributed neural trajectories with low tangling, meaning that neural trajectories (time sequences of neural states) are sparse in the high-dimensional space of neural spiking activity and that two dissimilar neural trajectories tend to correspond to dissimilar behavioral trajectories. The authors support these assumptions through analysis of previously collected data, and then validate the performance of their method by comparing it to a suite of alternative approaches. The authors attribute the typically improved decoding performance by MINT to its assumptions being more faithfully aligned to the properties of neural spiking data relative to assumptions made by the alternatives.

Strengths:<br /> The paper did an excellent job critically evaluating common assumptions made by neural analytical methods, such as neural state being low-dimensional relative to the number of recorded neurons. The authors made strong arguments, supported by evidence and literature, for potentially high-dimensional neural states and thus the need for approaches that do not rely on an assumption of low dimensionality.

The paper was thorough in considering multiple datasets across a variety of behaviors, as well as existing decoding methods, to benchmark the MINT approach. This provided a valuable comparison to validate the method. The authors also provided nice intuition regarding why MINT may offer performance improvement in some cases and in which instances MINT may not perform as well.

In addition to providing a philosophical discussion as to the advantages of MINT and benchmarking against alternatives, the authors also provided a detailed description of practical considerations. This included training time, amount of training data, robustness to data loss or changes in the data, and interpretability. These considerations not only provided objective evaluation of practical aspects but also provided insights to the flexibility and robustness of the method as they relate back to the underlying assumptions and construction of the approach.

Weaknesses:<br /> The authors posit that neural and behavioral trajectories are non-isometric. To support this point, they look at distances between neural states and distances between the corresponding behavioral states, in order to demonstrate that there are differences in these distances in each respective space. This supports the idea that neural states and behavioral states are non-isometric but does not directly address their point. In order to say the trajectories are non-isometric, it would be better to look at pairs of distances between corresponding trajectories in each space.

With regards to the idea of neural and behavioral trajectories having different geometries, this is dependent on what behavioral variables are selected. In the example for Fig 2a, the behavior is reach position. The geometry of the behavioral trajectory of interest would look different if instead the behavior of interest was reach velocity. The paper would be strengthened by acknowledgement that geometries of trajectories are shaped by extrinsic choices rather than (or as much as they are) intrinsic properties of the data.

The approach is built up on the idea of creating a "mesh" structure of possible states. In the body of the paper the definition of the mesh was not entirely clear and I could not find in the methods a more rigorous explicit definition. Since the mesh is integral to the approach, the paper would be improved with more description of this component.

Impact:<br /> This work is motivated by brain-computer interfaces applications, which it will surely impact in terms of neural decoder design. However, this work is also broadly impactful for neuroscientific analysis to relate neural spiking activity to observable behavioral features. Thus, MINT will likely impact neuroscience research generally. The methods are made publicly available, and the datasets used are all in public repositories, which facilitates adoption and validation of this method within the greater scientific community.

Reviewer #3 (Public Review):

Summary:

This manuscript develops a new method termed MINT for decoding of behavior. The method is essentially a table-lookup rather than a model. Within a given stereotyped task, MINT tabulates averaged firing rate trajectories of neurons (neural states) and corresponding averaged behavioral trajectories as stereotypes to construct a library. For a test trial with a realized neural trajectory, it then finds the closest neural trajectory to it in the table and declares the associated behavior trajectory in the table as the decoded behavior. The method can also interpolate between these tabulated trajectories. The authors mention that the method is based on three key assumptions: (1) Neural states may not be embedded in a low-dimensional subspace, but rather in a high-dimensional space. (2) Neural trajectories are sparsely distributed under different behavioral conditions. (3) These neural states traverse trajectories in a stereotyped order.

The authors conducted multiple analyses to validate MINT, demonstrating its decoding of behavioral trajectories in simulations and datasets (Figures 3, 4). The main behavior decoding comparison is shown in Figure 4. In stereotyped tasks, decoding performance is comparable (M_Cycle, MC_Maze) or better (Area 2_Bump) than other linear/nonlinear algorithms (Figure 4). However, MINT underperforms for the MC_RTT task, which is less stereotyped (Figure 4).

This paper is well-structured and its main idea is clear. The fact that performance on stereotyped tasks is high is interesting and informative, showing that these stereotyped tasks create stereotyped neural trajectories. The task-specific comparisons include various measures and a variety of common decoding approaches, which is a strength. However, I have several major concerns. I believe several of the conclusions in the paper, which are also emphasized in the abstract, are not accurate or supported, especially about generalization, computational scalability, and utility for BCIs. MINT is essentially a table-lookup algorithm based on stereotyped task-dependent trajectories and involves the tabulation of extensive data to build a vast library without modeling. These aspects will limit MINT's utility for real-world BCIs and tasks. These properties will also limit MINT's generalizability from task to task, which is important for BCIs and thus is commonly demonstrated in BCI experiments with other decoders without any retraining. Furthermore, MINT's computational and memory requirements can be prohibitive it seems. Finally, as MINT is based on tabulating data without learning models of data, I am unclear how it will be useful in basic investigations of neural computations. I expand on these concerns below.

Main comments:

1. MINT does not generalize to different tasks, which is a main limitation for BCI utility compared with prior BCI decoders that have shown this generalizability as I review below. Specifically, given that MINT tabulates task-specific trajectories, it will not generalize to tasks that are not seen in the training data even when these tasks cover the exact same space (e.g., the same 2D computer screen and associated neural space).

First, the authors provide a section on generalization, which is inaccurate because it mixes up two fundamentally different concepts: 1) collecting informative training data and 2) generalizing from task to task. The former is critical for any algorithm, but it does not imply the latter. For example, removing one direction of cycling from the training set as the authors do here is an example of generating poor training data because the two behavioral (and neural) directions are non-overlapping and/or orthogonal while being in the same space. As such, it is fully expected that all methods will fail. For proper training, the training data should explore the whole movement space and the associated neural space, but this does not mean all kinds of tasks performed in that space must be included in the training set (something MINT likely needs while modeling-based approaches do not). Many BCI studies have indeed shown this generalization ability using a model. For example, in Weiss et al. 2019, center-out reaching tasks are used for training and then the same trained decoder is used for typing on a keyboard or drawing on the 2D screen. In Gilja et al. 2012, training is on a center-out task but the same trained decoder generalizes to a completely different pinball task (hit four consecutive targets) and tasks requiring the avoidance of obstacles and curved movements. There are many more BCI studies, such as Jarosiewicz et al. 2015 that also show generalization to complex real-world tasks not included in the training set. Unlike MINT, these works can achieve generalization because they model the neural subspace and its association to movement. On the contrary, MINT models task-dependent neural trajectories, so the trained decoder is very task-dependent and cannot generalize to other tasks. So, unlike these prior BCIs methods, MINT will likely actually need to include every task in its library, which is not practical.

I suggest the authors remove claims of generalization and modify their arguments throughout the text and abstract. The generalization section needs to be substantially edited to clarify the above points. Please also provide the BCI citations and discuss the above limitation of MINT for BCIs.

2. MINT is shown to achieve competitive/high performance in highly stereotyped datasets with structured trials, but worse performance on MC_RTT, which is not based on repeated trials and is less stereotyped. This shows that MINT is valuable for decoding in repetitive stereotyped use-cases. However, it also highlights a limitation of MINT for BCIs, which is that MINT may not work well for real-world and/or less-constrained setups such as typing, moving a robotic arm in 3D space, etc. This is again due to MINT being a lookup table with a library of stereotyped trajectories rather than a model. Indeed, the authors acknowledge that the lower performance on MC_RTT (Figure 4) may be caused by the lack of repeated trials of the same type. However, real-world BCI decoding scenarios will also not have such stereotyped trial structure and will be less/un-constrained, in which MINT underperforms. Thus, the claim in the abstract or lines 480-481 that MINT is an "excellent" candidate for clinical BCI applications is not accurate and needs to be qualified. The authors should revise their statements according and discuss this issue. They should also make the use-case of MINT on BCI decoding clearer and more convincing.

3. Related to 2, it may also be that MINT achieves competitive performance in offline and trial-based stereotyped decoding by overfitting to the trial structure in a given task, and thus may not generalize well to online performance due to overfitting. For example, a recent work showed that offline decoding performance may be overfitted to the task structure and may not represent online performance (Deo et al. 2023). Please discuss.

4. Related to 2, since MINT requires firing rates to generate the library and simple averaging does not work for this purpose in the MC_RTT dataset (that does not have repeated trials), the authors needed to use AutoLFADS to infer the underlying firing rates. The fact that MINT requires the usage of another model to be constructed first and that this model can be computationally complex, will also be a limiting factor and should be clarified.

5. I also find the statement in the abstract and paper that "computations are simple, scalable" to be inaccurate. The authors state that MINT's computational cost is O(NC) only, but it seems this is achieved at a high memory cost as well as computational cost in training. The process is described in section "Lookup table of log-likelihoods" on line [978-990]. The idea is to precompute the log-likelihoods for any combination of all neurons with discretization x all delay/history segments x all conditions and to build a large lookup table for decoding. Basically, the computational cost of precomputing this table is O(V^{Nτ} x TC) and the table requires a memory of O(V^{Nτ}), where V is the number of discretization points for the neural firing rates, N is the number of neurons, τ is the history length, T is the trial length, and C is the number of conditions. This is a very large burden, especially the V^{Nτ} term. This cost is currently not mentioned in the manuscript and should be clarified in the main text. Accordingly, computation claims should be modified including in the abstract.

6. In addition to the above technical concerns, I also believe the authors should clarify the logic behind developing MINT better. From a scientific standpoint, we seek to gain insights into neural computations by making various assumptions and building models that parsimoniously describe the vast amount of neural data rather than simply tabulating the data. For instance, low-dimensional assumptions have led to the development of numerous dimensionality reduction algorithms and these models have led to important interpretations about the underlying dynamics (e.g., fixed points/limit cycles). While it is of course valid and even insightful to propose different assumptions from existing models as the authors do here, they do not actually translate these assumptions into a new model. Without a model and by just tabulating the data, I don't believe we can provide interpretation or advance the understanding of the fundamentals behind neural computations. As such, I am not clear as to how this library building approach can advance neuroscience or how these assumptions are useful. I think the authors should clarify and discuss this point.

7. Related to 6, there seems to be a logical inconsistency between the operations of MINT and one of its three assumptions, namely, sparsity. The authors state that neural states are sparsely distributed in some neural dimensions (Figure 1a, bottom). If this is the case, then why does MINT extend its decoding scope by interpolating known neural states (and behavior) in the training library? This interpolation suggests that the neural states are dense on the manifold rather than sparse, thus being contradictory to the assumption made. If interpolation-based dense meshes/manifolds underlie the data, then why not model the neural states through the subspace or manifold representations? I think the authors should address this logical inconsistency in MINT, especially since this sparsity assumption also questions the low-dimensional subspace/manifold assumption that is commonly made.

References

Weiss, Jeffrey M., Robert A. Gaunt, Robert Franklin, Michael L. Boninger, and Jennifer L. Collinger. 2019. "Demonstration of a Portable Intracortical Brain-Computer Interface." Brain-Computer Interfaces 6 (4): 106-17. https://doi.org/10.1080/2326263X.2019.1709260.

Gilja, Vikash, Paul Nuyujukian, Cindy A. Chestek, John P. Cunningham, Byron M. Yu, Joline M. Fan, Mark M. Churchland, et al. 2012. "A High-Performance Neural Prosthesis Enabled by Control Algorithm Design." Nature Neuroscience 15 (12): 1752-1757. https://doi.org/10.1038/nn.3265.

Jarosiewicz, Beata, Anish A. Sarma, Daniel Bacher, Nicolas Y. Masse, John D. Simeral, Brittany Sorice, Erin M. Oakley, et al. 2015. "Virtual Typing by People with Tetraplegia Using a Self-Calibrating Intracortical Brain-Computer Interface." Science Translational Medicine 7 (313): 313ra179-313ra179. https://doi.org/10.1126/scitranslmed.aac7328.

Darrel R. Deo, Francis R. Willett, Donald T. Avansino, Leigh R. Hochberg, Jaimie M. Henderson, and Krishna V. Shenoy. 2023. "Translating Deep Learning to Neuroprosthetic Control." BioRxiv, 2023.04.21.537581. https://doi.org/10.1101/2023.04.21.537581.

Reviewer #1 (Public Review):

This EEG study probes the prediction of a mechanistic account of P300 generation through the presence of underlying (alpha) oscillations with a non-zero mean. In this model, the P300 can be explained by a baseline shift mechanism. That is, the non-zero mean alpha oscillations induce asymmetries in the trial-averaged amplitudes of the EEG signal, and the associated baseline shifts can lead to apparent positive (or negative) deflections as alpha becomes desynchronized at around P300 latency. The present paper examines the predictions of this model in a substantial data set (using the typical P300-generating oddball paradigm and careful analyses). The results show that all predictions are fulfilled: the two electrophysiological events (P300, alpha desynchronization) share a common time-course, anatomical sources (from inverse solutions), and covariations with behaviour; plus relate (negatively) in amplitude, while the direction of this relationship is determined by the non-zero-mean deviation of alpha oscillations pre-stimulus (baseline shift index, BSI). This is indictive of a link of the P300 with underlying alpha oscillations through a baseline shift account, and hence that the P300 can be explained, at least in parts, by non-zero mean brain oscillations as they undergo post-stimulus changes.

Reviewer #2 (Public Review):

The authors show that event related changes in the alpha band, namely a decrease in alpha power over parieto/occipital areas, explains the P300 during an auditory target detection task. The proposed mechanism by which this happens is a baseline-shift, where ongoing oscillations which have a non-zero mean undergo an event-related modulation in amplitude which then mimics a low frequency event-related potential. In this specific case, it is a negative-mean alpha band oscillation which decreases in power post-stimulus and thus mimics a positivity over parieto-occipital areas, i.e. the P300. The authors lay out 4 criteria that should hold, if indeed alpha modulation generates the P300, which they then go about providing evidence for.

Strengths:<br /> - The authors do go about showing evidence for each prediction rigorously, which is very clearly laid out. In particular I found the 3rd section connecting resting-state alpha BSI to the P300 quite compelling.<br /> - The study is obviously very well-powered.<br /> - Very well-written and clearly laid out. Also the EEG analysis is thorough overall, with sensible analysis choices made.<br /> - I also enjoyed the discussion of the literature.<br /> - The mediation analyses make a convincing argument for behavioural effects being related to BSI also.

Weaknesses:<br /> In general, if one were to be trying to show the potential overlap and confound of alpha-related baseline shift and the P300, as something for future researchers to consider in their experimental design and analysis choices, the four predictions hold well. However, if one were to assert that the P300 is "generated" via alpha baseline shift, even partially, then the predictions either do not hold, or if they do, they are not sufficient to support that hypothesis. Thankfully, the authors no longer make this stronger claim in the revised print. Weaknesses pertaining to the previous draft can be found in the prior review.

In reviewing this paper, I have found the authors have made a convincing case that alpha amplitude modulation potentially confounds with P300 amplitude via baseline shift, and this is a valuable finding.

Reviewer #1 (Public Review):

Colin et al demonstrated that condensin is a key factor for the disjunction of sister-telomeres during mitosis and proposed that it is due to that condensin restrains the telomere association of cohesin. The authors first showed that condensin binds telomeres in mitosis evidenced by ChIP-qPCR and calibrated ChIP-seq. They further demonstrated that compromising condensin's activity leads to a failure in the disjunction of telomeres, with convincing cytological and HI-seq evidence. Two telomeric proteins Taz1 and Mit1 were identified to specifically regulate the telomere association of cohesin. Deletion of these genes decreased/increased condensin's telomere association and exacerbated/remedied the defected telomere disjunction in a condensin mutant, echoing the role of condensin in telomere disjunction. They proposed that the underlying mechanism is that condensin inhibits cohesin's accumulation at telomeres. However, the evidence for this claim might need to be further strengthened. Nevertheless, this study uncovered a novel role of condensin in the separation of telomeres of sister chromosomes and open a question of how condensin regulates the structure of chromosomal ends.

Reviewer #2 (Public Review):

This manuscript presents a comprehensive investigation into the role of condensin complexes in telomere segregation in fission yeast. The authors employ chromatin immunoprecipitation analysis to demonstrate the enrichment of condensin at telomeres during anaphase. They then use condensin conditional mutants to confirm that this complex plays a crucial role in sister telomere disjunction. Interestingly, they show that condensin role in telomere disjunction is unlikely related to catenation removal but rather related to the organization of telomeres in cis and/or the elimination of structural constraints or proteins that hinder separation.

The authors also investigate the regulation of condensin localization to telomeres and reveal the involvement of the shelterin subunit Taz1 in promoting condensin's association with telomeres while demonstrating that the chromatin remodeler Mit1 prevents excessive loading of condensin onto telomeres. Finally, they show that cohesin acts as a negative regulator of telomere separation, counteracting the positive effects of condensin.

Overall, the manuscript is well-executed, and the authors provide sufficient supporting evidence for their claims. There are a couple of aspects that arise from this study that when fully elucidated will lead to mechanistic understanding of important biological processes. For instance, the exact mechanism by which Taz1 affects condensin loading or the mechanistic link between cohesin and condensin, especially in the context of their opposing roles, are exciting prospects for the future and it is possible that future work within the context of telomeres might provide valuable insights to these questions .

Reviewer #3 (Public Review):

This study explores how condensin and telomere proteins cooperate to facilitate sister chromatid disjunction at chromosome ends during anaphase. Building upon previous results published by the same group (Reyes et al. 2015, Berthezene et al. 2020), the authors demonstrate that condensin is essential for sister telomere disjunction in anaphase in fission yeast. The primary role of condensin appears to be counteracting cohesin, which holds sister telomeres together. Furthermore, condensin is found to be enriched at telomeres, and this enrichment partially relies on Taz1, the principal telomere factor in S. pombe. The loss of Taz1 does not cause an obvious defect in sister telomere disjunction, which prevents drawing strong conclusions about its role in this process.

Reviewer #1 (Public Review):

Summary:<br /> In this paper the authors present genome-wide association analyses of 11 different cancers including time-to-event analyses. The authors use two recently published Bayesian methods, one of which is constructed to handle time-to-event data. The authors demonstrate that polygenic risk scores trained on these models give nominally better predictions than standard polygenic risk scores. Further they show that performing 11 GWASs in UKB while adjusting for the polygenic effects estimated by their improved predictor, they find seven novel loci are implicated by one or both of these methods of which the authors find that three replicate in Estonian Biobank.

Strengths:<br /> A clear strength is that the authors evaluate the performance of the model in a completely different dataset (Estonian Biobank) than the one it is trained in.

Weaknesses:<br /> The 11 phenotypes that the authors chose have the challenge that they are rare, particularly in healthy biobank participants, which means that (i) the benefit of modeling it as a time-to-event analysis is expected to be smaller and (ii) that models have to be stable under imbalanced case/control fractions. In GWAS analyses authors handle this second problem by using a recently published association test, which is robust to imbalanced data, which likely means that they avoid inflated test statistics, but also that they do not leverage the actual time-to-event information to its full potential.

The authors chose not to use the recently published methods BayesRR-RC and BayesW, but instead they run these models and then add an extra step where they run a logistic regression with an offset term set to the LOCO genomic values as estimated by GRMR-BayesW and GRMR-BayesRR-RC respectively. They write that this was because of the imbalanced case/control proportion, but not how the problem was detected. If the authors have insight about when the standard GRMR-BayesW and GRMR-BayesRR-RC become unreliable, I think it would be helpful to share in this paper. Further, if the associations implicated by standard GRMR-BayesW and GRMR-BayesRR-RC are not reliable, I think we need some justification that the variance components reported in Figure 1 are still reliable.

The authors chose to compare the two new GWAS methods, GMRM-BayesW-adjusted and GMRM-BayesRR-RC-adjusted, to REGENIE, so an obvious first question in my opinion is if GMRM-BayesW-adjusted and GMRM-BayesRR-RC-adjusted find more signal than REGENIE.<br /> a. We see that 7 loci where found by GMRM-BayesW but not by REGENIE, but how many were found by REGENIE but not by GMRM-BayesW?<br /> b. Figure S5 as I understand it is showing that the mean -log(p-value) is lower in GMRM-BayesW than REGENIE for variants that have a p-value in GMRM-BayesW that is lower than 5e-8. I don't think this is a valid way to check if GMRM-BayesW has more power. I have a feeling that there could be a winner's curse-like phenomenon here. I think a more principled comparison could be provided.

The title of the paper ("Novel discoveries and enhanced genomic prediction from modelling genetic risk of cancer age-at-onset") seems to imply that the age of onset informed model (GMRM-BayesW) does better. But I think the foundation for that statement could be strengthened.<br /> Figure S6 shows that 261 previously reported loci were replicated by GMRM-BayesW-adjusted whereas 256 were replicated by GMRM-BayesRR-RC. How were previously reported loci defined? did they include UKB data? and how many where there in total?<br /> In the PRS analyses presented in Figure 3a GMRM-BayesW does better than GMRM-BayesRR-RC in 8/11 phenotypes, which does not itself appear significant to me. And with overlapping confidence intervals the significance of the improvement is hard to see.

In Table 1 it says that rs35763415, rs117972357 and rs7902587 replicated in the Estonian Biobank but Figure 3b it says that rs35763415, rs117972357 and rs1015362 replicated in the Estonian Biobank. What is the difference between these two analyses? In the methods it says that you checked your findings for replication in FinnGen, but I don't see any results from FinnGen anywhere?

Reviewer #2 (Public Review):

Summary: Maksimova, Ojavee, and colleagues extend two of their methods, BayesW and BayesRR-RC to be used as mixed-model association methods by combining them with a similar approach as in step 2 of REGENIE. BayesW handles time-to-event data whereas BayesRR-RC works for case-control phenotypes. They provide UKBB results for 11 cancers and replicate findings and assess predictions in the Estonian biobank.

Strengths: Age-of-onset is becoming more and more available, and developing methods that make the best use of this additional information is valuable.

Weaknesses: In this work, there is (for now) limited validation of results and comparison with other existing methods.

Reviewer #1 (Public Review):

Summary<br /> The authors investigated the antigenic diversity of recent (2009- 2017) A/H3N2 influenza neuraminidases (NAs), the second major antigenic protein after haemagglutinin. They used 27 viruses and 43 ferret sera and performed NA inhibition. This work was supported by a subset of mouse sera. Clustering analysis determined 4 antigenic clusters, mostly in concordance with the genetic groupings. Association analysis was used to estimate important amino acid positions, which were shown to be more likely close to the catalytic site. Antigenic distances were calculated and a random forest model was used to determine potential important sites.

This has the potential to be a very interesting piece of work. At present, there are inconsistencies in the methods, results and presentation that limit its impact. In particular, there are weaknesses in some of the computational work.

Strengths<br /> 1. The data cover recent NA evolution and a substantial number (43) of ferret (and mouse) sera were generated and titrated against 27 viruses. This is laborious experimental work and is the largest publicly available neuraminidase inhibition dataset that I am aware of. As such, it will prove a useful resource for the influenza community.

2. A variety of computational methods were used to analyse the data, which give a rounded picture of the antigenic and genetic relationships and link between sequence, structure and phenotype.

Weaknesses<br /> 1. Inconsistency in experimental methods<br /> Two ferret sera were boosted with H1N2, while recombinant NA protein for the others. This, and the underlying reason, are clearly explained in the manuscript. The authors note that boosting with live virus did not increase titres. Nevertheless, these results are included in the analysis when it would be better to exclude them (Figure 2 shows much lower titres to their own group than other sera).

2. Inconsistency in experimental results<br /> Clustering of the NA inhibition results identifies three viruses which do not cluster with their phylogenetic group. Again this is clearly pointed out in the paper. Further investigation of this inconsistency is required to determine whether this has a genetic basis or is an experimental issue. It is difficult to trust the remaining data while this issue is unresolved.

3. Inconsistency in group labelling<br /> A/Hatay/4990/2016 & A/New Caledonia/23/2016 are in phylogenetic group 1 in Figure 2 and phylogenetic group 1 in Figure 5 - figure supplement 1 panel a.<br /> A/Kansas/14/2017 is selected as a representative of antigenic group 2, when in Figure 2 it is labelled as AC1 (although Figure 2 - supplement 4 which the text is referring to shows data for A/Singapore/Infimh-16-0019/2016 as the representative of AC2). A/Kansas/14/2017 is coloured and labelled as AC2 in Figure 2 - supplement 5.<br /> The colouring is changed for Figure 3a at the bottom. A/Heilongjiang-Xiangyang/1134/2011 is coloured the same as AC4 viruses when it is AC1 in Figure 2.<br /> This lack of consistency makes the figures misleading.

4. Data not presented, without explanation<br /> The paper states that 44 sera and 27 H6N2 viruses were used (line 158). However, the results for the Kansas/14/2017 sera do not appear to be presented in any of the figures (e.g. Figure 2 phylogenetic tree, Figure 5 - figure supplement 1). It is not obvious why these data were not presented. The exclusion of this serum could affect the results as often the homologous titre is the highest and several heatmaps show the fold down from the highest titre.

5. The cMDS plot does not have sufficient quality assurance<br /> A cMDS plot is shown in Figure 5 - figure supplement 1, generated using classical MDS. The following support for the appropriateness of this visualisation is not given.<br /> a. Goodness of fit of the cMDS projection, including per point and per titre.<br /> b. Testing of the appropriate number of dimensions (the two sera from phylogenetic group 3 are clustered with phylogenetic group 2; additional dimensions might separate these groups).<br /> c. A measure of uncertainty in positioning, e.g. bootstrapping.<br /> d. A sensitivity analysis of the assumption about titres below the level of detection (i.e. that <20 = 10).<br /> Without this information, it is difficult to judge if the projection is reliable.

6. Choice of antigenic distance measure<br /> The measure of antigenic distance used here is the average difference between titres for two sera. This is dependent on which viruses have been included in the analysis and will be biased by the unbalanced number of viruses in the different clusters (12, 8, 2, 5).

7. Association analysis does not account for correlations<br /> For each H6N2 virus and position, significance was calculated by comparing the titres between sera that did or did not have a change at that position. This does not take into account the correlations between positions. For haemagglutinin, it can be impossible to determine the true antigenic effects of such correlated substitutions with mutagenesis studies.

8. Random forest method<br /> 25 features are used to classify 43 sera, which seems high (p/3 is typical for classification). By only considering mismatches, rather than the specific amino acid changes, some signals may be lost (for example, at a given position, one amino acid change might be neutral while another has a large antigenic effect). Features may be highly, or perfectly correlated, which will give them a lower reported importance and skew the results.

Reviewer #2 (Public Review):

Summary:<br /> The authors characterized the antigenicity of N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 using ferret and mice immune sera. Four antigenic groups were identified, which correlated with their respective phylogenic/ genetic groups. Among 102 amino acids differed by the 44 selected N2 proteins, the authors identified residues that differentiate the antigenicity of the four groups and constructed a machine-learning model that provides antigenic distance estimation. Three recent A(H3N2) vaccine strains were tested in the model but there was no experimental data to confirm the model prediction results.

Strengths:<br /> This study used N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 and generated corresponding panels of ferret and mouse sera to react with the selected strains. The amount of experimental data for N2 antigenicity characterization is large enough for model building.

Weaknesses:<br /> The main weakness is that the strategy of selecting 44 A(H3N2) viruses from 2009-2017 was not explained. It is not clear if they represent the overall genetic diversity of human A(H3N2) viruses circulating during this time. A comprehensive N2 phylogenetic tree of human A(H3N2) viruses from 2009-2017, with the selected 44 strains labeled in the tree, would be helpful to assess the representativeness of the strains included in the study. The second weakness is the use of double-immune ferret sera (post-infection plus immunization with recombinant NA protein) or mouse sera (immunized twice with recombinant NA protein) to characterize the antigenicity of the selected A(H3N2) viruses. Conventionally, NA antigenicity is characterized using ferret sera after a single infection. Repeated influenza exposure in ferrets has been shown to enhance antibody binding affinity and may affect the cross-reactivity to heterologous strains (PMID: 29672713). The increased cross-reactivity is supported by the NAI titers shown in Table S3, as many of the double immune ferret sera showed the highest reactivity not against its own homologous virus but to heterologous strains. Although the authors used the post-infection ferret sera to characterize 5 viruses (Figure 2, Figure Supplement 4), the patterns did not correlate well. If the authors repeat the NA antigenic analysis using the post-infection ferret sera with lower cross-reactivity, will the authors be able to identify more antigenic groups instead of 4 groups? Another weakness is that the authors used the newly constructed model to predict the antigenic distance of three recent A(H3N2) viruses but there is no experimental data to validate their prediction (eg. if these viruses are indeed antigenically deviating from group 2 strains as concluded by the authors).

Reviewer #3 (Public Review):

Summary:<br /> This paper by Portela Catani et al examines the antigenic relationships (measured using monotypic ferret and mouse sera) across a panel of N2 genes from the past 14 years, along with the underlying sequence differences and phylogenetic relationships. This is a highly significant topic given the recent increased appreciation of the importance of NA as a vaccine target, and the relative lack of information about NA antigenic evolution compared with what is known about HA. Thus, these data will be of interest to those studying the antigenic evolution of influenza viruses. The methods used are generally quite sound, though there are a few addressable concerns that limit the confidence with which conclusions can be drawn from the data/analyses.

Strengths:<br /> - The significance of the work, and the (general) soundness of the methods.<br /> - Explicit comparison of results obtained with mouse and ferret sera.

Weaknesses:<br /> - Approach for assessing the influence of individual polymorphisms on antigenicity does not account for the potential effects of epistasis.<br /> - Machine learning analyses were neither experimentally validated nor shown to be better than simple, phylogenetic-based inference.

Reviewer #1 (Public Review):

Summary:<br /> In the present study, the authors examined the possibility of using phosphatidyl-inositol kinase 3-kinase alpha (PI3Ka) inhibitors for heterotopic ossification (HO) in fibrodysplasia ossificans progressiva (FOP). Administration of BYL719, a chemical inhibitor of PI3Ka, prevented HO in a mouse model of FOP that expressed a mutated ACVR1 receptor. Genetic ablation of PI3Ka (p110a) also suppressed HO in mice. BYL719 blocked osteochondroprogenitor specification and reduced inflammatory responses, such as pro-inflammatory cytokine expression and migration/proliferation of immune cells. The authors claimed that inhibition of PI3Ka is a safe and effective therapeutic strategy for HO.

Strengths:<br /> This manuscript reports an interesting finding that BYL719 inhibits HO in a mouse model of FOP.

Weaknesses:<br /> The molecular mechanisms of BYL719 were still unclear because BYL719 affected multiple events and many types of cells. Additional experimental data would be needed to show more clearly how PI3Ka regulates HO.

Reviewer #2 (Public Review):

Summary:<br /> The authors in this study previously reported that BYL719, an inhibitor of PI3Kα, suppressed heterotopic ossification in mice model of a human genetic disease, fibrodysplasia ossificans progressive, which is caused by the activation of mutant ACVR1/R206H by Activin A. The aim of this study is to identify the mechanism of BYL719 for the inhibition of heterotopic ossification. They found that BYL719 suppressed heterotopic ossification in two ways: one is to inhibit the specification of precursor cells for chondrogenic and osteogenic differentiation and the other is to suppress the activation of inflammatory cells.

Strengths:<br /> This study is based on the authors' previous reports and the experimental procedures including the animal model are established. In addition, to confirm the role of PI3Kα, the authors used the conditional knock-out mice of the subunit of PI3Kα. They clearly demonstrated the evidence indicating that the targets of PI3Kα are not members of TGFBR by a newly established experimental method.

Weaknesses:<br /> Overall, the presented data were closely related to those previously published by the authors' group or others, and there were very few new findings.<br /> Heterotopic ossification in the mice model was not stable and was inappropriate for scientific evaluation.<br /> The method for chondrogenic differentiation was not appropriate, and the scientific evidence of successful differentiation was lacking.<br /> The design of the gene expression profile comparison was not appropriate and failed to obtain the data for the main aim of this study.<br /> The experiments of inflammatory cells were performed in cell lines without ACVR1/R206H mutation, and therefore the obtained data were not precisely related to the inflammation in FOP.

Reviewer #1 (Public Review):

The manuscript aims to provide mechanistic insight into the activation of PI3Kbeta by its known regulators tyrosine phosphorylated peptides, GTP-loaded Rac1 and G-protein beta-gamma subunits. To achieve this the authors have used supported lipid bilayers, engineered recombinant peptides and proteins (often tagged with fluorophores) and TIRF microscopy to enable bulk (averages of many molecules) and single molecule quantitation. The great strength of this approach is the precision and clarity of mechanistic insight. Although the study does not use "in transfecto" or in vivo models the experiments are performed using "physiologically-based" conditions and provide a powerful insight into core regulatory principles that will be relevant in vivo.

The results are beautiful, high quality, well controlled and internally consistent (and with other published work that overlaps on some points) and as a result are compelling. The primary conclusion is that the primary regulator of PI3Kbeta are tyrosine phosphorylated peptides (and by inference tyrosine phsophorylated receptors/adaptors) and that the other activators can synergise with that input but have relatively weak impacts on their own.

Although the methodology is not easily imported, for reasons of both cost and the experience needed to execute them well, the results have broad importance for the field and reverse an impression that had built in large parts of the broader signalling and PI3K communities that all of the inputs to PI3Kbeta were relatively equivalent, however, these conclusions were based on "in cell" or in vivo studies that were very difficult to interpret clearly.

Reviewer #3 (Public Review):

Summary: In this paper, Ruan et al. studied the long-term impact of warming and altered precipitations on the composition and growth of the soil microbial community. The researchers adopted an experimental approach to assess the impact of climate change on microbial diversity and functionality. This study was carried out within a controlled environment, wherein two primary factors were assessed: temperature (in two distinct levels) and humidity (across three different levels). These factors were manipulated in a full factorial design, resulting in a total of six treatments. This experimental setup was maintained for ten years. To analyze the active microbial community, the researchers employed a technique involving the incorporation of radiolabeled water into biomolecules (particularly DNA) through quantitative stable isotope probing. This allowed for the tracking of the active fraction of microbes, accomplished via isopycnic centrifugation, followed by Illumina sequencing of the denser fraction. This study was followed by a series of statistical analysis to identify the impact of these two variables on the whole community and specific taxonomic groups. The full factorial design arrangement enabled the researchers to discern both individual contributions as well as potential interactions among the variables

Strengths: This work presents a timely study that assesses in a controlled fashion the potential impact of global warming and altered precipitations on microbial populations. The experimental setup, experimental approach and data analysis seem to be overall solid. I consider the paper of high interest for the whole community as it provides a baseline to the assessment of global warming on microbial diversity.

Weaknesses: While taxonomic information is interesting, it would have been highly valuable to include transcriptomics data as well. This would allow us to understand what active pathways become enriched under warming and altered precipitations. Non-metabolic OTUs hold significance as well. The authors could have potentially described these non-incorporators and derived hypotheses from the gathered information. The work would have benefited from using more biological replicates of each treatment.

Reviewer #2 (Public Review):

Summary: The authors aimed to describe the effect of different temperature and precipitation regimes on microbial growth responses in an alpine grassland ecosystem using quantitative 18O stable isotope probing. It was found that all climate manipulations had negative effects on microbial growth, and that single-factor manipulations exerted larger negative effects as compared to combined-factor manipulations. The degree of antagonism between factors was analyzed in detail, as well as the differential effect of these divergent antagonistic responses on microbial taxa that incorporated the isotope. Finally, a hypothetical functional profiling was performed based on taxonomic affiliations. This work gives additional evidence that altered warming and precipitation regimes negatively impact microbial growth.

Strengths: A long term experiment with a thorough experimental design in apparently field conditions is a plus for this work, making the results potentially generalisable to the alpine grassland ecosystem. Also, the implementation of a qSIP approach to determine microbial growth ensures that only active members of the community are assessed. Finally, particular attention was given to the interaction between factors and a robust approach was implemented to quantify the weight of the combined-factor manipulations on microbial growth.

Weaknesses: The methodology does not mention whether the samples taken for the incubations were rhizosphere soil, bulk soil or a mix between both type of soils. If the samples were taken from rhizosphere soil, I wonder how the plants were affected by the infrared heaters and if the resulting shadow (also in the controls with dummy heaters) had an effect on the plants and the root exudates of the parcels as compared to plants outside the blocks? If the samples were bulk soil, are the results generalisable for a grassland ecosystem? In my opinion, it is needed to add more info on the origin of the soil samples and how these were taken.

The qSIP calculations reported in the methodology for this work are rather superficial and the reader must be experienced in this technique to understand how the incorporators were identified and their growth quantified. For instance, the GC content of taxa was calculated for reads clustered in OTUs, and it is not discussed in the text the validity of such approach working at genus level.

The selection of V4-V5 region over V3-V4 region to quantify the number of copies of the 16S rRNA gene should be substantiated in the text. Classic works determined one decade ago that primer pairs that amplify V3-V4 are most suitable to assess soil bacterial communities. Hungate et al. (2015), worked with the V3-V4 region when establishing the qSIP method. Maybe the number of unassigned OTUs is related with the selection of this region.

Report of preprocessing and processing of the sequences does not comply state of the art standards. More info on how the sequences were handled is needed, taking into account that a significant part of the manuscript relies on taxonomic classification of such sequences. Also, an OTU approach for an almost species-dependent analysis (GC contents) should be replaced or complemented with an ASV or subOTUs approach, using denoisers such as DADA2 or deblur. Usage of functional prediction tools underestimates gene frequencies, including those related with biogeochemical significance for soil-carbon and nitrogen cycling.

Reviewer #1 (Public Review):

Warming and precipitation regime change significantly influences both above-ground and below-ground processes across Earth's ecosystems. Soil microbial communities, which underpin the biogeochemical processes that often shape ecosystem function, are no exception to this, and although research shows they can adapt to this warming, population dynamics and ecophysiological responses to these disturbances are not currently known. The Qinghai-Tibet Plateau, the Third Pole of the Earth, is considered among the most sensitive ecosystems to climate change. The manuscript described an integrated, trait-based understanding of these dynamics with the qSIP data. The experimental design and methods appear to be of sufficient quality. The data and analyses are of great value to the larger microbial ecological community and may help advance our understanding of how microbial systems will respond to global change. There are very few studies in which the growth rates of bacterial populations from multifactorial manipulation experiments on the Qinghai-Tibet Plateau have been investigated via qSIP, and the large quantity of data that comprises the study described in this manuscript, will substantially advance our knowledge of bacterial responses to warming and precipitation manipulations.

Joint Public Review:

Using Ts65Dn - the most commonly used mouse model of Down syndrome (DS) - the goal of this study is two-pronged: 1) to conduct a thorough assessment of DS-related genotypic, physiological, behavioral, and phenotypic measures in a longitudinal manner; and 2) to measure the effects of chronic GTE-EGCG on these measures in the Ts65Dn mouse model. Corroborating results from several previous studies on Ts65Dn mice, findings of this study show confirm the Ts65Dn mouse model exhibits the suite of traits associated with DS. The findings also suggest that the mouse model might have experienced drift, given the milder phenotypes than those reported by earlier studies. Results of the GTE-EGCG treatment do not support its therapeutic use and instead show that the treatment exacerbated certain DS-related phenotypes.

Strengths:<br /> The authors performed a rigorous assessment of treatment and examined treatment and genotypic alterations at multiple time points during growth and aging. Detailed analysis shows differences in genotype during aging as well as genotype with treatment. This study is solid in the overarching methodological approach (with the exception of RNAseq, described below). The biggest strength of the study is its approach and dataset, which corroborate results from a multitude of past studies on Ts65Dn mice, albeit on adult specimens. It would be beneficial for the dataset to be made available to other researchers using a public data repository.

Weaknesses:<br /> There are several primary weaknesses, described below:

Sex was not considered in the analyses<br /> The number of experimental animals of each sex are not clearly represented in the paper, but are buried in supplemental tables, and the Ns for the RNAseq are unclear. No analyses were done to examine sex differences in male/female DS or WT animals with or without treatment. Body measurements will greatly vary by sex, but this was not taken into consideration during assessments. As such, there is a high amount of variability within each cohort measured for body assessments (tibia, body weight, skeletal development etc.). Supplemental table 14 had the list of each animal, but not collated by sex, genotype or treatment, making it difficult to assess the strength of each measurement.

Key results are not clearly depicted in the main figures<br /> Rigorous assessment of each figure and the clarity of the figure to convey the results of the analysis needs to be performed. Many of the figures do not clearly represent the findings, with authors heavily relying on supplemental figures to present details to explain results. Figure legends do not adequately describe figures; rather, they are limited to describing how the analysis is performed. For example, LDA plots in Figure 4 do not clearly convey the results of metabolite analysis.<br /> Overall, the amount of data presented here is overwhelming, making it difficult to interpret the findings. Some assessments that do not add to the overall paper need to be removed. Clarifying the text, figures and trimming the supplement to represent the data in a manner that is easily understood will improve the readability of the paper. For example, perhaps measures which are not strongly impacted by genotype could be moved to the supplement, because they are not directly relevant to the question of whether GTE-EGCG reverses the impact of trisomy on the measures.

Lack of clarity in the behavioral analyses<br /> Behavioral assessments are not clearly written in the methods. For example, for the novel object recognition task, it isn't clear how preference was calculated. Is this simply the percent of time spent with the novel object, or is this a relative measure (novel:familiar ratio)? This matters because if it is simply the percent of time, the relevant measure is to compare each group to 50% (the absence of a preference). The key measures for each test need to be readily distinguished from the control measures.<br /> There are also many dependent behavioral measures. For example, speed and distance are directly related to each other, but these are typically reported as control measures to help interpret the key measure, which is the anxiety-like behavior. Similarly, some behavioral tests were used to represent multiple behavioral dimensions, such as anxiety and arousal. In general, the measurements of arousal seem atypical (speed and distance are typically reported as control measures, not measures of arousal). Similarly, measures of latency during training would not typically be used as a measure of long-term memory but instead reported as a control measure to show learning occurred. LDA analysis requires independence of the measures, as well as normality. It does not appear that all of the measures fed into this analysis would have met these assumptions, but the methods also do not clearly describe which measures were actually used in the LDA.

Unclear value of RNAseq<br /> RNAseq was performed in cerebellum, a relatively spared region in DS pathology at an early time point in disease. Further, the expression of 125 genes triplicated in DS was shown in a PCA plot to highly overlap with WT, indicating that there are minimal differences in gene expression in these genes. If these genes are not critical for cerebellar function, perhaps this could account for the lack of differences between WT and Ts65Dn mice. If the authors are interested in performing RNAseq, it would have made more sense to perform this in hippocampus (to compare with metabolites) and to perform more stringent bioinformatic analysis than assessment by PCA of a limited subset of genes. Supplementary Table S14, which shows the differentially expressed genes, appears to be missing from the manuscript and cannot be evaluated. Additionally, the methods of the RNAseq are not sufficiently described and lack critical details. For example, what was the normalization performed, and which groups were compared to identify differentially expressed genes? It would also be worthwhile to describe how animals were identified for RNAseq-were those animals representative of their groups across other measures?

Reviewer #1 (Public Review):

Wheeler et al. have discovered a new RNA circuit that regulates T-cell function. They found that the long non-coding RNA Malat1 sponges miR-15/16, which controls many genes related to T cell activation, survival, and memory. This suggests that Malat1 indirectly regulates T-cell function. They used CRISPR to mutate the miR-15/16 binding site in Malat1 and observed that this disrupted the RNA circuit and impaired cytotoxic T-cell responses. While this study presents a novel molecular mechanism of T-cell regulation by Malat1-miR-15/16, the effects of Malat1 are weaker compared to miR-15/16. This could be due to several reasons, including higher levels of miR-15/16 compared to Malat1 or Malat1 expression being mostly restricted to the nucleus. Although the role of miR15/16 in T-cell activation has been previously published, if the authors can demonstrate that miR15/16 and/or Malat1 affect the clearance of Listeria or LCMV, this will significantly add to the current findings and provide physiological context to the study.

Reviewer #2 (Public Review):

This study connects prior findings on MicroRNA15/16 and Malat1 to demonstrate a functional interaction that is consequential for T cell activation and cell fate.

The study uses mice (Malat1scr/scr) with a precise genetic modification of Malat1 to specifically excise the sites of interaction with the microRNA, but sparing all other sequences, and mice with T-cell specific deletion of miR-15/16. The effects of genetic modification on in vivo T-cell responses are detected using specific mutations and shown to be T-cell intrinsic.

It is not known where in the cell the consequential interactions between MicroRNA15/16 and Malat1 take place. The authors depict in the graphical abstract Malat1 to be a nuclear lncRNA. Malat 1 is very abundant, but it is unclear if it can shuttle between the nucleus and cytoplasm. As the authors discuss future work defining where in the cell the relevant interactions take place will be important.

In addition to showing physiological phenotypic effects, the mouse models prove to be very helpful when the effects measured are small and sometimes hard to quantitate in the context of considerable variation between biological replicates (for example the results in Figure 4D).

The impact of the genetic modification on the CD28-IL2- Bcl2 axis is quantitatively small at the level of expression of individual proteins and there are likely to be additional components to this circuitry.

Joint Public Review:

The authors of this manuscript studied cell-cell interaction between fibroblast and cancer cells as an intermediary model of tumor cell migration/invasion. The work focused on the mesenchymal cadherin-11 (CDH11) which is expressed in the later stages of the epithelial mesenchymal transition (EMT) in tumor cellular models, and whose expression is correlated with tumor progression in vivo. The authors employed 3-D matrix and live cell imaging to visualize the nutrient-dependent co-migration of fibroblast and cancer cells. By siRNA-based suppression of CDH11 expression in tumor cell line and/or fibroblast cells, the authors observed decreased co-movement and attenuated growth of mixed xenograft. Accordingly, the authors conclude that post-EMT cancer cells are capable of migrating/invading through CDH11-mediated cell-cell contact.

While the data point to the involvement of CDH11 in fibroblast mediated co-invasion, as it stands it is difficult to fully contextualize these observations within the broader context of the molecular mechanisms underlying metastasis, and in particular do not firmly establish a primary role for CDH11 at this time. The reviewers were specifically concerned about indirect effects of CDH11 manipulation on the physiology and cell biology of the tumor cells, and the possibility that several of the results could be consequences of these changes rather than due specifically to CDH11 mediated interactions.

The reviewers acknowledge the difficulty in fully controlling for these phenomena, and believe this work will be of interest to the large number of researchers investigating the molecular basis for metastasis and specifically of trans cell-type interactions. However until experiments establishing the specific formation and CDH11-mediated interactions in co-invasion are carried out, the author's conclusions about the prominent role of CDH11 should be treated as intriguing, but speculative.

Reviewer #1 (Public Review):

The overall tone of the rebuttal and lack of responses on several questions was surprising. Clearly, the authors took umbrage at the phrase 'no smoking gun' and provided a lengthy repetition of the fair argument about 'ticking boxes' on the classic list of criteria. They also make repeated historical references that descriptions of neurotransmitters include many papers, typically over decades, e.g. in the case of ACh and its discovery by Sir Henry Dale. While I empathize with the authors' apparent frustration (I quote: '...accept the reality that Rome was not built in a single day and that no transmitter was proven by a one single paper') I am a bit surprised at the complete brushing away of the argument, and in fact the discussion. In the original paper, the notion of a receptor was mentioned only in a single sentence and all three reviewers brought up this rather obvious question. The historical comparisons are difficult: Of course many papers contribute to the identification of a neurotransmitter, but there is a much higher burden of proof in 2023 compared to the work by Otto Loewi and Sir Henry Dale: most, if not all, currently accepted neurotransmitter have a clear biological function at the level of the brain and animal behavior or function - and were in fact first proposed to exist based on a functional biological experiment (e.g. Loewi's heart rate change). This, and the isolation of the chemical that does the job, were clear, unquestionable 'smoking guns' a hundred years ago. Fast forward 2023: Creatine has been carefully studied by the authors to tick many of the boxes for neurotransmitters, but there is no clear role for its function in an animal. The authors show convincing effects upon K+ stimulation and electrophysiological recordings that show altered neuronal activity using the slc6a8 and agat mutants as well as Cr application - but, as has been pointed out by other reviewers, these effects are not a clear-cut demonstration of a chemical transmitter function, however many boxes are ticked. The identification of a role of a neurotransmitter for brain function and animal behavior has reasonably more advanced possibilities in 2023 than a hundred years ago - and e.g. a discussion of approaches for possible receptor candidates should be possible.

Again, I reviewed this positively and agree that a lot of cumulative data are great to be put out there and allow the discovery to be more broadly discussed and tested. But I have to note, that the authors simply respond with the 'Rome was not built in a single day' statement to my suggestions on at least 'have some lead' how to approach the question of a receptor e.g. through agonists or antagonists (while clearly stating 'I do not think the publication of this manuscript should not be made dependent' on this). Similarly, in response to reviewer 2's concerns about a missing receptor, the authors' only (may I say snarky) response is ' We have deleted this sentence, though what could mediate postsynaptic responses other than receptors?' The bullet point by reviewer 3 ' • No candidate receptor for creatine has been identified postsynaptically.' is the one point by that reviewer that is simply ignored by the authors completely. Finally, I note that my reivew question on the K stimulation issues (e.g. 35 neurons that simply did not respond at all) was: ' Response: To avoid the disadvantage of K stimulation, we also performed optogenetic experiments recently and obtained encouraging preliminary results.' No details, not data - no response really.

In sum, I find this all a bit strange and the rebuttal surprising - all three reviewers were supportive and have carefully listed points of discussion that I found all valid and thoughtful. In response, the authors selectively responded scientifically to some experimental questions, but otherwise simply rather non-scientifically dismissed questions with 'Rome was not built in a day'-type answers, or less. I my view, the authors have disregarded the review process and the effort of three supportive reviewers, which should be part of the permanent record of this paper.

Reviewer #2 (Public Review):

Summary:<br /> Bian et al studied creatine (Cr) in the context of central nervous system (CNS) function. They detected Cr in synaptic vesicles purified from mouse brains with anti-Synaptophysin using capillary electrophoresis-mass spectrometry. Cr levels in the synaptic vesicle fraction was reduced in mice lacking the Cr synthetase AGAT, or the Cr transporter SLC6A8. They provide evidence for Cr release within several minutes after treating brain slices with KCl. This KCl-induced Cr release was partially calcium dependent and was attenuated in slices obtained from AGAT and SLC6A8 mutant mice. Cr application also decreased the excitability of cortical pyramidal cells in one third of the cells tested. Finally, they provide evidence for SLC6A8-dependent Cr uptake into synaptosomes, and ATP-dependent Cr loading into synaptic vesicles. Based on these data, the authors propose that Cr may act as neurotransmitter in the CNS.

Strengths:<br /> 1. A major strength of the paper is the broad spectrum of tools used to investigate Cr.<br /> 2. The study provides evidence that Cr is present in/loaded into synaptic vesicles.

Weaknesses:<br /> 1. There is no significant decrease in Cr content pulled down by anti-Syp in AGAT-/- mice when normalized to IgG controls. Hence, blocking AGAT activity/Cr synthesis does not affect Cr levels in the synaptic vesicle fraction, arguing against a Cr enrichment.<br /> 2. There is no difference in KCl-induced Cr release between SLC6A8-/Y and SLC6A8+/Y when normalizing the data to the respective controls. Thus, the data are not consistent with the idea that depolarization-induced Cr release requires SLC6A8.<br /> 3. The rationale of grouping the excitability data into responders and non-responders is not convincing because the threshold of 10% decrease in AP rate is arbitrary. The data do therefore not support the conclusion that Cr reduces neuronal excitability.

Reviewer #3 (Public Review):

SUMMARY:

The manuscript by Bian et al. promotes the idea that creatine is a new neurotransmitter. The authors conduct an impressive combination of mass spectrometry (Fig. 1), genetics (Figs. 2, 3, 6), biochemistry (Figs. 2, 3, 8), immunostaining (Fig. 4), electrophysiology (Figs. 5, 6, 7), and EM (Fig. 8) in order to offer support for the hypothesis that creatine is a CNS neurotransmitter.

STRENGTHS:

There are many strengths to this study.<br /> • The combinatorial approach is a strength. There is no shortage of data in this study.<br /> • The careful consideration of specific criteria that creatine would need to meet in order to be considered a neurotransmitter is a strength.<br /> • The comparison studies that the authors have done in parallel with classical neurotransmitters is helpful.<br /> • Demonstration that creatine has inhibitory effects is another strength.<br /> • The new genetic mutations for Slc6a8 and AGAT are strengths and potentially incredibly helpful for downstream work.

WEAKNESSES:<br /> • Some data are indirect. Even though Slc6a8 and AGAT are helpful sentinels for the presence of creatine, they are not creatine themselves. Of note, these molecules themselves are not essential for making the case that creatine is a neurotransmitter.<br /> • Regarding Slc6a8, it seems to work only as a reuptake transporter - not as a transporter into SVs. Therefore, we do not know what the transporter into the TVs is.<br /> • Puzzlingly, Slc6a8 and AGAT are in different cells, setting up the complicated model that creatine is created in one cell type and then processed as a neurotransmitter in another. This matter will likely need to be resolved in future studies.<br /> • No candidate receptor for creatine has been identified postsynaptically. This will likely need to be resolved in future studies.<br /> • Because no candidate receptor has been identified, it is important to fully consider other possibilities for roles of creatine that would explain these observations other than it being a neurotransmitter? There is some attention to this in the Discussion.

There are several criteria that define a neurotransmitter. The authors nicely delineated many criteria in their discussion, but it is worth it for readers to do the same with their own understanding of the data.

By this reviewer's understanding (and combining some textbook definitions together) a neurotransmitter: 1) must be present within the presynaptic neuron and stored in vesicles; 2) must be released by depolarization of the presynaptic terminal; 3) must require Ca2+ influx upon depolarization prior to release; 4) must bind specific receptors present on the postsynaptic cell; 5) exogenous transmitter can mimic presynaptic release; 6) there exists a mechanism of removal of the neurotransmitter from the synaptic cleft.

For a paper to claim that the published work has identified a new neurotransmitter, several of these criteria would be met - and the paper would acknowledge in the discussion which ones have not been met. For this particular paper, this reviewer finds that condition 1 is clearly met.

Conditions 2 and 3 seem to be met by electrophysiology, but there are caveats here. High KCl stimulation is a blunt instrument that will depolarize absolutely everything in the prep all at once and could result in any number of non-specific biological reactions as a result of K+ rushing into all neurons in the prep. Moreover, the results in 0 Ca2+ are puzzling. For creatine (and for the other neurotransmitters), why is there such a massive uptick in release, even when the extracellular saline is devoid of calcium?

Condition 4 is not discussed in detail at all. In the discussion, the authors elide the criterion of receptors specified by Purves by inferring that the existence of postsynaptic responses implies the existence of receptors. True, but does it specifically imply the existence of creatinergic receptors? This reviewer does not think that is necessarily the case. The authors should be appropriately circumspect and consider other modes of inhibition that are induced by activation or potentiation of other receptors (e.g., GABAergic or glycinergic).

Condition 5 may be met, because authors applied exogenous creatine and observed inhibition. However, this is tough to know without understanding the effects of endogenous release of creatine. if they were to test if the absence of creatine caused excess excitation (at putative creatinergic synapses), then that would be supportive of the same. Nicely, Ghirardini et al., 2023 study cited by the reviewers does provide support for this exact notion in pyramidal neurons.

For condition 6, the authors made a great effort with Slc6a8. This is a very tough criterion to understand or prove for many synapses and neurotransmitters.

In terms of fundamental neuroscience, the story should be impactful. There are certainly more neurotransmitters out there than currently identified and by textbook criteria, creatine seems to be one of them taking all of the data in this study and others into account.

Reviewer #3 (Public Review):

Summary:

The authors, Y Chang and colleagues, have performed elegant studies in transgenic mouse models that were designed to examine glutamatergic transmission in noradrenergic neurons, with a focus on respiratory regulation. They generated 3 different transgenic lines, in which a red fluorophore was expressed in dopamine-B-hydroxylase (DBH; noradrenergic and adrenergic neurons) neurons that did not express a vesicular glutamate transporter (Vglut) and a green fluorophore in DBH neurons that did express one of either Vglut1, Vglut2 or Vglut3.

Further experiments generated a transgenic mouse with knockout of Vglut2 in DBH neurons. The authors used plethysmography to measure respiratory parameters in conscious, unrestrained mice in response to various challenges.

Strengths:

The distribution of the Vglut expression is broadly in agreement with other studies, but with the addition of some novel Vglut3 expression. Validation of the transgenic results, using in situ hybridization histochemistry to examine mRNA expression, revealed potential modulation of Vglut2 expression during phases of development. This dataset is comprehensive, well-presented and very useful.

In the physiological studies the authors observed that neither baseline respiratory parameters, nor respiratory responses to hypercapnea (5, 7, 10% CO2) or hypoxia (10% O2) were different between knockout mice and littermate controls. The studies are well-designed and comprehensive. They provide observations that are supportive of previous reports using similar methodology.

Weaknesses:

In relation to the expression of Vglut2, the authors conclude that modulation of expression occurs, such that in adulthood there are differences in expression patterns in some (nor)adrenergic cell groups. Altered sensitivity is provided as an explanation for different results between studies examining mRNA expression. These are likely explanations; however, the conclusion would really be definitive with inclusion of a conditional cre expressing mouse. Given the effort taken to generate this dataset, it seems to me that taking that extra step would be of value for the overall understanding of glutamatergic expression in these catecholaminergic neurons

The respiratory physiology is very convincing and provides clear support for the view that Vglut2 is not required for modulation of the respiratory parameters measured and the reflex responses tested. It is stated that this is surprising. However, comparison with the data from Abbott et al., Eur J Neurosci (2014) in which the same transgenic approach was used, shows that they also observed no change in baseline breathing frequency. Differences were observed with strong, coordinated optogenetic stimulation, but, as discussed in this manuscript, it is not clear what physiological function this is relevant to. It just shows that some C1 neurons can use glutamate as a signaling molecule. Further, Holloway et al., Eur J Neurosci (2015), using the same transgenic mouse approach, showed that the respiratory response to optogenetic activation of Phox2 expressing neurons is not altered in DBH-Vglut2 KO mice. The conclusion seems to be that some C1 neuron effects are reliant upon glutamatergic transmission (C1-DMV for example), and some not.

Further contrast is made in this manuscript to the work of Malheiros-Lima and colleagues (eLife 2020) who showed that the activation of abdominal expiratory nerve activity in response to peripheral chemoreceptor activation with cyanide was dependent upon C1 neurons and could be attenuated by blockade of glutamate receptors in the pFRG - i.e. the supposition that glutamate release from C1 neurons was responsible for the function. However, it is interesting to observe that diaphragm EMG responses to hypercapnia (10% CO2) or cyanide, and the expiratory activation to hypercapnia, were not affected by the glutamate receptor blockade. Thus, a very specific response is affected and one that was not measured in the current study.

These previous published observations are consistent with the current study which provides a more comprehensive analysis of the role of glutamatergic contributions respiratory physiology. A more nuanced discussion of the data and acknowledgement of the differences, which are not actually at odds, would improve the paper and place the information within a more comprehensive model.

Reviewer #2 (Public Review):

Summary:

This study takes a new approach to studying the role of corticofugal projections from auditory cortex to inferior colliculus. The authors performed two-photon imaging of cortico-recipient IC neurons during a click detection task in mice with and without lesions of auditory cortex. In both groups of animals, they observed similar task performance and relatively small differences in the encoding of task-response variables in the IC population. They conclude that non-cortical inputs to the IC provide can substantial task-related modulation, at least when AC is absent.

Strengths:

This study provides valuable new insight into big and challenging questions around top-down modulation of activity in the IC. The approach here is novel and appears to have been executed thoughtfully. Thus, it should be of interest to the community.

Weaknesses:

There are, however, substantial concerns about the interpretation of the findings and limitations to the current analysis. In particular, Analysis of single unit activity is absent, making interpretation of population clusters and decoding less interpretable. These concerns should be addressed to make sure that the results can be interpreted clearly in an active field that already contains a number of confusing and possibly contradictory findings.

Reviewer #3 (Public Review):

Summary:

This study aims to demonstrate that cortical feedback is not necessary to signal behavioral outcome to shell neurons of the inferior colliculus during a sound detection task. The demonstration is achieved by the observation of the activity of cortico-recipient neurons in animals which have received lesions of the auditory cortex. The experiment shows that neither behavior performance nor neuronal responses are significantly impacted by cortical lesions except for the case of partial lesions which seem to have a disruptive effect on behavioral outcome signaling.

Strengths:

The experimental procedure is based on state of the art methods. There is an in depth discussion of the different effects of auditory cortical lesions on sound detection behavior.

Weaknesses:

The analysis is not documented enough to be correctly evaluated. Have the authors pooled together trials with different sound levels for the key hit vs miss decoding/clustering analysis? If so, the conclusions are not well supported, as there are more misses for low sound levels, which would completely bias the outcome of the analysis. It would possible that the classification of hit versus misses actually only reflects a decoding of sound level based on sensory responses in the colliculus, and it would not be surprising then that in the presence or absence of cortical feedback, some neurons responds more to higher sound levels (hits) and less to lower sound levels (misses). It is important that the authors clarify and in any case perform an analysis in which the classification of hits vs misses is done only for the same sound levels. The description of feedback signals could be more detailed although it is difficult to achieve good temporal resolution with the calcium imaging technique necessary for targeting cortico-recipient neurons.

Reviewer #2 (Public Review):

Extracellular vesicles have recently gained significant attention across a wide variety of fields, and they have therefore been implicated in numerous physiological and pathophysiological processes. When such a discovery and an explosion of interest occur in science, there is often much excitement and hope for answers to mechanisms that have remained elusive and poorly understood. Unfortunately, there is an equal amount of hype and overstatement that may also be put forth in the name of "impact", but this temptation must be avoided so that scientists and the broader public are not misled by overreaching interpretations and statements that lack rigorous and fully convincing evidence.

The study presented by Kapustin et al. is certainly intriguing and timely, and it offers an interesting working hypothesis for the fields of extracellular vesicles and vascular biology to consider. The authors do a reasonable job at detecting these small extracellular vesicles, though some aspects of data presentation are missing such as full Western blots with accompanying size markers for the viewer to more fully appreciate that data and comparisons being made (see Figures 1 and 7).

Much of the imaging data from cell-based experiments is strong and conducted with many cutting-edge tools and approaches. That said, the static images and the dynamic imaging fall short of being fully convincing that the small extracellular vesicles found in the neighboring extracellular matrix are indeed being deposited there via the smooth muscle cell filopodia. Many of the lines of evidence presented suggest that this could occur, but alternative hypotheses also exist that were not fully ruled out, such as the ECM-deposited vesicles were secreted more from the soma and/or the lamellipodia that are also emitted and retracted from the cells. In particular, the authors show very nice dynamic imaging (Supplementary Figure S2A and Supplemental Video S1) that is interpreted as "extracellular vesicles being released from the cell" and these are seen as "bursts" of fluorescent signal; however, none of these appear to occur in filopodia as they appear within the cell proper (a "burst" of signal vs. a more intense "streak" of signal), which would be a stronger and more consistent observation predicted by the working model proposed by the authors.

Imaging of related human samples is certainly a strength of the paper, and the authors are commended for attempting to connect the findings from their cell culture experiments to an important clinical scenario. However, the marker selected for marking extracellular vesicles is CD81, which has been described as present on the endothelium of atherosclerotic plaques with a proposed role in the recruitment of monocytes into diseased arteries (Rohlena et al. Cardiovasc Res 2009). More data should address this potentially confounding interpretation of the signals presented in images within Figure 4.

On a conceptual level, the idea that the small extracellular vesicles contain Type VI Collagen, and this element of their cargo is modulating smooth muscle cell migration, is an intriguing aspect of the authors' working model. Nevertheless, the evidence supporting this potential mechanism does not quite fit together as presented. It is not entirely clear how the collagen VI within the vesicles is somehow accessed by the smooth muscle cell filopodia during migration. Are the vesicles lysed open once on the extracellular matrix? If so, what is the proposed mechanism for that to occur? If not, how are the adhesion molecules on the smooth muscle cell surface engaging the collagen VI fibers that are contained within the vesicles? This aspect of the model does not quite fit together with the proposed mechanism and may be an interesting speculative interpretation, warranting further investigation, but it should not be considered a strong conclusion with sufficient convincing data supporting this idea.

On a technical level, some of the statistical analysis is not readily understood from the data presented. It is very much appreciated that the authors show many of the graphs with technical and biological replicate values in addition to the means and standard deviations (though this is not clearly stated in all figure legends). However, in figures such as Figure 5, there are bars shown and indicated to be different by statistical comparison (see panel B in Figure 5). It is not clear how the values for Group 1 (no FN, no 3-OMS, no sEV) are statistically different (denoted by three asterisks but no p value provided in the legend) than Group 3 (no FN, 3-OMS added, no sEV), when their means and standard deviations appear almost identical. If this is an oversight, this needs to be corrected. If this is truly the outcome, further explanation is warranted. A higher level of transparency in such instances would certainly go a long way in helping address the current crisis of mistrust within the scientific community and at the interface with society at-large.

Reviewer #1 (Public Review):

Summary. In this investigation Kapustin et al. demonstrate that vascular smooth muscle cells (VSMCs) exposed to the extracellular matrix fibronectin stimulates the release of small extracellular vesicles (sEVs). The authors provide experimental evidence that stimulation of the actin cytoskeleton boosts sEV secretion and posit that sEVs harbor both fibronectin and collagen IV protein themselves which also, in turn, alter cell migration parameters. It is well established that fibronectin is associated with increased cell migration and adherence; therefore, this association with VSMCs is not novel. The authors purport that sEV are largely born of filopodia origin; however, this data is not well executed and seems generally at odds with the presented data. Similarly, the effect of sEVs on parameters of cell migration has almost no magnitude of effect, making mechanism exploration somewhat nebulous. Lastly, the proposed mechanism of VSMCs responding to, and depositing, ECM proteins via sEVs was not rigorously executed; again, making the conclusions challenging for the reader to interpret.

Strengths. The authors provide a comprehensive battery of cytoskeletal experiments to test how fibronectin and sEVs impact both sEV release and vascular smooth muscle cell migratory activation.

Weaknesses. Unfortunately, this article suffers from many weaknesses. First, the rigor of the experimental approach is low, which calls into question the merit of the conclusions. In this vein, there is a lack of proper controls or inclusion of experiments addressing alternative explanations for the phenotype or lack thereof.

Reviewer #1 (Public Review):

Summary:

HP1 plays a pivotal role in orchestrating chromatin packaging through the creation of biomolecular condensates. The existence of distinct homologs offers an intriguing avenue for investigating the interplay between genetic sequence and condensate formation. In this study, the authors conducted extensive coarse-grained simulations to delve into the phase separation behavior of HP1 paralogs. Additionally, the researchers delved into the captivating possibility of various HP1 paralogs co-localizing within assemblies composed of multiple components. Importantly, the study also delved into the critical role of DNA in finely tuning this complex process.

Strengths:

I applaud the authors for their methodical approach in conducting simulations aimed at dissecting the contributions of hinges, CTE, NTE, and folded regions. The comprehensive insights unveiled in Figure 3 compellingly substantiate the significance of these protein components in facilitating the process of phase separation.

This systematic exploration has yielded several innovative revelations. Notably, the authors uncovered a nuanced interplay between the folded and disordered domains. Although disordered regions have traditionally been linked to driving phase separation through their capacity for forming multivalent interactions, the authors have demonstrated that the contribution of the CD cannot be overlooked, as it significantly impacts the saturation concentration.

The outcomes of this study serve to elucidate the intricate mechanisms and regulatory aspects governing HP1 LLPS.

Weaknesses:

The authors do not provide an assessment of the quantitative precision of their model. To illustrate, HP1a is anticipated to undergo phase separation primarily under low salt concentrations. Does the model effectively capture this sensitivity to salt conditions? Regrettably, the specific salt conditions employed in the simulations are not explicitly stated. While I anticipate that numerous findings in the manuscript remain valid, it could be beneficial to acknowledge potential limitations tied to the simulations. For instance, might the absence of quantitative precision impact certain predictions, such as the CD's influence on phase separation?

Reviewer #2 (Public Review):

In this paper, Phan et al. investigate the properties of human HP1 paralogs, their interactions and abilities to undergo liquid-liquid phase separation. For this, they use a coarse-grained computational approach (validated with additional all-atom simulations) which allows to explore complex mixtures. Matching (wet-lab) experimental results, HP1 beta (HP1b) exhibits different properties from HP1 alpha and gamma (HP1a,g), in that it does not phase separate. Using domain switch experiments, the authors determine that the more negatively charged hinge in HP1b, compared to HP1a and HP1g, is mainly responsible for this effect. Exploring heterotypic complexes, mixtures between HP1 subtypes and DNA, the authors further show that HP1a can serve as a scaffold for HP1b to enter into condensed phases and that DNA can further stabilize phase separated compartments. Most interestingly, they show that a multicomponent mixture containing DNA, and HP1a and HP1b generates spatial separation between the HP1 paralogs: due to increased negative charge of DNA within the condensates, HP1b is pushed out and accumulates at the phase boundary. This represents an example how complex assemblies could form in the cell.<br /> Overall, this is purely computational work, which however builds on extensive experimental results (including from the authors). The methods showcase how coarse-grained models can be employed to generate and test hypotheses how proteins can condense. Applied to HP1 proteins, the results from this tour-de-force study are consistent and convincing, within the experimental constraints. Moreover, they generate further models to test experimentally, in particular in light of multicomponent mixtures.

There are, of course, some limitations to these models.

First, the CG models employed probably will not be able to pick up more complex structure-driven interactions (i.e. specific binding of a peptide in a protein cleft, including defined H-bonds, or induced structural elements). Some of those interactions (i.e. beyond charge-charge or hydrophobics) may also play a role in HP1, and might be ignored here. There is also the question of specificity, i.e. how can diverse phases coexist in cells, when the only parameters are charge and hydrophobicity? Does the arrangement of charges in the NTD, hinges and CTDs matter or are only the average properties important?

Second, the authors fix CSD-CSD dimers, whereas these interactions are expected to be quite dynamic. In the particular example of HP1 proteins, having dimerization equilibria may change the behavior of complex mixtures significantly, e.g. in view of the proposed accumulation of HP1b at a phase boundary. This point would warrant more discussion in the paper. Moreover, the biological plausibility of such a behavior would be interesting. Is there any experimental data supporting such assemblies?

Reviewer #1 (Public Review):

The authors have generated a set of yeast S. cerevisiae strains containing different numbers of chromosomes. Elimination of telomerase activates homologous recombination (HR) to maintain telomeres in cells containing the original 16 chromosomes. However, elimination of telomerase leads to circularization of cells containing a single or two chromosomes. The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes. They found that the subtelomeric sequences X and Y' are dispensable for cell proliferation and HR-mediated telomere maintenance in telomerase-minus SY12 cells. They conclude that subtelomeric X and Y' sequences do not play essential roles in both telomerase-proficient and telomerase-null cells and propose that these sequences represent remnants of genome evolution.<br /> Interestingly, telomerase-minus SY12 generate survivors that are different from Type I or Type II survivors.

Strengths: The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes.

Weaknesses:<br /> It is not determined how atypical survivors or Type X survivors are generated in telomerase-deficient SY12 cells.<br /> Survivor generation of each type (Type I, Type II, Type X or atypical and circularization) is not quantitated.

Reviewer #2 (Public Review):

Summary:<br /> In this work, Hu and colleagues investigate telomerase-independent survival in Saccharomyces cerevisiae strains engineered to have different chromosome numbers. The authors describe the molecular patterns of survival that change with fewer chromosomes and that differ from the well-described canonical Type I and Type II, including chromosome circularization and other atypical outcomes. They then take advantage of the strain with 3 chromosomes to examine the effect of deleting all the subtelomeric elements, called X and Y'. For most of the tested phenotypes, they find no significant effect of the absence of X- and Y'-element, and show that they are not essential for survivor formation. They speculate that X- and Y'-elements are remnants of ancient telomere maintenance mechanisms.

Strengths:<br /> This work advances our understanding of the telomerase-independent strategies available to the cell by altering the structure of the genome and of the subtelomeres, a feat that was enabled by the set of strains they engineered previously. By using strains with non-standard genome structures, several alternative survival mechanisms are uncovered, revealing the diversity and plasticity of telomere maintenance mechanisms. Overall, the conclusions are well supported by the data, with adequate sample sizes for investigating survivors. The molecular analyses mostly based on Southern blots are also very well-conducted.

Weaknesses:<br /> The qualification of survivor types mostly relies on molecular patterns in Southern blots. While this is a valid method for a standard strain, it might be more difficult to apply to the strains used in this study. For example, in SY8, SY11 and SY12, the telomere signal at 1-1.2 kb can be very faint due to the small number of terminal Y' elements left. As another example, for the Y'-less strain, it might seem obvious that no Type I survivor can emerge given that Y' amplification is a signature of Type I, but maybe Type-I-specific molecular mechanisms might still be used. To reinforce the characterization of survivor types, an analysis of the genetic requirements for Type I and Type II survivors (e.g. RAD51, RAD54, RAD59, RAD50) could complement the molecular characterization in specific result sections.

In the title, the abstract and throughout the discussion, the authors chose to focus on the effect of X- and Y'-element deletion on different phenotypes and on survivor formation, as the main message to convey. While it is a legitimate and interesting message, other important results of this work might benefit from more spotlight. Namely, the observation that strains with different chromosome numbers show different survivor patterns and that several survival strategies beyond Type I and II exist and can reach substantial frequencies depending on the chromosomal context.

In SY12 strain, while X- and Y'-elements are not essential for survivor emergence, they do modulate the frequency of each type of survivors, with more chromosome circularization events observed for SY12Y∆, SY12XY∆ and SY12XY∆+Y strains. This result should be stated and discussed, maybe alongside the change in survivor patterns in the other SY strains, to more accurately assess the roles of these subtelomeric elements.

Reviewer #3 (Public Review):

Summary:<br /> This study investigates subtelomeric repetitive sequences in the budding yeast Saccharomyces cerevisiae, known as Y' and X-elements. Taking advantage of yeast strain SY12 that contains only 3 chromosomes and six telomeres (normal yeast strains contain 32 telomeres) the authors are able to generate a strain completely devoid of Y'- and X-elements.

Strengths: They demonstrate that the SY12 delta XY strain displays normal growth, with stable telomeres of normal length that were transcriptionally silenced, a key finding with wide implications for telomere biology. Inactivation of telomerase in the SY12 and SY12 delta XY strains frequently resulted in survivors that had circularized all three chromosomes, hence bypassing the need for telomeres altogether. The SY12 and SY12 delta XY yeast strains can become a useful tool for future studies of telomere biology. The conclusions of this manuscript are mostly well supported by the data and are important for researchers studying telomeres.

Weaknesses: A weakness of the manuscript is the analysis of telomere transcriptional silencing. They state: "The results demonstrated a significant increase in the expression of the MPH3 and HSP32 upon Sir2 deletion, indicating that telomere silencing remains effective in the absence of X and Y'-elements". However, there are no statistical analyses performed as far as I can see. For some of the strains, the significance of the increased expression in sir2 (especially for MPH3) looks questionable. In addition, a striking observation is that the SY12 strain (with only three chromosomes) express much less of both MPH3 and HSP32 than the parental strain BY4742 (16 chromosomes), both in the presence and absence of Sir2. In fact, the expression of both MPH3 and HSP32 in the SY12 sir2 strain is lower than in the BY4742 SIR2+ strain. In addition, relating this work to previous studies of subtelomeric sequences in other organisms would make the discussion more interesting.

Reviewer #2 (Public Review):

Summary:<br /> This paper further investigates the role of self-assembly of ice-binding bacterial proteins in promoting ice-nucleation. For the P. borealis Ice Nucleating Protein (PbINP) studied here, earlier work had already determined clearly distinct roles for different subdomains of the protein in determining activity. Key players are the water-organizing loops (WO-loops) of the central beta-solenoid structure and a set of non-water-organizing C-terminal loops, called the R-loops in view of characteristically located arginines. Previous mutation studies (using nucleation activity as a read-out) had already suggested the R-loops interact with the WO loops, to cause self-assembly of PbINP, which in turn was thought to lead to enhanced ice-nucleating activity. In this paper, the activities of additional mutants are studied, and a bioinformatics analysis on the statistics of the number of WO- and R-loops is presented for a wide range of bacterial ice-nucleating proteins, and additional electron-microscopy results are presented on fibrils formed by the non-mutated PbINP in E coli lysates.

Strengths:<br /> -A very complete set of additional mutants is investigated to further strengthen the earlier hypothesis.<br /> -A nice bioinformatics analysis that underscores that the hypothesis should apply not only to PbINP but to a wide range of (related) bacterial ice-nucleating proteins.<br /> -Convincing data that PbINP overexpressed in E coli forms fibrils (electron microscopy on E coli lysates).

Weaknesses:<br /> -The new data is interesting and further strengthens the hypotheses put forward in the earlier work. However, just as in the earlier work, the proof for the link between self-assembly and ice-nucleation remains indirect. Assembly into fibrils is shown for E coli lysates expressing non-mutated pbINP, hence it is indeed clear that pbINP self-associates. It is not shown however that the mutations that lead to loss of ice-nucleating activity also lead to loss of self-assembly. A more quantitative or additional self-assembly assay could shine light on this, either in the present or in future studies.

-Also the "working model" for the self-assembly of the fibers remains not more than that, just as in the earlier papers, since the mutation-activity relationship does not contain enough information to build a good structural model. Again, a better model would require different kinds of experiments, that yield more detailed structural data on the fibrils.

Reviewer #1 (Public Review):

Summary: Hansen et al. dissect the molecular mechanisms of bacterial ice nucleating proteins mutating the protein systematically. They assay the ice nucleating ability for variants changing the R-coils as well as the coil capping motifs. The ice nucleation mechanism depends on the integrity of the R-coils, without which the multimerization and formation of fibrils are disrupted.

Strengths: The effects of mutations are really dramatic, so there is no doubt about the effect. The variants tested are logical and progressively advance the story. The authors identify an underlying mechanism involving multimerization, which is plausible and compatible with EM data. The model is further shown to work in cells by tomography.

Weaknesses: The theoretical model presented for how the proteins assemble into fibrils is simple, but not supported by much data.

Reviewer #3 (Public Review):

Summary: in this manuscript, Hansen and co-authors investigated the role of R-coils in the multimerization and ice nucleation activity of PbINP, an ice nucleation protein identified in Pseudomonas borealis. The results of this work suggest that the length, localization, and amino acid composition of R-coils are crucial for the formation of PbINP multimers.

Strengths: The authors use a rational mutagenesis approach to identify the role of the length, localisation, and amino acid composition of R-coils in ice nucleation activity. Based on these results, the authors hypothesize a multimerization model. Overall, this is a multidisciplinary work that provides new insights into the molecular mechanisms underlying ice nucleation activity.

Weaknesses: Several parts of the work appear cryptic and unsuitable for non-expert readers. The results of this work should be better described and presented.

Reviewer #3 (Public Review):

ZMYM2 is a transcriptional repressor known to bind to the post-translational modification SUMO2/3. It has been implicated in the silencing of genes and transposons in a variety of contexts, but lacking sequence-specific DNA binding, little is known about how it is targeted to specific regions. At least two reports indicate association with TRIM28 targets (Tsusaka 2020 Epigenetics & Chromatin, Graham-Paquin 2023 NAR) but no physical association with TRIM28 targets had been demonstrated. Tsusaka 2020 theorizes an indirect, potentially SUMO-independent, interaction via ATF7IP and SETDB1.

Here, Owen and colleagues show that a subset of ZMYM2-binding sites in U2OS cells are clearly TRIM28 sites, and further find that hundreds of genes are silenced by both ZMYM2 and TRIM28. They next demonstrate that ZMYM2 homes to chromatin, and interacts with TRIM28, in a SUMOylation-dependent manner, suggesting that ZMYM2 is recognizing SUMOylation on TRIM28 or a protein associated with TRIM28. ZMYM2 separately homes to SINE elements bound by the ChAHP complex in an apparently SUMOylation independent manner. Although this is not the first report to show physical interaction between ZMYM2 and ChAHP, it is the first to show that ZMYM2 homes to ChAHP-binding sites and functions as a corepressor at these sites. Finally the authors demonstrate that ZMYM2 and TRIM28 coregulate genic targets by inducing repression at LTRs within the same TADs as the genes in question.

Overall, the manuscript is well-written, convincing, and fills a significant hole in our understanding of ZMYM2's mechanistic function. The revised version of this manuscript addresses all of my previous concerns well.

Reviewer #1 (Public Review):

Owen D et al. investigated the protein partners and molecular functions of ZMYM2, a transcriptional repressor with key roles in cell identity and mutated in several human diseases, in human U2OS cells using mass spectrometry, siRNA knockdown, ChIP-seq and RNA-seq. They tried to identify chromatin bound complexes containing ZMYM2 and identified known and novel protein partners, including ADNP and the newly described partner TRIM28. Focusing mainly on these two proteins, they show that ZMYM2 physically interacts with ADNP or TRIM28, and co-occupies an overlapping set of genomic regions with ADNP and TRIM28. By generating a large set of knockdown and RNA-seq experiments, they show that ZMYM2 co-regulates a large number of genes with ADNP and TRIM28 in U2OS cells. Interestingly, ZMYM2-TRIM28 do not appear to repress genes directly at promoters, but the authors find that ZMYM2/TRIM28 repress LTR elements and suggest that this leads to gene deregulation at distance by affecting the chromatin environment within TADs.

A strength of the study is that, compared to previous studies of ZMYM2 protein partners, it investigates binding partners of ZMYM2 using the RIME method on chromatin. The RIME method makes it possible to identify low-affinity protein-protein interactions and proteins interactions occurring at chromatin, therefore revealing partners most relevant for gene regulation at chromatin. This allowed the identification of novel ZMYM2 partners not identified before, such as TRIM28.

The authors present solid interaction data with appropriate controls and generated an impressive amount of datasets (ChIP-seq for TRIM28 and ADNP, RNA-seq in ZMYM2, ADNP and TRIM28 knockdown cells) that are important to understand the molecular functions of ZMYM2. These datasets were generated with replicates and will be very useful for the scientific community. This study provides important novel insights into the molecular roles of ZMYM2 in human U2OS cells.

Reviewer #2 (Public Review):

In this study the authors investigate functional associations made by transcription factor ZMYM2 with chromatin regulators, and the impact of perturbing these complexes on the transcriptome of the U2OS cell line. They focus on validating two novel chromatin-templated interactions: with TRIM28/KAP1 and with ADNP, concluding that via these distinct chromatin regulators, ZMYM2 contributes to transcriptional control of LTR and SINE retrotransposons, respectively.

Strengths of the study:

-The co-localization of ZMYM2 with ADNP and TRIM28 is validated through RIME, ChIP-seq and co-IP. Since TRIM28 is a highly abundant nuclear protein, the use of multiple methods is important to add confidence in particular for the novel (SUMO-dependent interaction identified between ZMYM2 and TRIM28. That TRIM28 pulls down less of the ZMYM2-SIM mutant is reassuring.

-It is good that uniquely-mapped reads are used in the ChIP-seq analysis given the interest in repetitive elements. Likewise, though the RT-qPCR data in Fig 6 should be complemented by analysis of the RNA-seq data that the authors already have, it seems that the primers are carefully designed such that a single retrotransposon copy is amplified.

-The paper is generally written very clearly, the experiments well done and the different datasets appear to be robust.

Weaknesses of the study:

-The transcriptional response using bulk RNA-seq in ZMYM2-depleted cells remains gene-centric despite the title of the paper being about TE transcription. In fact, the only panels about TE transcription are the RT-qPCR data in Fig 6D, F. During the revision the authors said that their RNA-seq data is unfortunately too shallow to retrieve TEs. Fair enough - however, it remains the case that the central claim is control of TE transcription by ZMYM2. Thus, without additional transcriptomic analysis we are left with only a few qPCRs, even if they are nicely done! Perhaps the title could be modified a bit in that case?

-The mechanism by which ZMYM2 and TRIM28 work together does remain a mystery. Following review the authors performed TRIM28 ChIP on ZMYM2-depleted cells, but identified no changes over three transposons. It remains unclear if H3K9me3 levels are altered.

Reviewer #2 (Public Review):

This study aims to investigate the mediatory role of intestinal ILC3-derived IL-22 in intermittent fasting-elicited metabolic benefits.

Strengths:<br /> The observation of induction of IL-22 production by intestinal ILC3 is significant, and the scRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding.

Weaknesses:<br /> The experimental design for some studies needs to be improved to enhance the rigor of the overall study. There is a lack of direct evidence showing that the metabolically beneficial effects of IF are mediated by intestinal ILC3 and their derived IL-22. The mechanism by which IL-22 induces a thermogenic program is unknown. The browning effect induced by IF may involve constitutive activation of lipolysis, which was not considered.

Reviewer #3 (Public Review):

Chen et al. investigated how intermittent fasting causes metabolic benefits in obese mice and found that intestinal ILC3 and IL-22-IL-22R signaling contribute to the beiging of white adipose tissue (WAT) and consequent metabolic benefits including improved glucose and lipid metabolism in diet-induced obese mice. They demonstrate that intermittent fasting causes increased IL22+ILC3 in small intestines of mice. Adoptive transfer of purified intestinal ILC3 or administration of exogenous IL-22 can lead to increases in UCP1 gene expression and energy expenditure as well as improved glucose metabolism. Importantly, the above metabolic benefits caused by intermittent fasting are abolished in IL-22R-/- mice. Using an in vitro experiment, the authors show that ILC3-derived IL-22 may directly act on adipocytes to promote SVF beige differentiation. Finally, by performing sc-RNA-seq analysis of intestinal immune cells from mice with different treatments, the authors indicate a possible way of intestinal ILC3 being activated by intermittent fasting. Overall, this study provides a new mechanistic explanation for the metabolic benefits of intermittent fasting and reveals the role of intestinal ILC3 in the enhancement of the whole-body energy expenditure and glucose metabolism likely via IL-22-induced beige adipogenesis.

Although this study presents some interesting findings, particularly IL-22 derived from intestinal ILC3 could induce beiging of WAT by directly acting on adipocytes, the experimental data are not sufficient to support the key claims in the manuscript.

Reviewer #1 (Public Review):

In the present study, the authors carefully evaluated the metabolic effects of intermittent fasting on normal chow and HFD fed mice and reported that intermittent fasting induces beiging of subcutaneous white adipose tissue. By employing complementary mouse models, the authors provided compelling evidence to support a mechanism through ILC3/IL-22/IL22R pathway. They further performed comprehensive single-cell sequencing analyses of intestinal immune cells from lean, obese, obese undergone intermittent fasting mice and revealed altered interactome in intestinal myeloid cells and ILC3s by intermittent fasting via activating AhR. Overall, this is a very interesting and timely study uncovering a novel connection between intestine and adipose tissue in the context of executing metabolic benefits of intermittent fasting.

Joint Public Review:

Smirnova et al. present a cryo-EM structure of human SIRT6 bound to a nucleosome as well as the results from molecular dynamics simulations. The results show that the combined conformational flexibilities of SIRT6 and the N-terminal tail of histone H3 limit the residues with access to the active site, partially explaining the substrate specificity of this sirtuin-class histone deacetylase. Two other groups have recently published cryo-EM structures of SIRT6:nucleosome complexes; this manuscript confirms and complements these previous findings, with the addition of some novel insights into the role of structural flexibility in substrate selection.

This manuscript is the third in a recent series of reports of cryo-EM structures of Sirt6:nucleosome complexes. The main conclusions of the three studies are similar, but this manuscript from Smirnova et al. includes additional molecular dynamics analysis of the histone tails. These studies suggest that part of the specificity for sites on the H3 tail is the result of only this tail having significant access to the active site. The results are partially validated by showing that H3-K27Ac is sometimes found near the active site in the simulations, and is a weak substrate for the deacetylase in vitro. All of the structures show Sirt6 contacting the acidic patch of H2A-H2B, partial displacement of the H2A C-terminal tail, and displacement of the DNA at the entry-exit site to "unclamp" the H3 N-terminal tail. This manuscript provides additional support for the conclusions drawn in the first two published structures, adds molecular dynamics simulations that provide further insight and includes a biochemical assay that helps to resolve an apparent conflict regarding the deacetylation of H3-K27Ac from the other two papers.

Reviewer #1 (Public Review):

In this study, Satake and colleagues endeavored to explore the rates and patterns of somatic mutations in wild plants, with a focus on their relationship to longevity. The researchers examined slow- and fast-growing tropical tree species, demonstrating that slow-growing species exhibited five times more mutations than their fast-growing counterparts. The number of somatic mutations was found to increase linearly with branch length. Interestingly, the somatic mutation rate per meter was higher in slow-growing species, but the rate per year remained consistent across both species. A closer inspection revealed a prevalence of clock-like spontaneous mutations, specifically cytosine-to-thymine substitutions at CpG sites. The author suggested that somatic mutations were identified as neutral within an individual, but subject to purifying selection when transmitted to subsequent generations. The authors developed a model to assess the influence of cell division on mutational processes, suggesting that cell-division independent mutagenesis is the primary mechanism.

The authors have gathered valuable data on somatic mutations, particularly regarding differences in growth rates among trees. Their meticulous computational analysis led to fascinating conclusions, primarily that most somatic mutations accumulate in a cell-division independent manner. The discovery of a molecular clock in somatic mutations significantly advances our comprehension of mutational processes that may generate genetic diversity in tropical ecosystems. The interpretation of the data appears to be based on the assumption that somatic mutations can be effectively transmitted to the next generation unless negative selection intervenes. However, accumulating evidence suggests that plants may also possess "effective germlines," which could render the somatic mutations detected in this study non-transmittable to progeny. Incorporating additional analyses/discussion in the context of plant developmental biology, particularly recent studies on cell lineage, could further enhance this study.

Specifically, several recent studies address the topics of effective germline in plants. For instance, Robert Lanfear published an article in PLoS Biology exploring the fundamental question, "Do plants have a segregated germline?" A study in PNAS posited that "germline replications and somatic mutation accumulation are independent of vegetative life span in Arabidopsis." A phylogenetic-based analysis titled "Rates of Molecular Evolution Are Linked to Life History in Flowering Plants" discovered that "rates of molecular evolution are consistently low in trees and shrubs, with relatively long generation times, as compared with related herbaceous plants, which generally have shorter generation times." Another compelling study, "The architecture of intra-organism mutation rate variation in plants," published in PLoS Biology, detected somatic mutations in peach trees and strawberries. Although some of these studies are cited in the current work, a deeper examination of the findings in relation to the existing literature would strengthen the interpretation of the data.

Reviewer #2 (Public Review):

In this manuscript, the authors used an original empirical design to test if somatic mutation rates are different depending on the plant growth rates. They detected somatic mutations along the growth axes of four trees - two individuals per species for two dipterocarp tree species growing at different rates. They found here that plant somatic mutations are accumulated are a relatively constant rate per year in the two species, suggesting that somatic mutation rates correlate with time rather than with growth, i.e. the number of cell divisions. The authors then suggest that this result is consistent with a low relative contribution of DNA replication errors (referred to as α in the manuscript) to the somatic mutation rates as compared to the other sources of mutations (β). Given that plants - in particular, trees - are generally assumed to deviate from the August Weismann's theory (a part of the somatic variation is expected to be transmitted to the next generation), this work could be of interest for a large readership interested by mutation rates as a whole, since it has implications also for heritable mutation rates too. In addition, even if this is not discussed, the putatively low contribution of DNA replication errors could help to understand the apparent paradox associated to trees. Indeed, trees exhibit clear signatures of lower molecular evolution (Lanfear et al. 2013), therefore suggesting lower mutation rates per unit of time. Trees could partly keep somatic mutations under control thanks to a long-term evolution towards low α values, resulting in low α/β ratios as compared to short-lived species. I therefore consider that the paper tackles a fundamental albeit complex question in the field.

Overall, I consider that the authors should clearly indicate the weaknesses of the studies. For instance, because of the bioinformatic tools used, they have reasonably detected a small part of the somatic mutations, those that have reached a high allele frequency in tissues. Mutation counts are known to be highly dependent on the experimental design and the methods used. Consequently, (i) this should be explicit and (ii) a particular effort should be made to demonstrate that the observed differences in mutation counts are robust to the potential experimental biases. This is important since, empirically, we know how mutation counts can vary depending on the experimental designs. For instance, a difference of an order of magnitude has been observed between the two papers focusing on oaks (Schmid-Siegert et al. 2017 and Plomion et al. 2018) and this difference is now known to be due to the differences in the experimental designs, in particular the sequencing effort (Schmitt et al. 2022).

Having said that, my overall opinion is that (i) the authors have worked on an interesting design and generated unique data, (ii) the results are probably robust to some biases and therefore strong enough (but see my comments regarding possible improvements), (iii) the interpretations are reasonable and (iv) the discussion regarding the source of somatic mutations is valuable (even if I also made some suggestions here also).

Reviewer #3 (Public Review):

In animals, several recent studies have revealed a substantial role for non-replicative mutagenic processes such as DNA damage and repair rather than replicative error as was previously believed. Much less is known about how mutation operates in plants, with only a handful of studies devoted to the topic. Authors Satake et al. aimed to address this gap in our understanding by comparing the rates and patterns of somatic mutation in a pair of tropical tree species, slow-growing Shorea lavis and fast-growing S. leprosula. They find that the yearly somatic mutation rates in the two species is highly similar despite their difference in growth rates. The authors further find that the mutation spectrum is enriched for signatures of spontaneous mutation and that a model of mutation arising from different sources is consistent with a large input of mutation from sources uncorrelated with cell division. The authors conclude that somatic mutation rates in these plants appears to be dictated by time, not cell division numbers, a finding that is in line with other eukaryotes studied so far.

In general, this work shows careful consideration and study design, and the multiple lines of evidence presented provide good support for the authors' conclusions. In particular, they use a sound approach to identify rare somatic mutations in the sampled trees including biological replicates, multiple SNP-callers and thresholds, and without presumption of a branching pattern.

Inter-species comparisons of absolute mutation rates is challenging. This is largely due to differences in SNP-calling methods and reference genome quality leading to variable sensitivity and specificity in identifying mutations. By applying their pipeline consistently across both species, the authors provide confidence in the comparative mutation rate results. Moreover, the presented false negative and false positive rate estimates for each species would apparently have minimal impact on the overall findings.

Despite the overall elegance of the authors' experimental setup, one methodological wrinkle warrants consideration. The authors compare the mutation rate per meter of growth, demonstrating that the rate is higher in slow-growing S. laevis: a key piece of evidence in favor of the authors' conclusion that somatic mutations track absolute time rather than cell division. To estimate the mutation rate per unit distance, they regress the per base-pair rate of mutations found between all pairwise branch tips against the physical distance separating the tips (Fig. 2a). While a regression approach is appropriate, the narrowness of the confidence interval is overstated as the points are not statistically independent: internal branches are represented multiple times. (For example, all pairwise comparisons involving a cambium sample will include the mutations arising along the lower trunk.) Regressing rates and lengths of distinct branches might be more appropriate. Judging from the data presented, however, the point estimates seem unlikely to change much.

This work deepens our understanding of how mutation operates at the cellular level by adding plants to the list of eukaryotes in which many mutations appear to derive from non-replicative sources. Given these results, it is intriguing to consider whether there is a fundamental mechanism linking mutation across distantly related species. Plants, generally, present a unique opportunity in the study of mutation as the germline is not sequestered, as it is in animals, and thus the forces of both mutation and selection acting throughout an individual plant's life could in principle affect the mutations transmitted to seed. The authors touch on this aspect, finding no evidence for a reduction in non-synonymous somatic mutations relative to the background rate, but more work-both experimental and observational-is needed to understand the dynamics of mutation and cell-competition within an individual plant. Overall, these results open the door to several intriguing questions in plant mutation. For example, is somatic mutation age-dependent in other species, and do other tropical plants harbor a high mutation rate relative to temperate genera? Any future inquiries on this topic would benefit from modeling their approach for identifying somatic mutations on the methods laid out here.

Reviewer #1 (Public Review):

The authors have employed a digital twin approach to show that depending on the underlying disease mechanism, a digital replica constructed from human data can both recapitulate clinical findings, but also provide important insights into the fundamental disease state by revealing underlying contributing mechanisms. Moreover, the authors are able to show that a disease state caused by two different underlying genetic anomalies exhibit different electrical and morphological profiles.

This is important information as it allows for potential stratification of treatment approaches in future cases based on underlying phenotype by linking it to specific genotype properties. One of the most innovative aspects of the study is the mismatch switching between personalized structure, remodeling and genotype specific electrophysiological properties. The approach is elegant and allows for further exposure of the key mechanisms that contribute to the development of ventricular tachycardia circuits. One addition that could add more insight is to predict the effect of structural remodeling alone well, considering only normal electrophysiological models. Another interesting approach would be a sensitivity analysis, to determine how sensitive the VT circuits are to the specific geometry of the patient and remodeling that occurs during the disease, such an approach could also be used to determine how sensitive the outputs are to electrophysiological model inputs.

Reviewer #2 (Public Review):

The authors of this paper use a "digital twin" computational model of electrophysiology to investigate the pathology of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) in several patients undergoing Electro-Physiological Studies (EPS) to treat Ventricular Tachycardias (VTs). The digital twin computational models are customised to the individual patient in two ways. Firstly, information on the patient's heart geometry and muscle/fibrous structure is extracted from Late Gadolium-Enhanced Magnetic Resonance Image (LGE-MRI) scans. Secondly, information from the patient's genotype is used to decide the particular electrophysiological cell model to use in the computational model. The two patient genotypes investigated include a Gene Ellusive (GE) group characterised by abnormal fibrous but normal cell electrical physiology and a palakophilin-2 (PKP2) group in which patients have abnormal fibrotic remodelling and distorted electrical conduction. The computational model predicts the locations and pathways of re-entrant circuits that cause VT. The model results are compared to previous recordings of induced VTs obtained from EPS studies.

The paper is very well written, and the modelling study is well thought out and thorough and represents an exemplar in the field. The major strengths of the paper are the use of a personalised patient model (geometry, fibrous structure and genotype) in a clinically relevant setting. Such a comprehensive personal model puts this paper at the forefront of such models in the field. The main weaknesses of the paper are more of a reflection on what is required for creating such models than on the study itself. As the authors acknowledge, the number of patients in each group is small. Additional patients would allow for statistical significance to be investigated.

The paper's authors set out to demonstrate the use of a "digital twin" computational model in the clinical setting of ARVC. The main findings of the paper were threefold. Firstly, the locations of VTs could be accurately predicted. There was a difference in the abnormal fibrous structure between the two genotype groups. Finally, there was an interplay between the fibrous structure of the heart and the cellular electrophysiology in that the fibrous remodelling was responsible for VTs in the GE group, but in the PKP2 group VTs were caused by slowed electrical conduction and altered restitution. The study successfully met the aims of the paper.

The major impact of the paper will be in demonstrating that a personalised computational model can a) be developed from available measurements (albeit at the high end of what would normally be measured clinically) and b) generate accurate results that may prove helpful in a clinical setting. Another impact is the finding in the paper that the cause of VTs may be different for the two genotypes investigated. The different interplay between fibrous and electrophysiology suggested by the modelling results may provide insights into different treatments for the different genotypes of the pathology. The authors use open-source software and have deposited all non-confidential data in publically available repositories.

Reviewer #3 (Public Review):

Overview<br /> The authors propose a personalized ventricular computational model (Geno-DT) that incorporates the patient's structural remodeling (fibrosis and scar locations based on LGE-CMR scans) as well as genotyping (cell membrane kinetics based on genetic testing results) to predict VT locations and morphologies in ARVC setting.<br /> To test the model, the authors conducted a retrospective study using 16 ARVC patient data with two genotypes (PKP2, GE) and reported high degree of sensitivity, specificity, and accuracy. In addition, the authors determined that in GE patients, VT was driven by fibrotic remodeling, whereas, in PKP2 patients, VT was associated with a combination of structural and electrical remodeling (slowed conduction and altered restitution).<br /> Based on the findings, the authors recommend using Geno-DT approach to augment therapeutic accuracy in treatment of ARVC patients.

Critiques<br /> 1. The small sample size is a limitation but has already been acknowledge and documented by the authors.<br /> 2. Another limitation is the consideration of only two of the possible genotypes in developing the cell membrane kinetics, but again has acknowledged by the authors.

Final Thoughts<br /> The authors have done a commendable job in targeting a disease phenotype that is relatively rare, which constrains the type of data that can be collected for research. Their personalized computational model approach makes a valuable contribution in furthering our understanding of ARVC mechanisms.

Reviewer #1 (Public Review):

The research titled "Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli" by Lin Chao, Chun Kuen Chen, Chao Shi, and Camilla U. Rang addresses the asymmetric distribution of ribosomes in single E. coli cells during aging by time-lapse microscopy, as well as its correlation to protein misfolding. The presented research is an important contribution to the field of protein biosynthesis pathways and their link to aging, especially in regard to the thorough analysis of variation in cell elongation rate in old and new daughter cells derived from old and new mother cells. However, the imaging results, analysis, and methodologies require substantial elaboration, as in its current form several key characteristics remain unanswered. Furthermore, the results should be compared and discussed in regard to several other reports, which analyzed ribosome asymmetric distribution and inheritance in E.coli, see detailed comments below.

Major comments:<br /> *It is not clear from the results or the material and methods sections how the authors define and detect old vs. new mother cells up to 128 cells division, which is the limit the manuscript describes in line 574: "To avoid effects of crowding within the micro-colonies, movies were ended when micro-colonies exceeded 128 cells". The results described only refer to 3 cell divisions (Fig.1 for example). As this is the key issue the manuscript addresses this requires elaboration.

* The authors should present several representative images of the results described, including: "New daughters at birth from old mothers have more ribosomes" - this should include clear quantification, of normalized fluorescence intensity vs. normalized cell length, as well as for "Ribosomal asymmetry between daughters are spatially in place in mothers before division"(line 218) for example. This should include annotation of the exact time points in minutes. The quantification can be done and presented as in their previous work, which provides the basis for this study: (Figure 2b, for example) "Allocation of gene products to daughter cells is determined by the age of the mother in single Escherichia coli cells" Chao Shi, Lin Chao, Audrey Menegaz Proenca, Andrew Qiu, Jasper Chao and Camilla U. Rang, May 2020, https://doi.org/10.1098/rspb.2020.0569.

* Quantification of variations over generations time during the time lapse is required: the change in cell-length (y-axis, the length of full-grown cell normalized to 1) vs. ribosomes number (y-axis) relative to the generation time analysis should be presented, based on the time-lapse images. The mean from ~10 independent cells should be presented, as in many similar research, for example: "Organization of Ribosomes and Nucleoids in Escherichia coli Cells during Growth and in Quiescence" Qian Chai, Bhupender Singh, Kristin Peisker, Nicole Metzendorf, Xueliang Ge, Santanu Dasgupta, Suparna Sanyal, 2014, JBC (Figure 3b).

* The distribution of ribosomes should be compared to the nucleoid distribution, as this is a major factor in RNA and translation distribution in bacterial cells (for example Gray, W. T., Govers, S. K., Xiang, Y., Parry, B. R., Campos, M., Kim, S., & Jacobs-Wagner, C. (2019). Nucleoid size scaling and intracellular organization of translation across bacteria. Cell, 177(6), 1632-1648.e20. https://doi.org/10.1016/j.cell.2019.05.017 , as reviewed in RNA localization in prokaryotes: Where, when,how, and why, Mikel Irastortza-Olaziregi, Orna Amster-Choder, 2020). The authors should add and discuss this, or elaborate on the reasons to omit this analysis.

* The results should be compared and discussed in regard to several other reports, which analyzed ribosome asymmetric distribution and inheritance in E.coli by tagging different ribosomal proteins, as well as different methodologies, including:

Organization of Ribosomes and Nucleoids in Escherichia coli Cells during Growth and in Quiescence" Qian Chai, Bhupender Singh, Kristin Peisker, Nicole Metzendorf, Xueliang Ge, Santanu Dasgupta, Suparna Sanyal, 2014, JBC

Gray, W. T., Govers, S. K., Xiang, Y., Parry, B. R., Campos, M., Kim, S., & Jacobs-Wagner, C. (2019). Nucleoid size scaling and intracellular organization of translation across bacteria. Cell, 177(6), 1632-1648.e20. https://doi.org/10.1016/j.cell.2019.05.017

Spatiotemporal Organization of the E. coli Transcriptome: Translation Independence and Engagement in Regulation Graphical Abstract Highlights d RNAs in E. coli exhibit asymmetric distribution on a transcriptome-wide scale, Shanmugapriya Kannaiah, Jonathan Livny, Orna Amster-Choder, 2019

Several of the findings reported, including asymmetric ribosome distribution and inheritance levels seem different than the ones reported here. This should be discussed in regard to the different methodologies.

Reviewer #2 (Public Review):

In the article "Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli" the authors discovered that the aging process correlates with lower cellular levels of ribosomes in Escherichia coli. The article is well-written and easy to follow and understand. The experiments are conducted rigorously with the appropriate controls. However, it is not novel and exhaustive enough. In particular, the causes and effects of this spatial and temporal distribution of ribosomes have not been investigated. What happens when this distribution is perturbed? Does stress influence this distribution? What is the biological significance of this distribution? These are examples of questions that should be addressed in order to broaden the interest of the paper.

Reviewer #3 (Public Review):

Summary:<br /> During successive rounds of cell division in E. coli, a lineage of increasingly aging progeny arises whose members exhibit decreased elongation rates, increased accumulation of inclusion bodies, and reduced gene expression. These hallmarks of physiological aging point to an evolutionary antecedent to the better-studied phenomenon of biological aging in eukaryotic systems. In this work, the authors find an upstream phenotype attributable to this aging lineage of E. coli cells: a marked decrease in cellular ribosome levels. The authors conjecture that such an upstream effect may have cascading effects on cellular metabolism and reduced gene expression. This is a new hypothesis that challenges the more broadly held view that toxicity from protein aggregates asymmetrically retained by mother cells is the cause of asymmetric growth rates. The thesis and the broad scope that it entails offer a number of exciting directions to engage with in the future.

Strengths:<br /> The authors' single-cell analysis convincingly shows differential partitioning of ribosomes that correlates with growth (elongation) rates between daughter cells. This makes the authors' novel hypothesis that asymmetric ribosome partitioning determines asymmetric cell growth plausible.

Weaknesses:<br /> The authors' did not measure levels of misfolded proteins in mother and daughter cells to distinguish between a toxicity model (retained aggregates are toxic to older cells) and a protein synthesis disadvantage model (less ribosomes, slower growth in older cells) to explain slower growth in aged cells. Therefore, while the authors' hypothesis is plausible, it is not the sole potential mechanism that explains their observations.

Reviewer #1 (Public Review):

Summary:<br /> Here the authors have tethered a Pgp substrate to strategically place cysteine residues in the protein. Notably, the cysteine-linked substrate (ANC-DNPT)- stimulates ATP hydrolyse and so is able to undergo IF to OF transitions. The authors then determined cryo-EM structures of these complexes and MD simulations of bound states. By capturing unforeseen OF conformations with substate they propose that TM1 undergoes local conformational changes that are sufficient to translocate substrates, rather than large bundle movements.

Strengths:<br /> This paper provides the first substrate (ANC-DNPT)- bound conformations of PgP and a new mechanistic model of how substrates are translocated.

Weaknesses:<br /> Although the cross-links stimulate ATP hydrolysis, further controls are needed to convince me that the TM1 conformations observed in the structures are physiologically relevant, since they have been trapped by "large" substrates covalently-tethered by cross-links.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Gewering and coworkers is an elegant mechanistic investigation of the mammalian multidrug transporter Pgp. I will not elaborate on the significance of this protein except to point out its clinical involvement in cancer resistance to chemotherapy.

Strengths:<br /> The strengths of the investigation are partly in the combination of sophisticated chemical synthesis, state-of-the-art cryoEM in a well-established biochemical context. What is more exciting is the tackling of a long-standing question in the field: namely how do drugs make their way through the structure to be exported across the membrane? Unfortunately, the field has been stuck in hand waving model based on structures that in the outward-facing conformations are devoid of substrates. The work challenges the dogma that emerged from this hand-waving model and presents an alternative model that appears to be supported by the data.

Weaknesses:<br /> There is much to like about the experimental work here but I am less sanguine on the interpretation. The main idea is to covalently link via disulfide bonds a model tripeptide substrate under different conditions that mimic transport and then image the resulting conformations. The choice of the Pgp cysteine mutants here is critical but also poses questions regarding the interpretation. What seems to be missing, or not reported, is a series of control experiments for further cysteine mutations.

Reviewer #3 (Public Review):

Summary:<br /> The authors employed a new strategy, covalent substrate-labeling, to address the open issue of the substrate transport mechanism by single particle cryogenic-EM. A cyclic peptide (QZ-Ala), which was already used in the past as a substrate for structural purposes, was modified and covalently attached to ABCB1 at strategic positions in the transmembrane domain via Cys-specific coupling chemistry. Overall, four mutations (two per TMD) were generated and functionally analyzed. These residues are in proximity to the QZ-Ala binding site and are labeled by verapamil. Interestingly, two mutants could only be labeled if ATP and Mg2+ were present.

Strengths:<br /> Three of the four mutants were structurally analyzed by single particle cryo-EM with structures in both, the inward- and outward-facing conformation and overall resolutions ranging from 2.6 to 4.3 Å. Applying multi-model analyses allowed for the extraction of additional structures from one data set. These structures formed the basis for a detailed analysis of the substrate translocation pathway. This enabled the researcher to compare the IF and OF states of the same mutant and same substrate, which is pivotal for their conclusions. The mutations 335/978 trap the substrate at different points of the translocation pathway, while 971 located two helical turns away from the first set, trapped the system at a later stage. The described strategy revealed a cascade of conformational changes during substrate transport which focus on TMH1, which is straight in the IF state, but swings out in the OF state. Pivotal for such a change is G72. This residue was mutated to Ala and also structurally analyzed. These structures were supported by MD simulations and functional data. Thus, the new prosed kinking and straightening mechanisms are different from the so far accepted wide-open OF state observed in bacterial transporters. This clearly suggests a different mechanism for ABCB1.

Weaknesses:<br /> I have a couple of minor issues that I have listed in the section recommendations for authors Overall, the manuscript is very well written, sheds new light on the molecular mechanism of substrate translocation by ABCB1, and might even provide a new starting point for inhibitor design. I know that it is unusual, but I like the manuscript in its current version and recommend acceptance in its current form.

Reviewer #1 (Public Review):

In their article, "Cis-regulatory modes of Ultrabithorax inactivation in butterfly forewings," Tendolkar and colleagues explore Ubx regulation in butterflies. The authors investigated how Ubx expression is restricted to the hindwing in butterflies through a series of genomic analyses and genetic perturbations. The authors provide evidence that a Topoologiacally Associated Domain (TAD) maintains a hindwing-enriched profile of chromatin around Ubx, largely through an apparent boundary element. CRISPR mutations of this boundary element led to ectopic Ubx expression in forewings, resulting in homeotic transformation in the wings. The authors also explore the results of the mutation in two non-coding RNA regions as well as a possible enhancer module. Each of these induces homeotic phenotypes. Finally, the authors describe a number of homeotic phenotypes in butterflies, which they relate to their work.

Together, this was an interesting paper with compelling initial data. That said, I have several items that I feel would warrant further discussion, presentation, or data.

First, I would not state, "Little is known about how Hox genes are regulated outside of flies." They should add "in insects" since so much in known in vertebrates

For Figure 1, it would aid the readers if the authors could show the number of RNAseq reads across the locus. This would allow the readership to evaluate the frequency of the lncRNAs, splice variants, etc.

How common are boundary elements within introns? Typically, boundary elements are outside gene bodies, so this could be explored further. This seems like an interesting bit of biology which, following from the above point, it would be interesting to, at a minimum, discuss, but also relate to how transcription occurs through a possible boundary element (are there splice variants, for example?).

The CRISPR experiments led to compelling phenotypes. However, as a Drosophila biologist, I found it hard to interpret the data from mosaic experiments. For example, in control experiments, how often do butterflies die? Are there offsite effects? It's striking that single-guide RNAs led to such strong effects. Is this common outside of this system? Is it possible to explore the function effects at the boundary element - are these generating large deletions (for example, like Mazo-Vargas et al., 2022)?

For the mosaic experiments, how frequent are these effects in nature or captive stocks? Would it be possible to resequence these types of effects? At the moment, this data, while compelling, was hard to put into the context of the experiments above without understanding how common the effects are. Ideally, there would be resequencing of these tissues, which could be targeted, but it was not clear to me the general rates of these variants.

In sum, I enjoyed the extensive mosaic perturbations. However, I feel that more molecular descriptions would elevate the work and make a larger impact on the field.

Reviewer #2 (Public Review):

Summary:<br /> The existence of hox gene complexes conserved in animals with bilateral symmetry and in which the genes are arranged along the chromosome in the same order as the structures they specify along the anteroposterior axis of organisms is one of the most spectacular discoveries of recent developmental biology. In brief, homeotic mutations lead to the transformation of a given body segment of the fly into a copy of the next adjacent segment. For the sake of understanding the main observation of this work, it is important to know that in loss-of-function (LOF) alleles, a given segment develops like a copy of the segment immediately anterior to it, and in gain-of-function mutations (GOF), the affected segment develops like a copy of the immediately posterior segment. Over the last 30 years the molecular lesions associated with GOF alleles led to a model where the sequential activation of the hox genes along the chromosome result from the sequential opening of chromosomal domains. Most of these GOF alleles turned out to be deletions of boundary elements (BE) that define the extent of the segment-specific regulatory domains. The fruit fly Drosophila is a highly specialized insect with a very rapid mode of segmentation. Furthermore, the hox clusters in this lineage have split. Given these specificities it is legitimate to question whether the regulatory landscape of the BX-C we know of in D.melanogaster is the result of very high specialization in this lineage, or whether it reflects a more ancestral organization. In this article, the authors address this question by analyzing the continuous hox cluster in butterflies. They focus on the intergenic region between the Antennapedia and the Ubx gene, where the split occurred in D.melanogaster. Hi-C and ATAC-seq data suggest the existence of a boundary element between 2 Topologically-Associated-Domain (TAD) which is also characterized by the presence of CTCF binding sites. Butterflies have 2 pairs of wings originating from T2 (forewing) specified by Antp and T3 specified by Ubx (hindwing). Remarkably, CRISPR mutational perturbation of this boundary leads to the hatching of butterflies with homeotic clones of cells with hindwings identities in the forewing (a posteriorly oriented homeotic transformation). In agreement with this phenotype, the authors observe ectopic expression of Ubx in these clones of cells. In other words, CRISPR mutagenesis of this BE region identified by molecular tool give rise to homeotic transformations directed towards more posterior segment as the boundary mutations that had been 1st identified on the basis of their posterior oriented homeotic transformation in Drosophila. None of the mutant clones they observed affect the hindwing, indicating that their scheme did not affect the nearby Ubx transcription unit. This is reassuring and important first evidence that some of the regulatory paradigms that have been proposed in fruit flies are also at work in the common ancestor to Drosophilae and Lepideptora.

Given the large size of the Ubx transcription unit and its associated regulatory regions it is not surprising that the authors have identified ncRNA that are conserved in 4 species of Nymphalinae butterflies, some of which also present in D.melanogaster. Attempts to target the promoters by CRISPR give rise to clones of cells in both forewings and hindwings, suggesting the generation of regulatory mutations associated with both LOF and GOF transformations. The presence of clones with dual homeosis suggests the targeting of Ubx activator and repression CRMs. Unfortunately, these experiments do not allow us to make further conclusions on the role of these ncRNA or in the identification of specific regulatory elements. To the opinion of this reviewer, some recent papers addressing the role that these ncRNA may play in boundary function should be taken with caution, and evidence that ncRNA(s) regulate boundaries in the BX-C in a WT context is still lacking.

Strengths:<br /> The convincing GOF phenotype resulting from the targeting of the Antp-Ubx_BE.

Weaknesses:<br /> The lack of comparisons with the equivalent phenotypes obtained in D.melanogaster with for example the Fub mutation.

Reviewer #1 (Public Review):

Summary: Here, the authors were attempting to use molecular simulation or probe the nature of how lipids, especially PIP lipids, bind to a medically-important ion channel. In particular, they look at how this binding impact the function of the channel.

Strengths: the study is very well written and composed. The techniques are used appropriately, with plenty of sampling and analysis. The findings are compelling and provide clear insights into the biology of the system.

Weaknesses: a few of the analyses are hard to understand/follow, and rely on "in house" scripts. This is particularly the case for the lipid binding events, which can be difficult to compute accurately. Additionally, a lack of experimental validation, or coupling to existing experimental data, limits the study.

It is my view that the authors have achieved their aims, and their findings are compelling and believable. Their findings should have impacts on how researchers understand the functioning of the Nav1.4 channel, as well as on the study of other ion channels and how they interact with membrane lipids.

Reviewer #2 (Public Review):

Summary:<br /> Y., Tao E., et al. used multiscale MD simulations to show that PI(4,5)P2 binds stably to an inactivated state of Nav channels at a conserved site within the DIV S4-S5 linker, which couples the voltage sensing domain (VSD) to the pore. The authors hypothesized that PI(4,5)P2 prolongs inactivation by binding to the same site where the C-terminal tail is proposed to bind during recovery from inactivation. They convincingly showed that PI(4,5)P2 reduces the mobility of both the DIV S4-S5 linker and the DIII-IV linker, thus slowing the conformational changes required for the channel to recover to the resting state. They also conducted MD simulations to show that phosphoinositides bind to VSD gating charges in the resting state of Nav channels. These interactions may anchor VDS at the resting state and impede its activation. Their results provide a mechanism by which phosphoinositides alter the voltage dependence of activation and the recovery rate from inactivation, an important step for developing novel therapies to treat Nav-related diseases. However, the study is incomplete and lacks the expected confirmatory studies which are relevant to such proposals.

Strengths:<br /> The authors identified a novel binding between phosphoinositides and the VSD of Nav and showed that the strength of this interaction is state-dependent. Based on their work, the affinity of PIPs to the inactivated state is higher than the resting state. This work will help pave the way for designing novel therapeutics that may help relieve pain or treat diseases like arrhythmia, which may result from a leftward shift of the channel's activation.

Weaknesses:<br /> However, the study lacks the expected confirmatory studies which are relevant to such proposals. For example, one would expect that the authors would mutate the positive residues that they claim to make interactions with phosphoinositides to show that there are much fewer interactions once they make these mutations. Another point is that the authors found that the main interaction site of PIPs with Nav1.4 is the VSD-DIV and DIII-DIV linker, an interaction that is expected to delay fast inactivation if it happens at the resting state. The authors should make a resting state model of the Nav1.4 channel to explain the recent experimental data showing that PIP2 delays the activation of Nav1.4, with almost no effect on the voltage dependence of fast inactivation.

Major concern:<br /> 1- Lack of confirmatory experiments, e.g., mutating the positive residues that show a high affinity towards PIPs to a neutral and negative residue and assessing the effect of mutagenesis on binding.<br /> 2- Nav1.4 is the only channel that has been studied in terms of the effect of PIPs on it, therefore the authors should build a resting state model of Nav1.4 and study the effect of PIPs on it.<br /> Minor points:

There are a lot of incorrect statements in many areas, e.g., "These diseases 335 are associated with accelerated rates of channel recovery from inactivation, consistent with our observations that an interaction between PI(4,5)P2 and the residue corresponding to R1469 in other Nav 337 subtypes could be important for prolonging the fast-inactivated state." Prolonging the fast inactivated state would actually reduce recovery from inactivation and not accelerate it.

Reviewer #3 (Public Review):

Summary:<br /> This work uses multiscale molecular dynamics simulations to demonstrate molecular mechanism(s) for phosphatidylinositol regulation of voltage gated sodium channel (Nav1.4) gating. Recent experimental work by Gada et al. JGP 2023 showed altered Nav1.4 gating when Nav1.4 current was recorded with simultaneous application of PI(4,5)P2 dephosphorylate. Here the authors revealed probable molecular mechanism that can explain PI(4,5)P2 modulation of Nav1.4 gating. They found PIP lipids interacting with the gating charges - potentially making it harder to move the voltage sensor domain and altering the channels voltage sensitivity. They also found a stable PIP binding site that reaches the D_IV S4-S5 linker, reducing the mobility of the linker and potentially competing with the C-terminal domain.

Strengths:<br /> Using multiscale simulations with course-grained simulations to capture lipid-protein interactions and the overall protein lipid fingerprint and then all-atom simulations to verify atomistic details for specific lipid-protein interactions is extremely appropriate for the question at hand. Overall, the types of simulation and their length are suitable for the questions the authors pose and a thorough set of analysis was done which illustrates the observed PIP-protein interactions.

Weaknesses:<br /> Although the set of current simulations and analysis supports the conclusions drawn nicely, there are some limitations imposed by the authors on the course-grained simulations. If those were not imposed, it would have allowed for an even richer set and more thorough exploration of the protein-lipid interactions. The Martini 2 force field indeed cannot change secondary structure but if run with a properly tuned elastic network instead of backbone restraints, the change in protein configuration can be sampled and/or some adaptation of the protein to the specific protein environment can be observed. Additionally, with the 4to1 heavy atoms to a bead mapping some detailed chemical specificity is averaged out but parameters for different PIP family members do exist - including specific PIP(4,5)P2 vs PIP(3,4)P2, and could have been explored.

Joint Public Review:

Strengths:

Gain-of-function mutations and amplifications of PPM1D are found across several human cancers and are associated with advanced tumor stage, worse prognosis, and increased lymph node metastasis. In this study, Zhang and colleagues investigate the synthetic-lethal dependencies of PPM1D (protein phosphatase, Mg2+/Mn2+ dependent 1D) in leukemia cells using CRISPR/Cas9 screening. They identified that SOD1 (superoxide dismutase-1) as the top hit, whose loss reduces cellular growth in PPM1D-mutant cells, but not wild-type (WT) cells. Consistently, the authors demonstrate that PPM1D-mutant cells are more sensitive to SOD1 inhibitor treatment. By performing different in vitro studies, they show that PPM1D-mutant leukemia cells have an elevated level of reactive oxygen species (ROS), decreased basal respiration, increased genomic instability, and impaired non-homologous end-joining repair. The data strongly support that PPMD1 mutant cells have high levels of total peroxides and elevated DNA breaks and that genetic depletion of SOD1 decreases cell growth in two AML cell lines. These data highlight the potential of SOD1 inhibition as a strategy to achieve therapeutic synergism for PPM1D-mutant leukemia; and demonstrate the redox landscape of PPM1D-mutant cells.

Weaknesses:

It is not explained how superoxide radical (which is not damaging by itself) induces damage, the on-target effects of the SOD1 inhibitors at the concentrations are not clear, the increase in total hydroperoxides is not supported by loss of SOD1, the changes in mitochondrial function are small, and there is no assessment of how the mitochondrial SOD2 expression or function, which dismutates mitochondrial superoxide, is altered. Overall these studies do not distinguish between signal vs. damaging aspects of ROS in their models and do not rule out an alternate hypothesis that loss of SOD1 increases superoxide production by cytosolic NADPH activity which would significantly alter ROS-driven regulation of kinase/phosphatase signal modulation, affecting cell growth and proliferation as well as DNA repair. Additionally, with the exception of growth defects demonstrated with sgSOD1, the majority of data are acquired using two chemical inhibitors, LCS1 and ATN-224, without supporting evidence that these inhibitors are acting in an on-target manner.

Overall, the authors address an important problem by seeking targetable vulnerabilities in PPM1D mutant AML cells. It is clear that SOD1 deletion induces strong growth defects in the AML cell lines tested, that most of the approaches are appropriate for the outcomes being evaluated, and that the data are technically solid and well-presented. The major weakness lies in which redox pathways and ROS species are evaluated, how the resulting data are interpreted, and gaps in the follow-up experiments. Due to these omissions, as currently presented, the broader impact of these findings is unclear.

Reviewer #1 (Public Review):

The authors propose a hypothesis for ovarian carcinogenesis based on epidemiological data, and more specifically they suggest that the latter relates to ascending genital tract "infection" or "dysbiosis", the resulting fallopian tube inflammation ultimately predisposing to ovarian cancer.

While this hypothesis would ideally be addressed in a longitudinal set-up with repeated female genital tract sampling, such an approach is obviously hard to realize. Rather, the authors present this hypothesis as a rationale for a cross-sectional study involving 81 patients with ovarian cancer (most with the most common subtype of high grade serous ovarian carcinoma, though other subtypes were also included), as well as 106 control patients with various non-infectious conditions including endometriosis and benign ovarian cysts. In all patients was there a comprehensive microbiome sampling of ovarian surface/fallopian tube, cervix and peritoneal cavity as well sampling of a number of potential sources of contamination, including surgery sites, ambient environment, consumables used in the DNA extraction and sequencing pipeline, etc. In line with the hypothesis presented at the outset, species with a threshold of at least 100 reads in both at least one cervical and at least one fallopian tube sample, while absent from environmental swabs, were considered relevant to the postulated pathway.

Remarkably, fallopian tube microbiota in ovarian cancer patients tended to cluster more closely to those retrieved from the paracolic gutter, than fallopian tube microbiota in non-cancer controls, which showed more relative similarity to vaginal/genital tract microbiota.

Although not really addressed by the authors, there also seem to be quite a few differences, at least in terms of abundance, in cervical microbiota between ovarian cancer patients and controls as well, which is an interesting finding, even when accounting for differences in age distribution between ovarian cancer patients and included control patients.

Overall, very few data are available thus far on the upper genital tract/fallopian tube microbiome, while also invariably controversial, as it has proven extremely difficult to obtain pelvic samples in a valid, "sterile" manner, i.e. without affecting a resident low-biomass microbiome to be analyzed. The authors took a number of measures to counter so, and in this respect, this is likely the largest and most valid study on the subject, even though biases and contamination can never be completely excluded in this context.

As such, I believe the strength of this study and paper primarily relates to the rigour of the methodology, thereby giving us a valuable insight in the presumed fallopian tube/ovarian surface microbiome, which may definitely serve as an impetus and a reference to future translational ovarian cancer research, or ovarian microbiome research for that matter.

I believe that the authors should acknowledge in more detail, that the data obtained from their cross-sectional study, valid as these are, do not provide any direct support to the hypothesis - albeit also plausible - set forth, a discussion that I somehow missed to a certain extent. It is important to realize in this and related contexts that neoplasia may well induce microbiome alterations through a variety of mechanisms, hence microbiome alterations not per se being causative. Conclusions should therefore be more reserved. Along the same lines, potential biases introduced through the selection of control patients (some detail here would be insightful) also deserves some discussion, as it is not known, whether other conditions such as benign ovarian cysts or endometriosis have some relationship with the human microbiome, be it causative or 'reversely causative', see for instance very recent work in Science Translational Medicine.

Reviewer #2 (Public Review):

The authors aimed to investigate the microbiota present in the fallopian tubes (FT) and its potential association with ovarian cancer (OC). They collected swabs intraoperatively from the FT and other surgical sites as controls to profile the FT microbiota and assess its relationship with OC.<br /> They observed a clear shift in the FT microbiota of OC patients compared to non-cancer patients. Specifically, the FT of OC patients had more types of bacteria typically found in the gastrointestinal tract and the mouth. In contrast, vaginal bacterial species were more prevalent in non-cancer patients. Serous carcinoma, the most common OC subtype, showed a higher prevalence of almost all FT bacterial species compared to other OC subtypes.

The strengths of the study include its large sample size, rigorous collection methods, and use of controls to identify the possible contaminants. Additionally, the study employed advanced sequencing techniques for microbiota analysis. However, there are some weaknesses to consider. The study relied on swabs collected intraoperatively, which may not fully represent the microbiota in the FT during normal physiological conditions. The study also did not establish causality between the identified bacteria and OC but rather demonstrated an association. Regardless, the findings are important and these questions need to be addressed by future studies. A few additions in data representation and analysis are instead recommended.

Overall, the authors achieved their aims of identifying the FT microbiota and assessing its relationship with OC. The results support the conclusion that there is a clear shift in the FT microbiota in OC patients, paving the way for further investigations into the role of these bacteria in the pathogenesis of ovarian cancer.

The identification of specific bacterial species associated with OC could contribute to the development of novel diagnostic and therapeutic approaches. The study design and the data generated here can be valuable to the research community studying the microbiota and its impact on cancer development. However, further research is needed to validate these findings and elucidate the underlying mechanisms linking the FT microbiota shift and OC.

Reviewer #3 (Public Review):

The findings of Bo Yu and colleagues titled "Identification of fallopian tube microbiota and its association with ovarian cancer: a prospective study of intraoperative swab collections from 187 patients" describes the identification of the fallopian tube microbiome and relationship with ovarian cancer. The studies are highly rigorous obtaining specimens from the fallopian tube, ovarian surfaces, paracolic gutter of patients of known or suspected ovarian cancer or benign tumor patients. The investigators took great care to ensure there was no or limited contamination including test the surgical suite air, as the test locations are from low abundance microbiota. The findings provide evidence that the microbiota in the fallopian tube, especially in ovarian cancer has similarities to gut microbial communities. This is a potentially novel observation.

The studies investigate the microbiome of >1000 swabs from 81 ovarian cancer and 106 non-cancer patients. The sites collected are low biomass microbiota making the study particularly challenging. The studies provide descriptive evidence that the ovarian cancer fallopian tube microbiota contain species that are similar to the gut microbiota. In contrast the fallopian tube microbiota of non-cancer patients that exhibit more similarity to the uterine/cervical microbiota. This may be a relevant observation but is highly descriptive with limited insights on the functional relevance.

The data indicate the presence of low biomass FT microbiota. The findings support the existence of FT microbiota in ovarian cancer that appears to be related to gut microbial species. While interesting, there is no insights on how and why these microbial species are found in the FT. The studies only identify the species but there is no transcriptomic analysis to provide an indication on whether the bacteria are activating DNA damage pathways. This is an interesting observation that requires more insights to address how these bacteria reach the fallopian tube and a related question is whether these bacteria are found in the peritoneum.

An additional concern is whether these data can be used to develop biomarkers of disease and early detection of disease. can the investigators detect the ovarian cancer FT microbiota in cervical/vaginal secretions? That may yield more significant insights for the field.

Joint Public Review:

The enteroviruses comprise a medically important genus in the large and diverse picornavirus family, and are known to be released without lysis from infected cells in large vesicles containing numerous RNA genome-containing capsids - a feature allowing for en bloc transmission of multiple viral genomes to newly infected cells that engulf these vesicles. SIRT-1 is an NAD-dependent protein deacetylase that has numerous and wide ranging effects on cellular physiology and homeostasis, and it is known to be engaged in cellular responses to stress and autophagy.

Jassey et al. show that RNAi depletion of SIRT-1 impairs the release of enterovirus D-68 (EV-D68) in EVs recovered from the supernatant fluids of infected cells using a commercial exosome isolation kit. The many functions attributed to SIRT-1 in the literature reflect its capacity to deacetylate various cell proteins engaged in transcription, DNA repair, and regulation of metabolism, apoptosis and autophagy. However, Jassey et al. make the surprising claim that the proviral role of SIRT-1 in promoting enterovirus release is not dependent on its deacetylase activity. Fig. S1C is crucial to this suggestion but it is less than completely convincing. It shows that both wild-type and mutant SIRT-1are massively over-expressed in the rescue experiment compared to the normal endogenous level of SIRT-1 expression. Moreover, the blots are heavily saturated, making it difficult to assess the relative expression of wild-type vs. mutant. In addition, Fig. S1B and Fig. 4C convincingly show that EX527, a small molecule inhibitor of the deacetylase activity of SIRT-1, inhibits extracellular release of the virus. This suggests that the deacetylase activity of SIRT-1 may in fact be required for the proviral effect of SIRT-1. This is a fundamentally important question that requires more investigation.

Fig. 6 shows how SIRT-1 knockdown impacts the release of enterovirus D68 in EVs recovered from cell culture supernatant using a commercial 'Total Exosome Isolation Kit'. The authors are appropriately cautious in describing the vesicles they presume to be isolated by the kit as simply 'extracellular vesicles', since there are multiple types of EVs with very different mechanisms of biogenesis, of which 'exosomes' are but one specific type. It would have been more elegant had the authors shown that SIRT-1 is required for EV-D68 release in detergent-sensitive vesicles with low buoyant density in isopycnic gradients, and to characterize the size and number of viral capsids in these vesicles by electron microscopy.

The authors claim that "reduction of SIRT-1 attenuates the release of virus-loaded CD63-positive EVs" but they never actually show that the vesicles containing EV-D68 are in fact CD63-positive. Can a CD63 pulldown immunoprecipitate EV-D68 capsid proteins or viral RNA? This is important since CD63 is strongly associated with exosomes released from cells through the multi-vesicular body pathway, which are distinct from the LC3-positive EVs released by secretory autophagy that have previously been associated with enteroviruses.

The authors claim "that most EV-D68 is released non-lytically in an enveloped form" but they show data from only from early time points following infection (5 or 6 hrs post-infection) - prior to cell lysis. It would have been interesting to see a more complete temporal analysis, and to know the overall proportion of virus released in EVs versus lytic release of nonenveloped virus.

Fig. 1D indicates that a small fraction of SIRT-1 leaks from the nucleus in EV-D68 infected cells. The authors suggest this is due to targeted nuclear export, rather than simply leaky nuclear pores which are well known to exist in enterovirus-infected cells, but the evidence for this is questionable. The authors present similar fluorescent microscopy data showing inhibition of TFEB export in leptomycin-B treated cells in Fig. S2A in support of their claim that there is specific SIRT-1 export, but there is equivalent residual TFEB and SIRT-1 in the cytoplasm of the treated cells. Quantitative immunoblots of cytoplasmic and nuclear cell fractions might prove more compelling.

Joint Public Review:

This study investigated the mechanisms and biological processes associated with eccDNA generation in germline cells. They enriched eccDNA from cells at each step of spermatogenesis in mouse as well as human sperm using a commonly-used method to enrich small eccDNA: column purification, exonuclease digestion, rolling circle amplification, followed by short-read Illumina sequencing. From the fragment size analyses, dominant sizes were shown to be those protected by mono- or di-nucleosomes. The authors developed a computational pipeline to investigate eccDNA breakpoints in detail from split reads and reported a prevalence of a microhomology-mediated mechanism. Features of small germline eccDNA closely matched with small eccDNA generated by apoptosis, suggesting apoptotic germline cells as a major source.

Combined with analyses of publically available data from mouse tissues, the study established a strong link between small eccDNA and DNA fragments protected by mono-or di-nucleosomes. The rigorous investigation of microhomologies revealed that eccDNA sizes correlated with the lengths of microhomology in spermatogonial cells. Small eccDNA tends to originate from euchromatic regions, while longer eccDNA is derived from heterochromatic regions. These are novel findings.

The authors repeatedly stated the rare association between eccDNA and recombination hotspots. The argument was backed by (1) the abundance of eccDNA coming from dead cells, and (2) the small number of eccDNA from SPA cells undergoing miosis. The argument seems to have a point; however, the observation that the authors recovered hundreds of eccDNA at recombination hotspots may indicate that miotic recombination is a significant source of eccDNA. Because of the bulk isolation of eccDNA, those eccDNAs were outnumbered by the abundant eccDNA coming from apoptotic cell death. Indeed, eccDNAs from recombination hotspots are slightly more than random in all cell types (Fig. 4A).

Related to this issue, the dominance of both 180- and 360-bp fragments in most mouse tissues put the single 180-bp peaks of SPA, RST, and EST eccDNA in a peculiar position. Fewer numbers of these cells were used for eccDNA isolation than sperm cells, resulting in fewer eccDNA in these cell types, despite the same amount (10ng) of DNA input for rolling circle amplification. There might be a technical issue behind the peculiar observation, which is understandable given the challenging nature of isolating pure cell populations.

Reviewer #1 (Public Review):

Here, in this revised manuscript, the authors describe the transition between the summer form and the winter form of the pear psyllid pest, Cacopsylla chinensis (hemiptera). While the authors explore many components of this transition, the central hypotheses they seek to test are (i) that a protein they deem CcTRPM is a cold-sensitive Transient Receptor Potential Melastatin (TRPM) channel, and (ii) that this channel is involved in the summer-to-winter transition, in response to cold.<br /> The authors demonstrate that: both cold and menthol can initiate the summer-to-winter transition; that the protein of interest is required for the summer-to-winter transition (in vivo); that the protein of interest is involved in menthol- and cold-dependent Ca2+ transients (in vitro); that miR-252 expression is temperature-dependent, modulates the seasonal transition, and affects the expression of the transcript of interest; and finally, somewhat separately, that the chitin biosynthesis pathway is linked to the summer-to-winter transition.

However, I note three weaknesses, which are largely inherited from the original manuscript.

Firstly, the identification of the TRPM gene seems to be partially couched in the ab initio structural identification of "conserved ankyrin repeats." The methodology used to identify these so-called ankyrin repeats is not sufficiently described, and their conserved status is not sufficiently demonstrated nor cited (to my knowledge, this would be the first description of ankyrin repeats in TRPM, whereas previous studies have not detected them). There is also no discussion of previously identified structural components of TRPMs (see: Yin et al 2018, DOI: 10.1126/science.aan4325)

Secondly, the phylogenetic analysis still appears to be incomplete. The authors claim that "insects TRPM and mammals TRPM belong to different branches in evolution." While this is not a paper centered on the evolutionary analysis of this gene/protein family, the phylogenetic analysis here is insufficient for justifying this claim, especially since this claim is counter to previous studies (many in the literature over the past 10 years).

Thirdly, the methods lack sufficient detail to completely reproduce the phylogenetics and the cold-induced Ca2+ imaging.

Despite these weaknesses, I find the organismal/molecular component of this manuscript to be clear and convincing.

Reviewer #2 (Public Review):

The pear psylla Cacopsylla chinensis has two morphologically different forms, winter- and summer-forms depending on the temperatures. The authors provided solid data showing that the cold sensor CcTRPM is responsible for switching summer- to winter forms, which is in turn regulated by the miRNA miR-252. This finding is interesting and novel.

Reviewer #1 (Public Review):

Summary:

Developing vaccination capable of inducing persistent antibody responses capable of broadly neutralizing HIV strains is of high importance. However, our ability to design vaccines to achieve this is limited by our relative lack of understanding of the role of T-follicular helper (Tfh) subtypes in the responses. In this report Verma et al investigate the effects of different prime and boost vaccination strategies to induce skewed Tfh responses and its relationship to antibody levels. They initially find that live-attenuated measles vaccine, known to be effective at inducing prolonged antibody responses has a significant minority of germinal center Tfh (GC-Tfh) with a Th1 phenotype (GC-Tfh1) and then explore whether a prime and boost vaccination strategy designed to induce GC-Tfh1 is effective in the context of anti-HIV vaccination. They conclude that a vaccine formulation referred to as MPLA before concluding that this is the case.

Strengths:

While there is a lot of literature on Tfh subtypes in blood, how this relates to the germinal centers is not always clear. The strength of this paper is that they use a relevant model to allow some longitudinal insight into the detailed events of the germinal center Tfh (GC-Tfh) compartment across time and how this related to antibody production.

Weaknesses:

The authors focus strongly on the numbers of GC-Tfh1 as a proportion of memory cells and their comparison to GC-Tfh17. There seems to be little consideration of the large proportion of GC-Tfh which express neither CCR6 and CXCR3 and currently no clear reasoning for excluding the majority of GC-Tfh from most analysis. There seems to be an assumption that since the MPLA vaccine has a higher number of GC-Tfh1 that this explains the higher levels of antibodies. There is not sufficient information to make it clear if the primary difference in vaccine efficacy is due to a greater proportion of GC-Tfh1 or an overall increase in GC-Tfh of which the percentage of GC-Tfh1 is relatively fixed.

Reviewer #2 (Public Review):

Summary:

Anil Verma et al. have performed prime-boost HIV vaccination to enhance HIV-1 Env antibodies in the rhesus macaques model. The authors used two different adjuvants, a cationic liposome-based adjuvant (CAF01) and a monophosphoryl lipid A (MPLA)+QS-21 adjuvant. They demonstrated that these two adjuvants promote different transcriptomes in the GC-TFH subsets. The MPLA+QS-21 adjuvant induces abundant GC TFH1 cells expressing CXCR3 at first priming, while the CAF01 adjuvant predominantly induced GC TFH1/17 cells co-expressing CXCR3 and CCR6. Both adjuvants initiate comparable Env antibody responses. However, MPLA+QS-21 shows more significant IgG1 antibodies binding to gp140 even after 30 weeks.

The enhancement of memory responses by MPLA+QS-21 consistently associates with the emergence of GC TFH1 cells that preferentially produce IFN-γ.

Strengths:

The strength of this manuscript is that all experiments have been done in the rhesus macaque model with great care. This manuscript beautifully indicated that MPLA+QS-21 would be a promising adjuvant to induce the memory B cell response in the HIV vaccine.

Weaknesses:

The authors did not provide clear evidence to indicate the functional relevance of GC TFH1 in IgG1 class-switch and B cell memory responses.

Reviewer #1 (Public Review):

Previous work by this group has established that cholinergic projections from the forebrain to the basolateral amygdala (BLA) contribute to the acquisition of auditory-cued fear memories (Jiang et al., 2016). Here, the authors continue these studies, using a combination of techniques including genetic access to cFos expressing neurons, in-vivo optogenetics, and optical detection of acetylcholine (ACh) in the BLA. The main findings are that ACh is not only released during footshock presentation (the unconditioned stimulus, US, used in the fear learning) but that in addition, ACh is released upon CS presentation after fear learning. This implies that cholinergic neurons in the basal forebrain (BF) "learn" the response to tones and that they are recruited into a memory engram in the brain. The authors then follow up these ideas by showing with genetic, activity-dependent cFos labeling that BF ChAT+ neurons which are activated during the training session, are also re-activated by tone recall (Figure 2). Moreover, hM4Di- mediated block of the activity of those ChAT neurons activated during the training session strongly suppresses tone(CS) - driven freezing behavior during recall (Figure 3), again suggesting that re-activation of ChAT neurons in the BF is an important element for the retrieval of fear memory (or else, for the expression of a fear memory). Overall, I think the paper convincingly shows that learning of a tone response occurs in a neuromodulatory system and that neuromodulatory neurons are recruited to a fear memory engram. This adds a new dimension to the circuit- and neuromodulatory mechanisms that underlie learning and memory.

The paper, as it stands, has weaknesses in data presentation, data analysis, and statistical reporting. For most experiments, significantly more raw data should be shown (e.g. raw example traces for GRAB-ACh3.0), and also brain section images for almost all experiments (specific examples below). Raw data should also be shown in the Main Figures.

Major point<br /> 1) The authors use hM4Di to "silence" Fos-tagged neurons in the basal forebrain, but they have not validated the efficiency or the possible various effects of this reagent.<br /> It is possible that hM4Di actually has a relatively small effect on suppressing the AP activity of neurons. Nevertheless, hM4Di might still be an effective manipulation, because it was shown to additionally reduce transmitter release at the nerve terminal (see e.g. Stachniak et al. (Sternson) 2014, Neuron). Thus, the authors should evaluate in control experiments whether hM4Di expression plus CNO actually electrically silences the AP-firing of ChAT neurons in the BF as they seem to suggest, and/or if it reduces ACh release at the terminals. For example, one experiment to test the latter would be to perfuse CNO locally in the BLA; after expressing hM4Di in the cholinergic neurons of the BF. At the very least, the assumed action of hM4Di, and the possible caveats in the interpretation of these results should be discussed in the paper.

Further specific points.<br /> 1) The names of brain areas like "NBM/SIp" and "VP-SIa" need to be better introduced, and somehow contextualized (in the Introduction, and also at first reading in the Results).

2) Figure 3C: Application of CNO on the memory recall day leads to a strong reduction in CS-driven freezing. However, in this experiment, and also in Fig. S7, the pre-tone value of freezing is also strongly reduced. This would indicate that the activity of NBM/SIp cells (or else, ACh-release from these cells - see also Major point 1), also influences contextual learning. The authors should, first, statistically, test these effects (I am not sure this was done). If these differences are significant, a possible role of ACh in contextual fear learning should be discussed. Has it been shown before whether ACh is involved in contextual fear learning? Does this indicate the involvement of another target area of ACh neurons (e.g., the hippocampus?).

3) The discussion could be improved by better comparing what they found, to the wider literature. For example, previous papers studying other neuromodulatory systems found evidence for a modulation of neuromodulator release after learning; e.g. see Martins and Froemke 2015 Nat. Neuroscience for the noradrenergic system, Tang et al. (Schneggenburger lab) 2020 J. Neuroscience for the dopaminergic system and fear learning; and Uematsu et al., 2017, Nat. Neuroscience for the noradrenergic system and fear learning. Maybe the authors could include these and similar references when revising their discussion to take into account a broader view of previous findings related to other neuromodulatory systems.

Reviewer #2 (Public Review):

In this manuscript, the authors use a number of approaches to show that a posterior subset of cholinergic neurons located in the nucleus basalis of myenert (NBV) and substantia innominata (SIp) region of the basal forebrain, and projecting to the basolateral nucleus of the amygdala (BLA), are part of the conditioned threat-memory engram that is associated with the defensive freezing response. The paper clearly demonstrates that NBM/SIp inputs to the BLA are selectively activated during cued-associative learning which is then reactivated upon cued memory retrieval, leading to cholinergic release in the BLA. Likewise, the authors also use in-vitro recordings of cue-activated vs inactivated cholinergic cells to demonstrate that activated neurons are more excitable (firing more action potentials) and with a lower rheobase. Collectively, these data support the notion that NBM/SIp is part of the memory engram for the learned association. To better characterize the importance of the cholinergic input to the amygdala for behavior, the authors delineate the segregation of function in cholinergic input to the BLA along the rostrocaudal axis. They show that inputs to the BLA originating from the more anterior NBM/SIa region mediate innate anxiety behavior whereas the more posterior cholinergic inputs are involved in associative fear conditioning.

Overall, these findings make a significant contribution to our understanding of how the cholinergic system partakes in mediating cue-specific and non-specific emotional behavior. There are several group comparisons and statistical analyses that could strengthen the claims made in the paper.

1) Throughout the paper, the authors use comparisons of cell activity between groups to address questions about projection-specific and cue-specific cell activation and reactivation. However, statistical comparisons are sometimes done between biological replicates (e.g. Fig. 5A), whereas a lot of them are done between technical replicates (e.g. Fig. 2B, 5B, 7B). Adding statistics that compare biological replicates would help increase confidence in the results.

2) To demonstrate engram-like specificity, in figure 4C the authors show fold change in cholinergic reactivation in low and high responders (animals that show low and high defensive freezing upon cue presentation) as normalized by cell activity while sitting in the home cage. However, the authors also collected a better control for this comparison, which is shown in figure S4, where the animals were exposed to an unconditioned tone cue. Comparing fold change to this tone-alone condition would provide stronger evidence for the authors' point, as this would directly compare the specificity of cholinergic reactivation to a conditioned vs an unconditioned cue. A discussion of the same comparison is relevant for figure 2 (and is shown in figure S4) but is not mentioned in the text.

3) The significant correlation between cue-evoked percent change in defensive freezing from pretone and fold change in cholinergic cell activity relative to the home cage that is shown in figure 4D is somewhat confusing. Is the correlation considering all the points shown (high and low responders as depicted by black and grey points)? It's first reported as one correlation but then is discussed as two populations that have different results. Further, is the average amount of reactivation for the home-cage controls used here the same denominator for each reported animal? Similarly to the point above, a correlation looking at fold change from tone-alone would also be helpful to determine the degree to which cholinergic reactivation is specific to threat-association learning versus the more general attentional component that this system is known for.

4) The compelling argument of this paper is that the authors are separating out the general attention role typically attributed to the cholinergic system from a more specific, engram-based role. Given the importance of untangling this, it would useful to see the recorded traces and behavioral scoring for the data shown in figure S2B. For example, was the higher slope in the recorded cholinergic response during unconditioned tone 1 also accompanied by an increase in freezing, which later went away with additional non-reinforced tones? Given that the animals were not habituated to tones (according to the Methods), this activity could be related to a habituation/general attention response, which may then be weaker than the learned response.

Reviewer #2 (Public Review):

The manuscript by Gubensak et al describes the structure of the periplasmic domains of the Vibrio cholerae proteins ToxR and ToxS. These proteins control virulence in V. cholerae, however they are conserved throughout the Vibrionaceae and are important for controlling outermembrane porin expression, as well as other factors. ToxR specifically has been the focus of intense study for several decades, and this work is a nice contribution to a deeper understanding of exactly how this protein works. The authors show by a variety of biochemical techniques, including Xray crystallography, that the ToxR and ToxS periplasmic domains fold into a structure that forms a binding pocket in ToxS to allow binding of bile salts, a known modulator of ToxR activity. The detailed structural studies show how the interaction between the two proteins is critical to alter the co-structure of the two proteins and form the binding pocket.

The study was very straightforward, and the biochemical techniques were extensive and convincing. These studies add a nice rigorous insight into bile modulation of signal transduction in the Vibrios.

Reviewer #1 (Public Review):

The manuscript "Vibrio cholerae´s ToxRS bile sensing system" by Gubensäk et al. reports the crystal structure of a periplasmic, hetero-dimeric bile-sensing protein complex ToxRSp. The authors show that the intrinsically disordered C-terminus of ToxRp folds upon binding to ToxSp, thus completing the defective bile-binding interface of ToxSp. Using NMR experiments they find that bile acid binds to the ToxRSp hetero-dimer but not to ToxSp or ToxRp alone. Results from NMR and microfluidic modulation spectroscopy indicate additional, weak binding sites in the ToxRSp complex and local conformational changes associated with binding. The authors apply AlphaFold to predict ToxRSp structures from various Vibrio strains, showing gross structural conservation with greater variability in ToxRp compared to ToxSp. The authors conclude to have shown that ToxS is a main sensor in Vibrio strains and requires ToxR for binding bile, forming part of a regulation mechanism for survival and virulence after infection.

Cholera is a severe and often lethal disease affecting a high number of people in the developing world. It is caused by the bacterium Vibrio cholerae, which rapidly adapts to hostile conditions in the stomach where it produces toxins. The pathogen uses sensory proteins, like the ToxR-ToxS system, that facilitate bile resistance and virulence. The present studies by Gubensäk et al. reveal an intriguing molecular mechanism by which V. cholerae creates a sensor for bile, transducing the signal through the cellular membrane of the bacterium. Their crystal structure of ToxRSp and complementary biophysical experiments conclusively show a split binding interface for bile formed by the individual periplasmic domains ToxRp and ToxSp. The folding of an intrinsically disordered segment of ToxRp upon binding to ToxSp adds a missing beta-strand to a defective beta-barrel, thus creating the intact interface for the ligand. The mechanism provides new molecular level insights into bile resistance of V. cholerae. Experiments are carefully conducted and analysed. The manuscript is well written.

However, there are some ambiguities in the proposed stoichiometry of the ToxRSp/bile interaction inferred from SEC-MALS experiments and MD simulation. Results may contain additional information on the order of events in formation of the ternary complex. Moreover, the quality of the manuscript could be improved by expanding analyses and discussion on the apparent necessity of a split protein binding interface in mechanisms of resistance and virulence.

Reviewer #3 (Public Review):

The presented structure of the ToxR and ToxS periplasmic domain complex reveals the formation of a bile binding pocket at the interface, stabilized in the heterodimer structure. In addition to the structural data, a series of biophysical interaction experiments were performed between sodium cholate and the ToxR periplasmic domain alone, as well as the ToxR-ToxS complex, to characterize the bile binding.

Reviewer #3 (Public Review):

In this study, the authors developed and tested a novel framework for extracting muscle synergies. The approach aims at removing some limitations and constraints typical of previous approaches used in the field. In particular, the authors propose a mathematical formulation that removes constraints of linearity and couples the synergies to their motor outcome, supporting the concept of functional synergies and distinguishing the task-related performance related to each synergy. While some concepts behind this work were already introduced in recent work in the field, the methodology provided here encapsulates all these features in an original formulation providing a step forward with respect to the currently available algorithms. The authors also successfully demonstrated the applicability of their method to previously available datasets of multi-joint movements.

Preliminary results positively support the scientific soundness of the presented approach and its potential. The added values of the method should be documented more in future work to understand how the presented formulation relates to previous approaches and what novel insights can be achieved in practical scenarios and confirm/exploit the potential of the theoretical findings.

In their revision, the authors have implemented major revisions and improved their paper. The work was already of good quality and now it has improved further. The authors were able to successfully:<br /> - improve the clarity of the writing (e.g.: better explaining the rationale and the aims of the paper);<br /> - extend the clarification of some of the key novel concepts introduced in their work, like the redundant synergies;<br /> - show a scenario in which their approach might be useful for increasing the understanding of motor control in patients with respect to traditional algorithms such as NMF. In particular, their example illustrates why considering the task space is a fundamental step forward when extracting muscle synergies, improving the practical and physiological interpretation of the results.

Reviewer #1 (Public Review):

The proposed study provides an innovative framework for the identification of muscle synergies taking into account their task relevance. State-of-the-art techniques for extracting muscle interactions use unsupervised machine-learning algorithms applied to the envelopes of the electromyographic signals without taking into account the information related to the task being performed. In this work, the authors suggest including the task parameters in extracting muscle synergies using a network information framework previously proposed. This allows the identification of muscle interactions that are relevant, irrelevant, or redundant to the parameters of the task executed.

The proposed framework is a powerful tool to understand and identify muscle interactions for specific task parameters and it may be used to improve man-machine interfaces for the control of prostheses and robotic exoskeletons.

With respect to the network information framework recently published, this work added an important part to estimate the relevance of specific muscle interactions to the parameters of the task executed. However, the authors should better explain what is the added value of this contribution with respect to the previous one, also in terms of computational methods.

It is not clear how the well-known phenomenon of cross-talk during the recording of electromyographic muscle activity may affect the performance of the proposed technique and how it may bias the overall outcomes of the framework.

Reviewer #2 (Public Review):

This paper is an attempt to extend or augment muscle synergy and motor primitive ideas with task measures. The authors idea is to use information metrics (mutual information, co-information) in 'synergy' constraint creation that includes task information directly. By using task related information and muscle information sources and then sparsification, the methods construct task relevant network communities among muscles, together with task redundant communities, and task irrelevant communities. This process of creating network communities may then constrain and help to guide subsequent synergy identification using the authors published sNM3F algorithm to detect spatial and temporal synergies.

The revised paper is much clearer and examples are helpful in various ways. However, figure 2 as presented does not convincingly show why task muscle mutual information helps in separating synergies, though it is helpful in defining the various network communities used in the toy example.

The impact of the information theoretic constraints developed as network communities on subsequent synergy separation are posited to be benign and to improve over other methods (e.g., NNMF). However, not fully addressed are the possible impacts of the methods on compositionality links with physiological bases, and the possibility remains of the methods sometimes instead leading to modules that represent more descriptive ML frameworks that may not support physiological work easily. Accordingly, there is a caveat. This is recognized and acknowledged by the authors in their rebuttal of the prior review. It will remain for other work to explore this issue, likely through testing on detailed high degree of freedom artificial neuromechanical models and tasks. This possible issue with the strategy here likely needs to be fully acknowledged in the paper.

The approach of the methods seeks to identify task relevant coordinative couplings. This is a meta problem for more classical synergy analyses. Classical analyses seek compositional elements stable across tasks. These elements may then be explored in causal experiments and generative simulations of coupling and control strategies. However, task-based understanding of synergy roles and functional uses is significant and is clearly likely to be aided by methods in this study.

Information based separation has been used in muscle synergy analyses using infomax ICA, which is information based at core. Though linear mixing of sources is assumed in ICA, minimized mutual information among source (synergy) drives is the basis of the separation and detects low variance synergy contributions (e.g., see Yang, Logan, Giszter, 2019). In the work in this paper, instead, mutual information approaches are used to cluster muscles and task features into network communities preceding the SNM3F algorithm use for separation, rather than using minimized information in separation. This contrast of an accretive or agglomerative mutual information strategy here used to cluster into networks, versus a minimizing mutual information source separation used in infomax ICA epitomizes a key difference in approach here.

Physiological causal testing of synergy ideas is neglected in the literature reviews in the paper. Although these are only in animal work (Hart and Giszter, 2010; Takei and Seki, 2017), the clear connection of muscle synergy analysis choices to physiology is important, and eventually these issues need to be better managed and understood in relation to the new methods proposed here, even if not in this paper.

Analyses of synergies using the methods the paper has proposed will likely be very much dependent on the number and quality of task variables included and how these are managed, and the impacts of these on the ensuing sparsification and network communities used prior to SNM3F. The authors acknowledge this in their response. This caveat should likely be made very explicit in the paper.

It would be useful in the future to explore the approach described with a range of simulated data to better understand the caveats, and optimizations for best practices in this approach.

Reviewer #1 (Public Review):

Picard et al. report a novel neural signature of facial expressions of pain. In other words, they provide evidence that a specific set of brain activations, as measured by means of functional magnetic resonance imaging (fMRI), can tell us when someone is expressing pain via a concerted activation of distinctive facial muscles. They demonstrate that this signature provides a better characterization of this pain behaviour when compared with other signatures of pain reported by past research. The Facial Expression of Pain Signature (FEPS) thus enriches this collection and, if further validated, may allow scientists to identify the neural structures subserving important non-verbal pain behaviour. I have, however, some reservations about the strength of the evidence, relating to insufficient characterization of the underlying processes involved.

Strengths:<br /> The study relies on a robust machine-learning approach, able to capitalise on the multivariate nature of the fMRI data, an approach pioneered in the field of pain by one of the authors (Dr. Tor Wager). This paper extends Wager's and other colleagues' work attempting to identify specific combinations of brain structures subserving different aspects of the pain experience while examining the extent of similarity/dissimilarity with the other signatures. In doing so, the study provides further methodological insight into fine-grained network characterization that may inspire future work beyond this specific field.

Weaknesses:<br /> The main weakness concerns the lack of a targeted experimental design aimed to dissect the shared variance explained by activations both specific to facial expressions and to pain reports. In particular, I believe that two elements would have significantly increased the robustness of the findings:<br /> 1) Control conditions for both the facial expressions and the sensory input. An efficient signature should not be predictive of neutral and emotional facial expressions (e.g., disgust) other than pain expressions, as well as it should not be predictive of sensations originating from innocuous warm stimulation or other unpleasant but non-painful stimulation.<br /> 2) Graded intensity of the sensory stimulation: different intensities of the thermal stimulation would have caused a graded facial expression (from neutral to pain) and graded verbal reports (from no pain to strong pain), thus offering a sensitive characterisation of the signal associated with this condition (and the warm control condition).<br /> However, these conditions are missing from the current design, and therefore we cannot make a strong conclusion about the generalisability of the signature (regardless of whether it can predict better than other signatures - which may/may not suffer from similar or other methodological issues - another potential interesting scientific question!). The authors seem to work on the assumption that the trials where warm stimulation was delivered are of no use. I beg to disagree. As per my previous comment, warm trials (and associated neutral expressions) could be incorporated into the statistical model to increase the classification sensitivity and precision of the FEPS decoding.

Reviewer #2 (Public Review):

Summary:<br /> The objective of this study was to further our understanding of the brain mechanisms associated with facial expressions of pain. To achieve this, participants' facial expressions and brain activity were recorded while they received noxious heat stimulation. The authors then used a decoding approach to predict facial expressions from functional magnetic resonance imaging (fMRI) data. They found a distinctive brain signature for pain facial expressions. This signature had minimal overlap with brain signatures reflecting other components of pain phenomenology, such as signatures reflecting subjective pain intensity or negative effects.

Strength:<br /> The manuscript is clearly written. The authors used a rigorous approach involving multivariate brain decoding to predict the occurrence and intensity of pain facial expressions during noxious heat stimulation. The analyses seem solid and well-conducted. I think that this is an important study of fundamental and clinical relevance.

Weaknesses:<br /> Despite those major strengths, I felt that the authors did not suffciently explain their own interpretation of the significance of the findings. What does it mean, according to them, that the brain signature associated with facial expressions of pain shows a minimal overlap with other pain-related brain signatures?

A few questions also arose during my reading.

Question 1: Is the FEPS really specific to pain expressions? Is it possible that the signature includes a facial expression signal that would be shared with facial expressions of other emotions, especially since it involves socio-affective regulation processes? Perhaps this question should be discussed as a limit of the study?

Question 2: All AUs are combined together in a composite score for the regression. Given that the authors have other work showing that different AUs may be associated with different components of pain (affective vs. sensory), is it possible that combining all AUs together has decreased the correlation with other pain signatures? Or that the FEPS actually reflects multiple independent signatures?

Question 3: Is facial expressivity constant throughout the experiment? Is it possible that the expressivity changes between the beginning and the end of the experiment? For instance, if there is a habituation, or if the participant is less surprised by the pain, or in contrast if they get tired by the end of the experiment and do not inhibit their expression as much as they did at the beginning. If facial expressivity changes, this could perhaps affect the correlation with the pain ratings and/or with the brain signatures; perhaps time (trial number) could be added as one of the variables in the model to address this question.

Reviewer #3 (Public Review):

In this manuscript, Picard et al. propose a Facial Expression Pain Signature (FEPS) as a distinctive marker of pain processing in the brain. Specifically, they attempt to use functional magnetic resonance imaging (fMRI) data to predict facial expressions associated with painful heat stimulation.

The main strengths of the manuscript are that it is built on an extensive foundation of work from the research group, and that experience can be observed in the analysis of fMRI data and the development of the machine learning model. Additionally, it provides a comparative account of the similarities of the FEPS with other proposed pain signatures. The main weaknesses of the manuscript are the absence of a proper control condition to assess the specificity of the facial pain expressions, a few relevant omissions in the methodology regarding the original analysis of the data and its purpose, and a biased interpretation of the results.

I believe that the authors partially succeed in their aims, as described in the introduction, which are to assess the association between pain facial expression and existing pain-relevant brain signatures, and to develop a predictive brain activation model of the facial responses to painful thermal stimulation. However, I believe that there is a clear difference between those aims and the claim of the title, and that the interpretation of the results needs to be more rigorous.

Reviewer #1 (Public Review):

Activity has effects on the development of neural circuitry during almost any step of differentiation. In particular during specific time periods of circuit development, so-called critical periods (CP), altered neural activity can induce permanent changes in network excitability. In complex neural networks, it is often difficult to pinpoint the specific network components that are permanently altered by activity, and it often remains unclear how activity is integrated during the CP to set mature network excitability. This study combines electrophysiology with pharmacological and optogenetic manipulation in the Drosophila genetic model system to pinpoint the neural substrate that is influenced by altered activity during a critical period (CP) of larval locomotor circuit development. Moreover, it is then tested whether and how different manipulations of synaptic input are integrated during the CP to tune network excitability.

Strengths:<br /> Based on previous work, during the CP, network activity is increased by feeding the GABA-AR antagonist PTX. This results in permanent network activity changes, as highly convincingly assayed by a prolonged recovery period following induced seizure and by altered intersegmental locomotor network coordination. This is then used to provide two important findings: First, compelling electro- and optophysiological experiments track the site of network change down to the level of single neurons and pre- versus postsynaptic specializations. In short, increased activity during the CP increases both the magnitude of excitatory and inhibitory synaptic transmission to the aCC motoneuron, but excitation is affected more strongly. This results in altered excitation inhibition ratios. Fine electrophysiology shows that excitatory synapse strengthening occurs postsynaptically. High-quality anatomy shows that dendrite size and numbers of synaptic contacts remain unaltered. It is a major accomplishment to track the tuning of network excitability during the CP down to the physiology of specific synapses to identified neurons.

Second, additional experiments with single neuron resolution demonstrate that during the CP different forms of activity manipulation are integrated so that opposing manipulations can rescue altered setpoints. This provides novel insight into how developing neural network excitability is tuned, and it indicates that during the CP, training can rescue the effects of hyperactivity.

Weaknesses:<br /> There are no major weaknesses to the findings presented, but the molecular cause that underlies increased motoneuron postsynaptic responsiveness as well as the mechanism that integrates different forms of activity during the CP remain unknown. It is clear that addressing these experimentally is beyond the scope of this study, but some discussion about different candidates would be helpful.

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors use the tractable Drosophila embryonic/larval motor circuit to determine how manipulations of activity during a critical period (CP) modify the circuit in ways that persist into later developmental stages. Previously, this group demonstrated that manipulations to the aCC/MN-Ib neuron in embryonic stages enhance (or can rescue) susceptibility to seizures at later larval stages. Here, the authors demonstrate that following enhanced excitatory drive (by PTX feeding), the aCC neuron acquires increased sensitivity to cholinergic excitatory transmission, presumably due to increased postsynaptic receptor abundance and/or sensitivity, although this is not clarified. Although locomotion is not altered at later developmental larval stages, the authors suggest there is reduced "robustness" to induced seizures. The second part of the study then goes on to enhance inhibition during the CP in an attempt to counteract the enhanced excitation, and show that many aspects of the CP plasticity are rescued. The authors conclude that "average" E/I activity is integrated during the CP to determine the excitability of the mature locomotor network.

Overall, this study provides compelling mechanistic insight into how a final motor output neuron changes in response to enhanced excitatory drive during a CP to change the functionality of the circuit at later mature developmental stages. The first part of this study is strong, clearly showing the changes in the aCC neuron that result from enhanced excitatory input. This includes very nice electrophysiology and imaging data that assess synaptic function and structure onto aCC neurons from pre-motor inputs resulting from PTX exposure during development. However, the later experiments in Figures 6 and 7 designed to counteract the CP plasticity are somewhat difficult to interpret. In particular, the specificity of the manipulations of the ch neuron intended to counteract the CP plasticity is unclear, given the complexities of how these changes impact the excitability of all neurons during development. It is clear that CP plasticity is largely rescued in later stages, but it is hard to know if downstream or secondary adaptations may be masking the PTX-induced plasticity normally observed. Nonetheless, this study provides an important advance in our understanding of what parameters change during CPs to calibrate network dynamics at later developmental stages.

Reviewer #3 (Public Review):

Summary:<br /> In Hunter, Coulson et al, the authors seek to expand our understanding of how neural activity during developmental critical periods might control the function of the nervous system later in life. To achieve increased excitation, the authors build on their previous results and apply picrotoxin 17-19 hours after egg-laying, which is a critical period of nervous system development. This early enhancement of excitation leads to multiple effects in third-instar larvae, including prolonged recovery from electroshock, increased synchronization of motor neuron networks, and increased AP firing frequency. Using optogenetics and whole-cell patch clamp electrophysiology, the authors elegantly show that picrotoxin-induced over-excitation leads to increased strength of excitatory inputs and not loss of inhibitory inputs. To enhance inhibition, the authors chose an approach that involved the stimulation of mechanosensory neurons; this counteracts picrotoxin-induced signs of increased excitation. This approach to enhancing inhibition requires further control experiments and validation.

Strengths:<br /> • The authors confirm their previous results and show that 17-19 hours after egg laying is a critical period of nervous system development.<br /> • Using Ca2+/Sr2+ substitutions, the authors demonstrate that synaptic connections between A18a  aCC show increased mEPSP amplitudes. The authors show that this aCC input is what is driving enhanced excitation.<br /> • The authors demonstrate that the effects of over-excitation attributed to picrotoxin exposure are generalizable and also occur in bss mutant flies.

Weaknesses:<br /> • The authors build on their previous work and argue that the critical period (17-19h after egg-laying) is a uniquely sensitive period of development. Have the authors already demonstrated that exposure to picrotoxin at L1 or L2 (and even early L3 if experimentally possible) does not lead to changes in induced seizure at L3? This would further the authors' hypothesis of the uniqueness of the 17-19h AEL period. If this has already been established in prior publications, then this needs to be further explained. I do note in Gaicehllo and Baines (2015) that Fig 2E shows the identification of the 17-19h window.<br /> • Regarding experiments in Fig 2, authors only report changes in AP firing frequency. Can the authors also report other metrics of excitability, including measures of intrinsic excitability with and without picrotoxin exposure (including RMP, Rm)? Was a different amount of current injection needed to evoke stable 5-10 Hz firing with and without picrotoxin? In the representative figure (Fig. 2A), it appears that the baseline firing frequencies are different prior to optogenetic stimulation.<br /> • The ch-related experiments require further controls and explanation. Regarding experiments in Fig 6, what is the effect of ch neuron stimulation alone on time lag and AP frequency? Can the authors further clarify what is known about connections between aCC and ch neurons? It is difficult for this reviewer to conceptualize how enhancing ch-mediated inhibition would worsen seizures. While the cited study (Carreira-Rosario et al 2021) convincingly shows that inhibition of mechanosensory input leads to excessive spontaneous network activity, has it been shown that the converse - stimulation of ch neurons - indeed enhances network inhibition?<br /> • The interpretation of ch-related experiments is further complicated by the explanation in the Discussion that ch neuron stimulation depolarizes aCC neurons; this seems to undercut the authors' previous explanation that the increased E:I ratio is corrected by enhanced inhibition from ch neurons. The idea that ch neurons are placing neurons in a depolarized refractory state is not substantiated by data in the paper or citations.<br /> • In the Discussion, the authors suggest that enhanced proprioception leading to seizures is reminiscent of neurological conditions. This seems to be an oversimplification. Connecting abnormal proprioception to seizures is quite different from connecting abnormal proprioception to disorders of coordination. This should be revised.

Reviewer #1 (Public Review):

Summary:<br /> As adult-born granule neurons have been shown to play diverse roles, both positive and negative, to modulate hippocampal circuitry and function in epilepsy, understanding the mechanisms by which altered neurogenesis contributes to seizures is important for future therapeutic strategies. The work by Jain et al. demonstrates that increasing adult neurogenesis before status epilepticus (SE) leads to a suppression of chronic seizures in the pilocarpine model of temporal lobe epilepsy. This work is potentially interesting because previous studies showed suppressing neurogenesis led to reduced chronic seizures.

To increase neurogenesis, the authors conditionally delete the pro-apoptotic gene Bax using a tamoxifen-inducible Nestin-CreERT2 which has been previously published to increase proliferation and survival of adult-born neurons by Sahay et al. After 6 weeks of tamoxifen injection, the authors subjected male and female mice to pilocarpine-induced SE. In the first study, at 2 hours after pilocarpine, the authors examine latency to the first seizure, severity and total number of acute seizures, and power during SE. In the second study in a separate group of mice, at 3 weeks after pilocarpine, the authors examine chronic seizure number and frequency, seizure duration, postictal depression, and seizure distribution/cluster seizures. Overall, the study concludes that increasing adult neurogenesis in the normal adult brain can reduce epilepsy in females specifically. However, important BrdU birthdating experiments in both male and female mice need to be included to support the conclusions made by the authors. Furthermore, speculative mechanisms lacking direct evidence reduce enthusiasm for the findings.

Strengths:<br /> 1. The study is sex-matched and reveals differences in response to increasing adult neurogenesis in chronic seizures between males and females.

2. The EEG recording parameters are stringent, and the analysis of chronic seizures is comprehensive. In two separate experiments, the electrodes were implanted to record EEG from the cortex as well as the hippocampus. The recording was done for 10 hours post pilocarpine to analyze acute seizures, and for 3 weeks continuous video EEG recording was done to analyze chronic seizures.

Weaknesses:<br /> 1. Cells generated during acute seizures have different properties to cells generated in chronic seizures. In this study, the authors employ two bouts of neurogenesis stimuli (Bax deletion dependent and SE dependent), with two phases of epilepsy (acute and chronic). There are multiple confounding variables to effectively conclude that conditionally deleting Bax in Nestin-Cre+ cells leads to increased neurogenesis and hilar ectopic granule cells, thereby reducing chronic seizures.

2. Related to this is the degree of neurogenesis between Cre+ and Cre- mice and the nature of the sex differences. It is crucial to know the rate/fold change of increased neurogenesis before pilocarpine treatment and whether it is different between male and female mice.

3. The authors observe more hilar Prox1 cells in Cre+ mice compared to Cre- mice. The authors should confirm the source of the hilar Prox1+ cells.

4. The biggest weakness is the lack of mechanism. The authors postulate a hypothetical mechanism to reconcile how increasing and decreasing adult-born neurons in GCL and hilus and loss of hilar mossy and SOM cells would lead to opposite effects - more or fewer seizures. The authors suggest the reason could be due to rewiring or no rewiring of hilar ectopic GCs, respectively, but do not provide clear-cut evidence.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Jain et al explore whether increasing adult neurogenesis is protective against status epilepticus (SE) and the development of spontaneous recurrent seizures (chronic epilepsy) in a mouse pilocarpine model of TLE. The authors increase adult neurogenesis via conditional deletion of Bax, a pro-apoptotic gene, in Nestin-CreERT2Baxfl/fl mice. Cre- littermates are used as controls for comparisons. In addition to characterizing seizure phenotypes, the authors also compare the abundance of hilar ectopic granule cells, mossy cells, hilar SOM interneurons, and the degree of neuronal damage between mice with increased neurogenesis (Cre+) vs Cre- controls. The authors find less severe SE and a reduction in chronic seizures in female mice with pre-insult increased adult-born neurons. Immunolabeling experiments show these females also have preservation of hilar mossy cells and somatostatin interneurons, suggesting the pre-insult increase in adult neurogenesis is protective.

Strengths:<br /> 1. The finding that female mice with increased neurogenesis at the time of pilocarpine exposure have fewer seizures despite having increased hilar ectopic granule cells is very interesting.<br /> 2. The work builds nicely on the group's prior studies.<br /> 3. Apparent sex differences are a potentially important finding.<br /> 4, The immunohistochemistry data are compelling.<br /> 5. Good controls for EEG electrode implantation effects.<br /> 6. Nice analysis of most of the SE EEG data.

Weaknesses:<br /> 1. In addition to the Cre- littermate controls, a no Tamoxifen treatment group is necessary to control for both insertional effects and leaky expression of the Nestin-CreERT2 transgene.

2. The authors suggest sex differences; however, experimental procedures differed between male and female mice (as the authors note). Female mice received diazepam 40 minutes after the first pilocarpine-induced seizure onset, whereas male mice did not receive diazepam until 2 hours post-onset. The former would likely lessen the effects of SE on the female mice. Therefore, sex differences cannot be accurately assessed by comparing these two groups, and instead, should be compared between mice with matching diazepam time courses. Additionally, the authors state that female mice that received diazepam 2 hours post-onset had severe brain damage. This is concerning as it would suggest that SE is more severe in the female than in the male mice.

3. Some sample sizes are low, particularly when sex and genotypes are split (n=3-5), which could cause a type II statistical error.

4. Several figures show a datapoint in the sex and genotype-separated graphs that is missing from the corresponding male and female pooled graphs (Figs. 2C, 2D, 4B).

5. In Suppl Figs. 1B & 1C, subsections 1c and 2c, the EEG trace recording is described as the end of SE; however, SE appears to still be ongoing in these traces in the form of periodic discharges in the EEG.

6. In Results section II.D and associated Fig.3, what the authors refer to as "postictal EEG depression" is more appropriately termed "postictal EEG suppression". Also, postictal EEG suppression has established criteria to define it that should be used. The example traces in Fig. 3A and B should also be expanded to better show this potential phenomenon.

7. In Fig.5D, the area fraction of DCX in Cre+ female mice is comparable to that of Cre- and Cre+ male mice. Is it possible that there is a ceiling effect in DCX expression that may explain why male Cre+ mice do not have a significant increase compared to male Cre- mice?

8. In Suppl. Fig 6, the authors should include DCX immunolabeling quantification from conditional Cre+ male mice used in this study, rather than showing data from a previous publication.

9. In Fig 8, please also include Fluorojade-C staining and quantification for male mice.

10. Page 13: Please specify in the first paragraph of the discussion that findings were specific to female mice with pre-insult increases in adult-born neurogenesis.

Minor:<br /> 11. In Fig. 1 and suppl. figure 1, please clarify whether traces are from male or female mice.

12. Please be consistent with indicating whether immunolabeling images are from female or male mice.

a. Fig 5B images labeled as from "Cre- Females" and "Cre+ Females".

b. Suppl. Fig 8: Images labeled as "Cre- F" and "Cre+ F".

c. Fig 6: sex not specified.

d. Fig. 7: sex only specified in the figure legend.

e. Fig 8: only female mice were included in these experiments, but this is not clear from the figure title or legend.

13. Page 4: the last paragraph of the introduction belongs within the discussion section.

14. Page 6: The sentence "The data are consistent with prior studies..." is unnecessary.

15. Suppl. Fig 6A: Please include representative images of normal condition DCX immunolabeling.

16. In Suppl. Fig 7C, I believe the authors mean "no loss of hilar mossy and SOM cells" instead of "loss of hilar mossy and SOM cells".

Reviewer #1 (Public Review):

Summary:<br /> This study examined the role of statistical learning in pain perception, suggesting that individuals' expectations about a sequence of events influence their perception of pain intensity. They incorporated the components of volatility and stochasticity into their experimental design and asked participants (n = 27) to rate the pain intensity, their prediction, and their confidence level. They compared two different inference strategies - optimal Bayesian inference vs. heuristic-employing Kalman filters and model-free reinforcement learning and showed that the expectation-weighted Kalman filter best explained the temporal pattern of participants' ratings. These results provide evidence for a Bayesian inference perspective on pain, supported by a computational model that elucidates the underlying process.

Strengths:<br /> Their experimental design included a wide range of input intensities and the levels of volatility and stochasticity.

Weaknesses:<br /> - Selection of candidate computational models: While the paper juxtaposes the simple model-free RL model against a Kalman Filter model in the context of pain perception, the rationale behind this choice remains ambiguous. It prompts the question: could other RL-based models, such as model-based RL or hierarchical RL, offer additional insights? A more detailed explanation of their computational model selection would provide greater clarity and depth to the study.

- Effects of varying levels of volatility and stochasticity: The study commendably integrates varying levels of volatility and stochasticity into its experimental design. However, the depth of analysis concerning the effects of these variables on model fit appears shallow. A looming concern is whether the superior performance of the expectation-weighted Kalman Filter model might be a natural outcome of the experimental design. While the non-significant difference between eKF and eRL for the high stochasticity condition somewhat alleviates this concern, it raises another query: Would a more granular analysis of volatility and stochasticity effects reveal fine-grained model fit patterns?

- Rating instruction: According to Fig. 1A, participants were prompted to rate their responses to the question, "How much pain DID you just feel?" and to specify their confidence level regarding their pain. It is difficult for me to understand the meaning of confidence in this context, given that they were asked to report their *subjective* feelings. It might have been better to query participants about perceived stimulus intensity levels. This perspective is seemingly echoed in lines 100-101, "the primary aim of the experiment was to determine whether the expectations participants hold about the sequence inform their perceptual beliefs about the intensity of the stimuli."

- Relevance to clinical pain: While the authors underscore the relevance of their findings to chronic pain, they did not include data pertaining to clinical pain. Notably, their initial preprint seemed to encompass data from a clinical sample (https://www.medrxiv.org/content/10.1101/2023.03.23.23287656v1), which, for reasons unexplained, has been omitted in the current version. Clarification on this discrepancy would be instrumental in discerning the true relevance of the study's findings to clinical pain scenarios.

- Paper organization: The paper's organization appears a little bit weird, possibly due to the removal of significant content from their initial preprint. Sections 2.1-2.2 and 2.4 seem more suitable for the Methods section, while 2.3 and 2.4.1 are the only parts that present results. In addition, enhancing clarity through graphical diagrams, especially for the experimental design and computational models, would be quite beneficial. A reference point could be Fig. 1 and Fig. 5 from Jepma et al. (2018), which similarly explored RL and KF models.

Reviewer #2 (Public Review):

Summary:<br /> The present study aims to investigate whether learning about temporal regularities of painful events, i.e. statistical learning can influence pain perception. To this end, sequences of heat pain stimuli with fluctuating intensity are applied to 27 healthy human participants. The participants are asked to provide ratings of perceived as well as predicted pain intensity. Using an advanced modelling strategy, the results reveal that statistical expectations and confidence scale the judgment of pain in sequences of noxious stimuli as predicted by hierarchical Bayesian inference theory.

Strengths:<br /> This is a highly interesting and novel finding with potential implications for the understanding and treatment of chronic pain where pain regulation is deficient. The paradigm is clear, the analysis is state-of-the-art, the results are convincing, and the interpretation is adequate.

Reviewer #3 (Public Review):

Summary:<br /> I am pleased to have had the opportunity to review this manuscript, which investigated the role of statistical learning in the modulation of pain perception. In short, the study showed that statistical aspects of temperature sequences, with respect to specific manipulations of stochasticity (i.e., randomness of a sequence) and volatility (i.e., speed at which a sequence unfolded) influenced pain perception. Computational modelling of perceptual variables (i.e., multi-dimensional ratings of perceived or predicted stimuli) indicated that models of perception weighted by expectations were the best explanation for the data. My comments below are not intended to undermine or question the quality of this research. Rather, they are offered with the intention of enhancing what is already a significant contribution to the pain neuroscience field. Below, I highlight the strengths and weaknesses of the manuscript and offer suggestions for incorporating additional methodological details.

Strengths:<br /> - The manuscript is articulate, coherent, and skilfully written, making it accessible and engaging.

- The innovative stimulation paradigm enables the exploration of expectancy effects on perception without depending on external cues, lending a unique angle to the research.

- By including participants' ratings of both perceptual aspects and their confidence in what they perceived or predicted, the study provides an additional layer of information to the understanding of perceptual decision-making. This information was thoughtfully incorporated into the modelling, enabling the investigation of how confidence influences learning.

- The computational modelling techniques utilised here are methodologically robust. I commend the authors for their attention to model and parameter recovery, a facet often neglected in previous computational neuroscience studies.

- The well-chosen citations not only reflect a clear grasp of the current research landscape but also contribute thoughtfully to ongoing discussions within the field of pain neuroscience.

Weaknesses:<br /> - In Figure 1, panel C, the authors illustrate the stimulation intensity, perceived intensity, and prediction intensity on the same scale, facilitating a more direct comparison. It appears that the stimulation intensity has been mathematically transformed to fit a scale from 0 to 100, aligning it with the intensity ratings corresponding to either past or future stimuli. Given that the pain threshold is specifically marked at 50 on this scale, one could logically infer that all ratings falling below this value should be deemed non-painful. However, I find myself uncertain about this interpretation, especially in relation to the term "arbitrary units" used in the figure. I would greatly appreciate clarification on how to accurately interpret these units, as well as an explanation of the relationship between these values and the definition of pain threshold in this experiment.

- The method of generating fluctuations in stimulation temperatures, along with the handling of perceptual uncertainty in modelling, requires further elucidation. The current models appear to presume that participants perceive each stimulus accurately, introducing noise only at the response stage. This assumption may fail to capture the inherent uncertainty in the perception of each stimulus intensity, especially when differences in consecutive temperatures are as minimal as 1{degree sign}C.

- A key conclusion drawn is that eKF is a better model than eRL. However, a closer examination of the results reveals that the two models behave very similarly, and it is not clear that they can be readily distinguished based on model recovery and model comparison results.

Regarding model recovery, the distinction between the eKF and eRL models seems blurred. When the simulation is based on the eKF, there is no ability to distinguish whether either eKF or eRL is better. When the simulation is based on the eRL, the eRL appears to be the best model, but the difference with eKF is small. This raises a few more questions. What is the range of the parameters used for the simulations? Is it possible that either eRL or eKF are best when different parameters are simulated? Additionally, increasing the number of simulations to at least 100 could provide more convincing model recovery results.

Regarding model comparison, the authors reported that "the expectation-weighted KF model offered a better fit than the eRL, although in conditions of high stochasticity, this difference was short of significance against the eRL model." This interpretation is based on a significance test that hinges on the ratio between the ELPD and the surrounding standard error (SE). Unfortunately, there's no agreed-upon threshold of SEs that determines significance, but a general guideline is to consider "several SEs," with a higher number typically viewed as more robust. However, the text lacks clarity regarding the specific number of SEs applied in this test. At a cursory glance, it appears that the authors may have employed 2 SEs in their interpretation, while only depicting 1 SE in Figure 4.

- With respect to parameter recovery, a few additional details could be included for completeness. Specifically, while the range of the learning rate is understandably confined between 0 and 1, the range of other simulated parameters, particularly those without clear boundaries, remains ambiguous. Including scatter plots with the simulated parameters on the x-axis and the recovered parameters on the y-axis would effectively convey this missing information. Furthermore, it would be beneficial for the authors to clarify whether the same priors were used for both the modelling results presented in the main paper and the parameter recovery presented in the supplementary material.

- While the reliance on R-hat values for convergence in model fitting is standard, a more comprehensive assessment could include estimates of the effective sample size (bulk_ESS and/or tail_ESS) and the Estimated Bayesian Fraction of Missing Information (EBFMI), to show efficient sampling across the distribution. Consideration of divergences, if any, would further enhance the reliability of the results.

- The authors write: "Going beyond conditioning paradigms based in cuing of pain outcomes, our findings offer a more accurate description of endogenous pain regulation." Unfortunately, this statement isn't substantiated by the results. The authors did not engage in a direct comparison between conditioning and sequence-based paradigms. Moreover, even if such a comparison had been made, it remains unclear what would constitute the gold standard for quantifying "endogenous pain regulation."