Reviewer #2 (Public review):

Summary:

In this manuscript, Arnould et. al. develop an unbiased, affinity-guided reagent to label P2X7 receptor and use super-resolution imaging to monitor P2X7 redistribution in response to inflammatory signaling.

Strengths:

I think the X7-uP probe that they developed is very useful for visualizing localization of P2X7 receptor. They convincingly show that under inflammatory conditions, there is a reorganization of P2X7 localization into receptor clusters. Moreover, I think they have shown a very clever way to specifically label any receptor of interest. This has broad appeal

Weaknesses:

Overall, the manuscript is novel and interesting. However, I do have some suggestions for improvement.

(1) While the authors state that chemical modification of AZ10606120 to produce the X7-UP reagent has "minimal impact" on the inhibition of P2X7, we can see from Figure 2A and 2B that it does not antagonize P2X7 as effectively as the original antagonist. For the sake of completeness and quantitation, I think it would be great if the authors could determine the IC50 for X7-uP and compare it to the IC50 of AZ10606120.

(2) Do the authors know whether modification of the lysines with biotin affects the receptor's affinity for ATP (or ability to be activated by ATP)? What about P2X7 that has been modified with biotin and then labeled with Alexa 647? For the sake of completeness and quantitation, I think it would be great if the authors could determine the EC50 of biotinylated P2X7 for ATP as well as biotinylated and then Alexa 647 labeled P2X7 for ATP and compare these values to the affinity of unmodified WT P2X7 for ATP.

(3) It is a little misleading to color the fluorescence signal from mScarlet green (for example, in Figure 3 and Figure 4). The fluorescence is not at the same wavelength as GFP. In fact, the wavelength (570 nm - 610 nm) for emission is closer to orange/red than to green. I think this color should be changed to differentiate the signal of mScarlet from the GFP signal used for each of the other P2X receptor subtypes.

(4) It is my understanding that P2X6 does not form homotrimers. Thus, I was a little surprised to see that the density and distribution of P2X6-GFP in Figure 3 looks very similar to the density and distribution of the other P2X subtypes. Do the authors have an explanation for this? Are they looking at P2X6 protomers inserted into the plasma membrane? Does the cell line have endogenous P2X receptor subtypes? Is Figure 3 showing heterotrimers with P2X6 receptor? A little explanation might be helpful.

(5) It is easy to overlook the fact that the antagonist leaves the binding pocket once the biotin has been attached to the lysines. It might be helpful if the authors made this a little more apparent in Figure 1 or in the text describing the NASA chemistry reaction.

Reviewer #3 (Public review):

Summary:

This manuscript describes the development of a covalent labeling probe (X7-uP) that selectively targets and tags native P2X7 receptors at the plasma membrane of BV2 microglial cells. Using super-resolution imaging (dSTORM), the authors demonstrate that P2X7 receptors form nanoscale clusters upon microglial activation by lipopolysaccharide (LPS) and ATP, correlating with synergistic IL-1β release. These findings advance understanding of P2X7 reorganization during inflammation and provide a generalizable labeling strategy for monitoring endogenous P2X7 in immune cells.

Strengths:

(1) The authors designed X7-uP by coupling a high-affinity, P2X7-specific antagonist (AZ10606120) with N-cyanomethyl NASA chemistry to achieve site-directed biotinylation. This approach offers high specificity, minimal off-target reactivity, and a straightforward pull-down/imaging readout.<br /> (2) The results connect P2X7's nanoscale clustering directly with IL-1β secretion in microglia, reinforcing the role of P2X7 in inflammation. By localizing endogenous P2X7 at single-molecule resolution, the authors reveal how LPS priming and ATP stimulation synergistically reorganize the receptor.<br /> (3) The authors systematically validate their method in recombinant systems (HEK293 cells) and in BV2 cells, showing selective inhibition, mutational confirmation of the binding site, and Western blot pulldown experiments.

Weaknesses:

(1) While the data strongly indicate that P2X7 clustering contributes to IL-1β release, the manuscript would benefit from additional experiments (if feasible) or discussion on how receptor clustering interfaces with downstream inflammasome assembly. Clarification of whether the P2X7 clusters physically colocalize with known inflammasome proteins would solidify the mechanism.<br /> (2) The authors might expand on the scope of X7-uP in other native cells that endogenously express P2X7 (e.g., macrophages, dendritic cells). Although they mention the possibility, demonstrating the probe's applicability in at least one other primary immune cell type would strengthen its general utility.<br /> (3) The authors do include appropriate negative controls, yet providing additional details (e.g., average single-molecule on-time or blinking characteristics) in supplementary materials could help readers assess cluster calculations.

Reviewer #1 (Public review):

Although the use of antimony has been discontinued in India, the observation that Leishmania parasites resistant to antimony are in circulation has been cited as evidence that these resistant parasites are now a distinct strain with properties that ensure their transmission and persistence. It is of interest to determine the properties that favor the retention of their drug resistance phenotype even in the absence of the selective pressure that the drug would otherwise exert. The hypothesis that these authors set out to test is that these parasites have developed a new capacity to acquire and utilize lipids, especially cholesterol, which enables them to grow robustly in infected hosts. The authors present compelling evidence that supports their hypothesis. However, the genetic basis for the parasite's gluttony for lipids remains unresolved.

An issue raised in the initial review was the insufficient detail in the discussion of experiments in which parasitophorous vacuoles were isolated from infected cells and their molecular content was investigated. In this new version, the authors have provided more details of those experiments, including the relative enrichment of the preparations.

A puzzling observation for which they provide compelling evidence is the capacity of LD-R parasites to undergo logarithmic growth between 4 and 24 hours in infected cells. Interestingly, after logarithmic growth within the macrophages at those early times, parasite growth slows down inexplicably after 24 hours. One is left to imagine what the consequences of such growth within an infected host will be.

They made the novel observation that Lamp1 expression increases as early as 4 hours after infection with LD-R and by 12 hours after infection with both LD-S and LD-R. Interestingly, transcription analysis did not provide evidence for increased Lamp1 transcripts, leaving open the possibility that parasite infection may exert control over host cell biology at the translational level. How this might be achieved and what genes would be targets for such controls are open questions.

The dynamic changes in lipid biosynthesis pathways, in comparison to lipid uptake and the formation of lipid droplets in infected cells, are tracked. The basis for the beneficial effect of aspirin to stifle parasite resistance to antimony is explored.

Reviewer #2 (Public review):

Summary:

Idiopathic scoliosis (IS) is a common spinal deformity. Various studies have linked genes to IS, but underlying mechanisms are unclear such that we still lack understanding of the causes of IS. The current manuscript analyzes IS patient populations and identified EPHA4 as a novel associated gene, finding three rare variants in EPHA4 from three patients (one disrupting splicing and two missense variants) as well as a large deletion (encompassing EPHA4) in a Waardenburg syndrome patient with scoliosis. EPHA4 is a member of the Eph receptor family. Drawing on data from zebrafish experiments, the authors argue that EPHA4 loss of function disrupts central pattern generator (CPG) function necessary for motor coordination.

Strengths:

The main strength of this manuscript is the human genetic data, which provide convincing evidence linking EPHA4 variants to IS. The loss of function experiments in zebrafish strongly support the conclusion that EPHA4 variants that reduce function lead to IS.

Weaknesses:

The conclusion that disruption of CPG function causes spinal curves in the zebrafish model is not fully supported. The authors' final model is that a disrupted CPG leads to asymmetric mechanical loading on the spine and, over time, the development of curves. This is a reasonable idea, but currently not strongly backed up by data in the manuscript. Potentially, the impaired larval movements simply coincide with, but do not cause, juvenile-onset scoliosis. Support for the authors' conclusion would require independent methods of disrupting CPG function and determining if this is accompanied by spine curvature. Nevertheless, the data showing correlations between spine curvature and abnormal neural patterning, neuronal firing, and swimming in eph4a loss-of-function mutant larvae are sound.

Comments on revisions:

I think the authors misunderstood my point about genetic nomenclature for the zebrafish alleles. The nomenclature guidelines are described at ZFIN, and ZFIN will ask for appropriate allele designations.

Reviewer #1 (Public review):

Public Review

The authors investigated the role of the C. elegans Flower protein, FLWR-1, in synaptic transmission, vesicle recycling, and neuronal excitability. They confirmed that FLWR-1 localizes to synaptic vesicles and the plasma membrane and facilitates synaptic vesicle recycling at neuromuscular junctions. They observed that hyperstimulation results in endosome accumulation in flwr-1 mutant synapses, suggesting that FLWR-1 facilitates the breakdown of endocytic endosomes. Using tissue-specific rescue experiments, the authors showed that expressing FLWR-1 in GABAergic neurons restored the aldicarb-resistant phenotype of flwr-1 mutants to wild-type levels. By contrast, cholinergic neuron expression did not rescue aldicarb sensitivity at all. They also showed that FLWR-1 removal leads to increased Ca2+ signaling in motor neurons upon photo-stimulation. From these findings, the authors conclude that FLWR-1 helps maintain the balance between excitation and inhibition (E/I) by preferentially regulating GABAergic neuronal excitability in a cell-autonomous manner.

Overall, the work presents solid data and interesting findings, however the proposed cell-autonomous model of GABAergic FLWR-1 function may be overly simplified in my opinion.

Most of my previous comments have been addressed; however, two issues remain.

(1) I appreciate the authors' efforts conducting additional aldicarb sensitivity assays that combine muscle-specific rescue with either cholinergic or GABergic neuron-specific expression of FLWR-1. In the revised manuscript, they conclude, "This did not show any additive effects to the pure neuronal rescues, thus FLWR-1 effects on muscle cell responses to cholinergic agonists must be cell-autonomous." However, I find this interpretation confusing for the reasons outlined below.

Figure 1 - Figure Supplement 3B shows that muscle-specific FLWR-1 expression in flwr-1 mutants significantly restores aldicarb sensitivity. However, when FLWR-1 is co-expressed in both cholinergic neurons and muscle, the worms behave like flwr-1 mutants and no rescue is observed. Similarly, cholinergic FLWR-1 alone fails to restore aldicarb sensitivity (shown in the previous manuscript). These observations indicate a non-cell-autonomous interaction between cholinergic neurons and muscle, rather than a strictly muscle cell-autonomous mechanism. In other words, FLWR-1 expressed in cholinergic neurons appears to negate or block the rescue effect of muscle-expressed FLWR-1. Therefore, FLWR-1 could play a more complex role in coordinating physiology across different tissues. This complexity may affect interpretations of Ca2+ dynamics and/or functional data, particularly in relation to E/I balance, and thus warrants careful discussion or further investigation.

(2) The revised manuscript includes new GCaMP analyses restricted to synaptic puncta. The authors mention that "we compared Ca2+ signals in synaptic puncta versus axon shafts, and did not find any differences," concluding that "FLWR-1's impact is local, in synaptic boutons." This is puzzling: the similarity of Ca2+ signals in synaptic regions and axon shafts seems to indicate a more global effect on Ca2+ dynamics or may simply reflect limited temporal resolution in distinguishing local from global signals due to rapid Ca2+ diffusion. The authors should clarify how they reached the conclusion that FLWR-1 has a localized impact at synaptic boutons, given that synaptic and axonal signals appear similar. Based on the presented data, the evidence supporting a local effect of FLWR-1 on Ca2+ dynamics appears limited.

Reviewer #2 (Public review):

Summary:

The Flower protein is expressed in various cell types, including neurons. Previous studies in flies have proposed that Flower plays a role in neuronal endocytosis by functioning as a Ca2+ channel. However, its precise physiological roles and molecular mechanisms in neurons remain largely unclear. This study employs C. elegans as a model to explore the function and mechanism of FLWR-1, the C. elegans homolog of Flower. This study offers intriguing observations that could potentially challenge or expand our current understanding of the Flower protein. Nevertheless, further clarification or additional experiments are required to substantiate the study's conclusions.

Strengths:

A range of approaches was employed, including the use of a flwr-1 knockout strain, assessment of cholinergic synaptic activity via analyzing aldicarb (a cholinesterase inhibitor) sensitivity, imaging Ca2+ dynamics with GCaMP3, analyzing pHluorin fluorescence, examination of presynaptic ultrastructure by EM, and recording postsynaptic currents at the neuromuscular junction. The findings include notable observations on the effects of flwr-1 knockout, such as increased Ca2+ levels in motor neurons, changes in endosome numbers in motor neurons, altered aldicarb sensitivity, and potential involvement of a Ca2+-ATPase and PIP2 binding in FLWR-1's function.

The authors have adequately addressed most of my previous concerns, however, I recommend minor revisions to further strengthen the study's rigor and interpretation:

Major suggestions

(1) This study relies heavily on aldicarb assays to support its conclusions. While these assays are valuable, their results may not fully align with direct assessment of neurotransmitter release from motor neurons. For instance, prior work has shown that two presynaptic modulators identified through aldicarb sensitivity assays exhibited no corresponding electrophysiological defects at the neuromuscular junction (Liu et al., J Neurosci 27: 10404-10413, 2007). Similarly, at least one study from the Kaplan lab has noted discrepancies between aldicarb assays and electrophysiological analyses. The authors should consider adding a few sentences in the Discussion to acknowledge this limitation and the potential caveats of using aldicarb assays, especially since some of the aldicarb assay results in this study are not easily interpretable.

(2) The manuscript states, "Elevated Ca2+ levels were not further enhanced in a flwr-1;mca-3 double mutant." (lines 549-550). However, Figure 7C does not include statistical comparisons between the single and double mutants of flwr-1 and mca-3. Please add the necessary statistical analysis to support this statement.

(3) The term "Ca2+ influx" should be avoided, as this study does not provide direct evidence (e.g. voltage-clamp recordings of Ca2+ inward currents in motor neurons) for an effect of the flwr-1 mutation of Ca2+ influx. The observed increase in neuronal GCaMP signals in response to optogenetic activation of ChR2 may result from, or be influenced by, Ca2+ mobilization from of intracellular stores. For example, optogenetic stimulation could trigger ryanodine receptor-mediated Ca2+ release from the ER via calcium-induced calcium release (CICR) or depolarization-induced calcium release (DICR). It would be more appropriate to describe the observed increase in Ca2+ signal as "Ca2+ elevation" rather than increased "Ca2+ influx".

Reviewer #1 (Public review):

Summary:

In this study from Belato, Knight and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed molecular dynamics and functional experiments on full-length GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the guide RNA binding or cleavage activities of the mutant GeoCas9 variants.

Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and can serve as the basis for future similar studies of GeoCas9 Rec domain mutants. While the two mutants tested in the study did not produce significant differences from wild-type GeoCas9, the study rules out the possibility that analogous mutations can be translated between type II-A and II-C Cas9 orthologs. Together, these findings may provide the grounds for future engineering of higher fidelity variants of GeoCas9

Reviewer #2 (Public review):

The manuscript from Belato et al., used advanced NMR approaches and a mutagenesis campaign probe the conformational dynamics of the recognition lobe (Rec) of the CRISPR Cas9 enzyme from G. stearothermophilus (GeoCas9). Using truncated and full-length constructs they assess the impacts of two different point mutations have on the redistribution and timescale of these motions and assess gRNA recognition and specificity. Single point mutations in the Rec domain in a Cas9 from a related species had profound impacts on- and off-target DNA editing, therefore the authors reasoned analogous mutations in GeoCas9 would have similar effects. However, despite a redistribution of local motions and changes in global stability, their chosen mutations had little impact on DNA editing in the context of the full-length enzyme.

In their revised manuscript, the authors were highly responsive to the reviewer's comments incorporating new experimental results including molecular dynamics simulations and RNA binding data using full-length GeoCas9, as well as reframing their discussion and conclusions in consideration of the new data. They were receptive to suggestions for clarification in both the text and methods section. With these changes, the manuscript has been significantly improved.

Their studies highlight the species-specific complexity of interdomain communication and allosteric mechanisms used by these multi-domain endonucleases. The noted strengths of the article remain, and despite the negative results, their approach will garner interest from investigators interested in understanding how the activity and specificity of these enzymes can be engineered to tune activity and limit off-target cleavage by these enzymes. Generally, the manuscript highlights the challenges of studying the effect of allosteric networks on protein function, particularly in multidomain proteins, and thus will be of broad interest to the community.

Reviewer #3 (Public review):

The authors explore the role of Rec domains in a thermophilic Cas9 enzyme. They report on the crystal structure of part of the recognition lobe, its dynamics from NMR spin relaxation and relaxation-dispersion data, its interaction mode with guide RNA, and the effect of two single-point mutations hypothesised to enhance specificity. They find that mutations have small effects on Rec domain structure and stability but lead to significant rearrangement of micro- to milli-second dynamics which does not translate into major changes in guide RNA affinity or DNA cleavage specificity, illustrating the inherent tolerance of GeoCas9. The work can be considered as a first step towards understanding motions in GeoCas9 recognition lobe, although no clear hotspots were discovered with potential for future rational design of enhanced Cas9 variants.

Strengths:

- Detailed biophysical and structural investigation, despite a few technical limitations inherent with working with complex targets, provides converging evidence that molecular dynamics embedded in the recognition lobes allow GeoCas9 to operate on a broad range of substrates.<br /> - Since the authors and others have shown that substrate specificity is dictated by equivalent hotspot mutations in other Cas9 variants, we are one step closer to understanding this phenomenon.

Weaknesses:

- Since the mutations investigated here do not significantly affect substrate binding or enzymatic activity, it is difficult to rationalize anything for enzyme engineering at this point.<br /> - Further investigation of the determinants of the observed dynamic modes, and follow-up with rationally designed mutations would hopefully allow to create a real model of the mechanism, but I do understand that this goes beyond the scope of this study.

Reviewer #1 (Public review):

Summary.

The authors goal was to map the neural circuitry underlying cold sensitive contraction in Drosophila. The circuitry underlying most sensory modalities has been characterized but noxious cold sensory circuitry has not been well studied. Importantly, they analyze all downstream partner neurons connected to the Class III sensory neurons. The authors achieve their goal and map out sensory and post-sensory neurons involved in this behavior.

Strengths.

The manuscript provides compelling evidence for sensory and post sensory neurons involved in noxious cold sensitive behavior. They use both connectivity data and functional data to identify these neurons. This work is a clear advance in our understanding of noxious cold behavior. The experiments are done with a high degree of experimental rigor.

Weaknesses.

I find no major weaknesses in this work. It is a massive amount of data that clearly shows the role of the Class III neurons in cold-induced larval body contraction.

Reviewer #2 (Public review):

Patel et al perform the analysis of neurons in a somatosensory network involved in responses to noxious cold in Drosophila larva. Using a combination of behavioral experiments, Calcium imaging, optogenetics and synaptic connectivity analysis in the Drosophila larval they assess the function of circuit elements in the somatosensory network downstream of multimodal somatosensory neurons involved in innocuous and noxious stimuli sensing and probe their function in noxious cold processing, Consistent with their previous findings they find the multidendritic class III neurons , to be the key cold sensing neurons that are both required and sufficient for the CT behaviors response (shown to evoked by noxious cold). They further investigate the downstream neurons identified based on literature and connectivity from EM at different stages of sensory processing characterize the different phenotypes upon activating/silencing those neurons and monitor their responses to noxious cold. The work reveals diverse phenotypes for the different neurons studied and provides the groundwork for understanding how information is processed in the nervous system from sensory input to motor output and how information from different modalities is processed by neuronal networks. However, at times the writing could be clearer and some results interpretations more rigorous

Reviewer #3 (Public review):

Summary:

The authors follow up on prior studies where they have argued for the existence of cold nociception in Drosophila larvae. In the proposed pathway, mechanosensitive Class III multidendritic neurons are the noxious cold responding sensory cells. The current study attempts to explore the potential roles of second and third order neurons, based on information of the Class III neuron synaptic outputs that has been obtained from the larval connectome.

Strengths:

The major strength of the manuscript is the detailed discussion of the second and third order neurons that are downstream of the mechanosensory Class III multidendritic neurons. These will be useful in further studies of gentle touch mechanosensation and mechanonociception both of which rely on sensory input from these cells. Calcium imaging experiments on Class III activation with optogenetics support the wiring diagram.

Weaknesses:

The scientific premise is that a full body contraction in larvae that are exposed to noxious cold is a sensorimotor behavioral pathway. This premise is, to start with, questionable. A common definition of behavior is a set of "orderly movements with recognizable and repeatable patterns of activity produced by members of a species (Baker et al., 2001)." In the case of nociception behaviors, the patterns of movement are typically thought to play a protective role and to protect from potential tissue damage.

Does noxious cold elicit a set of orderly movements with a recognizable and repeatable pattern in larvae? Can the patterns of movement that are stimulated by noxious cold allow the larvae to escape harm? Based on the available evidence, the answer to both questions is seemingly no. In response to noxious cold stimulation many, if not all, of the muscles in the larva, simultaneously contract (Turner et al., 2016) and as a result the larva becomes stationary. In response to cold, the larva is literally "frozen" in place and it is incapable of moving away. This incapacitation by cold is the antithesis of what one might expect from a behavior that protects the animals from harm.

An extensive literature has investigated the physiological responses of insects to cold (reviewed in Overgaard and MacMillan, 2017). In numerous studies of insects across many genera (excluding cold adapted insects such as snow flies), exposure to very cold temperatures quickly incapacitates the animal and induces a state that is known as a chill coma. During a chill coma the insect becomes immobilized by the cold exposure, but if the exposure to cold is very brief the insect can often be revived without apparent damage. Indeed, it is common practice for many laboratories that use adult Drosophila for studies of behavior to use a brief chilling on ice as a form of anesthesia because chilling is less disruptive to subsequent behaviors than the more commonly used carbon dioxide anesthesia. If flies were to perceive cold as a noxious nociceptive stimulus, then this "chill coma" procedure would likely be disruptive to behavioral studies, but is not. Furthermore, there is no evidence to suggest that larval sensation of "noxious cold" is aversive.

The insect chill coma literature has investigated the effects of extreme cold on the physiology of nerves and muscle and the consensus view of the field is that the paralysis that results from cold is due to complex and combined action of direct effects of cold on muscle and on nerves (Overgaard and MacMillan, 2017). Electrophysiological measurements of muscles and neurons find that they are initially depolarized by cold, and after prolonged cold exposure they are unable to maintain potassium homeostasis and this eventually inhibits the firing of action potentials (Overgaard and MacMillan, 2017). The very small thermal capacitance of a Drosophila larva means that its entire neuromuscular system will be quickly exposed to the effect of cold in the behavioral assays under consideration here. It would seem impossible to disentangle the emergent properties of a complex combination of effects on physiology (including neuronal, glial, and muscle homeostasis) on any proposed sensorimotor transformation pathway.

Nevertheless, the manuscript before us makes a courageous attempt at attempting this. A number of GAL4 drivers tested in the paper are found to affect parameters of contraction behavior (CT) in cold exposed larvae in silencing experiments. However, notably absent from all of the silencing experiments are measurements of larval mobility following cold exposure. Thus, it is not known from the study if these manipulations are truly protecting the larvae from paralysis following cold exposure, or if they are simply reducing the magnitude of the initial muscle contraction that occurs immediately following cold (ie reducing CT). The strongest effect of silencing occurs with the 19-12-GAL4 driver which targets Class III neurons (but is not completely specific to these cells).

Optogenetic experiments for Class III neurons relying on the 19-12-GAL4 driver combined with a very strong optogenetic acuator (ChETA) show the CT behavior that was reported in prior studies. It should be noted that this actuator drives very strong activation, and other studies with milder optogenetic stimulation of Class III neurons have shown that these cells produce behavioral responses that resemble gentle touch responses (Tsubouchi et al 2012 and Yan et al 2013). As well, these neurons express mechanoreceptor ion channels such as NompC and Rpk that are required for gentle touch responses.

A major weakness of the study is that none of the second or third order neurons (that are downstream of CIII neurons) are found to trigger the CT behavioral responses even when strongly activated with the ChETA actuator (Figure 2 Supplement 2). These findings raise major concerns for this and prior studies and it does not support the hypothesis that the CIII neurons drive the CT behaviors.

Later experiments in the paper that investigate strong CIII activation (with ChETA) in combination with other second and third order neurons does support the idea activating those neurons can facilitate the body-wide muscle contractions. But many of the co-activated cells in question are either repeated in each abdominal neuromere or they project to cells that are found all along the ventral nerve cord, so it is therefore unsurprising that their activation would contribute to what appears to be a non-specific body-wide activation of muscles along the AP axis. As well, if these neurons are already downstream of the CIII neurons the logic of this co-activation approach is not particular clear. A more convincing experiment would be to silence the different classes of cells in the context of the optogenetic activation of CIII neurons to test for a block of the effects, a set of experiments that is notably absent from the study.

The authors argument that the co-activation studies support "a population code" for cold nociception is a very optimistic interpretation of a brute force optogenetics approach that ultimately results in an enhancement of a relatively non-specific body-wide muscle convulsion.

Comments on revisions:

The resubmitted version of this manuscript suffers from the same weaknesses that were raised in the prior round of review. The authors claim that muscles have been removed from the electrophysiological preparations of prior studies is overstated. A small subset of muscles are removed during their recording procedures and this does not rule out the possibility that mechanical forces that are generated by the remaining muscles are being sensed by the mechanosensory neurons.

Reviewer #1 (Public review):

Summary:

In this study, Nakagawa and colleagues report the observation that YAP is differentially localized, and thus differentially transcriptionally active, in spheroid cultures versus monolayer cultures. YAP is known to play a critical role in the survival of drug-tolerant cancer cells, and as such, the higher levels of basally activated YAP in monolayer cultures lead to higher fractions of surviving drug-tolerant cells relative to spheroid culture (or in vivo culture). The findings of this study, revealed through convincing experiments, are elegantly simple and straightforward, yet they add significantly to the literature in this field by revealing that monolayer cultures may actually be a preferential system for studying residual cell biology simply because the abundance of residual cells in this format is much greater than in spheroid or xenograft models. The potential linkage between matrix density and stiffness and YAP activation, while only speculated upon in this manuscript, is intriguing and a rich starting point for future studies.

Although this work, like any important study, inspires many interesting follow-on questions, I am limiting my questions to only a few minor ones, which may potentially be explored either in the context of the current study or in separate, follow-on studies.

Strengths:

The major strengths of the work are described above.

Weaknesses:

Rather than considering the following points as weaknesses, I instead prefer to think of them as areas for future study:

(1) Given the field's intense interest in the biology and therapeutic vulnerabilities of residual disease cells, I suspect that one major practical implication of this work could be that it inspires scientists interested in working in the residual disease space to model it in monolayer culture. However, this relies upon the assumption that drug-tolerant cells isolated in monolayer culture are at least reasonably similar in nature to drug-tolerant cells isolated from spheroid or xenograft systems. Is this true? An intriguing experiment that could help answer this question would be to perform gene expression profiling on a cell line model in the following conditions: monolayer growth, drug tolerant cells isolated from monolayer growth conditions, spheroid growth, drug tolerant cells isolated from spheroid growth conditions, xenograft tumors, and drug tolerant cells isolated from xenograft tumors. What are the genes and programs shared between drug-tolerant cells cultured in the three conditions above? Which genes and programs differ between these conditions? Data from this exercise could help provide additional, useful context with which to understand the benefits and pitfalls of modeling residual tumor cell growth in monolayer culture.

(2) In relation to the point above, there is an interesting and established connection between mesenchymal gene expression and YAP/TAZ signaling. For example, analyses of gene expression data from human tumors and cell lines demonstrate an extremely strong correlation between these two gene expression programs. Further, residual persister cancer cells have often been characterized as having undergone an EMT-like transition. From the analysis above, is there evidence that residual tumor cells with increased YAP signaling also exhibit increased mesenchymal gene expression?

Reviewer #2 (Public review):

The manuscript by Nakagawa R, et al describes a mechanism of how NSCLC cells become resistant to EGFR and KRAS G12C inhibition. Here, the authors focus on the initial cellular changes that occur to confer resistance and identify YAP activation as a non-genetic mechanism of acute resistance.

The authors performed an initial xenograft study to identify YAP nuclear localization as a potential mechanism of resistance to EGFRi. The increase in the stromal component of the tumors upon Afatinib treatment leads the authors to explore the response to these inhibitors in both 2D and 3D culture. The authors extend their findings to both KRAS G12C and BRAF inhibitors, suggesting that the mechanism of resistance may be shared along this pathway.

The paper would benefit from additional cell lines to determine the generalizability of the findings they presented. While the change in the localization of YAP upon Afatinib treatment was identified in a xenograft model, the authors do not return to animal models to test their potential mechanism, and the effects of the hyperactivated S127A YAP protein on Afatinib sensitivity in culture are modest. Also, combination studies of YAP inhibitors and EGFR/RAS/RAF inhibitors would have strengthened the studies.

Reviewer #1 (Public review):

Summary

Olfactory sensory neurons (OSNs) in the olfactory epithelium detect myriads of environmental odors that signal essential cues for survival. OSNs are born throughout life and thus represent one of the few neurons that undergo life-long neurogenesis. Until recently, it was assumed that OSN neurogenesis is strictly stochastic with respect to subtype (i.e. the receptor the OSN chooses to express). However, a recent study showed that olfactory deprivation via naris occlusion selectively reduced birthrates of only a fraction of OSN subtypes and indicated that these subtypes appear to have a special capacity to undergo changes in birthrates in accordance with the level of olfactory stimulation. These previous findings raised the interesting question of what type of stimulation influences neurogenesis, since naris occlusion does not only reduce the exposure to potentially thousands of odors, but also to more generalized mechanical stimuli via preventing airflow.

In this study, the authors set out to identify the stimuli that are required to promote the neurogenesis of specific OSN subtypes. Specifically, they aim to test the hypothesis if discrete odorants selectively stimulate the same OSN subtypes whose birthrates are affected. This would imply a highly specific mechanism in which exposure to certain odors can "amplify" OSN subtypes responsive to those odors suggesting that OE neurogenesis serves, in part, an adaptive function.

To address this question, the authors focused on a family of OSN subtypes that had previously been identified to respond to musk-related odors and that exhibit higher transcript levels in the olfactory epithelium of mice exposed to males compared to mice isolated from males. First, the authors confirm via a previously established cell birth dating assay in unilateral naris occluded mice that this increase in transcript levels actually reflects a stimulus-dependent birthrate acceleration of this OSN subtype family. In a series of experiments (in unilateral occluded and non-occluded mice) using the same birth dating assay, they show that several subtypes of this OSN family, but not other "control" subtypes exhibit increased birthrates in response to adolescent male exposure, but not to female exposure.

In the core experiment of the study, they expose unilaterally naris occluded and non-occluded mice to two musk-related odors and two "control" odors (that do not activate musk-responsive OSN subtypes) to test if these odors specifically accelerate the birth rates of OSN types that are responsive to these odors. This experiment reveals that (for the tested odors and OSN subtypes) indeed birthrates are only affected by discrete odorants that stimulate these OSN subtypes (with a complex relationship between birth rate acceleration and odor concentrations) suggesting that OE neurogenesis may serve, in part, as an adaptive function

Strength:

The scientific question is valid and opens an interesting direction. The previously established cell birth dating assay in naris occluded and non-occluded mice is well performed and accompanied by several control experiments addressing potential other interpretations of the data.

In this revised version, the authors added several new experiments addressing the previous concern that only the effect of one specific odor (muscone) on musk-responsive OSN subtypes had been tested to make the general claim that discrete odors specifically accelerate the birth rate of OSN subtypes they stimulate. Now the authors demonstrate that another musk-related odor (ambretone) also induces this effect and that other non-musk odors do not. In addition, they show that two other OSN subtypes that do not respond to musk-related odors are not affected. These experiments further substantiate the above claim.

Weakness:

(1) The main research question of this study was to test if discrete odors specifically accelerate the birth rate of OSN subtypes they stimulate, i.e. does muscone only accelerate the birth rate of OSNs that express muscone-responsive ORs, or vice versa is the birthrate of muscone-responsive OSNs only accelerated by odors they respond to?<br /> As mentioned under "strength" the authors added several experiments to further substantiate their claim. While these controls are very important to show that the observed effect is indeed specific for musk-related odors on musk-responsive OSN subtypes, these experiments still only focus on one closely related family of musk-responsive OSN subtypes. To understand if this phenomenon is a more generalized mechanism and plays a role for other OSN subtypes beyond this small family of related receptors, further experiments showing this effect for other OSN subtypes are critical.

(2) Previous concerns (#2, #4, #5 and #6) about a lack of increase in UNO effect size for olfr1440 under any muscone concentrations, strong fluctuations of newborn neurons on the closed side as well as a seemingly contradicting statement that overstimulation possibly reflects reduced survival have been addressed by adding potential explanations to the text.

In addition, the previous remark (#3) that certain phrases gave the misleading impression that musk-related odors are indeed excreted into male mouse urine at certain concentrations was addressed not only by re-phrasing, but by performing additional experiments. Although these did not deliver clear results (because of technical difficulties), interesting possibilities are discussed.

Reviewer #3 (Public review):

Summary

Neurogenesis in the mammalian olfactory epithelium continues throughout the animal's lifespan, replacing damaged or dying olfactory sensory neurons. It has been tacitly assumed that the replacement of olfactory receptor (OR) subtypes occurs randomly. However, anecdotal evidence has suggested otherwise. In this study, Santoro and colleagues challenge this assumption by systematically exploring three key questions: Is there enrichment of specific OR subtypes during neurogenesis? Is this enrichment influenced by sensory stimuli? Does enrichment result from differential generation of OR types or differential cell death regulated by neural activity? The authors present convincing evidence that muscone stimulus selectively enhances the neurogenesis of OSNs expressing muscone receptors, suggesting that the selection of ORs in regenerating neurons is not random.

Strengths

This study is the first in formulating and systematically testing the selective promotion hypothesis. It is a comprehensive and systematic examination of multiple musk receptors under conditions of unilateral naris occlusion and various stimuli. The controls are properly done. The quality of in situ hybridization and immunofluorescent staining is high, allowing the authors to effectively estimates the number of OR types. The data convincingly demonstrate that increased expression of musk receptors in response to male odor or muscone stimulation.

Weaknesses

The revised version has addressed most initial weaknesses. However, some inconsistencies remain, raising questions about the proposed model. For instance, in the unilateral naris occlusion experiment, although average expression of non-musk receptors shows no significant change, receptors seem to fall into two groups with one subset increasing and another decreasing (Fig. 1E). This suggests naris occlusion may regulate OR expression independently of odor-induced activity, a possibility that remains unaddressed.

There is curiosity regarding receptors for the male odor SBT, olfr912, and olfr1295, which exhibit increased expression on the occluded side. The explanation that SBT exposure shortens these neurons' lifespan lacks substantiation and is inconsistent with later data. For example, Figure 3-figure supplement 3 I does not show olfr912 changes on the UNO side, and Figure 4-figure supplement 4 shows no significant decrease in olfr912 expression in SBT-exposed mice. Additionally, single-cell RNASeq experiments did not examine olfr912 and olfr1295 expression.

While the study convincingly demonstrates muscone's selective stimulation of olfr235-expressing OSNs, it lacks exploration of the mechanisms underlying this specificity. The discussion of signaling pathways remains too generic.

In summary, while the study offers significant insights into neurogenesis and OR subtype enrichment, further investigation into underlying mechanisms and addressing existing inconsistencies would strengthen its conclusions.

Reviewer #1 (Public review):

Summary:

In this study, Le et al.. aimed to explore whether AAV-mediated overexpression of Oct4 could induce neurogenic competence in adult murine Müller glia, a cell type that, unlike its counterparts in cold-blooded vertebrates, lacks regenerative potential in mammals. The primary goal was to determine whether Oct4 alone, or in combination with Notch signaling inhibition, could drive Müller glia to transdifferentiate into bipolar neurons, offering a potential strategy for retinal regeneration.

The authors demonstrated that Oct4 overexpression alone resulted in the conversion of 5.1% of Müller glia into Otx2+ bipolar-like neurons by five weeks post-injury, compared to 1.1% at two weeks. To further enhance the efficiency of this conversion, they investigated the synergistic effect of Notch signaling inhibition by genetically disrupting Rbpj, a key Notch effector. Under these conditions, the percentage of Müller glia-derived bipolar cells increased significantly to 24.3%, compared to 4.5% in Rbpj-deficient controls without Oct4 overexpression. Similarly, in Notch1/2 double-knockout Müller glia, Oct4 overexpression increased the proportion of GFP+ bipolar cells from 6.6% to 15.8%.

To elucidate the molecular mechanisms driving this reprogramming, the authors performed single-cell RNA sequencing (scRNA-seq) and ATAC-seq, revealing that Oct4 overexpression significantly altered gene regulatory networks. They identified Rfx4, Sox2, and Klf4 as potential mediators of Oct4-induced neurogenic competence, suggesting that Oct4 cooperates with endogenously expressed neurogenic factors to reshape Müller glia identity.

Overall, this study aimed to establish Oct4 overexpression as a novel and efficient strategy to reprogram mammalian Müller glia into retinal neurons, demonstrating both its independent and synergistic effects with Notch pathway inhibition. The findings have important implications for regenerative therapies as they suggest that manipulating pluripotency factors in vivo could unlock the neurogenic potential of Müller glia for treating retinal degenerative diseases.

Strengths:

(1) Novelty: The study provides compelling evidence that Oct4 overexpression alone can induce Müller glia-to-bipolar neuron conversion, challenging the conventional view that mammalian Müller glia lacks neurogenic potential.<br /> (2) Technological Advances: The combination of Muller glia-specific labeling and modifying mouse line, AAV-GFAP promoter-mediated gene expression, single-cell RNA-seq, and ATAC-seq provides a comprehensive mechanistic dissection of glial reprogramming.<br /> (3) Synergistic Effects: The finding that Oct4 overexpression enhances neurogenesis in the absence of Notch signaling introduces a new avenue for retinal repair strategies.

Weaknesses:

(1) In this study, the authors did not perform a comprehensive functional assessment of the bipolar cells derived from Müller glia to confirm their neuronal identity and functionality.<br /> (2) Demonstrating visual recovery in a bipolar cell-deficiency disease model would significantly enhance the translational impact of this work and further validate its therapeutic potential.

Comments on revisions:

The author answered all my questions and corrected the minor comments, so I have no more comments on the manuscript.

Reviewer #2 (Public review):

Summary:

The authors harness single cell RNAseq data from zebrafish and mice to identify Oct4 as a candidate driver of neurogenesis. They then use adeno-associated virus vectors to show that while Oct4 overexpression alone converts rare adult Müller glia (MG) to bipolar cells, it synergizes with Notch pathway inhibition to cause this neurogenesis (achieved by Cre-mediated knockout of Rbpj floxed allele). Importantly, they genetically lineage-mark adult MG using a GLAST-CreER transgene and a Sun-GFP reporter, so that any non-MG cells that convert can be identified unambiguously. This is crucial because several high-profile papers made erroneous claims using short promoters in the viral delivery vector itself to mark MG, but those promoters are leaky and mark other non-MG cell types, making it impossible to definitively state whether manipulations studied were actually causing neurogenesis, or were merely the result of expression in pre-existing neurons. Once the authors establish Oct4 + RbpjKO synergy they use snRNAseq/ATACseq to identify known and novel transcription factors that could play a role in driving neurogenesis.

Strengths:

The system to mark MG is stringent, so the authors are studying transdifferentiation, not artifactual effects due to leaky viral promoters. The synergy between Oct4 and Notch pathway blockade is notable. The single cell results add the potential involvement of new players such as Rfx4 in adult-MG-neurogenesis.

Weaknesses:

The revised version is clear and there are no major weaknesses.

Overall, the authors achieved what they set out to do, and have made new insights into how neurogenesis can be stimulated in MG. Ultimately, a major long-term goal in the field is to replace lost photoreceptors as this is most relevant to many human visual disorders, and while this paper (like all others before it) does not generate rods or cones, it opens new strategies to coax MG to form a related neuronal cell type. Their approach underscores the benefits of using a gold standard approach for lineage tracing.

Reviewer #2 (Public review):

This study by Yu and coworkers investigates the potential role of Secretory leukocyte protease inhibitor (SLPI) in Lyme arthritis. They show that, after needle inoculation of the Lyme disease agent, B. burgdorferi, compared to wild type mice, a SLPI-deficient mouse suffers elevated bacterial burden, joint swelling and inflammation, pro-inflammatory cytokines in the joint, and levels of serum neutrophil elastase (NE). They suggest that SLPI levels of Lyme disease patients are diminished relative to healthy controls. Finally, using a powerful screen of secreted mammalian proteins, they find that SLPI interacts directly B. burgdorferi.

The known role of SLPI in dampening inflammation and inflammatory damage by inhibition of NE makes the enhanced inflammation in the joint of B. burgdorferi-infected mice a predicted result but it has not previously been demonstrated and could spur further study. A limitation that is unaddressed experimentally is potential contribution of the greater bacterial burden to the enhanced inflammation, leaving open the question of whether greater immunologic stimulus or a defect in the regulation of inflammation is responsible for the observed enhanced disease. Answering this question would better justify the statement in the abstract that "These data demonstrate the importance of SLPI in suppressing periarticular joint inflammation in Lyme disease."

Although the finding of SLPI binding to bacteria is potentially quite interesting the biological relevance of this interaction is not addressed. Readers of only the abstract, which describes the direct interaction of SLPI with bacteria, may mistakenly conclude that the authors demonstrate that recruitment of this immunoregulatory factor to the bacterial surface enhances inflammation of infected tissues. This attractive possibility has not been demonstrated in this study; such assertion would require comparison of bacteria that either bind or do not bind SLPI in a mouse infection model.

Finally, the investigators take advantage of clinical samples to ask if serum SLPI levels a diminished in Lyme disease patients relative to healthy controls. The assessment of human samples is interesting and generally to be lauded, but here the comparison is limited by: (a) a small sample number, with only 5 healthy control samples (which should not be difficult to obtain); and (b) the inclusion of samples from 4 patients with erythema migrans rather than Lyme arthritis, which was the manifestation tracked in the mouse studies. Moreover, of the 3 Lyme arthritis patients, serum samples from multiple blood draws were included, resulting in 5 data points; similarly, of the 4 erythema migrans patients, 13 separate samples were included. The multiple samplings from some but not all subjects could result in differential "weighting" of samples. Therefore, although the investigators provide a statistical analysis of these data, it is difficult to evaluate the validity of this apparent difference.

In summary, this is an interesting study that provides new information regarding infection in a host deficient in SLPI and, using a state-of-the-art screen of the mammalian secretome to show that B. burgdorferi binds SLPI, raising the attractive possibility that this pathogen utilizes a host immune regulator to enhance inflammation. The conclusions that SLPI enhances inflammation directly due to its immunoregulatory activity and that SLPI levels are diminished in human Lyme disease patients, as well as the implication that SLPI binding by the bacterium has pathogenic significance, each require further study.

Reviewer #1 (Public review):

The paper proposes an interesting perspective on the spatio-temporal relationship between FC in fMRI and electrophysiology. The study found that while similar networks configurations are found in both modalities, there is a tendency for the networks to spatially converge more commonly at synchronous than asynchronous timepoints.

My confidence in the findings and their interpretation has been improved by the addition of some basic simulations. It helps give confidence in the measure being used to distinguish between scenarios.

Of course, there may be other scenarios that are problematic that are not covered by the current simulations - this highlights the difficulty of making a claim based on a heuristic measure.

That said, with the simulations included and if the caveat above is acknowledged, then I think the paper is in good shape.

Reviewer #2 (Public review):

Summary:

The study investigates the brain's functional connectivity (FC) dynamics across different timescales using simultaneous recordings of intracranial EEG/source-localized EEG and fMRI. The primary research goal was to determine which of three convergence/divergence scenarios is the most likely to occur.

The results indicate that despite similar FC patterns found in different data modalities, the timepoints were not aligned, indicating spatial convergence but temporal divergence.

The researchers also found that FC patterns in different frequencies do not overlap significantly, emphasizing the multi-frequency nature of brain connectivity. Such asynchronous activity across frequency bands supports the idea of multiple connectivity states that operate independently and are organized into a multiplex system.

Strengths:

The data supporting the authors' claims are convincing and come from simultaneous recordings of fMRI and iEEG/EEG, which has been recently developed and adapted.

The analysis methods are solid and involved a novel approach to analyzing the co-occurrence of FC patterns across modalities (cross-modal recurrence plot, CRP) and robust statistics, including replication of the main results using multiple operationalizations of the functional connectome (e.g., amplitude, orthogonalized, and phase-based coupling).

In addition, the authors provided a detailed interpretation of the results, placing them in the context of recent advances and understanding of the relationships between functional connectivity and cognitive states.

The authors also did a control analysis and verified the effect of temporal window size or different functional connecvitity operationalizations. I also applaud their effort to make the analysis code open-sourced.

Comments on revisions:

The authors addressed all my concerns in the previous round of review.

Reviewer #1 (Public review):

Summary:

Huntington's disease (HD) is characterized by the expansion of polyglutamine repeats in huntingtin protein (HTT), leading to the formation of aggresomes composed of mutant huntingtin (mHTT). This study investigates the potential therapeutic strategy of enhancing autophagy to clear mHTT. The authors' evaluation of the autophagic-lysosomal pathway (ALP) in human HD brains shows that, in early stages, there is upregulated lysosomal biogenesis and relatively normal autophagy flux, while late-stage brains exhibit impaired autolysosome clearance, suggesting that early intervention may be beneficial. The authors cross the Q175 HD knock-in model with the TRGL autophagy reporter mouse to investigate ALP dynamics in vivo. In these models, mHTT is detected in autophagic vacuoles and colocalizes with autophagy receptors p62/SQSTM1 and ubiquitin. Although ALP alterations in the Q175 model are milder and later onset compared to human HD, they do show lysosome depletion and impaired autophagic flux. Treatment with an mTOR inhibitor in 6-month-old TRGL/Q175 mice normalized lysosome numbers, alleviated aggresome pathology, and reduced mHTT, p62, and ubiquitin levels. These findings suggest that autophagy modulation during the early stages of disease progression may offer potential therapeutic interventions for HD pathology.

Strengths:

Provide supportive animal evidence for mTOR inhibition in enhancing autophagy and reducing toxicity in HD animal models.

Weaknesses:

Lacks animal behavior and survival rate data, particularly regarding whether the extent of motor dysfunction in TRGL/Q175 mice is comparable to that in Q175 mice and whether the administration of mTORi INK improves these symptoms.

Reviewer #2 (Public review):

Summary:

In this manuscript the authors have explored the beneficial effect of autophagy upregulation in the context of HD pathology in a disease stage-specific manner. The authors have observed functional autophagy lysosomal pathway (ALP) and its machineries at the early stage in HD mouse model, whereas impairment of ALP has been documented at the later stages of the disease progression. Eventually, the authors have taken advantage of operational ALP pathway at the early stage of HD pathology, in order to upregulate ALP and autophagy flux by inhibiting mTORC1 in vivo, which ultimately reverted back multiple ALP-related abnormalities and phenotypes. Therefore, this manuscript is a promising effort to shed light on the therapeutic interventions with which HD pathology can be treated at the patient level in future.

Strengths:

The study has shown alteration of ALP in HD mouse model in a very detailed manner. Such stage dependent in vivo study will be informative and has not been done before. Also, this research provides possible therapeutic intervention in patients in future.

Weaknesses:

In this revised version of the manuscript, the authors have satisfactorily addressed all the concerns raised by the reviewers. They have also provided futuristic viewpoints towards tackling neurodegenerative disorder, especially Huntington Disease (HD).

Reviewer #1 (Public review):

This report addresses a compelling topic. However, I have significant concerns, which necessitate a reassessment of the report's overall value.

Anatomical Specificity and Stimulation Site:<br /> While the authors clarify that the ventral MGB (MGv) was the intended stimulation target, the electrode track (Fig. 1A) and viral spread (Fig. 2E) suggest possible involvement of the dorsal MGB (MGd) and broader area. Given that MGv-AI and MGd-AC pathways have distinct-and sometimes opposing-effects on plasticity, the reported LTP values (with unusually small standard deviations) raise concerns about the specificity of the findings. Additional anatomical verification would help resolve this issue.

Statistical Rigor and Data Variability:<br /> The remarkably low standard deviations in LTP measurements are unexpected based on established variability in thalamocortical plasticity. The authors' response confirms these values are accurate, but further justification, such as methodological controls or replication-would bolster confidence in these results. Additionally, the comparison of in vivo vs. in vitro LTP variability requires more substantive support.

Viral Targeting and Specificity:<br /> The manuscript does not clearly address whether cortical neurons were inadvertently infected by AAV9. Given the potential for off-target effects, explicit confirmation (e.g., microphotograph of stimulation site) would strengthen the study's conclusions.

Integration of Prior Literature:<br /> The discussion of existing work is adequate but could be more comprehensive. A deeper engagement with contrasting findings would provide better context for the study's contributions.

Therapeutic Implications:<br /> The authors' discussion of therapeutic potential is now appropriately cautious and well-reasoned.

Conclusion:<br /> While the study presents intriguing findings, the concerns outlined above must be addressed to fully establish the validity and impact of the results. I appreciate the authors' efforts thus far and hope they can provide additional data or clarification to resolve these issues. With these revisions, the manuscript could make a valuable contribution to the field.

Reviewer #2 (Public review):

Summary:

This work used multiple approaches to show that CCK is critical for long-term potentiation (LTP) in the auditory thalamocortical pathway. They also showed that the CCK mediation of LTP is age-dependent and supports frequency discrimination. This work is important because is opens up a new avenue of investigation of the roles of neuropeptides in sensory plasticity.

Strengths:

The main strength is the multiple approaches used to comprehensively examine the role of CCK in auditory thalamocortical LTP. Thus, the authors do provide a compelling set of data that CCK mediates thalamocortical LTP in an age-dependent manner.

Weaknesses:

There are some details that should be addressed, primarily regarding potential baseline differences in comparison groups. The behavioral assessment is relatively limited, but may be fleshed out in future work.

Reviewer #3 (Public review):

Summary:

Cholecystokinin (CCK) is highly expressed in auditory thalamocortical (MGB) neurons and CCK has been found to shape cortical plasticity dynamics. In order to understand how CCK shapes synaptic plasticity in the auditory thalamocortical pathway, they assessed the role of CCK signaling across multiple mechanisms of LTP induction with the auditory thalamocortical (MGB - layer IV Auditory Cortex) circuit in mice. In these physiology experiments that leverage multiple mechanisms of LTP induction and a rigorous manipulation of CCK and CCK-dependent signaling, they establish an essential role of auditory thalamocortical LTP on the co-release of CCK from auditory thalamic neurons. By carefully assessing the development of this plasticity over time and CCK expression, they go on to identify a window of time that CCK is produced throughout early and middle adulthood in auditory thalamocortical neurons to establish a window for plasticity from 3 weeks to 1.5 years in mice, with limited LTP occurring outside of this window. The authors go on to show that CCK signaling and its effect on LTP in the auditory cortex is also capable of modifying frequency discrimination accuracy in an auditory PPI task. In evaluating the impact of CCK on modulating PPI task performance, it also seems that in mice <1.5 years old CCK-dependent effects on cortical plasticity is almost saturated. While exogenous CCK can modestly improve discrimination of only very similar tones, exogenous focal delivery of CCK in older mice can significantly improve learning in a PPI task to bring their discrimination ability in line with those from young adult mice.

Strengths:

(1) The clarity of the results, along with the rigor multi-angled approach, provide significant support for the claim that CCK is essential for auditory thalamocortical synaptic LTP. This approach uses a combination of electrical, acoustic, and optogenetic pathway stimulation alongside conditional expression approaches, germline knockout, viral RNA downregulation and pharmacological blockade. Through the combination of these experimental configures the authors demonstrate that high-frequency stimulation-induced LTP is reliant on co-release of CCK from glutamatergic MGB terminals projecting to the auditory cortex.

(2) The careful analysis of the CCK, CCKB receptor, and LTP expression is also a strength that puts the finding into the context of mechanistic causes and potential therapies for age-dependent sensory/auditory processing changes. Similarly, not only do these data identify a fundamental biological mechanism, but they also provide support for the idea that exogenous asynchronous stimulation of the CCKBR is capable of restoring an age-dependent loss in plasticity.

(3) Although experiments to simultaneously relate LTP and behavioral change or identify a causal relationship between LTP and frequency discrimination are not made, there is still convincing evidence that CCK signaling in the auditory cortex (known to determine synaptic LTP) is important for auditory processing/frequency discrimination. These experiments are key for establishing the relevance of this mechanism.

Weaknesses:

(1) Given the magnitude of the evoked responses, one expects that pyramidal neurons in layer IV are primarily those that undergo CCK-dependent plasticity, but the degree to which PV-interneurons and pyramidal neurons participate in this process differently is unclear.

(2) While these data support an important role for CCK in synaptic LTP in the auditory thalamocortical pathway, perhaps temporal processing of acoustic stimuli is as or more important than frequency discrimination. Given the enhanced responsivity of the system, it is unclear whether this mechanism would improve or reduce the fidelity of temporal processing in this circuit. Understanding this dynamic may also require consideration of cell type as raised in weakness #1.

(3) In Figure 1, an example of increased spontaneous and evoked firing activity of single neurons after HFS is provided. Yet it is surprising that the group data are analyzed only for the fEPSP. It seems that single neuron data would also be useful at this point to provide insight into how CCK and HFS affect temporal processing and spontaneous activity/excitability, especially given the example in 1F.

(4) The circuitry that determines PPI requires multiple brain areas, including the auditory cortex. Given the complicated dynamics of this process, it may be helpful to consider what, if anything, is known specifically about how layer IV synaptic plasticity in the auditory cortex may shape this behavior.

Comments on revisions:

The manuscript is much improved and many of the issues or questions have been addressed. Ideally, evidence for the degree of transsynaptic spread for AAV9-Syn-ChrimsonR-tdTomato would also be provided in some form since in the authors' response in sounds like some was observed, as expected.

Reviewer #1 (Public review):

Summary:

The manuscript provides a novel method for the automated detection of scent marks from urine and feces in rodents. Given the importance of scent communication in these animals and their role as model organisms, this is a welcome tool.

Strengths:

The method uses a single video stream to allow for the distinction between urine and feces. It is automated.

Weaknesses:

The accuracy is decent but not perfect and may be too low to detect some effects that are biologically real but subtle (e.g. less than 10% differences). For many assays, however, this tools will be useful.

Reviewer #1 (Public review):

About R squared in the plots:<br /> The authors have used a z-scored R squared in the main ridge regression plots. While this may be interpretable, it seems non-standard and overly complicated. The authors could use a simple Pearson r to be most direct and informative (and in line with similar work, including Goldstein et al. 2022 which they mentioned). This way the sign of the relationships is preserved.

About the new TRF analysis:<br /> The new TRF analysis is a necessary addition and much appreciated. However, it is missing the results for the acoustic regressors, which should be there analogous to the HM-LSTM ridge analysis. The authors should also specify which software they have utilized to conduct the new TRF analysis. It also seems that the linguistic predictors/regressors have been newly constructed in a way more consistent with previous literature (instead of using the HM-LSTM features); these specifics should also be included in the manuscript (did it come from Montreal Forced Aligner, etc.?). Now that the original HM-LSTM can be compared to a more standard TRF analysis, it is apparent that the results are similar.

The authors' wording about this suggests that these new regressors have a nonzero sample at each linguistic event's offset, not onset. This should also be clarified. As the authors know, the onset would be more standard, and using the offset has implications for understanding the timing of the TRFs, as a phoneme has a different duration than a word, which has a different duration from a sentence, etc.

About offsets:<br /> TRFs can still be interpretable using the offset timings though; however, the main original analysis seems to be utilizing the offset times in a different, more confusing way. The authors still seem to be saying that only the peri-offset time of the EEG was analyzed at all, meaning the vast majority of the EEG trial durations do not factor into the main HM-LSTM response results whatsoever. The way the authors describe this does not seem to be present in any other literature, including the papers that they cite. Therefore, much more clarification on this issue is needed. If the authors mean that the regressors are simply time-locked to the EEG by aligning their offsets (rather than their onsets, because they have varying onsets or some such experimental design complexity), then this would be fine. But it does not seem to be what the authors want to say. This may be a miscommunication about the methods, or the authors may have actually only analyzed a small portion of the data. Either way, this should be clarified to be able to be interpretable.

Reviewer #2 (Public review):

This study presents a valuable finding on the neural encoding of speech in listeners with normal hearing and hearing impairment, uncovering marked differences in how attention to different levels of speech information is allocated, especially when having to selectively attend to one speaker while ignoring an irrelevant speaker. The results overall support the claims of the authors, although a more explicit behavioural task to demonstrate successful attention allocation would have strengthened the study. Importantly, the use of more "temporally continuous" analysis frameworks could have provided a better methodology to assess the entire time course of neural activity during speech listening. Despite these limitations, this interesting work will be useful to the hearing impairment and speech processing research community.

The study compares speech-in-quiet vs. multi-talker scenarios, allowing to assess within-participant the impact that the addition of a competing talker has on the neural tracking of speech. Moreover, the inclusion of a population with hearing loss is useful to disentangle the effects of attention orienting and hearing ability. The diagnosis of high-frequency hearing loss was done as part of the experimental procedure by professional audiologists, leading to a high control of the main contrast of interest for the experiment. Sample size was big, allowing to draw meaningful comparisons between the two populations.

An HM-LSTM model was employed to jointly extract speech features spanning from the stimulus acoustics to word-level and phrase-level information, represented by embeddings extracted at successive layers of the model. The model was specifically expanded to include lower level acoustic and phonetic information, reaching a good representation of all intermediate levels of speech.

Despite conveniently extracting all features jointly, the HM-LSTM model processes linguistic input sentence-by-sentence, and therefore only allows to assess the corresponding EEG data at sentence offset. If I understood correctly, while the sentence information extracted with the HM-LSTM reflects the entire sentence - in terms of its acoustic, phonetic and more abstract linguistic features - it only gives a condensed final representation of the sentence. As such, feature extraction with the HM-LSTM is not compatible with a continuous temporal mapping on the EEG signal, and this is the main reason behind the authors' decision to fit a regression at nine separate time points surrounding sentence offsets.

While valid and previously used in the literature, this methodology, in the particular context of this experiment, might be obscuring important attentional effects impacted by hearing-loss. By fitting a regression only around sentence-final speech representations, the method might be overlooking the more "online" speech processing dynamics, and only assessing the permanence of information at different speech levels at sentence offset. In other words, the acoustic attentional bias between Attended and Unattended speech might exist even in hearing-impaired participants but, due to a lower encoding or permanence of acoustic information in this population, it might only emerge when using methodologies with a higher temporal resolution, such as Temporal Response Functions (TRFs). If a univariate TRF fit simply on the continuous speech envelope did not show any attentional bias (different trial lengths should not be a problem for fitting TRFs), I would be entirely convinced of the result. For now, I am unsure on how to interpret this finding.

Despite my doubts on the appropriateness of condensed speech representations and single-point regression for acoustic features in particular, the current methodology allows the authors to explore their research questions, and the results support their conclusions.

This work presents an interesting finding on the limits of attentional bias in a cocktail-party scenario, suggesting that fundamentally different neural attentional filters are employed by listeners with high-frequency hearing loss, even in terms of the tracking of speech acoustics. Moreover, the rich dataset collected by the authors is a great contribution to open science and will offer opportunities for re-analysis.

Reviewer #1 (Public review):

I want to reiterate my comment from the first round of reviews: that I am insufficiently familiar with the intricacies of Maxwell's equations to assess the validity of the assumptions and the equations being used by WETCOW. The work ideally needs assessing by someone more versed in that area, especially given the potential impact of this method if valid.

Effort has been made in these revisions to improve explanations of the proposed approach (a lot of new text has been added) and to add new simulations.

However, the authors have still not compared their method on real data with existing standard approaches for reconstructing data from sensor to physical space. Refusing to do so because existing approaches are deemed inappropriate (i.e. they "are solving a different problem") is illogical.

Similarly, refusing to compare their method with existing standard approaches for spatio-temporally describing brain activity, just because existing approaches are deemed inappropriate, is illogical.

For example, the authors say that "it's not even clear what one would compare [between the new method and standard approaches]". How about:

(1) Qualitatively: compare EEG activation maps. I.e. compare what you would report to a researcher about the brain activity found in a standard experimental task dataset (e.g. their gambling task). People simply want to be able to judge, at least qualitatively on the same data, what the most equivalent output would be from the two approaches. Note, both approaches do not need to be done at the same spatial resolution if there are constraints on this for the comparison to be useful.

and

(2) Quantitatively: compare the correlation scores between EEG activation maps and fMRI activation maps

The abstract claims that there is a "direct comparison with standard state-of-the-art EEG analysis in a well-established attention paradigm", but no actual comparison appears to have been completed in the paper.

Reviewer #2 (Public review):

Summary:

The manuscript claims to present a novel method for direct imaging of electric field networks from EEG data with higher spatiotemporal resolution than even fMRI. Validation of the EEG reconstructions with EEG/FMRI, EEG, and iEEG datasets are presented. Subsequently, reconstructions from a large EEG datasets of subjects performing a gambling task are presented.

Strengths:

If true and convincing, the proposed theoretical framework and reconstruction algorithm can revolutionise the use of EEG source reconstructions.

Weaknesses:

There is very little actual information in the paper about either the forward model or the novel method of reconstruction. Only citations to prior work by the authors are given with absolutely no benchmark comparisons, making the manuscript difficult to read and interpret in isolation to their prior body of work.

Comments on revisions:

This is a major rewrite of the paper. The authors have improved the discourse vastly. There is now a lot of didactics included but they are not always relevant to the paper. The section on Maxwell's equation does a disservice to the literature in prior work in bioelectromagnetism and does not even address the issues raised in classic text books by Plonsey et al. There is no logical "backwardness" in the literature. They are based on the relative values of constants in biological tissues. Several sections of the appendix discuss in terms of weather predictions and could just be written specifically for the problem here. There are reinventions of many standard ideas in terms of physics discourses, like Bayesian theory or PCA etc. I think that the paper remains quite opaque and many of the original criticisms remain, especially as they relate to multimodal datasets. The overall algorithm still remains poorly described. The comparisons to benchmark remain unaddressed and the authors state that they couldn't get Loreta to work and so aborted that. The figures are largely unaltered, although they have added a few more, and do not clearly depict the ideas. Again, no benchmark comparisons are provided to evaluate the results and the performance in comparison to other benchmarks.

Reviewer #2 (Public review):

Summary:

In this present Mendelian randomization-phenome-wide association study, the authors found BMI to be positively associated with many health-related conditions, such as heart disease, heart failure, and hypertensive heart disease. They also found sex differences in some traits, such as cancer, psychological disorders, and ApoB.

Strengths:

The use of the UK-biobank study with detailed phenotype and genotype information.

Comments on revisions:

I believe the authors have presented convincing arguments for the novelty and interpretation of their study. I have no additional comments.

Reviewer #1 (Public review):

Summary:

The study identifies two types of activation: one that is cue-triggered and non-specific to motion directions, and another that is specific to the exposed motion directions but occurs in a reversed manner. The finding that activity in the medial temporal lobe (MTL) preceded that in the visual cortex suggests that the visual cortex may serve as a platform for the manifestation of replay events, which potentially enhance visual sequence learning.

Evaluations:

Identifying the two types of activation after exposure to a sequence of motion directions is very interesting. The experimental design, procedures and analyses are solid. The findings are interesting and novel.

In the original submission, it was not immediately clear to me why the second type of activation was suggested to occur spontaneously. The procedural differences in the analyses that distinguished between the two types of activation need to be a little better clarified. However, this concern has been satisfactorily addressed in the revision.

Reviewer #2 (Public review):

This paper shows and analyzes an interesting phenomenon. It shows that when people are exposed to sequences of moving dots (That is moving dots in one direction, followed by another direction etc.), that showing either the starting movement direction, or ending movement direction causes a coarse-grained brain response that is similar to that elicited by the complete sequence of 4 directions. However, they show by decoding the sensor responses that this brain activity actually does not carry information about the actual sequence and the motion directions, at least not on the time scale of the initial sequence. They also show a reverse reply on a highly-compressed time scale, which is elicited during the period of elevated activity, and activated by the first and last elements of the sequence, but not others. Additionally, these replays seem to occur during periods of cortical ripples, similar to what is found in animal studies.

These results are intriguing. They are based on MEG recordings in humans, and finding such replays in humans is novel. Also, this is based on what seems to be sophisticated statistical analysis. The statistical methodology seems valid, but due to its complexity it is not easy to understand. The methods especially those described in figures 3 and 4 should be explained better.

Comments on second revised version by editorial team:

In response to the reviewer, the authors have substantially expanded and clarified their description of the methodology in this version of the manuscript.

Reviewer #1 (Public review):

Summary:

The submitted article reports the development of an unsupervised learning method that enables quantification of behaviour and poses of C. elegans from 15 minute long videos and presents a spatial map of both. The entire pipeline is a two part process, with the first part based on contrastive learning that represents spatial poses onto an embedded space, while the second part uses a transformer encoder to enable estimation of masked parts in a spatiotemporal sequence.

Strengths:

This analysis approach will prove to be useful for the C. elegans community. The application of the method on various age-related videos on various strains presents a good use-case for the approach. The manuscript is well written and presented.

Specific comments:

(1) One of the main motivations as mentioned in the introduction as well as emphasized in the discussion section is that this approach does not require key-point estimation for skeletonization and is also not dependent on the eigenworm approach for pose estimation. However, the eigenworm data has been estimated using the Tierpsy tracker in videos used in this work and stored as metadata. This is subsequently used for interpretation. It is not clear at this point, how else the spatial embedded map may be interpreted without using this kind of pose estimates obtained from other approaches. Please elaborate and comment.

(2) As per the manuscript, the second part of the pipeline is used to estimate the masked sequences of the spatiotemporal behavioral feature. However, it is not clear what the numbers listed in Fig. 2.3 represent?

(3) It is not clear how motion speed is linked to individual poses as mentioned in Figs. 4 (b) and (c).

Reviewer #2 (Public review):

Summary:

The manuscript by Maurice and Katarzyna describes a self-supervised, annotation-free deep-learning approach capable of quantitatively representing complex poses and behaviors of C. elegans directly from video pixel values. Their method overcomes limitations inherent to traditional methods relying on skeletonization or keypoint tracking, which often fail with highly coiled or self-intersecting worms. By applying self-supervised contrastive learning and a Transformer-based network architecture, the authors successfully capture diverse behavioral patterns and depict the aging trajectory of behavioral repertoire. This provides a useful new tool for behavioral research in C. elegans and other flexible-bodied organisms.

Strengths:

Reliable tracking and segmentation of complex poses remain significant bottlenecks in C. elegans behavioral research, and the authors made valuable attempts to address these challenges. The presented method offers several advantages over existing tools, including freedom from manual labeling, independence from explicit skeletonization or keypoint tracking, and the capability to capture highly coiled or overlapping poses. Thus, the proposed method would be useful to the C. elegans research community.

The research question is clearly defined. Methods and results are engagingly presented, and the manuscript is concise and well-organized.

Weaknesses:

(1) In the abstract, the claim of an 'unbiased' approach is not well-supported. The method is still affected by dataset biases, as mentioned in the aging results (section 4.3).<br /> (2) In section 3.2, the rationale behind rotating worm images to a vertical orientation is unclear.<br /> (3) The methods section is clearly written but uses overly technical language, making it less accessible to the audience of eLife, the majority of whom are biologists. Clearer explanations of key methods and the rationale behind their selection are needed. For example, in section 3.3, the authors should briefly explain in simple language what contrastive learning is, why they chose it, and why this method potentially achieves their goal.<br /> (4) The reason why the gray data points could not be resolved by Tierpsy is not quantitatively described. Are they all due to heavily coiled or overlapping poses?<br /> (5) In section 4.1, generating pose representations grouped by genetic strains would provide insights into strain-specific differences resolved by the proposed method.<br /> (6) Fig. 3a requires clarification. Highly bent poses (red points) intuitively should be close to highly coiled poses (gray points). The authors should explain the observed greenish/blueish points interfacing with the gray points.<br /> (7) In Fig. 3a, some colored points overlap with the gray point cloud. Why can Tierpsy resolve these overlapping points representing highly coiled poses? A more systematic quantitative comparison between Tierpsy and the proposed method is required.<br /> (8) The claim in section 4.2 regarding strain separation in pose embedding spaces is unsupported by Fig. 3a, which lacks strain-based distinctions. As mentioned in point #5, showing pose representations grouped by different strains is required.<br /> (9) In section 4.2, how the authors could verify the statement, "This likely occurs since most strains share common behaviors such as simple forward locomotion"?<br /> (10) An important weakness of the proposed method is its low direct interpretability, as it is not based on handcrafted features. To better interpret the pose/behavior embedding space, it would be helpful to compare it against more basic Tierpsy features in Fig. 3 and 4. This comparison could reveal what understandable features were learned by the neural network, thereby increasing human interpretability.<br /> (11) The main conclusion of section 4.3 is not sufficiently tested. Is Fig. 5a generated only from data of N2 animals? To quantitatively verify the statement, "Young individuals appear to display a wide range of behaviors, while as they age their behavior repertoire reduces," the authors should perform a formal analysis of behavioral variability throughout aging.<br /> (12) In Fig. 5a, better visualization of aging trajectories could include plotting the center of mass along with variance of the point cloud over time.<br /> (13) To better reveal aging trajectories of behavioral changes for different genetic backgrounds, it would be meaningful to generate behavior representations for different strains as they age.<br /> (14) As a methods paper, the ease of use for other researchers should be explicitly addressed, and source code and datasets should be provided.

Reviewer #3 (Public review):

Summary:

In this paper, the authors present an unsupervised learning approach to represent C. elegans poses and temporal sequences of poses in low-dimensional spaces by directly using pixel values from video frames. The method does not rely on the exact identification of the worm's contour/midline, nor on the identification of the head and tail prior to analyzing behavioral parameters. In particular, using contrastive learning, the model represents worm poses in low-dimensional spaces, while a transformer encoder neural network embeds sequences of worm postures over short time scales. The study evaluates this newly developed method using a dataset of different C. elegans genetic strains and aging individuals. The authors compared the representations inferred by the unsupervised learning with features extracted by an established approach, which relies on direct identification of the worm's posture and its head-tail direction.

Strengths:

The newly developed method provides a coarse classification of C. elegans posture types in a low-dimensional space using a relatively simple approach that directly analyzes video frames. The authors demonstrate that representations of postures or movements of different genotypes, based on pixel values, can be distinguishable to some extent.

Weaknesses:

- A significant disadvantage of the presented method is that it does not include the direction of the worm's body (e.g., head/tail identification). This highly limits the detailed and comprehensive identification of the worm's behavioral repertoire (on- and off-food), which requires body directionality in order to infer behaviors (for example, classifying forward vs. reverse movements). In addition, including a mix of opposite postures as input to the new method may create significant classification artifacts in the low-dimensional representation-such that, for example, curvature at opposite parts of the body could cluster together. This concern applies both to the representation of individual postures and to the representation of sequences of postures.<br /> - The authors state that head-tail direction can be inferred during forward movement. This is true when individuals are measured off-food, where they are highly likely to move forward. However, when animals are grown on food, head-tail identification can also be based on quantifying the speed of the two ends of the worm (the head shows side-to-side movements). This does not require identifying morphological features. See, for example, Harel et al. (2024) or Yemini et al. (2013).<br /> - Another confounding parameter that cannot be distinguished using the presented method is the size of individuals. Size can differ between genotypes, as well as with aging. This can potentially lead to clustering of individuals based on their size rather than behavior.<br /> - There is no quantitative comparison between classification based on the presented method and methods that rely on identifying the skeleton.

Reviewer #1 (Public review):

Summary:

Using a combination of EEG and behavioural measurements, the authors investigate the degree to which processing of spatially-overlapping targets (coherent motion) and distractors (affective images) are sampled rhythmically and how this affects behaviour. They found that both target processing (via measurement of amplitude modulations of SSVEP amplitude to target frequency) and distractor processing (via MVPA decoding accuracy of bandpassed EEG relative to distractor SSVEP frequency) displayed a pronounced rhythm at ~1Hz, time-locked to stimulus onset. Furthermore, the relative phase of this target/distractor sampling predicted the accuracy of coherent motion detection across participants.

Strengths:

(1) The authors are addressing a very interesting question with respect to sampling of targets and distractors, using neurophysiological measurements to their advantage in order to parse out target and distractor processing.

(2) The general EEG analysis pipeline is sensible and well-described.

(3) The main result of rhythmic sampling of targets and distractors is striking and very clear even on a participant level.

(4) The authors have gone to quite a lot of effort to ensure the validity of their analyses, especially in the Supplementary Material.

(5) It is incredibly striking how the phases of both target and distractor processing are so aligned across trials for a given participant. I would have thought that any endogenous fluctuation in attention or stimulus processing like that would not be so phase aligned. I know there is literature on phase resetting in this context, the results seem very strong here and it is worth noting. The authors have performed many analyses to rule out signal processing artifacts, e.g., the sideband and beating frequency analyses.

Weaknesses:

(1) In general, the representation of target and distractor processing is a bit of a reach. Target processing is represented by SSVEP amplitude, which is most likely going to be related to the contrast of the dots, as opposed to representing coherent motion energy, which is the actual target. These may well be linked (e.g., greater attention to the coherent motion task might increase SSVEP amplitude), but I would call it a limitation of the interpretation. Decoding accuracy of emotional content makes sense as a measure of distractor processing, and the supplementary analysis comparing target SSVEP amplitude to distractor decoding accuracy is duly noted.

(2) Comparing SSVEP amplitude to emotional category decoding accuracy feels a bit like comparing apples with oranges. They have different units and scales and probably reflect different neural processes. Is the result the authors find not a little surprising in this context? This relationship does predict performance and is thus intriguing, but I think this methodological aspect needs to be discussed further. For example, is the phase relationship with behaviour a result of a complex interaction between different levels of processing (fundamental contrast vs higher order emotional processing)?

Reviewer #2 (Public review):

Summary:

In this study, Xiong et al. investigate whether rhythmic sampling - a process typically observed in the attended processing of visual stimuli - extends to task-irrelevant distractors. By using EEG with frequency tagging and multivariate pattern analysis (MVPA), they aimed to characterize the temporal dynamics of both target and distractor processing and examine whether these processes oscillate in time. The central hypothesis is that target and distractor processing occur rhythmically, and the phase relationship between these rhythms correlates with behavioral performance.

Major Strengths:

(1) The extension of rhythmic attentional sampling to include distractors is a novel and interesting question.

(2) The decoding of emotional distractor content using MVPA from SSVEP signals is an elegant solution to the problem of assessing distractor engagement in the absence of direct behavioral measures.

(3) The finding that relative phase (between 1 Hz target and distractor processes) predicts behavioral performance is compelling.

Major Weaknesses and Limitations:

(1) Incomplete Evidence for Rhythmicity at 1 Hz: The central claim of 1 Hz rhythmic sampling is insufficiently validated. The windowing procedure (0.5s windows with 0.25s step) inherently restricts frequency resolution, potentially biasing toward low-frequency components like 1 Hz. Testing different window durations or providing controls would significantly strengthen this claim.

(2) No-Distractor Control Condition: The study lacks a baseline or control condition without distractors. This makes it difficult to determine whether the distractor-related decoding signals or the 1 Hz effect reflect genuine distractor processing or more general task dynamics.

(3) Decoding Near Chance Levels: The pairwise decoding accuracies for distractor categories hover close to chance (~55%), raising concerns about robustness. While statistically above chance, the small effect sizes need careful interpretation, particularly when linked to behavior.

(4) No Clear Correlation Between SSVEP and Behavior: Neither target nor distractor signal strength (SSVEP amplitude) correlates with behavioral accuracy. The study instead relies heavily on relative phase, which - while interesting - may benefit from additional converging evidence.

(5) Phase-analysis: phase analysis is performed between different types of signals hindering their interpretability (time-resolved SSVEP amplitude and time-resolved decoding accuracy).

Appraisal of Aims and Conclusions:

The authors largely achieved their stated goal of assessing rhythmic sampling of distractors. However, the conclusions drawn - particularly regarding the presence of 1 Hz rhythmicity - rest on analytical choices that should be scrutinized further. While the observed phase-performance relationship is interesting and potentially impactful, the lack of stronger and convergent evidence on the frequency component itself reduces confidence in the broader conclusions.

Impact and Utility to the Field:

If validated, the findings will advance our understanding of attentional dynamics and competition in complex visual environments. Demonstrating that ignored distractors can be rhythmically sampled at similar frequencies to targets has implications for models of attention and cognitive control. However, the methodological limitations currently constrain the paper's impact.

Additional Context and Considerations:

(1) The use of EEG-fMRI is mentioned but not leveraged. If BOLD data were collected, even exploratory fMRI analyses (e.g., distractor modulation in visual cortex) could provide valuable converging evidence.

(2) In turn, removal of fMRI artifacts might introduce biases or alter the data. For instance, the authors might consider investigating potential fMRI artifact harmonics around 1 Hz to address concerns regarding induced spectral components.

Reviewer #1 (Public review):

Summary:

Some years ago, Brookshire proposed a method to identify oscillations in behavioural data that controls for effects of aperiodic trends. Such trends can produce false positive results if not controlled for. Although this method successfully controlled for this issue, it was also relatively insensitive to true effects, and it remained unclear whether it was unable to replicate published evidence for behavioural oscillations because they were false positives or the method could not detect them. In simulated data, Harris & Beale show that their revised version of the method proposed by Brookshire is more sensitive to effects and equally unsusceptible to false positives. When applied to available data, this new version indeed revealed evidence for behavioural oscillations. This paper is therefore an important piece in the puzzle of the ongoing debate on behavioural oscillations.

Strengths:

(1) The paper is well written and compact.

(2) The new method proposed is tested thoroughly, and its application in simulated data shows its properties.

(3) It is very important that the code is made publicly available.

(4) The fact that this new version identifies behavioural oscillations in available datasets can resolve the current debate on the existence of such oscillations.

Weaknesses:

I see the following weaknesses as minor.

(1) I wonder whether the frequency-dependent results (e.g., Figures 7 and 8) need to be seen in light of the sampling rate used in the simulations. For example, a lower sampling rate might be sufficient if only low frequencies are of interest in the data and lead to higher sensitivity as the number of trials (per time point) can be increased. Conversely, a higher sampling rate might lead to a higher sensitivity for the detection of effects at higher frequencies.

(2) The behavioural oscillations from individual participants do not need to have common phases for this analysis to reveal an effect. However, this also means that in a scenario where they do have common phases, this similarity remains "unused" by the analysis (e.g., due to similar phases, the oscillation could be easier to identify on the group level as signals that are not phase locked are averaged out). In such a scenario, it remains unclear whether the analysis proposed is the most sensitive one.

Reviewer #2 (Public review):

Summary

Dozens of published studies have investigated rhythms in behavior. These studies have typically tested for oscillations by shuffling the timestamps of the individual observations and comparing the resulting shuffled spectra with the empirical spectrum. However, that shuffling-in-time method leads to strongly inflated rates of false positives. Brookshire (2022) suggested a method that controls the rate of false positives (the "AR-surrogate method"). In the current study, Harris and Beale propose a modification of the AR-surrogate analysis method with the goal of increasing the sensitivity while maintaining a low rate of false positives.

This study is carefully conducted and it addresses an interesting question. However, the simulations were performed in a way that ignores one important source of temporal structure: non-oscillatory patterns that are consistent across subjects. In order to know whether the updated AR-surrogate method would control the rate of false positives in real behavioral data, we need to know whether it controls the rate of false positives when the data includes aperiodic patterns that are consistent across subjects.

Strengths

This study was constructed carefully and written up very clearly. It's a clever idea to analyze the time series separately for each participant. After examining how the updated AR-surrogate method behaves when the simulated data includes consistency across subjects, this will be a useful contribution to the field.

Weaknesses

When describing their simulations of behavioral data, the authors write: "Each participant's data was produced by creating an independent idealised time-course of 1-second length, sampled at 60 Hz."

Because these simulations generated a totally independent time-course for every subject, they don't capture an important source of aperiodic structure in real behavior: consistent non-oscillatory patterns that occur across subjects. In other words, these simulations do not account for any pattern that remains after averaging across subjects. The literature is rich with patterns that persist across subjects, including all the studies of behavioral oscillations that analyze their data after averaging across subjects (e.g., Landau & Fries, 2012; Fiebelkorn, Saalmann, & Kastner, 2013, etc). As a consequence, I suspect that the reported increase in power comes at the expense of a corresponding increase in false positives, but that the false positives aren't captured here due to the lack of consistency across simulated subjects.

It's therefore possible that the authors' updated AR-surrogate method would mistakenly conclude that behavior oscillates when it only includes aperiodic consistency across subjects. Since that kind of aperiodic structure is ubiquitous, this analysis could lead to very high rates of false positives. Luckily, it's easy to find out whether this is the case - the authors could simulate data using an idealized time-course that is consistent across subjects.

Reviewer #3 (Public review):

Summary:

This work revises the autoregressive surrogate (AR-surrogate) method proposed in 2022 by Brookshire to estimate the oscillatory content of behavioural time series. The main issue raised by Brookshire was the inadequacy of methods used in a series of papers that rely on shuffling the time axis of the behavioural data. Brookshire argued that while this approach tests for temporal structures, it does not differentiate between 1/f activity and true oscillatory signals. The AR-surrogate, on the other hand, removes aperiodic activity and should therefore provide a more accurate representation of oscillatory behaviour.

In this well-written paper, Harris and Beale clearly describe an improvement to Brookshire's method, which has been called into question for its low sensitivity.

Strengths:

The starting point of this work is that oscillatory patterns should be tested at the individual participant level rather than at the group level. This is critical because anyone working with behavioural data will know that averaging across participants generates distorted time series. Averaging also assumes phase consistency across participants, which may not always be valid.

Once freed from this limitation, the results presented here are exciting and convincingly demonstrate a significant improvement over the original implementation.

The authors have devised a series of tests that systematically assess the effects of participant and trial number, and effect size on the accuracy of AR-surrogate results. This is particularly useful, as it may guide researchers in designing appropriate behavioural experiments.

Weaknesses:

The method proposed here is undoubtedly an improvement on the original. However, its biggest limitation is the restriction on the frequencies that can be investigated. This is acknowledged by the authors, who rightly point out that there is still room for improvement. Another issue is that modulation depths below 10-15% may be difficult to detect.

Reviewer #1 (Public review):

The authors note that very premature infants experience the visual world early and, as a consequence, sustain lasting deficits including compromised motion processing. Here they investigate the effects of early eye opening in ferret, choosing a time point after birth when both retinal waves and light traveling through closed lids drive sensory responses. The laboratory has long experience in quantitative studies of visual response properties across development and this study reflects their expertise.

The investigators find little or no difference in mean orientation and direction selectivity, or in spatial frequency tuning, as a result of early eye opening but marked differences in temporal frequency tuning. These changes are especially interesting as they relate to deficits seen in prematurely delivered children. Temporal frequency bandwidth for responses evoked from early-opened contralateral eyes were broader than for controls; this is the case for animals in which either one or both eyes were opened prematurely. Further, when only one eye was opened early, responses to low temporal frequencies were relatively stronger.

The investigators also found changes in firing rate and signs of response to visual stimuli. Premature eye-opening increased spontaneous rates in all test configurations. When only one eye was opened early, firing rates recorded from the ipsilateral cortex were strongly suppressed, with more modest effects in other test cases.

As the authors' discussion notes, these observations are just a starting point for studies underlying mechanism. The experiments are so difficult to perform and so carefully described that the results will be foundational for future studies of how premature birth influences cortical development.

Reviewer #2 (Public review):

In this paper, Griswold and Van Hooser investigate what happens if animals are exposed to patterned visual experience too early, before its natural onset. To this end, they make use of the benefits of the ferret as a well-established animal model for visual development. Ferrets naturally open their eyes around postnatal day 30; here, Griswold and Van Hooser opened either one or both eyes prematurely. Subsequent recordings in the mature primary visual cortex show that while some tuning properties like orientation and direction selectivity developed normally, the premature visual exposure triggered changes in temporal frequency tuning and overall firing rates. These changes were widespread, in that they occurred even for neurons responding to the eye that was not opened prematurely. These results demonstrate that the nature of the visual input well before eye opening can have profound consequences on the developing visual system.

The conclusions of this paper are well supported by the data, but some aspects of the data could be clarified, and the discussion could be extended.

(1) The assessment of the tuning properties is based on fits to the data. Presumably, neurons for which the fits were poor were excluded? It would be useful to know what the criteria were, how many neurons were excluded, and whether there was a significant difference between the groups in the numbers of neurons excluded (which could further point to differences between the groups).

(2) For the temporal frequency data, low- and high-frequency cut-offs are defined, but then only used for the computation of the bandwidth. Given that the responses to low temporal frequencies change profoundly with premature eye opening, it would be useful to directly compare the low- and high-frequency cut-offs between groups, in addition to the index that is currently used.

(3) In addition to the tuning functions and firing rates that have been analyzed so far, are there any differences in the temporal profiles of neural responses between the groups (sustained versus transient responses, rates of adaptation, latency)? If the temporal dynamics of the responses are altered significantly, that could be part of an explanation for the altered temporal tuning.

(4) It would be beneficial for the general interpretation of the results to extend the discussion. First, it would be useful to provide a more detailed discussion of what type of visual information might make it through the closed eyelids (the natural state), in contrast to the structured information available through open eyes. Second, it would be useful to highlight more clearly that these data were collected in peripheral V1 by discussing what might be expected in binocular, more central V1 regions. Third, it would be interesting to discuss the observed changes in firing rates in the context of the development of inhibitory neurons in V1 (which still undergo significant changes through the time period of premature visual experience chosen here).

Reviewer #1 (Public review):

Summary:

This computational modeling study builds on multiple previous lines of experimental and theoretical research to investigate how a single neuron can solve a nonlinear pattern classification task. The authors construct a detailed biophysical and morphological model of a single striatal medium spiny neuron, and endow excitatory and inhibitory synapses with dynamic synaptic plasticity mechanisms that are sensitive to (1) the presence or absence of a dopamine reward signal, and (2) spatiotemporal coincidence of synaptic activity in single dendritic branches. The latter coincidence is detected by voltage-dependent NMDA-type glutamate receptors, which can generate a type of dendritic spike referred to as a "plateau potential." In the absence of inhibitory plasticity, the proposed mechanisms result in good performance on a nonlinear classification task when specific input features are segregated and clustered onto individual branches, but reduced performance when input features are randomly distributed across branches. Interestingly, adding inhibitory plasticity improves classification performance even when input features are randomly distributed.

Strengths:

The integrative aspect of this study is its major strength. It is challenging to relate low-level details such as electrical spine compartmentalization, extrasynaptic neurotransmitter concentrations, dendritic nonlinearities, spatial clustering of correlated inputs, and plasticity of excitatory and inhibitory synapses to high-level computations such as nonlinear feature classification. Due to high simulation costs, it is rare to see highly biophysical and morphological models used for learning studies that require repeated stimulus presentations over the course of a training procedure. The study aspires to prove the principle that experimentally-supported biological mechanisms can explain complex learning.

Weaknesses:

The high level of complexity of each component of the model makes it difficult to gain an intuition for which aspects of the model are essential for its performance, or responsible for its poor performance under certain conditions. Stripping down some of the biophysical detail and comparing it to a simpler model may help better understand each component in isolation.

Reviewer #2 (Public review):

Summary:

The study explores how single striatal projection neurons (SPNs) utilize dendritic nonlinearities to solve complex integration tasks. It introduces a calcium-based synaptic learning rule that incorporates local calcium dynamics and dopaminergic signals, along with metaplasticity to ensure stability for synaptic weights. Results show SPNs can solve the nonlinear feature binding problem and enhance computational efficiency through inhibitory plasticity in dendrites, emphasizing the significant computational potential of individual neurons. In summary, the study provides a more biologically plausible solution to single-neuron learning and gives further mechanical insights into complex computations at the single-neuron level.

Strengths:

The paper introduces a novel learning rule for training a single multicompartmental neuron model to perform nonlinear feature binding tasks (NFBP), highlighting two main strengths: the learning rule is local, calcium-based, and requires only sparse reward signals, making it highly biologically plausible, and it applies to detailed neuron models that effectively preserve dendritic nonlinearities, contrasting with many previous studies that use simplified models.

Reviewer #1 (Public review):

Summary:

In this study, Jeong and Choi examine neural correlates of behavior during a naturalistic foraging task in which rats must dynamically balance resource acquisition (foraging) with the risk of threat. Rats first learn to forage for sucrose reward from a spout, and when a threat is introduced (an attack-like movement from a "LobsterBot"), they adjust their behavior to continue foraging while balancing exposure to the threat, adopting anticipatory withdraw behaviors to avoid encounter with the LobsterBot. Using electrode recordings targeting the medial prefrontal cortex (PFC), they identify heterogenous encoding of task variables across prelimbic and infralimbic cortex neurons, including correlates of distance to the reward/threat zone and correlates of both anticipatory and reactionary avoidance behavior. Based on analysis of population responses, they show that prefrontal cortex switches between different regimes of population activity to process spatial information or behavioral responses to threat in a context-dependent manner. Characterization of the heterogenous coding scheme by which frontal cortex represents information in different goal states is an important contribution to our understanding of brain mechanisms underlying flexible behavior in ecological settings.

Strengths:

As many behavioral neuroscience studies employ highly controlled task designs, relatively less is generally known about how the brain organizes navigation and behavioral selection in naturalistic settings, where environment states and goals are more fluid. Here, the authors take advantage of a natural challenge faced by many animals - how to forage for resources in an unpredictable environment - to investigate neural correlates of behavior when goal states are dynamic. Related to his, they also investigate prefrontal cortex (PFC) activity is structured to support different functional "modes" (here, between a navigational mode and a threat-sensitive foraging mode) for flexible behavior. Overall, an important strength and real value of this study is the design of the behavioral experiment, which is trial-structured, permitting strong statistical methods for neural data analysis, yet still rich enough to encourage natural behavior structured by the animal's volitional goals. The experiment is also phased to measure behavioral changes as animals first encounter a threat, and then learn to adapt their foraging strategy to its presence. Characterization of this adaptation process is itself quite interesting and sets a foundation for further study of threat learning and risk management in the foraging context. Finally, the characterization of single-neuron and population dynamics in PFC in this naturalistic setting with fluid goal states is an important contribution to the field. Previous studies have identified neural correlates of spatial and behavioral variables in frontal cortex, but how these representations are structured, or how they are dynamically adjusted when animals shift their goals, has been less clear. The authors synthesize their main conclusions into a conceptual model for how PFC activity can support mode switching, which can be tested in future studies with other task designed and functional manipulations.

Weaknesses:

While the task design in this study is intentionally stimulus-rich and places minimal constraint on the animal to preserve naturalistic behavior, this also introduces confounds that limit interpretability of the neural analysis. For example, some variables which are the target of neural correlation analysis, such as spatial/proximity coding and coding of threat and threat-related behaviors, are naturally entwined. To their credit, the authors have included careful analyses and control conditions to disambiguate these variables and significantly improve clarity.

The authors also claim that the heterogenous coding of spatial and behavioral variables in PFC is structured in a particular way that depends on the animal's goals or context. As the authors themselves discuss, the different "zones" contain distinct behaviors and stimuli, and since some neurons are modulated by these events (e.g., licking sucrose water, withdrawing from the LobsterBot, etc.), differences in population activity may to some extent reflect behavior/event coding. The authors have included a control analysis, removing timepoints corresponding to salient events, to substantiate the claim that PFC neurons switch between different coding "modes." While this significantly strengthens evidence for their conclusion, this analysis still depends on relatively coarse labeling of only very salient events. Future experiment designs, which intentionally separate task contexts (e.g. navigation vs. foraging), could serve to further clarify the structure of coding across contexts and/or goal states.

Finally, while the study includes many careful, in-depth neural and behavioral analyses to support the notion that modal coding of task variables in PFC may play a role in organizing flexible, dynamic behavior, the study still lacks functional manipulations to establish any form of causality. This limitation is acknowledged in the text, and the report is careful not to over interpret suggestions of causal contribution, instead setting a foundation for future investigations.

Reviewer #2 (Public review):

Summary:

Jeong & Choi (2023) use a semi-naturalistic paradigm to tackle the question of how the activity of neurons in the mPFC might continuously encode different functions. They offer two possibilities: either there are separate dedicated populations encoding each function, or cells alter their activity dependent on the current goal of the animal. In a threat-avoidance task rats procurred sucrose in an area of a chamber where, after remaining there for some amount of time, a 'Lobsterbot' robot attacked. In order to initiate the next trial rats had to move through the arena to another area before returning to the robot encounter zone. Therefore the task has two key components: threat avoidance and navigating through space. Recordings in the IL and PL of the mPFC revealed encoding that depended on what stage of the task the animal was currently engaged in. When animals were navigating, neuronal ensembles in these regions encoded distance from the threat. However, whilst animals were directly engaged with the threat and simultaneously consuming reward, it was possible to decode from a subset of the population whether animals would evade the threat. Therefore the authors claim that neurons in the mPFC switched between two functional modes: representing allocentric spatial information, and representing egocentric information pertaining to the reward and threat. Finally, the authors propose a conceptual model based on these data whereby this switching of population encoding is driven by either bottom-up sensory information or top-down arbitration.

Strengths:

Whilst these multiple functions of activity in the mPFC have generally been observed in tasks dedicated to the study of a singular function, less work has been done in contexts where animals continuously switch between different modes of behaviour in a more natural way. Being able to assess whether previous findings of mPFC function apply in natural contexts is very valuable to the field, even outside of those interested in the mPFC directly. This also speaks to the novelty of the work; although mixed selectivity encoding of threat assessment and action selection has been demonstrated in some contexts (e.g. Grunfeld & Likhtik, 2018) understanding the way in which encoding changes on-the-fly in a self-paced task is valuable both for verifying whether current understanding holds true and for extending our models of functional coding in the mPFC.

The authors are also generally thoughtful in their analyses and use a variety of approaches to probe the information encoded in the recorded activity. In particular, they use relatively close analysis of behaviour as well as manipulating the task itself by removing the threat to verify their own results. The use of such a rich task also allows them to draw comparisons, e.g. in different zones of the arena or different types of responses to threat, that a more reduced task would not otherwise allow. Additional in-depth analyses in the updated version of the manuscript, particularly the feature importance analysis, as well as complimentary null findings (a lack of cohesive place cell encoding, and no difference in location coding dependent on direction of trajectory) further support the authors' conclusion that populations of cells in the mPFC are switching their functional coding based on task context rather than behaviour per se. Finally, the authors' updated model schematic proposes an intriguing and testable implementation of how this encoding switch may be manifested by looking at differentiable inputs to these populations.

Weaknesses:

The main existing weakness of this study is that its findings are correlational (as the authors highlight in the discussion). Future work might aim to verify and expand the authors' findings - for example, whether the elevated response of Type 2 neurons directly contributes to the decision-making process or just represents fear/anxiety motivation/threat level - through direct physiological manipulation. However, I appreciate the challenges of interpreting data even in the presence of such manipulations and some of the additional analyses of behaviour, for example the stability of animals' inter-lick intervals in the E-zone, go some way towards ruling out alternative behavioural explanations. Yet the most ideal version of this analysis is to use a pose estimation method such as DeepLabCut to more fully measure behavioural changes. This, in combination with direct physiological manipulation, would allow the authors to fully validate that the switching of encoding by this population of neurons in the mPFC has the functional attributes as claimed here.

Reviewer #3 (Public review):

Summary:

This study investigates how various behavioral features are represented in the medial prefrontal cortex (mPFC) of rats engaged in a naturalistic foraging task. The authors recorded electrophysiological responses of individual neurons as animals transitioned between navigation, reward consumption, avoidance, and escape behaviors. Employing a range of computational and statistical methods, including artificial neural networks, dimensionality reduction, hierarchical clustering, and Bayesian classifiers, the authors sought to predict from neural activity distinct task variables (such as distance from the reward zone and the success or failure of avoidance behavior). The findings suggest that mPFC neurons alternate between at least two distinct functional modes, namely spatial encoding and threat evaluation, contingent on the specific location.

Strengths:

This study attempt to address an important question: understanding the role of mPFC across multiple dynamic behaviors. The authors highlight the diverse roles attributed to mPFC in previous literature and seek to explain this apparent heterogeneity. They designed an ethologically relevant foraging task that facilitated the examination of complex dynamic behavior, collecting comprehensive behavioral and neural data. The analyses conducted are both sound and rigorous.

Weaknesses:

Because the study still lacks experimental manipulation, the findings remain correlational. The authors have appropriately tempered their claims regarding the functional role of the mPFC in the task. The nature of the switch between functional modes encoding distinct task variables (i.e., distance to reward, and threat-avoidance behavior type) is not established. Moreover, the evidence presented to dissociate movement from these task variables is not fully convincing, particularly without single-session video analysis of movement. Specifically, while the new analyses in Figure 7 are informative, they may not fully account for all potential confounding variables arising from changes in context or behavior.

Joint Public Review:

Editors’ note: This is the third version of this article, and it addresses the points made during the peer review of the second version by performing additional analyses and clarifying some of the limitations of the study.

Comments made during the peer review of the first version, along with author's responses to these comments, are available with previous versions of the article.

The following summary of the article is taken from comments made by Reviewer #1 about version 2 of the article:

In this manuscript, the authors use a large dataset of neuroscience publications to elucidate the nature of self-citation within the neuroscience literature. The authors initially present descriptive measures of self-citation across time and author characteristics; they then produce an inclusive model to tease apart the potential role of various article and author features in shaping self-citation behavior. This is a valuable area of study, and the authors approach it with a rich dataset and solid methodology.

Reviewer #1 (Public review):

Summary:

This study seeks to investigate the role of the transcription factor Bcl11b/Ctip2 in regulating subcerebral projection neuron (SCPN) axon development through both cell-autonomous and non-cell-autonomous mechanisms. The authors demonstrate that Bcl11b is required within SCPNs for axonal outgrowth and proper entry into the internal capsule, while its expression in medium spiny neurons (MSNs) influences SCPN axon fasciculation and pathfinding in a non-cell-autonomous manner. Notably, through transcriptomic analysis, immunocytochemistry, and in vivo growth cone purification, the study identifies Cdh13 as a downstream mediator of Bcl11b function, localizing along axons and at growth cone surfaces to regulate SCPN axonal outgrowth.

Strengths:

To me the most interesting aspect of this study is how common transcriptional programs across neuronal cell types cooperate to facilitate axon pathfinding, this is a very interesting concept.

Overall, it could be of interest to the brain development field.

Weaknesses:

My main concern is that, as presented in the figures, many phenotypes are too subtle to be convincing and would require quantitative analyses to corroborate the claims of the study.

I also think that the growth cones transcription data needs additional validation to be incorporated into the manuscript. In fact, I am not even sure that it really brings anything to the story.

I also think that the CRISPR in utero electroporation experiments lack appropriate controls.

Reviewer #2 (Public review):

Summary:

Itoh et al. investigate the role of the zinc finger transcription factor Bcl11b/Citp2 on sub cerebral projection neurons (SCPN) development. They dissect Bcl11b cell-autonomous and non-cell-autonomous functions on subcerebral projection neurons. In addition, they identify Cdh13 as a downstream target of Bcl11b in the process of SCPN axon outgrowth.

Strengths:

Itoh et al. take advantage of a mouse CRE/Lox genetic system as a powerful tool to distinguish Bcl11b cell-autonomous function on cortical layer V subcerebral projection neurons and its non-cell-autonomous function mediated by the striatal medium spiny neurons (MSN).

Besides the description of the cellular and anatomical defects of the corticofugal projection neurons' outgrowth and fasciculation, they perform a transcriptomic analysis of SCPN somata to identify Bcl11b target genes. As a result, they find that Cdh13, a membrane-anchored cadherin , is downstream of Bcl11b and mediates its cell-autonomous role on axon outgrowth. To validate the role of Cdh13 as a mediator of Bcl11b on SCPN development, they set up a new technique to identify and quantify superficial antigens on growth cone membranes.

Weaknesses:

While the authors shed light on the role of Bcl11b on SCPN development, they lack to contextualize their findings on the previously described interplay between Bcl11a and b.<br /> In addition, this work is another example of the common practice of picking from a list of differentially expressed genes the most likely ones. This approach, while useful, does not allow the identification of new and unknown players.

Reviewer #1 (Public review):

Summary:

Nysten et al. use in vivo 2-photon calcium imaging in behaving mice learning a visual associative memory task to understand how neural dynamics in the postrhinal cortex and medial entorhinal cortex evolve over task learning and through reversal learning. Using a combination of analyses to measure trial-averaged neural responses, regression models, and population decoding methods, the authors argue that both POR and MEC dynamics evolve over learning, with relatively more neurons in MEC becoming responsive. The impact of this study comes from comparing neural dynamics across multiple medial temporal lobe circuits to show how different aspects of task structure are differentially encoded. Below, I have listed several major concerns that need to be addressed to ensure the findings are robust.

Strengths:

(1) The study employs a well-controlled behavioral paradigm alongside powerful cellular-resolution two-photon imaging, enabling high-throughput recordings of hundreds of neurons simultaneously in deep brain structures.

(2) The simplicity of the task allows for a detailed examination of learning dynamics across multiple stages, including early and late learning in the main task, as well as during reversal learning.

(3) The use of sophisticated analysis methods to compare and contrast learning dynamics in large neuronal populations strengthens the study, though additional steps are needed to ensure their robustness (detailed below).

(4) Two-photon imaging enables the investigation of functional topography, further supporting previous findings of functional clustering in MEC across different task and behavioral domains.

Weaknesses:

(1) GLM Robustness & Behavioral Attribution: The current GLM design may misattribute neural activity by lacking appropriate time lags for velocity and not accounting for distinct neural states (e.g., rest vs. run). Given MEC's known speed-invariant coding, the observed decrease in speed-modulated neurons may be an artifact rather than a true learning effect. Additionally, gradual behavioral stabilization over training could influence neural dynamics in ways not fully accounted for.

(2) Licking vs. Movement Encoding: The increase in lick-modulated neurons raises questions about whether these neurons encode reward anticipation or motor execution. Without a detailed analysis of error trials and the timing of licking vs. movement adjustments, it remains unclear whether MEC activity reflects predictive coding of reward or simply motor feedback.

(3) Clustering Interpretation Issues: The functional clustering approach does not control for correlations between behavioral features, making it difficult to determine whether speed modulation plays a role in cluster assignments. The anatomical analysis in Figure 6 relies heavily on clusters that may be predominantly defined by a single regressor, requiring further clarification.

(4) Data Presentation & Statistical Support: Some key claims, particularly the increase in task-modulated neurons with learning (Figure 3), lack statistical quantification.

Reviewer #2 (Public review):

Summary:

The authors examine medial entorhinal cortex (MEC) and postrhinal cortex (POR) responses using Ca imaging during a non-spatial, Go/No-Go visual association task. The authors specifically consider whether MEC encodes stimulus information, as previously seen and hypothesized in POR, as well as other task elements such as reward, and whether and how these responses evolve with learning in both regions. The authors find that, in general, POR encodes task-related information more strongly compared to MEC. In particular, POR encodes the stimulus even before the animal reaches expert performance, whereas MEC shows considerably weaker stimulus encoding that emerges with learning. Both regions also display licking-related coding, although notably this activity reflects choice or licking-preparation, which emerges with learning. Further, despite its overall reduced coding, MEC exhibits greater anatomical clustering of cells with similar functional properties compared to POR.

Strengths:

These data are generally well-presented, both in the description of the experimental paradigm - which is simple yet highly informative - and in the individual results for each section. A major strength is the dataset, which includes many cells, including a subset that are tracked across learning. I found the core findings - (1) that POR has robust stimulus encoding while MEC develops weaker stimulus information with learning, and (2) that both POR and MEC exhibit an increase in lick-modulated cells, although POR has more, and stronger, lick-modulated cells - to be generally well-supported by the data presented. The general question of whether and how MEC encodes non-spatial task-relevant features and how these responses (if they exist) emerge with learning is of general interest. In addition, how MEC activity contrasts with activity in an upstream region, thereby indicating what information MEC gets and what it does with it, is also of broad interest.

Weaknesses:

I perceived two primary weaknesses.

The first was that it was not entirely clear to me what was expected of MEC and POR responses, and whether the observations the authors made were surprising or entirely in line with what would've been predicted based on prior work. In some ways, the results seem expected - POR had visual signals, MEC had few visual signals but some reward signals.

The second is that it took me a long time to extract what I perceived to be the core results of the paper, and in some places, it was a little hard for me to understand all the analyses and results together as one cohesive step forward in our understanding of MEC and POR coding properties.

I think this was most evident in the results presented in Figure 4. Up until Figure 4, it seemed to me that the core results were:<br /> (1) visual (stimulus information) is present in POR responses from very early learning, whereas weak stimulus information develops in MEC with learning, and in both cases, there is a preference for the plus stimulus.<br /> (2), both POR and MEC show an increase in lick-modulated cells with learning, although more cells encode licking at all stages in POR.

This is nicely summarized in my view by Figure 3e. However, I became confused when Figure 4 entered the picture. Here, it seems that by far the most predominant coefficient in the model is the lick response, with stimulus features playing a smaller role - specifically, at the end of learning, 60% of POR cells were characterized as predominantly lick/non lick, compared to 25% defined by their coding to the stimulus. I can appreciate that there might be nuances to these and previous analyses such that all the results sit cohesively together, but I think that needs to be clarified.

A second example - Figure 2b - shows that many (75%) of MEC neurons seem to be selectively active for the plus stimulus, but when doing the GLM analysis with the plus stimulus (and reward/licking) as features, many fewer neurons (35%) are determined to be encoding task information. It was not clear to me what was contributing to the discrepancy between these two results - is it that MEC activity often increases with learning, but doesn't increase by that much?

I think in general this can be helped by specifically pointing out how the results of these different analyses relate to each other, including specifically mentioning where the results might seem unaligned (at least on the surface).

Reviewer #1 (Public review):

Summary:

The manuscript reports that expression of the E. coli operon topAI/yjhQ/yjhP is controlled by the translation status of a small open reading frame, that authors have discovered and named toiL, located in the leader region upstream of the operon. Authors propose the following model for topAI activation: Under normal conditions, toiL is translated but topAI is not expressed because of Rho-dependent transcription termination within the topAI ORF and because its ribosome binding site and start codon are trapped in an mRNA hairpin. Ribosome stalling at various codons of the toiL ORF, prompted in this work by some ribosome-targeting antibiotics, triggers an mRNA conformational switch which allows translation of topAI and, in addition, activation of the operon's transcription because presence of translating ribosomes at the topAI ORF blocks Rho from terminating transcription. The model is appealing and several of the experimental data mainly support it. However, it remains unanswered what is the true trigger of the translation arrest at toiL and what is the physiological role of the induced expression of the topAI/yjhQ/yjhP operon.

Reviewer #2 (Public review):

Summary:

Baniulyte and Wade describe how translation of an 8-codon uORF denoted toiL upstream of the topAI-yjhQP operon is responsive to different ribosome-targeting antibiotics, consequently controlling translation of the TopAI toxin as well as Rho-dependent termination with the gene.

Strengths:

The authors used multiple different approaches such as a genetic screen to identify factors such as 23S rRNA mutations that affect topA1 expression and ribosome profiling to examine the consequences of various antibiotics on toiL-mediated regulation.

Weaknesses: Future experiments will be needed to better understand the physiological role of the toiL-mediated regulation and elucidate the mechanism of specific antibiotic sensing.

The results are clearly described, and the revisions have helped to improve the presentation of the data.

Reviewer #3 (Public review):

In this revised manuscript, the authors provide convincing data to support an elegant model in which ribosome stalling by ToiL promotes downstream topAI translation and prevents premature Rho-dependent transcription termination. However, the physiological consequences of activating topAI-yjhQP expression upon exposure to various ribosome-targeting antibiotics remain unresolved. The authors have satisfactorily addressed all major concerns raised by the reviewers, particularly regarding the SHAPE-seq data. Overall, this study underscores the diversity of regulatory ribosome-stalling peptides in nature, highlighting ToiL's uniqueness in sensing multiple antibiotics and offering significant insights into bacterial gene regulation coordinated by transcription and translation.

Reviewer #1 (Public review):

The manuscript consists of two separate but interlinked investigations: genomic epidemiology and virulence assessment of Salmonella Dublin. ST10 dominates the epidemiological landscape of S. Dublin, while ST74 was uncommonly isolated. Detailed genomic epidemiology of ST10 unfolded the evolutionary history of this common genotype, highlighting clonal expansions linked to each distinct geography. Notably, North American ST10 was associated with more antimicrobial resistance compared to others. The authors also performed long read sequencing on a subset of isolates (ST10 and ST74), and uncovered a novel recombinant virulence plasmid in ST10 (IncX1/IncFII/IncN). Separately, the authors performed cell invasion and cytotoxicity assays on the two S. Dublin genotypes, showing differential responses between the two STs. ST74 replicates better intracellularly in macrophage compared to ST10, but both STs induced comparable cytotoxicity levels. Comparative genomic analyses between the two genotypes showed certain genetic content unique to each genotype, but no further analyses were conducted to investigate which genetic factors likely associated with the observed differences. The study provides a comprehensive and novel understanding on the evolution and adaptation of two S. Dublin genotypes, which can inform public health measures. The methodology included in both approaches were sound and written in sufficient detail, and data analysis were performed with rigour. Source data were fully presented and accessible to readers.

Comments on revised version:

The authors have addressed all the points raised by the reviewer. The manuscript is now much enhanced in clarity and accuracy. The rewritten Discussion is more relevant and brings in comparison with other invasive Salmonella serotypes.

Reviewer #2 (Public review):

This is a comprehensive analysis of Salmonella Dublin genomes that offers insights into the global spread of this pathogen and region-specific traits that are important to understand its evolution. The phenotyping of isolates of ST10 and ST74 also offer insights into the variability that can be seen in S. Dublin, which is also seen in other Salmonella serovars, and reminds the field that it is important to look beyond lab-adapted strains to truly understand these pathogens. This is a valuable contribution to the field. The only limitation, which the authors also acknowledge, is the bias towards S. Dublin genomes from high-income settings. However, there is no selection bias; this is simply a consequence of publicly available sequences.

Reviewer #1 (Public review):

Summary:

This work uses a novel, ethologically relevant behavioral task to explore decision-making paradigms in C. elegans foraging behavior. By rigorously quantifying multiple features of animal behavior as they navigate in a patch food environment, the authors provide strong evidence that worms exhibit one of three qualitatively distinct behavioral responses upon encountering a patch: (1) "search", in which the encountered patch is below the detection threshold; (2) "sample", in which animals detect a patch encounter and reduce their motor speed, but do not stay to exploit the resource and are therefore considered to have "rejected" it; and (3) "exploit", in which animals "accept" the patch and exploit the resource for tens of minutes. Interestingly, the probability of these outcomes varies with the density of the patch as well as the prior experience of the animal. Together, these experiments provide an interesting new framework for understanding the ability of the C. elegans nervous system to use sensory information and internal state to implement behavioral state decisions.

Strengths:

-The work uses a novel, neuroethologically-inspired approach to studying foraging behavior<br /> -The studies are carried out with an exceptional level of quantitative rigor and attention to detail<br /> -Powerful quantitative modeling approaches including GLMs are used to study the behavioral states that worms enter upon encountering food, and the parameters that govern the decision about which state to enter<br /> -The work provides strong evidence that C. elegans can make 'accept-reject' decisions upon encountering a food resource<br /> -Accept-reject decisions depend on the quality of the food resource encountered as well as on internally represented features that provide measurements of multiple dimensions of internal state, including feeding status and time

Reviewer #2 (Public review):

This study provides an experimental and computational framework to examine and understand how C. elegans make decisions while foraging environments with patches of food. The authors show that C. elegans reject or accept food patches depending on a number of internal and external factors.

The key novelty of this paper is the explicit demonstration of behavior analysis and quantitative modeling to elucidate decision-making processes. In particular, the description of the exploring vs. exploiting phases, and sensing vs. non-sensing categories of foraging behavior based on the clustering of behavioral states defined in a multi-dimensional behavior-metrics space, and the implementation of a generalized linear model (GLM) whose parameters can provide quantitative biological interpretations.

The work builds on the literature of C. elegans foraging by adding the reject/accept framework.

Reviewer #3 (Public review):

Summary:

In this study by Haley et al, the authors investigated explore-exploit foraging using C. elegans as a model system. Through an elegant set of patchy environment assays, the authors built a GLM based on past experience that predicts whether an animal will decide to stay on a patch to feed and exploit that resource, instead of choosing to leave and explore other patches.

Strengths:

I really enjoyed reading this paper. The experiments are simple and elegant, and address fundamental questions of foraging theory in a well-defined system. The experimental design is thoroughly vetted, and the authors provide a considerable volume of data to prove their points. My only criticisms have to do with the data interpretation, which I think are easily addressable.

Weaknesses:

History-dependence of the GLM

The logistic GLM seems like a logical way to model a binary choice, and I think the parameters you chose are certainly important. However, the framing of them seem odd to me. I do not doubt the animals are assessing the current state of the patch with an assessment of past experience; that makes perfect logical sense. However, it seems odd to reduce past experience to the categories of recently exploited patch, recently encountered patch, and time since last exploitation. This implies the animals have some way of discriminating these past patch experiences and committing them to memory. Also, it seems logical that the time on these patches, not just their density, should also matter, just as the time without food matters. Time is inherent to memory. This model also imposes a prior categorization in trying to distinguish between sensed vs. not-sensed patches, which I criticized earlier. Only "sensed" patches are used in the model, but it is questionable whether worms genuinely do not "sense" these patches.

It seems more likely that the worm simply has some memory of chemosensation and relative satiety, both of which increase on patches and decrease while off of patches. The magnitudes are likely a function of patch density. That being said, I leave it up to the reader to decide how best to interpret the data.

osm-6

The argument is that osm-6 animals can't sense food very well, so when they sense it, they enter the exploitation state by default. That is what they appear to do, but why? Clearly they are sensing the food in some other way, correct? Are ciliated neurons the only way worms can sense food? Don't they also actively pump on food, and can therefore sense the food entering their pharynx? I think you could provide further insight by commenting on this. Perhaps your decision model is dependent on comparing environmental sensing with pharyngeal sensing? Food intake certainly influences their decision, no? Perhaps food intake triggers exploitation behavior, which can be over-run by chemo/mechanosensory information?

Impact:

I think this work will have a solid impact on the field, as it provides tangible variables to test how animals assess their environment and decide to exploit resources. I think the strength of this research could be strengthened by a reassessment of their model that would both simplify it and provide testable timescales of satiety/starvation memory.

Reviewer #1 (Public review):

Summary:

The use of a multi-omics approach to elucidate the regulatory mechanism underlying parturition and myometrial quiescence adds novelty to the study. The identification of myometrial cis-acting elements and their association with gene expression, particularly the regulation of the PLCL2 gene by PGR opens the door to further investigate the impact of PGR and other regulators.

Strengths:

(1) Multi-Omic Approach: The paper employs a comprehensive multi-omic approach, combining ChIP-Seq, RNA-Seq, and CRISPRa-based Perturb-Seq assays, which allow for a thorough investigation of the regulatory mechanisms underlying myometrial gene expression.<br /> (2) Clinical Relevance: Investigating human myometrial specimens provides direct clinical relevance, as understanding the molecular mechanisms governing parturition and myometrial quiescence can have significant implications for the management of pregnancy-related disorders.<br /> (3) Functional work: For functional screening, They have used CRISPRa-based screening of PLCL2 gene regulation using immortalized human cell-line hTERT-HM and T-hESC to add more dimension to the work which strengthens their finding of PGR-dependent regulation of the PLCL2 gene in the human myometrial cells.

Weaknesses:

(1) Variability in epigenomic mapping: The significant variations in the number and location of H3K27ac-positive intervals across different samples and studies suggest potential challenges in accurately mapping the myometrial epigenome. This variability may introduce uncertainty and complicate the interpretation of results.<br /> (2) Sample specificity: The study focuses on term pregnant nonlabor myometrial specimens, limiting the generalizability of the findings to other stages of pregnancy or labor.<br /> (3) Limited Understanding of Regulatory Mechanisms: While the study identifies potential regulatory programs within super-enhancers, the exact mechanisms by which these enhancers regulate gene expression and cellular functions in the myometrium remain unclear. Further mechanistic studies are needed to elucidate these processes.<br /> (4) Discordant analysis: Why regular enhancers are being understood in terms of motif enrichment of transcription factors and super-enhancers in terms of pathways enriched for active genes? This needs a clear reason.

Reviewer #2 (Public review):

Summary:

In "Assessment of the Epigenomic Landscape in Human Myometrium at Term Pregnancy" the authors generate a number of genome-wide data sets to investigate epigenomic and transcriptomic regulation of the myometrium at term pregnancy. These data provide a useful resource for further evaluation of gene regulatory mechanisms in the myometrium and include the first Hi-C data published for this tissue. There is a comparison to previously published histone modification data and integration with RNA-seq to highlight potential enhancer-gene regulatory relationships. The authors further investigate putative enhancers upstream of the PLCL2 gene and identify a candidate region that may be regulated by the PGR (progesterone receptor) signaling.

Strengths:

The strengths of this study are in the multi-omics nature of the design as several genome-wide data sets are generated from the same patient samples. Extending this type of approach in the future to a larger number of samples will allow for additional investigation into gene regulation as correlation between epigenomic features and gene expression across a larger number of samples can reveal regulatory relationships.

Weaknesses:

One of the most interesting aspects of this study is the generation of the first Hi-C data for the human pregnant myometrium, however, there is minimal description in the results section of the Hi-C data analysis and the only data shown are the number of loops identified and one such loop that includes the PLCL2 promoter shown in figure 3A. The manuscript would benefit from a more extensive analysis of the Hi-C data, for example, the analysis of TADs (topological associating domains) would be interesting to add and could be used to evaluate to what extent H3K27ac domains and putative regulated genes fall within the same TAD.

The authors present some convincing evidence on the transcriptional regulation of the PLCL2 gene using Perturb-Seq to identify putative upstream enhancer regions and PGR over-expression showing PGR can act as an activator. These two experiments on their own are interesting, however, they are not as mechanistically integrated as they could be to clarify the molecular mechanisms. Deletion of the putative enhancer upstream of PLCL2 followed by over-expression of PGR would clarify the mechanistic relationship between the proposed enhancer, PGR and PLCL2 expression. Does PGR act through the proposed enhancer? In addition, reporter assays using this proposed enhancer region with and without increased expression of PGR and mutation of any PRE sequences would also provide mechanistic insight. Although CRISPRa and Perturb-Seq can be used to identify potential regulatory regions, the best approach to verify the requirement for a particular enhancer in regulating a specific gene is a deletion approach.

Comments on revisions:

The authors have addressed my comments that were directly sent to them, however, my comments in the public review, specifically the superficial nature of the Hi-C analysis were not addressed.

In addition, many of the comments to reviewer 3 were unaddressed and declared out of the scope of this study, as these were points of accuracy in the data analysis they are very much in scope.

I hope the authors reconsider presenting a more thorough analysis.

Reviewer #3 (Public review):

In this manuscript, Wu et al. investigate active H3K27ac and H3K4me1 marks in term pregnant nonlabor myometrial biopsies, linking putative enhancers and super enhancers to gene expression levels. Through their findings, they reveal the PGR-dependent regulation of the PLCL2 gene in human myometrial cells via a cis-acting element located 35-kilobases upstream of the PLCL2 gene. By targeting this region using a CRISPR activation system, they were able to increase the elevate the endogenous PLCL2 mRNA levels in immortalized human myometrial cells.

This research offers novel insights into the molecular mechanisms governing gene expression in myometrial tissues, advancing our understanding of pregnancy-related processes.

Major comments:

(1) A more comprehensive analysis of the epigenetic and transcriptomic data would have strengthened the paper, moving beyond basic association studies. Currently, it is challenging to assess the quality and significance of the data as much of the information is lacking.

Strengths:

- The combination of ChIP-Seq, RNA-Seq, and CRISPRa Perturb-Seq approaches to investigate gene regulation and expression in myometrial cells.<br /> - The use of CRISPR activation system to specifically target cis-acting elements.

Weaknesses:

- The manuscript would strongly benefit from a deeper analysis of the Omic datasets. Furthermore, expanding figures/graphs to effectively contextualize these datasets would be greatly beneficial and would add more value to this research.<br /> - Limited sample size, coupled with variability in results and overall lack of details, compromises the robustness of result interpretation.<br /> - Additional efforts are needed to dissect the proposed regulatory mechanisms.<br /> - While the discussion provided helpful context for understanding some of the experiments performed, it lacked interpretation of the results in relation to the existing literature.

Comments on revisions:

The authors have improved the manuscript by enhancing its readability and organization. Tables were added to present key information more clearly, and figures were refined for better visualization. Additionally, more details were included, particularly in the methods and bioinformatics analyses sections, ensuring a more comprehensive and precise presentation of the data.

However, in many cases, reviewers' questions and concerns were addressed in the response to reviewers rather than incorporated into the manuscript, or it was noted that these points would be explored in future studies.

Reviewer #2 (Public review):

Summary:

This study investigates the molecular function of the N-glycan-dependent endoplasmic reticulum protein quality control system (ERQC) in Cryptococcus neoformans and correlates this pathway with key features of C. neoformans virulence, especially those mediated by extracellular vesicle transport. The findings provide valuable insights into the connection between this pathway and the biogenesis of C. neoformans extracellular vesicles.

Strengths:

The strength of this study lies primarily in the careful selection of appropriate and current methodologies, which provide a solid foundation for the authors' results and conclusions across all presented data. All experiments are supported by well-designed and established controls in the study of C. neoformans, further strengthening the validity of the results and conclusions drawn from them. The study presents novel data on this important pathway in C. neoformans, establishing its connection with C. neoformans virulence. Interestingly, the findings led the authors to understand the relationship between this pathway and the transport of key fungal virulence factors via extracellular vesicles. This was demonstrated in the study, paving the way for a deeper understanding of extracellular vesicle biogenesis-a field still filled with gaps but one that this study contributes to with solid data, helping to clarify aspects of this process.

Reviewer #3 (Public review):

Summary:

Cryptococcus neoformans is a global critical threat pathogen and the manuscript by Mota et al demonstrates that the pathogen's N-glycan-dependent protein quality control system regulates the capacity of the fungus to cause disease. The system ensures that glycoproteins are folded correctly. The system is involved in fitness and virulence of the fungus by regulating aspects of cellular robustness and the trafficking of virulence-associated compounds outside of the cell via transport in extracellular vesicles.

Strengths:

The investigators use multiple modalities to demonstrate that the system is involved in cryptococcal pathogenesis. The investigators generated mutant C. neoformans to explore the role of genes involved in the protein folding system. Basic microbiology, genetic analyses, proteomics, fluorescence and transmission microscopy, nanotracking analyses, and murine studies were performed. The validity of the findings are thus very high. Hypotheses are robustly demonstrated.

Reviewer #1 (Public review):

Summary:

This manuscript aims to explain the emergence of grid-like spatial firing patterns. Rather than taking the existence of grid cells as a given and asking what does their properties say about their function, the authors reverse the approach: they begin with a proposed computational function that the brain may need to perform-coding of 2D spatial trajectories using sequences of neural activity-and ask what type of neural code would optimally support this function. They show that, under a set of formal assumptions, such a code leads to the emergence of spatial periodicity and a hexagonal grid pattern. The aim is to provide a normative explanation for the existence of grid cells grounded in functional constraints.

Strengths:

The manuscript presents a mathematically well-defined framework that is internally consistent. The derivation is structured and leads to a hexagonal lattice as the most efficient solution for representing directional trajectories. The authors provide comparisons to experimental observations and extend the model to explain several findings in the grid cell literature. In the revised version, the discussion of foundational assumptions is expanded, and the manuscript better situates itself in relation to prior theoretical work. Overall, this work adds a very interesting view to the broader conversation about the role and origin of grid cells by offering a theoretical alternative grounded in trajectory coding.

Weaknesses:

The model depends on assumptions that, while plausible, should be treated as chosen assumptions. These include the premise that (1) grid function is trajectory coding, (2) that trajectory coding is implemented through sequences of neural activity, and (3) that such sequences are largely independent of spatial position. In the revised manuscript, the authors provide more literature to support these assumptions.

Reviewer #2 (Public review):

Summary:

In this work, the authors consider the required functional properties of neurons that trajectories in 2D space using cell sequences, ultimately linking the required properties to those found in grid cells. In their argument, the authors first introduce a set of definitions and axioms, which then lead to their conclusion that a hexagonal pattern is the most efficient or parsimonious pattern one could use to uniquely label different 2D trajectories using sequences of cells. The authors then go through a set of classic experimental results in the grid cell literature - e.g. that the grid modules exhibit a multiplicative scaling, that the grid pattern expands with novelty or is warped by reward, etc. - and describe how these results are either consistent with or predicted by their theory. Overall, this paper asks a very interesting question and provides an intriguing answer.

Major strengths:

The general idea behind the paper is very interesting - why *does* the grid pattern take the form of a hexagonal grid? This is a question that has been raised many times; finding a truly satisfying answer is difficult but of great interest. The authors' main assertion that the answer to this question has to do with the ability of a hexagonal arrangement of neurons to uniquely encode 2D trajectories is an intriguing suggestion. It is also impressive that the authors considered such a wide range of experimental results in relation to their theory.

Major weaknesses:

One weakness I perceive is that the paper overstates what it delivers. In the introduction, the authors claim to provide "mathematical proof that ... the nature of the problem being solved by grid cells is coding of trajectories in 2-D space using cell sequences. By doing so, we offer a specific answer to the question of why grid cell firing patterns are observed in the mammalian brain." By virtue of the fact that the authors make assumptions about biological function in their claims, this paper does not provide proof of what grid cells are doing to support behavior nor provide the true answer as to why grid patterns are found in the brain. Although I find this study both intriguing and important - and I respect the authors' perspective - as an experimentalist guided by the principle that biological theories are never proven but instead continually supported by data, suggestions of a proof of grid cell function are hard for me to get behind. Regardless, the paper presents a compelling line of reasoning that enhance our understanding of grid cells.

Reviewer #3 (Public review):

Concerning the revised manuscript, the authors are to be commended for carefully addressing the reviewers' comments and updating the references cited.

I will differ with the authors' argument that Gardner et al's paper supports the idea of sequences, except in the most trivial sense, namely that topology implies continuity, and hence movement along the manifold will be continuous, and if one discretizes this movement, one would get a sequence.

This has very little to do with the idea that the authors propose in their manuscript. If the authors were to so choose, their idea will produce an embedded graph, and they could study the topology of this construct---but this would mean going off on a tangent.

Let us not hold up the authors to an impossible standard, namely that their theory should explain everything in the grid cell field. Not every finding under the sun needs be addressed in the discussion.

My own take on the manuscript had been that the authors' interesting idea might be fairly straightforwardly provable. The authors have decided to put another student on this particular project. That is perfectly OK. Just one final note: mathematically, the main focus ought to be on sequences of prime length (many other results will likely follow).

Joint Public Review:

Summary:

In this study, Daniel et al. used three cognitive tasks to investigate behavioural signatures of cerebellar degeneration. In the first two tasks, the authors found that if an equation was incorrect, reaction times slowed significantly more for cerebellar patients than for healthy controls. In comparison, the slowing in the reaction times when the task required more operations was comparable to normal controls. In the third task, the authors show increased errors in cerebellar patients when they had to judge whether a letter string corresponded to an artificial grammar.

Strengths:

Overall, the work is methodologically sound and the manuscript well written. The data do show some evidence for specific cognitive deficits in cerebellar degeneration patients.

Weaknesses:

The current version has some weaknesses in the visual presentation of results. Overall, the study lacks a more precise discussion on how the patterns of deficits relate to the hypothesized cerebellar function.

The reviewers and the editor agreed that the data are interesting and point to a specific cognitive deficit in cerebellar patients. However, in the discussion, we were somewhat confused about the interpretation of the result:

If the cerebellum (as proposed in the introduction) is involved in forming expectations in a cognitive task, should they not show problems both in the expected (1+3 =4) and unexpected (1+3=2) conditions? Without having formed the correct expectation, how can you correctly say "yes" in the expected condition? No increase in error rate is observed - just slowing in the unexpected condition. But this increase in error rate was not observed. If the patients make up for the lack of prediction by using some other strategy, why are they only slowing in the unexpected case?

If the cerebellum is NOT involved in making the prediction, but only involved in detecting the mismatch between predicted and real outcome, why would the patients not show specifically more errors in the unexpected condition?

Reviewer #1 (Public review):

Summary:

This study builds upon a major theoretical account of value-based choice, the 'attentional drift diffusion model' (aDDM), and examines whether and how this might be implemented in the human brain using functional magnetic resonance imaging (fMRI). The aDDM states that the process of internal evidence accumulation across time should be weighted by the decision maker's gaze, with more weight being assigned to the currently fixated item. The present study aims to test whether there are (a) regions of the brain where signals related to the currently presented value are affected by the participant's gaze; (b) regions of the brain where previously accumulated information is weighted by gaze.

To examine this, the authors developed a novel paradigm that allowed them to dissociate currently and previously presented evidence, at a timescale amenable to measuring neural responses with fMRI. They asked participants to choose between bundles or 'lotteries' of food times, which they revealed sequentially and slowly to the participant across time. This allowed modelling of the haemodynamic response to each new observation in the lottery, separately for previously accumulated and currently presented evidence.

Using this approach, they find that regions of the brain supporting valuation (vmPFC and ventral striatum) have responses reflecting gaze-weighted valuation of the currently presented item, whereas regions previously associated with evidence accumulation (preSMA and IPS) have responses reflecting gaze-weighted modulation of previously accumulated evidence.

Strengths:

A major strength of the current paper is the design of the task, nicely allowing the researchers to examine evidence accumulation across time despite using a technique with poor temporal resolution. The dissociation between currently presented and previously accumulated evidence in different brain regions in GLM1 (before gaze-weighting), as presented in Figure 5, is already compelling. The result that regions such as preSMA respond positively to |AV| (absolute difference in accumulated value) is particularly interesting, as it would seem that the 'decision conflict' account of this region's activity might predict the exact opposite result. Additionally, the behaviour has been well modelled at the end of the paper when examining temporal weighting functions across the multiple samples.

Weaknesses:

The results relating to gaze-weighting in the fMRI signal could do with some further explication to become more complete. A major concern with GLM2, which looks at the same effects as GLM1 but now with gaze-weighting, is that these gaze-weighted regressors may be (at least partially) correlated with their non-gaze-weighted counterparts (e.g., SVgaze will correlate with SV). But the non-gaze-weighted regressors have been excluded from this model. In other words, the authors are not testing for effects of gaze-weighting of value signals *over and above* the base effects of value in this model. In my mind, this means that the GLM2 results could simply be a replication of the findings from GLM1 at present. GLM3 is potentially a stronger test, as it includes the value signals and the interaction with gaze in the same model. But here, while the link to the currently attended item is quite clear (and a replication of Lim et al, 2011), the link to previously accumulated evidence is a bit contorted, depending upon the interpretation of a behavioural regression to interpret the fMRI evidence. The results from GLM3 are also, by the authors' own admission, marginal in places.

Reviewer #2 (Public review):

Summary:

In this paper, the authors seek to disentangle brain areas that encode the subjective value of individual stimuli/items (input regions) from those that accumulate those values into decision variables (integrators) for value-based choice. The authors used a novel task in which stimulus presentation was slowed down to ensure that such a dissociation was possible using fMRI despite its relatively low temporal resolution. In addition, the authors leveraged the fact that gaze increases item value, providing a means of distinguishing brain regions that encode decision variables from those that encode other quantities such as conflict or time-on-task. The authors adopt a region-of-interest approach based on an extensive previous literature and found that the ventral striatum and vmPFC correlated with the item values and not their accumulation, whereas the pre-SMA, IPS, and dlPFC correlated more strongly with their accumulation. Further analysis revealed that the pre-SMA was the only one of the three integrator regions to also exhibit gaze modulation.

Strengths:

The study uses a highly innovative design and addresses an important and timely topic. The manuscript is well-written and engaging, while the data analysis appears highly rigorous.

Weaknesses:

With 23 subjects, the study has relatively low statistical power for fMRI.

Reviewer #1 (Public review):

Summary:

This study builds on previous work demonstrating that several beta connexins (Cx26, Cx30, and Cx32) have a carbamylation motif which renders them sensitive to CO2. In response to CO2, hemichannels composed of these connexins open, enabling diffusion of small molecules (such as ATP) between the cytosol and extracellular environment. Here, the authors have identified that an alpha connexin, Cx43, also contains a carbamylation motif, and they demonstrate that CO2 opens Cx43 hemichannels. Most of the study involves using transfected cells expressing wild-type and mutant Cx43 to define amino acids required for CO2 sensitivity. Hippocampal tissue slices in culture were used to show that CO2-induced synaptic transmission was affected by Cx43 hemichannels, providing a physiological context. The authors point out that the Cx43 gene significantly diverges from the beta connexins that are CO2 sensitive, suggesting that the conserved carbamylation motif was present before the alpha and beta connexin genes diverged.

Strengths:

(1) The molecular analysis defining the amino acids that contribute to the CO2 sensitivity of Cx43 is a major strength of the study. The rigor of analysis was strengthened by using three independent assays for hemichannel opening: dye uptake, patch clamp channel measurements, and ATP secretion. The resulting analysis identified key lysines in Cx43 that were required for CO2-mediated hemichannel opening. A double K to E Cx43 mutant produced a construct that produced hemichannels that were constitutively open, which further strengthened the analysis.

(2) Using hippocampal tissue sections to demonstrate that CO2 can influence field excitatory postsynaptic potentials (fEPSPs) provides a native context for CO2 regulation of Cx43 hemichannels. Cx43 mutations associated with Oculodentodigital Dysplasia (ODDD) inhibited CO2-induced hemichannel opening, although the mechanism by which this occurs was not elucidated.

Weaknesses:

(1) Cx43 channels are sensitive to cytosolic pH, which will be affected by CO2. Cytosolic pH was not measured, and how this affects CO2-induced Cx43 hemichannel activity was not addressed.

(2) Cultured cells are typically grown in incubators containing 5% CO2, which is ~40 mmHg. It is unclear how cells would be viable if Cx43 hemichannels are open at this PCO2.

(3) Experiments using Gap26 to inhibit Cx43 hemichannels in fEPSP measurements used a scrambled peptide as a control. Analysis should also include Gap peptides specifically targeting Cx26, Cx30, and Cx32 as additional controls.

(4) The mechanism by which ODDD mutations impair CO2-mediated hemichannel opening was not addressed. Also, the potential roles for inhibiting Cx43 hemichannels in the pathology of ODDD are unclear.

(5) CO2 has no effect on Cx43-mediated gap junctional communication as opposed to Cx26 gap junctions, which are inhibited by CO2. The molecular basis for this difference was not determined.

(6) Whether there are other non-beta connexins that have a putative carbamylation motif was not addressed. Additional discussion/analysis of how the evolutionary trajectory for Cx43 maintaining a carbamylation motif is unique for non-beta connexins would strengthen the study.

Reviewer #2 (Public review):

Summary:

This paper examines the CO2 sensitivity of Cx43 hemichannels and gap junctional channels in transiently transfected Hela cells using several different assays, including ethidium dye uptake, ATP release, whole cell patch clamp recordings, and an imaging assay of gap junctional dye transfer. The results show that raising pCO2 from 20 to 70 mmHg (at a constant pH of 7.3) causes an increase in opening of Cx43 hemichannels but does not block Cx43 gap junctions. This study also showed that raising pCO2 from 20 to 35 mm Hg resulted in an increase in synaptic strength in hippocampal rat brain slices, presumably due to downstream ATP release, suggesting that the CO2 sensitivity of Cx43 may be physiologically relevant. As a further test of the physiological relevance of the CO2 sensitivity of Cx43, it was shown that two pathological mutations of Cx43 that are associated with ODDD caused loss of Cx43 CO2-sensitivity. Cx43 has a potential carbamylation motif that is homologous to the motif in Cx26. To understand the structural changes involved in CO2 sensitivity, a number of mutations were made in Cx43 sites thought to be the equivalent of those known to be involved in the CO2 sensitivity of Cx26, and the CO2 sensitivity of these mutants was investigated.

Strengths:

This study shows that the apparent lack of functional Cx43 hemichannels observed in a number of previous in vitro function studies may be due to the use of HEPES to buffer the external pH. When Cx43 hemichannels were studied in external solutions in which CO2/bicarbonate was used to buffer pH instead of HEPES, Cx43 hemichannels showed significantly higher levels of dye uptake, ATP release, and ionic conductance. These findings may have major physiological implications since Cx43 hemichannels are found in many organs throughout the body, including the brain, heart, and immune system.

Weaknesses:

(1) Interpretation of the site-directed mutation studies is complicated. Although Cx43 has a potential carbamylation motif that is homologous to the motif in Cx26, the results of site-directed mutation studies were inconsistent with a simple model in which K144 and K105 interact following carbamylation to cause the opening of Cx43 hemichannels.

(2) Secondly, although it is shown that two Cx43 ODDD-associated mutations show a loss of CO2 sensitivity, there is no evidence that the absence of CO2 sensitivity is involved in the pathology of ODDD.

Reviewer #3 (Public review):

In this paper, the authors aimed to investigate carbamylation effects on the function of Cx43-based hemichannels. Such effects have previously been characterized for other connexins, e.g., for Cx26, which display increased hemichannel (HC) opening and closure of gap junction channels upon exposure to increased CO2 partial pressure (accompanied by increased bicarbonate to keep pH constant).<br /> The authors used HeLa cells transiently transfected with Cx43 to investigate CO2-dependent carbamylation effects on Cx43 HC function. In contrast to Cx43-based gap junction channels that are reported here to be insensitive to PCO2 alterations, they provide evidence that Cx43 HC opening is highly dependent on the PCO2 pressure in the bath solution, over a range of 20 up to 70 mmHg encompassing the physiologically normal resting level of around 40 mmHg. They furthermore identified several Cx43 residues involved in Cx43 HC sensitivity to PCO2: K105, K109, K144 & K234; mutation of 2 or more of these AAs is necessary to abolish CO2 sensitivity. The subject is interesting and the results indicate that a fraction of HCs is open at a physiological 40 mmHg PCO2, which differs from the situation under HEPES buffered solutions where HCs are mostly closed under resting conditions. The mechanism of HC opening with CO2 gassing is linked to carbamylation, and the authors pinpointed several Lys residues involved in this process.

Overall, the work is interesting as it shows that Cx43 HCs have a significant open probability under resting conditions of physiological levels of CO2 gassing, probably applicable to the brain, heart, and other Cx43 expressing organs. The paper gives a detailed account of various experiments performed (dye uptake, electrophysiology, ATP release to assess HC function) and results concluded from those. They further consider many candidate carbamylation sites by mutating them to negatively charged Glu residues. The paper ends with hippocampal slice work showing evidence for connexin-dependent increases of the EPSP amplitude that could be inhibited by HC inhibition with Gap26 (Figure 10). Another line of evidence comes from the Cx43-linked ODDD genetic disease, whereby L90V as well as the A44V mutations of Cx43 prevented the CO2-induced hemichannel opening response (Figure 11). Although the paper is interesting, in its present state, it suffers from (i) a problematic Figure 3, precluding interpretation of the data shown, and (ii) the poor use of hemichannel inhibitors that are necessary to strengthen the evidence in the crucial experiment of Figure 2 and others.

Reviewer #1 (Public review):

Summary:

In this manuscript, Lau et al reported that KDM5 inhibition in luminal breast cancer cells results in R-loop-mediated DNA damage, reduced cell fitness and an increase in ISG and AP signatures as well as cell surface Major Histocompatibility Complex (MHC) class I, mediated by RNA:DNA hybrid activation of the CGAS/STING pathway.

Strengths:

More importantly, they have shown that KDM5 inhibition does not result in DNA damage or activation of the CGAS/STING pathway in normal breast epithelial cells. This suggests that KDM5 inhibitors may enable a wide therapeutic window in this setting, as compared to STING agonists or Type I Interferons. Their findings provide new insights into the interplay between epigenetic regulation of genomic repeats, R-loop formation, innate immunity, and cell fitness in the context of cancer evolution and therapeutic vulnerability.

Weaknesses:

More thorough analyses would be appreciated.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated how the type-I interferon response (ISG) and antigen presentation (AP) pathways are repressed in luminal breast cancer cells and how this repression can be overcome. They found that a STING agonist can reactivate these pathways in breast cancer cells, but it also does so in normal cells, suggesting that this is not a good way to create a therapeutic window. Depletion of ADAR and inhibition of KDM5 also activate ISG and AP genes. The activation of ISG and AP genes is dependent on cGAS/STING and the JAK kinase. Interestingly, although both ADAR depletion and KDM5 inhibition activate ISG and AP genes, their effects on cell fitness are different. Furthermore, KDM5 inhibitor selectively activates ISG and AP genes in tumor cells but not normal cells, arguing that it may create a larger therapeutic window than the STING agonist. These results also suggest that KDM5 inhibition may activate ISG and AP genes in a way different from ADAR loss, and this process may affect tumor cell fitness independently of the activation of ISG and AP genes.

The authors further showed that KDM5 inhibition increases R-loops and DNA damage in tumor cells, and XPF, a nuclease that cuts R-loops, is required for the activation of ISG and AP genes. Using H3K4me3 CUT&RUN, they found that KMD5 inhibition results in increased H3K4me3 not only at genes, but also at repetitive elements including SINE, LINE, LTR, telomeres, and centromeres. Using S9.6 CUT&TAG, they confirmed that R-loops are increased at SINE, LINE, and LTR repeated with increased H3K4me3. Together, the results of this study suggest that KMD5 inhibition leads to H3K4me3 and R-loop accumulation in repetitive elements, which induces DNA damage and cGAS/STING activation and subsequently activates AP genes. This provides an exciting approach to stimulate the anti-tumor immunity against breast tumors.

KDM5 inhibition activates interferon and antigen presentation genes through R-loops.

Strengths:

Overall, this study was carefully designed and executed. This is a new approach to make breast tumors "hot" for anti-tumor immunity.

Weaknesses:

Future in vivo studies are needed to show the effects of KDM5 inhibitors on the immunotherapy responses of breast tumors.

Reviewer #1 (Public review):

Summary:

In this study, the authors set out to define how arginine availability regulates lipid metabolism and to explore the implications of this relationship in pancreatic ductal adenocarcinoma (PDAC), a tumor type known to exist in an arginine-poor microenvironment. Using a combination of rigorous genetic and metabolomic approaches, they uncover a previously underappreciated role for arginine in maintaining lipid homeostasis. Importantly, they demonstrate that arginine deprivation sensitizes PDAC cells to ferroptosis through lipidome perturbations, which can be exploited therapeutically via co-treatment with aESA and ferroptosis inducers (FINs). These findings have meaningful implications for the field. They not only shed light on the metabolic vulnerabilities created by nutrient restriction in PDAC, but also suggest a practical avenue for combination therapies that exploit ferroptosis sensitivity. This is particularly relevant in the context of pancreatic cancer, which is notoriously resistant to conventional treatments. The methods employed are broadly applicable to other nutrient-stress contexts and may inspire similar investigations in other solid tumor types.

Strengths:

One of the major strengths of the study is the use of complementary and well-controlled approaches-including metabolomic profiling, genetic perturbations, and in vivo models-to support the central hypothesis. The experiments are thoughtfully designed and clearly presented, and the conclusions are, for the most part, well supported by the data. The findings provide mechanistic insight into nutrient-lipid crosstalk and identify a potential therapeutic strategy for targeting arginine-deprived tumors.

Weaknesses:

A key weakness of the study lies in the mechanistic connection between arginine levels and SREBP1 activation. While the authors show that arginine restriction leads to reduced SREBP1 expression, the magnitude of this effect appears modest relative to the substantial changes observed in the lipidome. The study would benefit from a deeper analysis of SREBP1 regulation-particularly whether nuclear translocation or activation is affected. This could be addressed by examining the nuclear pool of SREBP1, using either subcellular fractionation or improved immunofluorescence imaging in both cell lines and tissue samples.

Another area where additional context would strengthen the manuscript is in the transcriptomic profiling of PDAC cells cultured in a tumor interstitial fluid mimic (TIFM). While the study emphasizes lipid-related pathways, highlighting the most significantly upregulated and downregulated pathways in Figure 1B would give readers a broader perspective on how arginine restriction reprograms the PDAC transcriptome. For instance, because polyamines are downstream of arginine and are known to influence lipid metabolism, it would be worth discussing whether these metabolites contribute to the phenotypes observed. Similarly, an evaluation of whether Dgat1/2 expression is altered could help delineate the full scope of lipid metabolic rewiring.

Finally, it is worth noting that the KPC mouse model used in this study is based on conditional deletion of p53, which leads to faster-growing tumors and a distinct tumor microenvironment compared to models harboring the p53^R172H point mutation. Including a brief discussion of this distinction would help readers contextualize the translational relevance of the findings.

Reviewer #2 (Public review):

This study by Jonker et al. examines how the metabolic adaptations to the microenvironment by pancreatic ductal adenocarcinomas (PDAC) present vulnerabilities that could be used for therapeutic purposes. The evidence supporting the claims of the authors is mostly solid, and the multiplicity of models used, as well as the combination of in vitro and in vivo work, are appreciated, but some conclusions would benefit from additional substantiation. This work would be of interest to biologists working on the impact of microenvironment and metabolism in cancer, and especially those investigating pancreatic cancer.

In this study, the authors use mostly "doublings per day" as an indicator of cell death, notably for Figures 4 to 6. However, proliferative arrest (or a decrease in the proliferative rate) is not necessarily synonymous with cell death. It might be nice to complement these experiments with a true measure of cell death (e.g., PI uptake).

The composition of Tumor Interstitial Fluid Medium (TIFM) was published previously, but nonetheless a reminder of the composition of this medium in a Supplemental file of this study might be helpful. In particular, at the start of the Results section, the nature of serum/lipids in the different media should be specifically noted, especially given that the subsequent focus of the work is on lipids/SREBP. It is known that differences in the extracellular availability of lipids can profoundly alter de novo lipid biosynthesis pathways.

Reviewer #3 (Public review):

This important study investigates the impact of nutrient stress in the tumor microenvironment (TME), focusing on lipid metabolism in pancreatic ductal adenocarcinoma (PDAC).

Understanding TME composition is crucial, as it highlights cancer vulnerabilities independent of intracellular mutations, particularly because PDAC tumors are often exposed to limited nutrient availability due to reduced perfusion.

By utilizing a medium that mimics the nutrient conditions of PDAC tumors, the authors convincingly show that TME nutrient stress suppresses SREBP1, leading to reduced lipid synthesis, with low arginine levels identified as a key driver of this suppression. Importantly, mice with arginine-starved pancreatic tumors respond to a polyunsaturated fatty acid-rich diet. This discovery uncovers a synthetic lethal interaction in the tumor microenvironment that could be leveraged through dietary interventions.

The conclusions of this paper are mostly well supported by data; however, below are some aspects that could be further clarified.

This study uses PDAC cells from the LSL-Kras G12D/+ ; Trp53 ; Pdx-1-Cre PDAC model. The authors convincingly demonstrate that the cell-extrinsic stimuli of low arginine availability suppress lipid synthesis and thus exert a dominant effect over the cell-intrinsic oncogenic Ras mutation, which is known to enhance fatty acid synthesis. Could the effect of low arginine on lipid synthesis be specific for certain mutations in PDAC? It would be interesting to investigate or discuss whether different mutations show the same SREBP1 reduction caused by low arginine levels, and whether these low SREBP1 levels can be ameliorated by arginine re-supplementation. Here, Jonker et al. show that human PDAC cells cultured in TIFM have reduced SREBP1 levels (Figure 1 - Figure supplement 1C). It would be further supportive of their conclusions if the authors could show that arginine re-supplementation is sufficient to restore SREBP1 levels in human PDAC cells.

The authors demonstrate that mPDAC cells cultured in RPMI and subsequently implanted into an orthotopic mouse model exhibit reduced expression of SREBP target genes when compared to in vitro cultured mPDAC-RPMI cells. This finding is in line with the observation that culturing PDAC cells in TIFM downregulates SREBP target genes compared to PDAC cells cultured in RPMI. However, caution is needed when directly comparing mPDAC-RPMI cultured cells to those in the orthotopic model, as the latter may include non-tumor cells and additional factors that could confound the results. The authors should explicitly acknowledge this limitation in their study.

The in vivo evidence demonstrating that PUFA-rich tung oil reduces tumor size is compelling. However, the specific in vitro findings regarding its impact on doubling rates per day, particularly in the context of arginine-dependent PUFA supplementation, require further explanation. To enhance the robustness of their data and conclusions, the authors could consider conducting additional cell viability and proliferation assays. Moreover, it would be valuable to assess whether the observed effects on doubling rates per day remain significant after normalizing the data to the initial doubling time prior to PUFA supplementation. This is in particular important regarding the statement that "Addition of arginine significantly decreases sensitivity to a-ESA" as these cells already start with a higher doubling rate prior to a-ESA treatment.

Overall, this paper presents a compelling study that significantly enhances our understanding of the PDAC tumor microenvironment and its complex interactions with the tumor lipid metabolism.

Reviewer #1 (Public review):

Summary:

The manuscript uses state-of-the-art analysis technology to document the spatio-temporal dynamics of brain activity during the processing of threats. The authors offer convincing evidence that complex spatio-temporal aspects of brain dynamics are essential to describe brain operations during threat processing.

Strengths:

Rigorous complex analyses well suited to the data.

Weaknesses:

Lack of a simple take-home message about discovery of a new brain operation.

Comments on revisions:

The authors have improved the presentation of the work. The overstatements about existing models of brain functions ignoring exogenous components remains largely unaddressed. The clarifications and improvements provided in revision confirm my assessment of the paper.

Reviewer #2 (Public review):

Summary:

This paper by Misra and Pessoa uses switching linear dynamical systems (SLDS) to investigate the neural network dynamics underlying threat processing at varying levels of proximity. Using an existing dataset from a threat-of-shock paradigm in which threat proximity is manipulated in a continuous fashion, the authors first show that they can identify states that each have their own linear dynamical system and are consistently associated with distinct phases of the threat-of-shock task (e.g., "peri-shock", "not near", etc). They then show how activity maps associated with these states are in agreement with existing literature on neural mechanisms of threat processing, and how activity in underlying brain regions alters around state transitions. The central novelty of the paper lies in its analyses of how intrinsic and extrinsic factors contribute to within-state trajectories and between-state transitions. Additional analyses furthermore show how individual brain regions contribute to state dynamics. Finally, the authors show how their findings generalize to another (related) threat paradigm.

Strengths:

The analyses for this study are conducted at a very high level of mathematical and theoretical sophistication. The paper is very well written and effectively communicates complex concepts from dynamical systems. The paper provides valuable neuroscientific insights into threat processing, and the methodology has potential to deepen our understanding at a neurobiological level in future work.

Weaknesses:

I was somewhat disappointed initially by the level of inferences made by the authors based on their analyses at the level of systems neuroscience. After revision this has improved, for instance with inclusion of analyses on the importance of individual brain regions to state dynamics, but I still believe the findings can be made more biologically meaningful, for instance by focusing on what we learn from these sophisticated analyses beyond what is already known from more conventional methodologies. However, the paper as it stands is solid scientific work and such efforts may also be left to future work.

Reviewer #1 (Public review):

Summary:

A cortico-centric view is dominant in the study for the neural mechanisms of consciousness. This investigation represents the growing interest to understand how subcortical regions are involved in conscious perception. To achieve this, the authors engaged an ambitious and rare procedure in humans of directly recording from neurons in the subthalamic nucleus and thalamus. While participants were in surgery for the placement of deep brain stimulation devices for the treatment of essential tremor and Parkinson's disease, they were awakened and completed a perceptual-threshold tactile detection task. The authors identified individual neurons and analyzed single-unit activity corresponding with the task phases and tactile detection/perception. Among the neurons that were perception-responsive, the authors report changes in firing rate beginning ~150 milliseconds from the onset of the tactile stimulation. Curiously, the majority of the perception-responsive neurons had a higher firing rate for missed/not perceived trials. In summary, this investigation is a valuable addition to the growing literature on the role of subcortical regions in conscious perception.

Strengths:

The authors achieve the challenging task of recording human single-unit activity while participants performed a tactile perception task. The methods and statistics are clearly explained and rigorous, particularly for managing false positives and non-normal distributions. The results offer new detail at the level of individual neurons in the emerging recognition for the role of subcortical regions in conscious perception. Also, this study highlights the timing of neural activity linked to conscious perception (approximately 150 millisecond).

Weaknesses:

Due to constraints of testing with this patient population, a standard report-based detection task was administered. This type of task cannot fully exclude motor preparatory and post-perceptual processing as a factor that contributes to distinguishing between perceived versus not perceived stimuli. The authors show sensitivity to this issue by identifying task-selective neurons and their discussion of the results that refers to the confound of post-perceptual processing. Despite this limitation, the results are valuable for contributing to a growing body of literature on the subcortical neural mechanisms of consciousness.

Reviewer #2 (Public review):

The authors have examined subpopulations of individual neurons recorded in the thalamus and subthalamic nucleus (STN) of awake humans performing a simple cognitive task. They have carefully designed their task structure to minimize motor components that could confound their analyses in these subcortical structures, particularly given that the data was collected from patients with Parkinson's disease (PD) and essential tremor (ET). The recorded data represents a valuable contribution to the field. Pereira et al. conclude that their single-neuron recordings indicate task-related activity that is purportedly distinct from previously identified sensory signals.

Despite the significance of the dataset, important limitations arise due to the small number of recorded neurons relative to the high number of participants. That raises concerns about the generalizability of the conclusions drawn from the study.

(1) While I support the work conducted by the authors and their efforts to improve the manuscript, the number of significant neurons is considerably lower than the number of participants studied-approximately 8 neurons, compared to 32 participants. This low number of neurons involved in encoding raises concerns about the strength of the conclusions drawn.

(2) Additionally, the authors state that participants do not need to perform a motor execution, yet they are required to communicate their response verbally. This presents a contradiction, as speech involves the activation of facial muscles, and previous studies have shown that neuronal activity in the ventral premotor cortex can encode such movements in humans (Willet et al., Nature 2023). Clarifying this point would strengthen the argument and ensure consistency in the interpretation of results.

(3) One way to improve the study is to analyze the local field potentials (LFPs) recorded alongside the spikes. By examining different LFP components, particularly the beta band (Haegens et al., PNAS 2011), it may be possible to identify consistent modulation across the 32 recorded participants. This approach could provide additional support for the study's conclusions and help clarify the role of neural activity in the observed phenomena.

Reviewer #3 (Public review):

Summary:

This important study relies on a rare dataset: intracranial recordings within the thalamus and the subthalamic nucleus in awake humans, while they were performing a tactile detection task. This procedure allowed the authors to identify a small but significant proportion of individual neurons, in both structures, whose activity correlated with the task (e.g. their firing rate changed following the audio cue signalling the start of a trial) and/or with the stimulus presentation (change in firing rate around 200 ms following tactile stimulation) and/or with participant's reported subjective perception of the stimulus (difference between hits and misses around 200 ms following tactile stimulation). Whereas most studies interested in the neural underpinnings of conscious perception focus on cortical areas, these results suggest that subcortical structures might also play a role in conscious perception, notably tactile detection.

Strengths:

There are two strongly valuable aspects in this study that make the evidence convincing and even compelling. First, these type of data are exceptional, the authors could have access to subcortical recordings in awake and behaving humans during surgery. Additionally, the methods are solid. The behavioral study meets the best standards of the domain, with a careful calibration of the stimulation levels (staircase) to maintain them around detection threshold, and additional selection of time intervals where the behavior was stable. The authors also checked that stimulus intensity was the same on average for hits and misses within these selected periods, which warrants that the effects of detection that are observed here are not confounded by stimulus intensity. The neural data analysis is also very sound and well conducted. The statistical approach complies to current best practices, although I found that, on some instances, it was not entirely clear which type of permutations had been performed, and I would advocate for more clarity in these instances. Globally, the figures are nice, clear and well presented. I appreciated the fact that the precise anatomical location of the neurons was directly shown in each figure.

Weaknesses:

The results rely on a small number of neurons; it is only the beginning of this exploration! Figure S5 is important for observing the variety of ways the neurons' activity correlated with either stimulus presence, or perception, or both. Interpretations are still very open on these different profiles.

Reviewer #1 (Public review):

This study examines the role of host blood meal source, temperature, and photoperiod on the reproductive traits of Cx. quinquefasciatus, an important vector of numerous pathogens of medical importance. The host use pattern of Cx. quinquefasciatus is interesting in that it feeds on birds during spring and shifts to feeding on mammals towards fall. Various hypotheses have been proposed to explain the seasonal shift in host use in this species but have provided limited evidence. This study examines whether the shifting of host classes from birds to mammals towards autumn offers any reproductive advantages to Cx. quinquefasciatus in terms of enhanced fecundity, fertility, and hatchability of the offspring. The authors found no evidence of this, suggesting that alternate mechanisms may drive the seasonal shift in host use in Cx. quinquefasciatus.

Reviewer #2 (Public review):

Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness on birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used generalized linear mixed models to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity, fertility, and hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite from that hypothesized. The authors have done a very good job of addressing many of the reviewer's concerns, especially by adding two additional replicates.

Reviewer #1 (Public review):

In this study, Tiang et al. explore the role of ubiquitination of non-structural protein 16 (nsp16) in the SARS-CoV-2 life cycle. nsp16, in conjunction with nsp10, performs the final step of viral mRNA capping through its 2'-O-methylase activity. This modification allows the virus to evade host immune responses and protects its mRNA from degradation. The authors demonstrate that nsp16 undergoes ubiquitination and subsequent degradation by the host E3 ubiquitin ligases UBR5 and MARCHF7 via the ubiquitin-proteasome system (UPS). Specifically, UBR5 and MARCHF7 mediate nsp16 degradation through K48- and K27-linked ubiquitination, respectively. Notably, degradation of nsp16 by either UBR5 or MARCHF7 operates independently, with both mechanisms effectively inhibiting SARS-CoV-2 replication in vitro and in vivo. Furthermore, UBR5 and MARCHF7 exhibit broad-spectrum antiviral activity by targeting nsp16 variants from various SARS-CoV-2 strains. This research advances our understanding of how nsp16 ubiquitination impacts viral replication and highlights potential targets for developing broadly effective antiviral therapies.

Strengths:

The proposed study is of significant interest to the virology community because it aims to elucidate the biological role of ubiquitination in coronavirus proteins and its impact on the viral life cycle. Understanding these mechanisms will address broadly applicable questions about coronavirus biology and enhance our overall knowledge of ubiquitination's diverse functions in cell biology. Employing in vivo studies is a strength.

Weaknesses:

Minor comments:<br /> Figure 5A- The authors should ensure that the figure is properly labeled to clearly distinguish between the IP (Immunoprecipitation) panel and the input panel.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Comments on revisions:

I had gone through the revised form of the manuscript thoroughly. The authors have addressed all of my concerns. To me, the experimental approach looks convincing that the host E3 ubiquitin ligases (UBR5 and MARCHF7) ubiquitinate NSP16 and mark it for proteasomal degradation via K48- and K27- linkage. The authors have represented the final figure (Fig.8) in a convincing manner, opening a new window to explore the mechanism of capping the vRNA bu NSP16.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigated the effect of chronic activation of dopamine neurons using chemogenetics. Using Gq-DREADDs, the authors chronically activated midbrain dopamine neurons and observed that these neurons, particularly their axons, exhibit increased vulnerability and degeneration, resembling the pathological symptoms of Parkinson's disease. Baseline calcium levels in midbrain dopamine neurons were also significantly elevated following the chronic activation. Lastly, to identify cellular and circuit-level changes in response to dopaminergic neuronal degeneration caused by chronic activation, the authors employed spatial genomics (Visium) and revealed comprehensive changes in gene expression in the mouse model subjected to chronic activation. In conclusion, this study presents novel data on the consequences of chronic hyperactivation of midbrain dopamine neurons.

Strengths:

This study provides direct evidence that the chronic activation of dopamine neurons is toxic and gives rise to neurodegeneration. In addition, the authors achieved the chronic activation of dopamine neurons using water application of clozapine-N-oxide (CNO), a method not commonly employed by researchers. This approach may offer new insights into pathophysiological alterations of dopamine neurons in Parkinson's disease. The authors also utilized state-of-the-art spatial gene expression analysis, which can provide valuable information for other researchers studying dopamine neurons. They also presented a substantial number of intriguing ideas in their discussion, which are worth further investigation.

Weaknesses:

Although not fully supported by data, the authors provided a well-explained rationale and proposed possible mechanisms for dopamine neuron degeneration due to chronic activation in their results and discussion.

Comments on revised version:

The authors have adequately addressed most of my comments, and I have no further concerns.

Reviewer #2 (Public review):

Rademacher et al. present a paper showing that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important for two reasons: 1. This approach can be used as a mouse model for Parkinson's Disease without the need for the infusion of toxins (e.g. 6-OHDA or MPTP). This mouse model also has the advantage of showing a axon-first degeneration over an experimentally-useful time course (2-4 weeks). 2. The findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration, alters motor behavior, and alters mRNA expression is convincing. This is an exciting and important paper and will have an impact on the Parkinson's Disease field.

Strengths:

This is an exciting and important paper and will have an impact on the Parkinson's Disease field.

It presents a new highly useful mouse model of PD.

The paper compares mouse transcriptomics with human patient data.

It shows that selective degeneration can occur across the midbrain dopaminergic neurons even in the absence of a genetic, prion, or toxin neurodegeneration mechanism.

Weaknesses:

The authors have addressed all my concerns. This is an interesting, important, and carefully-controlled study.

Reviewer #3 (Public review):

Summary:

In this manuscript, Rademacher and colleagues examined the effect on the integrity of the dopamine system in mice of chronically stimulating dopamine neurons using a chemogenetic approach. They find that one to two weeks of constant exposure to the chemogenetic activator CNO leads to a decrease in the density of tyrosine hydroxylase staining in striatal brain sections and to a small reduction of the global population of tyrosine hydroxylase positive neurons in the ventral midbrain. They also report alterations in gene expression in both regions using a spatial transcriptomics approach. Globally, the work is well done and valuable and some of the conclusions are interesting. However, the conceptual advance is perhaps a bit limited in the sense that there is extensive previous work in the literature showing that excessive depolarization of multiple types of neurons associated with intracellular calcium elevations promotes neuronal degeneration. The present work adds to this by showing evidence of a similar phenomenon in dopamine neurons. In terms of the mechanisms explaining the neuronal loss observed after 2 to 4 weeks of chemogenetic activation, it would be important to consider that dopamine neurons are known from a lot of previous literature to undergo a decrease in firing through a depolarization-block mechanism when chronically depolarized. Is it possible that such a phenomenon explains much of the results observed in the present study? It would be important to consider this in the manuscript. The relevance to Parkinson's disease (PD) is also not totally clear because there is not a lot of previous solid evidence showing that the firing of dopamine neurons is increased in PD, either in human subjects or in mouse models of the disease.

Comments on revisions:

The authors have done a good job at revising the manuscript. The revised manuscript better frames the results in the context of previous literature.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigated the effect of chronic activation of dopamine neurons using chemogenetics. Using Gq-DREADDs, the authors chronically activated midbrain dopamine neurons and observed that these neurons, particularly their axons, exhibit increased vulnerability and degeneration, resembling the pathological symptoms of Parkinson's disease. Baseline calcium levels in midbrain dopamine neurons were also significantly elevated following the chronic activation. Lastly, to identify cellular and circuit-level changes in response to dopaminergic neuronal degeneration caused by chronic activation, the authors employed spatial genomics (Visium) and revealed comprehensive changes in gene expression in the mouse model subjected to chronic activation. In conclusion, this study presents novel data on the consequences of chronic hyperactivation of midbrain dopamine neurons.

Strengths:

This study provides direct evidence that the chronic activation of dopamine neurons is toxic and gives rise to neurodegeneration. In addition, the authors achieved the chronic activation of dopamine neurons using water application of clozapine-N-oxide (CNO), a method not commonly employed by researchers. This approach may offer new insights into pathophysiological alterations of dopamine neurons in Parkinson's disease. The authors also utilized state-of-the-art spatial gene expression analysis, which can provide valuable information for other researchers studying dopamine neurons. Although the authors did not elucidate the mechanisms underlying dopaminergic neuronal and axonal death, they presented a substantial number of intriguing ideas in their discussion, which are worth further investigation.

Weaknesses:

Many claims raised in this paper are only partially supported by the experimental results. So, additional data are necessary to strengthen the claims. The effects of chronic activation of dopamine neurons are intriguing; however, this paper does not go beyond reporting phenomena. It lacks a comprehensive explanation for the degeneration of dopamine neurons and their axons. While the authors proposed possible mechanisms for the degeneration in their discussion, such as differentially expressed genes, these remain experimentally unexplored.

Reviewer #2 (Public Review):<br /> <br /> Summary:

Rademacher et al. present a paper showing that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important. This mouse model also has the advantage of showing a axon-first degeneration over an experimentally-useful time course (2-4 weeks). 2. The findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration and alters mRNA expression is convincing, as the authors use both vehicle and CNO control groups, but the evidence that chronic dopaminergic activation alters circadian rhythm and motor behavior is incomplete as the authors did not run a CNO-control condition in these experiments.

Strengths:<br /> This is an exciting and important paper.<br /> The paper compares mouse transcriptomics with human patient data.<br /> It shows that selective degeneration can occur across the midbrain dopaminergic neurons even in the absence of a genetic, prion, or toxin neurodegeneration mechanism.

Weaknesses:

Major concerns:

(1) The lack of a CNO-positive, DREADD-negative control group in the behavioral experiments is the main limitation in interpreting the behavioral data. Without knowing whether CNO on its own has an impact on circadian rhythm or motor activity, the certainty that dopaminergic hyperactivity is causing these effects is lacking.

(2) One of the most exciting things about this paper is that the SNc degenerates more strongly than the VTA when both regions are, in theory, excited to the same extent. However, it is not perfectly clear that both regions respond to CNO to the same extent. The electrophysiological data showing CNO responsiveness is only conducted in the SNc. If the VTA response is significantly reduced vs the SNc response, then the selectivity of the SNc degeneration could just be because the SNc was more hyperactive than the VTA. Electrophysiology experiments comparing the VTA and SNc response to CNO could support the idea that the SNc has substantial intrinsic vulnerability factors compared to the VTA.

(3) The mice have access to a running wheel for the circadian rhythm experiments. Running has been shown to alter the dopaminergic system (Bastioli et al., 2022) and so the authors should clarify whether the histology, electrophysiology, fiber photometry, and transcriptomics data are conducted on mice that have been running or sedentary.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Rademacher and colleagues examined the effect on the integrity of the dopamine system in mice of chronically stimulating dopamine neurons using a chemogenetic approach. They find that one to two weeks of constant exposure to the chemogenetic activator CNO leads to a decrease in the density of tyrosine hydroxylase staining in striatal brain sections and to a small reduction of the global population of tyrosine hydroxylase positive neurons in the ventral midbrain. They also report alterations in gene expression in both regions using a spatial transcriptomics approach. Globally, the work is well done and valuable and some of the conclusions are interesting. However, the conceptual advance is perhaps a bit limited in the sense that there is extensive previous work in the literature showing that excessive depolarization of multiple types of neurons associated with intracellular calcium elevations promotes neuronal degeneration. The present work adds to this by showing evidence of a similar phenomenon in dopamine neurons. In terms of the mechanisms explaining the neuronal loss observed after 2 to 4 weeks of chemogenetic activation, it would be important to consider that dopamine neurons are known from a lot of previous literature to undergo a decrease in firing through a depolarization-block mechanism when chronically depolarized. Is it possible that such a phenomenon explains much of the results observed in the present study? It would be important to consider this in the manuscript. The relevance to Parkinson's disease (PD) is also not totally clear because there is not a lot of previous solid evidence showing that the firing of dopamine neurons is increased in PD, either in human subjects or in mouse models of the disease. As such, it is not clear if the present work is really modelling something that could happen in PD in humans.

Comments on the introduction:

The introduction cites a 1990 paper from the lab of Anthony Grace as support of the fact that DA neurons increase their firing rate in PD models. However, in this 1990 paper, the authors stated that: "With respect to DA cell activity, depletions of up to 96% of striatal DA did not result in substantial alterations in the proportion of DA neurons active, their mean firing rate, or their firing pattern. Increases in these parameters only occurred when striatal DA depletions exceeded 96%." Such results argue that an increase in firing rate is most likely to be a consequence of the almost complete loss of dopamine neurons rather than an initial driver of neuronal loss. The present introduction would thus benefit from being revised to clarify the overriding hypothesis and rationale in relation to PD and better represent the findings of the paper by Hollerman and Grace.

It would be good that the introduction refers to some of the literature on the links between excessive neuronal activity, calcium, and neurodegeneration. There is a large literature on this and referring to it would help frame the work and its novelty in a broader context.

Comments on the results section:

The running wheel results of Figure 1 suggest that the CNO treatment caused a brief increase in running on the first day after which there was a strong decrease during the subsequent days in the active phase. This observation is also in line with the appearance of a depolarization block.

The authors examined many basic electrophysiological parameters of recorded dopamine neurons in acute brain slices. However, it is surprising that they did not report the resting membrane potential, or the input resistance. It would be important that this be added because these two parameters provide key information on the basal excitability of the recorded neurons. They would also allow us to obtain insight into the possibility that the neurons are chronically depolarized and thus in depolarization block.

It is great that the authors quantified not only TH levels but also the levels of mCherry, co-expressed with the chemogenetic receptor. This could in principle help to distinguish between TH downregulation and true loss of dopamine neuron cell bodies. However, the approach used here has a major caveat in that the number of mCherry-positive dopamine neurons depends on the proportion of dopamine neurons that were infected and expressed the DREADD and this could very well vary between different mice. It is very unlikely that the virus injection allowed to infect 100% of the neurons in the VTA and SNc. This could for example explain in part the mismatch between the number of VTA dopamine neurons counted in panel 2G when comparing TH and mCherry counts. Also, I see that the mCherry counts were not provided at the 2-week time point. If the mCherry had been expressed genetically by crossing the DAT-Cre mice with a floxed fluorescent reported mice, the interpretation would have been simpler. In this context, I am not convinced of the benefit of the mCherry quantifications. The authors should consider either removing these results from the final manuscript or discussing this important limitation.

Although the authors conclude that there is a global decrease in the number of dopamine neurons after 4 weeks of CNO treatment, the post-hoc tests failed to confirm that the decrease in dopamine number was significant in the SNc, the region most relevant to Parkinson's. This could be due to the fact that only a small number of mice were tested. A "n" of just 4 or 5 mice is very small for a stereological counting experiment. As such, this experiment was clearly underpowered at the statistical level. Also, the choice of the image used to illustrate this in panel 2G should be reconsidered: the image suggests that a very large loss of dopamine neurons occurred in the SNc and this is not what the numbers show. A more representative image should be used.

In Figure 3, the authors attempt to compare intracellular calcium levels in dopamine neurons using GCaMP6 fluorescence. Because this calcium indicator is not quantitative (unlike ratiometric sensors such as Fura2), it is usually used to quantify relative changes in intracellular calcium. The present use of this probe to compare absolute values is unusual and the validity of this approach is unclear. This limitation needs to be discussed. The authors also need to refer in the text to the difference between panels D and E of this figure. It is surprising that the fluctuations in calcium levels were not quantified. I guess the hypothesis was that there should be more or larger fluctuations in the mice treated with CNO if the CNO treatment led to increased firing. This needs to be clarified.

Although the spatial transcriptomic results are intriguing and certainly a great way to start thinking about how the CNO treatment could lead to the loss of dopamine neurons, the presented results, the focussing of some broad classes of differentially expressed genes and on some specific examples, do not really suggest any clear mechanism of neurodegeneration. It would perhaps be useful for the authors to use the obtained data to validate that a state of chronic depolarization was indeed induced by the chronic CNO treatment. Were genes classically linked to increased activity like cfos or bdnf elevated in the SNc or VTA dopamine neurons? In the striatum, the authors report that the levels of DARP32, a gene whose levels are linked to dopamine levels, are unchanged. Does this mean that there were no major changes in dopamine levels in the striatum of these mice?

The usefulness of comparing the transcriptome of human PD SNc or VTA sections to that of the present mouse model should be better explained. In the human tissues, the transcriptome reflects the state of the tissue many years after extensive loss of dopamine neurons. It is expected that there will be few if any SNc neurons left in such sections. In comparison, the mice after 7 days of CNO treatment do not appear to have lost any dopamine neurons. As such, how can the two extremely different conditions be reasonably compared?

Comments on the discussion:

In the discussion, the authors state that their calcium photometry results support a central role of calcium in activity-induced neurodegeneration. This conclusion, although plausible because of the very broad pre-existing literature linking calcium elevation (such as in excitotoxicity) to neuronal loss, should be toned down a bit as no causal relationship was established in the experiments that were carried out in the present study.

In the discussion, the authors discuss some of the parallel changes in gene expression detected in the mouse model and in the human tissues. Because few if any dopamine neurons are expected to remain in the SNc of the human tissues used, this sort of comparison has important conceptual limitations and these need to be clearly addressed.

A major limitation of the present discussion is that it does not discuss the possibility that the observed phenotypes are caused by the induction of a chronic state of depolarization block by the chronic CNO treatment. I encourage the authors to consider and discuss this hypothesis. Also, the authors need to discuss the fact that previous work was only able to detect an increase in the firing rate of dopamine neurons after more than 95% loss of dopamine neurons. As such, the authors need to clearly discuss the relevance of the present model to PD. Are changes in firing rate a driver of neuronal loss in PD, as the authors try to make the case here, or are such changes only a secondary consequence of extensive neuronal loss (for example because a major loss of dopamine would lead to reduced D2 autoreceptor activation in the remaining neurons, and to reduced autoreceptor-mediated negative feedback on firing). This needs to be discussed.

There is a very large, multi-decade literature on calcium elevation and its effects on neuronal loss in many different types of neurons. The authors should discuss their findings in this context and refer to some of this previous work. In a nutshell, the observations of the present manuscript could be summarized by stating that the chronic membrane depolarization induced by the CNO treatment is likely to induce a chronic elevation of intracellular calcium and this is then likely to activate some of the well-known calcium-dependent cell death mechanisms. Whether such cell death is linked in any way to PD is not really demonstrated by the present results.

The authors are encouraged to perform a thorough revision of the discussion to address all of these issues, discuss the major limitations of the present model, and refer to the broad pre-existing literature linking membrane depolarization, calcium, and neuronal loss in many neuronal cell types.

Reviewer #2 (Public review):

The aim of the investigation was to find out more about the mechanism(s) by which the structural protein vimentin can facilitate the epithelial-mesenchymal transition in breast cancer cells.

The authors focused on a key amino acid of vimentin, C238, its role in the interaction between vimentin and actin microfilaments, and the downstream molecular and cellular consequences. They model the binding between vimentin and actin in silico to demonstrate the potential involvement of C238, due to its location in a rod domain known to bind beta-actin. The phenotype of a non-metastatic breast cancer cell line MCF7, which doesn't express vimentin, could be changed to a metastatic phenotype when mutant C238S vimentin, but not wild-type vimentin, was expressed in the cells. Expression of vimentin was confirmed at the level of mRNA, protein and microscopically. Patterns of expression of vimentin and actin reflected the distinct morphology of the two cell lines. Phenotypic changes were assessed through assay of cell adhesion, proliferation, migration and morphology and were consistent with greater metastatic potential in the C238S MCF7 cells. Changes in the transcriptome of MCF7 cells expressing wild-type and C238S vimentins were compared and expression of Xist long ncRNA was found to be the transcript most markedly increased in the metastatic cells expressing C238S vimentin. Moreover changes in expression of many other genes in the C238S cells are consistent with an epithelial mesenchymal transition. Tumourigenic potential of MCF7 cells carrying C238S but not wild-type, vimentin was confirmed by inoculation of cells into nude mice. This assay is a measure of stem-cell quality of the cells and not a measure of metastasis. It does demonstrate phenotypic changes that could be linked to metastasis.

shRNA was used to down-regulate vimentin or Xist in the MCF7 C238S cells. The description of the data is limited in parts and data sets require careful scrutiny to understand the full picture. Down-regulation of vimentin reversed the morphological changes to some degree, but down-regulation of Xist didn't. Conversely down-regulation of Xist inhibited cell growth, a sign of reversing metastatic potential, but down-regulation of vimentin had no effect on growth. Down-regulation of either did inhibit cell migration, another sign of metastatic reversal. Most of these findings are consistent with previous work based on ectopic expression of wild-type vimentin in MCF7 cells, but the mechanism of inhibition of cell migration by downregulation of Xist remains speculative. More complete knockdown of vimentin or Xist by CRISPR technology may be helpful.

Overall the study describes an intriguing model of metastasis that is worthy of further investigation, especially at the molecular level to unravel the connection between vimentin and metastasis. The identification of a potential role for Xist in metastasis, beyond its normal role in female cells to inactivate one of the X chromosomes, corroborates the work of others demonstrating increased levels in a variety of tumours in women and even in some tumours in men. It would be of great interest to see where in metastatic cells Xist is expressed and what it binds to.

Comments on revisions:

The revised manuscript incorporates changes in presentation of the data modelling interaction between the region of vimentin including C238 and F-actin. There is also inclusion of an extra citation supporting the role for Xist in cancer stem cell differentiation.

Reviewer #1 (Public review):

Summary:

Hua et al show how targeting amino acid metabolism can overcome Trastuzumab resistance in HER2+ breast cancer.

Strengths:

The authors used metabolomics, transcriptomics and epigenomics approaches in vitro and in preclinical models to demonstrate how trastuzumab resistant cells utilize cysteine metabolism.

Weaknesses:

However, there are some key aspects that needs to be addressed.

Major:

(1) Patient Samples for Transcriptomic Analysis: It is unclear from the text whether tumor tissues or blood samples were used for the transcriptomic analysis. This distinction is crucial, as these two sample types would yield vastly different inferences. The authors should clarify the source of these samples.

(2) The study only tested one trastuzumab-resistant and one trastuzumab-sensitive cell lines. It is unclear whether these findings are applicable to other HER2-positive tumor cell lines, such as HCC1954. The authors should validate their results in additional cell lines to strengthen their conclusions.

(3) Relevance to Metastatic Disease: Trastuzumab resistance often arises in patients during disease recurrence, which is frequently associated with metastasis. However, the mouse experiments described in this paper were conducted only in the primary tumors. This article will have more impact if the authors could demonstrate that the combination of Erastin or cysteine starvation with trastuzumab can also improve outcomes in metastasis models.

Minor:

(1) The figures lack information about the specific statistical tests used. Including this information is essential to show the robustness of the results.

(2) Figure 3K Interpretation: The significance asterisks in Figure 3K do not specify the comparison being made. Are they relative to the DMSO control? This should be clarified.

Comments on revisions:

While the authors acknowledge the limitation of using only a single trastuzumab resistant/sensitive pair, simply stating that additional cell lines will be tested in future work is simply inadequate. The biological heterogeneity of HER2-positive breast cancer demands validation in at least one independent resistant model (e.g., HCC1954 or BT 474R) alongside its parental counterpart. Without demonstrating that SLC7A11 upregulation, cysteine dependency, and sensitivity to Erastin plus trastuzumab extend beyond the original cell line pair, the generalizability and translational relevance of the findings remain uncertain. The authors need to perform and report key functional results (cell viability, apoptosis, and SLC7A11 expression) in an additional resistant and sensitive HER2-positive cell line before this manuscript can be considered robust.

Reviewer #2 (Public review):

In this manuscript, Hua et al. proposed SLC7A11, a protein facilitating cellular cystine uptake, as a potential target for the treatment of trastuzumab resistant HER2 positive breast cancer. If this claim holds true, the finding would be of significance and might be translated to clinical practice. Nevertheless, this reviewer finds that the conclusion was insufficiently supported by the data.

Notably, most of the data (Figures 2-6) were based on two cell lines - JIMT1 as a representative of trastuzumab resistant cell line, and SKBR3 as a representative of trastuzumab sensitive cell line. As such, these findings could be cell line specific while irrelevant to trastuzumab sensitivity at all. Furthermore, the authors' claim of ferroptosis induction is primarily based on lipid peroxidation assays (Figure 3). The rescuing effects of ferroptosis inhibitors on cell viability were missing. The xenograft experiments were also suspicious (Figure 4). Systemic cysteine starvation is known to cause adverse effects, including liver necrosis, and the compound (i.e., erastin) used by the authors is not suitable for in vivo experiments due to low solubility and low metabolic stability. Finally, the authors focus on epigenetic regulations (Figures 5 & 6) without first investigating well-established transcription factors, such as NRF2 and ATF4, which are known to regulate SLC7A11.

To sum up, this reviewer finds that the most valuable data in this manuscript is perhaps Figure 1, which provides unbiased information concerning the metabolic patterns in trastuzumab sensitive and primary resistant HER2 positive breast cancer patients.

Comments on revisions:

(1) Figure 3: The unit of concentration should be "μM". "μm" means micrometer.

(2) Figure S5: Ferroptosis inhibitors should be used in cell viability assays to exclude the off-target effect of RSL3 and erastin. Note that erastin also targets VDAC, while RSL3 may inhibit other selenoproteins at high concentrations. Cell viability assays are critical for demonstrating ferroptosis and should be included in the main figure rather than relegated to the supplemental materials.

(3) Figure 4B & 4C: the data of "H" group and "Erastin" group are inconsistent. In panel B, the tumor size in the "H" group appears smaller than in the "Erastin" group, while in panel C, the opposite trend is observed.

(4) The catalog numbers for the cystine/cysteine-deficient DMEM (from BIOTREE) and diet (from Xietong Bio) should be provided. This information is essential for readers to identify and verify the specific products used in the study.

Reviewer #1 (Public review):

Summary:

This study provides new insight into the non-canonical voltage-gating mechanism of BK channels through prolonged (10 μs) MD simulations of the Slo1 transmembrane domain conformation and K+ conduction in response to high imposed voltages (300, 750 mV). The results support previous conclusions based on functional and structural data and MD simulations that the voltage-sensor domain (VSD) of Slo1 undergoes limited conformational changes compared to Kv channels, and predicts gating charge movement comparable in magnitude to experimental results. The gating charge calculations further indicate that R213 and R210 in S4 are the main contributors owing to their large side chain movements and the presence of a locally focused electric field, consistent with recent experimental and MD simulation results by Carrasquel-Ursulaez et al.,2022. Most interestingly, changes in pore conformation and K+ conduction driven by VSD activation are resolved, providing information regarding changes in VSD/pore interaction through S4/S5/S6 segments proposed to underly electromechanical coupling.

Strengths:

Include that the prolonged timescale and high voltage of the simulation allow apparent equilibration in the voltage-sensor domain (VSD) conformational changes and at least partial opening of the pore. The study extends the results of previous MD simulations of VSD activation by providing quantitative estimates of gating charge movement, showing how the electric field distribution across the VSD is altered in resting and activated states, and testing the hypothesis that R213 and R210 are the primary gating charges by steered MD simulations. The ability to estimate gating charge contributions of individual residues in the WT channel is useful as a comparison to experimental studies based on mutagenesis which have yielded conflicting results that could reflect perturbations in structure. Use of dynamic community analysis to identify coupling pathways and information flow for VSD-pore (electromechanical) coupling, as well as analysis of state-dependent S4/S5/S6 interactions that could mediate coupling, provides useful predictions extending beyond what has been experimentally tested.

Weaknesses:

Include that a truncated channel (lacking the C-terminal gating ring) was used for simulations, which is known to have reduced single channel conductance and reduced electromechanical coupling compared to the full-length channel. In addition, as VSD activation in BK channels is much faster than opening, the timescale of simulations was likely insufficient to achieve a fully open state, as supported by differences in the degree of pore expansion in replicate simulations, which are also smaller than observed in Ca-bound open structures of the full-length channel. Taken together, these limitations suggest that the analysis regarding coupling pathways and interactions is incomplete. In addition, while the simulations convincingly demonstrate voltage-dependent channel opening as evidenced by pore expansion, and conduction of K+ and water through the pore, single channel conductance is underestimated by at least an order of magnitude, as in previous studies of other K+ channels. These quantitative discrepancies suggest that MD simulations may not yet be sufficiently advanced to provide insight into mechanisms underlying the extraordinarily large conductance of BK channels.

Reviewer #2 (Public review):

Summary:

This manuscript addresses the structural basis of voltage-activation of BK channels using computational approaches. Although a number of experimental studies using gating current and patch-clamp recording have analyzed voltage-activation in terms of observed charge movements and the apparent energetic coupling between voltage-sensor movement and channel opening, the structural changes that underlie this phenomenon have been unclear. The present studies use a reduced molecular system comprising the transmembrane portion of the BK channel (i.e., the cytosolic domain was deleted), embedded in a POPC membrane, with either 0 or 750 mV applied across the membrane. This system enabled acquisition of long simulations of 10 microseconds, to permit tracking of conformational changes of the channel. The authors' principal findings were that the side chains of R210 and R213 rapidly moved toward the extracellular side of the membrane (by 8 - 10 Å), with greater displacements than any of the other charged transmembrane residues. These movements appeared tightly coupled to the movement of the pore-lining helix, pore hydration, and ion permeation. The authors estimate that R210 and R213 contribute 0.25 and 0.19 elementary charges per residue to the gating current, which is roughly consistent with estimates based on electrophysiological measurements that used the full-length channel.

Strengths:

The methodologies used in this work are sound, and these studies certainly contribute to our understanding of voltage-gating of BK channels. An intriguing observation is the strongly coupled movement of the S4, S5, and S6 helices that appear to underlie voltage-dependent opening. Based on Figures 2a-d, the substantial movements of the R210 and R213 side chains occur nearly simultaneously to the S6 movement (between 4 - 5 usec of simulation time). This seems to provide support for a "helix-packing" mechanism of voltage gating in the so-called "non-domain-swapped" voltage-gated K channels.

Weaknesses:

The main limitation is that these studies used a truncated version of the BK channel, and there are likely to be differences in VSD-pore coupling in the context of the full-length channels that will not be resolved in the present work. Nonetheless, the authors provide a strong rationale for their use of the truncated channel, and the results presented will provide a good starting point for future computational studies of this channel.

Reviewer #1 (Public review):

In this work, Ligneul and coauthors implemented diffusion-weighted MRS in young rats to follow longitudinally and in vivo the microstructural changes occurring during brain development. Diffusion-weighted MRS is here instrumental in assessing microstructure in a cell-specific manner, as opposed to the claimed gold-standard (manganese-enhanced MRI) that can only probe changes in brain volume. Differential microstructure and complexification of the cerebellum and the thalamus during rat brain development were observed non-invasively. In particular, lower metabolite ADC with increasing age were measured in both brain regions, reflecting increasing cellular restriction with brain maturation. Higher sphere (representing cell bodies) fraction for neuronal metabolites (total NAA, glutamate) and total creatine and taurine in the cerebellum compared to the thalamus were estimated, reflecting the unique structure of the cerebellar granular layer with a high density of cell bodies. Decreasing sphere fraction with age was observed in the cerebellum, reflecting the development of the dendritic tree of Purkinje cells and Bergmann glia. From morphometric analyses, the authors could probe non-monotonic branching evolution in the cerebellum, matching 3D representations of Purkinje cells expansion and complexification with age. Finally, the authors highlighted taurine as a potential new marker of cerebellar development.

From a technical standpoint, this work clearly demonstrates the potential of diffusion-weighted MRS at probing microstructure changes of the developing brain non-invasively, paving the way for its application in pathological cases. Ligneul and coauthors also show that diffusion-weighted MRS acquisitions in neonates are feasible, despite the known technical challenges of such measurements, even in adult rats. They also provide all necessary resources to reproduce and build upon their work, which is highly valuable for the community.

From a biological standpoint, claims are well supported by the microstructure parameters derived from advanced biophysical modelling of the diffusion MRS data.

Specific strengths:

(1) The interpretation of dMRS data in terms of cell-specific microstructure through advanced biophysical modelling (e.g. the sphere fraction, modelling the fraction of cell bodies versus neuronal or astrocytic processes) is a strong asset of the study, going beyond the more commonly used signal representation metrics such as the apparent diffusion coefficient, which lacks specificity to biological phenomena.<br /> (2) The fairly good data quality despite the complexity of the experimental framework should be praised: diffusion-weighted MRS was acquired in two brain regions (although not in the same animals) and longitudinally, in neonates, including data at high b-values and multiple diffusion times, which altogether constitutes a large-scale dataset of high value for the diffusion-weighted MRS community.<br /> (3) The authors have shared publicly data and codes used for processing and fitting, which will allow one to reproduce or extend the scope of this work to disease populations, and which goes in line with the current effort of the MR(S) community for data sharing.

Specific weaknesses:

Ligneul and coauthors have convincingly addressed and included my comments in their revised manuscript.

I believe the following conceptual concerns, which are inherent to the nature of the study and do not require further adjustments of the manuscript, remain:

(1) Metabolite compartmentation in one cell type or the other has often been challenged and is currently impossible to validate in vivo. Here, Ligneul and coauthors did not use this assumption a priori and supported their claims also with non-MR literature (eg. for Taurine), but the interpretation of results in that direction should be made with care.

(2) Longitudinal MR studies of the developing brain make it difficult to extract parameters with an "absolute" meaning. Indirect assumptions used to derive such parameters may change with age and become confounding factors (brain structure, cell distribution, concentrations normalizing metabolites (here macromolecules), relaxation times...). While findings of the manuscript are convincing and supported with literature, the true underlying nature of such changes might be difficult to access.

(3) Diffusion MRI in addition to diffusion MRS would have been complementary and beneficial to validate some of the signal contributions, but was unfeasible in the time constraints of experiments on young animals.

Reviewer #2 (Public review):

This second revision has partially addressed criticisms previously raised; however, substantial inadequacies, particularly concerning rigorous validation and model justification, remain unresolved. While recognizing evident strength, novelty, and technical complexity of this work, the authors have yet to fully resolve key major concerns explicitly pointed out during revision in a satisfactory manner. As currently written, the manuscript does not yet provide sufficiently robust validation, methodological rigour, or clarity required for complete acceptance in a top-tier scientific journal.

Summary of Authors' Aim:

In this revised version, the authors aimed to address prior reviewer critiques harshly pinpointing the need for greater clarity in the manuscript's logical flow, rigorous external validation, clearer explanation of methodological normalization choices, and deeper elaboration of diffusion MRI method relevance and potential translation. The authors present a diffusion-weighted MRS approach paired with complex biophysical modelling to elucidate differential developmental trajectories of cellular structures in cerebellum and thalamus in rat neonates, providing a novel, non-invasive avenue for monitoring cellular microstructure.

Major Comments:

Rigorous Validation (Reviewer #1 - point R1.1, Reviewer #2 - point R2.2):

The major concern previously raised and reiterated here is the insufficient external cross-validation of the dMRS-derived interpretations about cellular changes, including the particularly speculative interpretation that taurine undergoes compartment switching between neuronal and glial compartments in the thalamus. The authors acknowledge this important shortcoming (R1.1, R2.2) but attempt to mitigate these concerns merely through additional contextual comparisons from existing literature (page 23, lines 877-878, Figure S11, Table S2). While better contextualization is welcome, the modified manuscript still falls notably short of the level of rigour necessary to validate such striking switches in compartmentalization. To justify claims of metabolites changing cellular compartments, explicit verification against independent molecular/histological data, ideally with additional immunohistochemical staining for cellular markers (e.g., glial fibrillary acidic protein, NeuN), is necessary. The mere presence of literature correlations (such as the reported visual comparisons to morphometric reconstructions, page 24, lines 883-884) does not constitute rigorous validation at the required standard for high-impact publication. The revised manuscript remains fundamentally weakened without such validation. To properly improve, the authors must consider incorporating independent ex vivo experiments or, if this is no longer feasible, extensively temper their compartment-switching claims, acknowledging explicitly and prominently the speculative nature of current interpretations.

Normalization of Metabolite Concentrations (Reviewer #1 - point R1.3):

The authors clearly responded to a reviewer wish for justification of metabolite normalisation to macromolecular concentrations (page 13, lines 493-503, Figure S2). However, the rationale provided remains only partially convincing. While the authors appropriately acknowledge the unusual nature of their methodological choice and possible confounding factors, they opt to supplement rather than substitute this approach with a more standard method (normalisation by water) in the main body of the manuscript. The additional supplementary Figure S2 is helpful, yet the conclusions derived with macromolecular normalization still remain potentially confounded by age-dependent macromolecular changes (Tkac et al., 2003). The justification given in the revised manuscript remains vague, unsatisfactory, and somewhat contradictory-authors accept macromolecules changes likely with age, yet largely overlook this effect. At least, the comparison between normalization by macromolecules and water should be explicitly discussed in the main text, and conclusions drawn from macromolecular normalization must be cautiously framed.

Choice and Justification of Biophysical Model (Reviewer #1 - point R1.4):

The reviewers questioned model assumptions, particularly ignoring macroscopic anisotropy effects due to white matter presence, myelination, and fibre orientation dispersion in the cerebellar voxel. Authors provided newly included DTI data and acknowledged this limitation explicitly (R1.4, Figure S8, page 25, lines 921-924). However, the addition of these poor-quality DTI data with limited interpretability paradoxically weakens rather than strengthens the manuscript as a whole, since the authors now present unclear supplementary results with little additional interpretative value. Recognizing poor data quality in this scenario, although intellectually honest, does not substantially increase the current robustness of their chosen model nor improve justification. To address this fully, either higher-quality data should be collected to robustly probe anisotropy or fibre dispersion effects, or the authors must much further restrict their interpretations in view of this clear limitation. Currently, the solution proposed is incomplete and insufficient to clarify the consequences of their chosen model.

Logical Flow and Clarity (Reviewer #2 - points R2.1 and R2.3):

The authors attempted to respond to reviewer comments on logical flow and accessibility (page 3, introduction restructuring). While the manuscript readability has improved, the introduction and discussion remain overly intricate, and at times, detail-oriented without clear links into central claims. In particular, the biological rationale for choosing the specific metabolite markers (especially tCho, Ins, Tau, etc.) and their known relevance must be further streamlined and simplified to increase accessibility and directness. Although some helpful restructuring was carried out, further careful paragraph-level revision for logical flow and readability remains necessary.

Translation to Human Studies (Reviewer #2 - point R2.4):

The authors have extended contextual discussion on translational potential regarding taurine as a developmental marker in humans (pages 24-25, lines 906-917). However, mention remains vague and cursory, without presenting sufficiently solid arguments nor drawing from human developmental studies adequately. Translational potential must be assessed within the realistic limitations inherent in clinical translation of MRS studies, particularly given the technical complexities clearly identified even in preclinical studies of this paper. Discussion remains relatively superficial, and if retained, must be expanded to fully discuss realistic human translational hurdles and requirements.

Reviewer #1 (Public review):

Summary:

This study by Torok et al. takes a creative approach to studying circuit perturbations in a sensorimotor region for vocalization control, in a songbird species, the zebra finch. By expressing the light chain of tetanus toxin in neurons in a sensorimotor region HVC, the authors constrain neural firing and study the resulting degradation and then recovery of song, after a protracted (> 70-day) period. Recording data suggest a form of synaptic homeostasis emergent in both HVC and RA as a result of the profound loss of (inhibitory?) tone in HVC. The methods to analyze changes in song are particularly strong here, using dimension reduction and visualization techniques. Single-cell sequencing data showed accompanying changes in microglia abundance, as well as several other markers that were not observed in control viral injections. LFP analyses in birds during the tetanus onset phase showed clear dysregulation of typical voltage deflections and spectral power, each of which showed recovery in parallel with song recovery. Lastly, the authors present data indicating that the anterior forebrain region LMAN is not critical for the song degradation process, pointing instead to the direct relationship between HVC and RA in song plasticity in adults. The methods are generally well established, but my main concerns regard the validation of the viral construct, the lack of direct confirmation of tetanus toxin on inhibitory neurons or E/I balance in HVC, and a missed opportunity to look at song syllable sequence degradation and recovery.

Strengths:

The species under investigation is the premier model for the neural basis of vocal learning, and the telencephalic brain regions investigated are well mapped out for their control of vocal learning behavior. The methods for electrophysiology recording and analysis, song analysis, scRNAseq, and in situ hybridization pose no concern as they are well established for this group of co-authors.

Weaknesses:

The introduction lays out a case for pursuing long-term E/I imbalances, vis-à-vis transient perturbations that have shown effects on the behavior. However, the rationale is not clearly stated. Why should the reader care that "prolonged E/I imbalances" may occur? Do they occur naturally or in some disease states (as alluded to in the first paragraph)? Without this rationale, the reader is left with an impression that the experiments were done because of a technical capability rather than a conceptual thrust.

The cited works for the statement the "AAV viral vector expressing TeNT undre the human dlx promoter, which is selective for HVC inhibitory interneurons" (reference 5 Kosche et al., 2016; and reference 10 Vallentin et al 2016) do not substantiate the targeting of this dlx5 promoter for interneurons in zebra finch HVC. Neither of these cited studies used viral vectors, and so this is a misattribution of the dlx5 promoter as targeting HVC inhibitory interneurons. However, the original development of this enhancer by Gord Fishell and others did have solid expression in HVC (Dimidschstein et al., 2016, Nature Neuroscience), and the enhancer was used to successfully target inhibitory neurons in nearby nidopallium NCM (Spool et al., 2022, Curr Biol). Citing these two studies would improve the standing of this viral approach. Nevertheless, the specific construct used here is not the same as the published studies mentioned above (AAV9-dlx-TeNT). The authors therefore need to show expression of the virus using some histological confirmation to cement the idea that they are indeed targeting inhibitory interneurons with this manipulation. The methods statement "a single injection (~100 nL) in the center of HVC was sufficient to label enough cells" is not convincing in the absence of quantified photomicrographs.

The authors present no physiological confirmation of TeNT on E/I balance directly, and so we don't have a clear picture of how/whether HVC interneurons are physiologically altered by this manipulation. That said, the Npix recordings show that there was a tremendous increase in gamma power following TeNT manipulation, which subsides as the protracted song recovery unfolds. This finding is somewhat counterintuitive, given that gamma oscillations are typically driven by inhibitory neurons in many systems (including songbird pallium) while the TeNT manipulation is purported to cause *reductions* in inhibitory neurotransmitter release within HVC. Some interpretation of these incongruent results would be useful in the Discussion.

The degradation and recovery of song is based mainly on the measures of duration of syllables and inter-syllable intervals, but HVC is also a key locus for song syllable sequence coding. The supplementary figures show some changes in sequences. It would improve the interpretation of both the degradation and recovery of the song to know whether syllable sequences (iiiABCCDDEF) truly recovered or were morphed in some way (e.g., iiiCDDDBEF). The PCA analyses (that the authors conducted) for these two potential outcomes would likely be very similar, but the actual songs would differ greatly under these two scenarios in terms of syllable sequence. From the representative spectrograms, it appears that the song syllable sequence does indeed recover well in these examples (perhaps less so in Supplementary Figure 3). A simple Markov-chain analysis of the syllable sequences across birds in the study would provide important confirmation of these insights.

Reviewer #2 (Public review):

This article addresses the question of how complex behavior is maintained despite perturbations in underlying motor circuits. Using zebra finch song production as a model system, the authors employ a genetic approach to perturb activity in GABAergic neurons within the vocal control nucleus HVC. Specifically, they use AAV to deliver the tetanus toxin light chain (TeNT) under the interneuron-specific DLX promoter, with the goal of silencing interneurons. This manipulation causes rapid degradation of song, followed by recovery over several weeks.

The authors characterize the recovery using a combination of transcriptomic analysis, electrophysiology, and lesion studies. Notably, the recovery does not require the lMAN, which is typically considered critical for vocal learning and plasticity. The authors speculate that homeostatic mechanisms within the motor pathway - potentially involving microglial remodeling -may mediate this recovery.

The strength of the study lies in the striking behavioral effects - both degradation and recovery - resulting from a specific circuit perturbation, and the use of complementary approaches (gene expression, neurophysiology, behavior, and lesions) to link circuit changes to behavior. The approach is creative, and the findings are intriguing. More detailed comments are provided below that may help enhance the manuscript's value to the community.

(1) In Figure 1b, the authors show changes in the relative abundance of cell types following TeNT expression in HVC. The most prominent change, as noted by the authors, is an increase in microglia. However, there are also apparent changes in the proportions of other cell types-particularly decreases in neurons and radial glia. How do the authors interpret the observed reductions in GABAergic and glutamatergic cells, as well as radial glia? Are these decreases statistically significant? Given the magnitude of these changes, could they reflect sampling differences (e.g., inclusion of tissue outside HVC) or neuronal cell death? Alternatively, is it possible that the absolute number of mature neurons remains constant, and increases in other cell types shift the relative proportions? The authors should clarify how to interpret the Y-axis of this plot. It appears to reflect relative abundance rather than absolute cell numbers, which has important implications for interpretation.

(2) The authors appear to define their own cell type clusters and labels, rather than using standard classifications (e.g., Colquitt et al. 2021; Colquitt et al. 2023). This makes cross-study comparisons difficult. For example, Colquitt describes four classes of putative immature neurons (pre2-pre4, GABA-pre). In contrast, the authors refer to "neuroblasts" in Figure 1b. Are these equivalent to pre2-pre4 and/or to "GABA-pre"? What about "migrating neuroblasts" in Supplementary Figure 11? The authors could consider using the standard nomenclature, or if they disagree with that classification, explain why an alternative scheme is warranted.

(3) The transcriptomic data are underexplored. Many genes appear differentially expressed (e.g., in Figure 1c), however, the main text contains little discussion of differential gene expression beyond MHC I and B2M. It would be useful to discuss whether transcriptomic data support or rule out any other specific mechanistic hypotheses for recovery.

(4) The authors attribute increased microglial markers to interneuron silencing rather than inflammation from viral injection, based on control virus results (lines 143-146). However, is it plausible that TeNT expression itself, or batch variability, could drive differences in inflammation? The authors could address these alternatives with additional evidence or discussion.

Reviewer #3 (Public review):

Summary:

This manuscript investigates at behavioral and mechanistic levels the recovery of zebra finch song production after a genetically targeted insult to HVC, a vocal premotor nucleus known to generate stereotyped neural sequences that drive the correspondingly stereotyped song. This study is a close follow up to past work, published in Nature Neuroscience last year (Wang et al, 2024), in which custom lentiviruses were used to deliver a persistently active sodium channel, NacBAC or TeNT to block synaptic release, specifically to the excitatory projection neurons in HVC. In this past work, these manipulations resulted in rapid degradation of song, followed by a slow recovery that, remarkably, did not require practice. Song recovery was associated with synaptic remodeling that appeared to homeostatically bring the affected neurons back to a normal firing regime. This past paper was important because it clearly demonstrated behaviorally and mechanistically how neural plasticity can restore a learned behavior without practice, showing that dominant reinforcement learning models of birdsong are not the full story.

This past work sets the context for the current paper, which instead targets the inhibitory neuronal population in HVC for silencing via viral-mediated expression of TeNT. Again, this sophisticated targeting of HVC interneurons resulted in rapid degradation of song, followed by a much slower but seemingly full recovery.

Strengths:

Overall, this paper has several strengths. First, it provides yet another convincing example of non-canonical vocal learning in the zebra finch because LMAN (a nucleus required for trial and error song learning) is not required for song recovery. Second, its targeting of interneurons clarifies the extent to which inhibition in HVC is essential for vocal patterning (not surprising but important to show). Third, by using RNAseq of HVC at the time of peak song disruption, it zeroes in on specific genetic/cellular activations associated with a lack of inhibition (e.g., microglial activation and MHC1 expression), opening up new avenues for future study. Using in vivo electrophysiology it also characterizes some gross circuit-level abnormalities in HVC-RA transmission and during sleep.

Weaknesses:

Yet the paper also has several areas for improvement, primarily:

Main issues

(1) Narrative-level confusion, a mix of results, many hanging threads

The arc of this paper is very hard to follow, new experiments arise without a clear setup or connection to past ones. Concepts jump around unpredictably. The reading experience would be dramatically improved if there were a clear single line of logic going through the entire paper, which could be accomplished by inserting a paragraph at the end of the intro section that walks the reader step-by-step through what they are going to see. I don't recommend this for all papers - but this paper requires it, in my opinion, because we have such an unusual combination of experimental approaches, outcomes, and data formats (behavior, RNA seq, targeted tests of microglial activation in the setting of adult impairment and song development, electrophysiology during sleep. It's very difficult for me to tie this all together into a crisp narrative that sticks with me days after reading the paper. Instead, it feels like some disconnected factoids. Examples:<br /> a) Characterization of degradation and slow recovery (much slower than targeting of projection neurons form past work (Wang et al, 2024).<br /> b) Activation of microglia and MHC1 during the degraded period; microglia return to normal at recovery.<br /> c) Developmenta profile of microglia expression.<br /> e) Sleep replay in HVC is perturbed during the degraded state. Mostly returns to normal following recovery, but *some* aspects are still abnormal.<br /> f) Detailed ephys analysis of HVC excitability and RA suppression, invoking ideas that HVC drives RA inhibition.<br /> g) LMAN lesions do not block degradation or recovery.

There are at least three threads of this paper - it therefore reads like three different papers stitched together into one - united only by the method of HVC interneuron targeting. In my view, a pretty major overhaul is required, even if it means cutting out specific details and figures that distract from the paper's message (for example there is a whole sub-section analyzing HVC impact on RA that vaguely invokes ideas of HVC engagement of RA

(2) Interpretation of microglia is confusing and unresolved

Microglia activation is measured at peak song disruption, and returns to normal following recovery. To test if this phenomenon is associated with learning or degradation, the authors measure microglia during development.

"The increased inhibitory tone in HVC and the number of microglia could induce synaptic changes that contribute to degraded song production. Alternatively, the rise in microglia could be part of the recovery response to produce synaptic changes needed to regain the song following perturbation."

This is a great if/then statement on how to interpret the microglial activation at the core of the paper. But it remains unresolved. Is there a causal experiment that could distinguish these possibilities?

(3) The quantification of song dynamics during the recovery process in LMAN lesioned birds is required to support claims. Perhaps the most interesting claim of the paper - that recovery happens without LMAN, is not sufficiently supported by data analyses. This is a major problem.

The same analysis used in the LMAN-intact degradation/recovery dataset should be used for the LMAN dataset. At present, there are no quantification, only example spectrograms. Also, Supplementary Figure 4 and Supplementary Figure 5 are identical, suggesting a lack of proofreading in this part of the manuscript. For example the reader cannot even ascertain if the key aspect of song degradation - the production of exceedingly long syllables - is occurring in the LMAN lesioned animals.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors Eapen, et al. investigated the peptide inhibitors of Cdc20. They applied a rational design approach, substituting residues found in the D-box consensus sequences to better align the peptides with the Cdc20-degron interface. In the process, the authors designed and tested a series of more potent binders, including ones that contain unnatural amino acids, and verified binding modes by elucidating the Cdc-20-peptide structures. The authors further showed that these peptides can engage with Cdc20 in the cellular context, and can inhibit APC/CCdc20 ubiquitination activity. Finally, the authors demonstrated that these peptides could be used as portable degron motifs that drive the degradation of a fused fluorescent protein.

Strengths:

This manuscript is clear and straightforward to follow. The investigation of different peptide variations was comprehensive and well-executed. This work provided the groundwork for the development of peptide drug modalities to inhibit degradation or applying peptides as portable motifs to achieve targeted degradation. Both of which are impactful. The additional points provided by the authors in response to reviewers further strengthened the manuscript and enhanced its clarity.

Weaknesses:

None, the authors have addressed all my comments, and I have no additional suggestions.

Reviewer #3 (Public review):

Summary:

Eapen and coworkers use a rational design approach to generate new peptide-inspired ligands at the D-box interface of cdc20. These new peptides serve as new starting points for blocking APC/C in the context of cancer, as well as manipulating APC/C for targeted protein degradation therapeutic approaches.

Strengths:

The characterization of new peptide-like ligands is generally solid and multifaceted, including binding assays, thermal stability enhancement in vitro and in cells, X-ray crystallography, and degradation assays.

Comments on revisions:

I am satisfied with the changes in response to the first round of review.

Reviewer #1 (Public review):

Summary:

The study dissects distinct pools of diacylglycerol (DAG), continuing a line of research on the central concept that there is a major lipid metabolism DAG pool in cells, but also a smaller signaling DAG pool. It tests the hypothesis that the second pool is regulated by Dip2, which influences Pkc1 signaling. The group shows that stressed yeast increase specific DAG species C36:0 and 36:1, and propose this promotes Pkc1 activation via Pck1 binding 36:0. The study also examines how perturbing the lipid metabolism DAG pool via various deletions such as lro1, dga1, and pah1 deletion impacts DAG and stress signaling. Overall this is an interesting study that adds new data to how different DAG pools influence cellular signaling.

Strengths:

The study nicely combined lipidomic profiling with stress signaling biochemistry and yeast growth assays.

Weaknesses:

One suggestion to improve the study is to examine the spatial organization of Dip2 within cells, and how this impacts its ability to modulate DAG pools. Dip2 has previously been proposed to function at mitochondria-vacuole contacts (Mondal 2022). Examining how Dip2 localization is impacted when different DAG pools are manipulated such as by deletion Pah1 (also suggested to work at yeast contact sites such as the nucleus-vacuole junction), or with Lro1 or Dga1 deletion would broaden the scope of the study.

Comments on revisions:

The revision addresses several of the concerns raised previously. Most importantly, it softens several conclusions that more clearly delineates limitations of the study. The study has yet to address how Dip2 and Pkc1 crosstalk, but new text addresses this limitation. There is also more analysis of Dip2 localization in other conditions where cell DAG pools are elevated (ie a LRO1 and DGA1 double KO, as well as PAH1 KO). Loss of these proteins elevates ER DAG, but Dip2 remains mitochondrially associated. This may imply DAG specificity, or that changes to DAG pools globally does not impact Dip2 import into mitochondria.

Reviewer #2 (Public review):

Summary:

The authors use yeast genetics, lipidomic and biochemical approaches to demonstrate the DAG isoforms (36:0 and 36:1) can specifically activate PKC. Further, these DAG isoforms originate from PI and PI(4,5)P2. The authors propose that the Psi1-Plc1-Dip2 functions to maintain a normal level of specific DAG species to modulate PKC signalling.

Strengths:

Data from yeast genetics are clear and strong. The concept is potentially interesting and novel.

Weaknesses: More evidence is needed to support the central hypothesis. The authors may consider the following:

(1) Figure 2: the authors should show/examine C36:1 DAG. Also, some structural evidence would be highly useful here. What is the structural basis for the assertion that the PKC C1 domain can only be activated by C36:0/1 DAG but not other DAGs? This is a critical conclusion of this work and clear evidence is needed.

(2) Does Dip2 colocalize with Plc1 or Pkc1? Does Dip2 reach the plasma membrane upon Plc activation?

Comments on revisions:

The authors have addressed my concerns.

Reviewer #1 (Public review):

Summary:

This manuscript addresses the challenge of understanding and capturing the similarity among large numbers of visual images. The authors show that an automated approach using artificial neural networks that focuses upon the embedding of similarity through behaviorally relevant dimensions can predict human similarity data up to a certain level of granularity.

Strengths:

The manuscript starts with a very useful introduction that sets the stage with an insightful Figure 1. The methods are state of the art and well thought off, and the data are compelling. The authors demonstrate the added value of their approach in several directions, resulting in a manuscript that is highly relevant for different domains. The authors also explore its limitations (e.g., granularity).

Weaknesses:

Although this manuscript and the work it describes are already of high quality, I see several ways in which it could be further improved. Below I rank these suggestions tentatively in order of importance.

Predictions obtain correlations above 0.80, often close to correlations of 0.90. The performance of DimPred is not trivial, given how much better it performs relative to classic RSA and feature reweighting. Yet, the ceiling is not sufficiently characterized. What is the noise ceiling in the main and additional similarity sets that are used? If the noise ceiling is higher than the prediction correlations, then can the authors try to find the stimulus pairs for which the approach systematically fails to capture similarity? Or is the mismatch very distributed across the full stimulus set?

Also in the section on p. 8-p.9, it is crucial to provide information on the noise ceiling of the various datasets.

This consideration of noise ceiling brings me to another consideration. Arguments have been made that a focus on overall prediction accuracy might mask important differences in underlying processes that can be demonstrated in more specific, experimental situations (Bowers et al., 2023). Can the authors exclude the possibility that their automatic approach would fail dramatically in specifically engineered situations? Some examples can be found in the 2024 challenge of the BrainScore platform. How can future users of this approach know whether they are in such a situation or not?

The authors demonstrated one limitation of the DimPred approach to capture fine-grained similarity among highly similar stimuli. The implications of this finding were not clear to me from the Abstract etc, because it is not sufficiently highlighted in the summaries that in this case DimPred performs even worse, and much worse, than more simple approaches like feature reweighting and even than classic RSA. I would discuss this outcome more in detail. With hindsight, this problem might not be so surprising given that DimPred relies upon the embedding with a few tens dimensions that mostly capture between-category differences. To me, this seems like a more fundamental limitation than a mere problem of granularity or lack of data, as suggested in the abstract.

The DimPred approach is based on the dimensions of a similarity embedding derived from human behavior. What is important here is (i) that DimPred is based upon an approach that tries to capture latent dimensions; or (ii) that these dimensions are behaviorally relevant? There are a lot of dimension-focused approaches. Generic ones are PCA, MDS, etc. More domain-specific approaches in cogneuro include the following: (i) for two-dimensional shape representations, good results have been obtained with image-computable dimensions of various levels of complexity (Morgenstern et al., 2021, PLOS Comput. Biol.); (ii) another dimension-focused approach has focused upon identifying dimensions that are universal across networks & human representations (Chen & Bonner, 2024, arXiv). Would such generic or more specific approaches work as well as DimPred?

Reviewer #2 (Public review):

In this paper, the authors successfully incorporated the 49 dimensions found in a human similarity judgment task to better train DNNs to perform accurate human-like object similarity judgments. The results of the model performance are impressive but I am not totally convinced that the present modeling approach may bring new insights regarding the mental and neural representations of visual objects in the human brain. I have a few thoughts that I would like the authors to consider.

(1) Can the authors provide a detailed description of what these off-the-shelf DNNs are trained on? For models trained on visual images only, because semantic information was never present during training, it is not surprising they fail to capture such information, even with additional DimPred training. For the CLIP models, because visual-sematic associations were included during training, it again comes as no surprise that these models can do better even without DimPred training. Similarly, the results of homogenous image sets are not particularly surprising. In this regard, I am finding the paper reports many obvious results. Better motivations should be used to justify why particular models and analyses were performed, what predictions can be made, and how the results may be informative beyond what we already know.

(2) I am curious as to what DimPred training is doing exactly. If you create an arbitrary similarity structure (i.e., not the one derived from human similarity judgment) by, e.g., shuffling the values during training or creating 49 arbitrary dimensions, can the models be trained to follow this new arbitrary structure? In other words, do the models intrinsically contain a human-like structure, but we just have to find the right parameters to align them with the human structure or do we actually impose/force the human similarity structure onto the model with DimPred training?

Is it also an issue that you are including more parameters during DimPred training and that increased parameters alone can increase performance?

(3) There is very little information on how Figure 8 is generated. I couldn't find in the Methods any detailed descriptions of how the values were calculated. Are results from both the category-insensitive and category-sensitive embedding obtained from the same OpenCLIP-RN50x64? Figure 8 reports the relative improvement. What do the raw activation maps look like for the category-insensitive and category-sensitive embedding? I am surprised that the improvement is seen primarily in the early visual cortex (EVC) and higher visual areas but not more extensively in association areas sensitive to semantics. Why should EVC show such large improvements, given that category information is stored elsewhere?

Related to this point, how do other DNN models account for human brain fMRI responses in the present study? Many prior studies have documented the similarities and differences between DNN and human fMRI visual object representations. Do category-sensitive CLIP models outperform other DNN models? It is important to report the full results. Even though category-sensitive CLIP models outperform category-insensitive CLIP ones, if the overall model performance is low compared to the other DNNs, the results would not be very meaningful/impressive. I am just wondering if, in the process of achieving better human-like similarity judgment performance, these models lose some of the ability to account for visual object representations in the human ventral visual cortex.

(4) I am wondering how precisely the present results may yield new insights into the mental and neural representations of visual objects in the human brain. Prior human studies have already identified 49 dimensions that can capture human similarity judgment. Beyond predicting performance for new pairs of objects, how would the present modeling approach help us understand more about the human brain? The authors discussed this, but I am not sure the arguments are convincing.

Reviewer #3 (Public review):

Summary:

The authors compare how well their automatic dimension prediction approach (DimPred) can support similarity judgements and compare it to more standard RSA approaches. The authors show that the DimPred approach does better when assessing out-of-sample heterogeneous image sets, but worse for out-of-sample homogeneous image sets. DimPred also does better at predicting brain-behaviour correspondences compared to an alternative approach. The work appears to be well done, but I'm left unsure what conclusions the authors are drawing.

In the abstract, the authors write: "Together, our results demonstrate that current neural networks carry information sufficient for capturing broadly-sampled similarity scores, offering a pathway towards the automated collection of similarity scores for natural images". If that is the main claim, then they have done a reasonable job supporting this conclusion. However the importance of automating this process for broadly-sampled object categories is not made so clear.

But the authors also highlight the importance that similarity judgements have been for theories of cognition and brain, such as in the first paragraph of the paper they write: "Similarity judgments allow us to improve our understanding of a variety of cognitive processes, including object recognition, categorization, decision making, and semantic memory6-13. In addition, they offer a convenient means for relating mental representations to representations in the human brain14,15 and other domains16,17". The fact that the authors also assess how well a CLIP model using DimPred can predict brain activation suggests that their work is not just about automating similarity judgements, but highlighting how their approach reveals that ANNs are more similar to brains than previously assessed.

My main concern is with regards to the claim that DimPred is revealing better similarities between ANNs and brains (a claim that the authors may not be making, but this should be clarified). The fact that predictions are poor for homogenous images is problematic for this claim, and I expect their DimPred scores would be very poor under many conditions, such as when applied to line drawings of objects, or a variety of addition out-of-sample stimuli that are easily identified by humans. The fact that so many different models get such similar prediction scores (Fig 3) also raises questions as to the inferences you can make about ANN-brain similarity based on the results. Do the authors want to claim that CLIP models are more like brains?

With regards to the brain prediction results, why is the DimPred approach doing so much better in V1? I would not think the 49 interpretable categories are encoded in V1, and the ability to predict would likely reflect a confound rather than V1 encoding these categories (e.g., if a category was "things that are burning" then DNN might predict V1 activation based on the encoding of colour).

In addition, more information is needed on the baseline model, as it is hard to appreciate whether we should be impressed by the better performance of DimPred based on what is provided: "As a baseline, we fit a voxel encoding model of all 49 dimensions. Since dimension scores were available only for one image per category36, for the baseline model, we used the same value for each image of the same category and estimated predictive performance using cross-validation". Is it surprising that predictions are not good with one image per category? Is this a reasonable comparison?

Relatedly, what was the ability of the baseline model to predict? (I don't think that information was provided). Did the authors attempt to predict outside the visual brain areas? What would it mean if predictions were still better there?

Minor points:

The authors write: "Please note that, for simplicity, we refer to the similarity matrix derived from this embedding as "ground-truth", even though this is only a predicted similarity". Given this, it does not seem a good idea to use "ground truth" as this clarification will be lost in future work citing this article.

It would be good to have the 49 interpretable dimensions listed in the supplemental materials rather than having to go to the original paper.

Strengths:

The experiments seem well done.

Weaknesses:

It is not clear what claims are being made.

Joint Public Reviews:

In this study, the authors suggest that DuoHexaBody-CD37, a biparatopic CD37-targeting antibody, can induce direct cytotoxicity in diffuse large B-cell lymphoma (DLBCL) cells through antibody clustering and SHP-1 activation, independent of complement. They further propose that DuoHexaBody-CD37 inhibits cytokine-mediated pro-survival signalling, suggesting a broader role for CD37-directed therapy in disrupting tumour supportive signalling networks.

A strength of the study is the systematic in vitro characterisation of signalling responses to DuoHexaBody-CD37 across both malignant and normal B-cells. The inclusion of phosphoproteomic profiling and mutant constructs provides mechanistic detail, and the findings may be of interest to researchers working on antibody therapeutics in lymphoma.

However, the evidence supporting key mechanistic processes - particularly the role of SHP-1 in mediating cytotoxicity and the requirement for Fc receptor crosslinking - is incomplete and would benefit from further functional validation. While CD37 has been explored previously as a therapeutic target, this study does add mechanistic insight into direct cytotoxicity and cytokine modulation. Nevertheless, the exclusive reliance on in vitro systems makes the translational relevance unclear.

Overall, the study provides valuable insight into CD37-mediated signalling in lymphoma cells, but the evidence remains incomplete to support broader conclusions about therapeutic impact.

Reviewer #1 (Public review):

Summary:

The authors analyze transcription in single cells before and after 4000 rads of ionizing radiation. They use Seuratv5 for their analyses, which allows them to show that most of the genes cluster along the proximal-distal axis. Due to the high heterogeneity in the transcripts, they use the Herfindahl-Hirschman index (HHI) from Economics, which measures market concentration. Using the HHI, they find that genes involved in several processes (like cell death, response to ROS, DNA damage response (DDR)) are relatively similar across clusters. However, ligands activating the JAK/STAT, Pvr, and JNK pathways and transcription factors Ets21C and dysf are upregulated regionally. The JAK/STAT ligands Upd1,2,3 require p53 for their upregulation after irradiation, but the normal expression of Upd1 in unirradiated discs is p53-independent. This analysis also identified a cluster of cells that expressed tribbles, encoding a factor that downregulates mitosis-promoting String and Twine, that appears to be G2/M arrested and expressed numerous genes involved in apoptosis, DDR, the aforementioned ligands, and TFs. As such, the tribbles-high cluster contains much of the heterogeneity.

Strengths:

(1) The authors have used robust methods for rearing Drosophila larvae, irradiating wing discs, and analyzing the data with Seurat v5 and HHI.

(2) These data will be informative for the field.

(3) Most of the data is well-presented.

(4) The literature is appropriately cited.

Weaknesses:

(1) The data in Figure 1 are single-image representations. I assume that counting the number of nuclei that are positive for these markers is difficult, but it would be good to get a sense of how representative these images are and how many discs were analyzed for each condition in B-M.

(2) Some of the figures are unclear.

Reviewer #2 (Public review):

This manuscript investigates the question of cellular heterogeneity using the response of Drosophila wing imaginal discs to ionizing radiation as a model system. A key advance here is the focus on quantitatively expressing various measures of heterogeneity, leveraging single-cell RNAseq approaches. To achieve this goal, the manuscript creatively uses a metric from the social sciences called the HHI to quantify the spatial heterogeneity of expression of individual genes across the identified cell clusters. Inter- and intra-regional levels of heterogeneity are revealed. Some highlights include the identification of spatial heterogeneity in the expression of ligands and transcription factors after IR. Expression of some of these genes shows dependence on p53. An intriguing finding, made possible by using an alternative clustering method focusing on cell cycle progression, was the identification of a high-trbl subset of cells characterized by concordant expression of multiple apoptosis, DNA damage repair, ROS-related genes, certain ligands, and transcription factors, collectively representing HIX genes. This high-trbl set of cells may correspond to an IR-induced G2/M arrested cell state.

Overall, the data presented in the manuscript are of high quality but are largely descriptive. This study is therefore perceived as a resource that can serve as an inspiration for the field to carry out follow-up experiments.

Reviewer #3 (Public review):

Summary:

Cruz and colleagues report a single-cell RNA sequencing analysis of irradiated Drosophila larval wing discs. This is a pioneering study because prior analyses used bulk RNAseq analysis, so differences at single-cell resolution were not discernible. To quantify heterogeneity in gene expression, the authors make clever use of a metric used to study market concentration, the Herfindahl-Hirschman Index. They make several important observations, including region-specific gene expression coupled with heterogeneity within each region and the identification of a cell population (high Trbl) that seems disproportionately responsible for radiation-induced gene expression.

Strengths:

Overall, the manuscript makes a compelling case for heterogeneity in gene expression changes that occur in response to uniform induction of damage by X-rays in a single-layer epithelium. This is an important finding that would be of interest to researchers in the field of DNA damage responses, regeneration, and development.

Weaknesses:

This work would be more useful to the field if the authors could provide a more comprehensive discussion of both the impact and the limitations of their findings, as explained below.

Propidium iodide staining was used as a quality control step to exclude cells with a compromised cell membrane. But this would exclude dead/dying cells that result from irradiation. What fraction of the total do these cells represent? Based on the literature, including works cited by the authors, up to 85% of cells die at 4000R, but this likely happens over a longer period than 4 hours after irradiation. Even if only half of the 85% are PI-positive by 4 hr, this still removes about 40% of the cell population from analysis. The remaining cells that manage to stay alive (excluding PI) at 4 hours and included in the analysis may or may not be representative of the whole disc. More relevant time points that anticipate apoptosis at 4 hr may be 2 hr after irradiation, at which time pro-apoptotic gene expression peaks (Wichmann 2006). Can the authors rule out the possibility that there is heterogeneity in apoptosis gene expression, but cells with higher expression are dead by 4 hours, and what is left behind (and analyzed in this study) may be the ones with more uniform, lower expression? I am not asking the authors to redo the study with a shorter time point, but to incorporate the known schedule of events into their data interpretation.

If cluster 3 is G1/S, cluster 5 is late S/G2, and cluster 4 is G2/M, what are clusters 0, 1, and 2 that collectively account for more than half of the cells in the wing disc? Are the proportions of clusters 3, 4, and 5 in agreement with prior studies that used FACS to quantify wing disc cells according to cell cycle stage?

The EdU data in Figure 1 is very interesting, especially the persistence in the hinge. The authors speculate that this may be due to cells staying in S phase or performing a higher level of repair-related DNA synthesis. If so, wouldn't you expect 'High PCNA' cells to overlap with the hinge clusters in Figures 6G-G'? Again, no new experiments are needed. Just a more thorough discussion of the data.

Trbl/G2/M cluster shows Ets21C induction, while the pattern of Ets21C induction as detected by HCR in Figures 5H-I appears in localized clusters. I thought G2/M cells are not spatially confined. Are Ets21C+ cells in Figure 5 in G2/M? Can the overlap be confirmed, for example, by co-staining for Trbl or a G2/M marker with Ets21C?

Induction of dysf in some but not all discs is interesting. What were the proportions? Any possibility of a sex-linked induction that can be addressed by separating male and female larvae?

Reviewer #1 (Public review):

In the manuscript, Aldridge and colleagues investigate the role of IL-27 in regulating hematopoiesis during T. gondii infection. Using loss-of-function approaches, reporter mice, and the generation of serial chimeric mice, they elegantly demonstrate that IL-27 induction plays a critical role in modulating bone marrow myelopoiesis and monocyte generation to the infection site. The study is well-designed, with clear experimental approaches that effectively address the mechanisms by which IL-27 regulates bone marrow myelopoiesis and prevents HSC exhaustion.

Reviewer #2 (Public review):

Summary:

Aldridge et al. aim to demonstrate the role of IL27 in limiting emergency myelopoiesis in response to Toxoplasma gondii infection by acting directly at the level of early haematopoietic progenitors.

They used different mouse genetic models, such as HSC lineage tracing, IL27 and IL27R-deficient mice, to show that:

(1) HSCs actively participate in emergency myelopoiesis during Toxoplasma gondii infection.

(2) The absence of IL27 and IL27R increases monocyte progenitors and monocytes, mainly inflammatory monocytes CCR2hi.

(3) At steady state, loss of IL27 impairs HSC fitness as competitive transplantation shows long-term engraftment deficiency of IL27 BM cells. This impairment is exacerbated after infection.

(4) IL27 is produced by various BM and other tissue cells at steady state, and its expression increases with infection, mainly by increasing the number of monocytes producing it.

Although it is indisputable that IL27 has a role in emergency myelopoiesis by limiting the number of pro-inflammatory monocytes in response to infection, the authors' claim that it acts only on HSCs and not on more committed progenitors (CMP, GMP, MP) is not supported by the quality of the data presented here, as described below in the weakness section. In addition, this study highlights a role for IL27 during infection, but does not focus on trained immunity, which is the focus of the targeted elife issue.

Weaknesses:

(1) In Figure 4, MFI quantification is required. This figure also shows the expression level (FACS and RNA) in progenitors (GMP and CMP, GP, MP), which is quite similar to that of HSC at this level, so it is really surprising that CMP does not respond at all to IL27 (S5C).

(2) Total BM was used to test the direct effect of IL27 on HSC. There could be an indirect effect from other more mature BM cells, even if they show lower receptor expression than HSC. This should be done on a different sorted population to prove the direct effect of IL27 on HSC. The authors need to look more closely at some stat-dependent genes or stat itself in different sorted cell populations, not just irgm1. It is also known that Stat is associated with increased HSC proliferation in response to IFN, which is the opposite of what is observed here.

(3) The decrease in HSC fitness in IL27R KO at steady state could be an indirect effect of the increase in proinflammatory monocytes contributing to high levels of inflammatory cytokines in the BM and thus chronic HSC activation that is enhanced in response to infection. What is the pro-inflammatory cytokine profile of the BM of IL27 or IL27R deficient mice and of mixed chimera mice?

(4) Furthermore, the FACS profile of KI67/brdu of Figure 7 is doubtful, as it is shown in different literature that KSL are not predominantly quiescent as shown here, but about 50% are KI67-. This is also inconsistent with the increase of HSC observed in Figure 1. Quantification of total BruDU+ HSC and other progenitors is also important to quantify all cells that have proliferated during infection. As the repopulation of IL27-deficient BM is also lower in the absence of infection, the proliferation of HSC in IL27R KO mice in the absence of infection is also important.

(5) The immunofluorescence in Figure 3 shows a high level of background and it is difficult to see the GFP and tomato positive cells. In this sense, the number of HSCs quantified as Procr+ (more than 8000 on a single BM section) is inconsistent with the total number of HSCs that a BM can contain (i.e., around 6000 per BM as quantified in Figure 1).

(6) The addition of arrows to the figure will help to visualise positive cells. It is also not clear why the author normalised the GFP+ cells to the tomato+ cells in Figure 3D.

(7) Furthermore, even if monocytes represent a high proportion of IL27-producing cells, they are only 50% of the cells at 5dpi, as shown in Figure 3 and S4. Without other monocyte markers, line 307 is incorrect.

(8) How do the authors explain that in Figure 1, 5-10% of labelled precursors and monocytes can give 100% of monocytes? This would mean that only labelled HSC can differentiate into PEC monocytes.

Reviewer #1 (Public review):

Summary:

This study addresses the encoding of forelimb movement parameters using a reach-to-grasp task in mice. The authors use a modified version of the water-reaching paradigm developed by Galinanes and Huber. Two-photon calcium imaging was then performed with GCaMP6f to measure activity across both the contralateral caudal forelimb area (CFA) and the forelimb portion of primary somatosensory cortex (fS1) as mice perform the reaching behavior. Established methods were used to extract the activity of imaged neurons in layer 2/3, including methods for deconvolving the calcium indicator's response function from fluorescence time series. Video-based limb tracking was performed to track the positions of several sites on the forelimb during reaching and extract numerous low-level (joint angle) and high-level (reach direction) parameters. The authors find substantial encoding of parameters for both the proximal and distal parts of the limb across both CFA and fS1, with individual neurons showing heterogeneous parameter encoding. Limb movement can be decoded similarly well from both CFA and fS1, though CFA activity enables decoding of reach direction earlier and for a more extended duration than fS1 activity. Collectively, these results indicate involvement of a broadly distributed sensorimotor region in mouse cortex in determining low-level features of limb movement during reach-to-grasp.

Strengths:

The technical approach is of very high quality. In particular, the decoding methods are well designed and rigorous. The use of partial correlations to distinguish correlation between cortical activity and either proximal or distal limb parameters or either low- or high-level movement parameters was very nice. The limb tracking was also of extremely high quality, and critical here to revealing the richness of distal limb movement during task performance.

The task itself also reflects an important extension of the original work by Galinanes and Huber. The demonstration of a clear, trackable grasp component in a paradigm where mice will perform hundreds of trials per day expands the experimental opportunities for the field. This is an exciting development.

The findings here are important and the support for them is solid. The work represents an important step forward toward understanding the cortical origins of limb control signals. One can imagine numerous extensions of this work to address basic questions that have not been reachable in other model systems.

Collectively, these strengths made this manuscript a pleasure to read and review.

Weaknesses:

In the last section of the results, the authors purport to examine the representation of "higher-level target-related signals," using the decoding of reach direction. While I think the authors are careful in their phrasing here, I think they should be more explicit about what these signals could be reflecting. The "signals" here that are used to decode direction could relate to anything - low-level signals related to limb or postural muscles, or true high-level commands that dictate only what movement downstream motor centers should execute, rather than the muscle commands that dictate how. One could imagine using a partial correlation-type approach again here to extract a signal uncorrelated with all the measured low-level parameters, but there would still be all the unmeasured ones. Again, I think it is still ok to call these "high-level signals," but I think some explicit discussion of what these signals could reflect is necessary.

Related to this, I think the manuscript in general does not do an adequate job of explicitly raising the important caveats in interpreting parametric correlations in motor system signals, like those raised by Todorov, 2000. The authors do an expert job of handling the correlations, using PCA to extract uncorrelated components and using the partial correlation approach. However, more clarity about the range of possible signal types the recorded activity could reflect seems necessary.

The manuscript could also do a better job of clarifying relevant similarities and differences between the rodent and primate systems, especially given the claims about the rodent being a "first-class" system for examining the cellular and circuit basis of motor control, which I certainly agree with. Interspecies similarities and differences could be better addressed both in the Introduction, where results from both rodents and primates are intermixed (second paragraph), and in the Discussion, where more clarity on how results here agree and disagree with those from primates would be helpful. For example, the ratio of corticospinal projections targeting sensory and motor divisions of the spinal cord differs substantially between rodents and primates. As another example, the relatively high physical proximity between the typical neurons in mouse M1 and S1 compared to primates seems likely to yoke their activity together to a greater extent. There is also the relatively large extent of fS1 from which forelimb movements can be elicited through intracortical microstimulation at current levels similar to those for evoking movement from M1. All of these seem relevant in the context of findings that activity in mouse M1 and S1 are similar.

In addition, there are a number of other issues related to the interpretation of findings here that are not adequately addressed. These are described in the Recommendations for improvement.

Reviewer #2 (Public review):

Summary:

In this manuscript, Grier, Salimian, and Kaufman characterize the relationship between the activity of neurons in sensorimotor cortex and forelimb kinematics in mice performing a reach-to-grasp task. First, they train animals to reach to two cued targets to retrieve water reward, measure limb motion with high resolution, and characterize the stereotyped kinematics of the shoulder, elbow, wrist, and digits. Next, they find that inactivation of the caudal forelimb motor area severely impairs coordination of the limb and prevents successful performance of the task. They then use calcium imaging to measure the activity of neurons in motor and somatosensory cortex, and demonstrate that fine details of limb kinematics can be decoded with high fidelity from this activity. Finally, they show reach direction (left vs right target) can be decoded earlier in the trial from motor than from somatosensory cortex.

Strengths:

In my opinion, this manuscript is technically outstanding and really sets a new bar for motor systems neurophysiology in the mouse. The writing and figures are clear, and the claims are supported by the data. This study is timely, as there has been a recent trend towards recording large numbers of neurons across the brain in relatively uncontrolled tasks and inferring a widespread but coarse encoding of high-level task variables. The central finding here, that sensorimotor cortical activity reflects fine details of forelimb movement, argues against the resurgent idea of cortical equipotentiality, and in favor of a high degree of specificity in the responses of individual neurons and of the specialization of cortical areas.

Weaknesses:

It would be helpful for the authors to be more explicit about which models of mouse cortical function their results support or rule out, and how their findings break new conceptual ground.

Reviewer #1 (Public review):

Summary

Lysine acetoacetylation (Kacac) is a recently discovered histone post-translational modification (PTM) connected to ketone body metabolism. This research outlines a chemo-immunological method for detecting Kacac, eliminating the requirement for creating new antibodies. The study demonstrates that acetoacetate acts as the precursor for Kacac, which is catalyzed by the acyltransferases GCN5, p300, and PCAF, and removed by the deacetylase HDAC3. Acetoacetyl-CoA synthetase (AACS) is identified as a central regulator of Kacac levels in cells. A proteomic analysis revealed 139 Kacac sites across 85 human proteins, showing the modification's extensive influence on various cellular functions. Additional bioinformatics and RNA sequencing data suggest a relationship between Kacac and other PTMs, such as lysine β-hydroxybutyrylation (Kbhb), in regulating biological pathways. The findings underscore Kacac's role in histone and non-histone protein regulation, providing a foundation for future research into the roles of ketone bodies in metabolic regulation and disease processes.

Strengths

(1) The study developed an innovative method by using a novel chemo-immunological approach to the detection of lysine acetoacetylation. This provides a reliable method for the detection of specific Kacac using commercially available antibodies.

(2) The research has done a comprehensive proteome analysis to identify unique Kacac sites on 85 human proteins by using proteomic profiling. This detailed landscape of lysine acetoacetylation provides a possible role in cellular processes.

(3) The functional characterization of enzymes explores the activity of acetoacetyltransferase of key enzymes like GCN5, p300, and PCAF. This provides a deeper understanding of their function in cellular regulation and histone modifications.

(4) The impact of acetyl-CoA and acetoacetyl-CoA on histone acetylation provides the differential regulation of acylations in mammalian cells, which contributes to the understanding of metabolic-epigenetic crosstalk.

(5) The study examined acetoacetylation levels and patterns, which involve experiments using treatment with acetohydroxamic acid or lovastatin in combination with lithium acetoacetate, providing insights into the regulation of SCOT and HMGCR activities.

Weakness

(1) There is a limitation to functional validation, related to the work on the biological relevance of identified acetoacetylation sites. Hence, the study requires certain functional validation experiments to provide robust conclusions regarding the functional implications of these modifications on cellular processes and protein function. For example, functional implications of the identified acetoacetylation sites on histone proteins would aid the interpretation of the results.

(2) The authors could have studied acetoacetylation patterns between healthy cells and disease models like cancer cells to investigate potential dysregulation of acetoacetylation in pathological conditions, which could provide insights into their PTM function in disease progression and pathogenesis.

(3) The time-course experiments could be performed following acetoacetate treatment to understand temporal dynamics, which can capture the acetoacetylation kinetic change, thereby providing a mechanistic understanding of the PTM changes and their regulatory mechanisms.

(4) Though the discussion section indeed provides critical analysis of the results in the context of existing literature, further providing insights into acetoacetylation's broader implications in histone modification. However, the study could provide a discussion on the impact of the overlap of other post-translational modifications with Kacac sites with their implications on protein functions.

Impact

The authors successfully identified novel acetoacetylation sites on proteins, expanding the understanding of this post-translational modification. The authors conducted experiments to validate the functional significance of acetoacetylation by studying its impact on histone modifications and cellular functions.

Reviewer #2 (Public review):

In the manuscript by Fu et al., the authors developed a chemo-immunological method for the reliable detection of Kacac, a novel post-translational modification, and demonstrated that acetoacetate and AACS serve as key regulators of cellular Kacac levels. Furthermore, the authors identified the enzymatic addition of the Kacac mark by acyltransferases GCN5, p300, and PCAF, as well as its removal by deacetylase HDAC3. These findings indicate that AACS utilizes acetoacetate to generate acetoacetyl-CoA in the cytosol, which is subsequently transferred into the nucleus for histone Kacac modification. A comprehensive proteomic analysis has identified 139 Kacac sites on 85 human proteins. Bioinformatics analysis of Kacac substrates and RNA-seq data reveals the broad impacts of Kacac on diverse cellular processes and various pathophysiological conditions. This study provides valuable additional insights into the investigation of Kacac and would serve as a helpful resource for future physiological or pathological research.

The following concerns should be addressed:

(1) A detailed explanation is needed for selecting H2B (1-26) K25 sites over other acetylation sites when evaluating the feasibility of the chemo-immunological method.

(2) In Figure 2(B), the addition of acetoacetate and NaBH4 resulted in an increase in Kbhb levels. Specifically, please investigate whether acetoacetylation is primarily mediated by acetoacetyl-CoA and whether acetoacetate can be converted into a precursor of β-hydroxybutyryl (bhb-CoA) within cells. Additional experiments should be included to support these conclusions.

(3) In Figure 2(E), the amount of pan-Kbhb decreased upon acetoacetate treatment when SCOT or AACS was added, whereas this decrease was not observed with NaBH4 treatment. What could be the underlying reason for this phenomenon?

(4) The paper demonstrates that p300, PCAF, and GCN5 exhibit significant acetoacetyltransferase activity and discusses the predicted binding modes of HATs (primarily PCAF and GCN5) with acetoacetyl-CoA. To validate the accuracy of these predicted binding models, it is recommended that the authors design experiments such as constructing and expressing protein mutants, to assess changes in enzymatic activity through western blot analysis.

(5) HDAC3 shows strong de-acetoacetylation activity compared to its de-acetylation activity. Specific experiments should be added to verify the molecular docking results. The use of HPLC is recommended, in order to demonstrate that HDAC3 acts as an eraser of acetoacetylation and to support the above conclusions. If feasible, mutating critical amino acids on HDAC3 (e.g., His134, Cys145) and subsequently analyzing the HDAC3 mutants via HPLC and western blot can further substantiate the findings.

(6) The resolution of the figures needs to be addressed in order to ensure clarity and readability.

Reviewer #3 (Public review):

Summary:

This paper presents a timely and significant contribution to the study of lysine acetoacetylation (Kacac). The authors successfully demonstrate a novel and practical chemo-immunological method using the reducing reagent NaBH4 to transform Kacac into lysine β-hydroxybutyrylation (Kbhb).

Strengths:

This innovative approach enables simultaneous investigation of Kacac and Kbhb, showcasing their potential in advancing our understanding of post-translational modifications and their roles in cellular metabolism and disease.

Weaknesses:

The paper's main weaknesses are the lack of SDS-PAGE analysis to confirm HATs purity and loading consistency, and the absence of cellular validation for the in vitro findings through knockdown experiments. These gaps weaken the evidence supporting the conclusions.

Reviewer #1 (Public review):

Summary:

In this paper, authors investigated the role of RUNT-related transcription factor 2 (RUNX2) in oral squamous carcinoma (OSCC) growth and resistance to ferroptosis. They found that RUNX2 suppresses ferroptosis through transcriptional regulation of peroxiredoxin-2. They further explored the upstream positive regulator of RUNX2, HOXA10 and found that HOXA1/RNUX2/PRDX2 axis protects OSCC from ferroptosis.

Strengths:

The study is well designed and provides a novel mechanism of HOXA1/RNUX2/PRDX2 control of ferroptosis in OSCC.

Weaknesses:

According to the data presented in (Figure 2F, Figure 3F and G, Figure 5D and Figure 6E and F), apoptosis seems to be affected in the same amount as ferroptosis by HOXA1/RNUX2/PRDX2 axis, which raises a question on the authors' specific focus on ferroptosis in this study. Reasonably, authors should adapt the title and the abstract in a way that it recapitulates the whole data, which is HOXA1/RNUX2/PRDX2 axis control of cell death, including ferroptosis and apoptosis in OSCC.

Comments on revisions:

The revised manuscript has been well improved, and I'm satisfied with the authors' response to my comments.

Reviewer #1 (Public review):

Summary:

Epiney et al. use single-nuclei RNA sequencing (snRNA-seq) to characterize the lineage of Type-2 (T2) neuroblasts (NBs) in the adult Drosophila brain. To isolate cells born from T2 NBs, the authors used a genetic tool that specifically allows the permanent labeling of T2-derived cell types, which are then FAC-sorted for snRNA-seq. This effective labeling approach also allows them to compare the isolated T2 lineage cells with T1-derived cell types by a simple exclusion method. The authors begin by describing a transcriptomic atlas for all T1 and T2-derived neuronal and glia clusters, reporting that the T2-derived lineage comprises 161 neuronal clusters, in contrast to the T1 lineage which comprises 114 of them. The authors then use the expression of VAChT, VGlut, Gad1, Tbh, Ple, SerT, and Tdc2 to show that T2 neuroblasts generate all major neuron classes of fast-acting neurotransmitters. Strikingly, they show that a subset of glia and neuronal clusters have disproportionate enrichment in males or females, suggesting that T2 neuroblasts generate sex-biased cell types. The authors then proceed to characterize neuropeptide expression across T2-derived neuronal clusters and argue that the same neuropeptide can be expressed across different cell types, while similar cell types can express distinct neuropeptides. The functional implication of both observations, however, remains to be tested. Furthermore, the authors describe combinatorial transcription factor (TF) codes that are correlated with neuropeptide expression for T2-derived neurons along with an overall TF code for all T2-derived cell types, both of which will serve as an important starting point for future investigations. Finally, the authors map well-studied neuronal types of the central complex to the clusters of their T2-derived snRNA-seq dataset. They use known marker combinations, bulk RNA-seq data and highly specific split-GAL4 driver lines to annotate their T2-derived atlas, establishing a comprehensive transcriptomic atlas that would guide future studies in this field.

Strengths:

This study provides an in-depth transcriptomic characterization of neurons and glia derived from Type-2 neuroblast lineages. The results of this manuscript offer several future directions to investigate the mechanisms of diversifying neuronal identity. The datasets of T1-derived and T2-derived cells will pave the way for studies focused on the functional analysis of combinatorial TF codes specifying cell identity, sex-based differences in neurogenesis and gliogenesis, the relationship between neuropeptide (co)expression and cell identity, and the differential contributions of distinct progenitor populations to the same cell type.

Weaknesses:

The study presents several important observations based on the characterization of Type II neuroblast-derived lineages. However, a mechanistic insight is missing for most observations. The idea that there is a sex-specific bias to certain T2-derived neurons and glial clusters is quite interesting, however, the functional significance of this observation is not tested or discussed extensively. Finally, the authors do not show whether the combinatorial TF code is indeed necessary for neuropeptide expression or if this is just a correlation due to cell identity being defined by TFs. Functional knockdown of some candidate TFs for a subset of neuropeptide-expressing cells would have been helpful in this case.

Comments on revisions:

The authors have addressed my recommendations.

Reviewer #2 (Public review):

In this manuscript, Epiney et al., present a single-nucleus sequencing analysis of Drosophila adult central brain neurons and glia. By employing an ingenious permanent labeling technique, they trace the progeny of T2 neuroblasts, which play a key role in the formation of the central complex. This transcriptomic dataset is poised to become a valuable resource for future research on neurogenesis, neuron morphology, and behavior.

The authors further delve into this dataset with several analyses, including the characterization of neurotransmitter expression profiles in T2-derived neurons. While some of the bioinformatic analyses are preliminary, they would benefit from additional experimental validation in future studies.

Comments on revisions:

We appreciate the authors' efforts to address some of the comments. While these revisions have improved the clarity of certain sections, some of the larger concerns remain unaddressed. Specifically, the manuscript still lacks the additional analyses that would allow for more specific conclusions, rather than the general observations currently presented. Although the revisions have certainly made the text clearer, the core issue of needing more detailed analysis to draw more concrete conclusions still stands.

Reviewer #2 (Public review):

Summary:

The authors developed a novel tool, SCellBOW, to perform cell clustering and infer survival risks on individual cancer cell clusters from the single cell RNA seq dataset. The key ideas/techniques used in the tool include transfer learning, bag of words (BOW), and phenotype algebra which is similar to word algebra from natural language processing (NLP). Comparisons with existing methods demonstrated that SCellBOW provides superior clustering results and exhibits robust performance across a wide range of datasets. Importantly, a distinguishing feature of SCellBOW compared to other tools is its ability to assign risk scores to specific cancer cell clusters. Using SCellBOW, the authors identified a new group of prostate cancer cells characterized by a highly aggressive and dedifferentiated phenotype.

Strengths:

The application of natural language processing (NLP) to single-cell RNA sequencing (scRNA-seq) datasets is both smart and insightful. Encoding gene expression levels as word frequencies is a creative way to apply text analysis techniques to biological data. When combined with transfer learning, this approach enhances our ability to describe the heterogeneity of different cells, offering a novel method for understanding the biological behavior of individual cells and surpassing the capabilities of existing cell clustering methods. Moreover, the ability of the package to predict risk, particularly within cancer datasets, significantly expands the potential applications.

Weaknesses:

Given the promising nature of this tool, it would be beneficial for the authors to test the risk-stratification functionality on other types of tumors with high heterogeneity, such as liver and pancreatic cancers, which currently lack clinically relevant and well-recognized stratification methods. Additionally, it would be worthwhile to investigate how the tool could be applied to spatial transcriptomics by analyzing cell embeddings from different layers within these tissues.

Reviewer #1 (Public review):

Summary:

The authors investigated the population structure of the invasive weed Lantana camara from 36 localities in India using 19,008 genome-wide SNPs obtained through ddRAD sequencing.

Strengths:<br /> The manuscript is well-written, the analyses are sound, and the figures are of great quality.

Weaknesses:

The narrative almost completely ignores the fact that this plant is popular in horticultural trade and the different color morphs that form genetic populations are most likely the result of artificial selection by humans for certain colors for trade, and not the result of natural selfing. Although it may be possible that the genetic clustering of color morphs is maintained in the wild through selfing, there is no evidence in this study to support that. The high levels of homozygosity are more likely explained as a result of artificial selection in horticulture and relatively recent introductions in India. Therefore, the claim of the title that "the population structure.. is shaped by its mating system" is in part moot, because any population structure is in large part shaped by the mating system of the organism, but further misleading because it is much more likely artificial selection that caused the patterns observed.

Reviewer #2 (Public review):

Summary:

The authors performed a series of population genetic analyses in Lantana camara using 19,008 genome-wide SNPs data from 359 individuals in India. They found a clear population structure that did not show a geographical pattern, and that flower color was rather associated with population structure. Excess of homozygosity indicates a high selfing rate, which may lead to fixation of alleles in local populations and explain the presence of population structure without a clear geographic pattern. The authors also performed a forward simulation analysis, theoretically confirming that selfing promotes fixation of alleles (higher Fst) and reduction in genetic diversity (lower heterozygosity).

Strengths:

Biological invasion is a critical driver of biodiversity loss, and it is important to understand how invasive species adapt to novel environments despite limited genetic diversity (genetic paradox of biological invasion). Lantana camara is one of the hundred most invasive species in the world (IUCN 2000), and the authors collected 359 plants from a wide geographical range in India, where L. camara has invaded. The scale of the dataset and the importance of the target species are the strengths of the present study.

Weaknesses:

One of the most critical weaknesses of this study would be that the output modelling analysis is largely qualitative, which cannot be directly comparable to the empirical data. The main findings of the SLiM-based simulation were that selfing promotes the fixation of alleles and the reduction of genetic diversity. These are theoretically well-reported knowledge, and such findings themselves are not novel, although it may have become interesting these findings are quantitatively integrated with their empirical findings in the studied species. In that sense, a coalescent-based analysis such as an Approximate Bayesian Computation method (e.g. DIY-ABC) utilizing their SNPs data would be more interesting. For example, by ABC-based methods, authors can infer the split time between subpopulations identified in this study. If such split time is older than the recorded invasion date, the result supports the scenario that multiple introductions may have contributed to the population structure of this species. In the current form of the manuscript, multiple introductions were implicated but not formally tested.

I also have several concerns regarding the authors' population genetic analyses. First, the authors removed SNPs that were not in Hardy-Weinberg equilibrium (HWE), but the studied populations would not satisfy the assumption of HWE, i.e., random mating, because of a high level of inbreeding. Thus, the first screening of the SNPs would be biased strongly, which may have led to spurious outputs in a series of downstream analyses. Second, in the genetic simulation, it is not clear how a set of parameters such as mutation rate, recombination rate, and growth rate were determined and how they are appropriate. Importantly, while authors assume the selfing rate in the simulation, selfing can also strongly influence the effective mutation rate (e.g. Nordborg & Donnelly 1997 Genetics, Nordborg 2000 Genetics). It is not clear how this effect is incorporated in the simulation. Third, while the authors argue the association between flower color and population structure, their statistical associations were not formally tested. Also, it is not mentioned how flower color polymorphisms are defined. Could it be possible to distinguish many flower color morphs shown in Figure 1b objectively? I am concerned particularly because the authors also mentioned that flower color may change temporally and that a single inflorescence can have flowers of different colors (L160).

Reviewer #1 (Public review):

The authors present tviblindi, an algorithm to infer cell development trajectories from single-cell molecular data. The paper is well-written and the algorithm is conceptually interesting. However, the validation is incomplete as the comparison against existing trajectory inference methods is weak: although the lack of a proper benchmark was pointed out as the main weakness of the original version of the manuscript, the revised version still only contains qualitative comparisons against state-of-the-art methods.

Both me and Reviewer 2 pointed out that the lack of a proper benchmark against state-of-the-art methods on a wider variety of datasets (including scRNA-seq data) was a major weakness of the original version of the manuscript. In response to this criticism, the authors now did the following:

- They ran various competitor methods on the datasets that were used already for the previous version of the manuscript.<br /> - They ran tviblindi and two of the competitors on two public scRNA-seq datasets.<br /> - For all datasets, they qualitatively assessed the trajectories computed by tviblindi and its competitors and argued that tviblindi's trajectories better reflect the biological signal in the data.<br /> - The results of all of these additional analyses are reported in the supplement, which has now become very lengthy (88 pages).

In my opinion, this is insufficient to establish that tviblindi is comparable or even superior to the state of the art in the field. To show that this is the case, the authors would have to carry out a systematic benchmark study which relies on quantitative evaluation metrics rather than on qualitative intepretations of trajectories. As method developers, we are all susceptive to confirmation bias when comparing our new algorithms to the state of the art. To avoid this pitfall, reporting quantitative performance metrics is required. At the moment, the only quantitative metric reported by the authors is runtime, which is insufficient.

Moreover, the results of a benchmark study should be reported in the main manuscript, not in the supplement. When presenting a new algorithm in a field as crowded as trajectory inference, a benchmark against the state of the art serves to establish trust in the new algorithm and to provide the readers with a rationale to use it for their research. For this, the results of the benchmark have to be presented prominently and should not be hidden in the supplement.

A second major criticism raised in Reviewer 2's review of the original version of the manuscript is that tviblindi invites cherry picking due to its inherently interactive design. In response to this, the authors now argue at length that "the data-driven expert interpretation approach of tviblindi" (quote from Section 2.2.2) is a strength rather than a weakness. If we concede for the sake of the argument that tviblindi's "expert interpretation approach" is indeed a strength of the method (although I tend to agree with Reviewer 2 that it is rather a limitation), usability for biologists becomes critical. However, given the current implementation of tviblindi, its usability is far from optimal. The authors do not provide tviblindi as a web interface that is directly usable for domain experts without programming experience and not even as a package that is installable via some widely used package manager such as conda. Instead, they implemented tviblindi as an R package with a Shiny GUI that can either run in a Docker container or requires the installation of several dependencies. I therefore strongly doubt that many biologists will be able or willing to run tviblindi, which substantially limits the value of its "expert interpretation approach". Moreover, tviblindi does not support Apple silicon, which prevented also myself from testing the tool.

Reviewer #1 (Public review):

Summary:

In this work, Huang et al. revealed the complex regulatory functions and transcription network of 172 unknown transcriptional factors (TFs) in Pseudomonas aeruginosa PAO1. They have built a global TF-DNA binding landscape and elucidated binding preferences and functional roles of these TFs. More specifically, the authors established a hierarchical regulatory network and identified ternary regulatory motifs, and co-association modules. Since P. aeruginosa is a well known pathogen, the authors thus identified key TFs associated with virulence pathways (e.g., quorum sensing [QS], motility, biofilm formation), which could be potential drug targets for future development. The authors also explored the TF conservation and functional evolution through pan-genome and phylogenetic analyses. For the easy searching by other researchers, the authors developed a publicly accessible database (PATF_Net) integrating ChIP-seq and HT-SELEX data.

Strengths:

(1) The authors performed ChIP-seq analysis of 172 TFs (nearly half of the 373 predicted TFs in P. aeruginosa) and identified 81,009 significant binding peaks, representing one of the largest TF-DNA interaction studies in the field. Also, The integration of HT-SELEX, pan-genome, and phylogenetic analyses provided multi-dimensional insights into TF conservation and function.

(2) The authors provided informative analytical Framework for presenting the TFs, where a hierarchical network model based on the "hierarchy index (h)" classified TFs into top, middle, and bottom levels. They identified 13 ternary regulatory motifs and co-association clusters, which deepened our understanding of complex regulatory interactions.

(3) The PATF_Net database provides TF-target network visualization and data-sharing capabilities, offering practical utility for researchers especially for the P. aeruginosa field.

Weaknesses:

(1) There is very limited experimental validation for this study. Although 24 virulence-related master regulators (e.g., PA0815 regulating motility, biofilm, and QS) were identified, functional validation (e.g., gene knockout or phenotypic assays) is lacking, leaving some conclusions reliant on bioinformatic predictions. Another approach for validation is checking the mutations of these TFs from clinical strains of P. aeruginosa, where chronically adapted isolates often gain mutations in virulence regulators.

(2) ChIP-seq in bacteria may suffer from low-abundance TF signals and off-target effects. The functional implications of non-promoter binding peaks (e.g., coding regions) were not discussed.

(3) PATF_Net currently supports basic queries but lacks advanced tools (e.g., dynamic network modeling or cross-species comparisons). User experience and accessibility remain underevaluated. But this could be improved in the future.

Achievement of Aims and Support for Conclusions

(1) The authors successfully mapped global P. aeruginosa TF binding sites, constructed hierarchical networks and co-association modules, and identified virulence-related TFs, fulfilling the primary objectives. The database and pan-genome analysis provide foundational resources for future studies.

(2) The hierarchical model aligns with known virulence mechanisms (e.g., LasR and ExsA at the bottom level directly regulating virulence genes). Co-association findings (e.g., PA2417 and PA2718 co-regulating pqsH) resonate with prior studies, though experimental confirmation of synergy is needed.

Impact on the Field and Utility of Data/Methods

(1) This study fills critical gaps in TF functional annotation in P. aeruginosa, offering new insights into pathogenicity mechanisms (e.g., antibiotic resistance, host adaptation). The hierarchical and co-association frameworks are transferable to other pathogens, advancing comparative studies of bacterial regulatory networks.

(2) PATF_Net enables rapid exploration of TF-target interactions, accelerating candidate regulator discovery.

Reviewer #3 (Public review):

Summary:

The authors utilized ChIP-seq on strains containing tagged transcription factor (TF)-overexpression plasmids to identify binding sites for 172 transcription factors in P. aeruginosa. High-quality binding site data provides a rich resource for understanding regulation in this critical pathogen. These TFs were selected to fill gaps in prior studies measuring TF binding sites in P. aeruginosa. The authors further perform a structured analysis of the resulting transcriptional regulatory network, focusing on regulators of virulence and metabolism, in addition to performing a pangenomic analysis of the TFs. The resulting dataset has been made available through an online database. While the implemented approach to determining functional TF binding sites has limitations, the resulting dataset still has substantial value to P. aeruginosa research.

Strengths:

The generated TF binding site database fills an important gap in regulatory data in the key pathogen P. aeruginosa. Key analyses of this dataset presented include an analysis of TF interactions and regulators of virulence and metabolism, which should provide important context for future studies into these processes. The online database containing this data is well organized and easy to access. As a data resource, this work should be of significant value to the infectious disease community.

Weaknesses:

Drawbacks of the study include 1) challenges interpreting binding site data obtained from TF overexpression due to unknown activity state of the TFs on the measured conditions, 2) limited practical value of the presented TRN topological analysis, and 3) lack of independent experimental validation of the proposed master regulators of virulence and metabolism.

Reviewer #1 (Public review):

Summary:

In their manuscript, the authors provide compelling evidence that stimulus-frequency otoacoustic emission (SFOAE) phase-gradient delays predict the sharpness (quality factors) of auditory-nerve-fiber (ANF) frequency tuning curves in budgerigars. In contrast with mammals, neither SFOAE- nor ANF-based measures of cochlear tuning match the frequency dependence of behavioral tuning in this species of parakeet. Although the reason for the discrepant behavioral results (taken from previous studies) remains unexplained, the present data provide significant and important support for the utility of otoacoustic estimates of cochlear tuning, a methodology previously explored only in mammals.

Strengths:

* The OAE and ANF data appear solid and believable. (The behavioral data are taken from previous studies and the resulting limitations are discussed.)

* No other study in birds (and only a single previous study in mammals) has combined behavioral, auditory-nerve, and otoacoustic estimates of cochlear tuning in a single species.

* SFOAE-based estimates of cochlear tuning were obtained by assuming that the tuning ratio estimated in chicken applies also to the budgerigar. Possible complications arising from an avian apical-basal transition analogous to that found in mammals are discussed.

Reviewer #2 (Public review):

Summary:

Earlier behavioral data in the budgerigar have suggested frequency selectivity that was different from that in many other avian species, showing particularly good selectivity at around 3-4 kHz. It was unknown whether this unusual selectivity was determined in the inner ear, or whether it was a more central adaptation. The results using direct auditory-nerve tuning curves and less invasive stimulus-frequency otoacoustic emissions, suggest fairly normal-looking cochlear tuning in the budgerigar, implying that any behavioral/perceptual differences in frequency selectivity are likely more central in original.

Strengths:

- The study presents novel data in budgerigar, comparing the bandwidths of auditory-nerve tuning curves with the latencies of stimulus-frequency otoacoustic emissions (SFOAEs), which are thought to reflect the sharpness of cochlear tuning.<br /> - Using a conversion factor taken from previous data in the chicken to avoid circularity of reasoning, the study shows quite good correspondence between the non-invasive estimates obtained from SFOAEs and the tuning obtained from auditory-nerve fibers. Similarity between budgerigar and chicken are harder to ascertain with the way the data are presented.

Weaknesses:

- The comparison of SFOAEs and auditory-nerve tuning curves in the most interesting regions (beyond 3.5 kHz, where some perceptual anomalies seem to occur in some previous data), relies on an extrapolation of the data from the chicken.<br /> - No new behavioral data are presented, so the comparisons made in the paper are between studies separated by decades. None of the behavioral studies cited used the more current techniques that have been claimed to provide a behavioral estimate of cochlear tuning.

Reviewer #2 (Public review):

Summary:

By combining bioinformatical and experimental approaches, the authors address the question why several vertebrate lineages lack specific genes of the necroptosis pathway, or those that regulate the interplay between apoptosis and necroptosis. The lack of such genes was already known from previous publications, but the current manuscript provides a more in-depth analysis and also uses experiments in human cells to address the question of functionality of the remaining genes and pathways. A particular focus is placed on RIPK3/RIPK1 and their dual roles in inducing NFkB and/or necroptosis.

Strengths:

The well documented bioinformatical analyses provide a comprehensive data basis of the presence/absence of RIP-kinases, other RHIM proteins, apoptosis signaling proteins (FADD,CASP8,CASP10) and some other genes involved in these pathway. Several of these genes are known to be missing in certain animal lineages, which raises the question why their canonical binding partners are present in these species. By expressing several such proteins (both wildtype and mutants destroying particular interaction regions) in human cells, the authors succeed in establishing a general role of RIPK3 and RIPK1 in NFkB activation. This function appears to be better conserved and more universal than the necroptotic function of the RHIM proteins. The authors also scrutinize the importance of the kinase function and RHIM integrity for these separate functionalities.

Weaknesses:

A weakness of the presented study is the experimental restriction to human HEK293 cells. There are several situations where the functionality of proteins from distant organisms (like lampreys or even mussels) in human cells is not necessarily indicative of their function in native context. In some cases, these problems are addressed by co-expressing potential interaction partners, but not all of these experiments are really informative. However, I agree with the authors that it is not possible to perform all the experiments in native cells, and that comparing all proteins in the same (human) cell type allows for a better comparison.

The conclusions drawn by the authors are supported by convincing evidence. I have no doubts that this study will be very useful for future studies addressing the evolution of necroptosis and its regulation by NFkB and apoptosis.

Reviewer #3 (Public review):

In this study, the authors employ both computational and experimental methods to reveal functional conservation of RIP family kinases and associated proteins in animals, with particular focus on mammals and other major groups of vertebrates. The bionformatic part of the work involves genomic data from diverse animal groups, providing insightful data on loss and duplications patterns for RIP and other necroptosis-related genes, and positive selection signals for RIPK1/3 genes in certain mammalian clades. These findings are then extensively used for selecting species and RHIM tetrad candidates for further experiments, in which the authors demonstrate different modes of functional conservation for RIPK proteins in necroptosis and NF-kB signaling across vertebrate species.

As an only major drawback, I would mention several important findings which the authors make in the course of their research but do not pursue further in the experimental part of the paper. These include:

• An additional copy for RIPK2 (RIPK2B) found in monotremes and non-mammalian vertebrates and its functions;<br /> • The entire diversity of RHIM functional tetrad variants; of particular interest here are IQFG and IQLG tetrads specific for bats, which are known to harbor human-affecting viruses and were demonstrated to have their RIPK1/3 genes under positive selection in this study;<br /> • Functions and involvement of RIPK3 protein in NF-kB pathway in lampreys;<br /> • The mode of NF-kB activation in non-mammalian species retaining ZBP1 copies.

Further elucidation of some or all of these points in the experimental part would facilitate conceptualizing the paper's numerous findings, which otherwise might appear insufficiently scrutinized. On the other hand, I agree that at least some of them require separate studies to be elucidated in. Given the importance of the results presented in this paper, I believe these points will be further addressed in future works.

Reviewer #1 (Public review):

Summary:

The authors have provided a mechanism by which how presence of truncated P53 can inactivate function of full length P53 protein. The authors proposed this happens by sequestration of full length P53 by truncated P53. In the study, the performed experiments are well described.

Significance:

The work in significant, since it points out more mechanistic insight how wild type full length P53 could be inactivated in the presence of truncated isoforms, this might offer new opportunity to recover P53 function as treatment strategies against cancer.

Comments on latest version:

The authors have made significant effort to address my concerns using the system available to them. I find the justifications provided in the rebuttal letter and the revised figures satisfactory. My initial concerns regarding the overexpression system have been largely addressed. However, the experimental system used by the authors lacks the means to measure the effect on endogenous p53, which remains a limitation.

Reviewer #2 (Public review):

Summary:

The revised manuscript by Zhao and colleagues presents a novel and compelling investigation into the p53 isoforms, Δ133p53 and Δ160p53, which are implicated in aggressive cancer phenotypes. The primary goal of this study was to elucidate how these isoforms exert a dominant-negative impact on the activity of full-length p53 (FLp53). The authors demonstrate that the Δ133p53 and Δ160p53 isoforms display impaired binding to p53-regulated promoters. Their findings suggest that the dominant-negative effects observed are primarily due to the co-aggregation of FLp53 with Δ133p53 and Δ160p53.

Overall, the study is innovative, thoroughly executed, and supported by robust data analysis. The authors have effectively addressed the reviewers' criticisms and incorporated their suggestions in this revised manuscript.

Significance:

The manuscript by Zhao and colleagues presents a novel and compelling study on the p53 isoforms, Δ133p53 and Δ160p53, which are associated with aggressive cancer types. The main objective of the study was to understand how these isoforms exert a dominant negative effect on full-length p53 (FLp53). The authors discovered that the Δ133p53 and Δ160p53 proteins exhibit impaired binding to p53-regulated promoters. The data suggest that the predominant mechanism driving the dominant-negative effect is the co-aggregation of FLp53 with Δ133p53 and Δ160p53.

Reviewer #1 (Public review):

Summary:

The concept that trained immunity, as defined, can be beneficial to subsequent immune challenges is important in the broad context of health and disease. The significance of this manuscript is the finding that trained immunity is actually a two-edged sword, herein, detrimental in the context of LPS-induced Acute Lung Injury that is mediated by AMs.

Strengths:

Several lines of evidence in different mouse models support this conclusion. The postulation that differences in immune responses in individuals is linked to differences in the mycobiome and consequent B-glucan makeup is provocative.

Weaknesses:

However, the findings that the authors state are relevant to sepsis are actually confined to a specific lung injury model and not classically-defined sepsis, the ontogeny of the reprogrammed AMs is uncertain, and links in the proposed signaling pathways need to be strengthened.

Comments on the latest version:

The manuscript is improved with further clarifications and additional experimentation. My prior concerns are addressed.

Reviewer #2 (Public review):

Summary:

Prével et al. present an in vivo study in which they reveal an interesting aspect of β-glucan, a known inducer of enhanced immune responses termed trained immunity in sterile inflammation. The authors can show that β-glucan's can reprogram alveolar macrophages (AMs) in the lungs through neutrophils and IFNγ signaling and independent of Dectin1. This reprogramming occurs at both transcriptional and metabolic levels. After β-glucan training, LPS induced sterile inflammation exacerbated acute lung injury via enhanced immunopathology. These findings highlight a new aspect of β-glucan's role in trained immunity and its potential detrimental effects when enhanced pathogen clearance is not required.

Strengths:

- This manuscript is well-written and effectively conveys its message.

- The authors provide important evidence that β-glucan training is not solely beneficial but depending on the context can also enhance immunopathology. This will be important to the field for two reasons. It shows again that trained immunity can also be harmful. Jentho et al. 2021 had already provided further evidence for this aspect. And it highlights anew that LPS application is an insufficient infection model.

Original weaknesses noted:

- Only a little physiological data from the in vivo models is provided.

- Effects in histology appear to be rather weak.

Comments on latest version:

The authors have revised the new version according to my suggestions or responded in a sufficient manner to my requests, with one exception. I recommend to rename TNF as explained by Grimstad in JAMA Dermatol. 2016;152(5):557.

Reviewer #1 (Public review):

Summary:

This manuscript presents a study on expectation manipulation to induce placebo and nocebo effects in healthy participants. The study follows standard placebo experiment conventions with the use of TENS stimulation as the placebo manipulation. The authors were able to achieve their aims. A key finding is that placebo and nocebo effects were predicted by recent experience, which is a novel contribution to the literature. The findings provide insights into the differences between placebo and nocebo effects and the potential moderators of these effects.

Specifically, the study aimed to:

(1) assess the magnitude of placebo and nocebo effects immediately after induction through verbal instructions and conditioning<br /> (2) examine the persistence of these effects one week later, and<br /> (3) identify predictors of sustained placebo and nocebo responses over time.

Strengths:

An innovation was to use sham TENS stimulation as the expectation manipulation. This expectation manipulation was reinforced not only by the change in pain stimulus intensity, but also by delivery of non-painful electrical stimulation, labelled as TENS stimulation.

Questionnaire-based treatment expectation ratings were collected before conditioning and after conditioning, and after the test session, which provided an explicit measure of participants' expectations about the manipulation.

The finding that placebo and nocebo effects are influenced by recent experience provides a novel insight into a potential moderator of individual placebo effects.

Weaknesses:

There are a limited number of trials per test condition (10), which means that the trajectory of responses to the manipulation may not be adequately explored.

On day 8, one stimulus per stimulation intensity (i.e., VAS 40, 60, and 80) was applied before the start of the test session to re-familiarise participants with the thermal stimulation. There is a potential risk of revealing the manipulation to participants during the re-familiarization process, as they were not previously briefed to expect the painful stimulus intensity to vary without the application of sham TENS stimulation.

The differences between the nocebo and control conditions in pain ratings during conditioning could be explained by the differing physiological effects of the different stimulus intensities, so it is difficult to make any claims about expectation effects here.

A randomisation error meant that 25 participants received an unbalanced number of 448 trials per condition (i.e., 10 x VAS 40, 14 x VAS 60, 12 x VAS 80).

Reviewer #2 (Public review):

Summary:

Kunkel et al aim to answer a fundamental question: Do placebo and nocebo effects differ in magnitude or longevity? To address this question, they used a powerful within-participants design, with a very large sample size (n=104), in which they compared placebo and nocebo effects - within the same individuals - across verbal expectations, conditioning, testing phase, and a 1-week follow-up. With elegant analyses, they establish that different mechanisms underlie the learning of placebo vs nocebo effects, with the latter being acquired faster and extinguished slower. This is an important finding for both the basic understanding of learning mechanisms in humans and for potential clinical applications to improve human health.

Strengths:

Beyond the above - the paper is well-written and very clear. It lays out nicely the need for the current investigation and what implications it holds. The design is elegant, and the analyses are rich, thoughtful, and interesting. The sample size is large which is highly appreciated, considering the longitudinal, in-lab study design. The question is super important and well-investigated, and the entire manuscript is very thoughtful with analyses closely examining the underlying mechanisms of placebo versus nocebo effects.

Weaknesses:

There were two highly addressable weaknesses in my opinion:

(1) I could not find the preregistration - this is crucial to verify what analyses the authors have committed to prior to writing the manuscript. Please provide a link leading directly to the preregistration - searching for the specified number in the suggested website yielded no results.

(2) There is a recurring issue which is easy to address: because the Methods are located after the Results, many of the constructs used, analyses conducted, and even the main placebo and nocebo inductions are unclear, making it hard to appreciate the results in full. I recommend finding a way to detail at the beginning of the results section how placebo and nocebo effects have been induced. While my background means I am familiar with these methods, other readers will lack that knowledge. Even a short paragraph or a figure (like Figure 4) could help clarify the results substantially. For example, a significant portion of the results is devoted to the conditioning part of the experiment, while it is unknown which part was involved (e.g., were temperatures lowered/increased in all trials or only in the beginning).

Reviewer #1 (Public review):

Summary:

Previous studies have shown that the MSH6 family of mismatch repair proteins contains an unstructured N-terminal domain that contains either a PWWP domain, a Tudor domain or neither and that the interaction of the histone reader domains with the appropriate histone H3 modification enhances mismatch repair, and hence reduces mutation rates in coding regions to some extent. However, the elimination of the MSH6-histone modification probably does not completely eliminate mismatch repair, although the published papers on this point do not seem definitive.

In this study, the authors perform a details phylogenetic analysis of the presence of the PWWP and Tudor domains in MSH6 proteins across the tree of life. They observe that there are basically three classes of organisms that contain either a PWWP domain, a Tudor domain, or neither. On the basis of their analysis, they suggest that this represents convergent evolution of the independent acquisition of histone reader domains and that key amino acid residues in the reader domains are selected for.

Strengths:

The phylogenetic aspects of the work seem well done and the basic evolutionary conclusions of the work are well supported. The basic evolutionary conclusions are interesting and there is little to criticize from my perspective.

Weaknesses:

A major concern about this paper is that the authors fail to put their work into the proper context of what is already known about the N-terminus of MSH6. Further, their structural studies, which are really structural illustrations, are misleading, often incorrect, and not always helpful in addition to having been published before.

Reviewer #2 (Public review):

Summary:

In this work, Monroe JG and colleagues show a compelling case of convergent evolution in the fusion between an important mismatch repair protein (MSH6) and histone reader domains across the tree of life. These fused MSH6 readers have been shown to be important for the recruitment of MSH6 to exon-rich genome locations, therefore improving the efficiency of reducing mutation rates in coding regions.

Comparative genomic analyses here performed revealed independent instances of MSH6 fusion with histone readers in plants and metazoa with several instances of putative loss (or gain) across the phylogeny. The work also unveiled instances of MSH6 fusion putatively interesting domains in fungi which might be worth exploring in the future.

The authors also show potential signatures of purifying selection in functional amino acids MSH6 histone readers.

Overall the approach is adequate for the questions proposed to be answered, the analyses are rigorous and support the authors' claims.

DNA repair genes are essential to maintain genome stability and fidelity, and alterations in these pathways have been associated with hypermutation phenotypes in the context for instance of cancer in humans, with sometimes implications in treatment resistance. This is an important work that contributes to our understanding of the evolutionary consequences of the evolution of epigenome-targeted DNA repair.

Strengths:

The methods used are adequate for the questions and support the results. The search for MSH6 fusions was rigorous and conservative, which strengthens the significance of the claims on the evolutionary history of these fusion events.

Weaknesses:

I did not identify any major weaknesses, but please see my suggestions/recommendations.

Reviewer #3 (Public review):

Summary:

In the manuscript entitled "Convergent evolution of epigenome recruited DNA repair across the Tree of Life", Monroe et al. investigate bioinformatically how some important mechanisms of epigenome-targeted DNA repair evolved at the tree of life scale. They provide a clear example of convergent evolution of these mechanisms between animals and plants, investigating more than 4000 eukaryotic genomes, and uncovering a significant association between gain/retention of such mechanisms with genome size and high intron content, that at least partially explains the evolutionary patterns observed within major eukaryotic lineages.

Strengths:

The manuscript is well written, clear, and understandable, and has potentially broad interest. It provides a thorough analysis of the evolution of MSH6-related DNA repair mechanisms using more than 4000 eukaryotic genomes, a pretty impressive number allowing to identify both large-scale (i.e. kingdoms) as well as shorter-scale (i.e. phyla, orders) evolutionary patterns. Moreover, despite providing no experimental validation, it investigates with a sufficient degree of depth, a potential relationship between gain/retention of epigenome recruited DNA repair mediated by MSH6 and genomic, as well as life-history (population size, body mass, lifespan), traits. In particular, it provides convincing evidence for a causative effect between genome size/intron content and the presence/absence of this mechanism. Moreover, it stimulates further scientific investigation and biological questions to be addressed, such as the conservation of epigenomes across the tree of life, the existence of potential trade-offs in gain/retention vs. loss of such mechanisms, and the relationship between these processes, mutation rate heterogeneity, and evolvability.

Weaknesses:

Despite the interesting and necessary insights provided on (1) the evolution of DNA repair mechanisms, and (2) the convergent evolution of molecular mechanisms, this bioinformatic study emanates from studies in humans and Arabidopsis already showing signs of potential convergent evolution in aspects of epigenome-recruited DNA repair. For this, this study, although bioinformatically remarkably thorough, does not come as a surprise, potentially lowering its novelty.

What could have increased further its impact, interest, and novelty could have been a more comprehensive understanding of the causative processes leading to gain/retention vs. loss of MSH6-related epigenetic recruitment mechanisms. The authors provide interesting associations with life-history traits (yet not significant), and significant links with genome size and intron content only at the theoretical level. For the first aspect, the analyses could have expanded toward other life-history traits. For the second, maybe it could have been even possible to tackle experimentally some of the generated questions, functionally in some models, or deepened using specific case studies.

Reviewer #1 (Public review):

Summary:

Is peristimulus alpha (8-14 Hz) frequency and/or phase involved in shaping the length of visual and audiovisual temporal binding windows, as posited by the discrete sampling hypothesis? If so, to what extent and perceptual scenario are they functionally relevant? The authors addressed such questions by collecting EEG data during the completion of the widely-known 2-flash fusion paradigm, administered both in a standard (i.e., visual only, F2) and audiovisual (i.e., 2 flashes and 1 beep, F2B1) fashion. Instantaneous frequency estimation performed over parieto-occipital sensors revealed slower alpha rhythms right after stimulus onset in the F2B1 condition, as compared to the F2, a pattern found to correlate with the difference between modality-specific ISIs (F2B1-F2). Of note, peristimulus alpha frequency differed also between 1 vs 2 flashes reports, although in the visual modality only (i.e., faster alpha oscillations in 2 flash percept vs 1 flash). This pattern of results was reinvigorated in a causal manner via occipital tACS, which was capable of, respectively, narrowing down vs enlarging the temporal binding window of individuals undergoing 13 Hz vs 8 Hz stimulation in the F2 modality alone. To elucidate what the oscillatory signatures of crossmodal integration might be, the authors further focused on the phase of posterior alpha rhythms. Accordingly, the Phase Opposition Sum proved to significantly differ between modalities (F2B1 vs F2) during the prestimulus time window, suggesting that audiovisual signals undergo finer processing based on the ongoing phase of occipital alpha oscillations, rather than the speed at which these rhythms cycle. As a last bit of information, a computational model factoring in the electrophysiological assumptions of both the discrete sampling hypothesis and auditory-induced phase-resetting was devised. Analyses run on such synthetic data were partially able to reproduce the patterns witnessed in the empirical dataset. While faster frequency rates broadly provide a higher probability to detect 2 flashes instead of 1, the occurrence of a concurrent auditory signal in cross-modal trials should cause a transient elongation (i.e. slower frequency rate) of the ongoing alpha cycle due to phase-reset dynamics (as revealed via inter-trial phase clustering), prompting larger ISIs during F2B1 trials. Conversely, the model provides that alpha oscillatory phase might predict how well an observer dissociates sensory information from noise (i.e., perceptual clarity), with the second flash clearly perceived as such as long as it falls within specific phase windows along the alpha cycle.

Strengths:

The authors leveraged complementary approaches (EEG, tACS, and computational modelling), the results thereof not only integrate, but depict an overarching mechanistic scenario elegantly framing phase-resetting dynamics into the broader theoretical architecture posited by the discrete sampling hypothesis. Analyses on brain oscillations (either via frequency sliding and phase opposition sum) mostly appear to be methodologically sound, and very-well supported by tACS results. Under this perspective, the modelling approach serves as a convenient tool to reconcile and shed more light on the pieces of evidence gathered on empirical data, returning an appealing account on how cross-modal stimuli interplay with ongoing alpha rhythms and differentially affect multisensory processing in humans.

Weaknesses:

Some information relative to the task and the analyses is missing. For instance, it is not entirely clear from the text what the number of flashes actually displayed in explicit short trials is (1 or 2?). We believe it is always two, but it should be explicitly stated.

Moreover, the sample size might be an issue. As highlighted by a recent meta-analysis on the matter (Samaha & Romei, 2024), an underpowered sample size may very well drive null-findings relative to tACS data in F2B1 trials, in interplay with broad and un-individualized frequency targets.

Some criticality arises regarding the actual "bistability" of bistable trials, as the statistics relative to the main task (i.e., the actual means and SEMs are missing) broadly point toward a higher proclivity to report 2 instead of 1 flash in both F2B1 and F2 trials. This makes sense to some extent, given that 2 flashes have always been displayed (at least in bistable trials), yet tells about something botched during the pretest titration procedure.

Coming to the analyses on brain waves, one main concern relates to the phase-reset-induced slow-down of posterior alpha rhythms being of true oscillatory nature, rather than a mere evoked response (i.e., not sustained over time). Another question calling for some further scrutiny regards the overlooked pattern linking the temporal extent of the IAF differences between F2 and F2B1 trials with the ISIs across experimental conditions (explicit short, bistable, and explicit long). That is, the wider the ISI, the longer the temporal extent of the IAF difference between sensory modalities. Although neglected by the authors, such a trend speaks in favour of a rather nuanced scenario stemming from not only auditory-induced phase-reset alpha cycle elongation, but also some non-linear and perhaps super-additive contribution of flash-induced phase-resetting. This consideration introduces some of the issues about the computational simulation, which was modelled around the assumption of phase-resetting being triggered by acoustic stimuli alone. Given how appealing the model already is, I wonder whether the authors might refine the model accordingly and integrate the phase-resetting impact of visual stimuli upon synthetic alpha rhythms. Relatedly, I would also suggest the authors to throw in a few more simulations to explore the parameter space and assay, to which quantitative extent the model still holds (e.g. allowing alpha frequency to randomly change within a range between 8 and 13 Hz, or pivoting the phase delay around 10 or 50 ms). As a last remark, I would avoid, or at least tone down, concluding that the results hereby presented might reconcile and/or explain the null effects in Buergers & Noppeney, 2022; as the relationship between IAFs and audiovisual abilities still holds when examining other cross-modal paradigms such as the Sound-Induced Flash-Illusion (Noguchi, 2022), and the aforementioned patterns might be due to other factors, such as a too small sample size (Samaha & Romei, 2024).

Reviewer #2 (Public review):

Summary:

The authors used a visual flash discrimination task in which two flashes are presented one after another with different inter-stimulus intervals. Participants either perceive one flash or two flashes. The authors show that the simultaneous presence of an auditory input extends the temporal window of integration, meaning that two flashes presented shortly after one another are more likely to be perceived as a single flash. Auditory inputs are accompanied by a reduction in alpha frequency over visual areas. Prestimulus alpha frequency predicts perceptual outcomes in the absence of auditory stimuli, whereas prestimulus alpha phase becomes the dominant predictor when auditory input is present. A computational model based on phase-resetting theory supports these findings. Additionally, a transcranial stimulation experiment confirms the causal role of alpha frequency in unimodal visual perception but not in cross-modal contexts.

Strengths:

The authors elegantly combined several approaches-from behavior to computational modeling and EEG-to provide a comprehensive overview of the mechanisms involved in visual integration in the presence or absence of auditory input. The methods used are state-of-the-art, and the authors attempted to address possible pitfalls.

Weaknesses:

The use of Bayesian statistics could further strengthen the paper, especially given that a few p-values are close to the significance threshold (lines 162 & 258), but they are interpreted differently in different cases (absence of effect vs. trend).

Overall, these results provide new insights into the role of alpha oscillations in visual processing and offer an interesting perspective on the current debate regarding the roles of alpha phase and frequency in visual perception. More generally, they contribute to our understanding of the neural dynamics of multisensory integration.

Reviewer #3 (Public review):

Summary:

The authors investigated the impact of an auditory stimulus on visual integration at the behavioral, electrophysiological, and mechanistic levels. Although the role of alpha brain oscillations on visual perception has been widely studied, how the brain dynamics in the visual cortices are influenced by a cross-modal stimulus remains ill-defined. The authors demonstrated that auditory stimulation systematically induced a drop in visual alpha frequency, increasing the time window for audio-visual integration, while in the unimodal condition, visual integration was modulated by small variations within the alpha frequency range. In addition, they only found a role of the phase of alpha brain oscillations on visual perception in the cross-modal condition. Based on the perceptual cycles' theory framework, the authors developed a model allowing them to describe their results according to a phase resetting induced by the auditory stimulation. These results showed that the influence of well-known brain dynamics on one modality can be disrupted by another modality. They provided insights into the importance of investigating cross-modal brain dynamics, and an interesting model that extends the perceptual cycle framework.

Strengths:

The results are supported by a combination of various, established experimental and analysis approaches (e.g., two-flash fusion task, psychometric curves, phase opposition), ensuring strong methodological bases and allowing direct comparisons with related findings in the literature.

The model the authors proposed is an extension and an improvement of the perceptual cycle's framework. Interestingly, this model could then be tested in other experimental approaches.

Weaknesses:

There is an increasing number of studies in cognitive neuroscience showing the importance of considering inter-individual variability. The individual alpha frequency (IAF) varied from 8 to 13 Hz with a huge variability across participants, and studies have shown that the IAF influenced visual perception. Investigating inter-individual variations of the IAF in the reported results would be of great interest, especially for the model.

Although the use of non-invasive brain stimulation to infer causality is a method of great interest, the use of tACS in the presented work is not optimal. Instead of inducing alpha brain oscillations in visual cortices, the use of tACS to activate the auditory cortex instead of the actual auditory stimulation would have presented more interest.

Reviewer #1 (Public Review):

Summary:

In this paper, the authors aimed to test the ability of bumblebees to use bird-view and ground-view for homing in cluttered landscapes. Using modelling and behavioural experiments, the authors showed that bumblebees rely most on ground-views for homing.

Strengths:

The behavioural experiments are well-designed, and the statistical analyses are appropriate for the data presented. 

Weaknesses:

Views of animals are from a rather small catchment area.

Missing a discussion on why image difference functions were sufficient to explain homing in wasps (Murray and Zeil 2017).

The artificial habitat is not really 'cluttered' since landmarks are quite uniform, making it difficult to infer ecological relevance.

Reviewer #2 (Public Review):

Summary:

In a 1.5m diameter, 0.8m high circular arena bumblebees were accustomed to exiting the entrance to their nest on the floor surrounded by an array of identical cylindrical landmarks and to forage in an adjacent compartment which they could reach through an exit tube in the arena wall at a height of 28cm. The movements of one group of bees were restricted to a height of 30cm, the height of the landmark array, while the other group was able to move up to heights of 80cm, thus being able to see the landmark array from above.

During one series of tests, the flights of bees returning from the foraging compartment were recorded as they tried to reach the nest entrance on the floor of the arena with the landmark array shifted to various positions away from the true nest entrance location. The results of these tests showed that the bees searched for the net entrance in the location that was defined by the landmark array.

In a second series of tests, access to the landmark array was prevented from the side, but not from the top, by a transparent screen surrounding the landmark array. These tests showed that the bees of both groups rarely entered the array from above, but kept trying to enter it from the side.<br /> The authors express surprise at this result because modelling the navigational information supplied by panoramic snapshots in this arena had indicated that the most robust information about the location of the nest entrance within the landmark array was supplied by views of the array from above, leading to the following strong conclusions:<br /> line 51: "Snapshot models perform best with bird's eye views";<br /> line 188: "Overall, our model analysis could show that snapshot models are not able to find home with views within a cluttered environment but only with views from above it.";<br /> line 231: "Our study underscores the limitations inherent in snapshot models, revealing their inability to provide precise positional estimates within densely cluttered environments, especially when compared to the navigational abilities of bees using frog's-eye views."

Strengths:

The experimental set-up allows for the recording of flight behaviour in bees, in great spatial and temporal detail. In principle, it also allows for the reconstruction of the visual information available to the bees throughout the arena.

Weaknesses:

Modelling:<br /> Modelling left out information potentially available to the bees from the arena wall and in particular from the top edge of the arena and cues such as cameras outside the arena. For instance, modelled IDF gradients within the landmark array degrade so rapidly in this environment, because distant visual features, which are available to bees, are lacking in the modelling. Modelling furthermore did not consider catchment volumes, but only horizontal slices through these volumes.

Behavioural analysis:<br /> The full potential of the set-up was not used to understand how the bees' navigation behaviour develops over time in this arena and what opportunities the bees have had to learn the location of the nest entrance during repeated learning flights and return flights.

Without a detailed analysis of the bees' behaviour during 'training', including learning flights and return flights, it is very hard to follow the authors' conclusions. The behaviour that is observed in the tests may be the result of the bees' extended experience shuttling between the nest and the entry to the foraging arena at 28cm height in the arena wall. For instance, it would have been important to see the return flights of bees following the learning flights shown in Figure 17.

Basically, both groups of bees (constrained to fly below the height of landmarks (F) or throughout the height of the arena (B)) had ample opportunities to learn that the nest entrance lies on the floor of the landmark array. The only reason why B-bees may not have entered the array from above when access from the side was prevented, may simply be that bumblebees, because they bumble, find it hard to perform a hovering descent into the array.

General:

The most serious weakness of the set-up is that it is spatially and visually constrained, in particular lacking a distant visual panorama, which under natural conditions is crucial for the range over which rotational image difference functions provide navigational guidance. In addition, the array of identical landmarks is not representative of natural clutter and, because it is visually repetitive, poses un-natural problems for view-based homing algorithms. This is the reason why the functions degrade so quickly from one position to the next (Figures 9-12), although it is not clear what these positions are (memory0-memory7).<br /> In conclusion, I do not feel that I have learnt anything useful from this experiment; it does suggest, however, that to fully appreciate and understand the homing abilities of insects, there is no alternative but to investigate these abilities in the natural conditions in which they have evolved.

Reviewer #1 (Public review):

Summary:

This paper tackles an important question: What drives the predictability of pre-stimulus brain activity? The authors challenge the claim that "pre-onset" encoding effects in naturalistic language data have to reflect the brain predicting the upcoming word. They lay out an alternative explanation: because language has statistical structure and dependencies, the "pre-onset" effect might arise from these dependencies, instead of active prediction. The authors analyze two MEG datasets with naturalistic data.

Strengths:

The paper proposes a very reasonable alternative hypothesis for claims in prior work. Two independent datasets are analyzed. The analyses with the most and least predictive words are clever, and nicely complement the more naturalistic analyses.

Weaknesses:

I have to admit that I have a hard time understanding one conceptual aspect of the work, and a few technical aspects of the analyses are unclear to me. Conceptually, I am not clear on why stimulus dependencies need to be different from those of prediction. Yes, it is true that actively predicting an upcoming word is different from just letting the regression model pick up on stimulus dependencies, but given that humans are statistical learners, we also just pick up on stimulus dependencies, and is that different from prediction? Isn't that in some way, the definition of prediction (sensitivity to stimulus dependencies, and anticipating the most likely upcoming input(s))?

This brings me to some of the technical points: If the encoding regression model is learning one set of regression weights, how can those reflect stimulus dependencies (or am I misunderstanding which weights are learned)? Would it help to fit regression models on for instance, every second word or something (that should get rid of stimulus dependencies, but still allow to test whether the model predicts brain activity associated with words)? Or does that miss the point? I am a bit unclear as to what the actual "problem" with the encoding model analyses is, and how the stimulus dependency bias would be evident. It would be very helpful if the authors could spell out, more explicitly, the precise predictions of how the bias would be present in the encoding model.

Reviewer #2 (Public review):

Summary:

At a high level, the reviewers demonstrate that there is an explanation for pre-word-onset predictivity in neural responses that does not invoke a theory of predictive coding or processing. The paper does this by demonstrating that this predictivity can be explained solely as a property of the local mutual information statistics of natural language. That is, the reason that pre-word onset predictivity exists could simply boil down to the common prevalence of redundant bigram or skip-gram information in natural language.

Strengths:

The paper addresses a problem of significance and uses methods from modern NeuroAI encoding model literature to do so. The arguments, both around stimulus dependencies and the problems of residualization, are compellingly motivated and point out major holes in the reasoning behind several influential papers in the field, most notably Goldstein et al. This result, together with other papers that have pointed out other serious problems in this body of work, should provoke a reconsideration of papers from encoding model literature that have promoted predictive coding. The paper also brings to the forefront issues in extremely common methods like residualization that are good to raise for those who might be tempted to use or interpret these methods incorrectly.

Weaknesses:

The authors don't completely settle the problem of whether pre-word onset predictivity is entirely explainable by stimulus dependencies, instead opting to show why naive attempts at resolving this problem (like residualization) don't work. The paper could certainly be better if the authors had managed to fully punch a hole in this.

Reviewer #3 (Public review):

Summary:

The study by Schönmann et al. presents compelling analyses based on two MEG datasets, offering strong evidence that the pre-onset response observed in a highly influential study (Goldstein et al., 2022) can be attributed to stimulus dependencies, specifically, the auto-correlation in the stimuli-rather than to predictive processing in the brain. Given that both the pre-onset response and the encoding model are central to the landmark study, and that similar approaches have been adopted in several influential works, this manuscript is likely to be of high interest to the field. Overall, this study encourages more cautious interpretation of pre-onset responses in neural data, and the paper is well written and clearly structured.

Strengths:

(1) The authors provide clear and convincing evidence that inherent dependencies in word embeddings can lead to pre-activation of upcoming words, previously interpreted as neural predictive processing in many influential studies.

(2) They demonstrate that dependencies across representational domains (word embeddings and acoustic features) can explain the pre-onset response, and that these effects are not eliminated by regressing out neighboring word embeddings - an approach used in prior work.

(3) The study is based on two large MEG datasets, showing that results previously observed in ECoG data can be replicated in MEG. Moreover, the stimulus dependencies appear to be consistent across the two datasets.

Weaknesses:

(1) To allow a more direct comparison with Goldstein et al., the authors could consider using their publicly available dataset.

(2) Goldstein et al. already addressed embedding dependencies and showed that their main results hold after regressing out the embedding dependencies. This may lessen the impact of the concerns about self-dependency raised here.

(3) While this study shows that stimulus dependency can account for pre-onset responses, it remains unclear whether this fully explains them, or whether predictive processing still plays a role. The more important question is whether pre-activation remains after accounting for these confounds.

Reviewer #1 (Public review):

Summary:

This fMRI study shows that two regions of the visual cortex (BA18 and BA19) of blind and sighted individuals carry information about the physical similarity of objects denoted by words. This effect was found for written words (Braille in blind, visual in sighted) but not spoken words. The evidence complements earlier studies reporting physical similarity effects in the occipitotemporal cortex of blind and sighted individuals (e.g., Peelen et al., 2014).

Strengths:

The study addresses an important question in the fields of neural plasticity and visual cortex organization. The study is generally well-conducted and the findings are clearly presented.

Weaknesses:

While the evidence is statistically strong, it is currently incomplete because of missing control analyses (see below). The framing of the results, as arguing against the pluripotent cortex account, is not entirely convincing as it was not clear that the study addressed the key predictions of that account.

Main comments:

(1) The study is framed as a test of Bedny's "cognitively pluripotent cortex" proposal (2017) that attributes the increased visual cortex response to linguistic stimuli in blind individuals to high-level cognitive functions. Key evidence for this account came from studies showing increased responses in blind visual cortex to certain grammatical manipulations and to solving mathematical equations. The current study did not include such manipulations. Instead, the current study focused on the representation of objects denoted by single words. Bedny's account did not make a strong argument that the physical similarity of word referents should be differently represented in blind and sighted individuals - if it did, please state this explicitly. Indeed, evidence that (some regions of) the visual cortex represent objects similarly in blind and sighted individuals does not seem incompatible with it.

(2) Throughout the manuscript (including the abstract) it was not clear what was meant with "visual cortex" or "visual areas"; whether this refers to early visual cortex (V1/BA17) or to visual cortex more generally (e.g., BA17-BA19, occipitotemporal cortex (MT, etc)). This is important for the theoretical arguments and for the interpretation of the results. If visual cortex = BA17, the current results point to potentially important differences between blind and sighted individuals, with the physical similarity of objects only observed in the visual cortex of the blind. If visual cortex is meant to include areas beyond BA17, the blind and sighted show similarities in the current study, although such similarities have been observed before using similar research approaches.

(3) Related to the point above, the abstract does not accurately describe the results, as it only describes the similarities between blind and sighted but not the differences. The study revealed differences between groups, particularly in BA17 - primary visual cortex. The differences between the groups are also illustrated by the strikingly different searchlight results in the two groups separately (Figure S6). These differences do not reach significance in a whole-brain-corrected contrast, but that likely reflects a lack of power (particularly for a between-group contrast).

(4) Results were found for written words but not spoken words (Figure S9). This is somewhat surprising considering that the visual cortex was more strongly activated for written words in the sighted, with this activation presumably not adding any information about the physical properties of word referents. Together with the widespread significance of clusters correlating with the physical similarity matrix (Figure 6), this raises the possibility of a confound. It would be good to ensure that this is not the case, e.g., you could create similarity matrices based on word length, word visual similarity (e.g., overlap in letters), and word frequency, and correlate these matrices with the physical similarity matrix to ensure that these correlations are not positive (or if they are, partial it out).

(5) The study included a task manipulation, with participants either judging physical or conceptual properties. This task manipulation is a central aspect of the design but does not feature anywhere in the results, and is also not discussed or introduced in the text. It would be interesting to know whether the results depend on the property (physical/conceptual) being task-relevant. But more importantly, a potential concern is that the responses in the task (given for each object using a two-response button box) correlate with physical or conceptual similarity and that this explains the fMRI findings. For example, two objects that are elongated would both receive a "yes" button press when participants answer the question "is this elongated"; these objects would also be rated as physically similar. This may apply more to physical than conceptual similarity. To exclude this possibility, the responses need to be analysed and included in the fMRI analyses, either as a regressor in the GLM or as another matrix to be partialed out at the final stage of analysis.

(4) Many of the blind participants had some residual vision (9/20 had light perception, 2/20 had contour perception); this could possibly have prevented the reorganization of visual cortex.

Reviewer #2 (Public review):

Summary:

The authors show, through rigorous and extensive analyses, that the visual cortex in both congenitally blind and sighted participants represented differences between individual words presented across sensory modalities. In both groups, the activation patterns for words in the visual cortex reflected physical, but not conceptual similarity between word referents. This suggests a similar representation for both groups of words, one derived from vision-oriented mechanisms, and does not reflect significant functional reorganization in blindness.

Strengths:

The theoretical question is sound, as is the analysis approach. The authors' literature discussion is thorough, and the writing is clear.

Weaknesses:

I have only minor concerns left open.

(1) In the representational connectivity analysis, what is the average value across the brain? The authors compare the representational correlation across brain regions to the average value, but the average itself is not reported.

(2) Can the authors add a map showing the representational connectivity values across the brain in addition to the bar plot? It would make it easier to see what networks show similar neural representation to the visual cortex.

(3) Are the participants in the behavioral experiment from which the physical and conceptual similarity between word referents were collected matching in age or education with the fMRI participants?

(4) Although there are no group differences in the correlation of the physical similarity, I think it is important to acknowledge that the effect is only significant at the searchlight level in the blind early visual cortex (Figure S6).

Reviewer #3 (Public review):

Summary:

This study examines semantic processing in the visual cortex of both congenitally blind and sighted individuals using fMRI and multivariate pattern analysis (MVPA). The key finding is that the visual cortex in both groups encodes the physical properties of word referents, rather than their conceptual similarities. These results suggest that the same representational mechanisms operate in both the blind and sighted brain.

Strengths:

(1) The findings contribute to a broader understanding of cortical reorganization and provide evidence for top-down processing of word referents, even in the absence of visual experience.

(2) The experiment incorporates both spoken and written word presentations (Braille for blind participants), ensuring that the results are not confounded by modality effects.

(3) The study employs a rigorous methodological approach, combining multivariate and univariate analyses to strengthen the validity of its findings.

(4) The paper is well-structured and clearly written, making it easy to follow.

Weaknesses:

(1) The word stimuli consists of only 20 nouns referring to concrete entities. However, in the behavioral experiment, participants rated the physical and conceptual similarity of only 30 word pairs, which represents just a subset of all possible word pair combinations. The average similarity ratings across subjects were then used to construct stimuli similarity matrices, which were correlated with the fMRI similarity matrices in the MVPA analysis. What is the rationale for presenting only a small subset of all possible word pair combinations to participants? Additionally, the instruction to rate the "conceptual similarity" of word pairs seems somewhat ambiguous. Would "conceptual similarity" correlate with "physical similarity"? Instead of subjective ratings, why not use cosine similarity scores from pretrained language models to construct the "conceptual similarity" matrices? This approach could provide a more objective and reproducible measure of conceptual similarity.

(2) There are only six questions each for assessing the physical and conceptual properties of the words in the fMRI experiment. Most of the physical property questions focus on shape-related attributes (e.g., round, angular, elongated, symmetrical), while the conceptual properties are limited to three pairs of antonyms (living/non-living, natural/manufactured, pleasant/unpleasant). These aspects seem insufficient to comprehensively characterize the physical and conceptual properties of the nouns. What was the rationale behind selecting only these six questions? Could this limited set of attributes introduce bias in how the neural representations in the visual cortex are interpreted?

(3) Two of the blind participants are right-handed, and two may have some form of contour vision. What was the rationale for including these participants? In addition, the sample size for blind participants is relatively small (N = 20). Does the sample size provide sufficient justification for the main conclusion that the visual cortex in both blind and sighted groups represents the physical properties of word referents? Additionally, could individual differences among blind participants impact the results, and were any analyses conducted to account for such variability?

(4) I appreciate the authors' effort to integrate both univariate and multivariate approaches in their analyses. However, the results appear somewhat contradictory: The MVPA results suggest similar neural representations of word referents in the visual cortex for both blind and sighted participants. However, the univariate analyses indicate higher activation in the visual cortex of blind participants. How can these two findings be reconciled? The authors attributed the increased activation in the visual cortex of blind participants to their "enhanced excitability", but what exactly does "excitability" mean in this context? Could this increased activation instead reflect an alternative neural strategy for processing semantic information in the blind brain? If so, how does this align with the claim that similar representational mechanisms exist in both blind and sighted individuals?

(5) The authors interpret their findings to suggest that the visual cortex can represent the physical properties of words even without visual experience, attributing this to top-down modulation from higher cognitive regions, which then backprojects to the visual cortex. However, it is unclear why only physical properties, and not conceptual properties, are backprojected. If higher cognitive regions modulate the visual cortex in a top-down manner, wouldn't both physical and conceptual attributes be expected to influence its activity? Could the authors clarify the mechanism that selectively supports physical property encoding over conceptual representation?

Reviewer #1 (Public review):

Summary:

It is known that the nrp operon is induced by copper deprivation and encodes the synthesis of chalkophores. The authors carried out a genetic analysis that revealed transcriptional differences for WT and Mtb∆nrp when exposed to the copper chelator tetrathiomolybdate (TTM). The authors found that copper chelation results in upregulation of genes in the chalkophore cluster as well as genes involved in the respiratory chain: including, components of the heme-dependent oxidase CytBD and subunits of the bcc:aa3 heme-copper oxidase. Utilizing several knockout variants and inhibitors, the authors showed that copper starvation survival requires chalkophore synthesis and that copper starvation results in dysfunctional bcc:aa3 oxidase. By monitoring oxygen consumption, they go on to show that copper deprivation inhibits respiration through the bcc:aa3 oxidase. Lastly, the authors compare virulence of WT Mtb, Mtb∆nrp and MtbΔnrpΔcydAB strains in mice spleen and lung. The Mtb∆nrp strain showed mild attenuation, but virulence in MtbΔnrpΔcydAB was severely attenuated and complementation with the chalkophore biosynthetic pathway restored Mtb virulence. These results suggest that chalkophore mediated protection of the respiratory chain is critical to Mtb virulence, and that redundant respiratory oxidases within Mtb provide respiratory chain flexibility that may promote host adaptation.

This new information about Mtb biology may be leveraged for drug discovery, highlighting that the Mtb respiratory pathway is a promising drug target, where one may target the Mtb chalkophore biosynthetic pathway in conjunction with CytBD, to obliterate Mtb.

Strengths: Overall, the paper is very clear and well written, with thorough and well-thought-out experimentation.

No weaknesses.

Comments on revisions:

The authors have addressed all the reviewers' comments.

Reviewer #2 (Public review):

Summary:

This is a well-written manuscript that clearly demonstrates that the nrp encoded diisonitrile chalkophore is necessary for function of the bcc-aa3 oxidase supercomplex under low copper conditions. In addition, the study demonstrates the chlakophore is important early during infection when copper sequestration is employed by the host as a method of nutritional immunity.

Strengths:

The authors use genetic approaches, including single and double mutants of chalkophore biosynthesis, and both the Mtb oxidases. Use a copper chelators to restrict copper in vitro. A strength of the work was the use of a synthesized a Mtb chalkophore analogue to show chemical complementation of the mutant nrp locus. Oxphos metabolic activity was measured by oxygen consumption and ATP levels. Importantly, the study demonstrated that chalkophore, especially in a strain lacking the secondary oxidase, was necessary for early infection and ruled out a role for adaptive immunity in the chalkophore lacking Mtb by use of SCID mice. It is interesting that after two weeks of infection and onset of adaptive immunity the chalkophore is not required, which is consistent with the host environment switching from a copper restricted to copper overload in phagosomes.

Weaknesses:

None noted

Reviewer #3 (Public review):

Summary:

In this manuscript, the group of Glickman expand on their previous studies on the function of chalkophores during growth of and infection by Mycobacterium tuberculosis. Previously, the group had shown that chalkophores, which are metallophores specific for the scavenging of copper, are induced by M. tuberculosis under copper deprivation conditions. Here, they show that chalkophores, under copper limiting conditions, are essential for the uptake of copper and maturation of a terminal oxidase, the heme-copper oxidase, cytochrome bcc:aa3. As M. tuberculosis has two redundant terminal oxidases, growth of and infection by M. tuberculosis is only moderated if both the chalkophores and the second terminal oxidase, cytochrome bd, are inhibited.