Reviewer #2 (Public review):

Summary:

The manuscript proposes interesting synaptic plasticity rules grounded in experimental data. Its main features are: (1) plasticity depends on local calcium concentration driven by presynaptic activity and is independent of somatic action potentials, (2) the rules incorporate metaplasticity, and (3) they demonstrate how a single neuron could address the feature-binding problem at the dendritic level.<br /> The work extends a previous study (https://doi.org/10.7554/eLife.97274.2), to which the author also contributed.

The author models two calcium thresholds (LTP/LTD) from two different calcium sources (NMDA/VGCC) and these thresholds are flexible (metaplasticity rule, similar to BCM) which is claimed to be necessary for successful learning of both FBP and NFBP (linear and nonlinear feature binding problem with 1 or 2 patterns). The role of each threshold seems to be is opposite and complementary. One extra condition has been added : an upper threshold for LTP. This threshold serves to stop synaptic strengthening once synapses are strong enough to evoke a plateau. With that, synapses are not strengthened to the maximal value, avoiding strong supralinear integration for irrelevant patterns.

Strengths:

The current model implements not only local synaptic plasticity but also metaplasticity and solves the FBP at the dendrite level. Another strong aspect of the model is that metaplasticity in the LTD threshold protects strengthened synapses from weakening. In this way, as the author mentioned, metaplasticity is able to protect learned patterns from being forgotten or weakened and prevent irrelevant patterns from being stored. This is a nice modelling example of metaplasticity being helpful in preventing the catastrophic interference or forgetting (as has been explicitly discussed in a recent article https://doi.org/10.1016/j.tins.2022.06.002). The author might want to briefly mention or emphasize this aspect of the model, which might be interesting also for the AI community.

Comments on revised version:

The author improved the paper significantly. He conducted new simulations on relearning. He addressed the problems and limitations, added new simulation results and reasoned better in the discussion and the introduction. Also, the figures are improved.

Reviewer #1 (Public review):

Summary:

In this study, the authors elegantly combined latent variable models (i.e., HMM, GPFA and dynamical system models) with a calcium imaging observation model (i.e., latent Poisson spiking and autoregressive calcium dynamics (AR)).

Strengths:

Integrating a calcium observation model into existing latent variable models improves significantly the inference of latent neural states compared to existing approaches such as spike deconvolution or Gaussian assumptions.

The authors also provide an open-source access to their method for direct application to calcium imaging data analysis.

Weaknesses:

As acknowledged by the authors, their method is dependent on the quality of calcium traces extraction from fluorescence videos. It should be noted that this limitation applies to alternative strategies.

While the contribution of this study should prove useful for researchers using calcium imaging, the novelty is limited, as it consists of an integration of the calcium imaging model from Ganmor et al. 2016 with existing LVM frameworks.

Comments on revised version.

The authors addressed my comments and I have no further concerns.

Reviewer #2 (Public review):

Summary:

This compelling study proposes a framework to implement latent variable models using population level calcium imaging data. The study incorporates autoregressive dynamics and latent Poisson spiking to improve inference of latent states across different model classes including HMMs, Gaussian Process Factor Analysis and nonlinear dynamical systems models. This approach allows for a more seamless integration of existing methods typically used with spiking data to apply on calcium imaging data. The authors test the model on piriform cortex recordings as well as a biophysical simulator to validate their methods. This approach promises to have wide usability for neuroscientists using large population level calcium imaging.

Strengths:

The strength of this study is the flexibility in the choice of models and relatively easy adaptation to user-specific use cases.

Weaknesses:

The weakness of the study lies in its limited validation of biological calcium imaging data. Calcium dynamics in a task-specific context in a sensory brain region might be very different from slower dynamics in a region of integration.

Reviewer #3 (Public review):

Summary:

S. Keeley & collaborators propose a computational approach to infer time-varying latent variables directly from calcium traces (e.g., obtained with 2p imaging) without the need for deconvolving the traces into spike trains in a preliminary, independent step. Their approach rests on 1 of 3 families of latent models: GPFA, HMM and dynamical systems - which they augment with an observation model that maps latent variables to fluorescence traces. They validate their approach on simulated data as well as a single real dataset, showing that the approach improves latent variable inference and model fitting, compared to more traditional approaches (although not directly compared with the 2-step one; see below). They provide a GitHub repository with code to fit their models (which I have not tested).

Strengths:

The approach is sound and well-motivated. The authors are specialists of latent variable models. The manuscript is succinct, well-written and the figures are clear. I particularly liked the diversity of latent models considered, in particular latent models with continuous (GPFA) vs. discrete (HMM) dynamics, which are useful for characterizing different types of neural computations. The validation on both simulated and real data is convincing.

Weaknesses:

The main weakness point that I see is that the approach is tested only on a single real dataset (odor response dataset). The other model fits are obtained from simulated data. While the results are convincing, it would be useful to see the approach tested on other datasets, for instance datasets with different brain areas, different behavioral conditions, or different calcium indicators. This would help assess the generality of the approach and its robustness to different experimental conditions.

Reviewer #1 (Public review):

In this work, Frey and colleagues have carried out a very large study of α-synuclein polymorphism as a function of aggregation conditions and sample preparation. They provide valuable insight into the many critical factors affecting α-synuclein polymorphism, thereby illuminating the need for detailed reporting in the literature as well as both rigorous and detail-oriented protocols when working with this protein. Indeed, their observations are in line with the difficulties of reproducing structural outcomes across different laboratories and experiments. The authors must be complemented on their openness about the difficulties experienced and the thoroughness of their work. Efforts like these are going to be crucial to achieve an understanding of the unparalleled structural plasticity of α-synuclein amyloid fibrils. It is particularly notable that the authors have managed to optimize protocols to form single-polymorph aggregation reactions with high reproducibility.

In this work, the authors focus on the influence of α-synuclein purity in aggregation reactions. They find that using reverse-phase HPLC to purify the protein significantly alters the aggregation behaviour. It is interesting, and rather uncommon in the field, to use reverse-phase HPLC as a final purification step, rather than SEC, which is commonly used in many laboratories. It would be useful to compare this new protocol even more directly and extensively with the commonly used SEC protocol. When mentioning their previously published work, it should be mentioned explicitly how the protein was purified in these previous studies.

On the point of protein purification, the authors lyophilize their protein prior to storage. In their work, they also find that pre-aggregation oligomer formation alters the aggregation pathway of α-synuclein. While they demonstrate that this can be solved by appropriate filtration, it should be discussed why the lyphilizaiton step was not reconsidered/omitted given that this process is known to facilitate oligomer formation. Do the authors have experience with aggregation studies using α-synuclein that has not undergone lyophilisation and are able to comment on the influence of this step in the protocol?

The authors make note of several degradation products affecting their aggregation reactions, which is why they employ a much more thorough purification protocol. However, they also point out that some of the degradation products found at the end of their reaction could form during the reaction itself. Unfortunately, they never investigate this further. In particular, it would be very useful to know if different aggregation conditions (pH, salt, agitation) lead to different and characteristic degradation patterns. HPLS/mass spec of the supernatant at the end of each aggregation reaction would have been a very insightful thing to do.

With respect to degradation products, in this work a NΔ4-variant is produced to mimic a disease-relevant degradation product and indeed it is found to alter the structural outcome even at low relative concentrations (5%). Have the authors investigated the minimal fraction of the NΔ4 variant necessary to still influence the structural outcome of the predominant WT protein? This type of analysis could have significant relevance to disease-related analysis, where several variants (truncations and PTM variants) are present in trace amounts.

While on this topic, the authors note that in several of their type 5 fibrils, they find unresolved peptide fragments in their cryo-EM structures. Can the authors speculate if these fragments are indeed peptide degradation products or residues wrapping around the fibril originating from the fibril-incorporated protein?

In this work, the authors have performed an extensive study of α-synuclein polymorphism. However, despite generating what is likely the largest single data set of fibril structures, they perform very little quantitative analysis of their data. It would be interesting to analyse the relative abundance of fibril polymorphs produced in each reaction. Perhaps from the particle-picking data it could be estimated the relative abundance of each polymorph as well as non-resolved fibrils to generate a more nuanced view of polymorphism beyond overall classifications of the resolved structures. Indeed, from such data it could also be studied if certain protofilaments are more prone to pair in asymmetric fibril structures over others or if fibril asymmetry can be attributed to random pairing of protofilaments in accord with their abundance. This latter point is particularly interesting for the type 1 fibrils. Perhaps, the propensity of α-synuclein to form specific symmetries could also be estimated.

The authors note that pH is a strong factor in determining polymorph selection. This does indeed appear to be the case, but other parameters do not appear to show any clear trend. Have the authors investigated the influence of aggregation parameters (agitation, duration) on structural outcomes systematically or quantitatively, such as with principal component analysis? Indeed, they also find that some fibril types that otherwise are not compatible at the same pH appear to co-exist when the shaking parameter is modified. Are the authors then confident in the claim that pH is a deterministic parameter?

It is evident from this and other work that amyloid aggregation is highly sensitive to kinetic effects. It is therefore curious that the effect of protein concentration and reaction time has not been systematically investigated. The authors have some data studying dilution series (Figure 6A) and different reaction times (reaction 56 & 57). Could the authors comment on the effects of these two parameters, and might there be more information touching upon this that could be highlighted in this work?

The authors state that this work likely underreports fibril polymorphisms in samples due to population size or data quality challenges. Could the authors, based on their extensive experience, try to quantify this statement?

Additionally, the authors point out that the current framework for classifying α-synuclein fibril polymorphism is not sufficient to describe the real complexity of this protein system. However, they do not seem to address some of the recent literature aiming to solve such issues (see Scheres 2026, Connor et al. 2025, Milchberg et al. 2025 & Price et al. 2025).

Was any biophysical/biochemical analysis performed of the many structures produced here, such as CD spectroscopy, Proteinase K digestion, dye binding or FTIR, which could act as low-resolution structure identifiers and might help to retrospectively explain some findings in the older literature? Such data would be very useful for the vast majority of researchers, who do not have access to cryo-EM.

Reviewer #2 (Public review):

Summary:

This manuscript describes insights gained during efforts to reproduce disease-relevant alpha-Synuclein (aSyn) fibrils using recombinant protein in vitro. It follows up on a similar article from this team published in 2024. Although the authors have not been able to produce fibrils with the structure of ex vivo fibrils isolated from patients, they share insights gained into which factors influence the formation of specific fibril polymorphs.

Strengths:

This is quite an unusual manuscript because it goes into minute detail about sample preparation that are usual just mentioned in the Materials and Methods sections of other manuscripts (if at all). This makes it very valuable for the scientific community working on exactly the problem of reproducing disease-relevant aSyn fibrils in vitro (which will be a major breakthrough in the field). The authors present an impressive array of cryo-EM fibril structures, some of which have not been described before.

Weaknesses:

A major concern with the manuscript is that its story and messaging are a bit murky. The authors describe a few new polymorphs, show that some polymorphs (type 1) have small variations, show that sample purity and fragmentation will influence polymorph formation, and present a helical-symmetry mystery. This all reads like a loose collection of findings without any major takeaway. Looking at Table 1, it still seems that the authors do not have a good control over any of these polymorphs. Are they able to make any of these polymorphs reliably? I think the impact of this work could be strengthened if it ended with a reliable protocol for the production of any of the polymorphs described.

A second major concern is the quality of the aggregation kinetics and their interpretation. Are these kinetics just done once per concentration? The figure caption talks about 'three independent samples' but it is unclear if this refers to the three different concentrations or NΔ4 percentages used, or true repetitions. Looking at the curves themselves, it seems that only one of the conditions was actually done in triplicate, which should be the minimum to draw conclusions. Further, it would have been helpful to characterize the kinetic data quantitatively. Finally, because there are only kinetic data for a fraction of the conditions tested, it is not clear what they add to the overall manuscript. My recommendation is to either remove the kinetics from the manuscript or substantially expand this section.

Reviewer #1 (Public review):

Summary:

The authors have assembled the genome of four local chicken breeds from China and analysed their gene content. They come to the conclusion that thousands of genes present in the current reference genome of chicken have become pseudogenized during chicken evolution and domestication. They argue that their study provides strong support for the importance of the "less-is-more" hypothesis for adaptive evolution.

Strengths:

The paper provides medium-quality genome assemblies for four individuals representing four local populations of chickens and analyses their gene content.

Weaknesses:

They have not excluded the possibility that the high rate of putative pseudogenes reflects the presence of errors in gene models, in particular in GC-rich microchromosomes that are challenging to assemble correctly. The paper contains no genotype-phenotype analysis, which means that the adaptive significance of a high rate of pseudogenization, if it exists, is unknown.

Reviewer #2 (Public review):

Summary:

The authors set out to investigate the evolutionary role of gene presence-absence variation and pseudogenization in chicken evolution and domestication. By comparing draft genome assemblies of four indigenous Chinese chicken breeds against the red junglefowl reference genome (GRCg6a) and four PacBio HiFi assemblies, the study proposes that the common ancestor possessed nearly 22,000 genes, and that each domestic lineage independently lost thousands of genes (identifying ~8,000 dispensable genes). The authors conclude that massive loss of function and pseudogenization represent major drivers of chicken evolution under the "less-is-more" hypothesis.

While the concept that gene loss can drive phenotypic diversification during domestication is compelling, the results do not convincingly support the central conclusions. The scale of reported gene loss and the specific patterns of pseudogenization appear to be potentially driven by well-known genome assembly gaps, annotation errors, and sequencing dropouts rather than genuine evolutionary events, and the authors do not provide enough convincing evidence that this is not the case.

Strengths:

(1) The study addresses an important and timely evolutionary question regarding the role of gene loss and loss-of-function variation in animal domestication.

(2) The inclusion of multiple indigenous Chinese chicken breeds alongside high-accuracy PacBio HiFi assemblies provides a valuable comparative genomic dataset.

(3) The authors attempt to evaluate pseudogene transcription using RNA-seq data and check for transcript isoforms that bypass candidate loss-of-function mutations.

Weaknesses:

(1) Unvalidated gene and pseudogene annotations: Long-read and consensus genome assemblies are known to suffer from residual indel errors that create artificial frameshifts and premature stop codons. The frequency of predicted pseudogenes in this study (~3.5%-4.5%) aligns closely with expected baseline annotation error rates. Although the authors state in their Methods that mutations were validated using short reads, this validation is never quantitatively demonstrated or shown in the results. The fact that most proposed pseudogenes are actively transcribed and lack a paralog strongly suggests that many are intact, functional genes affected by sequencing or annotation artifacts.

(2) Assembly gaps and GC-bias mistaken for gene loss: The claim that ancestral chickens possessed ~22,000 protein-coding genes and lost thousands of genes in only ~10,000-50,000 years is inconsistent with the evolutionary conservation of avian genomes. The missing genes are enriched for high GC content and preferentially located on microchromosomes. Avian microchromosomes and dot chromosomes are notoriously GC-rich, repeat-dense, and prone to severe assembly gaps in non-telomere-to-telomere assemblies. The reported gene absences reflect assembly fragmentation and coverage dropouts rather than evolutionary deletions.

(3) Lack of synteny validation: Genuine gene absence requires demonstrating conserved collinear synteny of flanking orthologous genes with an unambiguous sequence deletion at the locus. Relying on sequence alignment or short-read mapping failures across fragmented scaffolds substantially inflates false-positive gene loss calls.

(4) Positional bias of pseudogenization mutations: The observed concentration of pseudogenization mutations in the terminal 10% of coding sequences (the "bathtub" distribution) is characteristic of alignment boundary artifacts and non-canonical translation start/stop annotations, rather than positive selection to disrupt gene ends. Mutations in the terminal 3' region often produce functional proteins with slightly altered C-termini rather than complete loss of function.

(5) Inconsistent terminology: The manuscript alternates between identifying pseudogenes as unitary (lacking a functional paralog in the same genome) and evaluating sequence identity against "parental genes," creating substantial confusion regarding whether loci are duplicated paralogs or orthologous reference genes.

Reviewer #3 (Public review):

Summary:

The authors reanalyze genome assemblies of four indigenous chicken breeds from Yunnan Province together with the red jungle fowl reference (GRCg6a), and search for genes with disrupted protein-coding sequences. They catalog candidate pseudogenes and missing genes to estimate that 7,993 of the ancestral genes are dispensable. They characterize the positional distribution of pseudogenization mutations along coding sequences, their fixation in breeds, their estimated ages, and their pathway enrichments. Most results are replicated in four independent PacBio HiFi-based chicken assemblies. From the biased position of pseudogenization mutations toward CDS ends, their frequent fixation, and the phylogenetic signal in gene-loss patterns, the authors conclude that large-scale loss of function is a major driver of chicken evolution and domestication, consistent with the "less-is-more" hypothesis.

Strengths:

The catalog itself is a substantial resource: the comparison spans multiple closely related genomes, the main patterns are checked in a second, independently assembled set of HiFi genomes, and population resequencing data are used to ask whether the pseudogenization mutations are fixed rather than segregating. The finding that candidate loss-of-function genes are under relaxed purifying selection is well supported. The question of what gene loss contributes to domestication is worth asking, and this is a useful dataset for asking it.

Weaknesses:

The finding that genes carrying disruptive mutations are under relaxed selection is not particularly surprising, and the more interesting claim, that the observed patterns reflect positive selection for gene loss, is less certain in my opinion.

(1) Relaxed purifying selection versus positive selection. The bias of pseudogenization mutations toward the two ends of coding sequences is interpreted as positive or artificial selection, along with elevated dN/dS. But the alternative, that disruptive mutations at gene ends are simply better tolerated, is equally consistent with the results. Several mechanisms would produce this pattern under relaxed constraint without positive selection per se: alternative downstream start sites that rescue 5-prime disruptions; the small fraction of protein truncated by 3-prime disruptions; and the enrichment of disordered regions at protein termini.

(2) The functional status of the pseudogenes is assumed, not demonstrated. Genome-scale work cannot be expected to validate individual genes, but the language of the paper should reflect the candidate status of these calls. Nearly all predicted pseudogenes (~95%) were reported as transcribed in multiple tissues. It is possible for a nonfunctional coding sequence to retain intact regulatory sequences, but the observation deserves more attention in the paper, particularly because transcripts carrying premature termination codons can be the targets of nonsense-mediated decay, which is not discussed. These remain candidate pseudogenes defined by the presence of a putatively large-effect mutation (e.g. premature stop or frameshift).

(3) What "missing" means. For a gene to be scored as completely absent, it could be genuinely deleted, or its allele could be diverged enough that annotation and orthology/mapping no longer detect it. These are different phenomena. Related, since most pseudogenization mutations are reported as fixed or nearly fixed in their populations, the history of alleles matters: it is not clear how the authors established which state is derived, and whether the reference sequence assumed to be functional is in fact the "functional" version.

(4) Limited biological insight into domestication. The main biological interpretation rests on hierarchical clustering of dispensable genes followed by ontology enrichment within clusters (Figure 7a), with narrative connections to breed phenotypes. Only 19.6% of dispensable genes have Gene Ontology assignments, and the phenotype links are speculative. The section on the subspecies origin of the GRCg6a reference is only loosely connected to the loss-of-function story, and the population-genetic analysis supporting it is thin as described.

Reviewer #1 (Public review):

Summary:

The CATCHR complexes are a family of five multisubunit complexes that act in vesicle tethering in several key transport steps. COG and GARP act at the Golgi, EARP acts on early endosomes, EXOCYST acts in transport to the cell surface, and DSL1 acts on the endoplasmic reticulum (ER). The authors have used in vivo proximity biotinylation and mass spectrometry to look for new neighbours of three of these complexes, COG, GARP, and EARP (despite the title, only two of the three are on the Golgi). The authors then follow up two of the hits, CCDC186 and WWOX, with more directed experiments.

Strengths:

The strength of the paper is that proximity biotinylation is of a high standard. To avoid overexpression, the authors express TurboID-tagged CATCHR subunits in cell lines from which the genes have been deleted. This allows them to confirm that the tagged proteins are functional and correctly located. Mass spectrometry is used to identify the proteins biotinylated in each cell line with four replicates, and the data are clearly presented in figures and supplementary tables. The authors make a good choice of proteins to follow up, as both CCDC186 and WWOX appear potentially interesting.

Weaknesses:

Overall, although the paper is based on a high-quality initial set of data, it seems somewhat incomplete and preliminary. There is undoubted value in presenting a through if descriptive set of in vivo proximity labelling data for a comprehensive overview of proteins or complexes. However, in this case the authors have only addressed three of the five CATCHR complexes, and so it is not a complete overview. It was also somewhat unclear why they examined VPS52 and VPS53, as these are present in both GARP and EARP, which adds some ambiguity, even if they did at least provide useful confirmation of some of the hits with EARP. Of course, a proximity biotinylation analysis does not need to cover all members of a family if it generates substantial biological insight.

However, the investigation of CCDC186 and WWOX does not provide significant insight into either function or mechanism. CCDC186 has already been identified in C. elegans as a protein involved in dense core vesicle biogenesis (CCCP-1, as the authors acknowledge), and work in C. elegans and mammalian cells has already linked it to EARP function. Less has been published on WWOX, but all that is found here are some small changes in Golgi appearance and glycosylation when it is reduced by RNAi. Thus, the paper falls between two stools: it is neither a comprehensive application of proximity biotinylation to the CATCHR family, nor is it the application of proximity biotinylation to reveal new insight into membrane traffic. I feel that for a broad-interest journal such, it should be one or the other of these.

Reviewer #2 (Public review):

In this manuscript, Aragon-Ramirez et al. present the first systematic proximity-interaction map of the three Golgi/endosomal CATCHR tethering complexes - COG, GARP, and EARP. They generated hTERT-RPE1 knockout lines rescued with C-terminally TurboID-tagged subunits (COG4, COG6, VPS50, VPS52, VPS53, VPS54) expressed from the COG4 promoter at near-endogenous levels, verified that each construct rescues its KO phenotype, and confirmed expected localization by immunofluorescence. Fifteen-minute biotin pulses followed by streptavidin capture and label-free DIA mass spectrometry, benchmarked against GFP-TurboID, yielded compartment-resolved neighbor lists. The central claim of this work is that each complex sits within a distinct "trafficking module" of coiled-coil tethers (CCTs), SNAREs, SM proteins, Rab GTPases, coats, and homeostasis regulators. COG neighbors nearly all Golgi golgins plus the STX5-SCFD1 fusion machinery, with COG4 and COG6 lobes showing overlapping but non-identical hierarchies - this is offered as in vivo support for a two-lobe model. GARP associates with TGN golgins GOLGA1/GOLGA4, STX16 and partners, TBC1D23, and CLINT1. EARP associates with GRIPAP1, RELCH, RAB11FIP5, and the VPS33B-VIPAS39 (CHEVI) SM complex; a VPS53 MUN-domain mutant loses VPS33B proximity while retaining VPS50 labeling. Two hits are followed up in this study. CCDC186, a poorly characterized coiled-coil protein, localizes to the TGN and, when ectopically anchored to mitochondria, captures ~60 nm vesicles - presented as direct evidence of tethering activity. WWOX, a tumor suppressor with no prior trafficking role, colocalizes with COG8 in the medial Golgi; siRNA knockdown reduces Golgi area, increases HPA and GNL lectin binding (O- and N-glycosylation defects), and displaces COPB2 from the Golgi. Based on these findings, the authors conclude that CATCHRs are not isolated tethers but organizing hubs that assemble compartment-specific tethering-and-fusion modules. Overall, this is a solid piece of work that will be of interest to cell biologists.

(1) The CCDC186 mitochondrial assay demonstrates sufficiency in a non-native context but includes no loss-of-function work, and the cargo-specificity result carrying most of the interpretation is "data not shown." At a minimum, the authors should show KO/KD and rescue data.

(2) The WWOX section rests on a single siRNA with no second oligo, no rescue, knockdown shown only by RT-PCR, and localization based entirely on overexpressed myc-tagged protein.

(3) Proximity of labeling does not distinguish direct from indirect interactions. When referring to "interactions", the authors either need to show recombinant protein binding data, or soften the tone to acknowledge potential indirect interactions.

(4) The VPS53 MUN-domain mutant design rests on a "manuscript in preparation," and the mutant's localization isn't shown (VPS50 labeling establishes complex incorporation, not correct targeting). The HEK293T WWOX replication is "data not shown." The authors should either show the data or delete these claims.

(5) References 73 and 78 are duplicates.

(6) "NZR" is used in the introduction. Should this be NRZ?

Reviewer #3 (Public review):

Summary:

This manuscript presents a comprehensive proximity proteomics analysis of Golgi- and endosome-associated CATCHR complexes, including COG, GARP, and EARP, using near-endogenously expressed TurboID-tagged subunits. The study aims to define how these tethering complexes organize distinct trafficking modules involving coiled-coil tethers, Rab-associated proteins, SNAREs, SM proteins, and other trafficking regulators. In addition to validating known associations, the authors identify CCDC186 as a candidate vesicle tether and WWOX as a potential regulator of Golgi homeostasis and glycosylation. The work provides a broad resource for understanding the spatial organization of CATCHR-associated trafficking networks. However, several conclusions require further experimental and statistical support, particularly those interpreting proximity-labeling data as physical interactions or evidence of discrete functional complexes.

Strengths:

The manuscript addresses an important question in membrane trafficking and provides a systematic comparison of the proximity interactomes of COG, GARP, and EARP complexes. The use of near-endogenously expressed TurboID-tagged subunits is a strength, as it may reduce artifacts associated with protein overexpression. The dataset is comprehensive and has the potential to serve as a valuable resource for investigators studying Golgi and endosomal trafficking. The comparative analysis identifies both known trafficking factors and potentially novel regulators, including CCDC186 and WWOX. The functional follow-up experiments add biological relevance to the proteomic findings and extend the study beyond descriptive mapping. Overall, the scope is well defined, and the manuscript proposes an interesting model in which CATCHR complexes act as organizing hubs for vesicle tethering and fusion.

Weaknesses:

A major limitation is that TurboID proximity labeling is repeatedly interpreted as evidence of physical interaction or assembly into discrete complexes, although the method primarily reports spatial proximity. The soluble GFP-TurboID control may not adequately account for enrichment caused by membrane confinement and high local protein concentration in Golgi/endosomal microdomains. Some spatial enrichment analyses do not reach statistical significance, weakening claims of compartment-specific labeling. Several low-fold-change SNARE hits are emphasized despite limited enrichment. Additional quantitative imaging is needed, including colocalization analysis of streptavidin labeling with Golgi/endosomal markers and localization of GFP-TurboID. The WWOX knockdown phenotype requires validation by rescue, independent siRNA, or CRISPR-based approaches. Several supporting data, quantifications, figure corrections, and nomenclature revisions are also needed.

Reviewer #1 (Public review):

Gary, Soret et al., present an interesting and ambitious study investigating the cellular and signaling mechanisms by which GDNF induces enteric neurogenesis in a disease model of HSCR. The manuscript combines scRNA-Seq, pharmacological inhibition, and several lineage-tracing strategies. The lineage tracing experiments in particular are technically impressive and clearly represent a substantial amount of work. The figures are generally beautiful and high quality, and the biological question is an important one.

However, while I found the study interesting, I also think that several of the major conclusions are substantially stronger than what the current data support. In particular, the scRNA-Seq dataset that the study is founded on is difficult to interpret because of the RFP-based enrichment strategy, the lack of WT reference controls, and the very non-stringent FACS gating. Several mechanistic claims are also based primarily on expression patterns or sequencing results.

Major concerns:

(1) The G4-RFP based enrichment strategy raises some concerns. The authors note that 88-90% of SOX10+ glial cells (where did this number come from, it doesn't seem to match the range in the bar graph?) and only 70% of GDNF-induced neurons. They then sort in "yield" mode using a non-stringent gating strategy, but do not provide the flow graphs in the supplements for interpretation. Consistent with this, the initial dataset contains multiple non-ENS populations, including lymphoid, myeloid cells etc, suggesting that their strategy, in addition to missing cell populations, additionally includes potential negative cells based on background fluorescence.

(2) It's not clear to me why the authors did not include a wild-type control for comparison. Due to the RFP-enrichment strategy, it is additionally difficult to compare to integrated with scRNA-seq datasets. The comparison seems important because the central question is not only whether GDNF induces neurons in the mutant colon, but whether the induced cells and associated populations resemble those found in a normal ENS.

(3) The proportional changes in Figure 2 are hard to interpret. The authors write that GDNF treatment leads to an enrichment in enteric neurons, "at the expense of" SCPs. This seems to be a strange conclusion or writing, unless the authors are suggesting that certain cell populations are additionally depleted by GDNF treatment. I think the authors should provide stronger support, or dial down on conclusions based on cluster proportions, given the sorting strategy.

(4) Some of the mechanistic conclusions are far too strong for the evidence. For instance, the claim that GDNF signals through GFRa1/2 based on only expression UMAPs is not justified. The authors should at least confirm some of the major findings via smFISH (HCR or RNA-Scope), and dial down the mechanistic claims. The pharmacological data is more supportive but still indirect. This section would be stronger if the authors validated NCAM1/FAK activation in the specific progenitor populations proposed to respond to GDNF.

(5) The inhibitors are administered during the same P4-8 window as GDNF. Given that the authors report cellular-level responses as early as 6 hours post GDNF treatment, it is important to know whether the inhibitors were already active at the time of GDNF administration. Why were the inhibitors not administered prior to the start time of GDNF treatment?

(6) The authors draw inferences and conclusions based on IHC images, but do not provide any details on the analysis procedures. For example, in Figure 3, the authors interpret changes in NCAM and FAK expression level. However, it does not appear that there are notable differences in intensity between the two timepoints. There are however, differences in signal coverage. Without knowing what was actually measured and quantified, it is not possible to interpret the results. Please provide the necessary information for all experiments in the methods section.

(7) The final results section introduces one of the more surprising claims in the paper, that a non-neural crest-derived progenitor contributes to regeneration, but the section ends quite quickly and abruptly after introducing the observation. The authors should provide additional validation or interpretations of the data.

Reviewer #2 (Public review):

Summary:

Previous work from this group demonstrated regeneration of the ENS following exogenous GDNF treatment within the aganglionic portion of the bowel in several Hirschsprung (HSCR) murine models as well as colon from HSCR patients (Soret, et. al., Gastro. 2020). Focusing on the Holstein (HolTg/Tg) HSCR mouse model, the authors build upon their prior work utilizing lineage tracing, immunohistochemistry, scRNA sequencing, and pharmacological methods to further delineate the mechanisms and cell types contributing to ENS regeneration in this context. This work adds to the knowledge base regarding natural ENS development as well as ENS generation outside of natural ENS development. Furthermore, this work provides important clinical implications for potential curatives treatments for HSCR disease.

The conclusions in the paper are overall well supported by the data with the majority of technical and model limitations openly acknowledged. Strengths include the use of scRNA sequencing, several genetic mouse models with ample, well-planned time points within experiments. However, additional analysis, clarity or more detail around experimental protocols, and broader discussion of prior studies would strengthen the manuscript by improving interpretation of the findings and placing them more clearly within the context of existing work in the field.

First, utilizing the G4-RFP transgene for ENS cell selection and subsequent scRNA sequencing of RFP+ cells, the authors nicely demonstrate the presence of known cell clusters (based on markers and analysis from prior sequencing studies) including Schwann cell precursors (SCPs), enteric glial cells (EGCs) and neuron subtypes in the aganglionic colon of HolTg/Tg GDNF-treated and untreated mice. Further use of this dataset led to the discovery of Ncam1 expression, a GDNF receptor, within all ENS cell clusters, suggesting importance of this protein in the GDNF-induced ENS regeneration phenotype. Interestingly, Ret was limited to some neuron types. On the protein level, temporal and GDNF-treatment changes in NCAM1 expression and downstream phospho-FAK(Y397) were nicely demonstrated via Western blot. Mechanistically, the importance of NCAM1 in ENS regeneration was demonstrated given pharmacologic blockade of downstream FAK signaling via PF-562271 resulted in significantly fewer GDNF-induced neurons. The paper would be strengthened here, however, if the following areas were addressed:

1) Although the GDNF-induced regeneration appears likely through an NCAM1 signaling mechanism, inhibition of FAK phosphorylation by PF-562271 could affect more than NCAM1 signaling. Blocking NCAM signaling through another method (such as through NCAM1 targeted monoclonal antibodies or small molecules) would support the authors' interpretations further.

2) A point of ambiguity is the exact cells included in the final scRNAseq analysis. The authors noted they flowed and gated broadly, including RFP negative cells, in the initial set of cells selected for sequencing (given RFP expression is not visualized within all neurons and glia in GDNF-treated HolTg/Tg mice.) Pan-neuronal (Elavl4, Tubb3) and pan-glial (Sox10) marker expression were utilized to select cells for final analysis (unsupervised analysis, pseudotime trajectories, etc.) Here, it is unclear if RFP expression was examined in these cells, either by looking at unmapped reads or if included in the initial alignment. If this is discernable within the authors' data set, this provides an opportunity for an interesting additional analysis to determine if progenitors or neuronal or glia populations differ in the RFP+ and RFP- groups.

3) The authors presumably sequenced both the submucosal and myenteric plexus ENS components within their scRNAseq analysis. Given the relatively sparse numbers of ENS cells in the submucosal plexus compared to myenteric plexus in the distal colon, this is unlikely to change their analysis or conclusions. However, given their tissue analysis focuses on the myenteric plexus, this difference should be acknowledged.

The authors go on to further to utilize their scRNA sequencing data set with pseudotime trajectory analysis to determine that SCPs appear to go through an EGC-like state prior to GDNF-induced neurogenesis. This was followed nicely by use of transgenic mice (Dhh-Cre) and immunohistochemistry within their HolTg/Tg model to capture the SCP population and demonstrate in vivo this progression. Additionally, they were able to demonstrate that temporally, SCPs generated neurons much sooner (within 6 hours of GDNF-treatment) compared to neural crest derived EGCs (labeled by Slc18a2-Cre and GFAP-CreERT2 lines).

Fascinating here as well is that the authors unearthed that most generated neurons following GDNF-treatment appeared to derive from direct cell transdifferentiation (suggested by EdU incorporation investigation at various time points) and that these neurons did not seem to originate from SCPs or EGCs (i.e. a non-neural crest origin.) Acknowledging that their mouse genetic tools and sequencing could have missed a NCC-derived population, the authors go on to label neural crest derivates utilizing the Wnt1-Cre2 transgene in their wildtype and HolTg/Tg mouse model and find that while Wnt1 labels the vast majority of neurons in wildtype mice, nearly 25% of neurons in P20 HolTg/Tg mice appear non-NCC derived. Finally, once again utilizing various genetic mouse lines for lineage tracing and immunohistochemistry, the authors demonstrate NCC-derived neural progenitors (SCPs, EGCs) appear to preferentially give rise to cholinergic neurons where non-NCC derived neurons tend to be more nitrergic.

4) The high magnification of the majority of images provides the reader with extremely compelling evidence in regard to visible overlap or lack thereof across various reporter lines, antibody markers, and EdU labeling. Unfortunately, this can somewhat create a trade off with the area or number of cells examined which appears somewhat less than the number of cells and/or area examined by many prior studies in the field. The near equal averages across the three mice in each group in many of their experiments makes this less of a concern, but the paper may be strengthened by noting exactly how the 3-11 images per mouse were selected. Were these randomly selected across the tissue, moving from mesenteric to anti-mesenteric? Or caudally to distally?

5) In line with this, the authors report a near 100% of Wnt1-Cre2 driven reporter expression in wildtype mice but a large portion (~25%) of neurons in HolTg/Tg model appear non-NCC derived (i.e. not Wnt1-Cre2 labeled.) The original Wnt1Cre line (Danielian, et.al., Curr Biol. 1998) has been reported to incompletely label all neural crest derivatives/ENS (Hari, et. al., Development. 2012.; Deal, et. al., Dev Bio. 2021). To my knowledge, the same type of analysis has not been carried out with the same rigor in the ENS with the Wnt1-Cre2 line. It could be -- depending on tissue sampling, area covered via imaging, and if there is any patchy or unique patterning to non-NCC derived neuro regeneration -- any incomplete labeling of neural crest by Wnt1-Cre2 could be missed. Of course, alternative interpretations are that the non-labeled cells are truly non-NCC derived. Utilizing other lineage tracing models for other non-NCC derived lineages may help address this issue, but would require many mouse crosses and additional experiments, and thus likely outside the scope of this manuscript. However, this caveat should be addressed.

6) A very important and fascinating find by the authors is that the NCC versus non-NCC derivatives appear to preferentially give rise to cholinergic or nitrergic neurons respectively. This will have important implications in treatment options for ENS regeneration not only within HSCR disease, but other ENS disorders as well. A point of discussion the authors missed out on is several previous reports regarding skewing of ENS neurons (typically toward higher nitrergic numbers) in ganglionic and/or hypoganglionic segments of HSCR bowel in murine models and patients (Zaitoun, et.al., Neurogastroenterol. Motil. 2013.; Musser, et.al, CMGH. 2015.; Cheng, et.al., J Pediatr Surg, 2017.; Sukhada, et. al., Front. Cell Dev. Biol. 2022.) Could ganglionic portions of the bowel in HSCR disease contain more of the non-Wnt1 labeled population? Why do proportions in the aganglionic region generate correct proportions following GDNF-induced treatment compared to ganglionic bowel? This does not need to be experimentally addressed in the manuscript, but including in the discussion impresses upon the audience the importance of the authors findings and that these factors need to be further experimentally delineated and considered with any therapeutic interventions.

Reviewer #3 (Public review):

Summary:

In this work, the authors aim to build on their previous work to further define the mechanism by which GDNF can induce enteric nervous system migration and differentiation in the Holstein mouse model (Hol Tg/Tg) of Hirschsprung's disease (HSCR). They show that GDNF can cause neuronal differentiation from either Schwann cell precursors (SCP) that migrate from the periphery and/or enteric glia (or neural crest precursors located in the intestine). Surprisingly, the rescue effect of GDNF is mediated through signaling with NCAM1 rather than the canonical receptor RET, with blockade of NCAM1 significantly reducing the number of GDNF-treatment induced neurons in the distal colon of Holstein mice. The authors then perform scRNA-seq data of the colonic ENS from Holstein mice +/- GDNF, and pseudotime analysis of this data indicates the SCP downregulate SCP genes and upregulate classical enteric glial genes on their transition to becoming enteric neurons. Following this, the authors employ Dhh-Cre mice (to label SCP), Slc18a2Cre and GFAPCreERT2 (to label enteric glia) and finally Wnt1Cre2 mice (to label neural crest derived cells) to assess the kinetics and end identity of enteric neurons driven by GDNF treatment. Using these animal models, the authors propose a model by which transdifferentiation of SCP gives rise to enteric neurons first, followed by transdifferentiation of enteric glia; the resulting enteric neurons labelled by Dhh, Slc18a2 or GFAP Cres are all biased to a cholinergic lineage, raising a questions about the source of nitrergic neurons. Finally, the authors postulate that at least some nitrergic neurons come from a non-neural crest lineage in GDNF treated Hol Tg/Tg mice as they are not labelled by a Wnt1Cre2 model, while all ENS cells are labelled in three wildtype Wnt1Cre2Tg/+;R26YFP/+ mice.

Strengths and Weaknesses:

This work convincingly shows that NCAM1 is required for GDNF-induced rescue of the Holstein mouse model of HSCR and, along with the NCAM1 staining in human HSCR tissue, highlights the potential of this treatment even in HSCR patients with loss of function RET mutations. The major weakness of this study is in the interpretation of the mouse models; many of these models are not fully penetrant/show mosaicism in other studies (like the DhhCre and Wnt1Cre) or may not only label the specific subpopulation they present (in this case, the GfapCreERT2 and Slc18a2Cre; these genes have been shown in Schwann cells/SCP in other studies, and the expression pattern of these two genes outside of the gut at the relevant developmental timepoints are not shown). While these are unavoidable limitations with our current mouse models, the authors need to clearly acknowledge these limitations in the interpretation of their data (with the DhhCre and Wnt1Cre) or more definitively show the models are only labelling enteric glia (in the case of the Gfap and Slc18a2Cre). In addition, in some figures the authors should add untreated Hol Tg/Tg and ideally WT mice so readers can contextualise the effect of GDNF on Hol Tg/Tg mice. Finally, it appears the statistics throughout the paper are performed on using each ROI taken from n=3-5 animals - this is inappropriate, as images from the same animal are not independent samples. The statistical unit in question for every analysis performed should be 1 animal, thus the statistics should be done on the n=3-5 animals, not the n=3-11 images from 3-5 animals (which leads to an n of 6-55).

Specific comments:

In general I find the author's conclusions are relatively well supported, albeit a little overstated for the evidence presented in the later figures and with the need to correct the statistical analysis. For Figures 1-5, I have only minor comments, as follows.

In Figure 1-2, the Gata4-RFP reporter is used to sort cells for scRNA-seq, and the authors get a large number of non-ENS cells so utilise Elavl4 and Sox10 expression to pull out neurons and glia to analyse. Do other putative neuronal/glial genes pull out the same cells, and can the authors find evidence of non-neural crest derived glia/neurons in this dataset? This would ensure there isn't a bias in this first analysis and strengthen the later claims respectively.

In Figure 3, the interpretation of increased NCAM1 and pFAK would be aided by adding the MFI for the untreated Hol Tg/Tg and ideally WT mice at p10 to assess if this is a normal developmental increase or induced by GDNF treatment - I would ask the authors add at least untreated Hol Tg/Tg at p10 as authors already present this data as images in figure 3D. Similarly, it would be nice to have neuronal counts of untreated Hol Tg/Tg and WT mice presented in Figure 4c to assess if NCAM1 inhibition completely or only partially prevents the effect of GDNF.

In the text accompanying Figure 2 and 5, the authors use a variety of markers of assign SCP or enteric glia identity to the clusters, but some of the enteric glia genes can be expressed by Schwann cells/SCP in other contexts - it is worth adding references to the genes chosen to define SCP and enteric glia so readers can understand why those were chosen and the strength of evidence for each marker. For me, with the exception of Dhh I do not find any of these genes definitive as, at least on the SCP/Schwann cell side, they have been shown to express Gfap, Slc18a2, Sox2 and single cell analysis indicates they also express Cpe. The ability for SCP/Schwann cells to express both Gfap and Slc18a2 is important for the interpretation of the upcoming experiments.

In Figure 6, the authors state in line 213 that "quantitative analysis as a function of time revealed that GFAP+ cells in the distal colon are not all derived from Dhh-expressing SCPs on the first day of treatment"; however, the DhhCre is restricted to specific SCP subsets (Xie, Meng, et al. "Schwann cell precursors contribute to skeletal formation during embryonic development in mice and zebrafish." Proceedings of the National Academy of Sciences 116.30 (2019): 15068-15073) and thus may not be labelling all SCP coming into the intestine. As far as I know there are no models that would allow labelling of all SCP without labelling enteric glia so would require the generation of a new models or techniques that is out of scope for this work - however, the authors should acknowledge the possibility of Dhh negative SCP contributing to the ENS.

Figure 7 and 8 focuses on the contribution of Dhh+ cells, Slc18a2+ cells and cells expressing GFAP between p3-p8 to the ENS of GDNF treated Hol Tg/Tg mice. The authors first show that by p20 the number of neurons per mm2 is equivalent to those at p60, indicating p20 as an appropriate timepoint to assess the relative contribution of each pool of glia to the resulting neurons. The authors show that neurons derived from a DhhCre are detectable first, then Slc18a2, followed finally by GFAP. This data supports the authors claims that neurons first arise from Dhh+ SCP, but as I raised earlier, both Slc18a2 and GFAP can be expressed by schwann cells later in development - the authors in fact show that GFAP is in fact expressed by Dhh+ cells in figure 6, and showed with pseudotime analysis that SCP undergo a transition to Gfap+ Slc18a2+ glial cells before becoming neurons. The data presented here negates that analysis, or at least suggests some Dhh+ cells skip this step, otherwise the kinetics of neuronal differentiation would align across the 3 lines used. Could the authors address this discrepancy? For example, one addition could be to show that SCP/schwann cells on extrinsic gut innervating nerve fibres do not express Gfap or Slc18a2 at the timepoints used. In addition, their scRNA-seq analysis suggests that Gfap & Slc18a2 are expressed in the same cells, so one would expect similar kinetics in both populations - what is the overlap of GFAP staining with Slc18a2-YFP expression at the earlier stages (say p6 and p10?). Alternatively, the inducible nature of the GFAPCreERT2 means some bona fide GFAP expressing cells may be missed if the tamoxifen dose is not saturating, thus underestimating the contribution of this population to the total neuron count. As such, could the authors please show co-staining with GFAP in some induced GFAPCreERT2 samples to assess the effectiveness of this Cre. As with other figures, it would also be nice to add Holstein negative reporters at p20 as a control to assess the level of contribution each one of these cell lineages has in a normally developing animal compared to GDNF treated Hol Tg/Tg mice.

In Figure 9, the authors show that neurons derived from labelled cells in the DhhCre-YFP or Slc18a2Cre-YFP skew strongly cholinergic (81%) compared to nitrergic (13%), but only 52% of the total neurons in GDNF treated Hol Tg/Tg mice are cholinergic, while 42% are NOS1+. The authors say that a similar trend is seen in Slc18a2Cre-YFP mice with a 'slightly higher percentage' reflecting Slc18a2 expression in neurons. However, this 'slightly higher' percentage looks to be about 40%, which is the amount expected in GDNF treated Hol Tg/Tg. I think the authors underplay the level of nitrergic neurons that are labelled in the Slc18a2Cre mice and should consider the possibility that Slc18a2+ glia can give rise to the nitrergic neurons seen in GDNF treated Holstein mice. This data also contrasts with prior reports that indicate SCP tend to become NOS1 expressing in a Ret or Ednrb loss of function HSCR model (Uesaka, Toshihiro, et al. "Enhanced enteric neurogenesis by Schwann cell precursors in mouse models of Hirschsprung disease." Glia 69.11 (2021): 2575-2590), a discrepancy worth discussing.

In Figure 10, the authors assess the contribution of neural crest to the ENS of WT and Hol Tg/Tg mice using a Wnt1Cre2 line, and conclude there is non-neural crest contribution to the ENS of GDNF treated Hol Tg/Tg mice. This is an interesting idea and supported by a few studies the authors mention in the discussion; however, the labelling of neural crest derived cells in Wnt1Cre2 may not be fully penetrant. While this line has a well established leaky phenotype, others have reported it can have patchy recombination in the neural crest too (potentially in a background dependent manner, according to the line information on Jackson laboratories). For example, recent works shows significant mosaicism in the embryonic phase (Gandhi, S., Du, E. J., Pangilinan, E. S., & Harland, R. M. (2024). The Wnt1-Cre2 transgene causes aberrant recombination in non-neural crest cell types. bioRxiv, 2024-11.) This may not be the case in the authors home institution in a FVB background, as they show all HuCD+ and Sox+ cells overlap with the Wnt1Cre2 reporter, but the Hol Tg/Tg mice have aberrant neural crest development - this could interfere Wnt1 expression thus the effectiveness of the Wnt1Cre2, thus leading to non-labelled, but actually neural crest derived cells. It is also possible that those neurons are truly from a non-neural crest background, and the neural crest labelling tools are all flawed in one way or another - as such, I think the authors just need to discuss this alternative possibility in the discussion.

Finally, Figure 11 shows NCAM1 expression in human tissue resections from HSCR patients. This data bolsters the idea that GDNF treatment could be an effective treatment for HSCR. The methods indicate that 3 tissue samples from HSCR patients were obtained, but staining is only shown for one - could all 3 be included, along with secondary only controls? This is important as human tissue resections are often processed many hours after removal, so are prone to higher background. It would also be interesting to include tissue from non-HSCR patients (the controls used most often in other studies are resections from anorectal malformations which are performed at approximately the same age as HSCR resections) to see if NCAM1 expression is influenced by the absence of an ENS in human patients, but I understand these samples are not always possible to obtain. If not possible, the authors could consider analysing publicly available RNA sequencing datasets to assess if RET is solely expressed in mature neuronal populations while NCAM1 is expressed by glial and neuronal populations like in their mice data.

Overall, the authors clearly show that GDNF can drive differentiation of neurons from different glial populations through NCAM1 not RET, and supports continued effort to translate this work to the clinic as a potential therapy for HSCR patients. I am not convinced that the relative contributions of each glial subpopulation can be extrapolated from the mouse models used - this is a problem across the field, and will only be rectified with the development of new models, which is out of scope for this work. This work complements recent work showing NCAM1-GDNF signaling promotes neurogenesis in glia in Ednrb-/- mice (Mueller, Jessica L., et al. "Intramuscular enteric glia persist in Hirschsprung disease and undergo neurogenesis in response to GDNF-NCAM1 signaling." Scientific Reports 15.1 (2025): 33200), and will add to our understanding of neural development.

Reviewer #4 (Public review):

Summary: The manuscript by Gary et al works to reveal processes that generate enteric neurons in the distal colon of Holstein mutant mice that experience aganglionosis and are an established model of Hirschsprung disease (HSCR) following GDNF enema infusion. The primary goal of the study is to determine the how rectal infusion (enema) of GDNF drives neurogenesis in these mutants. The studies focus on determining the molecules that mediate this GDNF effect and identifying the cellular origins of the newly formed neurons. Given that prior work from this group and others has indicated formation of postnatal enteric neurons is feasible, understanding this process is an important step for the field. The data presented partially support the claims of the study. The analysis described do not support unequivocable conclusion that "transdifferentiation" is occurring. To instill confidence in the stated conclusions and make the text appropriately clear, clarifications of the methods and additional information is needed.

Strengths:

(1) The authors use in vivo experimentation with multiple mouse lines including Dhh-cre, Slc18A2-cre, and GFAP-creERT2 to trace the production of enteric neurons in the context of GDNF enema in the established Holstein mouse model of Hirschsprung disease over a time line of postnatal days 4 (P4) to P10.

(2) The authors generate novel molecular profiles of enteric neurons induced in the distal colons of Holstein HSCR mice after GDNF enema induction by flow sorting for fluorescently labeled and adjacent populations with novel gating parameters followed by single cell RNA-sequencing.

(3) The authors recognize broad expression of NCAM1 amongst the induced neurons in scRNA-seq data and apply experimental approaches to further investigate the role NCAM1 in generation of GDNF-induced ENS neurons.

(4) The authors apply a widely utilized experimental approach, EdU-labeling, to assess proliferation in the immediate timeframe of GDNF-inducation in an effort to discern the timing of when the newly produced neurons exit the cell cycle.

Weaknesses:

(1) The article lacks sufficient information justifying use of the Holstein HSCR mouse model for the study. Authors need be more thorough when introducing the readers to the various HSCR mouse models they consider analyzing and provide an expanded justification for use of the Holstein model in the introduction so the audience can appreciate the rationale behind the analysis presented.

(2) The text minimally describes the G4-RFP reporter that is a critical element of the analysis and upon which the scRNA-seq profiling hinges. Given the data presented in this submission it's not clear how much of the ENS this G4-RFP line labels.

(3) The authors state that "NCAM1 is already present in SOX10+ cells before GDNF treatment begins at P4, both within and outside extrinsic nerve fibers (Fig.3b,c)." However, the data shown in Figure 3 panels B and D do not allow one to conclude co-localization of Sox10 with NCAM1 or FAK. Because ENS cells are so closely positioned with one another the signal the authors present could be due to adjacent cells or processes of cells above and below the plane of Sox10+ nuclei.

(4) The authors use the inhibitor PF-562271 in an attempt to specifically inhibit phospho-FAK[Y397] shown in Figure 4. This particular inhibitor has the known side effect of causing apoptosis in phospho-FAK[Y397]+ cells as shown by Hu et al 2017 Cancer Sci (DOI: 10.1111/cas.13256). Because this compound causes apoptosis in phospho-FAK[Y397]+ cells, the data presented do not prove that the lack of neurons produced in this condition is due to inhibition of phospho-FAK[Y397]+ cells making the neurons versus those phospho-FAK[Y397]+ cells simply dying very early in the process.

(5) In the text describing the results of Figure 1A compared to Figure 1B the authors have missed an opportunity to elaborate on the spatial distribution of what appear to be small ganglia in the GDNF treated colon of Holstein mutant mice. The schematic shown is rather simple and it's unclear from the text where these ganglia are distributed circumferentially around the gut wall.

(6) The immunohistochemical labeling for Phox2b shown in Figure 6 is odd. Phox2b is expressed in neuronal progenitors, enteric glia, and ALL enteric neurons as shown in multiple publications. The images shown in Figure 6 offer an outlined region that appears to be a ganglion; however, within that encircled area fewer than half of the cells are labeling with Phox2b by this study.

(7) The authors conclude that "transdifferentiation" is the origin of the ENS neurons that appear in GDNF-treated Holstein mice. However, the data show simply that most of the newly produced neurons have not recently gone through cell division based on lack of EdU incorporation. Given the data presented, other mechanisms may be occurring and should be considered as possibilities.

(8) The authors utilized a Wnt1-cre2 transgenic line that has known issues with expression in the male germline and ectopic expression in cells that are dependent upon the reporter line utilized, like the Rosa26-YFP of this study. The methods lack information on whether crosses were performed in such a manner as to avoid issues with male germline activation of this reporter and the potential for ectopic expression cannot be excluded based on the information provided in the study.

(9) The study lacks data on how GDNF enemas affect enteric neuron density and ganglia distribution in wildtype animals. If the signaling mechanism that produces new neurons in the Holstein model is also operating in wildtype animals, this could be crucial information for investigators interested in neuronal replacement to treat ENS damage resulting from environmental damage, disease, or age.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

From a big picture viewpoint, this work aims to provide a method to fit parameters of reduced models for neural dynamics so that the resulting tuned model has a bifurcation diagram that matches that of a more complex, computationally expensive model. The matching of bifurcation diagrams ensures that the model dynamics agree on a region of parameter space, rather than just at specially tuned values, and that the models share properties such as qualitative features of their phase response curves, as the authors demonstrate. A notable point is the inclusion of extracellular potassium concentration dynamics into the reduced model - here, the quadratic integrate-and-fire model; this is straightforward but nonetheless useful for studying certain phenomena.

Strengths:

The paper demonstrates the method specifically on the fitting of the quadratic integrate-and-fire model, with potassium concentration dynamics included, to the Wang-Buzsaki model extended to include the potassium component. The method works very well overall in this instance. The resulting model is thoroughly compared with the original, in terms of bifurcation diagrams, production of various activity patterns, phase response curves, and associated phase-locking and synchronization properties.

Weaknesses:

It is important to note that the proposed method requires that a target bifurcation diagram be known. In practical terms, this means that the method may be well suited to fitting a reduced model to another, more complicated model, but is not likely to be useful for fitting the model to data.

Reviewer #2 (Public review):

Summary:

The authors derive an integrate-and-fire model to describe the dynamics of a more complex Wang-Buzsaki model and compare the two models. A detailed discussion of bifurcation schemes in both models is convincing and allows us to evaluate the simpler model.

Strengths:

The idea is interesting, and the mathematical approach appears to be convincing. In addition, differences between the simple and original models are also discussed.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

In this study, the authors examine what happens when two facultative endosymbionts, Rickettsiella viridis and Regiella insecticola, are introduced into a novel aphid host, the Russian wheat aphid (Diuraphis noxia). They ask whether these introduced symbionts affect aphid performance, plant damage, alate production, dispersal, plant defense responses, and symbiont dynamics. The main result is that the two symbionts have contrasting effects: Rickettsiella tends to increase plant damage and reduce dispersal-related traits, whereas Regiella tends to reduce plant damage and aphid population growth, with less evidence for an effect on dispersal.

Strengths:

The manuscript presents successful establishment of stable transinfected populations of an agriculturally important aphid species, which is a substantial technical achievement in itself. I also appreciated that the authors examined the system across several experimental contexts, including different host plants, mixed cages at two temperatures, whole-plant assays, and a mesocosm dispersal experiment, rather than relying on a single laboratory setup. Taken together, these experiments provide a useful and reasonably convincing demonstration that novel symbiont associations can generate contrasting phenotypes in this system.

Reviewer #2 (Public review):

Summary:

The authors generated two novel aphid-symbiont associations and examined the impact of these new symbiotic associations on plant-insect-symbiont interactions. The authors notably provide detailed phenotypic assessments of the insect hosts and host plants. They show that one introduced symbiont, Rickettsiella, increases aphid-induced damage to host plants, while the other, Regiella, ameliorates aphid damage. The authors suggest that such novel insect-symbiont pairings may be used as tools to mitigate crop damage in the future.

Strengths:

Although a few experiments seem to have limited sample sizes and limited statistical power, these are often complemented with highly replicated smaller-scale experiments. The combination of larger mesocosm and population-level experiments along with assessments of individual insects generally provides a comprehensive depiction of the effects of these symbionts on their hosts. The opposing impacts of Regiella and Rickettsiella infection on the aphid host plant are of broad interest. It is also surprising that the host plants did not exhibit strong differences in canonical defensive signalling, despite these differences.

Weaknesses:

It is a little surprising that mesocosm-dispersal experiments were not also conducted using Regiella-infected lines. At several points throughout the manuscript, the idea of using symbiont transfections to reduce plant harm is raised. I can understand that these experiments are likely time-, space-, and resource-intensive, but that seems like these would have been relevant experiments, especially in the context of controlling damage to plants.

Reviewer #3 (Public review):

Summary:

The authors were investigating the impact of introducing novel facultative bacterial endosymbionts into the pest aphid, Diuraphis noxia, to explore the possibility of using facultative symbionts as a crop protection tool. They successfully established the vertical transmission of both endosymbionts and performed a series of aphid performance and dispersal experiments together with measurement of aphid feeding on host plant health, growth, and metabolism. While most of the experiments revealed no effect of the endosymbionts, some significant treatment effects were found, showing that Rickettsiella reduced aphid dispersal, and Regiella reduced aphid population growth and feeding damage.

Strengths:

The team worked with two novel facultative symbionts (Rickettsiella viridis and Regiella insecticola) that they were able to successfully establish in D. noxia. The data were collected and analyzed using solid, well-described methodology.

Weaknesses:

While interpretation of the data is reasonable, the few experiments which revealed significant treatment effects rest on relatively small sample sizes.

Measuring symbiont density is difficult. The authors use quantitative PCR to measure the "density" of endosymbionts relative to a host gene. This is a standard approach in the field; however, recent work has shown that endosymbionts like the aphid primary endosymbiont, Buchnera, are variably polyploid [1]; further the aphid cells that house the symbionts are also highly polyploid and variable in their ploidy [2]. It is important to understand that what is being measured when using qPCR is DNA copy number and not quantification of the number of symbiont cells. Alternative approaches to measuring symbiont density include flow cytometry [3], and SymbiQuant [4], a machine vision tool that can quantitatively characterize symbiont populations from DAPI-stained confocal images. These alternate approaches also have their limitations. Currently, there is no perfect approach to measuring symbiont density, which remains an important measure in experiments such as these. Put simply, it is important for a reader to be aware of the limitations of each approach and interpret data accordingly.

[1] Komaki, K., and H. Ishikawa. 2000. Genomic copy number of intracellular bacterial symbionts of aphids varies in response to developmental stage and morph of their host. Insect Biochemistry and Molecular Biology 30:253-258.

[2] Nozaki, T., and S. Shigenobu. 2022. Ploidy dynamics in aphid host cells harboring bacterial symbionts. Scientific Reports 12:9111.

[3] Simonet, P., G. Duport, K. Gaget, M. Weiss-Gayet, S. Colella, G. Febvay, H. Charles, J. Viñuelas, A. Heddi, and F. Calevro. 2016. Direct flow cytometry measurements reveal a fine-tuning of symbiotic cell dynamics according to the host developmental needs in aphid symbiosis. Scientific Reports 6:19967.

[4] James, E. B., X. Pan, O. Schwartz, and A. C. C. Wilson. 2022. SymbiQuant: A machine learning object detection tool for polyploid independent estimates of endosymbiont population size. Frontiers in Microbiology 13:816608.

Impact and Significance:

Food security and production, and pest control are major challenges facing the human population. This work contributes knowledge that will benefit the development of alternate pest control strategies in agriculture.

Reviewer #1 (Public review):

[Editors' note: This revised version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have satisfactorily addressed the substantive comments raised in the previous round of review. The qualifications and limitations are now more clearly acknowledged in the revised manuscript.]

Summary:

This work compiles a comprehensive atlas of ncORFs across mammalian tissues and cell types, derived from reanalysis of ~400 public ribosome profiling datasets. The authors then evaluate cross-species conservation and functional signatures, proposing that evolutionarily ancient ncORFs tend to have higher translation potential, stronger expression, and closer relationships with canonical coding sequences.

Strengths:

In general, the study provides a large-scale and timely resource of annotated ncORFs, which could be broadly useful for the community. The authors collected ~400 public ribosome profiling datasets for annotations of ncORFs, which, to my best knowledge, is the largest collection of data for such purpose. The catalog could facilitate future investigations into ncORF biology and broaden understanding of the coding potential of the "non-coding" genome.

Comments on previous version:

The authors have made efforts to address most of the previous concerns, and several points have been clarified or improved in the revision. However, in a number of cases, the responses rely more on acknowledgment and reframing rather than substantive analytical strengthening. Overall, the manuscript is improved, particularly in terms of clarity, transparency, and positioning of claims. I support its publication and look forward to seeing how the field engages with and discusses these claims.

Reviewer #2 (Public review):

Summary:

Chang et al. attempted to analyze a large number of ribo-seq datasets through a standardized pipeline, identifying novel non-canonical ORFs and elucidating their evolutionary and expression characteristics.

Strengths:

(1) The datasets analyzed by the authors are sufficiently comprehensive, and the use of standardized pipelines ensures excellent analytical consistency.

(2) Their analyses of ORF evolution and co-expression further deepen our understanding of these ORFs.

Weaknesses:

(1) The authors primarily conducted analyses through bioinformatics, lacking sufficient wet-lab experimental evidence.

Reviewer #1 (Public review):

Summary:

The manuscript entitled "Autonomic reflex plasticity associates with time-dependent SUDEP susceptibility in a murine model with hyperactive stress circuits" by Dr. Saunders and colleagues combined a traditional mouse model of SUDEP, ventral intrahippocampal kainite (vIHKA) injection, with a genetic model of chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) that further increases the risk of SUDEP in the weeks following seizure.

Strengths:

Their results show during spontaneous seizures Kcc2/Crh mice had more pronounced reflex-like ictal bradycardias compared to WT controls that notably occurred prior (~10 sec) to seizure termination and had greater autonomic disturbances compared to WT controls, including a pronounced serotonin-mediated Bezold Jarisch reflex. These results show chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) increased autonomic disturbances and risk of SUDEP in a kainic acid model of epilepsy.

Weaknesses:

This study could be improved with a more thorough assessment of heart rate, blood pressure and breathing during and following the seizures, and in particular the fatal event. It is unclear if the bradycardias were spontaneous, or a result of preceding central or obstructive apneas, oxygen desaturations, hypercapnia, arrhythmias, or other possible triggers.

Considerable prior work in the literature suggests SUDEP could be mediated, in some patients, by a burst of parasympathetic activity to the heart. Were the heart rate changes in these animals during seizures inhibited or blocked by atropine, or atenolol? The injection of the 5HT agonist phenylbiguanide into the right jugular is not a selective approach for activating the Bezold Jarisch Reflex (BJR) which is caused by increased activity of intracardiac sensory neurons (generally activated with ischemia or a combination of low preload with high contractility). The results should be interpreted more cautiously, as a response to systemic administration of phenylbiguanide only.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors set out to evaluate the role of hypothalamic pituitary axis hyperactivity on cardiac and autonomic changes during epileptogenesis and following seizures in a mouse model of temporal lobe epilepsy. Epilepsy is very common. It can frequently result in death from sudden unexpected death in epilepsy, or SUDEP. SUDEP is thought to be at least in part due to seizure related cardiac and autonomic instability. Increased stress states are well known to be comorbid with epilepsy. This comorbidity is thought to increase the risk of SUDEP. Here the authors hypothesized that a mouse model of heightened stress in which there is hyperactivity of the CRH neurons in the hypothalamus would demonstrate exaggerated cardiac and autonomic effects of seizures and epilepsy.

Strengths:

For the chronic stress model, they employed the Kcc2/Crh mice that have a genetic deletion of the potassium chloride cotransporter in CRH neurons. They treated these mice and their wild type littermates with intra hippocampal kainic acid or saline, as epileptic and sham-treated animals respectively. The assessed cardiac activity, blood pressure, baroreflex, and the Bezold-Jerisch reflex during epileptogenesis. This in general is an interesting study. They make some interesting and potentially important observations regarding heart rate and blood pressure in seizures and epilepsy.

Weaknesses:

While the revised manuscript is much improved, there are still some concerns that should be addressed.

(1) The low-pressure baroreceptor responses they show in Figure 4 are somewhat confusing. Should they not be seeing a reflex increase in heart rate when blood pressure is lowered with sodium nitroprusside? It would be helpful if they could describe whether the control responses were as expected or not, and if not, why? This makes it difficult to assess changes seen in the different genotypes and conditions.

(2) It does not seem appropriate to label the assessments associated with Figure 5 as the Bezold Jarisch Reflex. This reflex involves bradycardia, hypotension, vasoconstriction, and hypopnea. They seem to be only looking at the cardiac component, which is likely mediated though peripheral 5HT3 receptors. Did they measure blood pressure and breathing? Can they include these? If they can only comment on HR, then the discussion should reflect this.

(3) In Figure 1B, it would be helpful to show some short (e.g., 0.5 sec) snippets of ECG traces that exemplify the changes in HR (spikes/second).

(4) The day 21 examples given in Figure 1B, do not seem to be representative of the data depicted in Figure 1C.

(5) From the top panel examples in Figure 2A it looks like there might be greater EEG suppression following seizures in the Kcc2/CRH mice. Was this consistent? It might be worth looking into.

(6) Can the authors include scale bars for the top panels in Figure 2A?

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

This work asks the question of how different organelles and structures in the apicomplexan parasite Toxoplasma gondii are recycled and/or segregated to the daughter cells during cell replication. In particular, they consider an unusual cell structure called the residual body that links replicating cells during the intracellular infection stage of this parasite. The residual body has historically been considered a 'dumping ground' for unnecessary relics of the mother cell during division, but this notion is increasingly being revised. Indeed, cell replication in Toxoplasma is often misinterpreted as cell division (cytokinesis), but in fact, the cell replicates its organelles and structures to multiple 10s of copies in seemingly distinctly formed daughter cells, but cytokinesis is delayed for many such cycles and typically only occurs simultaneously with parasite egress from its host cell. The residual body is, in fact, the connection between these pre-cytokinetic replicated daughters, and effectively, this is still a single cell at this stage. The authors have previously shown that an actin network extends through the residual body between these daughter cells, and ER and mitochondria common to all cells are also linked through this structure. This study examining the fates of organelles during cell replication is timely for continuing our understanding of how this fascinating component of the cell participates in these processes. The authors use Halo-tags as their principal tool to track discrete populations of proteins, labelling their organelle locations, and this provides beautiful insight into these processes.

Strengths:

Using dyes conjugated to Halo tags this work elegantly tracks the fates of proteins synthesised by an original 'mother' cell over several replication cycles of pre-cytokinetic 'daughters'. Using this tool, they show that some organelles are made intact just once and that some of these can be subsequently sorted to the daughters (micronemes and rhoptries) while others are dismantled (IMC) and the daughters must make their own. A third set of organelles (largely synthesis, sorting and metabolic compartments) are divided and inherited, and new daughter-synthesised proteins are added to the preexisting maternal proteins in these structures. A role for actin and myosin is clearly demonstrated for micronemes and rhoptries, and this correlates with their relatively late inheritance into the developing daughters. Overall, this work gives clarity to the behaviours of several cell structures during replication and paves the way to better understanding the mechanisms that drive the differences between structures and the universality of these processes in other apicomplexan parasites. In particular, this study shows that the residue body is a region of the cell syncytium that organelles can be actively transported from. Therefore, it is a space that can actively contribute to the segregation of the late segregating micronemes and rhoptries.

Reviewer #2 (Public review):

Summary:

Toxoplasma gondii is an obligate intracellular parasite and the causative agent of toxoplasmosis. Parasite invasion of host cells, intracellular replication, and subsequent egress, which results in destruction of the infected cell, are central to pathogenicity. This manuscript focuses on understanding how maternal resources, specifically cellular organelles, are shared between daughter parasites during cell division. Many organelles are present as a single copy, making their division and inheritance essential for successful replication. In T. gondii, our understanding of how organelles are divided during cell division remains limited, and this study helps address this important knowledge gap.

Strengths:

The major strength of this study is the use of a Halo-based pulse-chase assay to characterize patterns of organelle inheritance and to monitor protein synthesis, turnover, and movement. This approach will be of considerable interest to the field. Using this method, the authors identify three major modes of organelle inheritance:

(1) Organelles present in multiple copies (such as micronemes and rhoptries) are partitioned between daughter parasites, with additional contributions from newly formed vesicles. Newly synthesized and pre-existing material remain as distinct populations within the cell.

(2) Single-copy organelles, such as the Golgi and apicoplast, are expanded through the incorporation of newly synthesized material before division.

(3) Cytoskeletal structures are synthesized de novo during each round of cell division.

These findings provide a more refined understanding of organelle inheritance and demonstrate that secretory organelles are not generated entirely de novo during each round of division, as was previously thought.

The paper places particular emphasis on the fate of maternal micronemes and rhoptries during division. The data show that (1) during division in wild-type cells, maternal micronemes and rhoptries are detectable in the residual body (RB); however, the majority of these organelles are localized within the parasite body, either at the apical or basal ends of the daughter parasites (Fig. 6). (2) In the absence of the myosin motor MyoF, micronemes and rhoptries accumulate in the residual body and are not properly trafficked to the daughter cells. Upon restoration of MyoF protein levels, these organelles redistribute to the daughter cells, although in an uneven manner.

Weaknesses:

The second half of the paper focuses on a more detailed characterization of microneme and rhoptry recycling. While the authors propose that the RB acts as a central hub for recycling both organelles, the current data do not fully support this conclusion.<br /> The model that microneme and rhoptry recycling is RB-dependent relies largely on the MyoF depletion phenotype and the limited detection of maternal organelles in the RB of wild-type parasites. Alternative models remain plausible, including direct trafficking to daughter cells, with RB accumulation upon MyoF depletion reflecting impaired trafficking rather than an obligatory RB-dependent recycling pathway, as now discussed by the authors.

Reviewer #3 (Public review):

Summary:

Knoerzer-Suckow et al. explore the mechanisms of organelle inheritance during endodyogeny in Toxoplasma gondii using an innovative dual-labeling approach to track the distribution of maternal organelles into daughter parasites. They can clearly distinguish between maternal and daughter-derived organelles using their dual-labeling Halo Tag approach. They reveal that different organelles are trafficked to daughter parasites in three broad patterns they have binned into groups. Their findings reveal a role for MyoF in the inheritance of micronemes and rhoptries, and notably, they observe that the inner membrane complex (IMC) is not recycled. Instead, the IMC undergoes a pronounced relocalization to the posterior of the maternal cell, where it is likely targeted for degradation.

Strength:

The data surrounding their MyoF knockdown experiments, IMC degradation, and trafficking of MIC2 after auxin washout are convincing. These data add to the knowledge of how organelle inheritance occurs in T. gondii, increasing the field's understanding of endodyogeny.

Weakness:

The inability to achieve higher temporal resolution due to phototoxicity precluded tracking of single micronemes, thus it remains possible that some micronemes follow a path similar to rhoptries and enter daughter cells before development of the residual body while others are recycled via the residual body.

Reviewer #1 (Public review):

Summary:

This study demonstrates that nutrient resorption efficiency (NuRE) in Phragmites australis is genetically canalized rather than plastic to salt stress. Using 110 genotypes in a common garden, the authors show that intraspecific variation in NuRE is explained by phylogeographic lineage, ecotype, and latitude, not by effective salinity. Element specific regulatory strategies further reveal how N, P, and K resorption are differentially controlled. At the population level, this is an important study that fundamentally advances our understanding of plant functional trait evolution and its implications for ecosystem nutrient dynamics under global change.

Strengths:

This study is the first to demonstrate genetic determination of a key nutrient conservation trait under effective salt stress in a widespread macrophyte, directly testing the 'plastic acclimation versus inherent conservatism' paradigm in a non-nutrient stress context. The experimental design is rigorous: each genotype was paired across control and salt treatments, and multilevel stress effectiveness (metabolomics, biomass, Na accumulation) was confirmed before evaluating NuRE. The large sample size of a macrophyte and dual classification (phylogeography + ecotype) allow robust disentangling of genetic versus plastic sources of variation.

The analysis comprehensively tests three resorption control hypotheses using appropriate SMA regression, revealing element specific and condition dependent patterns. The latitudinal gradient and variation partitioning provide strong evidence that genetic origin and geographic context outweigh short term plasticity, with important implications for predicting ecosystem nutrient cycling under global change. This study provides a clear empirical demonstration that a key nutrient conservation trait can remain homeostatic under non nutrient stress, and that intraspecific variation is primarily a product of population differentiation rather than short term plasticity.

Weaknesses:

First, the salinity treatment spanned only one growing season. The conclusion of genetic canalization therefore specifically refers to the absence of plasticity to an acute salt shock. Whether long term, multigenerational chronic salinity could act as a selective agent or induce transgenerational plasticity remains an open and interesting question for further research. Likewise, the physiological mechanisms underlying the observed lack of plastic increase in NuRE (for example, phloem loading or senescence gene expression) are not directly resolved, leaving some inference about trade-offs versus true unresponsiveness. These points do not weaken the study's main conclusion. Instead, they suggest productive future directions, such as longer-term field manipulations and targeted molecular investigations.

Second, the test of nutrient limitation control relies on resorbed N:P and N:K ratios as proxies, an established but indirect approach. Direct nutrient addition experiments would provide stronger causal evidence. Also, the metabolomic analysis is used primarily to validate stress effectiveness; deeper integration of specific metabolites with NuRE variation across genotypes could have offered mechanistic insights but was not pursued. Additionally, the potential collinearity between ecotype and phylogeographic lineage among Chinese populations is not quantitatively addressed. None of these considerations undermine the main finding, which is supported by a robust experimental design and widely accepted analytical approaches.

Comments on revised version.

The author carefully revised the parts that might cause confusion.

Reviewer #2 (Public review):

Summary:

The manuscript shows that nutrient resorption efficiency in Phragmites australis is largely genetically canalized rather than plastic under effective salt stress, with variation mainly associated with phylogeographic lineage, ecotype, and latitude.

Strengths:

The common-garden experiment with 110 genotypes, paired control and salt treatments, multi-level stress validation, and element-specific analyses provides compelling support for the central conclusions.

Weaknesses:

The generality is limited by the focus on a single species and a single growing season, and some mechanisms are inferred indirectly.

Reviewer #1 (Public review):

Summary:

In this study, the authors trained mice to perform a memory-guided navigation task, in which they must navigate to a previously cued arm after a delay period. They optogenetically inhibited the dorsal hippocampus or mPFC (targeting PL) in different task epochs. They found that for both regions, inactivating at the beginning of the navigation epoch impaired performance and induced mice to revert to habitual side biases. Inactivating during other epochs, including a delay period before the navigation phase, had little or no impact on behavior. The relationship between trial duration and behavioral performance was differentially impacted by hippocampal and mPFC inactivation, suggesting that the nature of the deficits was somewhat different.

Strengths:

The effects of perturbations are robust across animals and generally convincing. The lack of effect at some task epochs serves as a nice internal control. The finding that hippocampus and mPFC inactivation produced subtly different effects is interesting.

Weaknesses:

The simplicity of the behavior makes it difficult to resolve how exactly the hippocampus and mPFC contribute to working memory. Also, the language does not always reflect the trends in the data: the authors claim that optogenetic perturbations cause mice to repeat previous choices, but the data show that perturbations increase the likelihood of choosing a preferred side (which is left for most mice). A side bias is not the same as choice repetition. This has implications for interpreting the nature of the behavioral effects.

Reviewer #2 (Public review):

Summary:

The study uses transient optogenetic silencing of the dorsal hippocampus or prefrontal cortex in mice using a delayed response task in a T-maze, with a temporal delay of 1s after a visual cue, followed by a central stem run period before choice execution. Silencing of either the dorsal hippocampus or the dorsal prefrontal cortex is executed for varying time periods during the stem/ central arm running epoch or the 1s temporal delay epoch by targeting either PV+ or Dlx interneurons in a block-wise or random-trial design. The main result reported is that silencing of either region during long periods of stem running impaired choice behavior, and silencing during the temporal delay period did not have an effect.

Strengths:

The major strength of the study is using the optogenetic silencing strategy to target different temporal periods of the task.

Weaknesses:

(1) A major weakness of the study is the lack of a balanced design with equal time periods of silencing during the stem running period and temporal delay period in many of the animals, which precludes any conclusion about distinct functional roles of the regions during these two phases of the task. The central question of this study is not new, with many previous studies investigating distinct and overlapping roles of hippocampus and prefrontal cortex in spatial working memory tasks and memory-guided navigation, using inactivation of one or both regions, crossed inactivation approaches, as well as targeting direct and indirect connections between the regions (PMIDs: 20074655, 9030646, 17045348, 30179661, 27511010, 10491611, 26017312, etc.), in addition to several physiology studies. A key extension for the current study would have been to show a distinction between roles in the temporal delay period after the cue and the stem-running working memory period. However, the inactivation period during stem running shows effects only for long inactivation periods, 2s initial periods and later ~1.6s periods (run after 0.8s, >2/3 total running periods), whereas the temporal delay period inactivation is 1s for the large majority of animals, which is a clear mismatch in inactivation periods, obviating this conclusion of distinction.

(2) It is not clarified why such short delay periods were used compared to long periods of ~10s in T-maze spatial alternation tasks with delay, and whether the temporal delay period of 1 sec is strictly distinct from the spatiotemporal delay period during stem running in terms of short-term memory function. The choice of time windows for inactivation needs to be better justified, which currently appears to be rather random (2s initial running period, run after 0.8s, run after 1.6s; for an average reported running period of ~2.4-2.5s). The ideal design clearly would have been to use a 2s temporal delay period so that the inactivation time in this epoch matched the initial 2s run period. Only a subset of 4 animals were run with a longer temporal delay period, and too with only with hippocampal inactivation (Figure 4d). The main conclusion of distinction between temporal delay and stem running delay periods is therefore not adequately tested for the prefrontal cortex, and the statistics in terms of number of animals for this important control for hippocampal inactivation are also not comparable to the main experiment.

(3) The mixture of PV-Cre animals (5 animals), Dlx targeting (2 animals), and one WT animal is also suggestive of a fragmented approach, and inactivation efficacy cannot be assumed to be similar for different animals. Importantly, there is no physiological evidence for confirmation of suppression in the optogenetic experiments, even in exemplar animals.

Reviewer #3 (Public review):

The authors sought to determine when the dorsal hippocampus and mPFC are causally required during a delayed spatial working memory task. Using temporally precise optogenetic silencing in mice performing a delayed cue-guided T-maze task, they tested the effects of transient perturbations during distinct behavioral epochs. Contrary to the common view that these regions are primarily required during the delay period to maintain working memory representations, they report that silencing during the delay had little effect on performance, whereas perturbation during the early phase of central-arm traversal consistently impaired performance. The authors conclude that hippocampal and prefrontal contributions to memory-guided behavior are dynamically engaged during active navigation rather than passive maintenance of information.

The study has several strengths. The behavioral paradigm is carefully designed to dissociate cue, delay, and movement epochs, allowing temporally specific causal manipulations. The systematic comparison of multiple task epochs represents a major strength and provides compelling evidence that the behavioral effects of perturbation are epoch-dependent. The authors also include several important controls, including stimulation during multiple task phases, a longer-delay condition to dissociate task epoch from elapsed time since cue presentation, and analyses of movement trajectories and perseverative behavior that provide additional insight into the nature of the behavioral deficits. Together, these experiments convincingly demonstrate that transient dorsal hippocampal and mPFC perturbations have markedly different behavioral consequences depending on when they occur within a trial.

The evidence is generally solid and supports the primary finding that perturbations during early navigation produce larger impairments than perturbations during the delay period. However, some aspects of the broader interpretation are less well supported. Most notably, the study lacks a non-memory control task, such as a visually guided version of the maze, making it difficult to determine whether the observed deficits specifically reflect disruption of memory-guided behavior or more general impairments in action selection, behavioral flexibility, or movement planning. The observed increase in perseverative responding and delayed commitment to a turn are consistent with either interpretation. In addition, several experimental conditions rely on relatively small numbers of animals, limiting confidence in some negative findings, particularly for the longer-delay and later-run manipulations. Finally, while the Discussion proposes that hippocampal-prefrontal circuits become engaged during the transformation of stored information into action, this mechanistic interpretation remains speculative because no neural recordings accompany the causal manipulations.

Overall, the authors achieve their primary aim of demonstrating that the behavioral consequences of dorsal hippocampal and mPFC silencing depend strongly on task epoch. The data convincingly support the conclusion that these structures are more vulnerable to perturbation during early navigation than during the brief delay period used in this task. The broader conclusion that these findings redefine when hippocampal-prefrontal circuits support working memory should be interpreted more cautiously, as alternative explanations involving action selection or behavioral state remain plausible in the absence of additional control tasks.

The findings are potentially important because they challenge the common assumption that hippocampal and prefrontal contributions to delayed-response tasks are centered on delay-period maintenance. Instead, the work supports the idea that these circuits may be recruited when remembered information is translated into goal-directed behavior. This framework is broadly consistent with recent distributed models of working memory and provides an interesting perspective that may help reconcile previous studies reporting effects during different task phases. The behavioral paradigm and temporally precise perturbation approach should also be useful for future studies aimed at dissecting the dynamic contributions of hippocampal-prefrontal circuits during memory-guided behavior.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

This manuscript uses sci-L3-Strand-seq to map sister chromatid exchange events following CRISPR/Cas9-induced DNA damage. Because exchanges between identical sister chromatids are largely invisible to conventional sequencing, the study addresses an important blind spot in the assessment of genome editing outcomes. The authors compare single-locus Cas9 cleavage, simultaneous targeting of 237 repetitive genomic sites, and Cas9 nickase variants. They further use reciprocal daughter-cell pair analysis to ask whether Cas9-associated SCEs are copy-neutral or linked to larger structural alterations. Overall, this is a valuable study that introduces an important additional layer to the analysis of CRISPR/Cas9 repair outcomes. The central finding that Cas9-induced DSBs can trigger frequent local SCE is well supported and likely to be of broad interest.

Strengths:

The major strength of the manuscript is the application of a strand-resolved, single-cell method to a question that is difficult to address with standard genome sequencing. The evidence that a single Cas9-induced DSB can trigger strong local SCE is compelling in concept and supported by multiple guide RNAs targeting distinct loci. The reported on-target SCE frequencies, reaching up to 41%, suggest that inter-sister exchange is a substantial and underappreciated outcome of Cas9 cleavage.

Of particular interest is the comparison between single-site and multi-site targeting. The finding that 237 programmed Cas9 targets produce only mild bulk enrichment of on-target SCE but stronger enrichment in a subpopulation of cells with elevated SCE burden is interesting and may have wider biological implications, particularly if the findings extend beyond Cas9-induced SCE to spontaneous SCEs.

The reciprocal daughter-cell pair analysis is another notable feature of the study. The observation that some Cas9-associated SCEs are accompanied by structural alterations could challenge the assumption that SCE after a programmed break reflects error-free homologous recombination.

Reviewer #2 (Public review):

Summary:

In this short paper, a clever single-cell Strand-seq method was used to study the number and location of sister chromatid exchange events (SCEs) in cells after CRISPR/Cas9-induced DNA double-strand breaks (DSBs). Unique as well as multiple genomic loci were targeted. Cas9-induced cuts at unique genomic locations led to statistical enrichment of SCEs at the target site, whereas Cas9 targeted at repetitive targets revealed only mild enrichment of on-target SCEs unless analysis was restricted to a subset of cells with >8 SCEs per cell. Interestingly, reciprocal daughter-cell pair analysis revealed large-scale structural alterations on some chromosomes. Whereas disruption of DNA repair genes, including LIG3, LIG4, XRCC1, and XRCC4, did not measurably alter SCE frequency per cell within 24 hrs, consistent with delayed functional loss following editing and selection against essential genes. Together, these findings demonstrate that Cas9-induced DSBs are potent local triggers of SCE at unique loci and can be associated with structural alterations, highlighting the influence of lesion type and genomic context on recombination outcomes during genome editing.

Strengths:

The data in this paper represent a very rich resource of how parental DNA template strands are distributed in paired daughter cells after various treatments. Abnormalities observed in only one of such paired daughter cells provide a novel and exciting approach to study mechanisms of DNA instability and DNA repair at a genome-wide level in general and following Cas9-induced DSB in particular.

Weaknesses:

The effect of Cas9-induced DSBs in the cells that are used will depend on the cell cycle stage of the cells that are targeted, as well as the number of times cuts are made. The latter could happen before, during, and after DNA repair reactions on one or both alleles in a diploid cell. As a result, it is very difficult to extrapolate the mechanisms of DNA instability and DNA repair from the observed genomic rearrangements. Novel approaches are needed to limit the number and timing of Cas9-induced breaks to overcome some of these limitations.

Reviewer #3 (Public review):

Chovanec and Yin used their newly developed sci-L3-Strand-seq powerful method to characterize SCE after Cas9 cleavage in a human cell line, using either a single target site or an element repeated 237 times in the genome. SCE are often neglected in DNA repair analyses since they are « genetically silent ». Interestingly, the authors found enrichment of SCE at unique Cas9 sites, but only a modest enrichment of SCE when Cas9 targets 237 sites in the genome. The genetic control of SCE formation at Cas9 sites is not deliberately addressed in this paper. However, the authors found that targeted SCE seem to be enriched in a subpopulation of cells, particularly « permissive » for SCE, but the determinants of such a population are unknown. Finally, the power of the sci-L3-Strand-seq allowed the authors to characterize a specific type of SCE based on the analysis of reciprocal daughter-cell pairs' genomes that is associated with a specific type of chromosomal rearrangement compatible with the ones observed in HR defective BRCA1/2 deficient cells.

Reviewer #1 (Public review):

In this manuscript, the authors present ClustIRR, a computational tool that analyzes multiple TCR repertoires together, instead of one at a time. It builds one shared similarity graph across all the repertoires, then finds communities (CJs) on that graph that can be compared across samples. Building one shared graph across repertoires, rather than clustering each repertoire on its own, is a real improvement over existing tools. However, there are a few concerns that need to be addressed.

(1) The Introduction motivates ClustIRR by contrasting it with beta-binomial regression, Fisher's exact test, and scCODA/tascCODA (lines 62-77), but none of these are actually run on the same data in the Results. Could the authors include a direct comparison, e.g., applying a standard beta-binomial or Fisher's exact test to the Dataset 1 CJ occupancy matrix, to show the Bayesian model gives a lower false-positive rate or better-calibrated intervals than the alternatives it's positioned against?

(2) Prior predictive and posterior predictive checks are both reported as "(data not shown)" (lines 644, 728). Since the manuscript's central claim is rigorous, uncertainty-aware inference, it would help to include these diagnostic plots, along with Rhat and ESS values, in the supplement rather than stating they were checked.

(3) With 7,505 CJs tested simultaneously for differential occupancy in Dataset 1 alone (Figure 1 legend), what is the expected false discovery rate under the non-overlapping-HDI criterion used throughout? A short discussion of multiple-comparisons correction, or an argument for why it isn't needed under this framework, would strengthen the statistical claims.

(4) Line 115 states the Dataset 1 joint graph produced 10,301 CJs, of which 3,038 were singletons, leaving 7,263 non-singleton CJs. The Figure 1 legend reports 7,505 CJs used for the β modeling. Could the authors clarify how these two numbers relate - whether some singletons were included in the model, or a filtering step was applied that isn't described in Methods?

(5) The Methods section states that archival pretreatment tumor tissue was available for four patients (Pt4, Pt32, Pt36, Pt38; line 531), but the T+/T- DCJ analysis in Fig. 3B-C is only shown for Pt4. Was this analysis attempted in the other three patients? Extending it, even partially, would substantially strengthen the claim that contracting DCJs are enriched for tumor-infiltrating TCRs, which is currently based on a single patient.

(6) Dataset 1 was generated by deliberately stimulating T cells with EBV or MART1 antigen, so recovering EBV/MART1-annotated CJs from VDJdb is closer to a positive control than a blinded validation. Do the authors have, or could they obtain, any independent confirmation (e.g., tetramer data or an orthogonal cohort) for the CJs with large β that lack VDJdb annotation (orange dots, Figures 1B-C)?

Reviewer #2 (Public review):

Summary:

The study confronts a major obstacle in repertoire analysis. Given that individual TCR sequences are diverse and sparsely detected across repertoires, identifying sample-specific enrichment of TCRs based on sample-to-sample comparison of exact clonotype sequences can be intractable. This paper attempts to build on insights that sequence-similar TCRs can share antigen recognition, such that aggregating similar sequences derived from multi-sample joint-graph communities (i.e. clusters of tightly connected nodes) could reduce sparsity and boost signal.

Strengths:

The study is a well-motivated effort to address a need in the field. The paper takes a unique approach. The core method is modeling community occupancy with a hierarchical Dirichlet-Multinomial model that attempts to account for the high level of overdispersion present in repertoire sampling, a technique that has been previously applied to compositional microbiome data.

The authors apply this framework to both single-cell paired-chain and bulk single-chain TCR data. They develop a set of examples from public and synthetic data, with the most promising real-world application shown in reanalysis of longitudinal data during treatment of cancer patients with checkpoint inhibitors.

The manuscript is well structured and cogent. The authors are to be commended for contributing a well-documented, open-source R/Bioconductor package and for providing the underlying analysis datasets in a well-organized repository. In the joint graph construction step, the authors opt to use an existing implementation of the BLAST algorithm on CDR3 sequences, which is a slightly odd choice since it ignores potential contributions of other V-gene germline-encoded CDRs, but the authors also envision that their statistical package could be extended to include community graphs developed with other established TCR clustering tools. This will allow others to potentially explore the utility of Bayesian hierarchical Dirichlet-Multinomial models for differential occupancy analysis of immune receptors under varied clustering criteria.

The methods described here were demonstrated on relatively small datasets from 2-5 samples, and future work is likely needed to extend the joint graph differential occupancy concept to larger datasets. The authors are transparent about this and some of the other limitations in their current tool, most notably the computational cost of graph construction based on an all-versus-all sequence alignment to construct a joint sequence graph and the challenge of Bayesian parameter estimation as the number of subgraph entities scales with input data size. Since efficient approximate methods exist to find edges between similar text strings, the underlying idea of applying uncertainty-aware statistical inference to subgraph communities is promising, and the paper advances its primary goal.

Weaknesses:

The paper proposes the utility of the joint-graph community occupancy framework through three examples. I discuss potential weaknesses apparent in each separate example in turn.

(1) Weaknesses in Example 1

A broad weakness of the first results section ("Detecting EBV- and MART1-antigen reactive T cell communities from single cell datasets") is its reliance on a single vendor-generated dataset generated by the company ParseBio with no published experimental protocols and limited, if any, prior peer review. For reasons I will explore in greater detail below, the EBV-sample data may be particularly prone to chimeric pairings that confound the authors' primary analysis goals, and, at the very least, may not reflect physiologically realistic conditions for identifying antigen-reactive TCRs in other contexts.

Let us first consider Dataset 1 in more detail. The authors compare 2 antigen-stimulated repertoires with 3 unstimulated controls. To improve on single clonotype-level comparisons, the authors propose comparing the cell count aggregated across cells within joint graph communities constructed from paired CDR3 sequences across all the samples. Thus, one of the most relevant questions one hopes the authors answer in this section is whether the resolved graph communities are made up of many distinct clonotypes (i.e., are they polyclonal), allowing the method to function as intended by aggregating across multiple clones with putative shared antigen-reactivity.

Supplementary Figure 1B shows the size of all the communities with callouts for the putative EBV-expanded communities. The authors listed communities strongly enriched in the EBV-stimulated sample as e1, e2, e3, and e5. Each contains {greater than or equal to}100 clonotypes, and the authors note they contain at least one clonotype with a CDR3 sequence matching an EBV-annotated clone in VDJdb - a database of TCRs with some experimental evidence of epitope-reactivity. Community "e2" is notable for its remarkable size, including 1,339 unique clonotypes. At first glance, this seems promising for a method attempting to boost signal through community detection. However, it is worth re-investigating the individual clone sizes and sequences within this extraordinary community.

In the EBV-associated community "e2", a look at the data provided by the authors on the paper's GitHub repository suggests a single clonotype (clonotype_9; TRAV12-3 CATQGSNDYKLSF / TRBV9 CASSTGQVATNEKLFF) comprises 26,917 cells. As such, it makes up 29% of the sample with a total of 90,588 cells. If one clone supplies most of a graph community's cell counts, the community-level posterior estimate of β (Figure 1B) effectively tracks a single-clone estimate, and the premise of borrowing statistical power across a polyclonal expansion in this example is hard to assess.

There is also considerable evidence to believe that the apparent mega-polyclonality of cluster e2 may be partially an illusion, stemming from an artifact of this hyper-expanded clone's massive size and the experimental method used to assign TCRα-TCRβ chain pairings. In fact, the same α-chain CDR3 (CATQGSNDYKLSF) appears in ~1,219 clonotypes paired to distinct β chains, generating much of e2's remarkable 1,339-clonotype count. I believe two features warrant caution here. First, a single clonotype making up ~29% of total T cells in the sample is highly unexpected in ex vivo repertoires, suggesting intense non-physiological expansion conditions unlikely to generalize to other settings. That is, one would almost never expect to see a signal this strong.

Second, one TCR-α chain paired to ~1,220 distinct and diverse β chains in one sample is also biologically unexpected given what we know of the best-characterized epitope-specific responses for EBV, including to the well-known HLA-A*02 EBV BMLF-1 epitope, which recruits a tetramer-stained repertoire with conserved CDR3 motifs in both chains and at least some constraint on favored V-gene/α-β pairing (See Extended Data Figure 5 in Dash et al., Nature 2017). This raises the concerning possibility of barcode collision and mispairing against a hyperexpanded clone in the ParseBio split-pool method, unlikely to be robust to a clone occupying a third of the sample. Most of the ~1,219 β chains paired to the dominant α have a cell count of 1, further raising the concern of artifactual pairing versus genuine convergence. The second largest community "e1" also seems to suffer from the same issue, with a TCRβ sequence from one super clone making up 7% of the sample potentially being artifactually over-paired to >500 rare single-cell-count TCR α chains.

Taken together, these observations suggest that the authors' first positive control example passes but probably for the wrong reason since at least some of the "antigen-specific communities" are strongly anchored by a single hyper-clone. This could be remedied by repeating the same type of analysis on an ex vivo single-cell repertoire following more modest stimulation or natural infection (e.g., yellow-fever vaccine, influenza, or SARS-CoV-2 single-cell TCR datasets). I would advise future work using an alternative data source with better-documented experimental protocols, given the concerns above.

(2) Weaknesses in Example 2

Example 2 explores the application of Bayesian methods for identifying sample-enriched joint graph communities found in longitudinal data from many participants at two time points and longitudinal data from 1 person (Pt4) at 5 time points. A potential weakness of Case Study 2 is that it yields limited additional biological insight compared to what was previously shown by the authors of the underlying input data. Previously, Formenti et al. 2018 showed that the number of expanded clones after treatment strongly reflects responder status in this cohort, greater in patients with CR/PR versus SD or PD (See Figure 2b of the study). This 2018 primary analysis showed that tracking individual clonotypes was sufficient to reveal biological insight without the need for the computational demands of constructing a massive sequence similarity graph, finding communities on joint graphs, or Bayesian statistical inference. Thus, the impact of Case Study 2 in proving the unique utility of ClustIRR is somewhat diminished.

It is not clear how this study's result is more "robust" than the original analysis. Perhaps the authors could further clarify what is learned from the uncertainty-aware approach that could not be learned from exact clone tracking in time series.

Thus, example 2 shows that a complex method recapitulated the finding of a much simpler method for analyzing longitudinal TCR data where a strong signal of expansion was already present at the single-clonotype level. Since the Dirichlet method is sensitive to absolute counts, the large expanding clone in each community at 22 days may alone have carried most of the signal, which is not fully explored.

In this section, the authors make an interesting observation that CDR3β detected in both PBMC and patient-matched tumor samples were enriched in contracting communities (7/14) versus expanded communities (1/41). The authors do not indicate whether a similar enrichment of tumor-infiltrating lymphocytes (TILs) matched Day 0-22 contracting communities in the other 4 patients with tumor-matched samples, which, if consistent, would strengthen their finding.

(3) Weaknesses in Example 3

The final example explores "convergent repertoire differences between species." This is intriguing in principle but less informative due to the use of synthetic data with somewhat predictable properties that some may reasonably consider baked in by the data-generating process. That is, some of the results might be guaranteed by the way the data is constructed using the OLGA/IGoR generative model. For instance, the authors observe a positive correlation between CJ community size and Pgen of constituent clonotypes, stating: "This indicates that CDR3 sequences with high Pgen are statistically more likely to be generated, leading to convergence of similar sequences into public CJs." I may be mistaken, but this conclusion is almost guaranteed by the way the data-generating OLGA model outputs more similar high-Pgen sequences and fewer lower-Pgen sequences.

An interesting finding in this section is shown in Figure 4B, where community-level aggregation allowed for discrete clustering of human samples away from mouse samples that was not possible by comparing cosine similarity of a sparse clonotype occurrence matrix, a result that would be higher impact if it could be shown to separate real repertoire samples from humans with differential serology, vaccination status, or HLA backgrounds.

(4) Weaknesses in General

More generally, one aspect of the method that seems under-emphasized is the fact that many of the nodes in a multi-sample joint sequence similarity graph may have no edges. These zero-degree nodes would probably frequently occur in only one sample but be absent in other samples. It is not strongly emphasized in the paper how the model would infer whether such a singleton found in only one sample in the graph could be reliably inferred to be sample-specific enriched (see, for example, the large single node in Figure 3D, the orange node labeled "GQYF" in the far-right position of the lowest row in panel D). Presumably the number of cell counts represented in this single-sequence node is so great at sampled timepoint Day 22 as to yield a statistically strong signal in the multinomial model; however, the authors may wish to comment on how, for such singleton sequences, the power to detect sample-specific enrichment differs from prior single-clonotype-based methods.

With any large effort to find statistically significant features from a large candidate set examined all at once, a reader might be concerned with the potential for false discovery. Throughout, the authors seem to assign statistical significance when the 95% high-density interval (HDI) of the posterior estimate excludes zero or when the 95% HDIs of two features do not overlap. There is little discussion of how this implicitly handles multiplicity adjustment via shrinkage, which the authors could address more directly and explain more clearly to a broad audience, including many non-statisticians, who will read this paper.

Reviewer #3 (Public review):

Summary:

Analysis of immune receptor repertoires (IRR) needs to take into account the underlying diversity of the repertoires analysed, and the limitations inherent to the technologies used to measure IRRs: limited sampling depth relative to total number of cells and clonotypes, and experimental noise. In this work, Kitanovski and colleagues present ClustIRR. ClustIRR proposes to improve the analysis of immune receptor repertoires, specifically TCRs in the presented applications, by performing two steps: (1) consistent and comparable sequence clustering across repertoires, to account for sparsity of sampling, and (2) estimation of sequence clusters of interest using a Bayesian approach. They showcase ClustIRR performance in 3 scenarios: detection of antigen-specific T cells in a peptide-stimulation, detection of T cells responding to immunotherapy in the context of lung cancer, and analysis of mouse and human T cell repertoires.

Strengths:

(1) The cluster occupancy calculation presents an important conceptual framework which would be of interest and useful to the TCR repertoire field as it smoothly integrates information over a set of experimental conditions or time points. The application to longitudinal TCR sequencing datasets is particularly interesting, and could easily be extended to BCR sequencing datasets. Moreover, the calculation can be performed with any user-defined grouping of TCR clones, which allows for usage of other existing methods as the user wishes.

(2) The results of the human and mouse repertoires provide a very insightful argument for the use of metaclones as opposed to single clones for analysis of repertoires compared to single clones.

Weaknesses:

(1) While ClustIRR provides an interesting framework to analyse TCR sequencing datasets, it is not clear whether ClustIRR can perform more informative sequence clustering than state-of-the-art methods. A comparison of obtained clusters with existing methods would provide a useful benchmark. Moreover, computation time scales quite fast with the number of sequences included. This is a major limitation, as the authors state that a time of 2.5 hours is required for clustering of ~100,000 sequences, a number of clones that can easily be reached when analysing multiple samples together.

(2) The authors claim in the abstract that ClustIRR is integrated with gene expression data. However, in the results presented, the gene expression and TCR sequencing data are analysed separately, and the results are simply correlated. No real integration in the analysis exists for these two data types. The claim should be removed from the abstract. Moreover, the differential gene expression section, while it presents interesting results, lacks clarity and transparency. Presentation of the data in more transparent ways (such as showing violin plots or clustering on the UMAP) would increase the strength of the claims.

(3) The score calculation does not seem to be normalized to take into account the underlying diversities of CDR3a and CDR3b. While still a useful metric for sequence clustering, I worry about the impact of the lack of normalisation on the conclusion that the "alpha chain drives functional convergence through germline bias". The observation that clustering is mostly driven by the J gene is known and expected (https://pmc.ncbi.nlm.nih.gov/articles/PMC5553937/), as the J gene has lower diversity and greater overlap with the definition of CDR3. Because CDR3a is lower diversity generally from CDR3b, it will likely dominate the sequence similarity signal. Thus, it will appear that Ja drives the signal. The authors do try to address this by looking at clusters driven by CDR3b similarity. However, a low number of CDR3b-driven clusters is consistent with the similarity definition. I wonder if instead the appropriate control for this analysis would be to run the same analysis disregarding CDR3a sequence altogether, and quantify whether similar species-specific DCJ are identified when only CDR3b similarity is used? Absence or reduction of species-specific clustering would confirm that the effect is driven by the CDR3a sequence.

Reviewer #1 (Public review):

This meta-analysis addresses long-standing questions about the reliability and interpretation of choice probability in macaque visual areas, and provides some important findings (e.g., the cross-study consistency of the CP-sensitivity relationship, V1 distinctiveness). However, the evidence for several claims is incomplete: the analysis does not consider the statistical dependence of data points from the same studies and monkeys, and both the bistable-stimulus effect and the stimulus-duration effect rely on interpretive assumptions.

Strengths:

The paper's transparency about its own limitations is a genuine strength. Several sections of the paper and the supplement report null results (task exposure, lapse rate, eccentricity) rather than omitting them. This kind of self-scrutiny is uncommon in meta-analyses and substantially increases confidence in the parts of the analysis that do hold up.

Weaknesses:

(1) No mixed/hierarchical statistical models for nested data. The paper considers 150 data points from 59 studies and treats them as independent samples, though many share monkeys and brain areas. This reduces the confidence in the reported p-values. A standard way of dealing with this would be to use mixed-effect models with random intercepts rather than OLS.

(2) Evidence for one of the main findings in the abstract ("First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception.") is weak. This effect relies entirely on studies using bistable rotating cylinder stimuli performed in a single lab (lines 702 - 711). I would suggest making this more explicit in the abstract / discussion and in Figure 8b,c.

(3) The interpretation of main drivers of CP is unclear. The discussion summarizes the 4 main drivers of CP as "four systematic drivers of this variability: neuronal sensi758tivity, brain area, stimulus duration, and task type." The independent contribution of task type is however, questionable. In line 623, it is stated that the difference between coarse and fine discrimination can be entirely explained by the difference in sensitivity (explained possibly by differences in optimizing the stimuli). Again, detection tasks (line 658) show a trend for higher CP because most studies used tailored stimuli from single-recording experiments. Bistable task: see point 2. Thus, all "task effects" can be attributed to confounds, and the claim of the "four drivers of CP" should be revised.

(4) The paper could be improved by a Discussion that synthesizes the results in a concise manner. Now it seems more like a re-iteration of the results. Overall, I appreciate that the paper is thorough and discusses many of the caveats. However, those are somewhat buried in the long subsections, and I fear that the quick reader may walk away with a stronger impression of "four robust independent drivers" than the text, read carefully, actually supports.

(5) Datapoints are not weighted according to their standard error (common practice in meta-analysis is inverse-variance weighting). The concern is that underpowered studies with high variance (e.g., due to a low number of recorded neurons) have the same impact as well-powered studies, and this may change some of the estimates. For example, Supplementary Figure 4 shows that mean CP values decrease with statistical power of the study, consistent with the concern. If SEMs are not available, could the authors show the robustness of the results by weighting by sample size as a partial check?

(6) Interpretation of feed-forward vs. feedback origin of CP [Disclosure: I am an author of Wimmer et al. 2015.]. This paper presents a mechanistic network model of area MT and a decision area that decomposes CP into two components with distinct time courses, and, directly relevant to Section 2.6, shows how a combination of an early feedforward and a late feedback component can produce a roughly time-invariant (flat) CP. This is a specific, quantitative instance of the "sustained plateau" pattern the authors themselves note is inconsistent across studies (lines 480-486) but don't develop further. Engaging with this model in Section 2.1/2.6 would let the authors contrast their duration-effect interpretation against an explicit dynamical model rather than the generic feedforward/feedback dichotomy in Figure 7a.

(7) Reaction-time experiments. I am worried that differences in CP in RT vs. fixed duration tasks (Supplementary Figure 12) could have an influence on the main regression analysis (because RT experiments are mostly from detection tasks, and because RT experiments presumably include less of a post-decision period). Could this factor be included in the main analysis?

Reviewer #2 (Public review):

Summary:

This manuscript by Pletenev et al. provides a meta-analysis of 59 published studies on decision-related activity in the macaque visual cortex. The work does not contain original research material, but by conducting extensive analyses and compilations of previously published data, it provides several new insights not already conveyed in recent reviews on this topic.

Strengths:

The work is scholarly and helps organize and integrate a broad set of findings. A difficulty in such an undertaking is making sure that the original studies are accurately characterized and tabulated. The lead authors should be commended for the rigorous approach they've taken; the inclusion of many of the authors of the original studies as co-authors provides additional reassurance that trends visible across studies reflect an accurate quantification of what each study has shown.

Weaknesses:

My sole scientific concern is on the 'duration' section (lines 487 to 536). Specifically, the authors relate the dependence of choice probability (CP) on time to two competing (but not mutually exclusive) views of how CPs arise-the 'feedforward' vs 'feedback' views. The basis for the predictions in this section was not clear to me. In particular, it was not obvious that the predictions fully considered all the relevant factors. For instance, did the feedforward predictions consider how the response covariance depends on duration and how this would affect CP values (Equation 1)? (See for example Figure 4 of Kang and Maunsell, 2012, JNP.)

I would suggest either explaining the basis of the predictions much more carefully or moving the predictions to a supplementary section where they can be presented in more detail (i.e., more convincingly). Alternatively, since the section is inconclusive in the end (there is not strong evidence in favor of FF or FB), the authors could mention the theoretical predictions in passing only, i.e., much more briefly, just to make the reader aware that the different theories can provide predictions about the duration dependence.

Reviewer #3 (Public review):

Summary:

This study presents a comprehensive meta-analysis of choice probability (CP), a classic metric of the relationship between single-neuron responses and an animal's perceptual judgment. The authors compiled data from 59 macaque electrophysiology studies and identified several factors that consistently influence CP magnitude, including neuronal sensitivity, brain area, stimulus duration, and task type. These results provide evidence that helps settle several long-standing debates about how CP should be interpreted.

Strengths:

This work is a rare example of meta-analysis in macaque electrophysiology, focusing on an important and long-debated metric, choice probability (CP), in the study of sensory and decision-making mechanisms. CP has been measured across many studies, but its interpretation remains contentious because it depends on numerous task and recording factors in addition to sensory and decision-making mechanisms. Individual macaque studies also typically include few subjects, and CP effects are generally small, which prevents any single study from drawing strong conclusions about general patterns. The authors identified an ideal use case for meta-analysis and combined fragmented findings from individual primate studies into a coherent picture of which factors matter most for CP and which do not. This work can also serve as a guide for future meta-analyses of macaque electrophysiology data.

Weaknesses:

While the survey and discussion of CP's interpretation are comprehensive, the paper would benefit from a clearer conclusion on why measuring CP remains important and what future directions could make CP more useful for revealing sensory and decision-making mechanisms.

Reviewer #1 (Public review):

Summary:

The authors investigated somatosensory processing along the afferent somatosensory pathway (cuneate nucleus, thalamus, S1) in a group of spinal cord injury patients and a group of controls. They propose that reduced motor function in SCI patients would reduce bottom-up activity; thus, recorded activity in SCI patients would reflect top-down modulation of overt or attempted movements.

Strengths:

(1) Strong methods.

(2) Experimental and control groups.

(3) Strong writing.

(4) Results well presented.

(5) Appropriate statistics.

Weaknesses:

Some results (or lack of) cast doubt about the ability of the used technique (3T fMRI) to detect the desired effects (bottom-up vs top-down activity).

Reviewer #2 (Public review):

Summary:

This study addresses a question that has been essentially inaccessible in humans: whether the early somatosensory relay nuclei are engaged by anything other than peripheral drive. Using functional and quantitative MRI in individuals with chronic cervical spinal cord injury, the authors show that the cuneate nucleus and VPL are robustly engaged during overt or attempted hand movement, and that this engagement persists in a participant with complete hand paralysis and no detectable muscle activity. They further report structural degeneration of the cuneate nucleus that is unrelated to the preserved task-evoked activity, and interpret the residual activity as reflecting top-down corticocuneate signalling.

Strengths:

The work is well conceived and clearly written, and the demonstration that the cuneate nucleus and VPL are robustly engaged during (attempted) hand movement after chronic cervical spinal cord injury is, to my knowledge, novel at this level of anatomical resolution. The finding is convincing. The dissociation between preserved task-evoked activity and marked structural degeneration of the cuneate nucleus is a highly interesting result with clear implications for rehabilitation. The manuscript is straightforward to follow, and the imaging protocol is carefully executed.

Weaknesses:

My main reservation concerns the inferential step from "not peripheral" to "corticocuneate". The data establish the former convincingly; the latter may not.

(1) Attribution of the observed activity to corticocuneate projections.

The central claim rests on an argument by elimination: because bottom-up drive is excluded in PT01, the residual activity must be top-down and, by extension, corticocuneate. Two distinct gaps should be addressed. First, "top-down" is not equivalent to "direct corticocuneate". Descending influence could reach the cuneate nucleus through multiple indirect pathways. Second, the activity observed at the three levels (cuneate, VPL, S1) need not be serially propagated, since layer 6 corticothalamic projections, for example, could drive VPL independently of any cuneate contribution. I would ask the authors to either provide evidence bearing on the routing, or to consistently use a route-neutral term (e.g. "descending" or "top-down") and reserve "corticocuneate" for the discussion of candidate mechanisms.

(2) Afferent input arising above the lesion level.

The EMG control in PT01 was restricted to hand and forearm muscles. Musculature innervated above C4 (cervical paraspinals, trapezius, and to a variable extent the shoulder girdle) remained available to this participant, and attempted hand movement is frequently accompanied by increased proximal co-contraction, postural stabilization, and altered respiratory effort. Afferent to the upper cervical cord is known to project to the ipsilateral cuneate nucleus, and its activity would produce lateralized, ipsilaterally dominant cuneate input - that is, precisely the pattern reported. This alternative is not excluded by the present control and should be addressed directly, ideally with proximal EMG in PT01 (and, if possible, in the other participants), or at minimum with an explicit discussion. Relatedly, the authors recorded respiratory and cardiac signals: please report whether respiratory volume or heart rate differed between movement and rest blocks, and between groups, since the dorsal medulla lies adjacent to cardiorespiratory nuclei.

(3) Functional significance of the preserved top-down signal.

The discussion establishes that top-down input persists but says relatively little about why it should. If the principal role of descending input to the cuneate nucleus is the gating of incoming afferent traffic, then in the absence of afferents there is nothing left to gate, and one might have expected the signal to be lost. Its persistence is the most interesting aspect of the finding and deserves fuller discussion. Candidate accounts the authors may wish to consider include: an efference copy or predictive signal delivered to a comparator that no longer receives its input, in the framework the authors already invoke (references 27, 28); engagement of the non-lemniscal outputs of the dorsal column nuclei (e.g., cuneocerebellar, cuneo-olivary projections); attempted movement engages motor imagery and attention, in which case the relevant question becomes what distinguishes these from movement-related gating. A related interpretational point: in behaving primates, movement-related modulation of cuneate transmission is bidirectional and includes prominent suppression (refs. 7/12). Note also that BOLD increases are compatible with increased inhibition, so they do not indicate facilitated throughput.

Reviewer #1 (Public review):

Summary:

This manuscript uses a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys to examine one aspect of the relationship between LC activity and pupil diameter: whether baseline LC activity predicts evoked pupil and whether baseline pupil predicts evoked LC. These relationships are largely absent in the present dataset, and the authors conclude that this type of prediction is not reliable.

Strengths:

This is a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys, the within-modal and within-epoch analyses are sound. The new results further caution the use of pupil diameter to infer LC activity.

Weaknesses:

There is an obvious rationale for asking whether baseline LC relates to baseline pupil or evoked LC relates to evoked pupil. It is also obvious to ask about the relationship between baseline and evoked LC activity, and between baseline and pupil responses. However, the rationale for the cross-modal and cross-epoch analysis is not clear. Why should one expect baseline LC to predict evoked pupil, or baseline pupil to predict evoked LC? What is the biological importance of such predictions? These analyses simultaneously change the modality and the temporal domain.

Furthermore, some recent studies, which are not referenced in this manuscript, showed variability in the relationship between pupil and LC within the same epoch, and that tonic and phasic pupil responses could be regulated by different inputs to LC. Given that the pupil-LC coupling is readily imperfect and potentially controlled by different cellular and circuit mechanisms, it is not surprising that their cross-epoch relationship is even more variable.

One main analysis that correlated baseline pupil with evoked LC showed statistically different results between the two monkeys, raising the question of to what extent a general claim for the cross-modal cross-epoch analysis can be made.

Reviewer #2 (Public review):

The manuscript by Thompson and Gold reported that, although baseline and evoked LC activity were positively correlated with baseline pupil size and evoked pupil dilation, respectively, there were no reliable cross-epoch relationships between LC activity and pupil size - that is, between baseline LC activity and evoked pupil dilation or between baseline pupil size and evoked LC activity. A major strength of the study is its large dataset, comprising recordings from more than 100 LC single units collected across 83 recording sessions in two monkeys. The authors further strengthened their conclusions by performing several control analyses to rule out potential confounds, including whether the findings were influenced by (1) the use of residuals in the main analyses, (2) the possibility that the auditory stimulus failed to evoke the full dynamic range of LC activity and pupil responses, and (3) nonlinear cross-epoch relationships between LC activity and pupil size.

These findings are important because they remind researchers to exercise caution when assuming that non-illuminance-mediated fluctuations in pupil size can reliably serve as a proxy for LC activity under all experimental conditions

With that being said, I have two suggestions that I believe would further strengthen the manuscript.

(1) Previous studies have suggested that the LC is organized into functionally distinct subpopulations (e.g., PMID 28920933 and PMID 40770025). It is therefore possible that a subset of the LC neurons recorded in this study does not participate in controlling pupil size. I encourage the authors to discuss this possibility in the Discussion. In addition, this possibility could be tested by repeating the cross-epoch relationship analyses using only LC units that exhibit a strong correlation with pupil size (the darker points in the last column of the top two rows of Figure 1?).

(2) The manuscript would benefit from a clearer visualization of the analyses addressing the possibility that the auditory stimulus failed to evoke the full dynamic range of LC activity and pupil responses. A supplemental figure illustrating the distributions or ranges of LC activity and pupil responses, together with the corresponding control analyses, would help readers better understand this important point.

Reviewer #1 (Public review):

Summary:

The authors asked whether neurofeedback during competing continuous speech can help to modulate the attention-related N1-component in the temporal response function (TRF), which is an event-related-response-like estimate of the phase-locked EEG activity following the envelope. The research question is relevant because it asks to what degree the strength of attention can be controlled beyond the binary decision to attend or ignore something, and whether this control is beneficial for the behavioral outcome.

Strengths:

(1) Sample size of 56 participants.

(2) Control group with sham feedback.

(3) Novelty: Under-explored field of neurofeedback in selective speech tracking.

(4) Pragmatic and reasonable methodological decisions.

(5) Transparent results not hiding the fact that effect sizes are small.

Weaknesses:

Besides some need for clarification, I could only find one methodological weakness, which the authors discuss anyway:

(1) Overall, speech tracking-based neurofeedback may lead to more robust results, because the N1-extraction does not have to be handcrafted and all components would be taken into account. As the authors state, the P2-component has been related to effort, and this may provide more "room to play" for voluntary modulation.

The following "weaknesses" are related to the impact of the results:

(2) Non-translating effects to post-training trials, neither neurally nor behaviorally.

(3) Neurofeedback-related Modulation of N1

Reviewer #2 (Public review):

Summary

This manuscript investigates whether neurofeedback based on the N1 component of the temporal response function can be used to modulate neural responses during selective attention to continuous speech. Participants listened to two competing audiobooks and were instructed to attend to one of them. In the neurofeedback group, trial-by-trial N1 responses were converted into visual feedback, whereas the sham-feedback group received replayed feedback from other participants. The authors found a significant interaction between group and block for the N1 response to target speech over a small fronto-central cluster, with larger N1 responses during feedback blocks in the genuine neurofeedback group but not in the sham group. No neurofeedback effect was found for the distractor response. The authors also reported exploratory post-training effects and an association between changes in N1 and speech-comprehension performance at right fronto-central electrodes.

Overall, the study is conceptually interesting and novel. The online, trial-by-trial estimation of neural responses from continuous speech is an attractive development for auditory neurofeedback, and the inclusion of a randomised sham-feedback group is an important strength. However, the manuscript provides stronger evidence for modulation of a neural response during feedback than for learning or training of selective attention. Some aspects of the analysis and interpretation also require further consideration/clarification, particularly the use of group-specific N1 time windows, the spatial confound between target and distractor streams, the absence of artefact correction in the signal used for feedback, and the relatively weak behavioural evidence.

Strengths

The main strength of this study is its novel use of neurofeedback during continuous competing speech. Rather than providing feedback based on a general measure of brain activity, the authors targeted a specific neural response associated with selective auditory attention. The online implementation is technically impressive, allowing neural responses to be estimated from 22-second speech segments and converted rapidly into feedback. The inclusion of a sham-feedback group is another important strength, as it helps distinguish effects of genuine neurofeedback from nonspecific effects such as task engagement or motivation. The relatively large sample for a neurofeedback study and the use of natural continuous speech also increase the robustness and ecological relevance of the work.

Weaknesses

(1) The effect was present during the feedback blocks but did not increase across training blocks, and the post-training effect was not found at the same electrodes used for feedback. The evidence therefore supports online modulation more strongly than learning or lasting self-regulation, and claims about successful training or persistent learning should be interpreted cautiously.

(2) The offline analysis used different N1 time windows for the neurofeedback and sham groups. This introduces a potential bias in the group comparison because the dependent measure was defined differently between groups. Confirmation of the main result using a common, independently defined N1 window would strengthen the evidence.

(3) The target speech was always presented from the front and the distractor from behind. Differences between target and distractor responses therefore cannot be attributed entirely to attention because spatial location is also different. This limits the interpretation of target-versus-distractor differences and may also contribute to the weaker reliability of the distractor response.

(4) Feedback blocks always contained two speakers, whereas half of the baseline trials contained only one speaker. Since the presence of a distractor altered the neural response, it is important that the neurofeedback comparison is based on acoustically matched multi-speaker baseline trials. If this were not the case, differences between baseline and feedback could partly reflect differences in the acoustic condition rather than neurofeedback.

(5) No artefact correction was applied to the signal used for online feedback. Because feedback was derived from fronto-central electrodes, eye or muscle activity could potentially contribute to the measured signal. An offline demonstration that the main neural effect remains after appropriate artefact control would strengthen the interpretation that the effect reflects neural modulation rather than systematic changes in non-neural activity.

(6) The behavioural evidence is weaker than the neural evidence. There was no significant overall improvement in speech comprehension in the neurofeedback group. The reported behavioural effect is instead based mainly on associations between changes in the neural response and changes in comprehension, and some of these effects were weak before the whole-scalp analysis. Therefore, these findings are better interpreted as exploratory associations rather than evidence that neural modulation directly caused improved comprehension.

(7) Adding the distractor did not significantly reduce comprehension performance. The absence of a significant distractor effect on comprehension suggests that the listening condition may not have produced a strong behavioural cocktail-party difficulty in this sample. The large spatial separation between speakers and the nature of the behavioural task may have reduced sensitivity to distraction, which could limit the strength of the conclusions regarding improvement of speech understanding in challenging listening conditions.

(8) The study is described as double-blind, but the manuscript provides limited detail on how blinding was maintained, particularly when the experimenter manually checked the N1 estimate. In addition, participants' belief in or perceived control over the feedback was not formally assessed. These factors make it difficult to determine how effectively expectancy or motivation-related effects were controlled.

Overall assessment:

This study provides a valuable methodological and conceptual advance by showing that online, trial-by-trial neurofeedback can modulate the neural response to attended speech during competing speech. The evidence is solid for an immediate neural effect during feedback, and it was supported by comparison with a sham-feedback group. However, it remains incomplete for broader claims about learned self-regulation, persistent effects, distractor suppression, and improved speech understanding.

Reviewer #1 (Public review):

This work provides a valuable toolkit for endogenous isolation of projection neuron subtypes. With further validation, it could present a solid method for low-input ribosome affinity purification using a ribosomal RNA (rRNA) antibody. The experimental evidence for the distinct ribosomal complexes is limited to this method and indirect support from complementary analyses of pre-existing data. However, with additional experimental data to support the specificity of ribosomal complex pulldown and confirmation of the putative ribosomal complex proteins of interest, the study would provide compelling evidence for translation regulation of neuronal development through compositional ribosome heterogeneity. This work would be of interest to neuroscientists, developmental biologists, and those studying translational networks underlying gene regulation.

Strengths

(1) This in vivo labeling of specific projection neurons and ribosomal rRNA affinity purification method accommodates a low input of <100K somata per replicate, which is useful for the study of neuronal subtypes with limited input. In principle, this set of techniques could work across different cell types with limited input depending on the molecule used for cell type labeling.

(2) The authors are also able to isolate endogenous neurons with minimal perturbation up to the point of collection, preserving the native state for the neuron in vivo as long as possible prior to processing.

(3) This study identified over a dozen potential non-ribosomal proteins associated with SCPN ribosomal complexes, as well as a ribosomal protein enriched in CPN.

Limitations

(1) In this study, the authors address the advantages of their ribosomal complex isolation method in SCPN and CPN against RPL22-HA affinity purification. While this does show more pull down of the ribosomal RNA by the Y10B rRNA antibody, the authors claim this method identifies cell-type specific ribosomal complex proteins without demonstrating a positive control for the method's specificity. There are very limited experiments to truly delineate how "specific" this method is working and whether there could be contamination from other complexes bound by the antibody. I see this as the major limitation that should be addressed. To boost their claims of capturing cell-type specific ribosomal complexes, the authors could consider applying their rRNA affinity purification pipeline to compare cell-types with well-characterized ribosome-associated proteins, like mouse embryonic stem cells and HELA cells. The reviewer can completely appreciate the elegance in the neural characterization here, but it seems there needs to be a solid foothold on the specificity of the method, perhaps facilitated by cell types that can be more readily scaled up and tested.

(2) The authors followed up on their differentially enriched ribosomal complex proteins by analyzing ribosome association of these proteins in external datasets. While this analysis supports the ribosome-association of these proteins, there is limited experimental validation of physical association with the ribosome, much less any functional characterization. The reciprocal pulldown of PRKCE is promising; however, I would recommend orthogonal validation of several putative ribosomal complex proteins to increase confidence. Specifically, the authors could use sucrose gradient fractionation of SCPN and CPN, followed by western blot to identify the putative interaction with the 80S monosome or polysomes. This would also provide evidence towards the pulldown capturing association with mature ribosome species, which is currently unclear. This experiment would provide substantial evidence for the direct association of these non-ribosomal proteins with subtype-specific ribosomal complexes.

(3) The authors state interest in learning more about the differences underlying translational regulation of projection neuron development. This method only captures neuronal somata, which will only capture ribosomes in the main cell body. There are also ribosomes regulating local translation in the axons, which may also play a critical role in axonal circuit establishment and activity. These ribosomal complex interactions may also be rather transient and difficult to capture at only one developmental stage. Therefore, this method is currently limited to a single developmental snapshot of ribosomal complexes at P3 within the main cell body. It would be exciting to see extended utility of this method to sample neurites and additional developmental stages to gain further resolution on the developmental translation regulation of these projection neurons.

Likely impact of the work on the field, and the utility of the methods and data to the community

The authors introduce a unique pipeline of techniques to identify cell-type specific ribosomal complex compositions. With more validation, there is certainly potential for those studying neuronal translation to leverage this method in limited primary cells as an alternative to existing methods that do not rely on ribosomal protein tagging, such as ARC-MS (Bartsch et al., 2023), RAPIDASH (Susanto and Hung et al., 2024), and RAPPL (Nature Communications, 2025).

Comments on revised version.

We thank the authors for their thorough response to our comments. The revised manuscript satisfactorily addresses most reviewer comments through clarification and expanded discussion, although we believe some important limitations remain. In particular, we continue to view experimental validation of the identified ribosome-associated proteins as an important component of introducing this methodology to the field, rather than work that falls beyond the scope of the study. The authors have acknowledged that these experiments are future directions, and it is clear they plan to pursue additional validation outside of the current manuscript. Given their emphasis that the primary contribution is the development of a methodological framework, we believe the work may be appropriately framed as a Tool and Resource article. Such positioning would better align reader expectations with the manuscript's strengths as a technical advance while recognizing that further validation and functional characterization will be needed in future studies. Despite these limitations, I believe the manuscript makes a valuable methodological contribution.

Reviewer #2 (Public review):

Summary:

The study by presents a sophisticated molecular dissection of ribosome-associated complexes (RCs) in two well-defined cortical projection neuron subtypes (ScPN and CPN) during early postnatal development. The authors develop and optimize an rRNA immunoprecipitation-mass spectrometry (rRNA IP-MS) workflow to recover RCs from FACS-purified, retrogradely labeled neurons, achieving remarkable subtype specificity and biochemical resolution. Through proteomic profiling, they reveal both shared and distinct ribosome-associated proteins between ScPN and CPN, with a focus on non-core RC components and their potential functional relevance. The work advances our understanding of cell-type-specific translation regulation, moving beyond the transcriptome to explore the proteome-level complexity in neuronal subtypes.

Strengths:

This work stands out for its technical sophistication and innovation. The authors combine retrograde labeling, FACS purification, and an optimized rRNA IP-MS approach (low input) to isolate ribosome-associated complexes from highly specific neuronal subtypes in vivo, a challenging issue that they execute with impressive rigor. The methodological pipeline is both elegant and well controlled, yielding high-quality, reproducible data. The depth of proteomic coverage is remarkable, with nearly all known cytoplasmic ribosomal proteins identified, along with hundreds of ribosome-associated proteins (RAPs), including translation factors, chaperones, and RNA-binding proteins. The analysis not only reveals shared components between ScPN and CPN RCs but also uncovers subtype-specific differences in associated proteins.

Particularly notable is the integration of this new proteomic dataset with previously published transcriptomic and ribosome footprinting data, which helps to validate the specificity and relevance of the findings. Overall, the clarity of the writing, the robustness of the data, and the transparency of the methods make this a strong and compelling contribution.

Weaknesses:

Despite the depth and high quality of the dataset, the study remains descriptive. While the identification of subtype-specific RC components is intriguing, the current version of the manuscript does not explore their functional roles or biological consequences of their alterations. There is no perturbation, causal testing, in vitro or in vivo manipulation to demonstrate whether these proteins are necessary for ScPN or CPN identity, specific axonal targeting, metabolism or synaptic function.

One important point that is also highlighted by the authors in their discussion and that is critical to establish the subtype specificity of the identified protein. One important point highlighted by the authors in the discussion - and critical for establishing the subtype specificity of the identified proteins-is that some ribosomal complexes may be specialized for specific developmental stages, rather than exclusively for the subtype-specific needs of projection neuron development. The work presented here provides a valuable starting point for further investigation into such RC specialization. However, it will be essential to determine to what extent these RCs exhibit true subtype specificity, independently of their temporal maturation context.

As a result, key mechanistic insights remain a bit speculative. Although several of the identified proteins have known roles in processes like synaptogenesis or metabolism, their relevance to the specific neuronal subtypes under study is not experimentally addressed. That said, given its rich content and the comprehensive early postnatal dataset, the manuscript represents an extremely valuable resource for the community. While primarily exploratory, it lays a strong foundation for future functional studies aimed at uncovering the biological impact of the identified ribosomal complexes.

Reviewer #3 (Public review):

Summary:

This manuscript presents a well-designed study examining human adaptation to room acoustics, building on prior work. The psychophysical results are convincing and add meaningful knowledge to our understanding of reverberation learning. The transcranial magnetic stimulation (TMS) component shows a role of prefrontal cortex in this listening task, targeting dorsolateral prefrontal cortex (dlPFC). Cautious interpretation of the TMS results is warranted, especially given the modest statistical effects, the fact that the main TMS result of interest is a null result, and the limited ability of TMS to precisely target dlPFC in individual subjects. A surprising and interesting finding in the study is that listeners performed the speech recognition task more poorly in anechoic conditions than in those with naturalistic levels of reverberation. This is likely due to contributions of spatial release from masking provided by reverberation acoustics, which may counteract the detrimental effects of reverberation on speech perception itself. Overall, the experiments are well performed and clearly presented, improving our understanding of how the brain copes with reverberant environments.

Strengths:

(1) Well designed acoustical stimuli and psychophysical task.

(2) Comparisons across room combinations is well conducted.

(3) Virtual acoustic environment is impressive and applied well here.

(4) Timely study with interesting behavioural results.

(5) Causal evidence of a role for dlPFC in reverberation learning.

Weaknesses:

(1) Poorer performance in anechoic environments than some reverberant environments suggests and interplay of spatial release from masking and speech intelligibility that are not fully unpicked here. This could be controlled in future experiments, for example by comparing monaural and binaural listening conditions.

(2) Lack of evidence for targeting TMS to dlPFC in individual participants. This is simply a limitation of the technique which the reader should keep in mind.

(3) Most interesting effect of TMS is a null result compared to a weak statistical effect for "meta-adaptation"

Reviewer #4 (Public review):

The authors use a d' defined for 2-alternative forced choice experiments, but their data are 4-alternative (for color) and 8-alternative (for number) forced-choice. So, the d' is not computed correctly. For mAFC experiments, the authors should use the Hacker-Ratcliff (1979) method, also defined in chapter 10 of the Macmillan & Creelman textbook.

Normalization of the stimuli was arbitrary, and consequently the unexpected improvement in performance in reverberation compared to anechoic condition is still not explained. A natural normalization across different environments is to take the direct portion of the BRIR (and HRTF for the anechoic condition) and make sure that that is scaled identically across the different simulated rooms (with the reverberant tails scaled naturally). That corresponds to the situation when the sources are emitting the sound at the same level in each environment. The current study scaled the overall levels. As a minimum, it should be reported how this scaling boosted/attenuated the targets and maskers in each environment.

The potential that the listeners are tuning to individual voices, as opposed to rooms, has not been eliminated. The authors suggest that a lack of interaction with different voices is evidence that that is not the case. This is not correct: lack of this interaction just means that there are no differences in tuning between the voices. But that does not mean that the same amount of tuning is happening for each voice, as observed in previous studies. Unless the authors provide a follow-up data with randomly varying voices within each trial, these claims should be tuned down.

Reviewer #2 (Public review):

The authors initial goal was to demonstrate loss of PG during the slow sporulation process of Myxococcus xanthus, with examination of the PG degradation products in order to implicate possible enzymes involved. Upon finding a predominance of LTG products, they examined sporulation in strains lacking each of the 14 candidate LTGs encoded in the genome, leading to the identification of two sporulation-linked LTGs. An extensive characterization of the roles played by these LTGs. One LTG is responsible for the slow sporulation PG degradation, while another is required for the rapid sporulation process. Interestingly, the "slow" LTG seems to provide an important regulatory brake on the rapid enzyme. Single molecule fluorescent tracking of these enzymes was used to develop a model for their interaction with PG that mimics their observed activity. The rate of PG synthesis activity was also shown to impact the rate of PG degradation, suggesting potential interplay between the synthetic and degradative enzymes.

Strengths:

The genetic analysis to identify sporulation-linked LTGs and their effects on growth sporulation, and spore properties was well done and productive. The fluorescence microscopy to track LTG mobility, presumably tied to activity, produced a convincing argument about the mechanism of regulation of one LTG by another. The authors have responded well to all points of the previous reviews.

Reviewer #1 (Public review):

Summary:

The study from Wu and Turrigiano investigates how disruption of taste coding in a mouse model of autism spectrum disorders (ASDs) affects aversive learning in the context of a conditioned taste aversion (CTA) paradigm. The experiments combine 2photon calcium imaging of neurons in the gustatory portion of the anterior insular cortex (i.e., gustatory cortex) with behavioral training and testing. The authors rely on Shank3 knockout mice as a model for ASDs. The authors found that Shank3 mice learn CTA more slowly and extinguish the memory more rapidly than control subjects. Calcium imaging identified impairments in taste evoked activity associated with memory encoding and extinction. During memory encoding, the authors found less suppressed neuronal activity and increased correlated variability in Shank3 mice compared to control. During extinction, they observed a faster loss of taste selectivity and degradation of taste discriminability in mutants compared to controls.

Strengths:

This is a well-written manuscript that presents interesting findings. The results on the learning and extinction deficits in Shank3 mice are of particular interest. Analyses of neural activity are well conducted and provide important information on the type of impaired cortical activity that may correlate with behavioral deficits.

Weaknesses:

The authors did an excellent job addressing the weaknesses highlighted in my first assessment.

Reviewer #2 (Public review):

Summary

Wu and Turrigiano investigate how Shank3 loss affects experience-dependent changes in sensory representations during conditioned taste aversion learning and extinction. Using longitudinal two-photon calcium imaging in the gustatory cortex, the authors show that Shank3 knockout mice acquire taste aversion more slowly but, after additional conditioning, reach an aversion comparable to wild-type mice; this learned aversion then extinguishes more rapidly. At the neural level, knockout mice exhibit reduced stimulus-evoked suppression and increased correlated variability; while learning and extinction are accompanied by changes in the reliability, selectivity and population-level discriminability of taste representations. The revised manuscript more clearly distinguishes baseline genotype-dependent differences in cortical activity from learning-associated changes and appropriately frames the relationship between neural activity and behaviour as associative rather than causal.

Strengths

A major strength of the study is the combination of longitudinal cellular-resolution imaging with a behavioural paradigm that allows cortical population activity to be followed across acquisition, retrieval and extinction. This provides a rich description of how sensory representations evolve as learned value changes, and how these dynamics differ following Shank3 deletion. The observation that knockout mice eventually acquire a robust aversion but subsequently extinguish it more rapidly is particularly useful because it separates impaired acquisition from subsequent instability of the learned association.

The revised manuscript has substantially addressed several concerns raised in the original review. Importantly, the authors now show that reduced stimulus-evoked suppression is already evident during pre-learning habituation and that increased coactivity therefore appears to reflect, at least in part, a pre-existing network property rather than a consequence of learning. They additionally report that the level of coactivity at the beginning of conditioning correlates with subsequent behavioural acquisition, providing a useful link between individual variation in cortical activity and learning performance. This analysis strengthens the association between cortical network state and behaviour without establishing causality.

Another useful addition concerns the potential contribution of licking behaviour to taste decoding. Because sampling behaviour necessarily differs as animals acquire an aversion, separating sensory representations from movement-related activity is difficult in this paradigm. The authors now perform decoding during the ten-second post-sampling period and find above-chance decoding after licking has ceased, making it less likely that differences in licking alone explain the principal population-decoding results.

The manuscript is also clearer in its anatomical and conceptual terminology. The recordings are now appropriately described as being from gustatory cortex rather than implying coverage of the broader anterior insular cortex, and the conclusions have been restricted primarily to conditioned taste aversion rather than generalised to cognitive flexibility more broadly. The latter is particularly important because whether these findings generalise to reversal learning, probabilistic learning, or other forms of adaptive behaviour remains unknown.

Weaknesses

The principal remaining limitation is mechanistic. The experiments establish a robust association between Shank3 deletion, altered cortical activity and altered learning dynamics, but they do not establish the causal relationships among these observations. The new correlation between early coactivity and subsequent learning is informative, but manipulating the relevant network property would ultimately be required to determine whether increased correlated variability contributes directly to slower acquisition. The authors now acknowledge this limitation and have appropriately removed language implying causality.

Similarly, the cellular or circuit origin of the altered correlated variability remains unresolved. Reduced inhibition is an interesting potential explanation, but the authors do not directly measure interneuron function or inhibitory transmission here. Consequently, the proposed relationship between Shank3 loss, altered inhibition, increased correlated activity, and impaired sensory encoding should remain a hypothesis emerging from the results rather than a demonstrated mechanism.

A further limitation is the absence of a full conditioned-stimulus-only Shank3 knockout control group. The newly analysed habituation recordings partly address this issue by demonstrating reduced suppression and a tendency toward increased coactivity before learning, and the cross-session decoding analysis suggests that naïve knockout cortical populations can nevertheless distinguish water from saccharin. These analyses considerably improve interpretation of the existing experiment, although they are not equivalent to longitudinal comparison with a knockout control group undergoing the complete protocol without aversive conditioning.

Finally, the interpretation of population activity in terms of taste identity, learned value and their interaction remains necessarily limited by the task design. The results clearly demonstrate experience-dependent changes in population discriminability, but because taste identity, learned value, and sampling behaviour covary during conditioned taste aversion and extinction, the present experiments cannot fully separate the precise information represented by these population changes.

Overall assessment

The revision has addressed the major interpretational concerns raised in the previous review and has strengthened the manuscript through several useful additional analyses. In particular, distinguishing pre-existing cortical abnormalities from learning-associated changes, relating early coactivity to subsequent behaviour, controlling more carefully for licking-related activity, and removing causal language better align the conclusions with the evidence. The study therefore provides solid evidence for altered experience-dependent sensory coding and learning dynamics following Shank3 loss, while the mechanisms connecting these phenomena remain an important question for future work.

Reviewer #3 (Public review):

In this study Wu & Turrigiano investigate an ethologically relevant form of associative learning (conditioned taste aversion-CTA) and its extinction in the Shank3 KO mouse model of ASD. They also examine the underlying circuits in anterior insular cortex (AIC) simultaneously, using two-photon calcium imaging through GRIN lens. They report that Shank3 KO mice learn CTA slower and suggest that this is mediated by a reduction in tastant-stimulus activity suppression of AIC neurons and reduced signal-to-noise ratio due to increased noise correlations in AIC neurons. Interestingly, once Shank3 KO mice do acquire CTA, they extinguish the aversive memory more rapidly than wild-type. This accelerated extinction is accompanied by a faster loss of neuronal and population-level taste selectivity and coding in the AIC compared to WT mice.

This is an important study that uses in vivo methods to assess circuit dysfunction in a mouse model of ASD, related to sensory perception valence (in this case taste). The study is well executed, the data are of high quality, and the analyses procedures are detailed. Furthermore, the behavioural paradigm is well thought, particularly the approach for assessing extinction through repeated retrieval sessions (T1-T5), which effectively tests discrimination between saccharin and water rather than relying solely on lick counts or total consumption as a measure of extinction. Finally, the statistical tests used are appropriate and justified.

Comments on revised version.

The authors have addressed all comments satisfactorily.

Reviewer #1 (Public review):

Summary:

This is a study which used 7T diffusion MRI in subjects from a Human Connectome Project dataset to characterize the zona incerta, an area of gray matter whose involvement has been demonstrated in a broad range of behavioral and physiologic functions. The authors employ tractography to model white matter tracts that involve connections with the ZI and use clustering techniques to segment the ZI into distinct subregions based on similar patterns of connectivity. The authors report a rostral-caudal organization of the ZI's streamlines where rostrally-projecting tracts are rostrally-positioned in the ZI and caudally-projecting tracts are caudally-positioned in the ZI.

Strengths:

The paper presents robust findings that demonstrate subregions of the human ZI that appear to be structurally distinct using a combination of spectral clustering and diffusion map embedding methods. The results of this work can contribute to our understanding of the anatomy and structural connectivity of the ZI, allowing us to further explore its role as a neuromodulatory target for various neurological disorders.

Weaknesses:

There should be further discussion of the clustering methods employed and why they are appropriate for the pertinent data. Additionally, the limitations of analyzing solely the cortical connections of the zona incerta should be addressed, as anatomical studies of the ZI have shown significant involvement of the ZI in tracts projecting to deep brain regions.

Comments on the latest version:

I reviewed the file and am more than satisfied with the authors responses and edits.

Reviewer #2 (Public review):

Summary:

Haast et al. investigated the organization of the zona incerta (ZI) in the human brain based on its structural connectivity to the neocortex. They found that the ZI is organized according to a primary rostro-caudal gradient, where the rostral ZI is more strongly connected to the prefrontal cortex and the caudal ZI to sensorimotor cortex. They also found that the central region of the ZI is differently connected to neocortex compared with the rostral and caudal regions and could be important as a deep brain stimulation target for the treatment of essential tremor.

Strengths:

I think the overall quality of this work is great, and the results are presented in a very clear and organized manner. I particularly appreciate the effort that the authors put into validating the results using 7T and 3T data, as well as test-retest data.

Weaknesses:

The initial version of the manuscript left me with a couple of minor concerns that the authors addressed in the revised version. These were related to the clinical relevance of the work (now addressed with the lower-resolution data), and to the initial emphasis on a dorso-ventral gradient that the data did not strongly support.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have responded critically to all issues raised in the initial round of reviews.]

Lohse et al. describe an open-source system for laser scanning photostimulation (LSPS) in head-fixed animals. Although similar systems have been developed and used by different groups, Zapit provides an open-source solution requiring few custom parts and minimal coding. This tool can clearly facilitate and speed the adoption of LSPS, particularly for the increasingly used purpose of mapping the effects of focal cortical silencing during behavior. Other potential uses include mapping optogenetically evoked movements and selectively activating genetically labeled neuronal subtypes of interest in the cortex. The design is well thought through, and the presentation is mostly clear and well written.

In general, the more modular such a system is, the better, in terms of compatibility with existing hardware and software that potential users may already have purchased - laser, galvo, and camera in particular.

Reviewer #2 (Public review):

Summary:

In this work, Lohse and colleagues develop a system for doing targeted photostimulation in mouse cortex. The system uses a camera image to target laser stimulation to stereotactically defined locations in mouse dorsal cortex.

Strengths:

The hardware is well designed, and the software is well documented and supported. The build guide and well-documented software package should allow for simple implementation of the technology. Without a doubt, this is a valuable community resource for the circuit neuroscience field.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #3 (Public review):

Zappit is an open-source implementation of arbitrary-access laser-scanning optogenetics for manipulation of neuronal activity in mice. As the method requires expertise ranging from optics, hardware control and programming, the authors make the point that this powerful strategy is underutilized in the field, and put forward a well-documented modular hardware and software platform aligned to the Allen Mouse Brain Atlas aimed at enabling the larger scientific community to use this approach (democratizing) for controlling cortical activity during behavior in mice.

The authors favor a galvanometric approach to laser targeting. The system is inexpensive, easy to build, well-documented and user friendly (Matlab based GUI and GitHub repository). The photo-stimulation laser is directed into an X-Y galvo scanner targeted to the specimen using a dichroic mirror and focused on the sample using a Plössl lens as scan lens which is also used as an objective. The scan lens/objective images the specimen onto a camera via tube lens (also a Plössl lens) in a 0.5X magnification ensuring to fit the extent of the mouse brain onto the camera sensor (USB-3 Basler acA120-40um).

The authors report short and reproducible onsite time (~ 0.5 ms) and block (mask) the stimulation source using the laser analog control (~0.5 ms). The system is reliable, aiming at up to 20 stimulation sites per sequence considered as quasi-simultaneous (10 ms). They minimize rebound by gentle ramping down of stimulation over 250 ms.

The system is fast to calibrate by mapping scanner positions to pixel space in the camera space and mapping stereotaxic coordinate onto the image of the exposed skull. The theoretical x-y PSF is 70 µm (measured ~90µm) while the authors make the point that due to scattering the photo-stimulation spot size (lateral extent) is about 1 mm in diameter. This is what they also observe in electrophysiological recordings using silicon probes. The effective radius of inactivation depends on laser power, but was about 1 mm for laser powers (1-2-4 mW) on which the authors observed significant behavioral perturbations - in several tasks: 1) a delayed response somatosensory discrimination, 2) a visual detection task assessing changes in temporal frequency of a drifting visual stimulus; and 3) a visual discrimination (International Brain Laboratory task) in which mice were tasked to report the location of visual stimuli by turning a wheel. As proof of principle, the authors used a photo-stimulation set composed of 52 bilateral sites positioned at 0.5 mm interval covering a large network of frontal, motor and somatosensory cortical areas. Indeed, photo-inhibition of frontal motor cortex sites produced robust increases in reaction time. In contrast, stimulation at other motor and somatosensory sites produced modest, but significant decreases in reaction times.

While the approach is not novel, it does serve the need of better disseminating this technique in the research community. Overall, the Zappit is well-documented and easy to build and use, and will have impact in increasing robust use of site directed photo-stimulation (exciting/inhibiting ensembles of neurons at particular ~1 mm size regions of interests across the dorsal surface of the brain). The authors also note that the axial resolution is ~1.5 mm.

Reviewer #1 (Public review):

Summary:

Yuan and colleagues present a thorough study of gene activation before and during metamorphosis in sponge larvae, combining in depth analyses of staged transcriptomes and chromatin accessibility profiling (ATACseq). Amongst several very interesting findings, the study reveals that the acquisition of settlement competence, which arises in response to decreasing light at sunset, is characterized by changes in chromatin accessibility that anticipate strong transcriptional shifts occurring as metamorphosis starts. Another notable finding is a set transcription factors amongst the genes strongly up-regulated at the onset of metamorphosis. In addition, larvae exposed to constant light, a condition that stalls metamorphosis, were found to activate metabolic pathways that are not normally expressed in swimming larva, Together the findings provide a rare level of understanding into how environmental conditions can promote deployment of alternative developmental programs in planktonic larvae.

Strengths:

This is a comprehensive and rigorous study of a phenomenon of wide interest. It will inspire researchers working on other species to look for similar, environmentally-driven "anticipatory" epigenetic mechanisms. It also provides a wealth of detailed information on genes, notably transcription factors, that are candidates for involvement in regulating specific metamorphosis transitions - and beyond. The data presented here are thus undoubtedly a rich and valuable resource.

Weaknesses:

It is not always straightforward to connect the conclusion statements in the text to the figures, or to grasp the aims and logic of the workflows.

Reviewer #2 (Public review):

Summary:

It is demonstrated that sponge larvae prepare for receiving the environmental cue (sunset) by extensively modifying their chromatin accessibility in the absence of large gene expression changes - "anticipatory" chromatin remodeling. This program can be offset by modifying the cue (making light constant), leading to a novel molecular state. These are the most important novel findings. Then, around metamorphosis there is dramatic regulation of transcription factors and their targets. While this result is hardly surprising, it is nice to see it demonstrated thoroughly in a phylogenetically fundamental animal study system.

Strengths:

This is a top-notch study of a key life cycle transition in an organism of great phylogenetic importance, involving concurrent gene expression and chromatic accessibility profiling (to the best of my knowledge, this has never been done in non-bilaterians and likely anywhere outside Vertebrata). The result is highly non-trivial. There is also an additional experiment modifying the key environmental cue (constant light), adding additional insight.

Weaknesses:

The paper presents a great amount of material, which somewhat obscures results related to the major novel finding ("anticipatory" chromatin remodeling). Among them is the fact that there is no significant statistical association between regions opened during remodeling and genes subsequently regulated during metamorphosis. This lack of direct association suggests that there may be more to the story than just priming the genome for metamorphosis.

Reviewer #3 (Public review):

Summary:

In their manuscript, Huifang Yan and colleagues perform RNA-seq (CEL-seq) and ATAC-seq experiments to profile the transcriptome and chromatin accessibility of sponge larvae across larval competence, settlement and early postlarval development. Amphimedon, the sponge species that they use, is amenable to lab experiments and can therefore be a convenient model for experimenting with this otherwise difficult to assay ecological parameters and cues. They had previously observed that light conditions (diminished light) at sunset are Sucritical for larvae to enter a pre-settlement stage and prime them for settlement and metamorphosis. In this paper they report that these conditions induce a gain of accessibility in many genes, including transcription factors, and that altering these conditions by providing continuous light at sunset affects this reprogramming event.

Strengths:

The above is a very interesting observation, one that the authors speculate that could have a broader significance and be a theme in many more larvae. I agree with the authors that this is an important finding and I think that the paper will be interesting for the broad readership of eLife. If this is the case, the authors open up a new theme of chromatin regulation, extensively studied in mammalian contexts, but severely understudied in pretty much every other context.

Weaknesses:

I think however that their paper often reports the data in a difficult to follow way, and that other sorts of analyses would have made the results more accessible for the broad readership.

Reviewer #1 (Public review):

Summary:

A well-presented computational work on how post-translational modifications take place from a thermodynamic and mechanistic point of view.

Strengths:

A model capable of recapitulating complex phenomena to simulate, such as phosphorylation.

Weaknesses:

The methodology relies on multiple user-defined parameters that alter the setup. Below are the specific concerns:

(1) The abstract reads: 'First, reactions that weaken favorable interactions are thermodynamically suppressed within condensates. As a consequence, regulation of condensate solubility is most efficient when PTMs tune interactions to values close to the solubility threshold.' This phrasing is confusing. PTMs that weaken interactions will, in principle, shift the solubility to higher values, and therefore closer to the thermodynamic conditions that allow for condensate formation, but if those transitions are most efficient when they tune interactions to values close to the solubility threshold, they will not be suppressed? The authors have to make this statement clearer to readers, which is particularly important in the abstract of the manuscript

(2) The computational framework used by the authors is reasonable given the coarse-grained nature of the model required to study this problem. However, there are multiple user-defined variables that require further validation in order to make their choices justifiable:

a) NN and NK have the same interaction epsilon value, as well as K-K. This would effectively make kinase form condensates on their own if the right stoichiometry was imposed. This should be re-evaluated with a reduced K-K interaction to validate whether the conclusions remain invariant with this assumption.

b) N, P and K beads also have the same molecular diameter. This should be justified, for instance, with solvent available surface area calculations to determine the excluded volume for the different species, or by citing other works that support this approach.

c) The phosphorylation reaction takes place when 2 particles are found within a 1.5sigma distance; however, this value choice is not justified. The authors should prove how variations to this choice affect their conclusions.

(3) Figure 2a is informative although not entirely intuitive to follow. It can be concluded, as the authors mention, that the capacity to form condensates decreases as phosphorylation is favored. Therefore, as the text also says, there is a higher fraction of P particles as lambdaP increases; however, the fraction NP/NT appears to decrease based on the color scale. According to the figure caption, this is meant to represent the fraction of P particles over the total, but this should not exceed 1. This should be clarified and better explained in a revised version. Moreover, the information related to this, shown in Figure S4a, is very informative, and I advise the authors to include it as part of the main set of figures, as it will potentially help many readers to follow the manuscript better. Moreover, in Figure S4a, some lines appear to be disconnected; this probably comes from trajectory merging; the authors must check this.

(4) 'At the interface, N and K concentrations remain relatively high, but scaffold proteins experience fewer stabilizing interactions, lowering the energetic cost of phosphorylation. This leads to enhanced reaction activity specifically at the boundary between phases.' This statement perfectly explains why the density profiles of K and N do not match the phosphorylation probability curve. This probability is determined by the energetic impact of the reaction and the probability of encountering each other in space, but also on the short timescale diffusion: N and K proteins have greater access to more microstates at the interface and can access them faster, while having enough density to encounter each other. It would be interesting for the authors to prove or invalidate this argument. At the very least, it should be mentioned.

(5) Characterizing the real impact of condensate interfaces in real size condensates is an interesting approach, nonetheless this paragraph lacks most of the necessary details to be robust and obtain any reliable conclusion out of it in its current form:

a) There are several CALVADOS parametrizations, which one do the authors use? The force field must be cited.

b) R is not well defined in the caption.

c) In the rendered images, periodic boundary conditions appear not to be implemented; this should be clarified

d) In the Intermolecular energy profiles, it seems that FUS-LC has no condensate bulk.

e)How is the interface width calculated?

f) Why do the authors choose the energy profile and not density? Or other observables such as the radius of gyration.

g) The interface width will depend on the temperature, and how distant this temperature is from the critical temperature for phase separation. Currently, this information is lacking.

h) Variations in the temperature, quantity used to define the interface, should be addressed in order to make the interfacial importance claim robust.

(6) 'Since the size of typical cellular condensates rarely exceeds the 2 μm diameter'. This statement should be supported by multiple references.

(7) Figure S2 should be improved: The use of 'weak' or 'strong' labels is subjective and it is unclear which parameters are being used. Moreover, 'exp reference' is not described or cited. Furthermore, this plot shows what appear to be sketched curves. The calculation of the coexistence densities to construct this phase diagram is trivial for the system studied here; the authors should provide direct estimates.

Reviewer #2 (Public review):

Summary:

The manuscript "Thermodynamic principles of enzymatic regulation in biomolecular condensates from reaction-coupled molecular modeling" reports results of a very coarse-grained molecular dynamics (MD) simulation of three types of particles that undergo phase separation and chemical reactions. The study focuses on a molecule that can exist in two states (phosphorylated vs. unphosphorylated), whereas the third species is an enzyme that catalyzes the reaction in one direction of the transition. This topic of chemically active multicomponent mixtures is timely, and its connection to biomolecular condensates is well motivated in the introduction. Using their minimal setup, the authors find that driven reactions affect the composition of the dilute and dense region, and can even suppress phase separation completely. Moreover, the reaction fluxes are heterogeneous and exhibit a pronounced peak at the interface. The authors then interpret this acceleration of reactions in light of the role of condensates as reaction centers and conclude that the effect they report is relevant in cells.

Strengths:

A strength of the manuscript is the setup of a minimal system to understand the complex roles of enzymatically controlled, active reactions in condensates. This is a subtle topic since the physics of phase separation, implying non-ideal systems, affects the reactions, which can then no longer be described in a dilute approximation. The authors tried to take special care to ensure thermodynamic consistency, which is key to describing the interplay of the two effects accurately. The authors also perform relevant numerical tests, e.g., by determining the effect of reactions on the phase diagram, and measuring densities and reaction fluxes carefully. Moreover, they attempt to interpret the obtained quantities with intuitive pictures, although this is not always convincing.

Weaknesses:

The main weakness of the work is its presentation: I could not follow the detailed setup of the model since important details (such as the concrete interaction potentials and particularly the implementation of the reactions) are not described thoroughly. In particular, the implementation of the actively driven reaction is mysterious, and a proper negative control without activity is missing. Such a control is crucial since it would allow testing whether the implementation of the code ensures local detailed balance and thus thermodynamic consistency. Furthermore, such a passive null model would surely help in establishing the effects of activity, which is currently unclear. Since I don't understand the detailed setup, I cannot judge whether the major result, namely that reactions are accelerated at interfaces, is correct. It might very well be true, but I'm unable to judge this based on the current presentation. I detail my criticism in separate points below, and I hope that addressing these points helps the authors to improve their manuscript:

(1) I find the model setup unclear, which makes it difficult for me to gauge the correctness of the results. I think the details of the model need to be explained in more detail, both in the main text and the SI. There are three different aspects that I find lacking:

1a) The setup of the interactions in the model is unclear. First, only single interaction parameters \epsilon_i are specified, but the simulation likely needs to specify pairwise interactions. Table S2 is not particularly helpful since it uses a different notation (Is this switch of notation necessary?). Second, the statement that k_BT = 0.75 is confusing since k_BT should have units of energy. Third, the authors mention "a truncated and shifted LJ potential", but it is unclear whether this is the potential they use or not. Given this lack of details, I would not be able to immediately repeat the simulation, even without reactions.

1b) In the main text (page 6), it is unclear whether an active or passive system is studied. The subsequent results suggest that the system is active (and thus has sustained energy fluxes), but this needs to be explained in detail. In any case, I would like to see an explicit activity parameter, so that a passive control can be added. For instance, I would expect that a passive system remains the same when reaction rates are changed, but the energetics are kept constant. In any case, since it is not explained how activity enters the system, the subsequent results are unclear to me.

1c) It is unclear how thermodynamic consistency (i.e., local detailed balance) is ensured. For instance, how is the formation of a scaffold-enzyme complex performed (page 6)? The SI is also light on details. For instance, it is unclear whether the transitions in Equations (1-8) refer to individual particles (in this case, how are bimolecular reactions implemented?) or refer to densities or even overall particle counts. It is also suspicious that the reactions are given for the "dilute limit", whereas the main text clearly discusses condensed regions. It is also unclear how ΔU is calculated and what it means. Generally, I would expect a detailed discussion of detailed balance conditions in the SI, if not even in the main text. Here, it might help to clearly separate thermodynamic aspects (involving detailed balance) from kinetic considerations.

(2) If the authors study an active system, reporting averaged concentrations and partition coefficients might be misleading. Generally, active systems develop gradients in the dilute and dense regions (Figure 1), so any averaged measurement (such as a density) will depend on the size of the region. It is thus necessary to clearly define the measurements in the main text (so readers know how to interpret the plots), and the discussion needs to be much more careful, particularly when comparing to phase diagrams, which typically discuss thermodynamically large systems.

(3) The strongly increased fluxes at the interface are a bit suspicious, particularly since they are hardly visible in passive systems (Figure S6). The enhancement might originate from large reaction rates, leading to a short reaction-diffusion length scale (although I would then expect balanced reactions in the phases). Alternatively, they might originate from the microscopic details, such as the cut-off length of the kinase-interaction range. In any case, it would be important to establish a negative control using a passive setup and (based on this) explain the observed flux increase clearly.

(4) I am not convinced by the statement about the bias of reactions in the dense and dilute phase, e.g., on page 12. I would find it extremely helpful to start with a passive system (without energy input), where I would expect balanced chemical potentials, so that all reactions are balanced at all points in the system. Already in this case, there might be accelerated reactions at the interface (due to kinetic details), but the two reactions need to be balanced to have overall homogeneous chemical potentials. Starting from such a base state, one could then discuss how activity biases reactions in a certain direction. While the current explanation correctly mentions that a transition can be hindered by energetics, it fails to account for the different abundances. In a passive system, these two aspects are perfectly balanced, leading to a linking of reaction rate constants and partition coefficients (e.g., see https://arxiv.org/abs/2202.13646). These aspects need to be discussed much more cleanly (and they are intimately linked to the setup of the model, which is currently unclear; see point 1).

(5) I think the title is misleading. The authors do not establish new "Thermodynamic principles". I am also not sure what they mean by "reaction-coupled molecular modeling". Finally, the 
"enzymatic regulation" is hardly discussed in the main text, which instead seems to emphasize the accelerated reactions at the interface.

Reviewer #1 (Public review):

The work shows that the ECS-induced calcium waves recapitulate several hallmarks of CSD, including hemodynamic alterations, distinct propagation patterns, and elevated Fos expression.

Update of the weakness section.

(1) I still have concerns about the use of Fos staining as the exclusive marker of neuroplasticity. Of course, Fos drives many forms of plasticity. But in addition to the role, Fos upregulation also reflects a recent history of elevated neuronal activity. This has been reported in numerous papers, including those cited in the article (e.g. Mahringer et al., 2019; Tyssowski et al., 2018). If the authors claim that their main finding is that ECS-induced CSD is necessary to drive Fos, then the relevant background should be presented in the Introduction.

(2) The authors did not sufficiently address the concern regarding the bilateral suppression of EEG following unilateral calcium waves. Unilateral CSD is known to depress EEG only in the affected (ipsilateral) cortex. I suspect that the bilateral EEG suppression can be driven by the bilateral seizure (phase III oscillations) that is always coupled with the ECS-induced calcium waves.

(3) Using the term 'phase III oscillations' instead of 'seizures' is confusing because the word "oscillations" covers a wide range of brain oscillations - from normal to pathological ones. First, the authors base the terminology change on the absence of "the ictal spikes characteristic of epileptic seizures..." during the phase. However, anesthesia can suppress ictal spiking and the phase III activity can represent an aborted seizure induced under anesthesia. Second, the authors cite the study by Brumback and Staton (1982) to justify their use of the term "phase III oscillations". However, the cited work describes the phase III as a seizure with "spike/polispike-wave activity".

(4) Cortical SD cannot invade the hippocampus in the in vivo brain, although SD can occur in the hippocampus in response to generalized seizures. Invasion of CSD suggests its non-synaptic propagation via the contiguous gray matter. The following studies showed that CSD cannot invade the hippocampus non-synaptically: Fifkova E. Spreading EEG depression in the neo-, paleo- and archicortical structures of the brain of the rat. 1964 (PMID: 14138725); Yoshida et al. Identification of the extent of cortical spreading depression propagation by Npas4 mRNA expression. 2015 (doi: 10.1016/j.neures.2015.04.003). Concerning the papers cited in the discussion ("In mice, the ECS driven CSD likely invades hippocampus" (Mitlasóczki et al., 2025)), and response (Bahari et al., 2020; Bonaccini Calia et al., 2022), hippocampal SD was triggered by focal seizures, independent of CSD, in the experiments.

Reviewer #3 (Public review):

In this revised version of the manuscript, the authors have addressed several of the Reviewer's prior questions and comments. However, the main elements of the critique remain largely intact in the absence of additional experiments.

Major:

(1) The authors and Reviewer disagree as to the extent to which the main findings replicate prior work vs. represent true novelty. In their response, the authors state, "This appears incorrect. It was known that direct cortical stimulation (as was done in the Rosenthal paper) can drive a calcium event that resembles a CSD. It was also known that CSD can drive Fos expression. What was not known is that the Fos expression driven by ECS is fully explained by the calcium event (putative CSD)." First, what appears incorrect is the author's statement that Rosenthal et al. use direct cortical stimulation. So far as the Reviewer can discern, Rosenthal et al. in fact did not use intracranial or direct cortical stimulation, as stated repeatedly in the rebuttal. Instead, Rosenthal et al. use stimulating electrodes that are attached to the skull (i.e., non-penetrating), as clearly shown in Figure 1 of that paper. Describing this as "intracranial stimulation" and equating it with direct cortical stimulation used to induce CSD in Leão (1944), is incorrect and misleading.

(2) The authors ask for guidance in improving the clarity of their messaging around this and cite the Abstract as clearly stating what they view as the novelty here. Yet, the key section of the Abstract reads: "We show that CSD drives increased expression of the immediate early gene Fos, a key marker of neuronal plasticity, and is associated with factors that predict positive ECT therapeutic outcome. Our results suggest that the therapeutic efficacy of ECT may be mediated by CSD. This challenges the seizure-centric model and implies that CSD, a currently unmonitored neurophysiological event, may serve as a more relevant biomarker for predicting and optimizing therapeutic outcomes of ECT." The Reviewer finds this quite misleading, as it suggests (at least to this Reviewer) that the authors view themselves as showing, for the first time, that ECT generates CSD and that this may be the therapeutic mechanism of ECT, while not clearly defining what is new. Instead, one could perhaps more accurately write: "Prior work has shown that ECT generates CSD and that CSD is associated with increases in the immediate early gene Fos, a key marker of neuronal plasticity. We provide data suggesting that ECT-associated CSD in fact drives this increased Fos expression. Our results imply the hypothesis that the therapeutic effect of ECT may be mediated by CSD-induced Fos expression and could serve as a biomarker of ECT efficacy."

(3) In claiming novelty, the authors further assert that Rosenthal et al. provided "no confirmation beyond the observation of the calcium event that this is indeed a CSD." This also appears to be incorrect or misleading. Rosenthal et al. show simultaneous calcium and intrinsic optical imaging of hemoglobin dynamics associated with the propagating event. Rosenthal et al. also show DC-coupled electrophysiology demonstrating the slow potential shift characteristic of CSD using auricular ECS (the very stimulation model that the authors argue distinguishes their work from Rosenthal et al.). Hence, speculation that the "cortical seizure Rosenthal and colleagues find is a methodological artifact" is unsupported and should be removed.

(4) In the rebuttal, the authors clarify the novelty of their manuscript as "that ECS drives CSD dependent immediately early gene expression (Fos)." The Reviewer agrees with this, yet as summarized in the bullet point, finds this novelty to be relatively limited and not particularly surprising, given that Fos is robustly induced in association with CSD in various contexts. This novelty could be markedly enhanced by linking increased Fos expression mechanistically to the therapeutic efficacy of ECT. Instead, any relevance of the CSD-dependent Fos induction is unclear, and statements to that effect, while interesting, are hypothetical, yet follow logically from Rosenthal et al. Any association between CSD occurrence and clinical outcome in human patients could establish predictive value but would also not prove causality, as suggested. Also unclear is how Fos might be used as a biomarker in humans, and how this might be valuable as a biomarker beyond CSD itself (which can actually be recorded), is unclear. The authors should state these limitations.

Minor:

(1) Regarding the microprism preparation, the added three-week postoperative interval is helpful toward alleviating this concern. Still the absence of spontaneous CSD does not address the fact that cortical incision and the CSD likely elicited during implantation could alter subsequent susceptibility to experimentally evoked CSD. This should simply be acknowledged as a limitation.

(2) The Reviewer recognizes that the authors have added Tables S3 and S4 detailing stimulation parameters. However, the response that properties of the traveling calcium event do not depend on stimulation charge does not resolve the concern regarding analyses in which stimulation parameters are used to predict whether CSD occurs. Manually selecting stimulation parameters rather than selecting them randomly or systematically may confound these analyses, an issue which could simply be acknowledged.

Reviewer #1 (Public review):

Summary:

The "multiple-demand" (MD) system is a well-known finding of human brain imaging and is thought to play a central role in cognitive control. To directly compare the MD system in humans and monkeys, Mione et al. used functional magnetic resonance imaging to measure whole brain activation in a multi-step saccadic maze task. In humans, the authors found a distributed pattern of brain activity close match to the canonical MD network and extending to adjacent regions of dorsal attention and other networks. While there was good correspondence between monkey and human data, differences were also notable in lateral frontal cortex, dorsal parietal cortex, and sensorimotor cortex.

Strengths:

Though previous data hint at a corresponding network in the macaque, there has been no direct comparison to human data. This study provides a direct cross-species comparison with whole-brain data of fMRI, and the findings suggest an extended and strongly interconnected brain network recruited by increased cognitive challenge.

Weaknesses:

In previous human imaging, the MD system is defined by overlapping activation for many kinds of cognitive demand. In the present work, however, the authors used just a single task. Although there is some overlap between putative monkey MD network and canonical MD network identified in human imaging, it should be cautious to link current findings to MD system based on limited task events.

Reviewer #2 (Public review):

Summary:

Mione et al. aim to resolve a long-standing question in comparative neuroscience: whether the macaque brain contains a functional analogue to the distributed human multiple-demand (MD) network. To address this, the authors employ a direct cross-species fMRI comparison using a multi-step saccadic maze task in humans and a simplified two-step version in macaques. By contrasting goal-directed navigation against a control condition that requires similar motor responses but no strategic planning, the study isolates the neural signatures of cognitive control across species.

Strengths:

The most compelling aspect of this work is its methodological alignment. Previous attempts to compare these systems often relied on comparisons of human BOLD signals and macaque single-unit recordings. By running parallel fMRI protocols, the authors establish a shared measurement basis that allows for a more direct comparison. The resulting activation maps demonstrate conserved network topology in dorsolateral and dorsomedial frontal cortex and insula.

Weaknesses:

However, there is concerning inter-individual variability in the macaque data, along with a notable design asymmetry between the human and monkey tasks. In the human experiment, 2-, 4-, and 6-step trials were mixed within the same blocks, whereas macaques performed only 2-step problems. This design difference likely places human participants in a state of sustained proactive cognitive control (Braver, 2012), as they must remain prepared for more demanding trials at any moment. This elevated baseline arousal may potentially inflate MD network activation even during the simpler 2-step trials in humans, making direct comparisons with the macaque data difficult.

The authors acknowledge this concern and note that similarities between species survive despite this procedural difference. However, their own individual-level data raise doubts about how robust these "similarities" really are. A defining feature of the MD system is consistent recruitment across individuals performing the same task. In this study, however, the two monkeys show markedly different activation maps in parietal cortex. The conjunction map (Supplementary Figure 6) does not support the claim that lateral and medial parietal regions are commonly activated across both animals at any meaningful statistical threshold, even when using a permissive threshold of |t| > 1.5, corresponding to approximately p ≈ 0.13 - 0.14 (two-tailed).

This suggests that the group-level parietal activations are largely driven by a single animal, raising questions about whether these regions can reliably be considered as part of the monkey MD network. Notably, in Premereur et al. (2018), the only other direct macaque fMRI study of a cognitively demanding task, their conjunction map between the two animals also failed to show common parietal activation during task switching. Taken together, these findings suggest that either the monkey MD network is not as similar to its human counterpart as claimed, or the monkey version of the maze task was simply not sufficiently challenging to fully engage parietal MD nodes.

Because of the design asymmetry described above, it remains difficult to determine which of these possibilities is correct (a genuine species difference versus insufficient task demands in macaques). The authors' current claims treat the group-level activations, which appear largely driven by one animal, as reliable evidence for homology, but without consistent individual-level support, such conclusions remain tentative.

In summary, the authors demonstrate functional correspondence between human and macaque cognitive control networks in dorsolateral and dorsomedial frontal regions. However, assertions that this extends to lateral and medial parietal cortex are not consistently supported at the individual level. While the overall conclusions are plausible, they would be significantly strengthened by demonstrating consistent activation across both animals in all claimed MD regions, ideally with a properly thresholded conjunction map.

Reviewer #1 (Public review):

[Editors' note: The reviewing editor has assessed the revisions. The authors have addressed the previous minor concerns of the reviewers, added more details on the generation of the brainbow constructs and have made the image stacks available on public repositories.]

Summary:

Pang et al. investigated the expression pattern of the transcription factor foxQ2II in an adult beetle brain. They find nine distinct clusters, with many neurons expressing Glut/ChaT and dopamine. Some of the dopamine neurons resemble cell types described in Drosophila. Several neurons seem to project to prominent higher brain regions such as the MB and CX, and might even connect to both.

Strengths:

The authors use state-of-the-art labeling techniques for the analysis of individual cell types, such as beetle brainbow, to investigate the until now unknown expression of the transcription factor in the adult beetle brain.

Rigorous cell reconstruction and image analysis revealed a better understanding of the anatomy of the labeled cells.

Reviewer #2 (Public review):

Summary:

The authors provide the first thorough profiling of neurons in Tribolium characterized by the expression of the transcription factor foxQ2, which will be useful for developmental neurobiology. They use state-of-the-art methods convincingly to not only identify the neurons, but also to further characterize them anatomically and neurochemically.

Strengths:

Thorough and meticulous application of state-of-the-art anatomical methods in a non-standard laboratory organism.

Joint Public Review:

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

The revised manuscript is much clearer, and the additional analyses address several of the original concerns. RAIN analyses (Rhythmicity Analysis Incorporating Nonparametric methods) now detects circadian rhythmicity in 7/11 recordings under light-dark conditions and 8/12 recordings in constant darkness, compared with 2/12 following treatment with the Orco antagonist. This supports circadian modulation of spontaneous firing and a role for Orco in its normal expression. The expanded qPCR analysis of Orco also supports the conclusion that Orco transcript abundance is not circadian, and the cAMP experiment shows that cAMP can modulate Orco-dependent activity.

The remaining issue concerns the mechanistic interpretation. The lack of rhythmic Orco transcript abundance does not distinguish an autonomous post-translational feedback-loop (PTFL) clock from a model in which the canonical transcriptional-translational (TTFL) clock acts upstream through cAMP, calcium, kinases, phosphatases, channel trafficking, or related pathways to regulate Orco.

Similarly, the new Figure 10 provides a useful representation of the authors' hypothesis, but the proposed delayed feedback and coupling mechanisms are not experimentally demonstrated.

We do not think any further experiments are necessary for the present study. Instead, we recommend that the manuscript should clearly distinguish between what the data show and what remains proposed. The data support circadian modulation of ORN firing a role for Orco in its normal expression, non-circadian Orco transcript abundance, and cAMP-sensitive modulation of Orco-dependent activity. The proposal that an Orco-centred membrane feedback loop generates the rhythm is intriguing and may remain a hypothesis generated through this study that needs formal testing in the future. This should be explicitly stated. While this has been done in the discussion section, elsewhere, including in the abstract and elsewhere, the original claim remains.

Reviewer #3 (Public review):

Combining a five-year field experiment with a global meta-analysis, Wu et al. investigate how grazing intensity influences ecosystem carbon dioxide (CO₂) fluxes in grasslands and how these effects are regulated by environmental conditions such as grazing duration, wetness index, and soil temperature and moisture responses.

The authors show that the response of net ecosystem productivity (NEP) to light grazing shifts from negative to positive along a wetness gradient, whereas heavy grazing consistently suppresses NEP across wetness conditions. Importantly, this pattern is supported by both the field experiment and the meta-analysis, suggesting that may help maintain moderate levels of grazing can potentially enhance both plant productivity and carbon sequestration under favorable moisture conditions.

The integration of experimental data with a global synthesis is a particular strength of the study, allowing the authors to evaluate grazing impacts across both temporal variability (precipitation fluctuations in the field experiment) and spatial variability (wetness gradients across global grasslands). Overall, the conclusions are well supported by the data.

Overall, the principal conclusions are generally supported by the reported results, and the study provides useful evidence that the effects of grazing on grassland carbon cycling depend on both grazing intensity and environmental context. The comparison between field and synthesis results is potentially valuable for understanding why grazing effects vary among grassland systems. However, some aspects of the meta-analysis remain insufficiently documented. In particular, the study-selection numbers presented in the new PRISMA diagram require clarification, and the manuscript does not clearly explain how individual response ratios were weighted when estimating the pooled effect sizes. Resolving these reporting and methodological issues would improve the reproducibility and interpretation of the synthesis.

Reviewer #1 (Public review):

Summary:

Choucri and Treiber have reassessed their previous study on TE-gene chimeric transcripts in neural genes in response to Azad et al (2024). Azad and colleagues argued that contrary to Choucri and Treiber's findings, chimeric TE-mRNAs are relatively infrequent, and they cautioned that further optimization of bioinformatics pipelines is needed to accurately detect TE insertions from RNA-seq. In this short response, Choucri and Treiber clearly show that differences in the tools used between their study and that of Azad et al. likely explain the contrasting results, along with RT-PCR failure to design primers that match the chimeric transcript and the use of different Drosophila lines. The authors emphasize the need for uniform, standardized criteria in such analysis, which would ultimately strengthen and advance the field.

Strengths:

The addition of a ratio to compute the number of splice reads specific to the chimeric transcript and to compare to the exon-exon splice reads is really interesting because it opens the door to finally quantify the contribution of chimeric TEs to the overall gene expression, although this is not the scope of the present article. The clear dissection of chimeric transcripts, along with the results from Azad et al, allows us to understand the differences between the two studies confidently. The methods are clear and thorough. The discussion on Drosophila lines is indeed essential, given that the lines and even individuals have high TE polymorphism.

The biological function, if any, of such chimeric transcripts remains to be determined by further analysis, including chimeric transcripts with low to high overall contribution to gene expression (Figure 1B).

Reviewer #3 (Public review):

Summary:

This manuscript by Choucri and Treiber responds to a recent paper by Azad et al., which responds to a paper by Treiber and Wadell (Genome Research, 2020). The controversy relates to the detection of transcripts with transposable elements (TEs) spliced into them in the Drosophila brain.

Strengths:

The authors now argue convincingly that these transcripts exist using an improved, updated version of their pipeline. They also validate some of their findings using RT-PCR and explain why Azad et al. failed to detect these transcripts due to methodological errors. Overall, I am convinced that these transcripts exist and that the TE-derived transcripts described by Choucri and Treiber are real.

Weaknesses:

The authors should mention that combining PCR-amplified cDNA generation with short-read sequencing is suboptimal for detecting TE-fusion transcripts. Recently, direct long-read ONT RNA sequencing, which does not require amplification and spans the entire transcript, has been used to detect similar transcripts in human stem cells and the human brain (PMID: 40848716 & Garza et al, BioRxiv) . Had the authors used this technology to validate their findings, there would be no question about these transcripts. If not doing such experiments, then they should at least discuss the possibility and the advantage of the approach.

Reviewer #1 (Public review):

Summary:

This paper by Boni and colleagues presents the engineering of a multi-step differentiation program in Escherichia coli based on synthetic gene circuits. The motivation behind the study was to engineer a system capable of undergoing differentiation in a step-wise manner without the presence of external spatial cues and without inducers added during the differentiation process. To achieve this, the authors created several synthetic gene circuits, one being a toggle switch, and the others being quorum-sensing-mediated gene expression modules. The outputs of the differentiation process are fluorescent proteins, which allowed the authors to quantify the behavior of the system using fluorescence intensity measurements. The authors additionally built a multi-component mathematical model which is able to reproduce the experimental data and to make interesting predictions (which require future validation).<br /> The data presented are convincing and support the claims, the work is well executed.

Strengths:

(1) The differentiation process proceeds autonomously after the initial step in liquid culture in the presence of external inducers.

(2) It is indeed a step-wise process.

(3) The mathematical model predicts the outcome (% of green, blue and red FP-expressing cells in the population) when changing the initial ratio of green:blue FP-expressing cells.

Comments on revised version:

The authors' replies to my comments were very satisfactory. I think the paper has been strengthened.

Reviewer #2 (Public review):

The revised manuscript by Boni et al. is substantially improved, and in my view the authors have responded constructively to the concerns raised during the first review. Most importantly, they now explicitly distinguish the bistable green/blue states generated by the toggle switch from the reversible red and yellow quorum-sensing outputs and acknowledge that the latter do not constitute irreversible differentiated states. This clarification improves the conceptual accuracy of the work.

The other revisions are also well justified. The authors clarify that Fig. 2d is derived quantitatively from flow-cytometry data and explain how the cross-sections in Fig. 2e were obtained; they introduce the nullcline interpretation of the toggle-switch landscape and distinguish stochastic single-cell fate from predictable population-level proportions. They also provide more information on pLux engineering, report the functional forms and parameters of fitted curves, quantify the different HSL induction ranges, explain the heuristic treatment of entry into stationary phase, and clarify image selection and sender-receiver distance calculations.

The principal strength remains the systematic engineering of a sequential multi-circuit programme in a single bacterial genetic circuitry (spread over two plasmids). The work combines bistable symmetry breaking, LuxI/LuxR-mediated communication and an orthogonal CinI/CinR layer to generate spatially organised colony-level behaviours. The DBTL engineering cycle is also convincing: substantial cross-talk in the initially tested Lux/Las quorum-sensing combination was experimentally identified and addressed by switching to the more orthogonal Lux/Cin architecture, while subsequent promoter leakiness was identified and mitigated by replacing pLux with pLuxLac.

Overall, I consider the revisions sufficient to address all the important concerns.

Reviewer #3 (Public review):

Summary:

This manuscript presents an engineered 3-step circuit in E. coli that combines toggle-switch-based symmetry breaking with quorum-sensing interactions to generate colony-scale spatial patterns. The work is interesting as a synthetic circuit integration study and as a demonstration of self-organized patterning across physically separated colonies. The authors provided a compelling demonstration of the characterization/tuning of parts to guide the overall system engineering. A notable strength is the demonstration that a single circuit can generate a range of self-organized spatial patterns across separate colonies.

Comments on revised version:

The authors have satisfactorily addressed my previously raised issues.

Reviewer #1 (Public review):

Summary:

This manuscript by Joshi and colleagues demonstrates that the precise theta-phase timing of spikes is causal for CA1 hippocampal theta sequences during locomotion on a linear track and is necessary for learning the cognitively demanding outbound component of a hippocampus-dependent alternation task (W-maze), independently of replay during immobility. To reach these conclusions, the authors developed a theta-phase-specific, closed-loop manipulation that used optogenetic activation of medial septal parvalbumin (PV) interneurons at the ascending phase of theta during locomotion. This protocol preserved immobility periods, allowing a clean and elegant dissociation from SWR-associated replay.

The manuscript is well written and was a pleasure to read. The work described if of high quality and introduces several notable advances to the field:

a) It extends prior studies that manipulated theta oscillations by examining precise temporal structure (specifically theta sequences) rather than only LFP features.

b) The closed-loop manipulation enabled dissociation between deficits in theta sequences during a behavioural task and SWR-associated replay activity.

c) As controls, the authors included rats with suboptimal viral transduction or optic-fibre placement, and, within subjects, both stimulation-on (stim-on) and stimulation-off (stim-off) trials. Notably, sequence disruption persisted into stim-off periods within the same session.

Overall, this is a strong manuscript that will provide valuable insights to the field.

After revision, the manuscript has been substantially strengthened. The authors did incorporate the vast majority of the reviewer's comments and have expanded the discussion of prior medial septal manipulations, clarified the rationale for their theta-sequence analyses, added analyses of SWR and replay in the rest/sleep box as well as provided additional methodological and histological validation.

The new rest-box analysis is a great addition and directly addresses my request to distinguish aSWRs from events during longer off-track rest periods (rSWR). The data support the narrower conclusion that no large group difference was detected in rest-box ripple rate or duration.

The new observation (in response to reviewer #2, point3.2) that on the W-track theta power does not fully recover during stimulation-off periods does change the interpretation of the results. It means that these epochs are then not a physiologically recovered control condition. Therefore, the persistent disruption of theta sequences during the middle block cannot, alone, demonstrate that disrupting sequences during the earliest experience produced a lasting plasticity-related effect. It could also reflect a lingering network effect of the stimulation that persists after laser delivery has stopped. In my opinion the discussion should present at least these two alternatives: the disruption of early experience-dependent plasticity, as well as the incomplete physiological recovery from the preceding stimulation. The linear-track recovery data is helpful, but it does not guarantee the same mechanisms/effects will be present on the novel Wmaze (versus the familiar linear track).

Reviewer #2 (Public review):

Summary:

The authors of this study developed a closed-loop optogenetic stimulation system with high temporal precision in rats to examine the effect of medial septum (MS) stimulation on the disruption of hippocampal activity at both behavioral and compressed time scales. They found that this manipulation preserved hippocampus single-cell-level spatial coding but affected theta sequences and performance during a spatial alternation task. The performance deficits were observed during the more cognitively demanding component of the task and even persisted after the stimulation was turned off. However, the effects of this disruption were confined to locomotor periods and did not impact waking rest replay, even during the early phase of stimulation-on. Their conclusion is consistent with previous findings from the Pastalkova lab, where MS disruption (using different methods) affected theta sequences and task performance but spared replay (Wang et al., 2015; Wang et al., 2016). However, it differs from a recent study in which optogenetic disruption of EC inputs during running affected both theta sequences and replay (Liu et al., 2023).

Strengths:

The experiments were well designed and controlled, and the results were generally well presented.

Comments on revised version.

The authors of this study addressed all my concerns, some of them successfully. The stimulation disrupted theta oscillations, making quantification of theta sequences problematic. Within the constraints of their experimental design, the authors tried their best to address my concerns. Therefore, I am satisfied with the current version and express no further comments.

Reviewer #1 (Public review):

Summary:

This manuscript investigates how the Saccharomyces cerevisiae telomere-binding protein Cdc13 assembles on a 12-nucleotide single-stranded telomeric DNA substrate. Using complementary smFRET and CoSMoS measurements, together with dimerization- and DNA-binding-defective mutants, mass photometry, photobleaching analysis, and kinetic modeling, the authors assign state II to a DNA-bound Cdc13 monomer and state III to a stable complex containing two Cdc13 molecules. They propose that the stable DNA-bound dimer forms predominantly through sequential recruitment of two monomers, while direct binding of a preformed dimer represents a less frequent pathway. This work addresses an important mechanistic question in telomere biology because the pathway of Cdc13 assembly may influence telomere recognition, end protection, and recruitment of telomere-maintenance factors.

Strengths:

Overall, the manuscript is well written, and the combination of two complementary single-molecule approaches is a strength. The central model is interesting and potentially important.

Weaknesses:

Several issues require clarification or additional analysis.

Major comments:

(1) The mass photometry results are central to the mechanistic model and should be presented more prominently.

The conclusion that Cdc13 binds DNA predominantly through sequential monomer recruitment depends strongly on the oligomeric state of Cdc13 at the concentrations used in the single-molecule experiments. The mass photometry results currently provide the principal direct evidence that Cdc13 is predominantly monomeric at 5 nM but exists as a mixture of monomers and dimers at 20 nM. These results should therefore be included in a main figure rather than only in the Supplementary Information. The authors should also provide a complete description of the mass photometry in the Methods section.

Related to lines 191-192, the authors should discuss the estimated cellular or nuclear concentration and abundance of Cdc13 and compare these values with the experimental concentrations at which states II and III are populated. Because the relevant quantity may be the effective local concentration at a telomere rather than the average nuclear concentration, this distinction should also be acknowledged. Such a discussion is needed to establish under what physiological conditions sequential monomer loading versus binding of a preassembled dimer would be expected.

(2) 75% labeling efficiency must be clearly defined and incorporated into both the stoichiometric and kinetic analyses.

In line 251, the authors state that the labeling efficiency of DY-649P1-Cdc13 is 75%, but it is not clear how this value was measured. The authors should state whether 75% refers to the efficiency of the sortase reaction, the fraction of labeled molecules in the final purified preparation, or a value inferred from the plateau in Figure 3B. If it was inferred from the binding plateau, the plateau below 100% could also arise from inactive or inaccessible DNA molecules, incomplete colocalization detection, inactive protein, or an effect of the fluorophore on binding. An independent measurement, such as absorbance-based determination of the dye-to-protein ratio, quantitative gel analysis, or intact-mass analysis, would be preferable.

Incomplete labeling has direct consequences for the interpretation of Figure 3. With a labeling probability of 0.75, a true Cdc13 dimer would contain zero, one, or two fluorophores. Thus, even among detectable dimers, 40% would appear as one-step photobleaching events. A one-step event therefore cannot automatically be equated with a monomer without correcting for labeling efficiency. The authors should quantitatively account for incomplete labeling when inferring the relative monomer and dimer populations from the photobleaching data.

The same issue is even more important for the CoSMoS kinetic model. The authors should incorporate labeling efficiency into the observation model, or at minimum perform simulations or a sensitivity analysis demonstrating that the inferred transition rates and state assignments are robust to 75% labeling.

(3) Apparent state I→III transitions do not by themselves demonstrate direct binding of a preformed Cdc13 dimer.

At lines 326-330, the authors interpret state I→III transitions as direct binding of a solution dimer and conclude that sequential binding is approximately eightfold faster than direct dimer binding. This interpretation is not yet sufficiently established. An observed I→III transition demonstrates only that no state II intermediate was resolved; it does not distinguish true binding of a preformed dimer from sequential binding in which the state II lifetime is shorter than the temporal resolution of the experiment.

This concern is particularly important because the CoSMoS experiments were conducted at only 0.3-1.25 nM Cdc13, whereas mass photometry indicates that Cdc13 is predominantly monomeric even at 5 nM. In addition, the smFRET signals were averaged over a sliding window of ten 50-ms frames, which could obscure short-lived intermediate states.

The authors should show representative raw traces containing apparent I→III transitions in a supplementary figure and quantify the shortest state II dwell time that could be detected under the acquisition, smoothing, and HMM procedures used.

(4) The interpretation of the WT-Cdc13/Cdc13^R635C mixture requires further clarification.

For Figures 2G-H and lines 209-218, the reduced state III population in the mixture of 2.5 nM WT Cdc13 and 2.5 nM Cdc1^R635C is interpreted as evidence for a solution monomer-dimer equilibrium and formation of a nonfunctional WT-mutant heterodimer. However, at least two nonexclusive explanations should be considered:

a) Formation of WT-mutant heterodimers in solution could reduce the concentration of free WT monomers and WT homodimers available to form state III.<br /> b) A WT-mutant heterodimer, or recruitment of Cdc13^R635C to a DNA-bound WT molecule through protein-protein interactions, could produce a DNA-bound complex that cannot adopt the state III conformation because only one subunit has an intact DNA-binding interface.

The authors should discuss these possibilities explicitly and clarify expected FRET states.

For direct visual comparison, Figure 2G should include the FRET histograms for 2.5 nM WT Cdc13 alone and 5 nM WT Cdc13 alone, in addition to the WT-mutant mixture. The concentrations of both the initially loaded WT Cdc13 and the WT or mutant protein added during the chase experiment in Figure 2I should also be stated in the main text and figure legend.

(5) The physical basis of the different FRET values for states II and III should be explained earlier and more carefully.

The assignment of state II and state III to one and two bound Cdc13 molecules is supported by the combined smFRET and CoSMoS results. However, the manuscript should explain earlier why the addition of a second Cdc13 molecule is expected to produce a further decrease in FRET. Because the fluorophores are attached to the DNA, the different FRET values imply a change in the distance, orientation, or local photophysical environment of the DNA-linked dyes when the second Cdc13 binds. CoSMoS establishes a change in protein stoichiometry, but it does not by itself establish that the DNA has undergone a particular conformational change.

The discussion at lines 404-423 suggests that the second Cdc13 induces a rearrangement of the first Cdc13-DNA complex. This is a reasonable hypothesis, but it should be presented as an inference rather than as a demonstrated DNA conformational transition. References 44-46 describe different RPA binding modes and rearrangements of protein-DNA contacts; they do not directly demonstrate the specific DNA conformational change proposed here. The authors should either provide more direct support or revise the discussion accordingly. The distance estimates should also be described cautiously because they assume that dye orientation and photophysical properties are unchanged between states.

The rationale for the internally positioned Cy3 constructs in lines 147-149 should also be explained more clearly. Why does it demonstrate that Cdc13 cannot bind duplex DNA?

Reviewer #2 (Public review):

Summary:

The manuscript presents an interesting and potentially important single-molecule study of Cdc13 assembly on telomeric ssDNA. The experimental observations are intriguing, particularly the identification of distinct FRET states associated with different Cdc13 occupancies. However, I have substantial concerns about whether the current data support the central mechanistic conclusion as strongly as the authors claim. In particular, the manuscript does not yet clearly distinguish between the observation that two Cdc13 molecules are associated with DNA and the stronger mechanistic claim that Cdc13 loads sequentially as monomers and subsequently dimerizes on DNA.

Major concerns

(1) The central mechanistic conclusion is stronger than the evidence

The manuscript's principal model is that Cdc13 proceeds through the pathway monomer → DNA-bound monomer → recruitment of a second monomer → stable DNA-bound dimer. However, the experiments establish this sequence only indirectly.

The authors show that FRET state II is associated with one Cdc13 molecule. FRET state III is associated with two Cdc13 molecules. Cdc13-DM produces state II but not state III. WT Cdc13 can undergo I→II→III transitions. Direct I→III transitions also occur.

These observations are consistent with sequential binding, but they do not uniquely demonstrate that the second Cdc13 molecule first binds as a monomer and subsequently undergoes dimerization on DNA. In particular, the direct I→III events indicate that a preassembled dimer or another cooperative pathway can also contribute.

I therefore recommend substantially tempering statements such as "Cdc13 initially loads onto telomeres as a monomer." A more defensible formulation would be: "The data support a kinetically favored sequential pathway involving an initial Cdc13 binding event followed by recruitment of a second Cdc13 molecule." The authors could still present sequential loading as the preferred model, but the language should clearly distinguish a kinetically supported pathway from a uniquely established molecular mechanism.

(2) The assignment of FRET states II and III to exactly one and two Cdc13 molecules requires stronger validation

The interpretation of states II and III as one- and two-Cdc13 states is central to the entire mechanistic model. Because labeling efficiency, incomplete labeling, photophysics, and heterogeneous molecular populations can all affect the observed distributions, the authors should provide a quantitative probabilistic model. Specifically, the authors should calculate the expected distribution of one- and two-labeled-Cdc13 species given the experimentally determined labeling efficiency and compare these expectations with the observed FRET-state populations. This analysis would provide an important independent validation of the proposed stoichiometric assignments.

(3) The TG12 substrate raises an important stoichiometric and conformational question

The manuscript argues that a single Cdc13 molecule binds approximately 11 nt, while two Cdc13 molecules can bind a 12-nt ssDNA substrate. This raises an immediate mechanistic question: if one Cdc13 occupies approximately 11 nt, how can two Cdc13 molecules simultaneously associate with only 12 nt of ssDNA? This issue should be addressed experimentally rather than only structurally or schematically. A particularly informative experiment would be to systematically vary ssDNA length. The probability and kinetics of state III formation could then be quantified as a function of substrate length. Such an experiment would determine whether formation of the two-Cdc13 state genuinely requires additional DNA and whether the two proteins occupy overlapping or distinct regions of the substrate.

(4) The "salt-resistant" interpretation is overstated

The manuscript repeatedly describes state III as "salt-resistant" and uses this observation to support the existence of a highly stable physiological complex. However, the reported experiment examines only a relatively modest range of NaCl concentrations (50, 75, and 100 mM).

I recommend either expanding the salt-dependence analysis substantially or using more quantitative language. For example, the authors could report the fraction and lifetime of state III as a function of salt concentration and define explicitly what they mean by "salt-resistant." The current data support persistence under the tested conditions, but they do not by themselves establish exceptional physiological stability.

(5) The mass-photometry experiment does not establish the physiological solution equilibrium

The mass-photometry data are useful for demonstrating that Cdc13 can exist in monomeric and dimeric forms, but the current experiment does not establish the equilibrium between these species under physiologically relevant conditions.

A concentration series would be valuable. The observed monomer/dimer populations should be fit to an explicit equilibrium model to obtain an apparent dimerization constant and assess how strongly the equilibrium depends on Cdc13 concentration. This would also help connect the solution behavior to the single-molecule observations and determine whether the observed DNA-bound dimer could plausibly arise from a pre-existing solution dimer.

(6) The WT + R635C mixing experiment is overinterpreted

The interpretation of the WT + R635C experiment is currently complicated and somewhat speculative. The experiment is potentially informative, but the conclusions appear stronger than what can be directly inferred from the data. The authors should clearly distinguish between the observations directly supported by the mixing experiment and the mechanistic interpretation proposed from them. In particular, the experiment does not necessarily establish the precise sequence of DNA binding and dimerization events.

(7) The requirement for DNA-binding activity in both Cdc13 molecules is not fully established

The manuscript concludes that both Cdc13 molecules must possess DNA-binding activity. However, the R635C experiment does not clearly distinguish between:<br /> two independently DNA-bound Cdc13 molecules; and one Cdc13 molecule directly bound to DNA plus a second molecule whose DNA-binding surface is required for allosteric stabilization of the dimer.

This distinction is mechanistically important. Additional experiments using DNA-binding-defective mutants in defined heterodimeric configurations would help determine whether both molecules directly contact DNA or whether DNA binding by one molecule promotes recruitment/stabilization of the second through protein-protein interactions.

(8) Stronger controls are needed for FRET-state assignment

The FRET states are treated as discrete molecular states, but alternative explanations for heterogeneous FRET populations should be considered more explicitly.

Important controls would include: concentration-dependent FRET measurements in the absence of DNA binding; fluorescence controls to determine whether the observed states could arise from dye-protein interactions; Cdc13 mutants with altered DNA-binding specificity; alternative dye positions; demonstration that the major FRET states are reproduced with independent labeling configurations. The duplex-positioned Cy3 controls, which show little FRET change, are useful. However, they do not completely exclude the possibility that protein-induced changes in DNA conformation contribute to the observed FRET states. Independent labeling geometries would substantially strengthen the assignment.

(9) The physiological relevance of the 12-nt substrate requires better justification

The authors use TG12 as their primary substrate and state that telomeres contain approximately 12-14 nt of ssDNA during most of the cell cycle. This rationale requires greater biological context. Telomere length and the extent of the exposed G-rich strand are dynamic and heterogeneous, and Cdc13 has established functions throughout telomere replication. The authors should explain more carefully why TG12 is biologically representative and how the proposed mechanism is expected to behave on substantially longer telomeric substrates. The TG25 experiment is useful, but at present it functions primarily as a stoichiometric observation. A systematic substrate-length analysis, as suggested above, would turn this observation into a mechanistic test.

(10) The relationship to existing structural studies requires deeper discussion

The manuscript presents sequential loading as a novel mechanism, but existing structural and biochemical studies of Cdc13 dimerization and Cdc13-DNA architecture are essential for interpreting these observations. The authors should explicitly reconcile their proposed model with the existing structural literature. In particular, they should address:

Does the known Cdc13 dimerization interface permit simultaneous DNA binding by both subunits?

Is the dimerization interface compatible with the proposed DNA-bound state II?

Could DNA binding alter the dimerization interface?

Are the two Cdc13 molecules predicted to bind overlapping or distinct portions of the telomeric sequence?

Can the structural models accommodate the apparent stoichiometry on a TG12 substrate?

Without this reconciliation, the proposed sequential-loading mechanism remains somewhat disconnected from the established structural framework.

Other important issues:

(11) The Kd comparisons are confusing

The manuscript should include a table summarizing the different Kd values and explicitly explaining why they differ. In particular, describing 3.7 nM as the Kd for the first monomeric binding step while reporting an apparent Kd of 1.2 nM requires careful kinetic and statistical justification. The authors should distinguish clearly among microscopic Kd values, apparent Kd values, and parameters inferred from kinetic models.

(12) The direct-dimer pathway deserves greater attention

The occurrence of direct I→III transitions is mechanistically important and should not be treated primarily as an exception to the sequential pathway. A more balanced conclusion would be:

"Both pathways contribute to formation of the final Cdc13-DNA complex, with the sequential pathway being kinetically favored under the experimental conditions." This interpretation appears better aligned with the data and would still constitute a strong mechanistic conclusion.

(13) The "kinetic proofreading" interpretation is currently speculative

The Discussion proposes that the first Cdc13 monomer provides a kinetic proofreading step. This is an interesting hypothesis, but it is not directly demonstrated by the current experiments.

I recommend changing this to language such as "a kinetic proofreading-like mechanism may be possible" unless the authors can provide direct evidence that the first binding event selectively promotes productive complex formation or rejects nonproductive substrates.

(14) Biological-function claims should be clearly separated from the in vitro findings

The manuscript frequently connects the stable state III complex with telomere protection, telomere length regulation, CST formation, Est1 recruitment, Pol α recruitment, and prevention of DNA degradation. None of these functions are directly tested in the present study.

The experiments establish a biochemical/single-molecule mechanism in vitro. They do not establish that state III is the functional protective species in vivo.

This distinction should therefore be maintained throughout the Abstract, Discussion, Key Points, and concluding statements. The authors can appropriately discuss these possibilities as<br /> implications or hypotheses, but should avoid presenting them as demonstrated functions of state III.

Reviewer #1 (Public review):

Excitation/inhibition (E/I) balance between excitatory (glutamate) and inhibitory (GABA) neurotransmission is being increasingly studied using magnetic resonance spectroscopy (MRS), for example in autism spectrum disorder, schizophrenia and attention deficit/hyperactivity disorder. These are typically measured using standard single-voxel MRS methods (eg PRESS, sLASER) to measure glutamate/glutamine or "Glx" and spectral editing methods (eg MEGAPRESS, MEGA-sLASER) techniques to measure GABA. Such methods only give a measure of the total MR-visible metabolite concentration in the voxel. That is, they don't distinguish between glutamate/GABA involved in neurotransmission or in other metabolic processes.

Cherix et al present a method for measuring glucose metabolism, with the potential to be used on a standard clinical MRI scanner. This proof-of-concept study focused on measuring proton signals from glucose metabolites, including lactate, glutamate, GABA & Glx. The method works by administering 13C universally labelled glucose (where all six carbon atoms are substituted with 13C). When the glucose is metabolised, 13C label is incorporated into specific positions within its metabolites. Protons attached to 13C don't produce a signal in 1H-MRS in a subsequent MEGA-sLASER scan, leading to a drop in the signal as the labelled metabolite concentration builds up. At the same time, "satellite resonances" appear for protons coupled to 13C, which increase as the labelled metabolite concentration builds up. Metabolite concentrations were inferred using a simple dynamic model.

The main strength of the method is that it enables dynamic metabolic information that would typically only be available with multi-nuclear MRS capability (13C or 2H) to be achievable using standard preclinical or high field (>= 7T) human MRI systems, with widely available spectral-editing acquisitions.

The results in the mouse spectra seem very convincing for lactate and GABA/Glx. For the human scans, changes in lactate weren't detectable, which is not surprising given how little lactate appears in the normal brain. In the discussion, the authors argue the method can potentially be used in a standard, 3T clinical scanner. It may be too soon to conclude that, as it's not yet clear there would be sufficient SNR in spectra at that field strength. Additionally, the heteronuclear coupling constants are quite high. The authors recognise that this may complicate detection of satellite resonances due to signal dephasing. Another potential complication at 3T (or 2.9T) is the potential for the satellite resonances to come close to the GABA peak at 3 ppm. More accurate measurements of coupling constants will allow that to be determined. Another potential limitation of the method is macromolecule contamination of the 3 ppm GABA peak. That may be overcome by using macromolecule-nulled MEGA-editing, though frequency navigators may be necessary to overcome the increased sensitivity to frequency drift.

The authors achieved their aims of showing that imaging glucose metabolites was possible using standard proton-only MRI systems, without the need for additional multinuclear coils, transmitters and receivers. The evidence if very compelling for the mouse scans but only incomplete for the human scans.

The ability to quantify metabolites involved in E/I balance has the potential to revolutionise studies into disorders where changes in E/I balance are implicated. This is especially the case for preclinical models. Such studies may be less feasible in clinical studies due to the high cost of universally 13C-labelled glucose, but this proof-of-concept is a promising start.

Reviewer #2 (Public review):

Summary:

The main aim of the presented manuscript was to test and validate proton observed proton edited 13C MRS and track the 13C label from uniformly labeled U-13C-glucose into glutamine, glutamate, GABA and lactate in rodent and human brain in vivo.

Strengths:

In contrast to already established methods of 13C and 2H MRSI this method applies only proton RF and thus can potentially be implemented on a standard clinical scanner.

Weaknesses:

The validation of the method in a human setting is rudimentary. First, even at ultra-high field strength of 7T, the authors did not reach sufficient SNR to detect and quantify GABA with good CV, and further, the experiment needs optimisation to reach metabolic and fractional enrichment steady state and/or for additional conditions to show the possibility of lactate detection.

Reviewer #3 (Public review):

Summary:

In their paper, the authors propose using dynamic MEGA-sLASER acquisitions to track the incorporation of ¹³C from uniformly ¹³C-labeled glucose into glutamate(+glutamine) and GABA pools. This approach enables the direct and simultaneous investigation of excitatory and inhibitory neurotransmission and metabolism without requiring a ¹³C radiofrequency coil. While the authors' goals and efforts are commendable, the work has several significant limitations.

Strengths:

Use of excellent hardware (¹H cryoprobe, ultra-high-field MRI scanners); Ambitious objectives.

Weaknesses:

MRS data analysis requires improvement; Small cohort sizes; No demonstration that the proposed acquisition scheme is superior in terms of robustness, accuracy, or performance.

Reviewer #1 (Public review):

Summary:

Remapping is clearly degraded in amyloid models, but people and animals with a lot of pathology often hold onto more function than their spatial maps would predict. The authors' idea is that CA1 carries two things at once: an explicit code where rate maps onto position, and an implicit one in the temporal relationships between cells, and that AD hits the first much harder. They recorded CA1 with tetrodes in App(NL-G-F) and WT rats running an A-B-B-A sequence of open field sessions, repeated daily for six days, with rest in between. They then compared rate map measures against a cofiring measure (pairwise Kendall's tau) and looked at SWR reactivation during rest.

Strengths:

(1) The design is right for the question. Alternating back to the familiar arena separates "can the network register a new context" from "can it get back to the old one," and the finding that App rats look OK on the first A to B transition but fall apart on the return is the most striking thing here. The confused cell result, 24% vs 4.5%, is easy to read and hard to dismiss.

(2) Six consecutive days is also worth something. Most work on this is cross-sectional, and looking at how the coding changes with accumulated experience is the right way to ask about plasticity.

(3) The PIR analysis in Figure 5 is the bit I liked best. Subtracting each cell's position-predicted rate before computing tau is a reasonable check that the cofiring effects aren't place fields in disguise, and it's more than most papers making this argument do. The theta index control is a good instinct too, though see below on how it's analysed.

Weaknesses:

(1) No behaviour. This is the main problem and everything else is secondary. The title, abstract, intro and discussion all turn on preserved learning and memory, and the rats were never tested on anything. They foraged for popcorn in an open field. No discrimination measure, no novelty preference, no probe, nothing. So "learning" ends up being defined as "decoder accuracy went up across days," which makes the central claim circular. Either add a behavioural readout in these animals or take the learning language out of the title and abstract and say what was actually measured, which is experience-dependent change in neural coding.

(2) Four animals per group is fine for this kind of work, but the statistics don't respect it. Degrees of freedom in the thousands and tens of thousands (t(8616), t(36293), F(1,2674)) treat cells and cell pairs as independent, which they aren't. The mixed models in Figure 1 are the right approach, and I couldn't see why they were dropped everywhere else. The theta result is the clearest casualty: a null across 36,293 cell pairs from four rats isn't evidence that theta coordination is preserved; it's an untested question with n=4.

(3) Also, the reported df do not always match the stated n. The Methods say 4 per genotype, but several animal-level tests give t(4), which implies 3. Figure 4C gives t(32), and Figure 5C gives t(31) for what look like per-day measures. I couldn't work out what the sampling unit was in each case.

(3) Some statistics can't be right. I noticed three, without looking hard. For example. Figure 1C, rate overlap: t(471) = 2.3 with p = 2.0e-7. Fig 1G: t(163) = 5.3 with p = 0.48. Fig 3F: F(1,483) = 36.5 with partial eta squared = 0.7, when the almost identical test in the previous sentence gives 0.07. These are likely all typos, but there are enough that the whole set needs going through.

(4) The dissociation isn't tested with matched methods. Explicit coding gets rate map correlations, PVC, rate overlap, and field size. Implicit coding gets an SVM across six days. The claim is that one improves with experience and the other doesn't, but they're never put through the same analysis. The authors should run the identical decoder on rate vectors and on tau vectors, same cross-validation, day by day, and show the slopes diverging. That would be a real dissociation. Figure 1G does run a rate decoder but only pooled, not across days. As it stands, the difference in learning slopes could partly be the two analyses having different sensitivity.

(5) The PIR residual may not be as clean as it looks. PIR is observed rate minus rate predicted by the cell's own spatial map. If the spatial map is a worse model of firing in App rats, which is the paper's own claim, then less gets subtracted and more is left in the residual. So a group difference in residual tau structure could be partly downstream of the group difference in place coding quality rather than something independent. This is worth some kind of check, e.g. matching cells on spatial information, or at least reporting how much variance the spatial model explains in each group.

(6) Reactivation consistency. This carries a lot of the interpretation, and it's the thinnest evidence in the paper. r = 0.2, p = 0.04 in App against r = -0.2, p = 0.06 in WT. That's a difference in significance, not a tested difference between groups, and with both p-values sitting on either side of 0.05, I wouldn't build a mechanism on it. Needs a group x day interaction. Separately, mean pairwise correlation across SWR population vectors depends on how many cells are active, how many events there are (panels show 189 to 491) and how sparse the firing is. SWR rate, duration, participating cells and firing rates would let the reader judge whether "more consistent reactivation" means what's claimed.

(7) The hyperexcitability to excessive replay to Hebbian consolidation story on pp 21 to 22 runs about a page on the back of one marginal correlation. This section should be cut down and flagged as speculation.

(8) Missing controls. Things I expected and didn't find: histology confirming tetrode placement in CA1, any pathology verification in this cohort rather than a citation to Pang 2022, and A1-A2 spatial correlation shown next to B2-A2. That last one matters. If the App representation of A just drifts across the day, that's a different story from a specific failure to reinstate A, and the confused cell analysis as built can't tell them apart. Also, with the threshold set at the 95th percentile of the A1B1 baseline, the WT value of 4.5% is basically the chance floor by construction, so the number that carries information is the App one.

(9) The issue of males only should be mentioned.

Reviewer #2 (Public review):

This study by Wang et al. longitudinally tracks hippocampal CA1 population dynamics in Alzheimer model rats during repeated exposure to different environments. The authors dissociate two levels of neural coding. "Explicit" spatial coding, assessed by rate maps and population vector correlations, is severely impaired in AD rats and does not improve with experience. In contrast, "implicit" temporal cofiring structure, quantified by pairwise Kendall's tau and population cofiring correlations, becomes progressively more context-specific over days, mirroring behavioral learning. This preserved temporal coding is not merely a byproduct of spatial overlap, as position-independent rate analysis confirms that learning-dependent discrimination arises from intrinsic temporal dynamics rather than from residual spatial tuning. Moreover, offline sharp-wave ripple reactivation shows increasing consistency across days specifically in AD rats. These findings reveal a dissociation in the AD hippocampus and propose that temporally structured population dynamics, rather than spatially selective firing, may support residual cognitive function.

Overall, the findings are novel and thought-provoking; the analyses are comprehensive and well-controlled, and the proposed re-registration framework offers a compelling new lens for understanding cognitive resilience in Alzheimer's disease, with clear potential to guide future neuromodulation interventions.

I have only a few minor comments.

(1) Justification of terminology ("explicit" vs. "implicit").

The manuscript should clearly define the two terms early in the Introduction, ideally in a dedicated paragraph. In my opinion, the current use of "explicit" and "implicit" is not intuitive and may even be misleading.

(2) Does the dissociation reflect differential impairment between rest and running states in AD?

The authors could elaborate on this.

(3) Effect size in Figure 1D - the difference does not appear very large.

The statistical significance in Figure 1D is accompanied by relatively modest effect sizes. The authors may tone down the claim about "failure to distinguish" in the manuscript ("failed to distinguish different contexts during the second transition" on Page 8).

(4) Definition of "confused cells" - why not a fixed correlation threshold?

The authors define "confused cells" as those whose B2‑A2 spatial correlation exceeds the 95th percentile of the A1‑B1 baseline distribution within the same animal. This seems to be unnecessary. A fixed correlation threshold (e.g., r > 0.5 or r > 0.6) would have a direct biological interpretation: it would identify cells that maintain similar firing fields across two putatively distinct environments, i.e., cells that truly fail to remap. In contrast, a relative percentile threshold defines "confusion" not against an absolute standard of similarity, but against the degree of remapping observed during the first A‑B transition.

(5) SVM decoding on spike‑train temporal structure - missing justification.

The authors state that "the temporal structure of spike trains contained distinct contextual information" (P9) and then directly apply an SVM decoder to the data, but the logical bridge is missing. Why is a decoder necessary here, and is it useful for such a task?

(6) Figure 6 - learning occurs during reactivation but does not transfer to the online state (theta state), even after days of training.

What does this mean in terms of different phases of memory? Is the consolidation phase affected more? The authors may provide more discussion along these lines.

Reviewer #3 (Public review):

Summary:

Determining the ways in which Alzheimer's disease (AD) impacts the neural instantiations of memory is a fundamental aim of neuroscience and likely to be critical to understanding and treating disease progression. Previous work has highlighted how the hippocampal spatial code - typically context-specific - fails to discriminate between different environments in rodent models of AD. Here, Wang et al. leverage new analyses in a rat model of AD to test whether this deficit in 'remapping' reflects an impairment in intrinsic temporal coding. The authors find that the intrinsic temporal code of AD rats does come to effectively discriminate between environments (albeit more weakly than their wild-type counterparts), despite persistent impairments in remapping.

Strengths:

One of the major strengths of this work is its focus on distinguishing between two different types of neural impairments in AD. While previous work has highlighted impairments in remapping, these impairments could be due to: (a) impairments in intrinsic neural computations, or (b) impairments in the way these intrinsic neural computations are anchored to the world. The author's evidence supports the latter, with important implications for the nature of these impairments.

Weaknesses:

A handful of weaknesses could be addressed to strengthen this work. Firstly, a number of key measures of place code quality and behavioral quality between groups are omitted. Given that the author's interpretations rely on comparisons between groups and often use decoding analyses for central conclusions, indicating whether the recordings are comparable between groups in terms of behaviors and cell counts would be helpful for the reader. Even better, matching cell counts between groups for decoding analyses could ensure that outcomes are not driven by this potential confound.

Another weakness that is worth addressing involves the pivotal comparison between time-averaged remapping (Figure 4) and intrinsic temporal code discrimination (Figure 3). For temporal code discrimination, the analysis relies on comparisons between pairs of epochs (e.g. from A1B1 to A2B2), while for remapping, the comparison averages together epochs (A1+A2 and B1+B2). As a result, these comparisons are characterizing two slightly different things. Given that this is a key comparison for this paper (cofiring evolves to discriminate contexts while the spatial code does not), I think it would be important to demonstrate that remapping between pairs of epochs also stagnates to more closely mirror the cofiring analysis.

A final weakness is the sharp wave ripple (SWR) ensemble analysis. Here, the authors extract population vectors during SWR (SWR-PVs) during rest in both WT and AD rats. Next, they compare the extent to which SWR-PVs on AVERAGE resemble other SWR-PVs for that epoch. The authors report that this measure increases with experience in AD rats but not wild-type (WT) rats. While the authors interpret this to mean that SWR-PVs come to be more reliable with experience in AD rats, it could alternatively mean that SWR-PVs become less diverse or 'muddier' with experience, while SWR-PVs in WT rats continue to represent diverse trajectories. To make this analysis compelling, a better measure might be something that quantifies the diversity or content of SWR-PVs and something that quantifies similarity between each SWR-PV and the most similar other SWR-PVs.

Reviewer #1 (Public review):

Summary:

This manuscript investigates state-, trait-, and recovery-related computational phenotypes in Major Depressive Disorder (MDD) using an unmedicated, four-group cross-sectional design comprising currently depressed participants, remitted individuals, first-degree relatives at familial risk, and healthy controls. Utilizing a volatile four-armed bandit task and an explicit risk gambling task alongside hierarchical Bayesian modeling, the authors report that remitted participants uniquely display a lower punishment learning rate relative to all other groups. The authors conclude that recovery from MDD does not represent a simple normalization to healthy baseline levels, but rather involves a protective computational recalibration that dampens reactivity to negative outcomes to sustain remission.

Strengths:

(1) Highly Valuable Clinical Sample: Evaluates a rare, unmedicated sample across four distinct clinical stages (MDD, REM, REL, CTR), providing an exceptionally controlled framework to disentangle state, trait, and recovery markers.

(2) Combines dynamic reinforcement learning under environmental volatility with prospect-theoretic decision-making under explicit risk to capture multiple dimensions of value-based choice.

(3) Challenges the conventional assumption of clinical "normalization," offering a compelling hypothesis that psychiatric recovery may depend on active, compensatory recalibrations of cognitive parameters.

(4) Utilizes hierarchical Bayesian parameter estimation and leverages Bayesian Model Averaging (BMA) to mitigate single-model selection bias.

Weaknesses:

(1) The Discussion characterizes MDD and familial-risk groups as exhibiting "noisier" choice behavior in the gambling task, which directly contradicts the reported higher inverse temperature values that mathematically denote more deterministic choices.

(2) Framing a reduced punishment learning rate as a "recovery mechanism" overinterprets single-timepoint data, which cannot differentiate an acquired post-episode adaptation from a pre-existing resilience trait.

(3) The theoretical claim that lower punishment learning is protective in remission directly conflicts with the authors' dimensional findings, where lower punishment learning correlates with worse subclinical apathy and anhedonia in non-depressed participants.

(4) Model-agnostic choice repetition yielded no significant group effects, contrasting sharply with the robust group differences in model-derived parameters and necessitating posterior predictive checks.

(5) Fails to provide parameter recovery analyses to demonstrate that punishment learning rates can be reliably disentangled from lapse rates and outcome sensitivities across a 200-trial task structure.

(6) Selects a lower-ranked model under LOOIC without sufficient quantitative justification, and lacks sensitivity analyses to confirm that group-specific hierarchical priors did not skew estimates given unequal group sizes.

(7) Relies on several marginal p-values bordering across multiple parameters and symptom correlations without establishing a clear family-wise error or FDR correction strategy.

Reviewer #2 (Public review):

This manuscript reports on reinforcement learning in participants with current depression, remitted depression (without current depression), in people without depression but with first-degree relatives with depression, as well as healthy controls. Participants completed two common tasks measuring reinforcement learning and risk aversion, and their behavior was fit to computational models assessing processes on these tasks.

Participants with remitted depression showed a lower punishment learning rate and more value-concordant decisions on the reinforcement learning task. Relatives of depressed participants, as well as people who are currently depressed, had higher inverse temperature, indicating more value-driven choices. Within the non-depressed participants, the punishment learning rate was negatively associated with symptoms of anhedonia and apathy.

I have reviewed this paper at a previous journal. This revised version is responsive to most of my concerns, particularly in terms of placing the manuscript more in the context of other related literature and providing more details on methods. There are some remaining concerns about sample size and the appropriateness of some of the methods (e.g., interpreting participant-level parameter estimates from hierarchical models estimated using BMA), but the latter has been adequately addressed with sensitivity analyses.

Reviewer #3 (Public review):

Summary:

This manuscript describes an interesting study (preceded by a pilot study) that combined computational modeling with two tasks to try to tease apart state, trait, and vulnerability-related effects of depression. Specifically, the authors administered a bandit task and a gambling task to healthy controls, currently depressed adults, formerly depressed adults, and adults at familial risk of depression, and then used a suite of computational models to identify group differences in key model parameters. Key results included the detection of lower punishment learning rates (during the bandit task) in the remitted depressed group, which the authors hypothesize may be a compensatory mechanism to counteract the over-reaction to negative feedback that often characterizes depression (and indeed, punishment learning rates were elevated in currently depressed adults). Among non-depressed adults, lower punishment learning rates were associated with more apathy and anhedonia. The remitted depressed group also showed lower lapse rates in the bandit task. In the gambling task, the inverse temperature parameter was elevated in currently depressed adults and in adults at high familial risk for depression; exactly how to interpret this last result seems unclear. This is a revised manuscript, and from what I can see it appears that the authors were responsive to earlier comments.

Strengths (and summary of weaknesses):

I think the study has several noteworthy strengths. Testing four groups is a strength, as there is great interest in teasing apart risk factors of depression vs. "scars" of the illness, and the use of unmedicated individuals removes a common confound. The work is hypothesis-driven, the modeling is sophisticated, and the paper is well-written. Moreover, as the authors note, modeling allowed the authors to identify group differences that were not evident in raw behavioral analyses.

However, I think the manuscript could be further improved because some aspects of the methodology are a bit confusing and/or do not seem optimal. I list these issues in the comments below, but to briefly summarize: (a) I did not understand why the authors estimated separate reward and punishment values for each bandit; (b) the rationale for Bayesian Model Averaging could be strengthened; (c) examining relationships between model parameters and symptom scores only in the control group is suboptimal given the goal to better understand depression; and (d) the group differences in inverse temperature seem like they may depend on potential outliers. I think addressing these concerns would improve the paper and ensure that the study has a strong impact on the field.

Details regarding weaknesses/concerns:

(1) I found a basic aspect of the 4-arm bandit modeling confusing - namely, the use of separate reward and punishment value estimates (see equations 1 and 2 in the supplement). The participants are choosing among the bandits (presumably) based on value estimates for each bandit. Clearly, delivery of rewards and punishments affect those estimates, but it is not clear to me why or how there are separate value terms for rewards and punishments; typically, rewards and punishments influence one overall value estimate per bandit. Can the authors clarify? (I see that similar models were used in references 29 and 30, but additional clarification for readers of the current manuscript would be helpful)

(2) Bayesian Model Averaging (BMA) is new to me and may be new to many readers, and it would be helpful to provide a stronger rationale for the approach. The manuscript argues that model selection amounts to a "winner-takes-all" approach that may introduce bias; maybe, but typically the goal is to figure out which mechanism(s) best explain behavior, and so winner-takes-all is often appropriate. My limited understanding is that BMA is often used when prediction-rather than mechanistic understanding-is the goal. Why is BMA the right choice here?

(3) The authors performed a confirmatory factor analysis on questionnaire data from healthy controls out of concern that extreme scores in the other groups might bias the factor structure; consequently, they can only relate model parameters to their latent factors in the healthy controls. This does not seem optimal. While the negative relationships between punishment learning rate and both anhedonia and apathy in controls are interesting, the controls are not struggling with anhedonia or apathy. It would be valuable to know if similar relationships obtain in the other groups, particularly because this would speak to the study's goal of distinguishing between risk for depression and state/trait aspects of depression.

(4) Figure 5 gives the impression that group differences in inverse temperature may depend on potential outliers in the relative and MDD groups. Is that correct?

(5) The paper notes a group difference in IQ as estimated from the WTAR, and looking at Table 1 it appears that the group difference is driven by a lower WTAR score in the healthy volunteers (HV) from the pilot study. First things first: the score in the HV group is too low to be a standardized WTAR score. Like IQ scores, standardized WTAR scores typically have a mean around 100; scores for the four Study 2 groups look alright, but the Study 1 mean score of 40 is much too low. Can the authors clarify?

Reviewer #1 (Public review):

The studies by Hwangbo et al. diligently attempt to account for many of the typically neglected dietary and non-dietary factors.

Strengths:

• Work addresses many potential artifacts of dietary (e.g., dehydration stress, macronutrient ratios, and protein source) and non-dietary (e.g., leaky expression of S106-GAL4) manipulations-important factors that are too often overlooked.

• Balanced and complementary behavioral, molecular, and bioinformatic experiments

• Show necessity of proteostatic subunits in the fat body for DR-mediated longevity. The findings in the current manuscript lay the ground for future studies that test sufficiency of fat body prosβ3 and rpn7, or necessity of other proteostatic genes in other tissues.

Comments on revised version:

The revised manuscript is substantially improved and addresses many of the prior concerns. I have only a few minor recommendations and remaining issues:

Clarify the interpretation of the Con‑Ex feeding data. The authors describe the ~70% higher intake on 1SY in Clk^Jrk as modest, and note a ~40% higher mean intake on 5SY that is not statistically significant. However, lack of significance can reflect limited power, and these differences are potentially biologically meaningful, given that relatively small changes in nutrient ingestion can substantially affect lifespan. If the average effects are real, the Clk^Jrk flies would be ingesting an effective diet closer to ~1.7SY and ~7SY relative to controls. A shift of the diet-lifespan response curve in Clk^Jrk therefore cannot be fully excluded, particularly given the absence of intermediate diets between 1SY and 5SY and the observation that Clk^Jrk is sometimes shorter‑ and sometimes longer‑lived than controls across different trials and diets.

Although the core finding is strengthened by using several diet formulations, most additional experiments continue to rely on whole‑food dilution, even as the field is moving toward more defined DR regimens (e.g., yeast‑only or yeast‑extract-based protocols). There remains considerable variability and, in some cases, a lack of clear DR‑mediated lifespan extension in control cohorts (for example, in some GeneSwitch experiments using whole‑food dilution). It would be helpful if the authors briefly commented on this variability and justified their continued use of whole‑food dilution in these experiments.

Please add a clear Methods description of the feeding assay (Con‑Ex), including fly age, assay duration, dye or tracer conditions, sample processing, quantification, and statistical analysis.

Please ensure that the survival data shown in Figure 5 and associated supplements are explicitly linked to Cox proportional hazards analyses in the text or figure legends, with clear indication of the models used (e.g., gene, diet, and gene×diet interaction terms). The Methods state that diet is used as a continuous variable; given the non‑linear (U‑shaped) lifespan-diet reaction norm (reduced survival at both 1SY and higher yeast), it would be important to clarify whether 1SY was excluded from these Cox models, or alternatively, to model diet categorically, restrict the continuous analysis to 5-20SY, or apply an appropriate non‑linear transformation (e.g., splines). As written, it is not clear how the Cox model accommodates the non‑linear diet response.

Reviewer #2 (Public review):

Summary:

Dietary restriction (DR) increases lifespan, an effect that has been consistently observed in several organisms, but we still lack a clear mechanism to explain this phenomenon. In this work, Hwangbo et al. revisited the role of the circadian clock in DR-mediated lifespan effects. They found that the increase in lifespan produced by DR is missing on a clock mutant, a clock dependency that is also observed at the level of nutrient-dependent egg laying. By conducting RNA-seq with an impressive temporal resolution, they showed that DR triggers an increment in the number of cycling genes expressed in the fat body, the fly functional analog of the mammalian liver. Interestingly, from these genes, a group of them are de novo daily expressed genes, meaning that their expression was not rhythmic under the control diet but appear rhythmically expressed under DR. Among those, genes encoding proteasome subunits are enriched. The authors finally showed that adult-specific knockdown of these genes in the fat body prevents the increase in lifespan under DR, further supporting a role of the proteasome in this process. Overall, the conclusions are mostly supported by the evidence presented, and the authors' discussion nicely frame their results with other research in the field.

Strengths:

- Many studies have limited their observations of DR on lifespan to a few dietary conditions which makes the reach of some previous conclusions somewhat limited. The dilution strategy that the authors used in this work provides a strong indication that the effect of DR on lifespan relies on clock expression regardless of the conditions used. Furthermore, the inclusion of the egg-laying assay is a good addition to support this hypothesis.

- Because the strength of the rhythmicity statistics relies heavily on the number of data points collected, the temporal resolution used for the RNA-seq experiments (every 2 hrs per 48hrs) is remarkable. This allows exquisite dissection of the phase of rhythmic genes in different conditions. The dataset produced in this work might be of use to other groups interested in weighting the role of other represented gene clusters in DR.

Weaknesses:

I see only minor flaws in this work, that if addressed, might strengthen the authors' conclusions, particularly:

- The results of the lifespan assays are quite variable and in some instances contradictory (Fig. S8) across trials, possibly because there are other unaccounted variables we still do not understand. The fecundity assay, in contrast, seems to be a better readout (Fig. 2). Confirming at least the two genes picked for the study (Fig. 5) would be good support for the claim that the proteasome mediates the effects of DR.

- According to the model, the acute effect of DR on gene expression is related to CLOCK protein function. However, I am not sure how this link was established. It is tempting to assume that CLOCK upstream is the reason for having an increase in rhythmic genes under DR, but the experiments did not test this. The tests conducted either assessed the role of clk or the effect of an impaired proteasome on DR-dependent extension of lifespan. Thus, it is difficult to assert the authors' claims on the link between CLK and the changes in cycling genes and to the proteasome upon DR.

Comments on revised version:

In this new version, Hwangbo and colleagues add new data to support a role of the clock in the effects of DR on lifespan. While adding this new data helps to alleviate some of the concerns previously raised, I think there are still some gaps. Below are my main concerns:

ClkJrk transcriptomic data: Adding this data supports a role of the clock in daily rhythmicity of genes in the fat body, likely due to a circadian role. However, it does not show that de novo rhythmicity of proteasomal genes is clock-related since there is no ClkJrk DR dataset. Thus, there is still a possibility this is a pleiotropic effect. While redoing an entire RNA-seq dataset might not be feasible, a possible way to support the circadian claim would be to use proxy genes observed in the Ctrl vs DR conditions and compare them by qPCR in ClkJrk Ctrl vs DR.

Feeding data: Are the flies reared in DR conditions, or do they just start the DR at the beginning of the experiment? If so, is it possible the flies will show a different feeding pattern after consecutive days of DR affecting overall (5-10 days) food consumption?

Clk expression is important for non-circadian roles in the ovaries (Wang et al., Cell Mol Life Sci, 2025). Therefore, it is possible that the fecundity effect is at the low level of the ovary/egg development instead of integration and processing of DR. This might be a confounding effect when interpreting data in Fig 2 in ClkJrk as solely the effect of DR.

Line 215: Considering the discussion above, I'd rather change "circadian-dependent change" to "daily"<br /> Considering that the ClkJrk RNA-seq transcriptomic was generated, presumably, at a different date/time than the original transcriptomic data from Control vs DR, comparative metrics (seq depth, mapping rate, etc.) between these are needed.

How is the feeding analysis conducted? I believe the method information was not updated.

Reviewer #1 (Public review):

Summary:

This manuscript provides fundamental insight into ciliary biology, specifically, how ciliary axoneme orientation is governed by microenvironmental bending or intrinsic cytoskeletal steering rather than strictly basal body docking coordinates.

Strengths:

There are three major strengths in this manuscript. First, combining high-resolution imaging with deep-tissue sectioning yields impressive lateral resolution, enabling robust separation of dual centrioles within the crowded chondrocyte extracellular matrix. Second, the authors established an automated pipeline that evaluates thousands of individual cells across multiple anatomical regions and differentiation zones, lending strong statistical weight to positional and volumetric measurements. Lastly, they demonstrate that ciliation peaks in the peripheral resting zone and ciliary length peaks in hypertrophic cells, providing a compelling cellular explanation for why Ift88 deletion impacts peripheral growth plate geometry and hypertrophic expansion.

Weaknesses:

There are three major weaknesses in this manuscript. First, the paper lacks explicit descriptions of data mentioned in the Abstract and Methods, including the RNA-seq differential expression, WGCNA modules, and immobilization/ciliary alignment data. Second, while the Methods section mentions correcting for "Z-blur" / point-spread function distortion in 3D spherical coordinate calculations, further detail is required on how orientations are disambiguated from optical sectioning depth artifacts. Lastly, the RNA-seq analysis demonstrates that ambulatory unloading alters hedgehog and primary cilia gene signatures, yet axoneme orientation itself remains static. The narrative requires a clearer mechanistic synthesis regarding how mechanical loading modulates ciliary signaling if physical alignment of the cilia is refractory to mechanical force in chondrocytes.

Reviewer #2 (Public review):

Summary:

The aim of this work was to characterise in detail the cellular organisation of the growth plate in the growing mouse limb, the effect of mechanical loading due to physical activity, and the role of primary cilia in mediating this effect as putative mechanosensors. Primary cilia are generally thought to function as mechanosensors in a range of different organs and tissues, e.g. in the kidney. Exposure to mechanical loading is a normal part of post-natal limb growth, and the central hypothesis underlying this work was that primary cilia will play an important role in transducing the effects of mechanical loading into cellular responses during this process. To investigate this, the authors used a mouse model encoding fluorescent markers for primary cilia, and also allowing conditional knockout of IFT88, a protein that plays a key role in primary cilium biogenesis. The authors compared the effects of mechanical loading by comparing tissue from mice with normal or surgically immobilised limbs. To investigate the role of primary cilia, the authors performed the same experiments with mice treated with tamoxifen to induce IFT88 knockout.

Strengths:

A major strength of this work is that it studied primary cilia in a fully in vivo system. The authors employed cutting-edge imaging approaches and image analysis pipelines to rigorously study cellular organisation, centriole positioning, cilium length, and orientation across thousands of cells in limbs from 18 animals. The imaging results presented are of an exceptionally high-quality. The analysis of imaging data is extremely quantitative and robust and utilised appropriate statistical analyses, which were clearly stated throughout. The imaging data were complemented with transcriptomic data and analyses, which provided an orthogonal dimension for understanding cellular responses. An interesting and unexpected outcome from this is that the primary cilia are oriented in the same direction, and inclined at a roughly 45{degree sign} angle to the mediolateral and proximal-distal axes of the limb. The authors speculate as to how this might arise and the role it may play in sensing.

Weaknesses:

Overall, the work reported in this study was of a very high quality, and I could not find any significant shortcomings. However, I did feel that the paper was not very well written in many places, which made it difficult to read.

Overall, I think that the authors did achieve their aims in this study. It will be interesting to unpick the cellular mechanisms that lead to alignment of the cilia, the role of this alignment in mechanosensing, and the molecular mechanisms by which the cilia sense mechanical strain. Thus, this work provides a fertile ground for future studies, which will have important consequences for the study of primary cilia in vivo.

Reviewer #3 (Public review):

Summary:

This study aims to characterize the three-dimensional organization of primary cilia in the postnatal mouse growth plate and to determine how ciliary prevalence, length, position, and orientation vary across anatomical regions and stages of chondrocyte differentiation. The authors combine volumetric imaging and automated image analysis with conditional disruption of IFT88, limb immobilization, and bulk transcriptomics. The work provides a valuable anatomical dataset and identifies several interesting spatial patterns, including increased ciliation in the lateral resting zone, longer cilia in hypertrophic chondrocytes, and, most notably, a non-random orientation of ciliary projections despite a much broader distribution of centriole positions.

The descriptive evidence is largely solid, and the imaging dataset should be useful to researchers studying primary cilia, skeletal development, and tissue mechanobiology. However, the evidence is incomplete for several of the central mechanistic conclusions. In particular, the current analyses do not establish that ciliary orientation is uncoupled from basal-body position, and they leave unresolved how ciliary orientation relates to cell orientation. The immobilization experiment also supports a narrower conclusion than the proposed cell-intrinsic orientation program, while the final model linking ciliary angle to multidirectional signal integration remains speculative. Overall, the authors succeed in identifying an interesting and reproducible anatomical pattern, but the mechanism underlying that pattern remains largely open.

Strengths:

A major strength is the scale and anatomical context of the imaging. Quantifying thousands of cilia and tens of thousands of centrioles in three dimensions while preserving information about growth-plate zone and position across the limb is technically demanding. This allows the authors to identify regional differences that would be lost in dissociated cells or bulk tissue measurements.

The study also provides several potentially useful observations. Ciliation is higher in the lateral periphery, particularly in the resting zone, cilia are longer in hypertrophic chondrocytes, and ciliary projections show a reproducible non-random orientation. The latter is the most interesting result of the study and provides a useful foundation for asking how organelle orientation is established within a developing tissue.

I also appreciated that the authors place these observations in several biological contexts rather than stopping at a descriptive atlas. IFT88 disruption alters ciliation and growth-plate cell organization, while immobilization changes growth-plate dimensions, cell morphology and orientation, and the transcriptome even though the measured ciliary properties remain comparatively stable. These perturbations give the anatomical observations useful biological context.

Weaknesses

The main concern is that the claim that ciliary orientation is uncoupled from basal-body position is not directly demonstrated. The manuscript shows that centriole positions are broadly distributed and, separately, that ciliary projections have a preferred tissue-level orientation. Different population-level distributions, however, do not establish independence within individual cells. For example, basal bodies could be broadly distributed while their position determines which of two opposite directions along a common tissue axis the cilium adopts. This possibility is particularly relevant because Centrin-2 labels both centrioles, whereas only one serves as the basal body. The current data therefore support a difference between the population distributions of position and orientation, but not yet the stronger claim that the two are uncoupled.

A related gap is the relationship between cell orientation and ciliary orientation. The manuscript measures both, and cell orientation changes with growth-plate region, IFT88 deletion, and immobilization, while ciliary orientation appears relatively stable. Yet the two measurements are never directly related within the same cells. It is therefore unclear whether cilia adopt a reproducible angle relative to the major axis of their own cell, whether this relationship changes between the center and periphery, or whether changes in cell organization can occur independently of local ciliary alignment. This seems important for interpreting the tissue-level orientation pattern.

The statistical treatment of orientation also deserves caution. These are circular or spherical measurements, yet much of the analysis relies on linear distributions and Kolmogorov-Smirnov tests. This is particularly problematic around the 0{degree sign}/360{degree sign} boundary, where values near 350{degree sign} and 30{degree sign} are geometrically close but appear separated in a linear representation. The manuscript also does not clearly distinguish between a preferred axis, where opposite directions are equivalent, and a preferred polarity, where one direction is favored. In addition, thousands of cilia are nested within a much smaller number of mice, so the apparent statistical power should not be driven primarily by pooled object counts. Given that regional differences are a central theme of the paper, it would also be useful to know more clearly whether the preferred axis or the strength of the orientation bias differs between the middle and lateral growth plate at the animal level. I also could not identify a formal comparison of the centriole or ciliary distributions with an appropriate uniform circular or spherical null. The reported tests mainly compare zones and regions, so the claims that centriole position is non-preferential and ciliary orientation is non-random are not yet statistically established in the form presented.

The IFT88 conditional knockout is not carried through to the principal orientation question. The authors examine cell size, cell-axis organization, ciliation, and cilium length, but do not report whether the remaining cilia retain the preferred orientation or whether centriole positioning changes. Given the central role of this genetic perturbation in the manuscript, this leaves the genetic and orientation arms of the study somewhat disconnected.

Finally, the immobilization experiment and the mechanistic interpretation should be separated more carefully. Only four animals were analyzed in the offloaded and contralateral conditions, and medial and lateral regions were averaged because of the small sample size. The experiment shows that the established ciliary orientation remains relatively stable over a two-week postnatal interval despite clear changes elsewhere in the tissue. It does not exclude a role for mechanical forces earlier in establishing the axis, nor does a nonsignificant difference with four animals demonstrate equivalence. Similarly, the proposed cell-intrinsic orientation program and the final "single-axis blindness" model are interesting hypotheses, but the study does not yet identify what establishes the axis or how the observed ciliary angle would alter sensitivity to a force or biochemical gradient. Those ideas are worth discussing, but they should remain clearly separated from the observations directly supported by the data.

Reviewer #1 (Public review):

Summary:

The review addresses an important and timely topic that concerns the role of cryo-EM in transforming RNA structural biology from a "static" discipline to one increasingly concerned with conformational ensembles and molecular dynamics. The scope is well within the eLife standards, and the style and general architecture do fit eLife.

Strengths:

The review is extremely well written, well-conceived and clear. The main strengths are in the breadth of coverage, the clear theme, and the inclusion of practical examples that explain in detail the construct design, sample preparation, vitrification, and data analysis. The manuscript will certainly be impactful and valuable, especially for readers who are not specialists in cryo-EM, as it provides an accessible overview of recent advances across a wide range of RNA systems.

Weaknesses:

My only reservation is that, currently, the review reads too much like a list of examples. The authors should make an effort, and I am sure they are well up to it, to try to synthesise the message, provide more critical insights and amalgamate the text better, to really reach a wider audience.

If revised along the lines detailed below, I am sure that the review will become an authoritative and influential resource for the RNA structural biology community.

Reviewer #2 (Public review):

Summary:

In this review, the authors set out to synthesize how cryo-EM is reshaping RNA structural biology, moving the field from the determination of static, individual conformations toward the reconstruction of dynamic conformational ensembles and energy landscapes. Through eight case studies spanning ribozymes, riboswitches, viral RNAs, and synthetic RNA assemblies, they aim to show how cryo-EM has revealed mechanisms of RNA motion, including folding, ligand-dependent switching, and cooperative assembly, and to provide a practical account of the experimental and computational challenges (construct design, sample preparation, vitrification, data analysis) that are specific to dynamic RNA targets.

Strengths:

The manuscript succeeds in bringing together a wide and genuinely current range of case studies illustrating the field's shift toward dynamics-focused cryo-EM, several published within the last one to two years. The dedicated "Challenges" section, which walks through construct engineering, buffer and vitrification optimization, grid screening, and heterogeneity-resolving computational approaches, is a particularly useful and practical contribution; it goes beyond simply cataloguing structures and gives readers new to the area a genuine methodological roadmap. The figures are detailed and well matched to the quantitative claims made in the text (helix rotations, distances, RMSDs), which strengthens the paper's value as a reference resource.

Weaknesses:

The coverage of two areas in particular, the SL5 viral RNA element and RNA quaternary/multimeric assemblies, would benefit from incorporating additional recent primary literature that is directly relevant but currently omitted. This does not undermine the manuscript's core narrative, but it means the review is presently less complete than it could be as a field synthesis, particularly for readers using it to identify the full body of recent work on these specific RNA classes.

More concerning is that one specific structural claim, describing conformer heterogeneity in the cobalamin riboswitch (Case study 3, holo dimer 4), appears to invert the finding reported in its own source paper (Ding, Deme et al., 2023). As written, the manuscript states that P2 and the distal half of P6 are structured in dimer 4, whereas the source paper reports that these are the regions that could not be modeled. This is worth flagging prominently because it is a factual claim about a specific structure, not an interpretive point, and readers relying on this review as a secondary source could come away with an inverted understanding of that structure's flexibility.

The manuscript also contains several minor internal inconsistencies. None of these individually threatens the paper's core arguments, but together they suggest the manuscript would benefit from a careful proofreading and reference-list audit pass.

Overall, the authors largely achieve their stated aim. The case studies convincingly illustrate that cryo-EM can now resolve discrete and continuous conformational states of RNA at near-atomic resolution, and the Challenges section substantiates the claim that construct design, sample preparation, and computational innovations have been jointly responsible for this progress. The gaps in coverage of SL5 and multimeric RNA literature, and the inverted claim in Case study 3, are the main respects in which the manuscript falls short of being a fully comprehensive and accurate synthesis at this stage, but these are correctable issues rather than flaws in the overall argument or framework.

This review is likely to be a useful entry point and practical reference for researchers moving into RNA cryo-EM, particularly given the level of methodological detail in the Challenges section. Its impact would be strengthened by two additions. First, a short discussion of recent cryo-EM advances in tRNA would round out the manuscript's coverage of classical RNA structural targets alongside the ribozyme, riboswitch, and viral RNA case studies already included. Second, the raiA non-coding RNA, currently mentioned only briefly, has in the last two years become a genuine model system for cryo-EM-based ncRNA structure determination, progressing from a single novel-fold discovery to a comparative structural framework spanning multiple raiA subtypes and candidate protein partners. Expanding this into a full case study would let the manuscript showcase, in a single worked example, exactly the kind of field-level progression (from novel fold to scaffold-based strategy and further to comparative structural framework) that the review's own framing describes as the trajectory of the field as a whole.

Reviewer #3 (Public review):

This review describes how cryo-EM is moving RNA structural biology from the determination of static structures toward the characterization of conformational ensembles. Eight case studies spanning self-splicing introns, riboswitches, viral RNA elements and synthetic assemblies show how cryo-EM has captured folding intermediates, hinge-mediated domain motions and ligand-dependent switching, and the authors pair these examples with practical guidance on construct design, sample preparation, vitrification and heterogeneity analysis. The argument that conformational heterogeneity is a source of mechanistic information, rather than a limitation, is well supported, and Table 1 will be a useful reference for laboratories entering the field. The manuscript is timely and of broad interest, and I recommend publication after minor revision.

(1) Scaffold-based structure determination (page 14, lines 5-9). The section on chimeric RNAs presents the scaffold strategies as a single group and cites Haack et al. (2025) and Langeberg & Kieft (2023) in one parenthetical, so individual results are not attributed to their sources. The distinction between these studies is substantive. Earlier scaffolds based on the Tetrahymena group I intron (Langeberg & Kieft, 2023) or on RNA origami (Sampedro Vallina et al., Nucleic Acids Res. 51:4613-4624, 2023) resolved the appended RNAs at approximately 4.4-5 Å. Haack et al. (2025) reported the first RNA scaffold to yield a high-resolution structure of the target itself, resolving the ligand-binding pocket of the thiamine pyrophosphate (TPP) riboswitch at 2.5 Å and extending nucleotide-level cryo-EM analysis to small RNAs that had previously been intractable. I ask the authors to attribute each result to its source and to state explicitly that Haack et al. (2025) achieved the first high-resolution structure of a scaffolded target RNA. Because the same study captured the ligand-free TPP riboswitch in an open, Y-shaped conformation, a direct example of the ligand-dependent switching that is central to this review, the TPP riboswitch should also appear in the riboswitch section (page 8, lines 15-36), together with the fluoride riboswitch of Langeberg & Kieft (2023).

(2) Page 6, lines 8-14. Self-splicing introns are described collectively as evolutionary ancestors of the spliceosome that reside in pre-mRNA transcripts. The proposed ancestral relationship to spliceosomal introns and snRNAs applies to group II introns. Group I introns, including the Tetrahymena intron, which interrupts a pre-rRNA, initiate splicing with an exogenous guanosine and are not considered spliceosomal precursors.

Reviewer #1 (Public review):

Summary:

The authors examine the impact of heat stress during an embryonic CP in Drosophila, focusing on the larval locomotor network. They show that elevated temperature increases neuronal activity and, when applied during the CP, results in long-term instability of the network which manifests in prolonged seizure recovery times. At the neuromuscular junction, substantial structural changes occur, including terminal overgrowth and altered receptor composition, yet synaptic transmission remains preserved due to homeostatic regulation. Motoneurons display reduced excitability but receive increased synaptic input from premotor interneurons. These findings suggest that maladaptive instability originates within the central circuitry rather than at the neuromuscular junction, where changes seem to be homeostatically compensated. The study concludes that different network components exhibit distinct and hierarchical responses to CP perturbations, with premotor interneurons setting the tone for downstream adjustments in motoneurons.

Strengths:

The work takes advantage of the unique accessibility of the Drosophila system. A major strength of the study is the integration of structural, physiological, and behavioral analyses, which allows the authors to draw a comprehensive picture of how CP perturbations shape the locomotor network. The choice of an ecologically relevant stimulus (heat stress) is particularly convincing, as it links experimental manipulations more closely to natural environmental conditions. The experiments are carefully designed, and the results are robust and consistent with previous findings in the field, while also extending them in new directions. Importantly the work clarifies how temperature perturbations within distinct developmental time windows affect different properties of motor circuit formation.

Weaknesses:

A small limitation of the study is that it remains difficult to integrate maladaptive (seizure recovery) and adaptive/homeostatic phenotypes within a single mechanistic framework, leaving some space for interpretation.

Comments on revised version.

I think the authors did a great job at revising the manuscript and they addressed all my comments.

Reviewer #2 (Public review):

Summary:

This manuscript presents a thoughtful and well-executed study of critical period plasticity in the Drosophila larval motor circuit. The authors examined how transient heat, 32C, during embryonic stage, altered network properties, showing that premotor interneurons A27h increase excitatory drive onto motoneurons, which respond with a reduction in excitability. At the NMJ, synaptic terminals expand and GluRIIA distribution shifts, yet synaptic transmission remains largely unaffected. Despite these local compensations, the treated larvae display slower crawling and prolonged recovery from seizures, indicating that the network is functionally compromised.

Strengths:

(1) One of the major strengths of this study is the elegant dissection of a defined circuit, tracking changes from premotor interneurons through motoneurons to the NMJ. The multimodal approach provides a comprehensive view of how connected elements respond to CP perturbations.

(2) An interesting finding is that NMJ morphology changes dramatically without corresponding deficits in synaptic transmission, challenging the common assumption that larger boutons necessarily indicate stronger synapses.

(3) Another intriguing result is that even with two layers of homeostatic compensation, locomotor behavior is still impaired, highlighting the limits of compensation and underscoring the critical role of CP timing.

(4) Beyond these scientific insights, the study benefits from a well-defined, tractable system and simple experimental manipulations, which together make the results highly interpretable and reproducible.

Comments on revised version.

The authors have carefully considered my comments and recommendations and have made substantial efforts to improve the clarity and validity of the study. Although additional electrophysiology experiments using shorter heat stress windows were not feasible, the authors performed additional analyses of postsynaptic GluRs and provided a clearer discussion of the study's limitations. Overall, this is a strong and well-written paper that establishes a valuable foundational framework for addressing interesting and important questions about adaptive responses in developing neural circuits.

Reviewer #1 (Public review):

Wang, Zhou et al. investigated coordination between prefrontal cortex (PFC), and hippocampus (Hp), during reward delivery via analyzing beta oscillation. Beta oscillations are associated with various cognitive functions but their role in coordinating brain networks during learning is still not thoroughly studied. Authors focused on the changes in power, peak frequencies and coherence of beta oscillations in two regions when rats learn a spatial task thru days. Contradicting with authors hypothesis, beta oscillations in those two regions during reward delivery were not coupled in spectral or temporal aspects. They were, however, able to show reverse changes in beta oscillations in PFC and Hp as the animal's performance got better. Authors were also able to show a small subset of cell population in PFC that are modulated by both beta oscillations in PFC and sharp wave ripples in Hp. A similarly modulated cell population was not observed in Hp. These results are valuable in pointing out distinct periods during a spatial task when two regions modulate their activity independent from each other.

Authors made a detailed analysis of the data to support their conclusions. Few more points of discussion would clarify the results of the paper.

(1) One of the big conclusions of the paper is how the beta burst power is changing after learning the task (Figure 3). Authors have also showed in Figure 6-1, how the SWR power and rate are changing thru the training days. Did they observe a change in coordination of Beta bursts and SWR between the days, which would also reflect how experience changes the coordination?

(2) Authors have shown in detail the opposite relationship between Beta phase locking and SWR modulation in Hippocampus in Figure 7I. This might require a different analysis, but is it possible to make a discussion on predicting a cell firing in a SWR after it fires in a beta burst.

Other than these two points, authors have addressed previous comments and made a convincing analysis of their data.

Reviewer #2 (Public review):

Using electrophysiological recordings in freely moving rats during a spatial navigation task, this study investigated the role of beta oscillations in the hippocampal-prefrontal network. Through a set of appropriate analyses-including oscillation-oscillation coupling, oscillation-spike modulation, and behavioral dependant measurements-the study presents convincing evidence for uncoupled beta activity between the two regions. These findings offer important insights into the network mechanisms of spatial navigation and may have significant implications for related neurological disorders.

Comments on revised version.

The authors have carried out additional analyses and made corresponding revisions to the manuscript in response to the earlier review comments, which have made the conclusions more convincing. However, please note that the last question about coexistence of beta and SWR has not been fully answered. Please supplement your response to address this point completely.

Reviewer #3 (Public review):

This paper explored the role of beta rhythms in the context of spatial learning and mPFC-hippocampal dynamics. The authors characterized mPFC and hippocampal beta oscillations, examining how their coordination and their spectral profiles related to learning and prefrontal neuronal firing. Rats performed two tasks, a Y-maze and F-maze, with the F-maze task being more cognitively demanding. Across learning, prefrontal beta oscillation power increased while beta frequency decreased. In contrast, hippocampal beta power and beta frequency decreased. This was particularly for the well-performed and well-learned Y-maze paradigm. The authors identified the timing of beta oscillations, revealing an interesting shift in beta burst timing relative to reward entry as learning progressed. They also discovered an interesting population of prefrontal neurons that were tuned to both prefrontal beta and hippocampal sharp-wave ripple events, revealing a spectrum of SWR-excited and SWR-inhibited neurons that were differentially phase locked to prefrontal beta rhythms.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review both by revising their original presentation where necessary and by providing responses to the reviewers in cases where they disagreed that revision of the original presentation would be necessary.]

Summary:

As a general phenomenon, adaptation of populations to their respective local conditions is well-documented, though not universally. In particular, local adaptation has been amply demonstrated in Arabidopsis thaliana, the focal species of this research, which is naturally highly selfing. Here, the authors report assays designed to evaluate the spatial scale of fitness variation among source populations and sites, as well as temporal variability in fitness expression. Further, they endeavor to identify traits and genomic regions that contribute to the demonstrated variation in fitness.

Strengths:

With many (200) inbred accessions drawn from throughout Sweden, the study offers an unusually fine sampling of genetic variation within this much-studied species, and through assays in multiple sites and years, it amply demonstrates the context-dependence of fitness expression. It supports the general phenomenon of local adaptation, with multiple nuances. Other examples exist, but it is of value to have further cases illustrating not only the context-dependence of fitness expression but also the sometimes idiosyncratic nature of fitness variation. I commend the authors on their cautionary language in relation to inferences about the roles of particular genomic regions (e.g.l.140-144; l.227)

Reviewer #2 (Public review):

Summary:

The goal of this study was to find evidence for local adaptation in survival and fecundity of the model plant Arabidopsis thaliana. The authors grew a large set of Swedish Arabidopsis accessions at four common garden sites in northern and southern Sweden. Accessions were grown from seed in trays, which were laid on the ground at each site in late summer, screened for survival in fall and the following spring, and fecundity was determined from rosette size and seed production in spring. Experiments were complemented by 'selection experiments', in which seeds of the same accessions were sown in plots, and after two years of growth, plants were sampled to determine fitness from genotype frequencies, providing a more comprehensive evaluation of lifetime fitness than can be gleaned from fecundity alone.

As the main result, southern accessions had higher mortality in northern sites in one of two years, but also suffered more slug damage in southern sites in one year, indicating a potential link between frost tolerance and herbivore resistance. Fecundity of accession was highest when growing close to the 'home' environment, but while accessions from one sand dune population in southern Sweden had among the lowest fecundities overall, they consistently had the highest fitness in the selection experiment. Accessions from this population had large seed size and rapid root growth, which might be related to establishment success when arriving in a new, partially occupied habitat. However, neither trait could fully explain the very high fitness of this population, suggesting the presence of other, unmeasured traits.

Overall, the authors could provide clear evidence of local adaptation in different traits for some of their experiments, but they also highlight high temporal and spatial variability that makes prediction of microevolutionary change so challenging.

Strengths:

A major strength of this study is the highly comprehensive evaluation of different fitness-related traits of Arabidopsis under natural conditions. The evaluation of survival and fecundity in common garden experiments across four sites and two years provides an estimate of variability and consistency of results. The addition of the 'selection experiment' provides an extended view on plant fitness that is both original and interesting, in particular highlighting potential limitations of 'fitness-proxies' such as seed production that don't take into account seedling establishment and competitive exclusion.

Throughout the study, the authors have gone to impressive depths in exploring their data, and particularly the discovery of 'native volunteers' in selection experiment plots and their statistical treatment is very elegant and has resulted in compelling conclusions. Also, while the authors are careful in the interpretation of their GWAS results, they nonetheless highlight a few interesting gene candidates that may be underlying the observed plant adaptations, and which likely will stimulate further research.

Overall, this study will likely make an important contribution to the field of evolutionary biology, and it is another very strong example of how the extensive molecular tools in Arabidopsis can be leveraged to address fundamental questions in evolution and ecology, to an extent that is not (yet) possible in other plant systems.

Reviewer #3 (Public review):

Summary:

The manuscript presents a large common garden experiment across Sweden using solely local germplasm. Additionally, there is a collection of selection experiments that begin investigating the factors shaping fecundity in these populations. This provides an impressive amount of data and analysis investigating the underlying factors involved. Together, this helps support the data showing that fluctuations and interactions are key components determining Arabidopsis fitness and are more broadly applicable across plant and non-plant species.

Strengths:

The field trials are well conducted with extensive effort and sampling. Similarly while the genetic analysis is complex it is well conducted and reflects the complexity of dealing with population structure that may be intricately linked to adaptive structure. This has no real solution and the option of presenting results with and without correction is likely the only appropriate option.

Reviewer #1 (Public review):

Summary:

The study identifies two previously uncharacterized endogenous receptors for Aplysia PRXamide peptides and shows that N-terminal pyroglutamylation can produce opposite effects on receptor activation. The authors further propose that this modification acts indirectly by altering peptide conformation and that receptor pocket properties determine the direction of its effect. The findings are potentially significant for understanding how peptide modifications influence receptor selectivity, but the evidence supporting the proposed molecular mechanism is not yet sufficiently strong.

Strengths:

The identification and functional characterization of the two receptors are valuable. The contrasting effects of pyroglutamylation, together with peptide and receptor mutagenesis and computational analyses, provide an interesting framework for investigating peptide-receptor selectivity.

Weaknesses:

Most of the statements about novelty and generality are stronger than warranted by the current data. The central mechanistic model relies heavily on computational predictions and indirect functional measurements, without direct structural or receptor-proximal evidence. In addition, the human receptor data provide only partial support for the proposed mechanism, particularly because the pyroglutamylated and non-pyroglutamylated peptides are not significantly different at human receptor 2. Thus, the data support differential effects of pyroglutamylation but do not yet fully establish the proposed distal conformational mechanism.

Reviewer #2 (Public review):

Summary:

The manuscript by Chang et al. presents the discovery and deorphanization of two bona fide PRXamide GPCRs, and their peptide agonists, in Aplysia californica (sea hare, a type of sea slug). Focusing on MMG2-DPb, the most potent peptide agonist, the authors demonstrate that pyroglutamination on the extracellularly facing N-terminus of the peptide reduces its agonist potency towards ApPRXa-R1 and increases potency towards ApPRXa-R2. Model-guided pocket and peptide mutagenesis demonstrate multiple differential dependencies and sensitivities of ApPRXa-R1 and ApPRXa-R2, supporting distinct mechanisms of peptide binding. The authors then show that a pyroglutaminated version of the dog Neuromedin U peptide has an increased potency towards human NMUR1, relative to the free-Gln version or the non-Gln-containing human peptide, whereas the potency towards NMUR1 is slightly reduced. These examples delineate N-terminal pyroglutamination of a peptide agonist as a receptor subtype selectivity controlling mechanism even when the peptide binds the receptor C-terminus.

Strengths:

(1) Identification of a class of GPCR-signaling peptides in a poorly characterized organism (Aplysia californica, a type of a sea slug).

(2) Deorphanization of two Aplysia californica GPCRs and the establishment of an Aplysia analog of the human Neuromedin U signaling system.

(3) A rigorous structure-function study of the Aplysia receptors and peptides.

(4) Identification of pyroglutamination as a mechanism controlling subtype selectivity in Aplysia PRXamide receptor system.

(5) Very clear and compelling graphics.

(6) Overall, the biochemical and pharmacological part of the study is strong, exciting, and well-presented.

Weaknesses:

(1) My biggest problem is with the emphasis on the 'non-contacting role' of the N-terminal pGlu: "purely on positional grounds, N-terminal pQ/Q is unlikely to form direct contacts with receptor residues", "Despite the absence of direct pQ/Q-receptor interactions...", "indirect PTM distal steering", etc. The absence of direct contacts between pGlu and the receptor residues is likely an artifact of limited precision in modeling and reflects insufficiently advanced modeling tools. The authors used Swiss-Model, Robetta, and HPEPDOCK: why not go for the state-of-the-art AI modeling software like Boltz, Chai, or AlphaFold? A quick AlphaFold3 generates a model where Gln and pGlu form perfect contacts with the receptor N-term and ECL2 (in ApPRXa-R2) or N-term and ECL3 (in ApPRXa-R1). The N-termini of both receptors are quite long, form well-defined tertiary structures, and fold onto the receptor extracellular loops; in the case of ApPRXa-R1, the N-terminal domain is stabilized by an intra-domain disulfide bond C15(NT)-C133(NT) and stapled to ECL2 via another disulfide bond C16(NT)-C322(ECL2), suggesting that these interactions are real. The 3D models generated by the authors are not available for review but based on figures, I don't see these N-terminal domains modeled at all, which would obviously affect the docked position of the peptide N-terminus and its contacts with the receptor. For example, in an AlphaFold model, ApPRXa-R1 F161, E317, R340 are in direct vicinity of the peptide's Gln / pGlu and are quite distinct in ApPRXa-R2 - direct contacts with these or nearby residues may easily explain the differential preferences for free Gln vs pGlu but none of them were tested via mutagenesis.

(2) Some conclusions and interpretations in the manuscript are overstated and lack precision. For example: "...a single N-terminal lactam modification converts a minimal chemical difference into bidirectional GPCR subtype outputs" makes the reader think about something as dramatic as an inversion of efficacy, an agonist becoming an antagonist, or at least the introduction of signaling bias, whereas in reality, the authors established that pyroglutamination reduces the potency of the peptide at one receptor but increases it at the other receptor. The use of PTMs and proteolytic processing is a broadly utilized mechanism for controlling GPCR peptide selectivity. The effects of pyroglutamination on the potency of MMG2-DPb towards its two Aplysia receptors very well align with this mechanism and should be described as such. Other examples of sentences that are similarly misleading: "... the same ligand, ..., produces opposite functional outcomes: pQ suppresses ApPRXa-R1 activation while enhancing ApPRXa-R2 activation" (in reality, both receptors are activated and the functional outcomes are the same, just achieved with different potency), "A single N-terminal lactam enables bidirectional GPCR subtype tuning...", "This bidirectional, subtype-specific effect of pQ is unprecedented in neuropeptide signaling..." (not bidirectional and not as unprecedented as the authors make it sound), etc.

(3) Overall, what the authors present as a new "indirect PTM distal steering" mechanism is really not supported by the data. The described systems fit the classical "lock-key" and "induced fit" paradigms rather than challenging them. I recommend the authors revisit their modeling approaches and model-guided interpretations of the biochemical/pharmacological data. Importantly, I do not think such revision would undermine the key strengths of the paper (listed above in Strengths). Based on experimental data alone, this is a very strong and interesting study and with more rigorous modeling and adequate interpretations, it can be made exceptional.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors used the ABCD study to understand how changes in body fat composition affect brain development during the teenage years. They found that the key determinants of changes in the brain were changes in fat accumulation rather than just baseline measures. Less importantly, but still interesting, they reaffirmed that more complex measures, such as body roundness index, better captured the impact of obesity than body mass index.

Strengths:

This study uses an excellent open access dataset, asks an important set of questions, and is executed with diligence for proper methodology. The finding that trajectories in adiposity matter more than baseline differences is important both for understanding how the brain adapts to body composition changes and has potential impact for public health interventions.

Weaknesses:

While I am overall impressed with the study, there are a few weaknesses I would like to see the authors address:

(1) There is no reason to limit analyses to the cerebral cortex. Body composition changes are as likely to affect the subcortex or cerebellum as the neocortex. In some cases, like the hypothalamus, potentially even more likely.

(2) Confounders should be examined in more detail. How are adiposity changes mediated by (for example) socio-economic status?

(3) I'd like to see more rationale for excluding 483 kids with extreme adiposity indicators. Is it that they are untrustworthy entries? Otherwise, they could be particularly informative.

(4) Are there any blood measures of glucose/insulin available?

(5) Some of the figures could benefit from having raw data included rather than just showing the fitted trend lines.

(6) Are there any alternate explanations for baseline differences? Particular examples that came to mind are the influence that maternal adiposity has on offspring brain development.

Reviewer #2 (Public review):

This manuscript addresses an important public health question in adolescents using a large longitudinal ABCD cohort. It is generally well organized and presents a compelling story linking central adiposity, brain development, and cognition. The authors use baseline and 4-year follow-up data from the ABCD Study (N = 8,519 baseline; N = 1,873 longitudinal, the use of 4-year follow-up only should be justified) to examine how adiposity relates to cognitive performance and cortical structure in early adolescence. Major findings include: (1) central adiposity indices (BRI, WHtR) show stronger cross-sectional associations with cognition than BMI, partially mediated by frontotemporal cortical morphology; (2) the rate of adiposity accrual, rather than static adiposity at either timepoint, predicts follow-up cognition and altered (attenuated) cortical thinning; and (3) among overweight/obese adolescents, central fat reduction is accompanied by accelerated cortical thinning and catch-up in inhibitory control.

The use of large longitudinal data from ABCD is considered a strength as most prior neuroimaging work is cross-sectional. The focus on adiposity change velocity within adolescence is considered novel over single-timepoint designs, and the comparison of central-fat indices (BRI/WHtR) against BMI in a neurodevelopmental context is important given growing interest in these markers in cardiometabolic research. The subgroup observation that fat reduction may be accompanied by normalization of both cortical trajectories and inhibitory control is potentially clinically meaningful, suggesting reversibility rather than fixed deficit, and would be of broad interest if it withstands more rigorous analysis.

However, several major issues were identified. For example, the strength of the causal language is not supported by the design, the headline comparison between adiposity indices rests on coefficients that are described as standardized but evidently are not, and several analytic and reporting issues (attrition and selection, family clustering, regression to the mean in the subgroup analysis, internal inconsistencies in reported p values) must be resolved before the conclusions can be considered established.

Major Concerns

(1) ABCD provides more follow-ups and should be included. Also, there is a severe longitudinal attrition (8519 vs 1873) that needs to be addressed. No comparison of completers versus non-completers is provided. The cohort description of having 78.5% White seems to be wrong, suggesting either a coding error in the race variable or strong selection introduced by the exclusions. The exclusion of 483 participants for "extreme adiposity indicator values" is especially concerning in a study of obesity and should be justified with explicit criteria in the main text, with sensitivity analyses retaining these participants where possible.

(2) Adiposity is heavily influenced by socio-economic status, which itself contributes heavily to cognition and mental health as well. Many ABCD studies have reported this. Another important factor contributing to adiposity is sleep, which itself can contribute significantly to cognition and mental health. Many ABCD-based sleep studies have been published and can be reviewed.

(3) The manuscript repeatedly uses causal language that the observational design cannot support (e.g., "longitudinal fat accumulation ... drives cortical alteration," "fat reduction activated adaptive neural change," "neuroprotective management"). The cited literature (Likhitweerawong et al., 2022) is explicitly bidirectional: poor inhibitory control may promote weight gain rather than the reverse. The baseline mediation analysis is particularly problematic because exposure, mediator, and outcome were measured concurrently, so the temporal ordering required for mediation is assumed rather than established. Causal claims should be tempered throughout. Similarly, mediation analyses should be interpreted cautiously as statistical rather than causal.

(4) zBMI, WC, BRI, and WHtR are highly intercorrelated, as are follow-up adiposity and delta-adiposity (Table 3). Entering them simultaneously invites unstable estimates and sign flips. Please report pairwise correlations and variance inflation factors, and demonstrate that the key conclusions are robust.

(5) Subgroup analysis: regression to the mean, group labels, and internal inconsistencies. (a) Stratifying on delta-BRI >= 0 enriches the "decreasing" group for high baseline values, so the observed cognitive "catch-up" and accelerated thinning may partly reflect regression to the mean; the percentile-based sensitivity analysis mitigates but does not resolve this. Group comparisons should adjust for baseline BRI and baseline cognition. (b) zBMI >= 1 corresponds to overweight by WHO criteria, not obesity; labelling this group "obese adolescents" throughout (including the Abstract) is inaccurate. (c) The Abstract claims a Flanker slope difference of p < 0.05, but the Results report p = 0.058 versus controls (described, incorrectly, as significant) and p = 0.021 only versus the increasing-BRI group; these statements must be reconciled. (d) It is unclear whether subgroup p values were FDR-corrected and how t-tests/Wilcoxon tests produced "adjusted" p values; if covariate adjustment was intended, regression models are required.

Tables 2-4 mention that beta values are standardized, yet the magnitudes are clearly scale-dependent (e.g., WHtR beta = -7.5 vs. zBMI beta = -0.42 in Table 2; WHtR delta-beta = -780 in Table 3). This undermines the central claim that BRI/WHtR "outperform" BMI, since predictors cannot be compared on unstandardized coefficients. Please either truly standardize all predictors and outcomes, or compare indices formally (e.g., delta-R2, AIC/BIC, or non-nested model comparison tests), and report 95% confidence intervals for all estimates.

(6) Underspecified mixed models and family clustering. The random-effects structure of the LME models is never stated. ABCD includes twins and siblings, so family nesting must be modelled (and the treatment of site - fixed covariate versus random effect - clarified). As written, the analyses may be anti-conservative. Please provide full model specifications and confidence intervals.

(7) Interpretation of accelerated cortical thinning is overly strong. The manuscript equates faster thinning with better maturation and slower thinning with delay. This reading is contested: apparent cortical thinning also reflects myelination-related signal changes, and thickness-cognition associations are age- and region-dependent. Moreover, the present null finding for baseline adiposity contradicts Kaltenhauser et al. (2023), who reported that baseline adiposity attenuates thinning in ABCD; the discrepancy is cited but never reconciled and deserves direct discussion (differences in sample, covariates, or modelling) Unclear units and implausible mediation estimates. Table 1 gives delta-WC = 0.264, interpretable only if delta is per month (age in months), yet the text describes "annualized" change. Units for all delta variables must be stated explicitly and used consistently. Mediation effects reported as wide ranges (e.g., ACME = -29.95 to -0.18; "ACME = -0.1.17" is a typographical error) are uninterpretable and, at face value, implausibly large relative to the cognitive score scale; please report per-indicator ACMEs with confidence intervals and proportion mediated. Not sure how the ranges such as "beta = -0.29 to -0.00" cited as significant effects are informative.

(8) Pubertal confounding. Only baseline pubertal category is adjusted for, but pubertal tempo over the follow-up window confounds both adiposity change and cortical development. This should be adjusted for change in pubertal stage or acknowledged as a substantive limitation. Puberty interactions and sex-specific analysis should be performed too.

(9) Effect sizes should be discussed.

(10) Inclusion of both baseline adiposity and adiposity change in longitudinal models should be justified.

(11) Would there be nonlinear age/puberty effects?

Reviewer #1 (Public review):

Summary:

The authors previously generated two cell-layer-specific mutants of petunia for the petal identity gene PhDEF. In this study, they profiled differential gene expression in those mutants through single-cell RNA sequencing (scRNA-seq). They found that more genes are highly and specifically expressed in the epidermal cell layer than in mesophyll cells. In addition, they identified cell-layer-specific and -aspecific PhDEF target genes. Using the extensive single-cell transcriptome and layer-specific target identification, the authors concluded that different cell identities affect homeotic regulator PhDEF, thereby influencing transcriptional regulation.

Major comments from first round of review:

This presented work provides comprehensive evidence, that pre-existing cell layer identity (epidermis and mesophyll) modulate transcriptional output of homeotic transcription factor, PhDEF.

However, a disconnection between PhDEF bindings to genome and transcriptional output undermines the robustness of their conclusion although some binding loci were shown to be correlated with DEG. This may indicate the chromatin state, the existence of interacting partners, and the non-productive binding of PhDEF, suggesting that PhDEF binding alone is not sufficient to predict transcriptional outcomes and additional regulatory mechanisms that shape gene expression in addition to the layer-specific regulatory mechanisms. This disconnection may also be due to the developmental timing. Indeed, it appears authors used different flower stages for ChIP-seq and scRNA-sequencing. In fully differentiated organs, PhDEF binding itself may be no longer transcriptionally productive, and differential gene expression results primarily from the pre-established cell identity rather than directly from the homeotic regulation of PhDEF. Therefore, the main question the authors asked-how homeotic identity works with cell-layer identity and how the homeotic gene, PhDEF, acts in mature organs-was not clearly explained by this study.

In Figure 2, the use of the term "target" is potentially misleading. It sounds like direct target genes (direct binding and differential expression) for PhDEF, but it refers only to DEGs.

Lines 496-497: When the authors state, "~ demonstrates for the first time that the regulatory function of homeotic factor is influenced by cell layer identity," it sounds overstated, as prior studies have shown that pre-existing tissue or cell identity can shape transcriptional activity and developmental output.

Significance:

This study is well-designed and technically sound. They utilize single-cell transcriptomics and ChIP-seq by using genetically well-defined genetic materials and layer-specific PhDEF deletion mutants. The analysis showed where PhDEF binds to genomic loci and which genes are differentially expressed in petal epidermis and mesophyll, providing evidence of cell-layer-specific function of homeotic gene in mature organs. Although certain mechanistic aspects were not elucidated, the data from the extensive genome-wide study contributed to drawing their conclusions.

Advances: This research goes beyond classical models of floral organ identity by showing that homeotic gene function is not uniform in the same floral organ. It represents a conceptual advance in our understanding by integrating cell layer identity into the framework of homeotic gene regulation.

Audience: This study will be of broad interest to scientists who study transcription networks, cell and organ identity in the context of plant development.

My field of expertise: Transcriptional regulation by transcription factor, epigenetic regulation of gene expression, plant development.

Comments on latest version:

Thank you for sharing the assessment. I am happy with the proposed eLife assessment. I do not have any further amendments to my review.

Reviewer #2 (Public review):

Summary:

This study from Cavallini-Speisser et al. cleverly leverages a tissue layer-specific mutant, single cell and bulk RNA-sequencing, and ChIP-sequencing to decipher tissue layer-specific regulation of petal development in petunia by the PhDEF transcription factor. The authors find common and unique targets of PhDEF between the epidermis and mesophyll and conclude that the activity of transcription factors like PhDEF are influenced by the pre-existing environment in the cell they are expressed in. Understanding when and how a given transcription factor drives expression of unique target genes in various contexts is an important aspect of developmental biology that can be elusive outside of highly tractable model systems. As such, I think this study is of high value and has strong potential to expand our understanding of how developmental specificity is mediated by commonly employed transcriptional regulators. However, I think there are some issues with possible over-interpretation and some places where documentation of experimental design and data quality control are lacking. I elaborate on these concerns below.

Major Comments From Review at Review Commons:

(1) Line 155: Assigning mesophyll clusters by default without any positive marker genes strikes me as problematic, especially as much of the analysis rests on comparing the transcriptomes of epidermis and mesophyll cells. Can the authors perhaps leverage published scRNA-seq datasets to find potential mesophyll markers, even homologs from other species, to improve confidence in the cluster assignment?

(3) Line 228: Through the description and interpretation of the ChIP-seq dataset, the authors use the fact that peaks are more abundant and bigger in the epidermis to conclude that binding of PhDEF is "stronger" in the epidermis. This implies a difference in physical interaction between the TF and the DNA that I don't think can be concluded from the data presented. This could be confounded by biology; if expression of PhDEF is more heterogeneous in the mesophyll than in the epidermis, the peaks from that tissue will be averaged out and appear smaller when in fact the binding is the same strength. This could also be a technical artifact if the ChIP was less efficient in one sample versus another. This conclusion requires reinterpretation. The authors have the power to address this at least partially with the scRNA-seq by measuring PhDEF heterogeneity. I believe assessing ChIP efficiency would have required a spike in control, but perhaps there is a computational way to address this. It is important to discuss these confounding factors in the text.

(3) Line 376: The authors risk overinterpreting a lack of differential gene expression detection in their analysis of PhDEF binding profiles. This can be affected by how deeply a library was sequenced or how many cells were analyzed per cell type. A gene might not be found to be DE if low depth or few cells resulted in noise or dropout. Lack of detection does not mean lack of differential regulation so the biological relevance of this portion of the analysis should be interpreted with caution.

(4) Line 476: The authors state there is a mismatch in developmental timing between the RNAseq and ChIP datasets. Why is this? This is mentioned briefly in the Discussion, but has the potential to be majorly confounding to the joint interpretation of the ChIP and RNAseq datasets. This experimental design choice should be justified more thoroughly and a consideration of the limitations it brings to data interpretation should be more prominent in the text.

Significance:

Strengths: The authors employ a unique and powerful mutant system to explore a fundamental developmental biology question. In addition, the datasets generated will likely be useful to other researchers working in petunia or flower development.

Limitations: While the mutant system employed here is a creative way to get at tissue-layer specific transcription factor activity, the ChIP samples still include heterogeneous cell types, which may impact the findings presented here.

Advance: This study uses a unique system to test the function of a transcription factor in distinct cell types. As stated above, understanding when and how a given transcription factor drives expression of unique target genes in various contexts is an important aspect of developmental biology.

Audience: I believe this work will be of primary interest to the plant development, single cell, and chromatin biology communities. These are specialized, basic research communities.

Reviewer Expertise: I am a plant developmental biologist who works with multiple modes of cell-type-specific NGS datasets including bulk and single cell RNAseq and ChIPseq among others.

Comments on latest version:

I find the authors' response to my review to be comprehensive and I think the revision looks solid. The eLife assessment works for me.

Reviewer #3 (Public review):

Summary:

This study addresses a fundamental but underexplored aspect of homeotic gene function: how regulators of cell identity act during late stages of organ development. The authors take advantage of layer-specific mutants of the MADS-box gene PhDEF in Petunia hybrida to dissect the roles of this floral identity regulator in the epidermis and mesophyll. By combining single-cell RNA sequencing with ChIP-seq analyses in wild-type and mutant chimeric petals, the work demonstrates that, although PhDEF is expressed at comparable levels in both petal layers, it binds to and regulates a substantially larger and more layer-enriched set of genes in the epidermis than in the mesophyll. The identification of both layer-specific and shared PhDEF binding sites supports a model in which pre-existing layer identity modulates the regulatory output of homeotic transcription factors.

Major comments from review at Review Commons:

Dissecting PhDEF binding preferences in the epidermis versus the mesophyll using the star and wico mutants is a clever and powerful approach. However, conclusions involving cell identity should be drawn with caution for two reasons. First, cell identities appear to be altered in the mutants: scRNA-seq data suggest that even cells assigned to the same cluster can be molecularly distinct across genotypes. For example, the transcriptomes of wild-type epidermis and mesophyll are highly similar (Pearson correlation R = 0.94), yet both show lower correlation with epidermal cells from star or wico petals. These results raise questions such as are the cells identified as epidermal cells really strictly epidermal in the mutants? Do you need to take into consideration cell composition of the mutants when you do differential expression analysis? Second, PhDEF is expressed in both epidermal and mesophyll clusters in all genotypes, albeit at different levels and in fewer cells in the mutants. As a result, the ChIP-seq profiles should be interpreted as cell type-enriched rather than cell type-specific. And there are a few things that need clarification:

a) Protoplasting and tissue dissection analyses suggest that mesophyll cells constitute more than 80% of the cells in wild-type petals, whereas the scRNA-seq data indicate a substantially lower proportion. Could this discrepancy reflect technical biases in cell recovery or capture efficiency, or issues related to cell identity assignment during clustering and annotation? Notably, the scRNA-seq data from star and wico petals show mesophyll proportions close to 80%. Is this difference due to an increased abundance of mesophyll cells in the mutants, or could it instead reflect differences in transcriptomic separability? In wild-type petals, the epidermal and mesophyll transcriptomes are highly correlated and express similar numbers of genes, with epidermal cells distinguished mainly by higher expression of a subset of genes. This raises the possibility that mesophyll cells in the wild type occupy a more plastic or less differentiated transcriptional state and may therefore be misclassified as epidermal cells, whereas disruption of regulatory mechanisms in the mutants enhances transcriptional divergence and alters cell clustering outcomes.

b) Cluster 0 appears to show internal heterogeneity, as the expression patterns of KCS3 and LLE2 are largely mutually exclusive. Do these patterns reflect the presence of distinct epidermal cell types within the limb that are currently grouped into a single cluster?

c) Clusters 0 and 7 both exhibit high expression of pigmentation genes, while cluster 7 additionally shows strong enrichment for cell division genes. Are cell cycle genes the primary features distinguishing these two clusters? If cell cycle effects are regressed out, would cluster 7 merge with cluster 0, potentially yielding a more continuous cell state trajectory and helping to resolve the pattern noted in point (b)?

d) Pearson correlation is largely driven by highly expressed genes and may therefore be insensitive to changes in cell identity markers. The conclusions that the less clear separation of mesophyll and epidermal cells in star is due to altered cell identity would be more convincing if supported by independent validation, such as in situ hybridization or reporter analyses, to directly visualize molecular alterations in the relevant cell types when comparing wild-type and mutant tissues.

Significance:

Overall, this work significantly advances our understanding of late homeotic gene function. It establishes compelling evidence for how developmental context constrains transcription factor activity and offers broadly relevant insights for studies of organ patterning. The combination of genetic mosaics with single-cell and chromatin-level analyses represents a powerful and generalizable strategy that will be of interest to both plant developmental biologists and researchers studying transcriptional regulation.

My expertise: single cell genomics, chromatin biology and plant development.

Comments on latest version:

The authors have addressed my concerns and questions. And I agree with your assessment of "valuable" for significance and "solid" for strength of evidence.

Reviewer #2 (Public review):

The authors investigate the contribution of dorsal CA1 hippocampal dysfunction to cognitive impairments in the Cntnap2 knockout mouse model of autism spectrum disorder. Using two complementary behavioral paradigms, trace fear conditioning and a relational/declarative memory radial maze task, together with fiber photometry, optogenetic manipulation, and cFos mapping, they examine whether altered CA1 function contributes to deficits in temporal binding and memory flexibility.

A major strength of the study is the combination of behavioral, recording, and causal manipulation approaches. The trace fear conditioning experiments show that Cntnap2 knockout mice retain associations across shorter temporal intervals but fail when the temporal gap is increased to 40 s. Fiber photometry reveals reduced dorsal CA1 activity under these conditions, and, importantly, optogenetic activation of dorsal CA1 pyramidal neurons during the trace interval rescues subsequent memory performance. This provides compelling evidence for a causal contribution of dorsal CA1 activity to the temporal binding deficit observed in this model.

The radial maze experiments extend these findings to a more complex form of relational/declarative memory. Cntnap2 knockout mice are able to acquire the task but show impaired flexibility when previously learned spatial relations must be recombined. Their behavior is also characterized by greater lateralization, consistent with increased reliance on an egocentric rather than an allocentric spatial strategy. The revised manuscript now explains more clearly how this paradigm distinguishes relational/declarative from procedural learning strategies and how the 20-s inter-trial interval introduces a temporal binding requirement. This clarification substantially improves the conceptual link between the two behavioral paradigms.

The accompanying cFos analyses further show reduced recruitment of hippocampal regions and increased engagement of striatal and prefrontal regions in Cntnap2 knockout mice. These findings are consistent with altered recruitment of memory systems accompanying the behavioral strategy shift. However, unlike the optogenetic experiments in the trace fear conditioning paradigm, the cFos measurements remain correlational. They therefore support, but do not by themselves establish, a causal reorganization from hippocampal-dependent declarative memory toward striatum-dependent procedural learning. The authors have appropriately moderated this interpretation in much of the revised manuscript, although some statements, particularly in the Abstract, could still be phrased more cautiously.

The revised manuscript also addresses the potential influence of the well-described hyperactivity of Cntnap2 knockout mice. The distinction between hyperactivity and impulsive-like behavior is now more explicitly discussed. In the trace fear conditioning experiments, comparable resting and freezing behavior under control conditions argues against locomotor activity accounting for the memory phenotype. In the radial maze, shorter decision latencies combined with longer post-choice running times are more consistent with reduced deliberation than with a simple increase in locomotor activity. Importantly, the authors acknowledge that the task was not specifically designed to measure impulsivity.

Overall, the revision has strengthened the manuscript and addressed my main concerns. The principal conclusion-that reduced dorsal CA1 activity contributes causally to impaired temporal binding in Cntnap2 knockout mice-is well supported by the converging behavioral, photometric, and optogenetic evidence. The broader proposal that hippocampal dysfunction is accompanied by greater reliance on egocentric/striatal learning strategies is also supported by the behavioral and cFos data, provided that it is interpreted as an association rather than a demonstrated causal reorganization of memory systems.

The study makes a valuable contribution by linking hippocampal circuit dysfunction to specific components of declarative memory in a widely used model of autism. More broadly, the combination of temporal binding and memory flexibility paradigms provides a useful framework for investigating how hippocampal dysfunction may alter the organization and flexible expression of memory in neurodevelopmental disorders.

Reviewer #3 (Public review):

Summary:

The manuscript evaluated behavioral phenotypes in the Cntnap2 knockout mouse using two behavioral paradigms: trace fear conditioning and a radial maze task. The trace fear conditioning training is normal, but memory generalization is impaired. The inflexibility is suggested to be related to low activity in dCA1 neurons, which can be rescued by ChR2. The radial maze task data suggested a similar conclusion. Brain-wide cFos mapping indicated impairments in the Cntnap2 knockout mouse. The brain-wide cFos mapping does not show direct correlations with Cntnap2, limiting the interpretation of these data in the context of this paper.

Strengths:

The behavior data are solid.

Comment on revised version.

The authors have addressed all my concerns.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers.]

Summary:

In this study, the authors investigate whether glycogen phosphorylase represents a molecular target of benzoylphenylurea insecticides and evaluate the physiological consequences of suppressing glycogen phosphorylase activity in the diamondback moth Plutella xylostella. The authors combine recombinant protein biochemistry, enzyme inhibition assays, RNA interference, structural modelling, metabolite profiling, gene expression analyses, and physiological measurements to determine whether diflubenzuron directly inhibits glycogen phosphorylase and whether suppression of this enzyme is sufficient to impair insect development. Based on these experiments, the authors conclude that diflubenzuron does not directly inhibit glycogen phosphorylase and that insects tolerate substantial suppression of this enzyme through compensatory metabolic responses.

Strengths:

This study addresses an important question in insect toxicology by systematically evaluating glycogen phosphorylase as a potential insecticidal target. The authors combine complementary biochemical, molecular, physiological, and structural approaches, including recombinant enzyme characterization, inhibitor assays, RNA interference, metabolite profiling, structural modelling, and measurements of fitness-related traits. This integrative approach provides a comprehensive evaluation of the biological consequences of glycogen phosphorylase suppression. In particular, the biochemical evidence that diflubenzuron does not inhibit glycogen phosphorylase, together with the observation that strong suppression of glycogen phosphorylase produces only transient physiological effects without measurable impacts on development or reproduction, provides strong support for the conclusion that glycogen phosphorylase is unlikely to represent an effective standalone insecticidal target.

Weaknesses:

The main limitation concerns the proposed mechanism underlying metabolic compensation. The observed increases in gluconeogenic gene expression, changes in metabolite abundance, and reductions in total protein are consistent with activation of compensatory metabolism, but are insufficient to directly demonstrate increased gluconeogenic flux or establish that amino acid-derived carbon is incorporated into newly synthesized glucose. Similarly, although the analyses of glycogen-associated enzymes strengthen the discussion of alternative metabolic pathways, changes in gene expression alone do not demonstrate that these pathways contribute to glycogen utilization in vivo.

Some mechanistic interpretations therefore extend beyond the data presented. For example, decreases in total protein are interpreted as evidence of protein catabolism fuelling gluconeogenesis, yet they do not directly demonstrate amino acid mobilization or incorporation into glucose. Likewise, increased expression of gluconeogenic genes is interpreted as evidence of increased pathway activity, although transcriptional changes do not necessarily reflect metabolic flux. Finally, the absence of major developmental defects following glycogen phosphorylase suppression is attributed primarily to metabolic compensation, but an alternative explanation is not fully considered. Such explanation could be that glycogen phosphorylase is not rate-limiting for glucose homeostasis under the nutrient-rich experimental conditions, where dietary carbohydrates are continuously available. Consequently, the proposed compensatory mechanism remains plausible and well supported by indirect evidence, but several aspects would benefit from more cautious interpretation.

Overall, the authors successfully achieve their primary objective of evaluating glycogen phosphorylase as a candidate insecticidal target. The study provides useful biochemical and physiological evidence that this enzyme is unlikely to represent an effective target for insecticide development in P. xylostella, while highlighting the importance of metabolic plasticity when assessing metabolic targets. The experimental approaches and datasets presented here should be valuable to researchers studying insect metabolism, insecticide mode of action, and target validation, although the precise mechanisms underlying the proposed metabolic compensation remain an important subject for future investigation.

Reviewer #3 (Public review):

Summary:

Large Language Models have revolutionized Artificial Intelligence and can now match or surpass human language abilities on many tasks. This has fueled interest in cognitive neuroscience in exposing representational similarities between Language Models and brain recordings of language comprehension. The current study breaks from this mold by: (1) Systematically identifying sentence structures for which brain and Large Language Model representations diverge. (2) Using models structured by semantic roles to help account for divergences. As such the study may now fuel interest in characterizing how Large Language Models and brain representations differ, which may prompt new more brain like language models.

Strengths:

(1) This study challenges a literature trend that has touted similarities between Transformer models and human cognition based on representational correlations with brain activity. This challenge is substantiated by identifying sentences for which brain and model representations of sentences diverge.

(2) This study conducts a rigorous pre-registered analysis of a comprehensive selection of the state-of-the-art Large Language Models, on a controlled sentence comprehension fMRI dataset. The analysis is conducted within a Representation Similarity framework to support similarity comparisons between graph structures and brain activity without needing to vectorize graphs. Transformer language models are predicted and shown to diverge from brain representations on subsets of sentences with similar word-level content but different sentence structures.

(3) The study introduces a 7T fMRI sentence comprehension dataset and accompanying human sentence similarity ratings which may be a fruitful resource for developing more human-like language models. Unlike other model-based sentence datasets, the relation between grammatical structure and word-level content is controlled, and subsets of sentences for which models and brains diverge are identified.

Weaknesses:

(1) The interpretation of findings is nuanced. Although Transformers underperform as brain models on the critical subsets of controlled sentences, a Transformer outperforms all other models when evaluated on the union of all sentences when both word-level content and structure vary. Transformers also yield equivalent or better models of human behavioral data. Thus, although Transformers have demonstrable flaws as human models which are pinpointed here, when tested on all sentences (some) Transformers are more human-like than the other models considered.

(2) There may be confounds between the critical sentence structure manipulations and visual processing. This is inconvenient because activation in brain regions that process semantics tends to partially correlate with low-level representations of sentence surface features encoded in visual cortex. Although the study commendably controls for confounds associated with sentence length, correlations with key sentence structure models are most salient in visual cortex and diminish in other brain networks when V1-V4 activation is controlled for.

(3) Sentence similarity computations are emphasized as the basis for unifying comparative analyses of graph structures and vector data. A strength of this approach is that correlation is not always the ideal similarity metric. However, a weakness is that similarity computations are not unified across models. This has practical consequences because different similarity metrics applied to the same model produce positive or negative correlations with brain data.

Comments on revised version.

Thanks again for the responses. In particular, the new sentence-length control is helpful for interpreting the anomalous outcomes from the DIEM analysis, and the amendments to the discussion are appreciated.

Joint Public Review:

Summary:

Brain sizes vary by orders of magnitude between different organisms, while neuronal circuits maintain essential computational functions. Castro and Cardona explore invariant features across animal species that lend themselves as fundamental constraints on scaling mechanisms. The authors leverage a number of existing connectomics datasets for their study, from which they extract morphologies and synaptic connections for numerous neurons, resulting in a set of neuronal features such as neuron lengths and synapse counts.

Their core result is a rather stable synapse density of 1 synapse per 1 µm of dendritic path length across neurons from different datasets, in line with prior results in mouse (Turner et al., 2022) and human (Lomba et al., 2022). The authors show that this finding also holds for the selected neurons in Drosophila (adult and larva) and zebrafish larva, and further aim to explore mechanisms creating this density and its consequences on neuronal excitability. They show that their data is in agreement with previously reported scaling rules of dendritic arborization (Cuntz et al., 2012). Through exploration of synapse sizes and dendrite radii, the authors identify a compensatory effect of dendrite radius for fluctuations of synaptic densities that can provide voltage response stabilities.

Overall, this study is an addition to the burgeoning field of comparative connectomics, and as such, the presented analyses are important methodological contributions. The conclusions presented here are, however, too general. The analyzed datasets are reduced to a few cell types due to technical challenges, and cell type identities are ignored even though they have large ramifications for the analyses presented (e.g., E vs I for stability analyses, and cell type correlations with synapse sizes).

Strengths:

(1) Novelty.

The authors provide new ways to compare neuronal measurements between brains and species and how to interpret the results. In particular, their conclusions for normalization of connection strength (by total number of synapses onto a neuron) are an important contribution to the analysis of neuronal circuits, especially in Drosophila. The finding of the density is important, but similar numbers have been reported by prior studies of some of the same datasets (Loomba, Turner).

(2) Wiring optimization.

The presented study is an important validation of the scaling law across organisms and cell types.

(3) Scale.

The authors collected neurons from several connectomics datasets from different organisms that were created by different labs, requiring standardizing reconstructions and extracting features across a large number of neurons

Weaknesses:

(1) Data preparation and presentation. The authors describe how the data was processed and manually corrected in the methods, but at no point other than in Figure S4 (which shows a single neuron from afar) is an actual neuron skeleton shown to convince the reader that this was done well. The resolution of the skeleton has important ramifications for the measured path lengths. Further, it is not clear how spine heads, very short branches, and twigs were handled. Tracing out spine heads could double the path length, similar for twigs. How these were handled should be discussed and justified. Radius measurements were taken at the trunk of the neuron, but for synapses on spines, the spine size (especially neck (Harnett et al., 2012)) is critical for estimating input resistance. This should at least be discussed and justified. Further, it is not clear how synapses onto the soma were handled. What was chosen as the radius there?

(2) Data filtering. The authors excluded substantial numbers of neurons from the analyzed datasets, leaving only cells from a few cell types. However, the manuscript gives the impression in many places that the analyses were run across the entirety of those datasets. Given the number of neurons used (e.g. only 60 from the Drosophila adult!), it would be much more prudent to talk about the specific cell types and not the datasets/animals. Further, the way the included neurons were chosen is likely to introduce a bias. E.g., in Drosophila datasets, neurons with more synapses on the backbone rather than twigs automatically have higher postsynaptic completion ratios. Overall, given the number of neurons, the results cannot be easily generalized even for the datasets used here.

(3) Ignoring cell types. Especially for the mammalian datasets, presynaptic cell type identity is correlated with synapse size and location. Ignoring this information removes important context from the analysis. For instance, inhibitory synapses are more prevalent close to the soma, etc.. This clearly impacts the analyses presented, yet is ignored and not discussed. Further, the sign of the synapses and, in particular, the balance of E vs I synapses, is important for the analysis of voltage response stability.

(4) Wiring optimization rule. The presented analysis convincingly confirms the scaling law from Cuntz, et al. (Figure 3b). However, taken together with the prior finding of the 1 synapse / 1 µm density along dendrites, the sensitivity analysis appears to be circular (Fig. 3c). Since the inputs are length and synapse count, the same that were put into the density analysis, the result rather reconfirms the scaling law.

(5) Synapse size and PSD area. Two measurements for the synapses were used for the MICrONS datasets, but in some places, this is confusing. Why were the volumetric synapse sizes not fully replaced with the PSD measurements, as these are likely a superior measurement of the "size" of the synapse? Annotations of the PSD should also be shown somewhere to convince the reader of their quality.

(6) Zebrafish dataset. The validity of the corrections used for the zebrafish dataset is difficult to judge for someone not familiar with that dataset. It appears that there are substantial problems in the reconstruction of the dendritic tips. Other datasets were ignored for seemingly similar reasons. Why was this one kept? The correction factor introduces an arbitrariness to the analysis, and it directly affects the core result of this study.

Reviewer #1 (Public review):

The mitochondrial intermembrane space (IMS) is a compartment under constant proteostasis stress. During the development of multicellularity, the IMS acquired the AAA+ ATPase CLPB, a disaggregase whose absence from cells results in aggregate formation in the IMS and whose mutation in humans leads to rare but severe human diseases.

The precise molecular function of CLPB in the human IMS remains unresolved and is addressed in this study, in particular the crosstalk with the IMS protein HAX1, which is a prominent interaction partner of CLPB.

The authors find HAX1 to serve as an activating cofactor of CLPB as a disaggregase and refoldase in a purified system. This is well in line with the similar phenotypes of HAX1 and CLPB loss, and is an exciting finding as it not only assigns a direct role for HAX1 in the IMS but also yields the potential for CLPB activity regulation by regulating amounts of HAX1. The experimental support for this finding is strong and acquired by a combination of different and carefully executed in vitro enzyme activity assays.

One potential weakness of this study is that it does not consider recently identified players in the CLPB-HAX1 axis, FAM136A (now called TIMCC) and MIA40, that might additionally modulate/regulate CLPB activity. This might constitute an exciting route for future research.

Reviewer #2 (Public review):

The authors sought to determine the mechanistic relationship between the mitochondrial intermembrane space proteins CLPB and HAX1, whose genetic, proteomic, and disease associations have long suggested a functional partnership. Using biochemical reconstitution with purified proteins, they provide evidence that HAX1, an intrinsically disordered protein, acts as a direct activating cofactor of CLPB, stimulating its oligomerisation, ATPase activity, disaggregase activity, and refoldase activity. They further identify a region of HAX1 required for CLPB interaction and propose a model in which HAX1 promotes formation of a distinct active CLPB assembly.

A major strength of the work is the comprehensive biochemical approach. The authors combine activity assays, mutational analysis, interaction studies, and oligomerisation measurements to address the central question from multiple angles. The data provide convincing evidence that HAX1 is not simply a client of CLPB but instead functions as a positive regulator.

The principal weakness concerns the mechanistic model of oligomer remodelling. While the SEC and stoichiometric analyses are consistent with the formation of a smaller HAX1-bound CLPB complex, the proposed transition from a dodecameric to a hexameric assembly is inferred rather than directly demonstrated. Additional structural or biophysical evidence would strengthen this aspect of the study.

Overall, the authors largely achieve their aims. The evidence strongly supports the conclusion that HAX1 is a direct stimulatory cofactor of CLPB and provides an important mechanistic framework linking two proteins associated with overlapping mitochondrial and hematological disease phenotypes. Some aspects of the proposed oligomeric remodeling mechanism should be interpreted more cautiously, as they remain supported primarily by indirect evidence.

Reviewer #1 (Public review):

Objectives of the study and impact of the work

The authors of this article primarily aim to reconstruct the evolutionary history of the insect odorant receptor (OR) family, which is responsible for the detection of odorant signals by olfactory neurons. Due to the lack of phylogenetic signal present in the sequences of this multigene family, which evolves very rapidly, phylogenetic analyses have so far never made it possible to precisely retrace how ORs diversified prior to the appearance of present-day insect orders, and what the drivers of this diversification were. For example, one may suspect that the adaptation of ORs to odors emitted by plants constituted a critical step in insect evolution during the "angiosperm terrestrial revolution," which occurred at the end of the Cretaceous, but nothing currently allows this to be asserted.

There are very nice examples, notably in drosophilids, derived from comparisons between closely related species and documenting mechanisms of OR adaptation to certain signals. However, what the authors attempt to do in this work is to produce a macroevolutionary analysis at the scale of insects as a whole, based almost exclusively on bioinformatic analyses. To do this, they annotated OR genes in about one hundred insect species and developed pipelines for analyzing sequence similarity, structural similarity and functional similarity, the latter being estimated through a molecular docking approach. An important element in the evolution of insect ORs is the appearance of a unique co-receptor, called Orco, which appears to be an OR that has lost the ability to bind odorants. In addition to the large-scale bioinformatic analysis, the authors also aim to explore more specifically the factors that favored the emergence of Orco and the selective advantage conferred by the existence of OR-Orco complexes.

Given the importance of odorant receptors in insect biology and in their adaptation to different environments and lifestyles, retracing their evolutionary history is indeed a major question in evolutionary biology. In principle, this type of work therefore has the potential to become a reference in the field and to provide a basis for significant scientific advances.

Major strengths and weaknesses

The sampling chosen for collecting OR sequences is very impressive, with more than 100 insect families represented, covering most of the major orders. This sampling appears appropriate for the question being addressed. The analysis pipeline used to collect the sequences makes sense, relying on homology-based annotation tools coupled with a structure-based filter. Nevertheless, one can note aberrant numbers of ORs for certain species (much lower than reality). A lower number of OR genes is somewhat expected, as the authors chose to apply a fairly stringent filter on sequence quality (based on predicted 3D structure), which reduces the number from 14,000 to 9,000. This choice seems logical given the subsequent use of these data, but it inevitably leads to data loss. However, the low number of genes also results from the fact that the pipeline did not function correctly for all genomes.

In the revised version of the manuscript, the authors included a benchmarking step, which is a good point. They compared their OR gene annotations with previous reports in the same species. Unfortunately, this comparison is irrelevant because the chosen reference OR repertoires are actually a mix of transcriptome and genome annotations. Furthermore, comparisons with entire OR gene repertoires essentially demonstrate that their annotation was of good quality for species in which OR sequences were already present in the query OR database, but poor for species in which they were not. Therefore, these supplementary analyses made by the authors are not particularly in favor of an overall good quality of OR gene repertoires in the >110 species studied. The fact that some OR genes may be missing and that the total number may not be exact for each species is not prohibitive for studying the evolution of the family on a broad scale. However, it does call into question the correlation between the number of ORs and lifestyles and diets.

From the dataset collected, the authors attempted to categorize ORs in several ways, starting with the reconstruction of sequence similarity networks. The approach is interesting, but fails to reveal homology relationships between ORs from species belonging to different insect orders. So it is unclear what the advantage of this approach is compared with the "classical" phylogenetic approach.

The clustering based on structure also leads to the identification of a majority of "order-specific" clusters, which does not provide major insights into the evolution of ORs. However, the authors highlight a group of ORs in flies that appear to possess an unusual intracellular region, as well as a cluster of OR shared across many insect orders that exhibit a larger binding cavity. This is really interesting, although more relevant to OR structure than to their evolution.

The analysis of structural diversity then leads the authors to focus on the Orco co-receptors, which are characterized by modifications of the binding pocket and the appearance of an extracellular loop that could explain the loss of the ability to bind odorant molecules. This part, which relies on in vitro experiments, is interesting and constitutes the most striking result of this study, which could in itself have been the subject of a separate manuscript.

The rest of the manuscript is based on the prediction of OR response spectra using molecular docking. The work that has been carried out is extremely substantial, and the objective of linking clusters based on sequence similarity or 3D structural similarity with functional categories is entirely relevant. The docking score threshold used was chosen thoughtfully, which is very good, and according to the calculation performed should ensure a true positive rate of more than 20%, which is excellent in such a docking analysis. But in the absence of functional validation, this 20% true positive rate is not sufficient to extrapolate OR function, and docking-derived binding breadth measures used in the remaining of the manuscript have to be taken with caution, as acknowledged by the authors themselves. Consequently, the chance that results of this part of the work will enlighten the evolution of OR on a broad scale is low. For example, the fact that insect lineages that emerged after the Permian-Triassic extinction have more broadly-tuned OR is an interesting observation, yet remains highly speculative.

In summary, despite the large number of analyses performed, the authors do not really succeed in achieving the stated objective of reconstructing the evolutionary history of insect ORs, and the results obtained do not strongly support all the conclusions regarding the links between OR repertoires and environment or lifestyle.

Reviewer #2 (Public review):

The remarkable evolvability of the olfactory system enables animals to rapidly adapt to dynamic and chemically complex environments. Over the past two decades, substantial effort has been devoted to uncovering the evolutionary principles that drive the diversification of odorant receptors (ORs), yielding key insights into the forces shaping their striking variability in both vertebrates and insects. In this manuscript, Zhang and colleagues analyze the OR repertoires of over 100 insect species, leveraging sequence and structural similarity to infer patterns of gene family evolution within this diverse and ecologically important clade. By integrating sequence-based and structure-based comparisons, their study builds on a compelling and recently emerging line of research made possible by the advent of AlphaFold, which has previously clarified the phylogenetic relationship between insect Ors and the gustatory receptor gene family and revealed the unexpectedly deep evolutionary origins of this ancient structural fold.

Applying this approach to a large set of ORs derived from species throughout the insect phylogeny, the authors confirm many previously reported patterns of OR evolution. More importantly, with their large-scale approach the authors found new structural features of different Or clades, resulting in intriguing testable hypotheses about Or evolution that have the potential to support future directions in studying this important gene family. For example, the authors identify a structural feature mostly unique to the OR co-receptor ORco, a beta-sheet in EL2, which they functionally show reduces odorant binding affinity - a key aspect of ORco, which does not bind ligands in the ancestral ligand-biding site. This is a particularly strong part of the manuscript, since the authors support their in silico-derived hypothesis with functional data.

In an attempt to assess the relationship between sequence identity and structure on one hand and function on the other, the authors perform an in-silico structure prediction and chemical docking analysis. While not suitable to assess the actual function of individual receptors without functional testing, this strategy revealed potential receptor clades with differences in the number and type of docked chemicals. As a response to the previous reviews, the authors now changed their writing to refer to these results as 'docking-derived function' instead of just 'function'. While I appreciate that the authors changed their wording, this semantic change still can be read as referring to docking-derived predictions as conclusions of actual biological function. However, this is not the case. Any functional claims based solely on the docking approach need to be interpreted with caution, as in silico-only approaches are currently not well enough predictors for actual receptor function. Accordingly, I strongly recommend to remove the parts that connect receptor function to structure or ecology.

Assessing their docking analyses with respect to species ecology, the authors identify correlations suggesting that Or repertoires might follow predictable evolutionary trajectories broadly aligned with species ecology. These are interesting hypotheses. However, due to the inability to predict actual receptor function the author's claims about ecology-function relationships are not well supported. Accordingly, the authors should change the respective parts of the manuscript in way that it is clear these are currently untested hypotheses. This includes adjusting the title, since the work does not find any experimental support for ecological tuning.

I believe that future studies combining functional testing with an explicit evo-eco framework could benefit from this work and the explicit hypotheses it generates. But the authors should be careful to not overstate their in-silico derived results.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

The manuscript by Ma et al. provides robust and novel evidence that the noctuid moth Spodoptera frugiperda (Fall Armyworm) possesses a complex compass mechanism for seasonal migration that integrates visual horizon cues with Earth's magnetic field (likely its horizontal component). This is an important and timely study: apart from the Bogong moth, no other nocturnal Lepidoptera has yet been shown to rely on such a dual-compass system. The research therefore expands our understanding of magnetic orientation in insects with both theoretical (evolution and sensory biology) and applied (agricultural pest management, a new model of magnetoreception) significance.

The study uses state-of-the-art methods and presents convincing behavioural evidence for a multimodal compass. It also establishes the Fall Armyworm as a tractable new insect model for exploring the sensory mechanisms of magnetoreception, given the experimental challenges of working with migratory birds. Overall, the experiments are well designed, the analyses are appropriate, and the conclusions are generally well supported by the data.

Strengths:

• Novelty and significance: First strong demonstration of a magnetic-visual compass in a globally relevant migratory moth species, extending previous findings from the Bogong moth and opening new research avenues in comparative magnetoreception.<br /> • Methodological robustness: Use of validated and sophisticated behavioural paradigms and magnetic manipulations consistent with best practices in the field. The use of 5 min bins to study a dynamic nature of magnetic compass which is anchored to a visual cue but updated with latency of several minutes is an important finding and a new methodological aspect in insect orientation studies.<br /> • Clarity of experimental logic: The cue-conflict and visual cue manipulations are conceptually sound and capable of addressing clear mechanistic questions.<br /> • Ecological and applied relevance: Results have implications for understanding migration in an invasive agricultural pest with expanding global range.<br /> • Potential model system: Provides a new, experimentally accessible species for dissecting the sensory and neural bases of magnetic orientation.

Weaknesses:

Overall, this is a strong study, and the authors have completed an excellent major revision.

Reviewer #2 (Public review):

Summary:

The work titled "Geomagnetic and visual cues guide seasonal migratory orientation in the nocturnal fall armyworm, the world's most invasive insect" provided experimental evidence on how geomagnetic and visual cues are integrated, and visual cues are indispensable for magnetic orientation in the nocturnal fall armyworm.

Strengths:

It has been demonstrated that the Australian Bogon moth could integrate global stellar cues with the geomagnetic field for long distance navigation. However, data are lacking for other insects. This study suggested that the integration of geomagnetic and visual cues may represent a conserved navigational mechanism broadly employed across migratory insects.

Weaknesses:

The visual cues used in the indoor experimental system designed by the authors may have some limitations in ecological relevance. The author may need more explanations on this experimental system.

In the revised manuscript, the authors have added explanations in the discussion section. I am fine with the revision.

Reviewer #1 (Public review):

Summary:

Davis and co-authors used many mouse models to investigate the mechanisms which regulate the contractility of mouse popliteal collecting vessels, primarily chronotropy. The authors use prior literature from the vasculature as a framework to test concepts in lymphatic vessels. The mouse models they used provide evidence for and against the involvement of multiple proteins in regulating chronotropy and other contractile properties in lymphatic vessels. The large amount of data indicate that mechano-stimulation of GNAQ/GNA11-coupled GPCRs generates IP3, which induces intracellular Ca2+ release through IP3R1 to drive depolarization through the activation of ANO1 Cl- channels.

Strengths:

Major strengths of the study are the vast number of mouse knockout models which were used to test the importance of ion channels and G protein signaling pathways in the regulation of lymphatic vessel contractility. The study is a valiant effort and contains a large amount of data. The authors achieved several objectives to find that ANO1 and IP3R1 regulate chronotropy and many other potential proteins do not regulate chronotropy. This study will have a major impact on the field.

Weaknesses:

The authors did an excellent job with the revision. There are no weaknesses.

Reviewer #2 (Public review):

Summary:

In this study, Davis et al., embarked on the quest of the molecular elements responsible for the regulation of lymphatic phasic contractile activity in response to variation of transmural pressure, a mechanism (termed pressure-induced lymphatic chronotropy by the authors). This contractile activity is critical for drainage of interstitial fluid from the tissue and transport of lymph and its cellular and molecular constituents back to the blood circulation. The authors' aim was to investigate the mechanism(s) involved in the pressure-induced regulation of lymphatic pumping, and test whether activation of cation channels, shown in other systems to play mechanosensitive roles are directly at play, and/or whether mechano-activation of Gq/11-coupled GPCRs is necessary to generate second messengers to activate those channels, as it has been suggested for the regulation of myogenic tone in arteries. To achieve their goal, the authors used their well-described, highly reliable protocols of mouse lymphatic vessel isolation, pressure myography, and data acquisition to obtain frequency-pressure relationships and other contractile parameters from transgenic mice where specific channels or molecular elements of interest have been ablated. They combined these data with scRNAseq analysis of these gene targets to determine their respective role and level of expression in lymphatic muscle cells. Their findings demonstrated that, with the exception of ANO1 Cl channels, part of the contractile pacemaker mechanism, none of the exhaustive list of tested ion channels was critical to pressure-induced lymphatic chronotropy, but only ablation of Gq/11 genes or IP3R1 gene in smooth muscle cells led to chronotropy inhibition. To strengthen these findings, they then repeated the myography experiments in the presence of a Gq/11 inhibitor and screened frequency-pressure relationships in vessels from transgenic mice lacking each of the 7 most expressed GPCR according to their scRNAseq dataset. While none of the GPCR ablation showed significant inhibition, they could conclude that transmural pressure activates GPCRs coupled to Gq/11 which generate IP3 to induce SR Ca2+ release through IP3R1 and activate ANO1-mediated depolarization and increase contraction frequency.

Strengths:

The manuscript's strengths reside primarily on very robust, clean and unequivocal pressure myography data and analysis. The research team is mastering these techniques they developed more than a decade ago and have implemented to mouse lymphatics to study their contractile properties, with consistent and convincing outcomes. They also provide data from an impressive list of transgenic mice in order to determine the role of the targeted genes in pressure-induced lymphatic chronotropy, relaying on pharmacological small molecule inhibitors to confirm their findings. Finally, the use of scRNAseq analysis they gathered from previously published dataset brings novelty with respect to expression of the genes of interest in all populations of cells comprising the lymphatic vessels, but more critically to validate or contrast the potential impact of genetic alteration of the given gene in the ability of lymphatic muscles to respond to change in pressure.

Comments on revised version.

The new experiments, additional data, and the now extensive discussion better temper the authors' initial conclusion, the new title as well. The authors should be commended for such an impressive amount of work.

Reviewer #3 (Public review):

In this manuscript, Davis and colleagues aimed to identify the molecular sensors and signaling cascade that enable collecting lymphatic vessels to increase their spontaneous contraction frequency in response to intraluminal pressure (pressure-induced chronotropy). They tested whether the process is similar to blood vessel myogenic constriction by relying on cation channels (TRPC6, TRPM4, PKD2, PIEZO1, etc.) or instead require the activation of G-protein-coupled receptors (presumably mechanosensitive GNAQ/GNA11-coupled receptors), using ex vivo pressure myography of mouse popliteal lymphatics, smooth muscle-specific conditional knockouts, quantitative PCR validation, and single-cell RNA sequencing for target prioritization. The authors convincingly demonstrate that pressure-induced chronotropy does not require the cation channels implicated in arterial myogenic tone but is blunted by deletion of GNAQ/GNA11 or IP3 receptor 1, supporting a model of GPCR > IP3 > Ca2+ release > Cl⁻ channel activation > depolarization. The core conclusion is robust. The work redefines lymphatic pacemaking as G-protein-coupled receptor-dependent mechanotransduction, distinct from arterial mechanisms, and provides a genetically validated toolkit that is useful for studying lymphatic function and dysfunction.

Strengths:

(1) The data are of high quality and highly sensitive functional readouts

(2) The systematic genetic targeting is a major strength that overcomes pharmacological artifacts

(3) Careful quantitative analyses of frequency-pressure slopes

Comments on revised version:

The authors have satisfactorily addressed my comments. No additional comments.

Reviewer #4 (Public review):

Reviewing Editor:

In this revised study Davis and colleagues provide novel findings that are fundamental to the understanding of pressure mechanosensation in lymphatic vessels and are of critical importance to other areas of mechanosensory physiology. The authors used an impressive number of knockout mouse models and employed rigorous state-of-the-art methods, including pressure myography recordings. They provide compelling evidence that mechano-activation of GNAQ/GNA11-coupled GPCRs generates IP3, which induces Ca2+ release from internal stores through IP3R1 and drives depolarization through the activation of ANO1 Cl- channels to induce lymphatic vessel contractility. To uncover the specific GPCR(s) involved in this response, the authors compiled and ranked a list of candidates using single cell RNA sequencing (scRNAseq). In addition to ruling out all major mechanosensitive ion channels previously implicated in this response, the authors also ruled out the involvement of G12/13-coupled GPCRs and 7 most consistently expressed GPCRs in lymphatic smooth muscle along with AT1R. The latter is considered the most likely mechanosensory GPCR in vascular smooth muscle. Although the authors' data fall short of identifying the specific GPCR(s) that mediates pressure-induced chronotropy, they provide compelling evidence that Gq/11-coupled GPCRs are of critical importance to this function. Furthermore, their scRNAseq analysis identified 136 GPCRs in lymphatic smooth muscle, including strongly or moderately expressed candidates such as an olfactory GPCR, three frizzled GPCRs and several adhesion GPCRs (aGPCRs) that encode their own agonist along when many GPCRs with low expression levels. This list represents a foundation for future studies using knockout animal models and aimed at identifying the molecular identity of the GPCR or GPCRs that mediate mechanosensation in lymphatic vessels."

Reviewer #1 (Public review):

Summary:

In this revised manuscript, Vineis et al. examined the functional capacity for organic matter decomposition among cooccurring microbes in Spartina patens dominated deep salt marsh sediment cores using genome reconstruction, cooccurrence networks, and genome scale metabolic modeling. They attempted to test a couple of hypotheses that include 1) microbial communities are structured according to sediment depth, 2) deeper communities are functionally streamlined, 3) the community found within deeper sediments is more likely to contain cooccurring members, 4) there is metabolic complimentary enabling sequential decomposition of complex carbon among microbial communities located in deeper sediments, and 5) the population structure is depth-dependent. They identified depth-dependent structure of microbial communities and populations, environmental filtering of microbes with depth, and metabolic complimentary among members of the Bathyarchaeia BA1 subnetwork that possibly enables sequential decomposition of organic carbon in the deep sediment. Overall, the authors have achieved their aims, with the results supporting their main conclusions. The findings of this work will contribute to our understanding of organic matter transformation in salt marsh sediments and, more broadly, microbial metabolism in energy-limited systems.

Strengths:

(1) Two long sediment cores (down to 240 cm deep) were collected in this study, allowing investigation of the less well characterised subsurface microbiome in salt marsh.

(2) A genome-resolved metagenomic approach was employed here, which provides information on both the structure and functional potential of the salt marsh sediment microbiome, which is not possible in commonly performed 16S rRNA-based surveys.

(3) Metabolic complementarity analysis and metatranscriptomics were used to address the likelihood of metabolic handoffs, providing evidence of potentially active microbial interactions.

Weaknesses:

(1) No geochemical data are available to provide context for the genomic analysis here. Without such information, readers cannot even tell whether the surface sediment samples were oxic or anoxic.

(2) A single metagenomic binning tool, CONCOCT, was used in this study, which very likely has resulted in a limited number of MAGs recovered. More (high-quality) MAGs are expected with the use of additional binners and a bin consolidation procedure. A manual bin refining process was used to improve the quality of the bins obtained though.

Reviewer #2 (Public review):

This work provides a detailed metabolic reconstruction of sediment microbiomes along a depth profile in a Spartina patens salt marsh in Massachusetts, USA. Using a combination of genome reconstruction, co-occurrence network analysis, and metabolic profiling, the authors describe the metabolic potential of co-occurring microbial consortia in understudied deep sediments.

Major strengths of this study include the detailed metagenomic and metatranscriptomic characterization of the understudied deep marsh sediments. The authors recovered genomes representing a substantial portion of the deep sediment microbiome (up to ~60%) and provided an initial explanation of pathways related to the potential for organic carbon decomposition in this environment. Of particular interest is the genomic capability of the deep sediment microbiome to process complex organic compounds, highlighting the need for a collaborative consortium to carry out their decomposition. Improved understanding of the microbial transformation of deep sediment organic carbon in blue carbon ecosystems is vital to better understand the fate of this large carbon pool in the face of climate change.

After assessing a revised version of the manuscript, I only have one methodological comment that readers may find useful as going through the manuscript:

The authors normalize the relative abundance of MAGs by dividing the reads mapping to a MAG by the reads mapping to their whole set of recovered MAGs. They provide a rationale for following this approach in the Methods section. However, I still argue that these values are misleading due to differences in read recruitment levels across samples (and importantly, across depths). In particular, the relative abundance of MAGs in the surface layers (0-40 cm) is overestimated, since the higher diversity in these samples recruited fewer reads due to poor assembly in samples with high sequence-space diversity (shown in Supp. Fig 2). A better normalization approach would be to divide MAG abundance by genome equivalents (e.g., using MicrobeCensus) or any other approach leveraging the abundance of universal single-copy genes in prokaryotes. These approaches are assembly-independent and leverage existing databases of universal single-copy genes. That being said, these methodological limitations do not seem to greatly impact the biological findings of this manuscript.

All other comments have been addressed.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. After previous evaluation by three competent reviewers, the authors have provided an extensive response to their criticisms and recommendations. I believe that authors have done an adequate job in addressing the initial reviews and recommend that the paper be processed for the Version of Record without further work at this time.]

Summary:

Torpor can be induced by chemogenetic activation of the medial preoptic area. This activation leads to protection from myocardial infarction in an isolated heart preparation despite normalization of the ambient temperature, thus, in principle, uncoupling hypothermia from torpor-induced neuroprotection. Putative pathways of protection are suggested by proteomic studies.

Strengths:

(1) Elegant strategy for inducing torpor in rats.

(2) Appropriate controls for verifying the neuron transducer.

(3) Cardiac protection is significant and appears independent of hypothermia.

(4) Interesting omic strategy to begin to find established and novel pathways mediating organ autonomous torpor-induced protection.

Reviewer #2 (Public review):

Summary:

Elley and colleagues induced a synthetic torpor-like state in rats (a non-hibernating species) by chemogenetically activating neurons in the medial preoptic area of the hypothalamus. They show that this state substantially reduced cardiac infarct size in an ex vivo ischemia-reperfusion model. They further report that protection persisted when ambient temperature was raised to prevent hypothermia and used exploratory phosphoproteomics to identify candidate cardioprotective signaling pathways.

Strengths:

This is the first demonstration that a torpor-like state is cardioprotective in a species that does not naturally enter torpor, which meaningfully advances the potential clinical utility of synthetic torpor. The experimental design is logical, and the controls are generally appropriate. The characterisation of the responsible neuronal population using ISH against QPLOT markers adds mechanistic depth and supports the cross-species conservation argument. The phosphoproteomic analysis, though exploratory, generates plausible and biologically coherent hypotheses grounded in the hibernation literature.

Reviewer #3 (Public review):

Summary:

The manuscript by Elley and colleagues describes experiments on the effects of synthetic torpor on ex vivo heart ischemia. The key aspect of the study was the use of viral-vector mediated manipulation of the hypothalamic medial preoptic area (MPA) in rats. They used AAV-CaMKIIa-hM3D(Gq). The authors report that chemogenetic activation of the MPA prior to an ex vivo heart ischemia-reperfusion insult induces cardio protection against infarct size that is independent of prior in vivo hypothermia. Phosphoproteomic analysis of cardiac tissue suggested changes in cell survival and death pathways.

Strengths:

This study has important strengths. The idea is novel. The experimental design is appropriately rationalized and fascinating. The manuscript is written and presented concisely.

Reviewer #4 (Public review):

From the Reviewing Editor:

The core finding and implication of this article is that reduced body temperature and hibernation conditions may have value in understanding basic physiology and during medical conditions. The subject of this submission should be considered as a new interoception topic, which is of current high interest that promises to link CNS regulatory mechanisms to the cardiovascular system and vice versa. But there is also substantial relevance to sleep, the immune system, cancer and protective mechanisms to other organ systems after injury and disease.

This submission demonstrates that a torpor-like state can be related to a cardioprotective effect in a model of ischemia-reperfusion injury. Torpor is characterized by hyperthermia and reduced heart rate and oxygen consumption. As such, it has complicated and unpredictable physiological impacts upon a variety of organ systems. The study contends that the effect of torpor is mediated by the medial preoptic region of the hypothalamus. Protein analysis in a rat model suggests the effects of a torpor-like state may involve detectable effects upon intrinsic cell death and stress related pathways. A further understanding the mechanisms of torpor research will likely reveal new protein and genetic targets that are conserved targets. The authors propose a hypothesis that torpor conditions may reflect an evolutionary mechanism that will have implications for considering application to clinical trials and therapeutic protocols.

This is a provocative study that raises many interesting questions and suggestions for further study. For the most part, the authors acknowledge that there are certainly many future experiments that should be carried out on the basis of the results from the current study. Notwithstanding the need for more experimentation to extend our understanding of torpor, the authors respond to the reviews with additional supplementary data and the recognition of important caveats for alternative brain and physiological mechanisms in play.

Reviewer #1 (Public review):

Pyne and Pandey et al. report the observation of early DNA degradation at the phagocytic cup during macrophage engulfment. Using an elegant experimental system that combines actin staining to visualise cup formation with direct monitoring of DNA degradation, the authors identify rapid recruitment of the membrane-bound nuclease DNase X (DNase1L1) to nascent phagocytic cups. This recruitment occurs within minutes of cup formation, is independent of DNA presence at the substrate, and appears to originate from intracellular membrane structures rather than from the extracellular environment. The results support the conclusion that DNase X activity is present at the phagocytic cup and that DNA digestion can begin prior to phagolysosomal maturation.

The study is technically strong. The experimental system is clean, specific, and allows precise spatial and temporal detection of DNA degradation. The imaging-based approaches are carefully executed and enable convincing visualisation of DNase X recruitment and activity. The use of an alternative substrate beyond the primary SNS system strengthens the core observation, and the data broadly support the authors' central claim.

However, several limitations temper the physiological interpretation. The system relies largely on short, free DNA substrates, leaving open how efficiently DNase X processes more complex or physiologically relevant DNA structures, such as nucleosome-bound DNA or neutrophil extracellular traps (NETs). It remains unclear whether DNase X deficiency would alter macrophage responses to larger nucleic acid structures, influence engulfment efficiency, or modify downstream inflammatory signalling pathways such as TLR9 or STING activation. Moreover, the experimental setup prevents full phagocytic cup closure, potentially prolonging DNase activity compared with physiological phagocytosis, which typically proceeds rapidly to cargo internalisation. For example, the peak signal observed in Figure 5 occurs approximately 90 minutes after phagocytic cup formation, a time point at which many phagocytic cups would be expected to have already closed under physiological conditions. Additional work using fully engulfed cargo in more physiological contexts would clarify whether early DNase X activity meaningfully contributes to overall DNA clearance kinetics.

Mechanistically, the signal that triggers DNase X recruitment remains unresolved. Although actin rearrangement was excluded as the primary driver, the upstream cues that direct DNase X-containing membrane structures to the forming cup are not yet defined.

In the broader context, early DNase X activity at the phagocytic cup could represent an additional safeguard against inflammatory signalling by limiting extracellular or surface-associated DNA before phagolysosomal degradation by DNase II. This mechanism may be particularly relevant in settings where DNA fragmentation before engulfment is incomplete, such as necroptosis or NET formation. Determining whether DNase X deficiency exacerbates inflammatory responses, alters DNA clearance efficiency in vivo, or contributes to immune pathology will be critical for establishing its physiological and disease relevance.

Overall, this is a compelling study that introduces a novel concept of pre-phagolysosomal DNA digestion. The conclusions are well supported within the in vitro system used, but further investigation using diverse DNA substrates and physiologically relevant models will be required to fully define the impact of this mechanism on immune regulation and disease.

Comments on revised version.

The authors have responded constructively to the points raised in my original review. Fig. S5 extends the substrate range beyond the 18-bp SNS construct by showing degradation of plasmid DNA immobilised on microbeads, and fig. S8 addresses my concern that the surface-immobilised platform prevents phagocytic cup closure, by demonstrating DNase activity at cups forming over free, internalisable beads. Together with the live-imaging data in Fig. 1I, these additions support the central claim that DNase activity begins at the nascent phagocytic cup, before closure and well before phagolysosomal maturation. I consider my principal concerns addressed and see no reason to alter the eLife Assessment.

One point remains for readers rather than as a request. The new data establish that DNA at the cup is degraded, but do not themselves demonstrate that DNaseX is responsible, since neither fig. S5 nor the biofilm experiments in Fig. 7 include the PI-PLC or siRNA controls used in Fig. 3; the authors appropriately acknowledge this limitation for the biofilm data. The physiological questions raised in my original review - the handling of chromatin-associated DNA and NETs, and whether DNaseX activity at the cup limits downstream sensing of extracellular DNA - remain open, and the manuscript is appropriately framed as establishing the phenomenon rather than resolving its physiological role.

Reviewer #2 (Public review):

Summary:

This manuscript presents an elegant and innovative imaging approach to visualize DNase activity at the interface between macrophages and extracellular substrates. The platform is technically strong and enables the study of localized DNA degradation with high spatial resolution. The work is of clear interest and provides a useful framework to investigate how immune cells process extracellular DNA. However, several aspects of the mechanistic interpretation and conceptual framing would benefit from clarification.

Strengths:

(1) The study introduces a creative and well-designed imaging platform that allows visualization of localized DNase activity at cell-substrate interfaces.

(2) The approach is technically robust and represents a valuable tool that could be broadly useful to the field.

(3) The experiments are thoughtfully designed and address an important question regarding how immune cells interact with extracellular DNA.

(4) The work opens interesting avenues for studying DNA processing in contexts such as infection and inflammation.

Comments on revised version.

The authors have carefully addressed the points raised in my previous review, and the manuscript has been revised accordingly. I am satisfied with the revisions and have no further comments at this stage.

Reviewer #1 (Public review):

This study applies a recently developed reverse-engineering framework for motor unit discharge to a large dataset from individuals with multiple sclerosis (MS) and neurologically intact controls. The authors aim to determine whether abnormalities in voluntary motor control in MS can be attributed to different patterns of excitatory, inhibitory, and neuromodulatory input to spinal motoneurons. A major conceptual emphasis of the study is on heterogeneity: rather than asking only whether people with MS differ from controls on average, the authors examine whether the distributions of motor unit discharge features and derived physiological variables are broader and more diverse across affected individuals.

A major strength of the work is the size and richness of the dataset. The study includes 89 participants with MS and 34 controls, with high-density surface electromyography (HDsEMG) used to obtain large populations of motor unit discharge patterns from the tibialis anterior (TA) and soleus (SOL) muscles. The resulting dataset contains many thousands of motor unit recordings and allows the authors to examine both group means and the shapes and variances of participant-level distributions. The finding that several motor unit discharge characteristics are more broadly distributed in MS than in controls is convincing and potentially important. In particular, the observation that affected individuals can occupy both high and low extremes of these distributions provides a useful empirical description of the diversity of motor unit behavior in this disease.

The principal limitation concerns the physiological interpretation assigned to these discharge patterns. The excitation, inhibition, and neuromodulation variables are not directly measured physiological inputs. They are composite variables derived from several features of motor unit discharge, with each feature weighted according to relationships identified in simulations reported previously by Chardon and colleagues (reference 1). Thus, the step from observed discharge behavior to specific underlying synaptic mechanisms is necessarily model-dependent. The distinction between these two levels of inference is important for interpreting the main conclusions of the study.

This issue is especially relevant because several different physiological processes can plausibly influence the same discharge features. Motor unit firing patterns reflect not only excitatory and inhibitory synaptic inputs and neuromodulation, but also intrinsic motoneuron properties, persistent inward currents (PICs), after-hyperpolarization (AHP) properties, tonic inhibition, the time course of synaptic excitation, and afferent input. Some of these factors are acknowledged as limitations of the modeling framework in the manuscript. The current data therefore provide strong evidence for heterogeneous motor unit discharge phenotypes in MS, but more indirect evidence that this heterogeneity can be uniquely attributed to distinct patterns of excitatory, inhibitory, and neuromodulatory input.

The interpretation of inhibition is a particularly clear example of this general inverse problem. In the underlying modeling framework, inhibition is represented along a continuum from proportional or balanced inhibition to reciprocal or push-pull inhibition. These different patterns influence PICs and consequently alter firing-rate nonlinearity and rate modulation. This provides a plausible forward-model relationship between inhibitory organization and motor unit discharge. However, observing a particular firing pattern in vivo does not necessarily identify the organization of inhibitory input uniquely, because similar changes in firing-rate modulation or hysteresis could arise from altered neuromodulation, intrinsic motoneuron properties, or other changes in synaptic drive. The inhibition composite is therefore best interpreted as a discharge phenotype that is consistent with a particular inhibitory organization under the assumptions of the model, rather than as a direct measure of inhibitory synaptic input.

A related methodological issue concerns the construction of the composite variables. The authors use mutual-information (MI) values from the previous simulation study as weights in signed linear combinations of normalized discharge features. Mutual information quantifies how informative a feature is about a modeled input parameter, but it is not itself a regression coefficient or a measure of the magnitude of a physiological effect. In addition, different discharge features may contain overlapping information about the same underlying process. The resulting composites are therefore useful summary measures of patterns associated with the modeled physiological variables, but their quantitative interpretation as direct estimates of those variables is less certain. This distinction is particularly relevant because the manuscript sometimes moves from describing the composite variables to describing the corresponding physiological inputs themselves.

The study's emphasis on variability also raises an important measurement issue. Because increased between-participant variance is itself one of the central biological findings, differences in measurement precision between the MS and control groups are more consequential here than in a conventional comparison of group means. Participants with MS sometimes had greater difficulty producing smooth triangular contractions, and motor unit yield and decomposition quality may plausibly vary more across affected participants. If measurement or decomposition uncertainty were more heterogeneous in the MS group, this could broaden participant-level distributions and thereby amplify the appearance of biological heterogeneity. The manuscript uses established decomposition and quality-control procedures, so this is not a general challenge to the validity of HDsEMG. Rather, it is a consideration that is particularly important when increased distributional spread is itself the primary result.

The manuscript also makes a stronger interpretive step from broad group distributions to patient-specific pathophysiology. The data convincingly show that motor unit discharge-derived measures are more heterogeneous among people with MS. They do not yet establish whether this variation represents distinct mechanisms in individual patients, continuous variation in a common mechanism, identifiable pathophysiological subgroups, differences in disease severity or lesion distribution, or some combination of these factors. The manuscript itself recognizes this distinction when it identifies the separation of individual-level variation from potential subgroups as an important goal for future work.

Overall, this is a valuable study with an unusually large motor unit dataset and a compelling demonstration that motor unit discharge behavior is markedly heterogeneous in MS. The work also provides an informative application of a model-based reverse-engineering framework to a clinically diverse human population. The evidence is strongest for the descriptive conclusion that motor unit discharge phenotypes are heterogeneous and altered in MS. The more specific attribution of these phenotypes to excitatory, inhibitory, and monoaminergic inputs is plausible and potentially useful, but remains contingent on the assumptions and identifiability of the underlying model. With this distinction in mind, the dataset and analytical approach should be useful to researchers interested in motor unit physiology, disease-related variability in motor control, and the possibilities and limitations of inferring latent physiological mechanisms from human motor unit discharge.

Reference 1: Chardon, M. K. et al. Supercomputer framework for reverse engineering firing patterns of neuron populations to identify their synaptic inputs. eLife 12, RP90624 (2024).

Reviewer #2 (Public review):

The Beauchamp and Chardon model, like any computational model, is only as informative as the physiological parameters it includes. By varying only three synaptic related dimensions, namely neuromodulatory (i.e., PIC strength from 5HT inputs, etc.), the pattern of inhibition relative to excitation, and the distribution of excitatory input across smaller versus larger motoneurons, the model necessarily holds constant many other properties that may differ substantially between individuals and between controls and patients with MS. These properties include intrinsic membrane conductance properties (with some conductances like NaV that may differ in MS not included in the Chardon model), afterhyperpolarization properties, tonic inhibition, dendritic and axonal structure, synaptic kinetics, glial changes, etc., etc. The present paper then moves one step further away from direct physiological estimation because it does not fit these three model parameters to each participant's data, but instead combines control-normalized firing pattern features using weights derived from the original simulations. As a result, the resulting "excitation," "inhibition," and "neuromodulation" scores should be regarded as indirect similarity scores within a restricted model space, with a substantial risk that changes caused by unmodeled physiology are misattributed to one of the three modeled components. An additional limitation is that the underlying motoneuron models were originally tuned to intracellular recordings from medial gastrocnemius motoneurons in decerebrate cats and then manually modified to generate more human-like firing rates and hysteresis, rather than being formally fitted to human motor unit recordings.

The authors should justify their conclusions using the Chardon reverse engineering method. In addition, more of the raw firing rate profiles should be presented to give a better sense of the data and the quality of the motor unit identification.

Reviewer #3 (Public review):

Summary:

The authors set out to describe how the three basic ingredients of a voluntary motor command, that is excitation, inhibition and neuromodulation, are altered in people with multiple sclerosis. They recorded high-density surface electromyograms from tibialis anterior and soleus during slow triangular contractions in 89 patients and 34 control participants, decomposed the signals into the discharge times of individual motor units, and extracted seven features of the resulting discharge patterns. These features were then combined into three composite scores intended to represent the three ingredients, and the authors asked whether the scores in patients differ from those in controls in their average value, in their spread, and in the shape of their distribution. The working hypothesis was that the motor command is disturbed in different ways in different patients rather than in one consistent direction, and the authors report findings that they consider consistent with that hypothesis.

Strengths:

The dataset is the main strength of this work, and it is quite a considerable one. Studies of motor unit behaviour in neurological populations are usually built on ten or twenty participants, whereas here there are 89 patients spanning the full range of disability together with 34 controls, two muscles per person, and more than 12,000 unique motor units. The clinical characterisation is thorough and includes disease subtype, symptom duration, disability score, walking tests and lesion locations from clinical imaging. The experimental protocol is appropriate and was clearly demanding to deliver in a population of this kind. The treatment of the motor unit data in the statistical models is also more careful than is common in this literature, in particular the recognition that motor unit labels are arbitrary and the correct nesting of units within muscle and within participant. The question itself is well worth asking, and the central observation, that average discharge rates and rate modulation are reduced while a minority of patients sit far above anything seen in controls, is interesting.

Weaknesses:

Three issues limit how far the conclusions can be taken as the paper stands.

First, the framework that gives the paper its title is not the framework that was used. The published approach searches a large database of simulations to find the combination of synaptic inputs that reproduces an observed discharge pattern. What is applied here is a weighted average of standardised discharge features, in which the weights are mutual information values taken from that earlier work and the signs of the weights are supplied by the authors on the basis of the literature. Mutual information measures how much a feature tells you about a parameter. It does not carry the direction of that association, and it does not become a regression coefficient by having a sign attached to it. Since the direction of every conclusion in the paper depends on those assigned signs, the reader has no way of judging how faithfully the composite scores track the physiological quantities they are named after. I do not understand why this was not done with simulations. The authors should expand or clarify this point.

The simulations have known inputs, so the composites could be computed on the simulated discharge patterns and their accuracy reported directly. Two of the features were also modified relative to those simulations, being computed against joint torque rather than against the synaptic drive, and using a normalised version of the hysteresis measure, while the weights derived for the original features were retained. The authors should justify this or specify why this was not done and how it affects the underlying physiology.

A related difficulty is that the three composite scores are not independent of one another. The hysteresis measure contributes to all three of them and several other features contribute to two. Finding abnormality in all three components of the motor command may therefore reflect a single underlying signal expressed three times over. The correlations between the composites are not reported, and without them the reader cannot tell which of these two readings is correct.

Second, the comparison with stroke and with spinal cord injury, which carries much of the novelty of the paper, is asserted rather than demonstrated. A good deal of recent motor unit work in spinal cord injury and in stroke is also omitted, which is an important weakness, and I would encourage the authors to engage with it directly rather than treat those populations as a settled contrast. The abstract and the discussion state that the variability seen here is fundamentally different from the consistency seen in those populations, but no stroke or spinal cord injury data are presented, and no quantitative comparison with published values is offered. This matters because the individual patterns illustrated in the paper, that is, reduced peak discharge rate, compressed rate modulation, a narrowed recruitment range, synchronisation between units, and continued firing after the end of the task, are all well-described features of spastic paresis of other causes. This is commonly observed in people with spinal cord injury as well. One of the three illustrated patients is described as having mild hemiparesis and spasticity. Most of this cohort also carries cervical and thoracic cord lesions in addition to lesions above the spinal cord, so a simpler reading of the spread in these data is a mixture of the mechanisms already known from stroke and from spinal cord injury, present in varying proportions in different patients. That would be a different and considerably less novel conclusion, and it deserves to be considered explicitly. There is a statistical asymmetry in the comparison as well, since the populations described as consistent have been studied in samples of ten to twenty people, and small samples cannot reveal the tails of a distribution.

Third, the central finding of greater variability between patients has plausible alternative explanations that have not been excluded. The value for each participant is the median across the motor units identified in that person, and the number of units varies widely between participants and between the two groups. The precision of a median depends on how many units contribute to it, so precision that differs systematically between groups will inflate the spread of the participant values on its own. In addition, the leg studied was the more affected leg in the patients but the dominant leg in the controls. Choosing the more affected of two limbs is a selection on an extreme value, and it will both shift the patient average and widen the patient distribution for reasons that are purely statistical. Since the Methods state that both legs were recorded, perhaps the authors could consider adding this as an additional control. Finally, the hypothesis is framed in terms of multiple peaks and possible subgroups of patients, yet no test of multimodality is performed, and the density estimates shown do not obviously support it.

The feature carrying by far the largest weight in the neuromodulation score shows no group difference at all, and depending on which version of the hysteresis measure entered the composite, either one or none of its six constituent features differs between groups. The group difference in neuromodulation is also absent in the primary model and emerges only when maximal strength is added as a covariate, a change that the text reports but describes as leaving the results generally unchanged.

Moreover, medication may be assessed more clearly considering the large cohort. Thirty-four of the 89 patients take antispastic drugs, and both tizanidine and baclofen act on the system that the neuromodulation score measures, while others take reuptake inhibitors that act in the opposite direction. A quantitative comparison, with the obvious caveat of confounding by indication, would be needed before the neuromodulation findings can be read as disease-related. The authors should consider this to strengthen the manuscript or justify why this was not done.

Appraisal:

The authors achieve their descriptive aim. They show convincingly that motor unit discharge is altered in multiple sclerosis, that the average change is towards lower discharge rates and reduced rate modulation, and that the patient group is more dispersed than the control group on most measures. I do not think they establish the two claims that give the work its stated significance, that is, that the abnormalities can be attributed specifically to excitatory, inhibitory, and neuromodulatory drive, and that the resulting pattern distinguishes multiple sclerosis from other conditions affecting the same pathways.

Impact and utility:

The findings and dataset are very novel and, once shared, will be a resource for the field, and I would encourage the authors to release the analysis code and the exact weights alongside it. Moreover, it would have been valuable to see more relationships reported between the clinical measures and motor unit behaviour, in particular disability, walking speed, lesion location and medication.

Reviewer #1 (Public review):

Summary:

Here, the authors attempt to show that CCL5 is increased after stroke, possibly due to decreased miR-324, and that this is a modifiable system to decrease stroke damage. By bidirectionally manipulating CCL5 levels through direct injection of CCL5; a CCL5 blocking antibody; miR324; miR324 antagomir; or CCR5-blocking Maraviroc, they broadly show improvement with lower CCL5 levels. This includes infarct size, behavioral analysis, and immunohistochemical analysis of astrocytes, microglia, and neurons. They further try to mechanistically tie miR324 and CCL5 in astrocytes specifically to stroke-induced changes using a neuronal/astrocytic coculture system. They argue that decreasing CCL5 leads to increased ERK and CREB phosphorylation as a potential neuroprotective mechanism. CCL5 is one potential ligand for CCR5, and recent work identified CCR5 as a targetable mechanism by clinically-approved drug Maraviroc to enhance stroke recovery. Particularly given the high level of interest in CCR5 in stroke recovery, the focus on CCL5 - one of CCR5's potential ligands - and its miR regulation is an exciting expansion of this area of stroke biology.

Strengths:

The authors' findings that decreasing CCL5 acutely after stroke shows behavioral improvement appear robust. This broadly replicates work from other groups, although the finding that miR324 manipulation can phenocopy direct CCL5 manipulation is novel and intriguing. However, many of their other claims are difficult to evaluate based on a combination of missing methodological information, inappropriate statistical testing, and a flawed culture system.

Weaknesses:

Broadly speaking, the manuscript takes a zoomed-out view of what is fundamentally highly localized biology.

(1) miRNA-based regulation, by definition, has to include miR and mRNA in the same cell type; as the authors note, CCL5 is expressed in many cells. It is therefore impossible to propose any interaction on the basis of the tissue-level changes described; any evidence of in vivo cell-type specificity would dramatically improve the claims.

(2) The authors treat an extensive area of ipsilesional cortex uniformly as "IP". Astrocytic and microglial responses to localized injuries such as stroke are highly location-dependent and undoubtedly change dramatically within this area. The presented data cannot be interpreted without confirmation that these were taken at identical distances from the injury, and what that distance was. These do not appear to be adjacent to the injury, where the responses would presumably be the most informative. Similarly, it is difficult to interpret the neuronal Sholl and spine data without more information on where within the large IP region these neurons were found.

The authors attempt to narrow in on cell-type specificity via culture. However, astrocytes are notoriously prone to a dramatic change in culture and require careful methods (immunopanning; see eg doi: 10.1016/j.neuron.2011.07.022) to maintain much resemblance to their in vivo counterpart. It is difficult to conclude much about the role of astrocytes in the CCL5 pathway based on the use of this shaking-based culture system, particularly in the absence of cell-type specific validation in vivo.

There is missing methodological information, including infarct size measurements, TUNEL staining, and statistical testing. The TTC figures look very odd, like a collection of overlapping stars have been placed on the images rather than the natural relatively smooth infarct edges one would expect. It is unclear if the infarct volume measurements accounted for edema, as is standard; there is no description of the protocol used for quantification. It is also unclear if the infarct volume measurement comparisons were also done with t-tests vs ANOVA, as the statistical test used is not listed in the figure legends. In numerous cases where statistical testing is listed, repeated t-tests between subgroups are used vs the more appropriate ANOVA (assuming normality; nonparametric testing as appropriate), making it difficult to have confidence in the results.

Reviewer #2 (Public review):

The authors presented evidence from various in vivo and in vitro experiments demonstrating the mutual interaction between CCL5 and astrocytic miR-342-5p in the ipsilateral core of cerebral ischemia. However, miR-342-5p was downregulated only late after MCAO (D3-7). Additionally, this downregulation was observed not only in the ipsilateral core but also in the ipsilateral penumbra and contralateral sides. Therefore, it is not convincing that the upregulation of CCL5 in the ipsilateral core at later time points (D3 and D7) is attributable to the decreased expression of miR-342-5p. In particular, infarct injury was already evident within a short time period (say 24 h) following MCAO.

(1) The temporal and spatial expression patterns of miR-324-5p do not match those of CCL-5, especially at D1 and D3 (see Figure 1C, 1D). Despite the inverse relationship between miR-324-5p and CCL-5 expression at D7 after MCAO, what was the purpose of administering miR-324-5p agomir (or antagomir) at D1 post-MCAO? If the connection cannot be clearly established, the conclusion reached at the end will be difficult to accept.

(2) Would administering miR-342-5p or anti-CCL5 at later time points (e.g., after D3) reduce infarct size or improve functional recovery? If this is not the case, the effect of CCL5 on neuronal cell damage (infarct size formation) must occur within a very short time after MCAO. Additionally, if the increased CCL5 expression is due to the downregulation of miR-342-5p, its impact would likely be less significant.

(3) While the study offers valuable insights into the roles of CCL5 and its connection with the regulation of miR-342-5p (though this connection is somewhat weak), it is recommended that the authors explore potential translational applications of these findings.

Overall, given the experimental designs and results, it is difficult to support the conclusions drawn in the manuscript.

Reviewer #1 (Public review):

Summary:

Hsiung et al. investigated whether the effects of autophagy gene knockdown on the lifespan of long-lived C. elegans mutants depend on experimental conditions. The authors first compiled published data on autophagy-dependent lifespan regulation in daf-2 and wild-type backgrounds, highlighting that prior results are notably inconsistent and likely context-dependent. They then systematically tested the lifespan effects of RNAi knockdown of six autophagy genes (atg-2, atg-4.1, atg-9, atg-13, atg-18, and bec-1) in wild-type (N2), daf-2 (reduced insulin/IGF-1 signalling), and glp-1 (germlineless) animals, while varying temperature, daf-2 allele, FUDR concentration, and bacterial infection status.

The key findings are as follows. In wild-type animals, lifespan suppression by most autophagy gene knockdowns was more pronounced at 20{degree sign}C than at 25{degree sign}C, where little or no effect was observed. In daf-2 mutants, stronger lifespan suppression was seen in the weaker daf-2(e1368) allele at 20{degree sign}C, but not in the stronger daf-2(e1370) allele, and effects were largely absent at 25{degree sign}C. In glp-1 mutants, four of six gene knockdowns suppressed lifespan to a greater extent than in N2, though again in a temperature-dependent manner. FUDR at a high concentration (800 µM) abolished the life-shortening effects of most knockdowns and, in the case of atg-9 and atg-13, led to lifespan extension. Kanamycin treatment to eliminate bacterial proliferation did not fully account for the lifespan effects, suggesting that increased susceptibility to infection is not the primary mechanism. The authors also tested the programmed aging hypothesis that autophagy promotes lifespan reduction through biomass repurposing, but found no changes in vitellogenin levels upon knockdown of any of the six genes.

Altogether, among all genes tested, atg-18 knockdown produced the strongest and most consistent lifespan suppression across nearly all conditions, including both daf-2 and glp-1 backgrounds. The authors probed whether atg-18 acts through the FOXO transcription factor DAF-16 by examining dauer formation and ftn-1 expression, but found no evidence for this, suggesting a DAF-16-independent mechanism.

Strengths:

The primary strength of this work lies in its systematic and comprehensive approach to dissecting how experimental variables influence the outcome of autophagy-lifespan epistasis tests. The compilation of prior data alongside the authors' own multi-condition dataset is a genuinely useful resource for the field. The study raises a timely and important point about condition selection bias in interpreting autophagy lifespan relationships, with broader relevance to C. elegans studies. The finding that atg-18 behaves distinctly from other autophagy genes across a range of experimental conditions is particularly noteworthy and provides an interesting direction for future mechanistic investigation.

Comments on revised version.

The authors have carefully addressed the concerns raised in the previous review and have incorporated most of the suggested revisions. In particular, the revised manuscript provides greater clarity regarding the effects of glp-1 and FUDR and improves the presentation and interpretation of the experimental findings. The authors have also provided useful clarification regarding the variability between lifespan experiments, the number of biological replicates, and the interpretation of RNAi efficacy.

I have only two minor suggestions concerning the wording and organization of the manuscript, which I have communicated separately to the authors. These points are intended to further improve clarity and accuracy and do not affect my overall assessment of the study.

Overall, I am satisfied with the revisions and consider the manuscript to be a valuable contribution to our understanding of the context dependence of autophagy-mediated lifespan regulation.

Reviewer #2 (Public review):

Summary:

This study examines how genes involved in cellular recycling (autophagy) influence lifespan under different experimental conditions. The findings help clarify why previous studies have reported conflicting results about whether blocking autophagy shortens or extends lifespan. The work will be of interest to researchers studying aging and cellular stress responses, particularly those using model organisms.

Strengths:

The findings are valuable, as they help resolve inconsistencies within a specific subfield of aging research. The evidence presented is solid, as the data broadly support the primary claims of the study. In addition, the discussion is thorough and thoughtfully integrates the findings within the broader context of the field.

Weaknesses:

Additional functional validation would further strengthen the conclusions.

Comments on revised version.

I have reviewed the revised manuscript. Overall, the authors have addressed most of my concerns, and the revised manuscript has been improved. The study provides a comprehensive examination of the context-dependent effects of autophagy gene knockdown on lifespan in C. elegans. The data are solid and provide valuable information for understanding the conflicting results currently reported in the literature regarding the role of autophagy in longevity.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The original reviews were generally positive. In their revision, the authors partially address reviewers concerns, but mention that a number of requested experiments are for future studies.]

Summary:

This is an interesting manuscript by Kirk and colleagues describing a highly valuable knock-down system that leverages CRISPRi in order to further elucidate the role of the Kruppel-Like Factor (KLF) transcription factor family in regulating the maturation of postnatal cortical projection neurons. The authors firstly use RNA-Seq and ATAC-Seq data in order to identify the KLF TF family as a potential regulator of cortical neuron maturation in the postnatal brain and subsequently knock down four KLF family members; KLF9, KL13, KLF6 and KLF7, in order to ascertain the functions of specific KLF genes in the developing cortex. The described CRISPRi knock down strategy is highly robust and penetrant as evidenced by a KD efficiency > 95% (assessed by both qPCR and single molecule FISH) and demonstrates that KLF6 and KLF7 play an activating role in driving the expression of target genes relating to axonal growth whereas KLF9 and 13 play a repressive role that inhibits the expression of overlapping gene targets. Together, the authors propose a model where the KLF TF family acts as a regulatory "switch" from activation to repression in the postnatal cortex as a mechanism to control a shift in projection neuron function from axonal growth to circuit refinement. The findings and conclusions of the manuscript offer a valuable contribution to the field of postnatal cortical development and further our understanding of the regulatory mechanisms that govern neuron maturation.

Reviewer #2 (Public review):

Summary:

Kirk et al. use RNA-Seq and CRISPRi to provide evidence that KLF family transcription factors regulate postnatal neuronal maturation of pyramidal neurons. The genetic programs regulating postnatal neuronal maturation are not well understood. The authors first analyzed chromatin accessibility and gene expression data from layer 4 and 6 pyramidal neurons and found that KLF TFs are predicted regulators of postnatal neuronal maturation. They then use CRISPRi knockdown and find that KLF activators first activate genes and then this is followed by KLF repressors repressing genes. Interestingly, some genes, such as those with cytoskeletal functions, are shared targets of KLF activators and repressors.

Strengths:

The study is well-executed and the paper is well-written. A major strength of this study is the application of state-of-the-art transgenic approaches. The CRISPRi approach used to knock down multiple KLFs is compelling. The genomic data generated appears to be high quality and is carefully analyzed. The presented findings provide important insights into the genetic programs that regulate postnatal maturation in cortical pyramidal neurons. The discovery that KLF family activators/repressors regulate gene expression changes during this critical step of neuronal development fills an important gap in the field.

Weaknesses:

While beyond the scope of the current study, future studies should investigate the contributions of KLFs on postnatal morphological and physiological changes.

Reviewer #3 (Public review):

Summary:

In their manuscript "Multiplexed CRISPRi Reveals a Transcriptional Switch Between KLF Activators and Repressors in the Maturing Neocortex", Kirk and colleagues seek to dissect the developmentally regulated pan-neuronal gene programs that control the postnatal maturation of cortical neurons. For this, the authors analyzed newly generated and existing RNA-seq and ATAC-seq of Layer 4 and Layer 6 cortical pyramidal neurons at postnatal day 2 (P2) and day 30 (P30) and identified thousands of shared developmentally regulated genes and genomic (promoter) regions, including genes involved in axon growth (tend to be downregulated) and synaptic function (tend to be upregulated). Motif enrichment analysis of promoters of differentially regulated genes revealed a strong presence of KLF/Sp family binding motifs, pointing to Krüppel-Like Factors (KLFs) as key transcriptional regulators of cortical maturation. Expression profiling showed a developmental switch from activating KLFs (Klf6, Klf7) expressed neonatally to repressive KLFs (Klf9, Klf13) upregulated during maturation. Using an elegant in vivo multiplexed CRISPR interference (CRISPRi) system, the authors achieved efficient, cell-type-specific knockdown of these TFs and showed that Klf9 and Klf13 repress a set of genes that includes cytoskeletal regulators such as Tubb2b, Dpysl3, and Rac3. Conversely, Klf6 and Klf7 promoted the expression of these same genes in the early postnatal period, and their knockdown led to reduced expression of these genes, particularly at P10 when their activating influence is strongest. Since promoters of shared KLF targets were enriched for KLF/Sp motifs but showed little change in chromatin accessibility, the authors propose a model in which distinct KLF family members function either as transcriptional repressors and activators that compete at constitutively accessible promoters and thereby act as a developmental transcriptional switch that coordinates the downregulation of axon growth programs and upregulation of synaptic maturation genes during cortical development.

Strengths:

The study addresses an interesting question and advances our understanding of the transcriptional regulation underlying postnatal cortical development. A major strength of the study lies in the innovative use of in vivo multiplexed CRISPR interference (CRISPRi), which allows for cell-type-specific, combinatorial knockdown of redundant TFs - this an elegant solution to a long-standing challenge in transcription factor research and should be useful also for other neuroscience studies that require local and cell-type-specific gene loss-of-function. Also, the integration of RNA-seq and ATAC-seq across developmental time points provides a robust foundation for identifying direct targets of the KLF family, and the findings are reinforced by cross-species conservation and the identification of targets with clear neurodevelopmental relevance.

Weaknesses:

The major weakness of the study lies in its relatively narrow scope: the study focuses primarily on transcriptional mechanisms and largely lacks functional validation of the neuronal phenotypes that are predicted by the gene expression data (e.g. axonal morphology). Despite these limitations, the paper offers an interesting model for a transcriptional switch during neuronal maturation in the cortex and establishes a powerful methodological framework for dissecting redundant gene networks in vivo.

Reviewer #1 (Public review):

Summary:

Lee et al. investigate how parallel retinal pathways respond to a common loss of photoreceptor input. The authors induce partial cone loss in adult mice and compare the functional responses of sustained OFF alpha (sOFFa) and transient OFF alpha (tOFFa) ganglion cells, together with changes in their presynaptic circuits. Using targeted patch-clamp recordings, linear-nonlinear analyses, pharmacological dissection of inhibitory inputs, and quantitative synaptic imaging, they show that the two pathways do not respond uniformly to cone loss. tOFFa ganglion cells exhibit more extensive changes in spatiotemporal receptive fields than sOFFa ganglion cells, with contributions from excitatory transmission, presynaptic glycinergic inhibition, direct GABAergic and glycinergic inhibition, and intrinsic properties. At the same time, transformations between synaptic input and spike output partially preserve ganglion cell signaling despite the loss of cones.

Strengths:

This is a technically careful and high-quality study. The comparison of two well-defined ganglion cell types and their dominant bipolar-cell pathways provides an unusually detailed view of where circuit modifications arise following a shared perturbation. The combination of recordings at successive stages of signal processing, pharmacological manipulations, and synaptic imaging is a particular strength. The use of partial stimulation in control retina also helps distinguish the immediate consequence of reduced input from subsequent circuit changes. The resulting conclusion that common photoreceptor loss produces pathway-specific forms of remodeling rather than a uniform retinal response is interesting and well supported. The work adds to our understanding of the diversity and circuit specificity of responses to retinal degeneration.

Weaknesses:

The principal limitations concern the precision of some mechanistic interpretations rather than the central observation of pathway-specific remodeling. First, the framework used to classify effects as compensation or circuit change sometimes treats the absence of a statistically significant difference as evidence that two conditions are equivalent. Second, the numbers of animals and retinas contributing to the main physiological and anatomical comparisons are not consistently reported, making it difficult to evaluate the independence of measurements obtained from multiple cells, images, or synaptic puncta. Finally, the consequences of the observed remodeling for the visual signals carried by these pathways remain unclear. This is particularly relevant for tOFFa ganglion cells, which have been implicated in responses to looming or approaching dark objects. The altered temporal filtering, center-surround organization, and input-output transformation could preserve, degrade, or otherwise transform such signals. These issues qualify the mechanistic and functional interpretation but do not substantially weaken the main conclusion that the two pathways respond differently to partial cone loss.

Reviewer #2 (Public review):

Summary:

This is an elegant, rigorous, and thought-provoking study that examines how different neural circuits are altered in response to loss of a common sensory input. To study this question, the authors use the mouse retina as a model system to investigate how downstream retinal circuits undergo modifications following a well-controlled partial loss of cone photoreceptors.

Strengths:

The experiments were conducted with a high degree of rigor, and the authors carefully considered and implemented appropriate controls throughout the study. Multiple parameters were tested, including pharmacological approaches to assess responses from different ganglion cell types. In addition, the authors complemented their functional data with confocal imaging to further support their findings. Overall, this is a well-written paper that provides a thorough analysis demonstrating how two similar ganglion cell types undergo distinct adaptations (i.e., compensation versus remodeling) in response to the loss of the same sensory input.

Weaknesses:

No additional experiments are needed. However, the authors may wish to consider the following points:

(1) Do the differences in compensation versus remodeling observed in ganglion cells reflect changes in the OPL? Different bipolar types may remodel their dendrites and form aberrant contacts with rods in the absence of cones. However, this would be challenging to test because there are currently no good markers for different bipolar types.

(2) It would be interesting to determine whether these functional changes can be detected at the transcriptomic level or whether they are mediated primarily through post-translational modifications.

Reviewer #1 (Public review):

Summary:

This study addresses the gap between calls to incentivize Open Science practices through research assessment reform and its implementation by Research Performing Organizations (RPOs). To help RPOs get started and prioritize their assessment reforms, it makes a series of recommendations for action. It does so via an expert Delphi process, where consensus around six standards was reached. The purpose is to provide a resource for would-be reformers in Research Performing Organizations around the world, in the hope of advancing the Responsible Research Assessment and Open Science reform movements across global academia. The standards are not meant to be one-size-fits-all, but customizable to local needs and implemented selectively at the discretion of a given RPO.

Strengths:

Overall I was impressed with the contribution. Generally speaking, it clearly sets out its methods and arguments. I recognize there is indeed a growing need to support RPOs at varying levels of maturity, to get started and orient themselves around research assessment reform, so this seems to me like it will be a useful offering. The Delphi approach is well explained, and further information is provided in supplementary files.

Weaknesses:

Some further reflection on the disciplinary make-up of the Delphi participants would be helpful. Somewhat more hedging on the limitations of the manuscript would help improve the contribution, as would further details on how this contribution sits in relation to existing resources and studies on implementing open science-aware research assessment reforms.

Reviewer #2 (Public review):

Summary:

This paper describes the employment of a Delphi process, a common consensus-reaching practice based on consecutive rounds of discussion and voting. In this study, the authors engaged in the Delphi process with stakeholders to reach consensus on recommended guidelines for use in tenure and promotion, specific to reproducible and transparent research practices.

Strengths:

The paper provides very practical guidelines for research institutions willing to push for reform regarding reproducible and transparent practices. Guidelines like these are important for institutional leadership that wishes to drive change at their institutions but does not necessarily hold topic expertise on research and reproducibility. The study's authors represent longstanding expertise on the topic, and the use of the Delphi process ensures that stakeholders were engaged in the recommendations, something that helps ensure uptake and buy-in.

Weaknesses:

The biggest weakness of the paper is a lack of engagement with the literature of tenure and promotion reform. This is a field that has been heavily studied with regard to incorporating change in practice to promote equity and inclusion. Other specific subfields that have dealt in this space are those that have pushed for reform to increase the importance of teaching, service, and (inclusion of) mentorship in tenure and promotion packages. Because this paper deals heavily with implementing change in this specific space, and provides guidelines with very practical implications for change, some literature review in the introduction and discussion on where past efforts have succeeded or faced roadblocks would be welcome. This would add to the study's value in helping people implement these practices in a very real and tangible way. The other weakness is a lack of further expansion on the recommendations that did not reach consensus, many of which were added in Round 3. Are more rounds warranted for future studies? Changing landscapes require changing recommendations, which is probably why things like the use of LLMs emerged later and did not reach consensus. How should the readers engage with these results, and what future steps are needed to implement guidelines (if any) around these topics?

Reviewer #3 (Public review):

Summary:

This work provides a novel guide for Research Performing Organizations (RPOs) to evaluate researchers in ways that promote responsible research practices. Such a tool could help inform the development of policies that foster these practices within RPOs and potentially influence decisions related to the hiring and promotion of scientific staff. The guide was developed through a modified three-round Delphi process based on a preliminary set of recommendations provided by members of various organizations. Each round included a survey, and items that did not reach a consensus of >80% were reconsidered in the subsequent round. Round 3 consisted of an in-person meeting, during which the final guide was developed based on criteria that reached {greater than or equal to}80% consensus among participants. The guide includes six practices for evaluation (verification efforts, prospective study registration, data/code/materials sharing, reporting transparency, open-access publishing, and disclosure of funding interests) with an additional seventh component. Each practice includes a clearly defined aim and criteria describing what good practice looks like. The complete study methodology, statistical analyses, and supporting data are available through Open Science Framework (OSF).

Strengths:

A major strength of this work is the development of a practical tool that could help foster responsible research practices among candidates and provide promotion and hiring panel members with clearer criteria for assessing such practices. The three-round Delphi process, which included international participants, provides a structured approach to reaching consensus on practices that could contribute positively to the research ecosystem.

Weaknesses:

The recruitment strategy may have introduced selection bias and limited the representation of researchers and other interest holders from diverse geographical and institutional contexts, particularly from the Global South. Although the authors acknowledge that variability across regions and institutions should be considered when applying the guide, greater representation of these contexts would strengthen confidence in the broad applicability and generalizability of the proposed framework.

Reviewer #1 (Public review):

Summary:

In this manuscript, Matar et al. introduce Mespilia globulus, the tuxedo sea urchin, as a new genomically-enabled model for echinoderm developmental biology. The authors establish a closed life-cycle culture system in a land-locked aquarium facility, demonstrate that key experimental techniques (hybridization chain reaction labelling and CRISPR/Cas9 gene knockout) are tractable in this species, and report chromosome-scale genome assemblies for two colour morphs and both sexes. Using these resources, they compare genome architecture and gene family evolution across sea urchin species, and investigate the genomic basis of sex determination.

Strengths:

The central motivation for this work is well justified: the long larval and juvenile periods of established sea urchin models such as Strongylocentrotus purpuratus have long limited the study of post-metamorphosis and adult biology, and M. globulus reaches metamorphosis in around two weeks and sexual maturity within four to six months, a substantial acceleration. The husbandry and life-cycle data are thorough, and the demonstration that hybridization chain reaction staining and CRISPR/Cas9 knockout both work as expected in this species convincingly establishes its experimental tractability. The two chromosome-scale genome assemblies are of high quality (BUSCO completeness above 99%, 21 chromosome-scale scaffolds consistent with other sea urchins), and the comparative synteny and gene family analyses are carefully constructed, drawing on a solid phylogenomic framework (CAFE-based gene family turnover analysis across six echinoderm species). The authors' finding that M. globulus has fewer duplicated genes in the gene repertoire relative to other camarodont urchins is a genuinely useful observation for researchers choosing a model system for functional genetics, since fewer paralogues should simplify interpretation of knockout phenotypes.

Weaknesses:

Some claims in the manuscript would benefit from additional supporting detail.

(1) The efficiency of the CRISPR/Cas9 knockout is illustrated qualitatively, but no sample size or penetrance value is reported, making it difficult for readers to judge how robust or reproducible this result is.

(2) The gene annotation is reported to have complete PFAM domain coverage for only 75% of predicted genes, but no independent completeness metric (such as BUSCO scored against the annotated gene set rather than the assembly) is provided, leaving open whether the remaining genes are genuinely novel, partial models, or annotation artefacts.

(3) Finally, at the time of review the NCBI BioProject accession cited for the genome and sequencing data (PRJNA1477966) could not be located, and it is not clear from the text whether this accession, once available, will include the gene annotation and RNA-seq datasets in addition to the raw genomic sequencing reads.

In summary, the authors achieve their stated aim of establishing M. globulus as a tractable, fast-developing echinoderm model, and the genomic and experimental resources presented support this conclusion. The comparative genomic conclusions - conservation of ancestral chromosome linkage groups, absence of a heteromorphic sex chromosome, and a comparatively low rate of gene family expansion - are well supported by the data shown, though some of the finer-grained claims (knockout efficiency, annotation completeness) require some clarification. Given the scarcity of tractable models for post-metamorphosis and adult echinoderm biology, this resource is likely to be of real value to the field, provided the genomic and transcriptomic data are made fully and clearly accessible to the community.

Reviewer #2 (Public review):

This manuscript introduces the tuxedo sea urchin, Mespilia globulus, as a new experimental model for developmental, reproductive and genomic biology. The authors establish culture methods that permit completion of the life cycle in a landlocked aquarium facility, demonstrate the applicability of developmental biology tools including HCR-FISH and CRISPR/Cas9-mediated gene disruption, generate chromosome-scale genome assemblies from two color morphs and both sexes, investigate potential sex determination mechanisms, and compare genome organization and gene family evolution with other sea urchin models. The authors conclude that M. globulus combines a relatively rapid life cycle with genomic tractability and therefore represents a valuable addition to the growing repertoire of genetically accessible sea urchin model systems.

Overall, I found this to be a strong and timely contribution that is well suited for the Tools and Resources category of eLife. The authors provide a comprehensive suite of resources, including husbandry protocols, genomic resources, developmental staging information, and proof-of-principle functional manipulations. The manuscript appropriately places M. globulus in the context of established sea urchin models, particularly Lytechinus pictus, and clearly argues that the new species is complementary rather than a replacement for existing systems. Given the increasing importance of genetically tractable echinoderm models, the development of an additional species that can be maintained and bred in closed aquarium systems is of considerable value to the field.

The evidence supporting the establishment of this model system is convincing, with multiple complementary datasets including life-cycle culture methods, genome assemblies, gene expression analyses, and gene-editing experiments.

My concerns primarily relate to two broader issues that should be addressed, followed by several specific comments.

(1) Genetic Background and Aquarium Trade Populations: A central argument of the manuscript is that M. globulus is attractive as a laboratory model because it is widely cultured in the aquarium trade and may exhibit reduced genetic variability due to captive propagation.

The manuscript states:

"M. globulus is a popular species in the aquarium industry and has excellent properties in tropical aquariums where it has been bred for many years in farming operations that reduce genomic heterogeneity..." (lines 96-98) and later:

"Captive breeding may also lower genetic variability compared to wild-caught individuals..." (lines 389-390).

However, the manuscript does not provide sufficient information to evaluate these claims. Several important questions remain unresolved:

(1) How genetically representative are the sequenced individuals relative to natural populations?

(2) What is known about the provenance and breeding history of the aquarium trade stocks used in this study?

(3) Are these animals derived from a small number of founder populations?

(4) Is there evidence for substantial inbreeding or genetic bottlenecks within commercial brood stocks?

(5) How similar are commercially available animals from different vendors and geographic sources?

These questions are important for both practical and biological reasons. From a practical perspective, researchers wishing to adopt M. globulus need to know whether animals purchased from aquarium suppliers are expected to resemble those analyzed here. From a biological perspective, reduced diversity or founder effects could influence genome assembly characteristics, heterozygosity estimates, gene family analyses, developmental traits, or responses to experimental manipulation.

Even if little information is currently available, the manuscript should explicitly discuss these uncertainties and provide available information regarding stock origin, aquaculture practices, and potential differences between captive and natural populations. A clear discussion of potential limitations would significantly strengthen the manuscript.

(2) Presentation and Interpretation of HCR and Phalloidin Data: Although the HCR and phalloidin experiments are not central to the major conclusions of the paper, they serve as important demonstrations of experimental tractability. At present, however, the presentation of these data is not fully convincing.

The HCR images show detectable signal, but the expression domains are only minimally documented. The manuscript states that expression patterns are consistent with known functions of Nodal and Notch signaling, yet the figures do not sufficiently guide readers to these conclusions (especially readers not familiar with sea urchin development). The signal is relatively diffuse and weak in some panels, and there is little annotation explaining exactly which embryonic territories are expressing the genes of interest. For readers without extensive sea urchin developmental biology expertise, it can be difficult to assess the validity and biological significance of the observed expression patterns.

Similarly, the phalloidin-labeled images provide limited anatomical information because the larvae are largely not labeled. I recommend:

(1) Adding labels identifying relevant embryonic regions and structures.

(2) Including arrows or overlays indicating key expression domains.

(3) Providing higher-magnification insets of relevant regions.

(4) Including selected optical sections rather than relying exclusively on 3D projections.

(5) Identifying known larval muscle groups in the phalloidin images.

(6) Improving image contrast and figure annotation where possible.

These changes would substantially strengthen the claim that established developmental biology methods are readily transferable to M. globulus.

Reviewer #3 (Public review):

Summary:

Omar Matar and colleagues describe how they successfully closed the life cycle of the tropical tuxedo urchin Mespilia globulus in a small, closed aquarium system. Its capacity to flourish under closed culturing conditions sets this sea urchin apart from most echinoderms and indeed most marine invertebrates, which require high-quality flow-through seawater (i.e. coastal access and a flow-through aquarium system). As M. globulus reaches sexual maturity in captivity in 4-6 months, which is shorter than other sea urchins, it opens the potential for transgenerational studies.

Matar et al. have developed a suite of molecular and genomic techniques and resources, including Cas9-mediated gene knockdown and chromosome-scale genome assemblies for both sexes and colour morphs. These strong aquaculture and genomics platforms suggest that M. globulus can provide insights into aspects of the sea urchin life cycle and history that would be difficult to study in other sea urchin models, which historically have been focused on embryogenesis.

Strengths:

This manuscript announces M. globulus as a novel, genome-enabled echinoderm model that can be cultured in a closed system with a few hundred litres of 23/24oC artificial seawater. This allows for experimental analysis of parts of the sea urchin life cycle that are not particularly tractable in other sea urchins, including the developmental biology of metamorphosis, symbiont interactions and immunity through the life cycle, post-settlement biomineralisation, and sex determination. The capacity to knock out embryonic/larval genes using CRISPR/Cas9 and visualise localised embryonic and larval gene expression using HCR are consistent with claims M. globulus can contribute novel insights into basic and applied (aquaculture) biology of sea urchins and echinoderms.

Weaknesses:

The general weakness of this manuscript is that the authors do not explain aspects of their study in enough detail (e.g. a single figure - Figure 2 - presents results of analysis of normal development, HCR and Cas9 knockdowns). This manuscript provides limited methodological detail about the culture system and the analysis of gene expression. Here are a few suggestions on how to improve the manuscript:

First, the authors should provide a thorough description of the methods used to cultivate and maintain M. globulus. This should include further details about the closed aquarium system; a schematic of the system would be insightful. Basic details about husbandry are needed, including (i) stocking densities of adults, embryos/larvae, postlarvae/juveniles; (ii) frequencies of level and water changes/top-ups; (iii) feeding regime at all phases of the life cycle (amount/sea urchin, post-feeding cleaning, etc.). These and other details are essential for the uptake of this model system. This documentation would provide the foundation for future improvements, which include shortening the time to acquire larval competence and sexual maturity, and improving and standardising larval settlement.

Second, the description of the procurement and analysis of mRNA is brief, unreferenced and reads as protocols used for an established model species (e.g. what is PFA in this case - the concentration of paraformaldehyde and the buffer can vary markedly between organisms and life stages). Even the RNA extraction protocols can vary between and within species. For instance, highly pigmented tissues tend to be more difficult to procure useable RNA. The HCR analysis, which is also scantily described, is restricted to embryonic and larval stages. Given the emphasis on the capacity of the M. globulus system to analyse all phases of the life cycle, it would be good to know if HCR can be performed on settled postlarvae, juveniles and adult tissues.

Third, the authors should consider dividing Figure 2, which consists of confocal images of normal development, HCR results and CRISPR/Cas9 knockout results, into three separate figures that explore these studies separately. A figure on normal development could, for instance, include documentation of metamorphosis, with a suite of images of postlarval stages. A figure documenting HCR could be expanded to include more stages, higher magnification images and other genes. A figure on the Cas9 knockdown of a PKS gene can provide details on the normal expression of this gene using HCR and possibly qRT-PCR.

Fourth, there should be consideration of providing more characterisation about the protein-coding genes comprising the chromosomal region (Chr. 4) that has marked differences between sexes. This could go beyond Supplementary Table 4 and Supplementary Figure 5B, and include analysis of expression in adult tissues (this would be enhanced by having matching male and female tissues), and KEGG pathways and GO enrichments.

Overall, this is an exciting development in the study of echinoids and echinoderms. This manuscript can be improved by providing the reader with more details. Given the exciting prospect of being able to study M. globulus settlement and metamorphosis in detail, the authors may consider providing more information about this part of the life cycle.

Reviewer #1 (Public review):

[Editors' note: Overall, the reviewing editor and reviewers agreed that authors rigorously addressed reviewers' major scientific concerns.]

Hanako and colleagues demonstrated that glycolipid MPIase is essential for the TAT system, and they successfully reconstituted the TAT system in vitro for the first time. This will facilitate the understanding of the mechanism of the TAT system.

Comments on revised version from Reviewer 1 and the Reviewing Editor:

In Reviewer 1's points 1 and 2 regarding statistical significance of immunoblotting data (in recommendation to authors), authors stated that they repeated the experiments three times in the rebuttal letter but not in the figure legends. We recommend authors to add a statement such as "errors denote +-SD (N = 3)" in the final version, which will make the data more solid and reliable.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated the relationship between the Tat system and MPIase, a glycolipid that facilitates protein integration into the bacterial cell membrane. The TAT (twin-arginine translocation) system is a unique membrane transport machinery that exports fully folded proteins containing a twin-arginine signal peptide. Using both in vivo and in vitro approaches, the authors demonstrated that a sufficient amount of MPIase is required for Tat-dependent protein translocation. Furthermore, the authors successfully reconstituted the Tat transport system by combining recombinant TatA, TatB, TatC, MPIase, and FoF1-ATP synthase.

Strengths:

The reconstituted system clearly demonstrated the requirement for each component, as substrate translocation occurred only when all components were present. Based on these findings, the authors proposed a mechanistic role for MPIase in facilitating Tat-mediated membrane translocation. Previous studies have shown that MPIase is involved in Sec-dependent protein translocation and membrane protein integration, as well as YidC-dependent membrane insertion. The present study further demonstrated that MPIase also plays an essential role in the Tat translocation pathway. Overall, this work highlights the central importance of MPIase in bacterial membrane protein biogenesis and provides new insights into the molecular mechanism of Tat-dependent protein transport.

Comments on revised version from Reviewer 2 and Reviewing Editor:

(Reviewer 2) It is nice to find the mistake in Fig. 4B (RR, EK413, (not +MPIase)) and corrected it in the revised version. However, the data of Fig. 4B and the related modified text on P.9 L256-269 are not very easy to understand what the authors are trying to argue. This reviewer believes that the magnitudes of MPIase expression level are Ek413 > +MPIase > delta-MPIase. Therefore, the means of supernatant in the delta-MPIase and EK413 represents mostly cytosol and periplasm, respectively. On the other hand, the +MPIase shows less supernatant that means a large part of TorA-GFP are trapped nearby membrane but not aggressively transported. Similar results are found also in (KK) case, whereas the sup level in EK413 is lower than that of (RR) case due to the lack of twin-arginine motif in the substrate.

Although these results are convincing in explaining the model in Figure 5, authors might be able to attempt to refine them more understandable. Especially, the revised text on P.9 L256-269 is not enough for leading readers to the author's claim. So that, the authors should revise the text about Fig. 4B again and the related description in the manuscript. Another option is it would be possible to delete whole Fig. 4B, because Fig. 4A, C already well support the model in Fig. 5.

(Reviewing Editor) I agree with Reviewer 2. The first paragraph in the section "MPIase serves as the TAT signal receptor" runs very long and the clarity of the descriptions on Fig. 4B could be further improved. Fig. 4A, C would sufficiently support author's arguments. I recommend that authors consider these options for the final version.

Reviewer #1 (Public review):

Summary:

Polymyxins are the last line of drugs to treat gram-negative bacteria induced multi-drug resistance, however, they cause nephrotoxicity in 60% of patients. In this work, authors have studied the structure-interaction relationship (SIR) of polymyxins with hPepT2 using computational and experimental methods. Moreover, it is observed that the electrostatic interactions coordinate the hPepT2-Polymyxin interactions, hence, an alanine scanning strategy is used to understand the interactions and derive the polymyxin variants.

Computational methods such as molecular modeling, coarse grained and all atom MD simulations, and interaction studies are performed. While the results are validated in the mouse model which is a great strategy to prove the hypothesis.

Strengths:

A clear understanding on the hPepT2-Polymyxin interactions and role of electrostatic interactions is one of the very important strengths of the paper. In addition, this work proposes a great pipeline for using computational approaches and experimental validation methods to guide the development of newer antibiotics.

Overall, the study proposes novel polymyxin analogues with reduced or no nephrotoxicity, thereby providing a promising foundation for the rational development of safer lipopeptide antibiotics.

Comment on revised manuscript:

I appreciate the effort by Authors to address my comments. The manuscript now contains details of ACE inhibitors in the introduction. In addition, method section is updated for better reproducibility of the MD simulation and structure modeling methods. I congratulate authors for reporting a wonderful scientific study. I don't have any further recommendations. Thank you!

Reviewer #3 (Public review):

Summary:

Jiang et al. described findings aimed at interrogating the interactions of the antibiotic polymyxin B with human kidney proteins that mediate nephrotoxicity. Their findings using both computational molecular dynamics simulations and experimental approaches illustrate the importance of aspartic acid residues (D215) in mediating the antibiotic uptake into the cells, and upon mutagenesis with Alanine, the effects are less pronounced. Further, they could modify the antibiotic units interacting with proteins into less toxic peptides with retained antibacterial properties.

Strengths:

I was impressed by this text, which advances the knowledge of how the antibiotic causes human nephrotoxicity and how this could be exploited into less problematic antibiotic peptides.

Comments on revised version.

Majority of the raised issues were addressed satisfactorily.

Reviewer #1 (Public review):

Summary:

How the regenerative capacity of the heart varies among different species has been a long-standing question. Within teleosts, zebrafish can regenerate their hearts, while medaka and cavefish cannot. The authors examined heart regeneration in two livebearers, platyfish and swordtails. Interestingly, they found that these two fish species lack the compact myocardium layer that contains coronary vessels. Furthermore, these fish form a "pseudoaneurysm" after cryoinjury without initial deposition of fibrotic tissues. However, delayed leukocyte infiltration and prolonged inflammation lead to permanent scar tissue in the injured heart. Although their cardiomyocytes can also proliferate, platyfish and swordtails can only regenerate partially. The authors argue that the restorative mechanism of platyfish and swordtails likely reflects "evolutionary innovations in the ventricle type and the immune system".

Strengths:

The authors took advantage of the annotated genome of platyfish to perform transcriptomic analyses. The histological analyses and immunostaining are beautifully done.

Comments on revised version:

The authors have addressed all my previous concerns. I don't have further questions.