Reviewer #1 (Public review):

This is an interesting and timely computational study using molecular dynamics simulation as well as quantum mechanical calculation to address why tyrosine (Y), as part of an intrinsically disordered protein (IDP) sequence, has been observed experimentally to be stronger than phenylalanine (F) as a promoter for biomolecular phase separation. Notably, the authors identified the aqueous nature of the condensate environment and the corresponding dielectric and hydrogen bonding effects as a key to understand the experimentally observed difference. This principle is illustrated by the difference in computed transfer free energy of Y- and F-containing pentapeptides into solvent with various degrees of polarity. The elucidation offered by this work is important. The computation appears to be carefully executed, the results are valuable, and the discussion is generally insightful. However, there is room for improvement in some parts of the presentation in terms of accuracy and clarity, including, e.g., the logic of the narrative should be clarified with additional information (and possibly additional computation), and the current effort should be better placed in the context of prior relevant theoretical and experimental works on cation-π interactions in biomolecules and dielectric properties of biomolecular condensates. Accordingly, this manuscript should be revised to address the following, with added discussion as well as inclusion of references mentioned below.

(1) Page 2, line 61: "Coarse-grained simulation models have failed to account for the greater propensity of arginine to promote phase separation in Ddx4 variants with Arg to Lys mutations (Das et al., 2020)". As it stands, this statement is not accurate, because the cited reference to Das et al. showed that although some coarse-grained model, namely the HPS model of Dignon et al., 2018 PLoS Comput did not capture the Arg to Lys trend, the KH model described in the same Dignon et al. paper was demonstrated by Das et al. (2020) to be capable of mimicking the greater propensity of Arg to promote phase separation than Lys. Accordingly, a possible minimal change that would correct the inaccuracy of this statement in the manuscript would be to add the word "Some" in front of "coarse-grained simulation models ...", i.e., it should read "Some coarse-grained simulation models have failed ...". In fact, a subsequent work [Wessén et al., J Phys Chem B 126: 9222-9245 (2022)] that applied the Mpipi interaction parameters (Joseph et al., 2021, already cited in the manuscript) showed that Mpipi is capable of capturing the rank ordering of phase separation propensity of Ddx4 variants, including a charge scrambled variant as well as both the Arg to Lys and the Phe to Ala variants (see Fig.11a of the above-cited Wessén et al. 2022 reference). The authors may wish to qualify their statements in the introduction to take note of these prior results. For example, they may consider adding a note immediately after the next sentence in the manuscript "However, by replacing the hydrophobicity scales ... (Das et al., 2020)" to refer to these subsequent findings in 2021-2022.

(2) Page 8, lines 285-290 (as well as the preceding discussion under the same subheading & Fig.4): "These findings suggest that ... is not primarily driven by differences in protein-protein interaction patterns ..." The authors' logic in terms of physical explanation is somewhat problematic here. In this regard, "Protein-protein interaction patterns" appears to be a straw man, so to speak. Indeed, who (reference?) has argued that the difference in the capability of Y and F in promoting phase separation should be reflected in the pairwise amino acid interaction pattern in a condensate that contains either only Y (and G, S) and only F (and G, S) but not both Y and F? Also, this paragraph in the manuscript seems to suggest that the authors' observation of similar contact patterns in the GSY and GSF condensates is "counterintuitive" given the difference in Y-Y and F-F potentials of mean force (Joseph et al., 2021); but there is nothing particularly counterintuitive about that. The two sets of observations are not mutually exclusive. For instance, consider two different homopolymers, one with a significantly stronger monomer-monomer attraction than the other. The condensates for the two different homopolymers will have essentially the same contact pattern but very different stabilities (different critical temperatures), and there is nothing surprising about it. In other words, phase separation propensity is not "driven" by contact pattern in general, it's driven by interaction (free) energy. The relevant issue here is total interaction energy or critical point of the phase separation. If it is computationally feasible, the authors should attempt to determine the critical temperatures for the GSY condensate versus the GSF condensate to verify that the GSY condensate has a higher critical temperature than the GSF condensate. That would be the most relevant piece of information for the question at hand.

(3) Page 9, lines 315-316: "...Our ε [relative permittivity] values ... are surprisingly close to that derived from experiment on Ddx4 condensates (45{plus minus}13) (Nott et al., 2015)". For accuracy, it should be noted here that the relative permittivity provided in the supplementary information of Nott et al. was not a direct experimental measurement but based on a fit using Flory-Huggins (FH), but FH is not the most appropriate theory for polymer with long-spatial-range Coulomb interactions. To this reviewer's knowledge, no direct measurement of relative permittivity in biomolecular condensates has been made to date. Explicit-water simulation suggests that relative permittivity of Ddx4 condensate with protein volume fraction ≈ 0.4 can have relative permittivity ≈ 35-50 (Das et al., PNAS 2020, Fig.7A), which happens to agree with the ε = 45{plus minus}13 estimate. This information should be useful to include in the authors' manuscript.

(4) As for the dielectric environment within biomolecular condensates, coarse-grained simulation has suggested that whereas condensates formed by essentially electric neutral polymers (as in the authors' model systems) have relative permittivities intermediate between that of bulk water and that of pure protein (ε = 2-4, or at most 15), condensates formed by highly charge polymers can have relative permittivity higher than that of bulk water [Wessén et al., J Phys Chem B 125:4337-4358 (2021), Fig.14 of this reference]. In view of the role of aromatic residues (mainly Y and F) in the phase separation of IDPs such as A1-LCD and LAF-1 that contain positively and negatively charged residues (Martin et al., 2020; Schuster et al., 2020, already cited in the manuscript), it should be useful to address briefly how the relationship between the relative phase-separation promotion strength of Y vs F and dielectric environment of the condensate may or may not be change with higher relative permittivities.

(5) The authors applied the dipole moment fluctuation formula (Eq.2 in the manuscript) to calculate relative permittivity in their model condensates. Does this formula apply only to an isotropic environment? The authors' model condensates were obtained from a "slab" approach (p.4) and thus the simulation box has a rectangular geometry. Did the authors apply their Eq.2 to the entire simulation box or only to the central part of the box with the condensate (see, e.g., Fig.3C in the manuscript). If the latter is the case, is it necessary to use a different dipole moment formula that distinguishes between the "parallel" and "perpendicular" components of the dipole moment (see, e.g., Eq.16 in the above-cited Wessén et al. 2021 paper). A brief added comments will be useful.

(6) With regard to the general role of Y and F in the phase separation of biomolecules containing positively charged Arg and Lys residues, the relative strength of cation-π interactions (cation-Y vs cation-F) should be addressed (in view of the generality implied by the title of the manuscript), or at least discussed briefly in the authors' manuscript if a detailed study is beyond the scope of their current effort. It has long been known that in the biomolecular context, cation-Y is slightly stronger than cation-F, whereas cation-tryptophan (W) is significantly stronger than either cation-Y and cation-F [Wu & McMahon, JACS 130:12554-12555 (2008)]. Experimental data from a study of EWS (Ewing sarcoma) transactivation domains indicated that Y is a slightly stronger promoter than F for transcription, whereas W is significantly stronger than either Y or F [Song et al., PLoS Comput Biol 9:e1003239 (2013)]. In view of the subsequent general recognition that "transcription factors activate genes through the phase-separation capacity of their activation domain" [Boija et al., Cell 175:1842-1855.e16 (2018)] which is applicable to EWS in particular [Johnson et al., JACS 146:8071-8085 (2024)], the experimental data in Song et al. 2013 (see Fig.3A of this reference) suggests that cation-Y interactions are stronger than cation-F interactions in promoting phase separation, thus generalizing the authors' observations (which focus primarily on Y-Y, Y-F and F-F interactions) to most situations in which cation-Y and cation-F interactions are relevant to biomolecular condensation.

(7) Page 9: The observation of a weaker effective F-F (and a few other nonpolar-nonpolar) interaction in a largely aqueous environment (as in an IDP condensate) than in a nonpolar environment (as in the core of a folded protein) is intimately related to (and expected from) the long-recognized distinction between "bulk" and "pair" as well as size dependence of hydrophobic effects that have been addressed in the context of protein folding [Wood & Thompson, PNAS 87:8921-8927 (1990); Shimizu & Chan, JACS 123:2083-2084 (2001); Proteins 49:560-566 (2002)]. It will be useful to add a brief pointer in the current manuscript to this body of relevant resource in protein science.

Comments on revisions:

The authors have largely addressed my previous concerns and the manuscript has been substantially improved. Nonetheless, it will benefit the readers more if the authors had included more of the relevant references provided in my previous review so as to afford a broader and more accurate context to the authors' effort. This deficiency is particularly pertinent for point number 6 in my previous report about cation-pi interactions. The authors have now added a brief discussion but with no references on the rank ordering of Y, F, and W interactions. I cannot see how providing additional information about a few related works could hurt. Quite the contrary, having the references will help readers establish scientific connections and contribute to conceptual advance.

Reviewer #1 (Public review):

Summary

In the presented paper, Lu and colleagues focus on how items held in working memory bias someone's attention. In a series of three experiments, they utilized a similar paradigm in which subjects were asked to maintain two colored squares in memory for a short and variable time. After this delay, they either tested one of the memory items or asked subjects to perform a search task.

In the search task, items could share colors with the memory items, and the authors were interested in how these would capture attention, using reaction time as a proxy. The behavioral data suggest that attention oscillates between the two items. At different maintenance intervals, the authors observed that items in memory captured different amounts of attention (attentional capture effect).

This attentional bias fluctuates over time at approximately the theta frequency range of the EEG spectrum. This part of the study is a replication of Peters and colleagues (2020).

Next, the authors used EEG recordings to better understand the neural mechanisms underlying this process. They present results suggesting that this attentional capture effect is positively correlated with the mean amplitude of alpha power. Furthermore, they show that the weighted phase lag index (wPLI) between the alpha and theta bands across different electrodes also fluctuates at the theta frequency.

Strengths

The authors focus on an interesting and timely topic: how items in working memory can bias our attention. This line of research could improve our understanding of the neural mechanisms underlying working memory, specifically how we maintain multiple items and how these interact with attentional processes. This approach is intriguing because it can shed light on neuronal mechanisms not only through behavioral measures but also by incorporating brain recordings, which is definitely a strength.<br /> Subjects performed several blocks of experiments, ranging from 4 to 30, over a few days depending on the experiment. This makes the results - especially those from behavioral experiments 2 and 3, which included the most repetitions - particularly robust.

Weaknesses

One of the main EEG results is based on the weighted phase lag index (wPLI) between oscillations in the alpha and theta bands. In my opinion, this is problematic, as wPLI measures the locking of oscillations at the same frequency. It quantifies how reliably the phase difference stays the same over time. If these oscillations have different frequencies, the phase difference cannot remain consistent. Even worse, modeling data show that even very small fluctuations in frequency between signals make wPLI artificially small (Cohen, 2015).

In response authors stated : "Additionally, the present study referenced previous research by using the wPLI index as a measure of cross-frequency coupling strength31,64-66"<br /> Unfortunately, after checking those publications, we can see that in paper 31 there is no mention of "wPLI" or "PLV." In 64 and 65, the authors use wPLI, but only to measure same-frequency coherence, whereas cross-frequency coupling is computed by phase-amplitude coupling or cross-frequency coupling also known as n:m-PS. In 66, I cannot find any cross-frequency results, only cross-species analysis. This is very problematic, as it indicates that the authors included references in their rebuttal without verifying their relevance.<br /> 31 de Vries, I. E. J., van Driel, J., Karacaoglu, M. & Olivers, C. N. L. Priority Switches in Visual Working Memory are Supported by Frontal Delta and Posterior Alpha Interactions. Cereb Cortex 28, 4090-4104, doi:10.1093/cercor/bhy223 (2018).64 Delgado-Sallent, C. et al. Atypical, but not typical, antipsychotic drugs reduce hypersynchronized prefrontal-hippocampal circuits during psychosis-like states in mice: Contribution of 5-HT2A and 5-HT1A receptors. Cerebral Cortex 32, 870 3472-3487 (2022). 65 Siebenhühner, F. et al. Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings. PLoS Biology 18, e3000685 (2020). 66 Zhang, F. et al. Cross-Species Investigation on Resting State Electroencephalogram. Brain Topogr 32, 808-824, doi:10.1007/s10548-019-00723-x (2019).

Another result from the electrophysiology data shows that the attentional capture effect is positively correlated with the mean amplitude of alpha power. In the presented scatter plot, it seems that this result is driven by one outlier. Unfortunately, Pearson correlation is very sensitive to outliers, and the entire analysis can be driven by an extreme case. I extracted data from the plot and obtained a Pearson correlation of 0.4, similar to what the authors report. However, the Spearman correlation, which is robust against outliers, was only 0.13 (p = 0.57) indicating a non-significant relationship.

Cohen, M. X. (2015). Effects of time lag and frequency matching on phase based connectivity. Journal of Neuroscience Methods, 250, 137-146

DOI: 10.1016/j.celrep.2025.116325

Resource: None

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-GENO-190430-1

What is this?

Joint Public Review:

Marshall et al describe the effects of altering metabotropic glutamate receptor 5 activity on activity of D1 receptor expressing spiny projection neurons in dorsolateral striatum focusing on two states - locomotion and rest. The authors examine effects of dSPN-specific constitutive mGlu5 deletion in several motor tests to arrive at this finding. Effects of inhibiting the degradation of the endocannabinoid 2-arachidonoyl glycerol are also examined. Overall, this is a valuable study that provides solid new information of relevance to movement disorders and possibly psychosis.

The combination of in vivo cellular calcium imaging, pharmacology, receptor knockout and movement analysis is effectively used. The main findings do not involve gross firing rates or numbers of active neurons, but rather are revealed by specialized measures involving Jaccard coefficient and an assessment of coactivity. The authors conclude that mGlu5 expressed in dSPNs contributes to movement through effects on clustered spatial coactivity of dSPNs. More specifically, reduced mGluR5 increases coactivity during rest (defined as low velocity periods) but not during locomotion periods. The authors observe a role for mGlu5 expression in dSPNs in modulating the frequency of mEPSCs, suggesting a role in presynaptic neurotransmitter release. Some data suggesting the story may be different in the other major SPN subpopulation (iSPNs) are also presented but these studies are relatively underdeveloped leaving some ambiguity as to how cell-selective the findings are. In addition, an occlusion experiment in which the pharmacological mGluR5 agents are delivered to the dSPN mGluR5 KO to clarify if other sites of action are involved beyond the proposed D1-expressing neurons is missing. Finally, the authors present a working model that sets the stage for future experimentation. Overall, this study provides an important and detailed assessment of mGluR5 contributions to striatal circuit function and behavior.

Remaining concerns include:

(1) To clarify that dSPNs are sole site of action, it is necessary to examine effects of the mGlu5 NAM in the dSPN mGlu5 cKO mice. If the effects of the two manipulations occluded one another this would certainly support the hypothesis that the drug effects are mediated by receptors expressed in dSPNs. A similar argument can be made for examining effects of the JNJ PAM in the cKO mice.

(2) There is a concern that the D1 Cre line used (Ey262), which may also target cortical neurons expands the interpretation of the study beyond the striatal populations. Further discussion of this point, particularly in the interpretation of the mGluR5 cKO experiments, would provide a better understanding of the contribution of the paper.

(3) The use of CsF-based whole-cell internal solutions has caused concern in some past studies due to possible interference with G-protein, phosphatase and channel function (https://www.sciencedirect.com/science/article/abs/pii/S1044743104000296, https://www.jneurosci.org/content/jneuro/6/10/2915.full.pdf). It is reassuring the DHPG-induced LTD was still observable with this solution. However, it might be worth examining this plasticity with a different internal to ensure that the magnitude of the agonist effect is not altered by this manipulation.

(4) Behavioral resolution of actions at low velocity that are termed "rest" are not explored in this study. Thus, a remaining ambiguity is whether the activities in rest include only periods of immobility or other low-velocity activities such as grooming or rearing.

Reviewer #1 (Public review):

This work addresses an important question in the field of Drosophila aggression and mating. Prior social isolation is known to increase aggression in males, manifesting as increased lunging, which is suppressed by group housing (GH). However, it is also known that single housed (SH) males, despite their higher attempts to court females, are less successful. Here, Gao et al., develop a modified aggression assay to address this issue by recording aggression in Drosophila males for 2 hours, with a virgin female immobilized by burying its head in the food. They found that while SH males frequently lunge in this assay, GH males switch to higher intensity but very low frequency tussling. Constitutive neuronal silencing and activation experiments implicate cVA sensing Or67d neurons in promoting high frequency lunging, similar to earlier studies, whereas Or47b neurons promote low frequency but higher intensity tussling. Optogenetic activation revealed that three pairs of pC1SS2 neurons increase tussling. Cell-type-specific DsxM manipulations combined with morphological analysis of pC1SS2 neurons and side-by-side tussling quantification link the developmental role of DsxM to the functional output of these aggression-promoting cells. In contrast, although optogenetic activation of P1a neurons in the dark did not increase tussling, thermogenetic activation under visible light drove aggressive tussling. Using a further modified aggression assay, GH males exhibit increased tussling and maintain territorial control, which could contribute to a mating advantage over SH males, although direct measures of reproductive success are still needed

Strengths:

Through a series of clever neurogenetic and behavioral approaches, the authors implicate specific subsets of ORNs and pC1 neurons in promoting distinct forms of aggressive behavior, particularly tussling. They have devised a refined territorial control paradigm, which appears more robust than earlier assays. This new setup is relatively clutter-free and could be amenable to future automation using computer vision approaches. The updated Figure 5, which combines cell-type-specific developmental manipulation of pC1SS2 neurons with behavioral output, provides a link between developmental mechanisms and functional aggression circuits. The manuscript is generally well written, and the claims are largely supported by the data.

Weakness:

All prior concerns have been addressed in the revised manuscript. The added 'Limitations of the study' section is a welcome and important clarification. Despite these limitations, the study provides valuable insights into the neural and behavioral mechanisms of Drosophila aggression.

Reviewer #1 (Public review):

Summary:

This study provides compelling evidence suggesting that ghrelin, a molecule released in the surrounding of the major adult brain neurogenic niche (V-SVZ) by blood vessels with high blood flow controls the migration of newborn interneurons towards the olfactory bulbs.

Strengths:

This study is a tour de force as it provides a solid set of data obtained by time lapse recordings in vivo. The data demonstrate that the migration and guidance of newborn neurons relies on factors released by selective type of blood vessels.

Weaknesses:

Some intermediate conclusions are weak and may be reinforced by additional experiments.

Comments on revisions: The manuscript has improved.

Reviewer #1 (Public review):

Summary:

LRRK2 protein is familially linked to Parkinson's disease by the presence of several gene variants that all confer a gain-of-function effect on LRRK2 kinase activity.

The authors examine the effects of BDNF stimulation in immortalized neuron-like cells, cultured mouse primary neurons, hIPSC-derived neurons, and brain tissue from genetically modified mice. They examine a LRRK2 regulatory phosphorylation residue, LRRK2 binding relationships, and measures of synaptic structure and function.

Strengths:

The study addresses an important research question: how does a PD-linked protein interact with other proteins, and contribute to responses to a well-characterized neuronal signalling pathway involved in the regulation of synaptic function and cell health.

They employ a range of good models and techniques to fairly convincingly demonstrate that BDNF stimulation alters LRRK2 phosphorylation and binding to many proteins. IN this revised manuscript, aspects are well validated e.g., drebrin binding, but there is a disconnect between these findings and alterations to LRRK2 substrates. A convincing phosphoproteomic analysis of PD mutant Knock-in mouse brain is included. Overall the links between LRRK2, LRRK2 activity, and the changes to synaptic molecules, structures, and activity are intriguing.

Weaknesses:

The data sets remain disjointed, conclusions are sweeping, and not always in line with what the data is showing. Validation of 'omics' data is light. Some inconsistencies with the major conclusions are ignored. Several of the assays employed (western blotting especially) are underpowered, findings key to their interpretation are addressed in only one or other of the several models employed, and supporting observations are lacking.

Main Conclusions of Abstract:

(1) Increase in pLRRK2 Ser935 and pRAB after BDNF in SH-SY5Y & mouse neurons

Well supported, but only for pLRRK2 in neurons, why not pERK pAkt & pRab?

(2) Omics Proteome remodelling of LRRK2 interactome with BDNF & different in G2019S mouse neurons.

Supports that the phosphoproteome of G2019S is different. Drebrin interaction with LRRK2 very well supported. Link between drebrin and LRRK2 activity somewhat supported (pS935 site), but the consequence (non-specific pRab8) not supported, as there is no evidence of a change in LRRK2 substrate(s).

(3) Golgi 1 month LKO mouse altered dendritic spines, transient at 1m not older.

Supported but very small transient change in spines, disconnected to other results (e.g., drebrin).

(4) iPSC-derived neurons BDNF increases mEPSC frequency (transient at 70 not 50 or 90 days) in WT not KO "which appear to bypass this regulation through developmental compensation"

Weak, not clear what is being bypassed.

Main Conclusions Based on Old and New Figure / Data:

(1) Increase in pLRRK2 Ser935 and pRAB after BDNF in SH-SY5Y & mouse neurons

Well supported, but only for pLRRK2 in neurons, why not ERK Akt & Rab?

(2) BDNF promotes LRRK2 interaction with "post-synaptic actin cytoskeleton components"

Tone down, only one postsynaptic validated - drebrin strong BUT CONTRADICTORY; link between drebrin and LRRK2 activity (pS935 site) supported, consequence (non-specific pRab8) broken, no evidence of change in LRRK2 substrate.

(3) LRRK2 G2019S striatal phosphoproteome is different from WT.

It is different. Where is link to BDNF or Drebrin?

(4) BDNF signaling is impaired in Lrrk2 knockout neurons

TrkB changes seem higher in SHSY5Y. pAKT impaired, pERK not convincing. Primary neurons Akt slower but it and Erk mostly intact. MLi-2 did not block pAkt or pErk in WT or KO (higher in latter). Whatever is happening in KO, Mli-2 not really blocking effect in WT. If we are to assume that studying the KO was a means to understand LRRK2 function, the authors data should explain why we care if an effect is absent in LKO, if LRRK2 isn't doing the same job in WT?

BDNF increases synaptic puncta in WT not LKO (which start higher?). Is this BDNF increase blocked by LRRK2 inhibition?

(5) Postsynaptic structural changes in Lrrk2 knockout neurons

Golgi impregnation shows some very small spine changes at 1m. Not sustained over age. mRNA changes are very small (10% not even a fold... very weak and should be written as so). Derbrin levels reduced clearly at 1m, but probably also at 4 & 18. Underpowered, disconnected time course from the spine changes.

(6) An effect on "spontaneous electrical activity" at Div70

Weak. What is so special at 70 days that means we should be confident in the differences, or be satisfied that the other time points are legitimately ignored? These are 10-11 cells from 3 cultures assayed at 3 time points but only one is presented (rest in supplement). This should be a 2 (time) or 3 way (+culture RM) ANOVA. As it stands, in WT there is a little - no activity at 50 days, little to no at 70 days, and variable to lots or none at 90. BDNF did nothing at 50 or 90 but may have at 70. In KO low activity stable at 50 & 70, tanks at 90. BDNF would seem to have a similar effect on KO at 90 as WT at 70, but as there are only 7 cells it remains inconclusive. Thus the conclusion that BDNF signalling is broken in LKO is not well supported by the ephys data, nor is the BDNF effect in WT cells (even at the 70 day time point) shown to be susceptible to LRRK2 inhibition.

Reviewer #1 (Public review):

Summary:

In the submitted manuscript, Steinbach et al describe the formation of a detergent-resistant "cloud" around the Legionella-containing vacuole (LCV) that functions as a protective barrier. The authors show that formation of the "cloud" barrier is contingent upon the phosphoribosyl-ubiquitination activity of the SidE/SdeABC effector family, and is temporally regulated, with the assembly and subsequent disassembly of the "cloud" coinciding with replication and vacuolar expansion. The authors postulate a model of "cloud" barrier formation that relies upon a wave of initial ubiquitination by the SidC effector family, after which the SidE/SdeABC family expands the ubiquitination and forms cross-links that render the ubiquitin cloud resistant to harsh detergents. Additionally, Steinbach et al. also demonstrate that Rab5 is recruited to the LCV and remains associated for a considerable period.

Strengths:

This manuscript is very well written, with clear justification provided for experiments that make it very easy to follow along with the experimental logic. The figures have clearly been designed with much thought and are easy to interpret. Steinbach et al have also done a commendable job of addressing the previous reviewers' comments, even though some may suggest that some of these comments could be viewed as slightly unreasonable. This work would be of interest to both the Legionella and ubiquitin fields. Legionella researchers would potentially be interested to explore the proposed barrier model as the function for the ubiquitin "cloud," whereas ubiquitin researchers may be interested in exploring the mechanisms underlying SidE's crosslinking ability.

Weaknesses:

While the work is important and describes the physical nature of the ubiquitin cloud on the Legionella vacuole, it is somewhat descriptive in nature and does not dig deeply into what purpose this cloud serves. This is a complicated topic that will certainly stimulate additional research in this area.

Reviewer #1 (Public review):

Summary:

This paper developed a model of chromosome mosaicism by using a new aneuploidy-inducing drug (AZ3146), and compared this to their previous work where they used reversine, to demonstrate the fate of aneuploid cells during murine preimplantation embryo development. They found that AZ3146 acts similarly to reversine in inducing aneuploidy in embryos, but interestingly showed that the developmental potential of embryos is higher in AZ3146-treated vs. reversine-treated embryos. This difference was associated with changes in HIF1A, p53 gene regulation, DNA damage, and fate of euploid and aneuploid cells when embryos were cultured in a hypoxic environment.

Strengths:

In the current study, the authors investigate the fate of aneuploid cells in the preimplantation murine embryo using a specific aneuploidy-inducing compound to generate embryos that were chimeras of euploid and aneuploid cells. The strength of the work is that they investigate the developmental potential and changes in gene expression profiles under normoxic and hypoxic culture conditions. Further, they also assessed how levels of DNA damage and DNA repair are altered in these culture conditions. They also assessed the allocation of aneuploid cells to the divergent cell lineages of the blastocyst stage embryo.

Reviewer #1 (Public review):

The authors note that it is challenging to perform diffusion MRI tractography consistently in both humans and macaques, particularly when deep subcortical structures are involved. The scientific advance described in this paper is effectively an update to the tracts that the XTRACT software supports. The changes to XTRACT are soundly motivated in theory (based on anatomical tracer studies) and practice (changes in seeding/masking for tractography).

Reviewer #1 (Public review):

The manuscript by Zhang et al describes the use of a protein language model (pLM) to analyse disordered regions in proteins, with a focus on those that may be important in biological phase separation. While the paper is relatively easy to read overall, my main comment is that the authors could perhaps make it clearer which observations are new, and which support previous work using related approaches. Further, while the link to phase separation is interesting, it is not completely clear which data supports the statements made, and this could also be made clearer.

Major comments:

(1) With respect to putting the work in a better context of what has previously been done before, this is not to say that there is not new information in it, but what the authors do is somewhat closely related to work by others. I think it would be useful to make those links more directly. Some examples:

(1a) Alderson et al (reference 71) analysed in detail the conservation of IDRs (via pLDDT, which is itself related to conservation) to show, for example, that conserved residues fold upon binding. This analysis is very similar to the analysis used in the current study (using ESM2 as a different measure of conservation). Thus, the approach (pages 7-8) described as "This distinction allows us to classify disordered regions into two types: "flexible disordered" regions, which show high ESM2 scores and greater mutational tolerance, and "conserved disordered" regions, which display low ESM2 scores, indicating varying levels of mutational constraint despite a lack of stable folding." is fundamentally very similar to that used by Alderson et al. Thus, the result that "Given that low ESM2 scores generally reflect mutational constraint in folded proteins, the presence of region a among disordered residues suggests that certain disordered amino acids are evolutionarily conserved and likely functionally significant" is in some ways very similar to the results of that paper.

(1b) Dasmeh et al (https://doi.org/10.1093/genetics/iyab184), Lu et al (https://doi.org/10.1371/journal.pcbi.1010238) and Ho & Huang (https://doi.org/10.1002/pro.4317) analysed conservation in IDRs, including aromatic residues and their role in phase separation

(1c) A number of groups have performed proteomewide saturation scans using pLMs, including variants of the ESM family, including Meier (reference 89, but cited about something else) and Cagiada et al (https://doi.org/10.1101/2024.05.21.595203) that analysed variant effects in IDRs using a pLM. Thus, I think statements such as "their applicability to studying the fitness and evolutionary pressures on IDRs has yet to be established" should possibly be qualified.

(2) On page 4, the authors write, "The conserved residues are primarily located in regions associated with phase separation." These results are presented as a central part of the work, but it is not completely clear what the evidence is.

(3) It would be useful with an assessment of what controls the authors used to assess whether there are folded domains within their set of IDRs.

Reviewer #1 (Public review):

Summary:

In this review, the author covered several aspects of the inflammation response, mainly focusing on the mechanisms controlling leukocyte extravasation and inflammation resolution.

Strengths:

This review is based on an impressive number of sources, trying to comprehensively present a very broad and complex topic.

Weaknesses:

(1) This reviewer feels that, despite the title, this review is quite broad and not centred on the role of the extracellular matrix.

(2) The review will benefit from a stronger focus on the specific roles of matrix components and dynamics, with more informative subheadings.

(3) The macrophage phenotype section doesn't seem well integrated with the rest of the review (and is not linked to the ECM).

(4) Table 1 is difficult to follow. It could be reformatted to facilitate reading and understanding

(5) Figure 2 appears very complex and broad.

(6) Spelling and grammar should be thoroughly checked to improve the readability.

Reviewer #1 (Public Review):

Summary:

The work used open peer reviews and followed them through a succession of reviews and author revisions. It assessed whether a reviewer had requested the author include additional citations and references to the reviewers' work. It then assessed whether the author had followed these suggestions and what the probability of acceptance was based on the authors decision.

Strengths and weaknesses:

The work's strengths are the in-depth and thorough statistical analysis it contains and the very large dataset it uses. The methods are robust and reported in detail. However, this is also a weakness of the work. Such thorough analysis makes it very hard to read! It's a very interesting paper with some excellent and thought provoking references but it needs to be careful not to overstate the results and improve the readability so it can be disseminated widely. It should also discuss more alternative explanations for the findings and, where possible, dismiss them.

Reviewer #1 (Public review):

This study presents an exploration of PPGL tumour bulk transcriptomics and identifies three clusters of samples (labeled as subtypes C1-C3). Each subtype is then investigated for the presence of somatic mutations, metabolism-associated pathways and inflammation correlates, and disease progression.

The proposed subtype descriptions are presented as an exploratory study. The proposed potential biomarkers from this subtype are suitably caveated, and will require further validation in PPGL cohorts together with a mechanistic study.

The first section uses WGCNA (a method to identify clusters of samples based on gene expression correlations) to discover three transcriptome-based clusters of PPGL tumours.

The second section inspects a previously published snRNAseq dataset, and labels some of the published cells as subtypes C1, C2, C3 (Methods could be clarified here), among other cells labelled as immune cell types. Further details about how the previously reported single-nuclei were assigned to the newly described subtypes C1-C3 require clarification.

The tumour samples are obtained from multiple locations in the body (Figure 1A). It will be important to see further investigation of how the sample origin is distributed among the C1-C3 clusters, and whether there is a sample-origin association with mutational drivers and disease progression.

Reviewer #1 (Public review):

The manuscript by Zhang et al describes the use of a protein language model (pLM) to analyse disordered regions in proteins, with a focus on those that may be important in biological phase separation. This is an interesting study that supports, complements and extends previous related analyses on the conservation and mutational tolerance of disordered regions, with a particular focus on disordered regions in proteins that are found in condensates.

Reviewer #1 (Public review):

Summary:

In this descriptive study, Tateishi et al. report a Tn-seq based analysis of genetic requirements for growth and fitness in 8 clinical strains of Mycobacterium intracellulare Mi), and compare the findings with a type strain ATCC13950. The study finds a core set of 131 genes that are essential in all nine strains, and therefore are reasonably argued as potential drug targets. Multiple other genes required for fitness in clinical isolates have been found to be important for hypoxic growth in the type strain.

Strengths:

The study has generated a large volume of Tn-seq datasets of multiple clinical strains of Mi from multiple growth conditions, including from mouse lungs. The dataset can serve as an important resource for future studies on Mi, which despite being clinically significant remains a relatively understudied species of mycobacteria.

Weaknesses:

The primary claim of the study that the clinical strains are better adapted for hypoxic growth is yet to be comprehensively investigated. However, this reviewer thinks such an investigation would require a complex experimental design and perhaps forms an independent study.

Reviewer #1 (Public review):

Summary:

The present study evaluates the role of visual experience in shaping functional correlations between human extrastriate visual cortex and frontal regions. The authors used fMRI to assess "resting-state" temporal correlations in three groups: sighted adults, congenitally blind adults, and neonates. Previous research has already demonstrated differences in functional correlations between visual and frontal regions in sighted compared to early blind individuals. The novel contribution of the current study lies in the inclusion of an infant dataset, which allows for an assessment of the developmental origins of these differences.

The main results of the study reveal that correlations between prefrontal and visual regions are more prominent in the blind and infant groups, with the blind group exhibiting greater lateralization. Conversely, correlations between visual and somato-motor cortices are more prominent in sighted adults. Based on these data, the authors conclude that visual experience plays an instructive role in shaping these cortical networks. This study provides valuable insights into the impact of visual experience on the development of functional connectivity in the brain.

Strengths:

The dissociations in functional correlations observed among the sighted adult, congenitally blind, and neonate groups provide strong support for the main conclusion regarding postnatal experience-driven shaping of visual-frontal connectivity.

The inclusion of neonates offers a unique and valuable developmental anchor for interpreting divergence between blind and sighted adults. This is a major advance over prior studies limited to adult comparisons.

Convergence with prior findings in the blind and sighted adult groups reinforces the reliability and external validity of the present results.

The split-half reliability analysis in the infant data increases confidence in the robustness of the reported group differences.

Weaknesses:

The manuscript risks overstating a mechanistic distinction between sighted and blind development by framing visual experience as "instructive" and blindness as "reorganizing." Similarly, the binary framing of visual experience and blindness as independent may oversimplify shared plasticity mechanisms.

The interpretation of changes in temporal correlations as altered neural communication does not adequately consider how shifts in shared variance across networks may influence these measures without reflecting true biological reorganization.

The discussion does not substantively engage with the longstanding debate over whether sensory experience plays an instructive or permissive role in cortical development.

The relationship between resting-state and task-based findings in blindness remains unclear.

Reviewer #1 (Public review):

Summary:

The work by Fisher et al describes the role of novel RSPO mimetics in the activation of WNT signaling and hepatocyte regeneration. However, the results of the experiments and weaknesses of the methods used do not support the conclusions of the authors that the new therapy can promote liver regeneration in alcohol-induced liver cirrhosis.

Strengths:

Similarly to its precursor, aASGR1-RSPO2-RA-IgG, SZN-043 can upregulate Wnt target genes and promote hepatocyte proliferation in the liver.

Comments on revisions:

The authors responded to all my comments and concerns.

Joint Public Review:

This study employs single-cell RNA sequencing to investigate how electroacupuncture (EA) stimulation alters the transcriptional profiles of central nervous system cell types following blood-brain barrier (BBB) opening. The authors seek to characterize changes in gene expression and pathway activities across diverse neural cells in response to electroacupuncture (EA) stimulation using high-resolution transcriptomics. This approach has the potential to elucidate the cellular mechanisms underlying EA stimulation and their implications for therapeutic intervention. The work engages with a timely and biologically significant question regarding noninvasive stimulation methods to manipulate BBB permeability. However, no in vivo/in vitro functional assays are provided to validate the changes in BBB permeability or cytokine release in the tested models. The experimental rationale remains inadequately explained, and key details regarding the magnitude, duration, and spatial distribution of BBB opening in this system are still lacking.

Reviewer #1 (Public review):

Summary:

The authors analyzed the expression of ATAD2 protein in post-meiotic stages and characterized the localization of various testis-specific proteins in the testis of the Atad2 knockout (KO). By cytological analysis as well as the ATAC sequencing, the study showed that increased levels of HIRA histone chaperone, accumulation of histone H3.3 on post-meiotic nuclei, defective chromatin accessibility and also delayed deposition of protamines. Sperm from the Atad2 KO mice reduces the success of in vitro fertilization. The work was performed well, and most of the results are convincing. However, this manuscript does not suggest a molecular mechanism for how ATAD2 promotes the formation of testis-specific chromatin.

Strengths:

The paper describes the role of ATAD2 AAA+ ATPase in the proper localization of sperm-specific chromatin proteins such as protamine, suggesting the importance of the DNA replication-independent histone exchanges with the HIRA-histone H3.3 axis.

Weaknesses:

(1) Some results lack quantification.

(2) The work was performed well, and most of the results are convincing. However, this manuscript does not suggest a molecular mechanism for how ATAD2 promotes the formation of testis-specific chromatin.

Reviewer #1 (Public review):

Summary:

Desveaux et al. describe human mAbs targeting protein from the Pseudomonas aeruginosa T3SS, discovered by employing single cell B cell sorting from cystic fibrosis patients. The mAbs were directed at the proteins PscF and PcrV. They particularly focused on two mAbs binding the T3SS with the potential of blocking activity. The supplemented biochemical analysis was crystal structures of P3D6 Fab complex. They also compared the blocking activity with mAbs that were described in previous studies, using an assay that evaluated the toxin injection. They conducted mechanistic structure analysis and found that these mAbs might act through different mechanisms by preventing PcrV oligomerization and disrupting PcrVs scaffolding function.

The antibiotic resistance crisis requires the development of new solutions to treat infections cause by MDR bacteria. The development of antibacterial mAbs holds great potential. In that context, this report is important as it paves the way for the development of additional mAbs targeting various pathogens that harbor the T3SS. In this report the authors present a comparative study of their discovered mAbs vs. a commercial mAb currently in clinical testing resulting in valuate data with applicative implications. The authors investigated the mechanism of action of the mAbs using advanced methods and assays for characterization of antibody and antigen interaction, underlining the effort to determine the discovered mAbs suitability for downstream application.

Reviewer #1 (Public review):

Summary:

The authors investigated the elasticity of controllability by developing a task that manipulates the probability of achieving a goal with a baseline investment (which they refer to as inelastic controllability) and the probability that additional investment would increase the probability of achieving a goal (which they refer to as elastic controllability). They found that a computational model representing the controllability and elasticity of the environment accounted better for the data than a model representing only the controllability. They also found that prior biases about the controllability and elasticity of the environment was associated with a composite psychopathology score. The authors conclude that elasticity inference and bias guide resource allocation.

Strengths:

This research takes a novel theoretical and methodological approach to understanding how people estimate the level of control they have over their environment, and how they adjust their actions accordingly. The task is innovative and both it and the findings are well-described (with excellent visuals). They also offer thorough validation for the particular model they develop. The research has the potential to theoretically inform understanding of control across domains, which is a topic of great importance.

Weaknesses:

In its revised form, the manuscript addresses most of my previous concerns. The main remaining weakness pertains to the analyses aimed at addressing my suggesting of Bayesian updating as an alternative to the model proposed by the authors. My suggestion was to assume that people perform a form of function approximation to relate resource expenditure to success probability. The authors performed a version of this where people were weighing evidence for a few canonical functions (flat, step, linear), and found that this model underperforms theirs. However, this Bayesian model is quite constrained in its ability to estimate the function relating resources. A more robust test would be to assume a more flexible form of updating that is able to capture a wide range of distributions (e.g., using basis functions, gaussian processes, or nonparametric estimators); see, e.g., work by Griffiths on human function learning). The benefit of testing this type of model is that it would make contact with a known form of inference that individuals engage in across various settings, and therefore could offer a more parsimonious and generalizable account of function learning, whereby learning of resource elasticity is a special case. I defer to the authors as to whether they'd like to pursue this direction, but if not I think it's still important that they acknowledge that they are unable to rule out a more general process like this as an alternative to their model. This also pertains to inferences about individual differences, which currently hinge on their preferred model being the most parsimonious.

Reviewer #1 (Public review):

Summary:

This study addresses the important question of how top-down cognitive processes affect tactile perception in autism - specifically, in the Fmr1-/y genetic mouse model of autism. Using a 2AFC tactile task in behaving mice, the study investigated multiple aspects of perceptual processing, including perceptual learning, stimulus categorization and discrimination, as well as the influence of prior experience and attention.

Strengths:

The experiments seem well performed, with interesting results. Thus, this study can/will advance our understanding of atypical tactile perception and its relation to cognitive factors in autism.

Weaknesses:

Certain aspects of the analyses (and therefore the results) are unclear, which makes the manuscript difficult to understand. Clearer presentation, with the addition of more standard psychometric analyses, and/or other useful models (like logistic regression) would improve this aspect. The use of d' needs better explanation, both in terms of how and why these analyses are appropriate (and perhaps it should be applied for more specific needs rather than as a ubiquitous measure).

Reviewer #1 (Public review):

Summary:

This study generated 3D cell constructs from endometrial cell mixtures that were seeded in the Matrigel scaffold. The cell assemblies were treated with hormones to induce a "window of implantation" (WOI) state. Although many bioinformatic analyses point in this direction, there are major concerns that must be addressed.

Strengths:

The addition of 3 hormones to enhance the WOI state (although not clearly supported in comparison to the secretory state).

Comments on revisions:

The authors did their best to revise their study according to the Reviewers' comments. However, the study remains unconvincing, incomplete and at the same time still too dense and not focused enough.

Reviewer #1 (Public review):

This manuscript reports a dual-task experiment intended to test whether language prediction relies on executive resources, using surprisal-based measures of predictability and an n-back task to manipulate cognitive load. While the study addresses a question under debate, the current design and modeling framework fall short of supporting the central claims. Key components of cognitive load, such as task switching, word prediction vs integration, are not adequately modeled. Moreover, the weak consistency in replication undermines the robustness of the reported findings. Below unpacks each point.

Cognitive load is a broad term. In the present study, it can be at least decomposed into the following components:

(1) Working memory (WM) load: news, color, and rank.

(2) Task switching load: domain of attention (color vs semantics), sensorimotor rules (c/m vs space).

(3) Word comprehension load (hypothesized against): prediction, integration.

The components of task switching load should be directly included in the statistical models. Switching of sensorimotor rules may be captured by the "n-back reaction" (binary) predictor. However, the switching of attended domains and the interaction between domain switching and rule complexity (1-back or 2-back) were not included. The attention control experiment (1) avoided useful statistical variation from the Read Only task, and (2) did not address interactions. More fundamentally, task-switching components should be directly modeled in both performance and full RT models to minimize selection bias. This principle also applies to other confounding factors, such as education level. While missing these important predictors, the current models have an abundance of predictors that are not so well motivated (see later comments). In sum, with the current models, one cannot determine whether the reduced performance or prolonged RT was due to affecting word prediction load (if it exists) or merely affecting the task switching load.

The entropy and surprisal need to be more clearly interpreted and modeled in the context of the word comprehension process. The entropy concerns the "prediction" part of the word comprehension (before seeing the next word), whereas surprisal concerns the "integration" part as a posterior. This interpretation is similar to the authors writing in the Introduction that "Graded language predictions necessitate the active generation of hypotheses on upcoming words as well as the integration of prediction errors to inform future predictions [1,5]." However, the Results of this study largely ignored entropy (treating it as a fixed effect) and only focus on surprisal without clear justification.

In Table S3, with original and replicated model fitting results, the only consistent interaction is surprisal x age x cognitive load [2-back vs. Reading Only]. None of the two-way interactions can be replicated. This is puzzling and undermines the robustness of the main claims of this paper.

Reviewer #1 (Public review):

Summary:

The researchers sought to determine whether Ptbp1, an RNA-binding protein formerly thought to be a master regulator of neuronal differentiation, is required for retinal neurogenesis and cell fate specification. They used a conditional knockout mouse line to remove Ptbp1 in retinal progenitors and analyzed the results using bulk RNA-seq, single-cell RNA-seq, immunohistochemistry, and EdU labeling. Their findings show that Ptbp1 deletion has no effect on retinal development, since no defects were found in retinal lamination, progenitor proliferation, or cell type composition. Although bulk RNA-seq indicated changes in RNA splicing and increased expression of late-stage progenitor and photoreceptor genes in the mutants, and single-cell RNA-seq detected relatively minor transcriptional shifts in Müller glia, the overall phenotypic impact was low. As a result, the authors conclude that Ptbp1 is not required for retinal neurogenesis and development, thus contradicting prior statements about its important role as a master regulator of neurogenesis. They argue for a reassessment of this stated role. While the findings are strong in the setting of the retina, the larger implications for other areas of the CNS require more investigation. Furthermore, questions about potential reimbursement from Ptbp2 warrant further research.

Strengths:

This study calls into doubt the commonly held belief that Ptbp1 is a critical regulator of neurogenesis in the CNS, particularly in retinal development. The adoption of a conditional knockout mouse model provides a reliable way for eliminating Ptbp1 in retinal progenitors while avoiding the off-target effects often reported in RNAi experiments. The combination of bulk RNA-seq, scRNA-seq, and immunohistochemistry enables a thorough examination of molecular and cellular alterations at both embryonic and postnatal stages, which strengthens the study's findings. Furthermore, using publicly available RNA-Seq datasets for comparison improves the investigation of splicing and expression across tissues and cell types. The work is well-organized, with informative figure legends and supplemental data that clearly show no substantial phenotypic changes in retinal lamination, proliferation, or cell destiny, despite identified transcriptional and splicing modifications.

Weaknesses:

The retina-specific method raises questions regarding whether Ptbp1 is required in other CNS locations where its neurogenic roles were first proposed. The claim that Ptbp1 is "fully dispensable" for retinal development may be toned down, given the transcriptional and splicing modifications identified. The possibility of subtle or transitory impacts, such as ectopic neuron development followed by cell death, is postulated, but not completely investigated. Furthermore, as the authors point out, the compensating potential of increased Ptbp2 warrants additional exploration. Although the study performs well in transcriptome and histological analyses, it lacks functional assessments (such as electrophysiological or behavioral testing) to determine if small changes in splicing or gene expression affect retinal function. While 864 splicing events have been found, the functional significance of these alterations, notably the 7% that are neuronal-enriched and the 35% that are rod-specific, has not been thoroughly investigated. The manuscript might be improved by describing how these splicing changes affect retinal development or function.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors aim to elucidate the mechanisms by which grid cells in the medial entorhinal cortex generate predictive representations of spatial location. To address this, they built a computational model integrating intrinsic neuronal dynamics with structured network connectivity. Specifically, they combine a conductance-based single-cell model incorporating biologically realistic HCN channels with a continuous attractor network that reflects known properties of grid cell circuitry. Their simulations show that HCN conductance can shift grid fields forward by approximately 5% of their diameter, consistent with experimental observations in layer II grid cells. Additionally, by introducing asymmetry in the connectivity of interneurons, the model produces larger forward shifts, which parallel properties observed in layer III grid cells. Together, these two mechanisms provide a unified framework for explaining layer-specific predictive coding in the entorhinal cortex.

Strengths:

A major strength of the study lies in its conceptual contribution. The authors propose two distinct mechanisms to generate forward-shifted grid fields for predictive coding. One mechanism is intrinsic and depends on the time constants associated with HCN channels. The other is network-based and results from asymmetries in interneuron connectivity. These two mechanisms correspond to different observed properties of grid cells in layer II and layer III, respectively. The modeling is based on previously validated frameworks of continuous attractor network models (e.g., Burak & Fiete; Kang & DeWeese), but it incorporates several novel features, including the incorporation of biophysically realistic HCN channels, a network architecture that excludes stellate-stellate connections and relies on interneurons, and asymmetric interneuron connectivity.

Weaknesses:

One of the proposed mechanisms for predictive coding, namely asymmetric interneuron connectivity, is a novel idea. However, this type of connectivity has not yet been demonstrated experimentally in the medial entorhinal cortex. Therefore, the biological plausibility of this mechanism remains uncertain and will need to be evaluated in future empirical studies.

Reviewer #1 (Public review):

Summary:

This paper addresses an important and topical issue: how temporal context - at various time scales - affects various psychophysical measures, including reaction times, accuracy and localization. It offers interesting insights, with separate mechanisms for different phenomena, which are well discussed.

Strengths:

The paradigm used is original and effective. The analyses are rigorous.

Comments on revised version:

I think the authors have dealt adequately with my issues, none of which were fundamental.

Reviewer #1 (Public review):

Summary:

This manuscript by Zung et al. describes a curated library of genetic lines labeling a class of important neurons called Descending Neurons in the fruit fly, Drosophila melanogaster. These neurons are especially important in their critical role in relaying information from the brain to motor circuits within the ventral nerve cord - the insect analogy of the vertebrate spinal cord. The authors screened through a vast resource of Gal4 lines to generate 500 new genetic lines that allow for the precise labeling of 190 (40%) of all Descending Neurons. The tools introduced here will allow researchers to perform precise circuit dissection of the exact roles these neurons play in linking the brain to the ventral nerve cord.

Strengths:

This manuscript represents an important follow-up to the author's 2018 paper in the extension of the genetic toolkit from 178 genetic lines that target 65 Descending Neuron (DN) classes to 806 lines that target 190 DN classes. The presentation of this toolkit is comprehensive with confocal images, informative classifications of lines based on specificity/consistency, and identification of the neuron types - when possible - in the EM dataset.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #1 (Public review):

SARS-CoV-2 encodes a macrodomain (Mac1) within the nsp3 protein that removes ADP-ribose groups from proteins. However, its role during infection is not well understood. Evidence suggests that Mac1 antagonizes the host interferon response by counteracting the wave of ADP ribosylation that occurs during infection. Indeed, several PARPs are interferon-stimulated genes. While multiple targets have been proposed, the mechanistic links between ADP ribosylation and a robust antiviral response remain unclear.

Genetic inactivation of Mac1 abrogates viral replication in vivo, suggesting that small-molecule inhibitors of Mac1 could be developed into antivirals to treat COVID-19 and other emerging coronaviruses. The authors report a potent and selective small molecule inhibitor targeting Mac1 (AVI-4206) that demonstrates efficacy in human airway organoids and animal models of SARS-CoV-2 infection. While these results are compelling and provide proof of concept for the therapeutic targeting of Mac1, I am particularly intrigued by the potential of this compound as a probe to elucidate the mechanistic connections between infection-induced ADP ribosylation and the host antiviral response.

The precise function of Mac1 remains unclear. Given its presence in multiple viruses, it likely acts on a fundamental host immune pathway(s). AVI-4206, while promising as a lead compound for the development of antivirals targeting coronaviruses, could also be a valuable tool for uncovering the function of the Mac1 domain. This may lead to fundamental insights into the host immune response to viral infection.

Reviewer #2 (Public review):

Summary:

The manuscript, by Xu and Peng, et al. investigates whether co-expression of 2 T cell receptor (TCR) clonotypes can be detected in FoxP3+ regulatory CD4+ T cells (Tregs) and if it is associated with identifiable phenotypic effects. This paper presents data reanalyzing publicly available single-cell TCR sequencing and transcriptional analysis, convincingly demonstrating that dual TCR co-expression can be detected in Tregs, both in peripheral circulation as well as among Tregs in tissues. They then compare metrics of TCR diversity between single-TCR and dual TCR Tregs, as well as between Tregs in different anatomic compartments, finding the TCR repertoires to be generally similar though with dual TCR Tregs exhibiting a less diverse repertoire and some moderate differences in clonal expansion in different anatomic compartments. Finally, they examine the transcriptional profile of dual TCR Tregs in these datasets, finding some potential differences in expression of key Treg genes such as Foxp3, CTLA4, Foxo3, Foxo1, CD27, IL2RA, and Ikzf2 associated with dual TCR-expressing Tregs, which the authors postulate implies a potential functional benefit for dual TCR expression in Tregs.

Strengths:

This report examines an interesting and potentially biologically significant question, given recent demonstrations that dual TCR co-expression is a much more common phenomenon than previously appreciated (approximately 15-20% of T cells) and that dual TCR co-expression has been associated with significant effects on the thymic development and antigenic reactivity of T cells. This investigation leverages large existing datasets of single-cell TCRseq/RNAseq to address dual TCR expression in Tregs. The identification and characterization of dual TCR Tregs is rigorously demonstrated and presented, providing convincing new evidence of their existence.

Weaknesses:

The existence of dual TCR expression by Tregs has previously been demonstrated in mice and humans, limiting the novelty of the reported findings. The presented results should be considered in the context of these prior important findings. The focus on self-citation of their previous work, using the same approach to measure dual TCR expression in other datasets. limits the discussion of other more relevant and impactful published research in this area. Also, Reference #7 continues to list incorrect authors. The authors do not present a balanced or representative description of the available knowledge about either dual TCR expression by T cells or TCR repertoires of Tregs.

The approach used follows a template used previously by this group for re-analysis of existing datasets generated by other research groups. The descriptions and interpretations of the data as presented are still shallow, lacking innovative or thoughtful approaches that would potentially be innovation or provide new insight.

This demonstration of dual TCR Tregs is notable, though the authors do not compare the frequency of dual TCR co-expression by Tregs with non-Tregs. This limits interpreting the findings in the context of what is known about dual TCR co-expression in T cells. The response to this criticism in a previous review is considered non-responsive and does not improve the data or findings.

Comparison of gene expression by single- and dual TCR Tregs is of interest, but as presented is difficult to interpret. The interpretations of the gene expression analyses are somewhat simplistic, focusing on single-gene expression of some genes known to have function in Tregs. However, the investigators continue to miss an opportunity to examine larger patterns of coordinated gene expression associated with developmental pathways and differential function in Tregs (Yang. 2015. Science. 348:589; Li. 2016. Nat Rev Immunol. Wyss. 2016. 16:220; Nat Immunol. 17:1093; Zenmour. 2018. Nat Immunol. 19:291). No attempt to define clusters is made. No comparison is made of the proportions of dual TCR cells in transcriptionally-defined clusters. The broad assessment of key genes by single- and dual TCR cells is conceptually interesting, but likely to be confounded by the heterogeneity of the Treg populations. This would need to be addressed and considered to make any analyses meaningful.

The study design, re-analysis of existing datasets generated by other scientific groups, precludes confirmation of any findings by orthogonal analyses.

Reviewer #1 (Public review):

Summary:

This work proposes a new approach to analyse cell-count data from multiple brain regions. Collecting such data can be expensive and time-intensive, so, more often than not, the dimensionality of the data is larger than the number of samples. The authors argue that Bayesian methods are much better suited to correctly analyse such data compared to classical (frequentist) statistical methods. They define a hierarchical structure, partial pooling, in which each observation contributes to the population estimate to more accurately explain the variance in the data. They present two case studies in which their method proves more sensitive in identifying regions where there are significant differences between conditions, which otherwise would be hidden.

Strengths:

The model is presented clearly, and the advantages of the hierarchical structure are strongly justified. Two alternative ways are presented to account for the presence of zero counts. The first involves the use of a horseshoe prior, which is the more flexible option, while the second involves a modified Poisson likelihood, which is better suited to datasets with a large number of zero counts, perhaps due to experimental artifacts. The results show a clear advantage of the Bayesian method for both case studies.<br /> The code is freely available, and it does not require a high-performance cluster to execute for smaller datasets. As Bayesian statistical methods become more accessible in various scientific fields, the whole scientific community will benefit from the transition away from p-values. Hierarchical Bayesian models are an especially useful tool that can be applied to many different experimental designs. However, while conceptually intuitive, their implementation can be difficult. The authors provide a good framework with room for improvement.

Weaknesses:

As with any Bayesian model, the choice of prior can significantly influence the results. The authors explain how the methodology can be adapted to different data properties, though selecting an appropriate prior or likelihood may not always be straightforward. They propose a 'standard workflow' as an alternative to traditional approaches, which could and should be used alongside established methods while Bayesian techniques continue to evolve and improve.

Reviewer #1 (Public review):

Summary

Xu et al. use transcriptomic comparisons of mouse cochlear and vestibular hair to show that the vestibular hair cells alone are enriched in gene expression for proteins necessary for cilia motility and to further argue that such motility is a normal function of the kinocilia.

Background:

Cilia are prominent in sensory receptors, including vertebrate photoreceptors, olfactory neurons, and mechanosensitive hair cells of the inner ear and lateral line. Cilia can be motile or nonmotile depending on their axonemal structure: motile cilia require dynein and the inner 2 singlet microtubules of the 9+2 array. Primary cilia, present early in development, are considered to have sensory functions and to be nonmotile (Mill et al., Nature Rev Gen 2023).

In hair cells, the kinocilium anchors and polarizes the mechanosensitive hair bundle of specialized microvilli. The kinocilium matures from the primary cilium of a newborn hair cell; behind it, the bundle of mechanosensory microvilli rises in a descending staircase of rows. During maturation of the mammalian cochlea, all hair cells lose the kinocilium, though not the associated basal body. The consensus for many years has been that most vertebrate kinocilia, and especially mammalian kinocilia, are nonmotile, based largely on the lack of spontaneous motility in excised mammalian vestibular organs, but also on the impression that the rare examples of spontaneous beating motility even in non-mammalian hair cells are associated with deterioration of the preparation (Rüsch & Thurm 1990).

Strengths

In comparing RNA expression across the 4 major types of mouse hair cells - 2 cochlear and 2 vestibular - Xu et al. noted that some ciliary genes related to motility are expressed by vestibular but not cochlear hair cells. They curated the ciliary genes into types known to be associated with different aspects of beating motility, and also investigated the expression of genes typical of primary cilia, which are considered to have sensory and cell signaling functions and to be nonmotile. They add immunostaining to back up some of the RNA data, and also evaluate relative expression by neonatal mouse cochlear and vestibular hair cells from a published dataset. The focus on kinociliary genes is an appropriate use of the comparative expression data for cochlear and vestibular hair cells, and the paper overall is readable and interesting. The transcriptome data are rounded off by comparing the authors' results in adult hair cells with published neonatal mouse cochlear and vestibular transcriptomes.

Weaknesses:

(1) Data:

a) The main weakness in the data is the lack of functional and anatomical data from mouse hair bundles. While the authors compensate in part for this difficulty with bullfrog crista bundles, those data are also fragmentary - one TEM and 2 exemplar videos. Much of the novelty of the EM depends on the different appearance of stretches of a single kinocilium - can we be sure of the absence of the central microtubule singlets at the ends?

b) While it was a good idea to compare ciliary motility expression in published P2 datasets for mouse cochlear and vestibular hair cells for comparison with the authors' adult hair cell data, the presentation is too superficial to assess (Figure 6C-E; text from line 336) - it is hard to see the basis for concluding that motility genes are specifically lower in P2 cochlear hair cells than vestibular hair cells. Visually, it is striking that CHCs have much darker bands for about 10 motility-related genes.

(2) Interpretation:

The authors take the view that kinociliary motility is likely to be normally present but is rare in their observations because the conditions are not right. But while others have described some (rare) kinociliary motility in fish organs (Rusch & Thurm 1990), they interpreted its occurrence as a sign of pathology. Indeed, in this paper, it is not clear, or even discussed, how kinociliary motility would help with mechanosensitivity in mature hair bundles. Rather, the presence of an autonomous rhythm would actively interfere with generating temporally faithful representations of the head motions that drive vestibular hair cells.

Could kinociliary beating play other roles, possibly during development - for example, by interacting with forming accessory structures (but see Whitfield 2020) or by activating mechanosensitivity cell-autonomously, before mature stimulation mechanisms are in place? Then a latent capacity to beat in mature vestibular hair cells might be activated by stressful conditions, as speculated regarding persistent Piezo channels that are normally silent in mature cochlear hair cells but may reappear when TMC channel gating is broken (Beurg and Fettiplace 2017). While these are highly speculative thoughts, there is a need in the paper for more nuanced consideration of whether the observed motility is normal and what good it would do.

Reviewer #1 (Public review):

Summary:

The authors aim to explore the effects of the electrogenic sodium-potassium pump (Na+/K+-ATPase) on the computational properties of highly active spiking neurons, using the weakly-electric fish electrocyte as a model system. Their work highlights how the pump's electrogenicity, while essential for maintaining ionic gradients, introduces challenges in neuronal firing stability and signal processing, especially in cells that fire at high rates. The study identifies compensatory mechanisms that cells might use to counteract these effects, and speculates on the role of voltage dependence in the pump's behavior, suggesting that Na+/K+-ATPase could be a factor in neuronal dysfunctions and diseases

Strengths:

(1) The study explores a less-examined aspect of neural dynamics-the effects of Na+/K+-ATPase electrogenicity. It offers a new perspective by highlighting the pump's role not only in ion homeostasis but also in its potential influence on neural computation.

(2) The mathematical modeling used is a significant strength, providing a clear and controlled framework to explore the effects of the Na+/K+-ATPase on spiking cells. This approach allows for the systematic testing of different conditions and behaviors that might be difficult to observe directly in biological experiments.

(3) The study several interesting compensatory mechanisms, such as sodium leak channels and extracellular potassium buffering, which provide useful theoretical frameworks for understanding how neurons maintain firing rate control despite the pump's effects.

Comments on revisions:proposes

The revised manuscript is notably improved.

Reviewer #1 (Public review):

Summary:

The authors developed a sequence-based method to predict drug-interacting residues in IDP, based on their recent work, to predict the transverse relaxation rates (R2) of IDP trained on 45 IDP sequences and their corresponding R2 values. The discovery is that the IDPs interact with drugs mostly using aromatic residues that are easy to understand, as most drugs contain aromatic rings. They validated the method using several case studies, and the predictions are in accordance with chemical shift perturbations and MD simulations. The location of the predicted residues serves as a starting point for ligand optimization.

Strengths:

This work provides the first sequence-based prediction method to identify potential drug-interacting residues in IDP. The validity of the method is supported by case studies. It is easy to use, and no time-consuming MD simulations and NMR studies are needed.

Weaknesses:

The method does not depend on the information of binding compounds, which may give general features of IDP-drug binding. However, due to the size and chemical structures of the compounds (for example, how many aromatic rings), the number of interacting residues varies, which is not considered in this work. Lacking specific information may restrict its application in compound optimization, aiming to derive specific and potent binding compounds.

Comments on revised version:

I'm satisfied with the authors' response and the public review does not need further changes.

Reviewer #1 (Public review):

Summary:

In this study, the authors explore a novel mechanism linking aging to chromosome mis-segregation and aneuploidy in yeast cells. They reveal that, in old yeast mother cells, chromosome loss occurs through asymmetric partitioning of chromosomes to daughter cells, a process coupled with the inheritance of an old Spindle Pole Body. Remarkably, the authors identify that remodeling of the nuclear pore complex (NPC), specifically the displacement of its nuclear basket, triggers these asymmetric segregation events. This disruption also leads to the leakage of unspliced pre-mRNAs into the cytoplasm, highlighting a breakdown in RNA quality control. Through genetic manipulation, the study demonstrates that removing introns from key chromosome segregation genes is sufficient to prevent chromosome loss in aged cells. Moreover, promoting pre-mRNA leakage in young cells mimics the chromosome mis-segregation observed in old cells, providing further evidence for the critical role of nuclear envelope integrity and RNA processing in aging-related genome instability.

Strengths:

The findings presented are not only intriguing but also well-supported by robust experimental data, highlighting a previously unrecognized connection between nuclear envelope integrity, RNA processing, and genome stability in aging cells, deepening our understanding of the molecular basis of chromosome loss in aging.

Weaknesses:

The authors have satisfactorily addressed my concerns.

Reviewer #1 (Public review):

Summary:

The authors demonstrate with a simple stochastic model that the initial composition of the community is important in achieving a target frequency during the artificial selection of a community.

Strengths:

To my knowledge, the intra-collective selection during artificial selection has not been seriously theoretically considered. However, in many cases, the species dynamics during the incubation of each selection cycle is important and relevant to the outcome of the artificial selection experiment. Stochasticity from birth and death (demographic stochasticity) plays a big role in these species' abundance dynamics. This work uses a simple framework to tackle this idea meticulously.

This work may or may not be related to hysteresis (path dependency). If this is true, maybe it would be nice to have a discussion paragraph talking about how this may be the case. Then, this work would even attract the interest of people studying dynamical systems.

Weaknesses:

(1) Connecting structure and function.<br /> In typical artificial selection literature, most of them select the community based on collective function. Here in this paper, the authors are selecting a target composition. Although there is a schematic cartoon illustrating the relationship between collective function (y-axis) and the community composition in the main figure 1, there is no explicit explanation or justification of what may be the origin of this relationship. I think giving the readers a naïve idea about how this structure-function relationship arises in the introduction section would help. This is because the conclusion of this paper is that the intra-collective selection makes it hard to artificially select for a community that has an intermediate frequency of f (or s). If there is really evidence or theoretical derivation from this framework that indeed the highest function comes from the intermediate frequency of f, then the impact of this paper would increase because the conclusions of this stochastic model could allude to the reasons for the prevalent failures of artificial selection in literature.

(2) Explain intra-collective and inter-collective selection better for readers.<br /> The abstract, the introduction, and the result section use these terms or intra-collective and inter-collective selection without much explanation. For the wide readership of eLife, a clear definition in the beginning would help the audience grasp the importance of this paper, because these concepts are at the core of this work.

(3) Achievable target frequency strongly depending on the degree of demographic stochasticity.<br /> I would expect that the experimentalists would find these results interesting and would want to consider these results during their artificial selection experiments. The main figure 4 indicates that the Newborn size N0 is a very important factor to consider during the artificial selection experiment. This would be equivalent to how much bottleneck you impose on the artificial selection process in every iteration step (i.e., the ratio of serial dilution experiment). However, with a low population size, all target frequencies can be achieved, and therefore in these regimes, the initial frequency now does not matter much. It would be great for the authors to provide what the N0 parameter actually means during the artificial selection experiments. Maybe relative to some other parameter in the model. I know this could be very hard. But without this, the main result of this paper (initial frequency matters) cannot be taken advantage of by the experimentalists.

(4) Consideration of environmental stochasticity.<br /> The success (gold area of Figure 2d) in this framework mainly depends on the size of the demographic stochasticity (birth-only model) during the intra-collective selection. However, during experiments, a lot of environmental stochasticity appears to be occurring during artificial selection. This may be out of the scope of this study. But it would definitely be exciting to see how much environmental stochasticity relative to the demographic stochasticity (variation in the Gaussian distribution of F and S) matters in succeeding in achieving the target composition from artificial selection.

(5) Assumption about mutation rates<br /> If setting the mutation rates to zero does not change the result of the simulations and the conclusion, what is the purpose of having the mutation rates \mu? Also, is the unidirectional (S -> F -> FF) mutation realistic? I didn't quite understand how the mutations could fit into the story of this paper.

(6) Minor points<br /> In Figure 3b, it is not clear to me how the frequency difference for the Intra-collective and the Inter-collective selection is computed.<br /> In Figure 5b, the gold region (success) near the FF is not visible. Maybe increase the size of the figure or have an inset for zoom-in. Why is the region not as big as the bottom gold region?

Comments on revisions:

I thank the authors for addressing many points raised by the reviewers. Overall, the readability of the manuscript has improved with more context provided around why they were solving this specific problem. However, I've found many of the responses to be too terse. It would have been nicer if there had been more discussion and description of the thought process that led up to the conclusions they made for each comment or question. Instead, many of the responses only showed the screenshot of the text they added.

Most of my comments or questions were answered. Below are my comments on some of the authors' responses.

(2) Explain intra-collective and inter-collective selection better for readers.<br /> In the Abstract and Introduction, you've added more sentences about the intra-collective or inter-collective selection. However, these are either making analogies to the waterfall or just describing the result of the intra/inter-collective selection. I would still appreciate a proper definition of those terms, which is paramount for readers to understand the entire paper.

(4) Consideration of environmental stochasticity.<br /> I think providing the reason 'why' the paper focuses on demographic stochasticity and not environmental stochasticity will greatly justify the paper's work. For example, citing papers that actually performed artificial selection and pointing out that your model captures the stochasticity from those kinds of experiments would be great.

(5) Assumption about mutation rates.<br /> It would be great if you could add a citation in the added sentence to support your claim: "This scenario is encountered in biotechnology: .....".

Reviewer #1 (Public review):

Summary:

The present work studies the coevolution of HIV-1 and the immune response in clinical patient data. Using the Marginal Path Likelihood (MPL) framework, they infer selection coefficients for HIV mutations from time-series data of virus sequences as they evolve in a given patient.

Strengths:

The authors analyze data from two human patients, consisting of HIV population sequence samples at various points in time during the infection. They inferred selection coefficients from the observed changes in sequence abundance using MPL. Most beneficial mutations appear in viral envelop proteins. The authors also analyze SHIV samples in rhesus macaques, and find selection coefficients that are compatible with those found in the corresponding human samples.

The manuscript is well written and organized.

Comments on revisions:

In their revised version the authors have addressed most of these points satisfactorily.

Reviewer #1 (Public review):

Summary:

Ever since the surprising discovery of the membrane-associated Periodic Skeleton (MPS) in axons, a significant body of published work has been aimed at trying to understand its assembly mechanism and function. Despite this, we still lack a mechanistic understanding of how this amazing structure is assembled in neuronal cells. In this article, the authors report a "gap-and-patch" pattern of labelled spectrin in iPSC-derived human motor neurons grown in culture. The mid-sections of these axons exhibit patches with reasonably well-organized MPS that are separated by gaps lacking any detectable MPS and having low spectrin content. Further, they report that the intensity modulation of spectrin is correlated with intensity modulations of tubulin as well. However, neurofilament fluorescence does not show any correlation. Using DIC imaging, the authors show that often the axonal diameter remains uniform across segments, showing a patch-gap pattern. Gaps are seen more abundantly in the midsection of the axon, with the proximal section showing continuous MPS and the distal segment showing continuous spectrin fluorescence but no organized MPS. The authors show that spectrin degradation by caspase/calpain is not responsible for gap formation, and the patches are nascent MPS domains. The gap and patch pattern increases with days in culture and can be enhanced by treating the cells using the general kinase inhibitor staurosporine. Treatment with the actin depolymerizing agent Latrunculin A reduces gap formation. The reasons for the last two observations are not well understood/explained.

Strengths:

The claims made in the paper are supported by extensive imaging work and quantification of MPS. Overall, the paper is well written and the findings are interesting. Although much of the reported data are from axons treated with staurosporine, this may be a convenient system to investigate the dynamics of MPS assembly, which is still an open question.

Weaknesses:

Much of the analysis is on staurosporine-treated cells, and the effects of this treatment can be broad. The increase in patch-gap pattern with days in culture is intriguing, and the reason for this needs to be checked carefully. It would have been nice to have live cell data on the evolution of the patch and gap pattern using a GFP tag on spectrin. The evolution of individual patches and possible coalescence of patches can be observed even with confocal microscopy if live cell super-resolution observation is difficult.

Some more comments:

(1) Axons can undergo transient beading or regularly spaced varicosity formation during media change if changes in osmolarity or chemical composition occur. Such shape modulations can induce cytoskeletal modulations as well (the authors report modulations in microtubule fluorescence). The authors mention axonal enlargements in some instances. Although they present DIC images to argue that the axons showing gaps are often tubular, possible beading artefacts need to be checked. Beading can be transient and can be checked by doing media changes while observing the axons on a microscope.

(2) Why do microtubules appear patchy? One would imagine the microtubule lengths to be greater than the patch size and hence to be more uniform.

(3) Why do axons with gaps increase with days in culture? If patches are nascent MPS that progressively grow, one would have expected fewer gaps with increasing days in culture. Is this indicative of some sort of degeneration of axons?

(4) It is surprising that Latrunculin A reduces gap formation induced by staurosporine (also seems to increase MPS correlation) while it decreases actin filament content. How can this be understood? If the idea is to block actin dynamics, have the authors tried using Jasplakinolide to stabilize the filaments?

(5) The authors speculate that the patches are formed by the condensation of free spectrins, which then leaves the immediate neighborhood depleted of these proteins. This is an interesting hypothesis, and exploring this in live cells using spectrin-GFP constructs will greatly strengthen the article. Will the patch-gap regions evolve into continuous MPS? If so, do these patches expand with time as new spectrin and actin are recruited and merge with neighboring patches, or can the entire patch "diffuse" and coalesce with neighboring patches, thus expanding the MPS region?

Reviewer #1 (Public review):

The authors describe a massively parallel reporter assays (MPRA) screen focused at identifying polymorphisms in 5' and 3' UTRs that affect translation efficiency and thus might have a functional impact on cells. The topic is of timely interest, and indeed, several related efforts have recently been published and preprinted (e.g., https://pubmed.ncbi.nlm.nih.gov/37516102/ and https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635273/). This study has several major issues with the results and their presentation.

Major comments:

• The main issue remains that it appears that the screen has largely failed, and the reasons for that remain unclear, which make it difficult to interpret how useful is the resulting data. The authors mention batch effects as a potential contributor. The authors start with a library that includes ~6,000 variants, which makes it a medium-size MPRA. But then, only 483 pairs of WT/mutated UTRs yield high confidence information, which is already a small number for any downstream statistical analysis, particularly since most don't actually affect translation in the reporter screen setting (which is not unexpected). It is unclear why >90% of the library did not give high-confidence information. The profiles presented as base-case examples in Fig. 2B don't look very informative or convincing. All the subsequent analysis is done on a very small set of UTRs that have an effect, and it is unclear to this reviewer how these can yield statistically significant and/or biologically-relevant associations.

• From the variants that had an effect, the authors go on to carry out some protein-level validations, and see some changes, but it is not clear if those changes are in the same direction was observed in the screen. In their rebuttal the authors explain that they largely can not infer directionality of changes form the screen, which further limits its utility.

• It is particularly puzzling how the authors can build a machine learning predictor with >3,000 features when the dataset they use for training the model has just a few dozens of translation-shifting variants.

Comments on revisions:

It appears that the authors have extracted the information they could from the problematic dataset they obtained. Repeating the experiments in a cleaner setting, obtaining data for the >6000 UTRs they intended will allow the authors to achieve the goals they set out to achieve in establishing the screen.

Reviewer #1 (Public review):

Summary:

In their current study, Cummings et al have approached this fundamental biochemical problem using a combination of purified enzyme-substrate reactions, MS/MS and microscopy in vitro to provide key insights into the hierarchy of generating polyglycylation in cilia and flagella. They first establish that TTLL8 is a monoglycylase, with the potential to add multiple mono glycine residues on both α- and β-tubulin. They then go on to establish that the monoglycylation is essential for TTLL10 binding and catalytic activity, which progressively reduces as the level of polyglycylation increases. This provides an interesting mechanism of how level of polyglycylation is regulated in the absence of a deglycylase. Finally, the authors also establish that for efficient TTLL10 activity, it is not just monoglycylation, but also polyglutamylation that is necessary, giving a key insight into how both these modifications interact with each other to ensure there is a balanced level of PTMs on the axonemes for efficient cilia function.

Strengths:

The manuscript is well written, and experiments are succinctly planned and outlined. The experiments used provide the conclusions to what the authors were hypothesising and provide some new novel possible mechanistic insights into the whole process of regulation of tubulin glycylation in motile cilia.

Weaknesses:

There were some weaknesses in the initial submission of the manuscript, but the authors have addressed these in their revised version either by giving clear explanations in the text or through additional experiments.

Reviewer #1 (Public review):

Summary:

Mou and Ji investigate the relationship between firing rates in the anterior cingulate cortex (ACC) and CA1 neurons during observational learning. They found trajectory-selective responses in the ACC, coordinated activity between ACC and CA1 place cells for specific trajectories, and reactivation of these ensembles during sharp-wave ripples (SWRs), particularly during hippocampal replay events. The study is methodologically sound, the data are clearly presented, and the conclusions are well supported. The work is both novel and highly relevant to our understanding of social learning. Compared to the previous version of the paper, they have added substantial characterization of neuronal properties related to their firing during the task and replay events. I believe that the authors have therefore addressed most of my concerns and recommend the paper for publication as is.

Strengths:

The study is well designed, the data presented is very clear and the conclusions are appropriate regarding their results. The study is novel and of high relevance for the understanding of social learning.

Weaknesses:

All previous weaknesses have been addressed.

Reviewer #1 (Public review):

Summary:

The manuscript presents a deep learning framework for predicting T cell receptor (TCR) binding to antigens (peptide-MHC) using a combination of data augmentation techniques to address class imbalance in experimental datasets, and introduces both peptide-specific and pan-specific models for TCR-MHC-I binding prediction. The authors leverage a large, curated dataset of experimentally validated TCR-MHC-I pairs and apply a data augmentation strategy based on generative modeling to generate new TCR sequences. The approach is evaluated on benchmark datasets, and the resulting models demonstrate improved accuracy and robustness.

Strengths:

The most significant contribution of the manuscript lies in its data augmentation approach to mitigate class imbalance, particularly for rare but immunologically relevant epitope classes. The authors employ a generative strategy based on two deep learning architectures:

(1) a Restricted Boltzmann Machine (RBM) and

(2) a BERT-based language model, which is used to generate new CDR3B sequences of TCRs that are used as synthetic training data for creating a class balance of TCR-pMHC binding pairs.

The distinction between peptide-specific (HLA allele-specific) and pan-specific (generalized across HLA alleles) models is well-motivated and addresses a key challenge in immunogenomics: balancing specificity and generalizability. The peptide-specific models show strong performance on known HLA alleles, which is expected, but the pan-specific model's ability to generalize across diverse HLA types, especially those not represented in training, is critical.

Weaknesses:

The paper would benefit from a more rigorous analysis of the biological validity of the augmented data. Specifically, how do the synthetic CDR3B sequences compare to real CDR3B in terms of sequence similarity, motif conservation? The authors should provide a quantitative assessment (via t-SNE or UMAP projections) of real vs. augmented sequences, or by measuring the overlap in known motif positions, before and after augmentation. Without such validation, the risk of introducing "hallucinated" sequences that distort model learning remains a concern. Moreover, it would strengthen the argument if the authors demonstrated that performance gains are not merely due to overfitting on synthetic data, but reflect genuine generalization to unseen real data. Ultimately, this can only be performed through elaborate experimental wet-lab validation experiments, which may be outside the scope of this study.

While generative modeling for sequence data is increasingly common, the choice of RBM, which is a relatively older architecture, could benefit from stronger justification, especially given the emergence of more powerful and scalable alternatives (e.g., ProGen, ESM, or diffusion-based models). While BERT was used, it will be valuable in the future to explore other architectures for data augmentation.

The manuscript would be more compelling if the authors performed a deeper analysis of the pan-specific model's behavior across HLA supertypes and allele groups. Are the learned representations truly "pan" or merely a weighted average of the most common alleles? The authors should assess whether the pan-specific model learns shared binding motifs (anchor residue preferences) and whether these features are interpretable through attention maps. A failure to identify such patterns would raise concerns about the model's interpretability and biological relevance.

The exclusive focus on CDR3β for TCR modeling is biologically problematic. TCRs are heterodimers composed of α and β chains, and both CDR1, CDR2, and CDR3 regions of both chains contribute to antigen recognition. The CDR3β loop is often more diverse and critical, but CDR3α and the CDR1/2 loops also play significant roles in binding affinity and specificity. By generating only CDR3B sequences and not modeling the full TCR αβ heterodimer, the authors risk introducing a systematic bias toward β-chain-dominated recognition, which will not reflect the full complexity of TCR-peptide-MHC interactions.

Reviewer #1 (Public review):

Summary:

In this manuscript, Guin and colleagues establish a microscopy-based CRISPR screen to find new factors involved in global chromatin organization. As a proxy of global chromatin organization, they use centromere clustering in two different cell lines. They find 52 genes whose CRISPR depletion leads to centromere clustering defects in both cell lines. Using cell cycle synchronisation, they demonstrate that centromeres-redistribution upon depletion of these hits necessitates cell cycle progression through mitosis.

Strengths:

This manuscript explores the mechanisms of global chromatin organization, which is a scale of chromatin organization that remains poorly understood. The imaging-based CRISPR screen is very elegant, and the use of appropriate positive and negative controls reinforces the solidity of the findings.

Weaknesses:

Although the data are generally solid and well interpreted, a control showing that protein depletion works properly in cell-cycle arrested cells is lacking, both when using siRNAs and degron-based depletion.

Reviewer #1 (Public review):

Multiple waves of follicles have been proven to exist in multiple species, and different waves of follicles contribute differently to oogenesis and fertility. This work characterizes the wave 1 follicles in mouse comprehensively and compares different waves of follicles regarding their cellular and molecular features. Elegant mouse genetics methods are applied to provide lineage tracing of the wave 1 folliculogenesis, together with sophisticated microscopic imaging and analyses. Single-cell RNA-seq is further applied to profile the molecular features of cells in mouse ovaries from week 2 until week 6. While extensive details about the wave 1 follicles, especially the atresia process, are provided, the authors also identified another group of follicles located in the medullary-cortical boundary, which could also be labeled by the FoxL2-mediated lineage tracing method. The "boundary" or "wave 1.5" follicles are proposed by the authors to be the earliest wave 2 follicles, which contribute to the early fertility of puberty mice, instead of the wave 1 follicles, which undergo atresia with very few oocytes generated. The wave 1 follicle atresia, which degrades most oocytes, on the other hand, expands the number of theca cells and generates the interstitial gland cells in the medulla, where the wave 1 follicles are located. These gland cells likely contribute to the generation of androgen and estrogen, which shape oogenesis and animal development. By comparing scRNA-seq data from cells collected from week 2 until week 6 ovaries, the author profiled the changes in numbers of different cells and identified key genes that differ between wave 1 and wave 2 follicles, which could potentially be another driver of different waves of folliculogenesis. In summary, the authors provide a high amount of new results with good quality that illustrate the molecular and cellular features of different waves of mouse follicles, which could be further reused by other researchers in related fields. The findings related to the boundary follicles could potentially bring many new findings related to oogenesis.

This paper is overall well-written with solid and intriguing conclusions that are well supported. The reviewer only has some minor comments for the authors' consideration that could potentially help with the readability of the paper.

(1) The authors identify the wave 1.5 follicles at the medullary-cortex boundary, which begin to develop shortly after 2 weeks. Since the authors already collected scRNA-seq data from week 2 until week 6, could any special gene expression patterns be identified that make wave 1.5 follicle cells different from wave 1 and wave 2?

(2) Are Figures 1C and 1E Z projections from multiple IF slices? If so, please provide representative IF slice(s) from Figures 1C and 1E and clearly label wave 1 and wave 2 follicles to better illustrate how the wave 1 follicles are clarified and quantified.

(3) For Figure 3D, please also provide an image showing the whole ovary section, like in Figures 3A and 3C, to better illustrate the localization and abundance of different cells.

(4) In Figure 4H, expressions of HSD3B1 and PLIN1 seem to be detected in almost all medulla cells. Does this mean all medulla cells gain gland cell features? Or there is only a subset of the medulla cells that are actively expressing these 2 proteins. Please provide image(s) with higher magnification to show more clearly how the expression of these 2 proteins differs among different cells.

(5) Figure 5: The authors discussed cell number changes for different types of cells from week 2 to week 6. A table, or some plots, visualizing numbers of different cell types, instead of just providing original clusters in Dataset S6, at different time points, would make the changes easier to observe.

(6) Figure S7: It would be more helpful to directly show the number of wave 1 follicles.

(7) Did the fluorescence cryosection staining (Line 587 - 595) use the same buffers as in the whole-mount staining (Line 575 - 586)? Please clarify.

(8) In Line 618, what tissue samples were collected? Please point out clearly.

Reviewer #1 (Public review):

Summary:

The authors have conducted the largest to date Mendelian Randomization (MR) analysis of the association between genetically predicted measures of adiposity and risk of head and neck cancer (HNC) overall and by subsites within HNC. MR uses genetic predictors of an exposure, such as gene variants associated with high BMI or tobacco use, rather than data from individual physical exams or questionnaires and if it can be done in its idealized state, there should be no problems with confounding. Traditional epidemiologic studies have reported a variety of associations between BMI (and a few other measures of adiposity) and risk of HNC that typically differs by the smoking status of the subjects. Those findings are controversial given the complex relationship between tobacco and both BMI and HNC risk. Tobacco smokers are often thinner than no-smokers so this could create an artificial ('confounded') association that may not be fully adjusted away in risk models. The findings of a BMI-HNC association are often attributed to residual confounding and this seems ripe for an MR approach if suitable genetic instrumental variables can be created. Here the authors built a variety of genetic instrumental variables for BMI and other measures of adiposity as well as two instrumental variables for smoking habits and then tested their hypotheses in a large case-controls set of HNC and controls with genetic data.

The authors found that the genetic model for BMI was associated with HNC risk in simple models, but this association disappeared when using models that better accounted for pleiotropy, the condition when genetic variants are associated with more than one trait such as both BMI and tobacco use. When they used both adiposity and tobacco use genetic instruments in a single model, there was a strong association with genetically predicted tobacco use (as is expected) but there was no remaining association with genetic predictors of adiposity. They conclude that high BMI/adiposity is not a risk factor for HNC.

Strengths:

The primary strength was the expansive use of a variety of different genetic instruments for BMI/adiposity/body size along with employing a variety of MR model types, several of which are known to be less sensitive to pleiotropy. They also used the largest case-control sample size to date.

Weaknesses:

The lack of pleiotropy is an unconfirmable assumption of MR and the addition of those models is therefore quite important as this is a primary weakness of the MR approach. Given that concern, I read the sensitivity analyses using pleiotropy-robust models as the main result and in that case, they are more limited in their ability to test their hypothesis as these models do not show a robust BMI instrumental variable association.

Comments on the revised manuscript:

After the first round of review, the authors have improved the manuscript by (1) adding the requested power calculations and adding text to help the reader integrate that additional information; (2) adding the main effects for the tobacco instruments; (3) updating the comparison of their results to the prior literature; (4) and some other edits to the text. They have declined to include the smoking stratified estimates and provide a rationale for this decision that references the potential for collider bias. While true that yet another bias might be introduced, that gets added to the list and the careful reader would know that. Many important questions in cancer etiology can only be addressed via observational approaches and each observational approach has the potential for a long list of biases. The best inference comes from integrating the totality of the data and realizing that most conclusions are subject to updating as we conduct more work and learn more.

Reviewer #1 (Public review):

Summary:

The authors use high-throughput gene editing technology in larval zebrafish to address whether microexons play important roles in the development and functional output of larval circuits. They find that individual microexon deletions rarely impact behavior, brain morphology, or activity, and raise the possibility that behavioral dysregulation occurs only with more global loss of microexon splicing regulation. Other possibilities exist: perhaps microexon splicing is more critical for later stages of brain development, perhaps microexon splicing is more critical in mammals, or perhaps the behavioral phenotypes observed when microexon splicing is lost are associated with loss of splicing in only a few genes.

Strengths:

- The authors provide a qualitative analysis of microexon inclusion during early zebrafish development

- The authors provide comprehensive phenotyping of microexon mutants, addressing the role of individual microexons in the regulation of brain morphology, activity, and behavior.

Reviewer #1 (Public review):

This study aims to elucidate the mechanisms by which stress-induced α2A-adrenergic receptor (α2A-AR) internalization leads to cytosolic noradrenaline (NA) accumulation and subsequent neuronal dysfunction in the locus coeruleus (LC). While the manuscript presents an interesting but ambitious model involving calcium dynamics, GIRK channel rundown, and autocrine NA signaling, several key limitations undermine the strength of the conclusions.

First, the revision does not include new experiments requested by reviewers to validate core aspects of the mechanism. Specifically, there is no direct measurement of cytosolic NA levels or MAO-A enzymatic activity to support the link between receptor internalization and neurochemical changes. The authors argue that such measurements are either not feasible or beyond the scope of the study, leaving a significant gap in the mechanistic chain of evidence.

Second, the behavioral analysis remains insufficient to support claims of cognitive impairment. The use of a single working memory test following an anxiety test is inadequate to verify memory dysfunction behaviors. Additional cognitive assays, such as the Morris Water Maze or Novel Object Recognition, are recommended but not performed.

Third, concerns regarding the lack of rigor in differential MAO-A expression in fluorescence imaging were not addressed experimentally. Instead of clarifying the issue, the authors moved the figure to supplementary data without providing further evidence (e.g., an enzymatic assay or quantitative reanalysis of Western blot, or re-staining of IF for MAO-A) to support their interpretation.

Fourth, concerns regarding TH staining remain unresolved. In Figure S7, the α2A-AR signal appears to resemble TH staining, and vice versa, raising the possibility of labeling errors. It is recommended that the authors re-examine this issue by either double-checking the raw data or repeating the immunostaining to validate the staining.

Overall, the manuscript offers a potentially interesting framework but falls short in providing the experimental rigor necessary to establish causality. The reliance on indirect reasoning and reorganizing existing data, rather than generating new evidence, limits the overall impact and interpretability of the study.

Reviewer #1 (Public review):

The authors previously reported that Heliconius, one genus of the Heliconiini butterflies, evolved to be efficient foragers to feed pollen of specific plants and have massively expanded mushroom bodies. Using the same image dataset, the authors segmented the central complex and associated brain regions and found that the volume of the central complex relative to the rest of the brain is largely conserved across the Heliconiini butterflies. By performing immunostaining to label a specific subset of neurons, the authors found several potential sites of evolutionary divergence in the central complex neural circuits, including the number of GABAergic ellipsoid body ring neurons and the innervation patterns of Allatostatin A expressing neurons in the noduli. These neuroanatomical data will be helpful to guide future studies to understand the evolution of the neural circuits for vector-based navigation.

Strengths:

The authors used a sufficiently large scale of dataset from 307 individuals of 41 species of Heliconiini butterflies to solidify the quantitative conclusions and present new microscopy data for fine neuroanatomical comparison of the central complex.

Weaknesses:

(1) Although the figures display a concise summary of anatomical findings, it would be difficult for non-experts to learn from this manuscript to identify the same neuronal processes in the raw confocal stacks. It would be helpful to have instructive movies to show a step-by-step guide for identification of neurons of interest, segmentations, and 3D visualizations (rotation) for several examples, including ER neurons (to supplement texts in line 347-353) and Allatostatin A neurons.

(2) Related to (1), it was difficult for me to assess if the data in Figure 7 support the author's conclusions that ER neuron number increased in Heliconius Melpomene. By my understanding, the resolution of this dataset isn't high enough to trace individual axons and therefore authors do not rule out that the portion of "ER ring neurons" in Heliconius may not innervate the ER, as stated in Line 635 "Importantly, we also found that some ER neurons bypass the ellipsoid body and give rise to dense branches within distinct layers in the fan-shaped body (ER-FB)". If they don't innervate the ellipsoid body, why are they named as "ER neurons"?

(3) Discussions around the lines 577-584 require the assumption that each ellipsoid body (EB) ring neuron typically arborises in a single microglomerulus to form a largely one-to-one connection with TuBu neurons within the bulb (BU), and therefore, the number of BU microglomeruli should provide an estimation of the number of ER neurons. Explain this key assumption or provide an alternative explanation.

(4) The details of antibody information are missing in the Key resource table. Instead of citing papers, list the catalogue numbers and identifier for commercially available antibodies, and describe the antigen, and whether they are monoclonal or polyclonal. Are antigens conserved across species?

(5) I did not understand why authors assume that foraging to feed on pollens is a more difficult cognitive task than foraging to feed on nectar. Would it be possible that they are equally demanding tasks, but pollen feeding allows Heliconius to pass more proteins and nucleic acids to their offspring and therefore they can develop larger mushroom bodies?

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors theoretically address the topic of interface resistance between a phase-separated condensate and the surrounding dilute phase. In a nutshell, "interface resistance" occurs if material in the dilute phase can only slowly pass through the interface region to enter the dense phase. There is some evidence from FRAP experiments that such a resistance may exist, and if it does, it could be biologically relevant insofar as the movement of material between dense and dilute phases can be rate-limiting for biological processes, including coarsening. The current study theoretically addresses interface resistance at two levels of description: first, the authors present a simple way of formulating interface resistance for a sharp interface model. Second, they derive a formula for interface resistance for a finite-width interface and present two scenarios where the interface resistance might be substantial.

Strengths:

The topic is of broad relevance to the important field of intracellular phase separation, and the work is overall credible.

Weaknesses:

There are a few problems with the study as presented - mainly that the key formula for the latter section has already been derived and presented in Reference 6 (notably also in this journal), and that the physical basis for the proposed scenarios leading to a large interface resistance is not clearly supported.

(1) As noted, Equation 32 of the current study is entirely equivalent to Equation 8 of Reference 6, with a very similar derivation presented in Appendix 1 of that paper. In fact, Equation 8 in Reference 6 takes one more step by combining Equations 32 and 35 to provide a general expression for the interface resistance in an integral form. These prior results should be properly cited in the current work - the existing citations to Reference 6 do not make this overlap apparent.

(2) The authors of the current study go on to examine cases where this shared equation (here Equation 32) might imply a large interface resistance. The examples are mathematically correct, but physically unsupported. In order to produce a substantial interface resistance, the current authors have to suppose that in the interface region between the dense and dilute phases, either there is a local minimum of the diffusion coefficient or a local minimum of the density. I am not aware of any realistic model that would produce either of these minima. Indeed, the authors do not present sufficient examples or physical arguments that would support the existence of such minima.

In my view, these two issues limit the general interest of the latter portion of the current manuscript. While point 1 can be remedied by proper citation, point 2 is not so simple to address. The two ways the authors present to produce a substantial interface resistance seem to me to be mathematical exercises without a physical basis. The manuscript will improve if the authors can provide examples or compelling arguments for a minimum of either diffusion coefficient or density between the dense and dilute phases that would address point 2.

Reviewer #1 (Public review):

Summary:

The authors aimed to examine how the covariation between cognition (represented by a g-factor based on 12 features of 11 cognitive tasks) and mental health (represented by 133 diverse features) is reflected in MR-based neural markers of cognition, as measured through multimodal neuroimaging (structural, rsfMRI, and diffusion MR). To integrate multiple neuroimaging phenotypes across MRI modalities, they used a so-called stacking approach, which employs two levels of machine learning. First, they built a predictive model from each neuroimaging phenotype to predict a target variable. Next, in the stacking level, they used predicted values (i.e., cognition predicted from each neuroimaging phenotype) from the first level as features to predict the target variable. To quantify the contribution of the neural indicators of cognition explaining the relationship between cognition and mental health, they conducted commonality analyses. Results showed that when they stacked neuroimaging phenotypes within dwMRI, rsMRI, and sMRI, they captured 25.5%, 29.8%, and 31.6% of the predictive relationship between cognition and mental health, respectively. By stacking all 72 neuroimaging phenotypes across three MRI modalities, they enhanced the explanation to 48%. Age and sex shared substantial overlapping variance with both mental health and neuroimaging in explaining cognition, accounting for 43% of the variance in the cognition-mental health relationship.

Strengths:

(1) A big study population (UK Biobank with 14000 subjects).

(2) The description of the methods (including Figure 1) is helpful in understanding the approach.

(3) This revised manuscript is much improved compared to the previous version.

Weaknesses:

(1) Although the background and reason for the study are better described in this version of the manuscript, the relevance of the question is, in my opinion, still questionable. The authors aimed to determine whether neural markers of cognition explain the covariance between cognition and mental health and which of the 72 MRI-based features contribute to explaining most of the covariance. I would like to invite the authors to make a stronger case for the relevance, keeping the clinical and scientific relevance in mind (what would you explain to the clinician, what would you explain to the people with lived experience, and how can this knowledge contribute to innovation in mental health care?).

(2) The discussion on the interpretation of the positive and negative PLRS loadings is not very convincing, and the findings are partly counterintuitive. For example (1) how to explain that distress has a positive loading and anxiety/trauma has a negative loading?; (2) how to explain that mental health features like wellbeing and happiness load in the same direction as psychosis and anxiety/trauma? From both a clinical and a neuroscientific perspective, this is hard to interpret.

(3) The analysis plan has not been preregistered (e.g. at OSF).

Note: the computational aspects of the methods fall beyond my expertise.

Reviewer #1 (Public review):

Summary:

The experiment is interesting and well executed and describes in high detail fish behaviour in thermally stratified waters. The evidence is strong but the experimental design cannot distinguish between temperature and vertical position of the treatments.

Strengths:

High statistical power, solid quantification of behaviour.

Weaknesses:

A major issue with the experimental design is the vertical component of the experiment. Many thermal preference and avoidance experiments are run using horizontal division in shuttlebox systems or in annular choice flumes. These remove the vertical stratification component so that hot and cold can be compared equally, without the vertical layering as a confounding factor. The method chosen, with its vertical stratification, is inherently unable to control for this effect because warm water is always above, and cold water is always below. This complicates the interpretations.

Reviewer #2 (Public review):

Summary:

Egawa et al describe the developmental timeline of the assembly of nodes of Ranvier in the chick brainstem auditory circuit. In this unique system, the spacing between nodes varies significantly in different regions of the same axon from early stages, which the authors suggest is critical for accurate sound localization. Egawa et al set out to determine which factors regulate this differential node spacing. They do this by using immunohistological analyses to test the correlation of node spacing with morphological properties of the axons, and properties of oligodendrocytes, glial cells that wrap axons with the myelin sheaths that flank the nodes of Ranvier. They find that axonal structure does not vary significantly, but that oligodendrocyte density and morphology varies in the different regions traversed by these axons, which suggests this is a key determinant of the region-specific differences in node density and myelin sheath length. They also find that differential oligodendrocyte density is partly determined by secreted neuronal signals, as (presumed) blockage of vesicle fusion with tetanus toxin reduced oligodendrocyte density in the region where it is normally higher. Based on these findings, the authors propose that oligodendrocyte morphology, myelin sheath length, and consequently nodal distribution are primarily determined by intrinsic oligodendrocyte properties rather than neuronal factors such as activity.

Major comments:

(1) The authors should test the efficiency of TeNT to validate that vesicular release is indeed inhibited from expressing neurons. Additionally, the authors should clarify if their TeNT expression system results in the whole tract being silenced, or results in sparse vesicular release inhibition in only a few neurons.

(2) The authors should revise their statistical analyses throughout, and supply additional information to explain the rationale for the statistical tests used, including e.g. data normality, paired sampling, number of samples/independent biological replicates.

(3) The main finding of the study is that the density of nodes differs between two regions of the chicken auditory circuit, probably due to morphological differences in the respective oligodendrocytes. Can the authors discuss if this finding is likely to be specific to the avian auditory circuit?

(4) The study shows a correlation between node spacing and oligodendrocyte density, but the authors did not manipulate oligodendrocyte density per se (i.e. cell-autonomously). The authors should either include such experiments, or discuss their value in supporting the interpretation of their results.

(5) The authors should discuss very pertinent prior studies, in particular to contextualize their findings with (a) known neuron-autonomous modes of node formation prior to myelination, (b) known effects of vesicular fusion directly on myelinating capacity and oligodendrogenesis, (c) known correlation of myelin length and thickness with axonal diameter, (d) regional heterogeneity in the oligodendrocyte transcriptome.

Significance:

In our view the study tackles a fundamental question likely to be of interest to a specialized audience of cellular neuroscientists. This descriptive study is suggestive that in the studied system, oligodendrocyte density determines the spacing between nodes of Ranvier, but further manipulations of oligodendrocyte density per se are needed to test this convincingly.

Reviewer #1 (Public review):

Summary:

This is a high-quality and extensive study that reveals differences in the self-assembly properties of the full set of 109 human death fold domains (DFDs). Distributed amphifluoric FRET (DAmFRET) is a powerful tool that reveals the self-assembly behaviour of the DFDs, in non-seeded and seeded contexts, and allows comparison of the nature and extent of self-assembly. The nature of the barriers to nucleation is revealed in the transition from low to high AmFRET. Alongside analysis of the saturation concentration and protein concentration in the absence of seed, the subset of proteins that exhibited discontinuous transitions to higher-order assemblies was observed to have higher concentrations than DFDs that exhibited continuous transitions. The experiments probing the ~20% of DFDs that exhibit discontinuous transition to polymeric form suggest that they populate a metastable, supersaturated form in the absence of cognate signal. This is suggestive of a high intrinsic barrier to nucleation.

Strengths:

The differences in self-assembly behaviour are significant and likely identify mechanistic differences across this large family of signalling adapter domains. The work is of high quality, and the evidence for a range of behaviours is strong. This is an important and useful starting point since the different assembly mechanisms point towards specific cellular roles. However, understanding the molecular basis for these differences will require further analysis.

An impressive optogenetic approach was engineered and applied to initiate self-assembly of CASP1 and CASP9 DFDs, as a model for apoptosome initiation in these two DFDs with differing continuous or discontinuous assembly properties. This comparison revealed clear differences in the stability and reversibility of the assemblies, supporting the hypothesis that supersaturation-mediated DFD assembly underlies signal amplification in at least some of the DFDs.

The study reveals interesting correlations between supersaturation of DFD adapters in short- and long-lived cells, suggestive of a relationship between the mechanism of assembly and cellular context. Additionally, the comprehensive nature of the study provides strong evidence that the interactions are almost all homomeric or limited to members of the same DFD subfamily or interaction network. Similar approaches with bacterial proteins from innate immunity operons suggest that their polymerisation may be driven by similar mechanisms.

Weaknesses:

Only a limited investigation of assembly morphology was conducted by microscopy. There was a tendency for discontinuous structures to form fibrillar structures and continuous to populate diffuse or punctate structures, but there was overlap across all categories, which is not fully explored. The methodology used to probe oligomeric assembly and stability (SDD-AGE) does not justify the conclusions drawn regarding stability and native structure within the assemblies.

The work identifies important differences between DFDs and clearly different patterns of association. However, most of the detailed analysis is of the DFDs that exhibit a discontinuous transition, and important questions remain about the majority of other DFDs and why some assemblies should be reversible and others not, and about the nature of signalling arising from a continuous transition to polymeric form.

Some key examples of well-studied DFDs, such as MyD88 and RIPK,1 deserve more discussion, since they display somewhat surprising results. More detailed exploration of these candidates, where much is known about their structures and the nature of the assemblies from other work, could substantiate the conclusions here and transform some of the conclusions from speculative to convincing.

The study concludes with general statements about the relationship between stochastic nucleation and mortality, which provide food for thought and discussion but which, as they concede, are highly speculative. The analogies that are drawn with batteries and privatisation will likely not be clearly understood by all readers. The authors do not discuss limitations of the study or elaborate on further experiments that could interrogate the model.

Reviewer #1 (Public review):

Summary:

This work shows that a specific adenosine deaminase protein in Dictyostelium generates the ammonia that is required for tip formation during Dictyostelium development. Cells with an insertion in the adgf gene aggregate but do not form tips. A remarkable result, shown by several different ways, is that the adgf mutant can be rescued by exposing the mutant to ammonia gas. The authors also describe other phenotypes of the adgf mutant such as increased mound size, altered cAMP signaling, and abnormal cell type differentiation. It appears that the adgf mutant has defects the expression of a large number of genes, resulting in not only the tip defect but also the mound size, cAMP signaling, and differentiation phenotypes.

Strengths:

The data and statistics are excellent.

Weaknesses:

The key weakness is understanding why the cells bother to use a diffusible gas like ammonia as a signal to form a tip and continue development. The rescue of the mutant by adding ammonia gas to the entire culture indicates that ammonia conveys no positional information within the mound. By the time the cells have formed a mound, the cells have been starving for several hours, and desperately need to form a fruiting body to disperse some of themselves as spores, and thus need to form a tip no matter what. One can envision that the local ammonia concentration is possibly informing the mound that some minimal number of cells are present (assuming that the ammonia concentration is proportional to the number of cells), but probably even a miniscule fruiting body would be preferable to the cells compared to a mound. This latter idea could be easily explored by examining the fate of the adgf cells in the mound - do they all form spores? Do some form spores? Or perhaps the ADGF is secreted by only one cell type, and the resulting ammonia tells the mound that for some reason that cell type is not present in the mound, allowing some of the cells to transdifferentiate into the needed cell type. Thus elucidating if all or some cells produce ADGF would greatly strengthen this puzzling story.

Comments on revisions:

Looks better, but I think you answered my questions (listed as weaknesses in the public review) in the reply to the reviewer but not in the paper. I'd suggest carefully thinking about my questions and addressing them in the Discussion. You did however do all of the things in the paper that were listed as "Recommendations for the authors"

Reviewer #1 (Public review):

Summary:

The paper sets out to examine the social recognition abilities of a 'solitary' jumping spider species. It demonstrates that based on vision alone spiders can habituate and dishabituate to the presence of conspecifics. The data support the interpretation that these spiders can distinguish between conspecifics on the basis of their appearance.

Strengths:

The study presents two experiments. The second set of data recapitulates the findings of the first experiment with a independent set of spiders, highlighting the strength of the results. The study also uses a highly quantitative approach to measuring relative interest between pairs of spiders based on their distance.

Weaknesses:

The study design is overly complicated, while missing key controls, and the data presented in the figures are not clearly connected to study. The discussion is challenging to understand and appears to make unsupported conclusions.

(1) Study design: The study design is rather complicated and as a result it is difficult to interpret the results. The spiders are presented with the same individual twice in a row, called a habituation trial. Then a new individual is presented twice in a row. The first of these is a dishabituation trial and the second another habituation trial (but now habituating to a second individual). This done with three pairings and then this entire structure is repeated over three sessions. The data appear to show the strong effects of differences between habituation and dishabituation trials in the first session. The decrease in differential behavior between the so-called habituation and dishabituation trials in sessions 2 and 3 are explained as a consequence of the spiders beginning to habituate in general to all of the individuals. The claim that the spiders remember specific individuals is somewhat undercut because all of the 'dishabituation' trials in session 2 are toward spiders they already met for 14 minute previously but seemingly do not remember in session 2. In session 3 it is ambiguous what is happening because the spiders no longer differentiate between the trial types. This could be due to fatigue or familiarity. A second experiment is done to show that introducing a totally novel individual, recovers a large dishabituation response, suggesting that the lack of differences between 'habituation' and 'dishabituation' trials in session 3 is the result of general habituation to all of the spiders in the session rather than fatigue. As mentioned before, these data do support the claim that the spiders differentiate among individuals.

The data from session 1 are easy to interpret. The data from sessions 2 and 3 are harder to understand, but these are the trials in which they meet an individual again after a substantial period of separation. Other studies looking at recognition in ants and wasps (cited by the authors) have done a 4 trial design in which focal animal A meets B in the first trial, then meet C in the second trial, meets B again in the third trial, and then meets D in the last trial. In that scenario trials 1, 2 and 4 are between unfamiliar individuals and trial 3 is between potentially familiar individuals. In both the ants and wasps, high aggression is seen in species with and without recognition on trial 1, with low aggression specifically for trials with familiar individuals in species with recognition. Across different tests, species or populations that lack recognition have shown a general reduction in aggression towards all individuals that becomes progressively less aggressive over time (reminiscent of the session 2 and 3 data) while others have maintained modest levels of aggression across all individuals. The 4 session design used in those other studies provides an unambiguous interpretation of the data, while controlling for 'fatigue'. That all trials in sessions 2 and 3 are always with familiar individuals make it challenging to understand how much the spiders are habituating to each other versus having some kind of associative learning of individual identity and behavior.

The data presentation is also very complicated. How is it the case that a negative proportion of time is spent? The methods reveal that this metric is derived by comparing the time individuals spent in each region relative to the previous time they saw that individual. At the very least, data showing the distribution of distances from the wall would be much easier to interpret for the reader.

(2) "Long-term social memory": It is not entirely clear what is meant by the authors when they say 'long-term social memory', though typically long-term memory refers to a form of a memory that require protein synthesis. While the precise timing of memory formation varies across species and contexts, a general rule is that long term memory should last for > 24 hours (e.g., Dreier et al 2007 Biol Letters). The longest time that spider are apart in this trial set up is something like an hour. There is no basis to claim that spiders have long term social memory as they are never asked to remember anyone after a long time apart. The odd phrasing of the 'long-term dishabutation' trial makes it seem that it is testing a long-term memory, but it is not. The spiders have never met. The fact that they are very habituated to one set of stimuli and then respond to a new stimulus is not evidence of long-term memory. To clearly test memory (which is the part really lacking from the design), the authors would need to show that spiders - upon the first instance of re-encountering a previously encountered individual are already 'habituated' to them but not to some other individuals. The current data suggest this may be the case, but it is just very hard to interpret given the design does not directly test memory of individuals in a clear and unambiguous manner.

(3) Lack of a functional explanation and the emphasis on 'asociality': It is entirely plausible that recognition is pleitropic byproduct of the overall visual cognition abilities in the spiders. However, the discussion that discounts territoriality as a potential explanation is not well laid out. First, many species that are 'asocial' nevertheless defend territories. It is perhaps best to say such species are not group living, but they have social lives because they encounter conspecifics and need to interact with them. Indeed, there are many examples of solitary living species that show the dear enemy effect, a form of individual recognition, towards familiar territorial neighbors. The authors in this case note that territorial competition is mediated by the size of color of the chelicerae (seemingly a trait that could be used to distinguish among individuals). Apparently because previous work has suggested that territorial disputes can be mediated by a trait in the absence of familiarity has led them to discount the possibility that keeping track of the local neighbors in a potentially cannibalistic species could be a sufficient functional reason. In any event, the current evidence presented certainly does not warrant discounting that hypothesis.

Comments on Revision:

The authors have not actually addressed my points and their comments conflate discrimination with recognition. The extensive discussion about how babies are tested for discrimination tasks in their rebuttal misses the point. I believe that the data do show that the spiders discriminate between individuals but whether individuals are recognized (i.e., remembered) is less clear. The authors defend their convoluted study design, but it is overly complex and challenging to interpret the data as a result.

The main issue with the design is that they do not actually test for any kind of memory of specific individuals after a substantial time of separation. Instead they show that a new individuals is still surprising/dishabituating. That is nice evidence for discrimination but does not show memory in a clear and unambiguous way.

My comments and critique are unchanged since they didn't really change the paper. New experiments were needed and they didn't do any. Perhaps it is hard to get the spiders where they are? I don't really understand why they didn't do additional experiments as part of this revision.

Reviewer #1 (Public review):

Summary:

The authors aim to explore how interdisciplinarity and internationalization-two increasingly prominent characteristics of scientific publishing-have evolved over the past century. By constructing entropy-based indices from a large-scale bibliometric dataset (OpenAlex), they examine both long-term trends and recent dynamics in these two dimensions across a selection of leading disciplinary and multidisciplinary journals. Their goal is to identify field-specific patterns and structural shifts that can inform our understanding of how science has become more globally collaborative and intellectually integrated.

Strengths and Weaknesses:

The paper's primary strength lies in its comprehensive temporal scope and use of a rich, openly available dataset covering over 56 million articles. The interdisciplinary and internationalization indices are well-founded and allow meaningful comparisons across fields and time. Moreover, the distinction between disciplinary and multidisciplinary journals adds valuable nuance. However, some methodological choices, such as the use of a 5-year sliding window to compute trend values, are insufficiently justified and under-explained. The paper also does not fully address disparities in data coverage across disciplines and time, which may affect the reliability of historical comparisons. Finally, minor issues in grammar and clarity reduce the overall polish of the manuscript.

Evaluation of Findings:

Overall, the authors have largely succeeded in achieving their stated aims. The findings-such as the sharp rise in internationalization in fields like Physics, and the divergence in interdisciplinarity trends across disciplines-are clearly presented and generally well-supported by the data. The authors effectively demonstrate that scientific journals have not followed a uniform trajectory in terms of structural evolution. However, greater clarity in trend estimation methods and better acknowledgment of dataset limitations would help to further substantiate the conclusions and enhance their generalizability.

Impact and Relevance:

This study makes a timely and meaningful contribution to the fields of scientometrics, sociology of science, and science policy. Its combination of scale, historical depth, and field-level comparison offers a useful framework for understanding changes in scientific publishing practices. The entropy-based indicators are simple yet flexible, and the use of open bibliometric data enhances reproducibility and accessibility for future research. Policymakers, journal editors, and researchers interested in publication dynamics will likely find this work informative, and its methods could be applied or extended to other structural dimensions of scholarly communication.

Reviewer #1 (Public review):

Summary:

This work investigated whether cytoplasmic poroelastic properties play an important role in cellular mechanical response over length scales and time scales relevant to cell physiology. Overall, the manuscript concludes that intracellular cytosolic flows and pressure gradients are important for cell physiology and that they act of time- and length-scales relevant to mechanotransduction and cell migration.

Strengths:

Their approach integrates both computational and experimental methods. The AFM deformation experiments combined with measuring z-position of beads is a challenging yet compelling method to determine poroelastic contributions to mechanical realization.

The work is quite interesting and will be of high value to the field of cell mechanics and mechanotransduction.

Weaknesses:

The weaknesses I noted earlier were adequately addressed in the revised version.

Reviewer #1 (Public review):

The study presents significant findings on the role of mitochondrial depletion in axons and its impact on neuronal proteostasis. It effectively demonstrates how the loss of axonal mitochondria and elevated levels of eIF2β contribute to autophagy collapse and neuronal dysfunction. The use of Drosophila as a model organism and comprehensive proteome analysis adds robustness to the findings.

In this revision, the authors have responded thoughtfully to previous concerns. In particular, they have addressed the need for a quantitative analysis of age-dependent changes in eIF2β and eIF2α. By adding western blot data from multiple time points (7 to 63 days), they show that eIF2β levels gradually increase until middle age, then decline. In milton knockdown flies, this pattern appears shifted, supporting the idea that mitochondrial defects may accelerate aging-related molecular changes. These additions clarify the temporal dynamics of eIF2β and improve the overall interpretation.

Other updates include appropriate corrections to figures and quantification methods. The authors have also revised some of their earlier mechanistic claims, presenting a more cautious interpretation of their findings.

Overall, this work provides new insights into how mitochondrial transport defects may influence aging-related proteostasis through eIF2β. The manuscript is now more convincing, and the revisions address the main points raised earlier. I find the updated version much improved.

Reviewer #1 (Public review):

Summary:

Zhang and colleagues examine neural representations underlying abstract navigation in the entorhinal cortex (EC) and hippocampus (HC) using fMRI. This paper replicates a previously identified hexagonal modulation of abstract navigation vectors in abstract space in EC in a novel task involving navigating in a conceptual Greeble space. In HC, the authors claim to identify a three-fold signal of the navigation angle. They also use a novel analysis technique (spectral analysis) to look at spatial patterns in these two areas and identify phase coupling between HC and EC. Finally, the authors propose an EC-HPC PhaseSync Model to understand how the EC and HC construct cognitive maps. While the wide array of techniques used is impressive and their creativity in analysis is admirable, overall, I found the paper a bit confusing and unconvincing. I recommend a significant rewrite of their paper to motivate their methods and clarify what they actually did and why. The claim of three-fold modulation in HC, while potentially highly interesting to the community, needs more background to motivate why they did the analysis in the first place, more interpretation as to why this would emerge in biology, and more care taken to consider alternative hypotheses seeped in existing models of HC function. I think this paper does have potential to be interesting and impactful, but I would like to see these issues improved first.

General comments:

(1) Some of the terminology used does not match the terminology used in previous relevant literature (e.g., sinusoidal analysis, 1D directional domain).

(2) Throughout the paper, novel methods and ideas are introduced without adequate explanation (e.g., the spectral analysis and three-fold periodicity of HC).

Reviewer #1 (Public review):

Summary:

The aim of the experiment reported in this paper is to examine the nature of the representation of a template of an upcoming target. To this end, participants were presented with compound gratings (consisting of tilted to the right and tilted to the left lines) and were cued to a particular orientation - red left tilt or blue right tilt (counterbalanced across participants). There two directly compared conditions: (i) no ping: where there was a cue, that was followed by a 5.5-7.5s delay, then followed by a target grating in which the cued orientation deviated from the standard 45 degrees; and (ii) ping condition in which all aspects were the same with the only difference that a ping (visual impulse presented for 100ms) was presented after the 2.5 seconds following the cue. There was also a perception task in which only the 45 degrees to the right or to the left lines were presented. It was observed that during the delay, only in the ping condition, were the authors able to decode orientation of the to be reported target using the cross-task generalization. Attention decoding, on the other hand, was decoded in both ping and non-ping conditions. It is concluded that the visual system has two different functional states associated with a template during preparation: a predominantly non-sensory representation for guidance and a latent sensory-like for prospective stimulus processing.

Strengths:

There is so much to be impressed with in this report. The writing of the manuscript is incredibly clear. The experimental design is clever and innovative. The analysis is sophisticated and also innovative -the cross-task decoding, the use of Mahalanobis distance as a function of representational similarity, the fact that the question is theoretically interesting, the excellent figures.

Comments on revisions:

I have no further comments.

Reviewer #1 (Public review):

Summary:

This study evaluates whether species can shift geographically, temporally, or both ways in response to climate change. It also teases out the relative importance of geographic context, temperature variability, and functional traits in predicting the shifts. The study system is large occurrence datasets for dragonflies and damselflies split between two time periods and two continents. Results indicate that more species exhibited both shifts than one or the other (or neither), and that geographic context and temperature variability were more influential than traits. The results have implications for future analyses (e.g. incorporating habitat availability) and for choosing winner and loser species under climate change. The results also seem to support climate vulnerability assessments for species that rely on geographic range size and geospatial climate data layers rather than more detailed information (like demographic rates, abundances, or traits) that may not be so readily available. The methodology would be useful for other taxa and study regions with strong participatory ("citizen") science and extensive occurrence data.

Strengths:

This is an organized and well written paper that builds on a popular topic and moves it forward. It has the right idea and approach, and the results are useful answers to the predictions and for conservation planning (i.e. identifying climate winners and losers). There is technical proficiency and analytical rigor driven by an understanding of the data and its limitations.

Reviewer #3 (Public review):

Summary:

The manuscript explores behavioral responses of C. elegans to hydrogen sulfide, which is known to exert remarkable effects on animal physiology in a range of contexts. The possibility of genetic and precise neuronal dissection of responses to H2S motivates the study of responses in C. elegans. The revised manuscript does not seem to have significantly addressed what was lacking in the initial version.

The authors have added further characterization of possible ASJ sensing of H2S by calcium imaging but ASJ does not appear to be directly involved. Genetic and parallel analysis of O2 and CO2 responsive pathways do not reveal further insights regarding potential mechanisms underlying H2S sensing. Gene expression analysis extends prior work. Finally, the authors have examined how H2S-evoked locomotory behavioral responses are affected in mutants with altered stress and detoxification response to H2S, most notably hif-1 and egl-9. These data, while examining locomotion, are more suggestive that observed effects on animal locomotion are secondary to altered organismal toxicity as opposed to specific behavioral responedse

Overall, the manuscript provides a wide range of intriguing observations, but mechanistic insight or a synthesis of disparate data is lacking.

Reviewer #1 (Public review):

The revised manuscript addresses several reviewer concerns, and the study continues to provide useful insights into how ZIP10 regulates zinc homeostasis and zinc sparks during fertilization in mice. The authors have improved the clarity of the figures, shifted emphasis in the abstract more clearly to ZIP10, and added brief discussion of ZIP6/ZIP10 interactions and ZIP10's role in zinc spark-calcium oscillation decoupling. However, some critical issues remain only partially addressed.

(1) Oocyte health confound: The use of Gdf9-Cre deletes ZIP10 during oocyte growth, meaning observed defects could result from earlier disruptions in zinc signaling rather than solely from the absence of zinc sparks at fertilization. The authors acknowledge this and propose transcriptome profiling as a future direction. However, since mRNA levels often do not accurately reflect protein levels and activity in oocytes, transcriptomics may not be particularly informative in this context. Proteomic approaches that directly assess the molecular effects of ZIP10 loss seem more promising. Although current sensitivity limitations make proteomics from small oocyte samples challenging, ongoing improvements in this area may soon allow for more detailed mechanistic insights.

(2) ZIP6 context and focus: The authors clarified the abstract to emphasize ZIP10, enhancing narrative clarity. This revision is appropriate and appreciated.

(3) Follicular development effects: The biological consequences of ZIP6 and ZIP10 knockout during folliculogenesis are still unknown. The authors now say these effects will be studied in the future, but this still leaves a major mechanistic gap unaddressed in the current version.

(4) Zinc spark imaging and probe limitations: The addition of calcium imaging enhances the clarity of Figure 3. However, zinc fluorescence remains inadequate, and the authors depend solely on FluoZin-3AM, a dye known for artifacts and limited ability to detect subcellular labile zinc. The suggestion that C57BL/6J mice may differ from CD1 in vesicle appearance is plausible but does not fully address concerns about probe specificity and resolution. As the authors acknowledge, future studies with more selective probes would increase confidence in both the spatial and quantitative analysis of zinc dynamics.

(5) Mechanistic insight remains limited: The revised discussion now recognizes the lack of detailed mechanistic understanding but does not significantly expand on potential signaling pathways or downstream targets of ZIP10. The descriptive data are useful, but the inability to pinpoint how ZIP10 mediates zinc spark regulation remains a key limitation. Again, proteomic profiling would probably be more informative than transcriptomic analysis for identifying ZIP10-dependent pathways once technical barriers to low-input proteomics are overcome.

Overall, the authors have reasonably revised and clarified key points raised by reviewers, and the manuscript now reads more clearly. However, the main limitation, lack of mechanistic insight and the inability to distinguish between developmental and fertilization-stage roles of ZIP10, remains unresolved. These should be explicitly acknowledged when framing the conclusions.

Reviewer #1 (Public review):

Summary:

This study builds on earlier work showing that early-life odor exposure can trigger glial-mediated pruning of specific olfactory neuron terminals in Drosophila. Moving from indirect to direct functional imaging, the authors show that pruning during a narrow developmental window leads to long-lasting suppression of odor responses in one neuron type (Or42a) but not another (Or43b). The combination of calcium and voltage imaging with connectomic analysis is a strength, though the voltage imaging results are less straightforward to interpret and may not reflect synaptic output changes alone.

Strengths:

Biologically, one of the main strengths of this work is the direct comparison between two odor-responsive OSN types that differ in their long-term adaptation to early-life odor exposure. While Or42a OSNs undergo pruning and remain persistently suppressed into late adulthood, Or43b OSNs, which also respond to the same odor, show little lasting change. This contrast not only underscores the cell-type specificity of critical-period plasticity but also points to a potential role of inhibitory network architecture in determining susceptibility. The persistence of the Or42a suppression well beyond the developmental window provides compelling evidence that early glia-mediated pruning can imprint a stable, life-long functional state on selected sensory channels. By situating these functional outcomes within the context of detailed connectomic data, the study offers a framework for linking structural connectivity to long-term sensory coding stability or vulnerability.

Weaknesses:

The narrative begins with the absence of changes in PN dendrites and axons. While this establishes specificity, it is a relatively weak starting point compared to the novel OSN functional results. Calcium imaging with GCaMP, though widely used, is an indirect measure of synaptic function, and reduced signals could reflect changes in non-synaptic calcium influx as well as release probability. The interpretation of the voltage imaging results is also unclear: if suppression were solely due to impaired synaptic release, one might expect action potential-evoked voltage signals to remain unchanged. The reported changes raise the possibility of deficits in action potential initiation or propagation, which would shift the mechanistic explanation.

The difference between Or42a and Or43b OSNs is attributed to varying inhibitory input densities from connectome data, but this remains speculative without functional tests such as manipulating GABA receptor expression in OSNs. In Or43b, there is essentially no strong phenotype, making it premature to ascribe the absence of suppression solely to inhibitory connectivity. Finally, the study does not connect circuit-level changes to behavioral outcomes; assays of odor-guided attraction or discrimination could place the findings in an organismal context. Some introduction material overlaps with the authors' 2024 paper, and the novelty of the present study could be signposted more clearly.

Reviewer #1 (Public review):

Summary:

The authors performed an in-depth analysis of three mouse strains with different levels of susceptibility to metabolic disease. Transcriptomics analyses of relevant deep tissues revealed many strain-specific differences in response to diet. They used gene set enrichment analysis to highlight possible biological pathways that may be involved in obesity and its metabolic consequences. These results were then confirmed using public data in both mice and humans.

Strengths:

Overall, this is an interesting study into the biological basis of differing phenotypic outcomes in response to metabolic challenges. The findings uncover several pathways that may shed light on the etiology of obesity and the associated health risks, as well as offer potential therapeutic avenues to prevent them.

Weaknesses:

While the experimental design and analysis are mostly good, some aspects of the present paper could be improved.

(1) Most results are insufficiently described. P-values are almost entirely absent in the main text. Sometimes the significance is indicated in the figures, and other times it is missing. For example, strains are sometimes described as having a higher XYZ, something that is never shown in the plots, and no p-value is ever given.

(2) While the biological methods are meticulously described, statistical methods are barely mentioned in the methods section. For example, line 578, "multiple comparisons (...) were performed using the glht function of the multcomp package". What is this? What method does it use? And how was mediation analysis done? Line 575 mentions that models were compared, with no description of how this was done. Mentioning the package (or even function) is not sufficient. The package and function are an implementation; they are not the method. The actual method needs to be clearly mentioned and (at least minimally) described, in addition to having the reference for methods that are not ubiquitous (i.e., the Benjamin-Hochberg method is well-enough established to forgo this).

(3) The methods should also be briefly introduced in the results section before describing the results of those methods.

(4) The role of immune signaling pathways and associated phenotypes (e.g., monocyte fraction) is over-interpreted. While the differences shown are convincing, they do not convincingly show a role in either obesity or disease. The parsimonious explanation is that such changes happen as a consequence of dyslipidemia rather than a cause. It is possible that these pathways play a more direct role in this, but the authors do not present compelling evidence of this, and, failing this, the language in the text needs to be toned down.

Reviewer #1 (Public review):

Summary:

In this manuscript, Yamazaki et al. conducted multiple microscopy-based GFP localization screens, from which they identified proteins that are associated with PM/cell wall damage stress response. Specifically, the authors identified that bud-localized TMD-containing proteins and endocytotic proteins are associated with PM damage stress. The authors further demonstrated that polarized exocytosis and CME are temporally coupled in response to PM damage, and CME is required for polarized exocytosis and the targeting of TMD-containing proteins to the damage site. From these results, the authors proposed a model that CME delivers TMD-containing repair proteins between the bud tip and the damage site.

Strengths:

Overall, this is a well-written manuscript, and the experiments are well-conducted. The authors identified many repair proteins and revealed the temporal coordination of different categories of repair proteins. Furthermore, the authors demonstrated that CME is required for targeting of repair proteins to the damage site, as well as cellular survival in response to stress related to PM/cell wall damage. Although the roles of CME and bud-localized proteins in damage repair are not completely new to the field, this work does have conceptual advances by identifying novel repair proteins and proposing the intriguing model that the repairing cargoes are shuttled between the bud tip and the damaged site through coupled exocytosis and endocytosis.

Weaknesses:

While the results presented in this manuscript are convincing, they might not be sufficient to support some of the authors' claims. Especially in the last two result sessions, the authors claimed CME delivers TMD-containing repair proteins from the bud tip to the damage site. The model is no doubt highly possible based on the data, but caveats still exist. For example, the repair proteins might not be transported from one localization to another localization, but are degraded and resynthesized. Although the Gal-induced expression system can further support the model to some extent, I think more direct verification (such as FLIP or photo-convertible fluorescence tags to distinguish between pre-existing and newly synthesized proteins) would significantly improve the strength of evidence.

Major experiment suggestions:

(1) The authors may want to provide more direct evidence for "protein shuttling" and for excluding the possibility that proteins at the bud are degraded and synthesized de novo near the damage site. For example, if the authors could use FLIP to bleach bud-localized fluorescent proteins, and the damaged site does not show fluorescent proteins upon laser damage, this will strongly support the authors' model. Alternatively, the authors could use photo-convertible tags (e.g., Dendra) to differentiate between pre-existing repair proteins and newly synthesized proteins.

(2) In line with point 1, the authors used Gal-inducible expression, which supported their model. However, the author may need to show protein abundance in galactose, glucose, and upon PM damage. Western blot would be ideal to show the level of full-length proteins, or whole-cell fluorescence quantification can also roughly indicate the protein abundance. Otherwise, we cannot assume that the tagged proteins are only expressed when they are growing in galactose-containing media.

(3) Similarly, for Myo2 and Exo70 localization in CME mutants (Figure 4), it might be worth doing a western or whole-cell fluorescence quantification to exclude the caveat that CME deficiency might affect protein abundance or synthesis.

(4) From the authors' model in Figure 7, it looks like the repair proteins contribute to bud growth. Does laser damage to the mother cell prevent bud growth due to the reduction of TMD-containing repair proteins at the bud? If the authors could provide evidence for that, it would further support the model.

(5) Is the PM repair cell-cycle-dependent? For example, would the recruitment of repair proteins to the damage site be impaired when the cells are under alpha-factor arrest?

Reviewer #1 (Public review):

(1) In this study, the authors aimed at characterizing Huntington's Disease (HD) - related microstructural abnormalities in the basal ganglia and thalami as revealed using Soma and Neurite Density Imaging (SANDI) indices (apparent soma density, apparent soma size, extracellular water signal fraction, extracellular diffusivity, apparent neurite density, fractional anisotropy and mean diffusivity).

(2) The study implements a novel biophysical diffusion model that extends up-to-date methodologies and presents a significant potential for quantifying neurodegenerative processes of the grey matter of the human brain in vivo. The authors comment on the usefulness of this technique in other pathologies, but they exemplify it only with multiple sclerosis. Further development of this, building evidence, should be provided.

(3) The study found that HD-related neurodegeneration in the striatum accounted significantly for striatal atrophy and correlated with motor impairments. HD was associated with reduced soma density, increased apparent soma size, and extracellular signal fraction in the basal ganglia, but not in the thalami. Additionally, these effects were larger at the manifest stage.

(4) The results of this work demonstrate the impact of HD on the basal ganglia and thalami, which can be further explored as a non-invasive biomarker of disease progression. Additionally, the study shows that SANDI can be used to explore grey matter microstructure in a variety of neurological conditions.

Reviewer #3 (Public review):

This is a fundamentally important study presenting cryo-EM structures of a human small conductance calcium-activated potassium (SK2) channel in the absence and presence of calcium, or with interesting pharmacological probes bound, including the bee toxin apamin, a small molecule inhibitor, and a small molecule activator. As efforts to solve structures of the wild-type hSK2 channel were unsuccessful, the authors engineered a chimera containing the intracellular domain of the SK4 channel, the subtype of SK channel that was successfully solved in a previous study (reference 13). The authors present many new and exciting findings, including opening of an internal gate (similar to SK4), for the first time resolving the S3-S4 linker sitting atop the outer vestibule of the pore and unanticipated plasticity of the ion selectivity filter, and the binding sites for apamin, one new small molecule inhibitor and another small molecule activator. Appropriate functional data are provided to frame interpretations arising from the structures of the chimeric protein; the data are compelling, the interpretations are sound, and the writing is clear. This high-quality study will be of interest to membrane protein structural biologists, ion channel biophysicists, and chemical biologists, and will be valuable for future drug development targeting SK channels.

Comments on revisions:

The authors have done a nice job of revising the manuscript to address the issues raised in the first round of review and I have no further suggestions.

Reviewer #1 (Public review):

While the structure of the melibiose permease in both outward and inward-facing forms has been solved previously, there remain unanswered questions regarding its mechanism. Hariharan et al set out to address this with further crystallographic studies complemented with ITC and hydrogen-deuterium exchange (HDX) mass spectrometry. They first report 4 different crystal structures of galactose derivatives to explore molecular recognition, showing that the galactose moiety itself is the main source of specificity. Interestingly, they observe a water-mediated hydrogen bonding interaction with the protein and suggest that this water molecule may be important in binding.

The results from the crystallography appear sensible, though the resolution of the data is low, with only the structure with NPG better than 3Å. However, it is a bit difficult to understand what novel information is being brought out here and what is known about the ligands. For instance, are these molecules transported by the protein or do they just bind? They measure the affinity by ITC, but draw very few conclusions about how the affinity correlates with the binding modes. Can the protein transport the trisaccharide raffinose?

The HDX also appears to be well done; however, in the manuscript as written, it is difficult to understand how this relates to the overall mechanism of the protein and the conformational changes that the protein undergoes.

Reviewer #2 (Public review):

General comment:

This is a very valuable and unique comparative study. An excellent combination of scanning and histological data from three different species is presented. Obtaining the material for such a comparative study is never trivial. The study presents new data and thus provides the basis for an in-depth discussion about chondrichthyan mineralised skeletal tissues.

Comments on previous revisions:

The manuscript has been revised and improved and can be published. A very nice manuscript, indeed. My only recommendation (point of discussion, not a requirement) would still be to think about the claim of paedomorphosis in a holocephalan.

Within the chondrichthyes, how distant holocephali are in relation to elasmobranchii remains uncertain, holocephali are quite a specialised group. Holocephali are also older than Batoidea and Selachii. As paedomorphosis is a derived character, I imagine it is difficult to establish that development in an extant holocephalan is derived compared to development in elasmobranchii. If this type of development would have been typical for the "older" holocephali it would not be paedomorphic. Also, the uncertainty how distant holocephali are from elasmobranchii makes it difficult to identify paedomorphosis with reference to chondrichthyes.

[Editors note: the authors have made further revisions in response to the previous reviews.]

Reviewer #1 (Public review):

Summary:

Participants learned a graph-based representation, but, contrary to the hypotheses, failed to show neural replay shortly after. This prompted a critical inquiry into temporally delayed linear modeling (TDLM)--the algorithm used to find replay. First, it was found that TDLM detects replay only at implausible numbers of replay events per second. Second, it detects replay-to-cognition correlations only at implausible densities. Third, there are concerning baseline shifts in sequenceness across participants. Fourth, spurious sequences arise in control conditions without a ground truth signal. Fifth, when reframing simulations previously published, similar evidence is apparent.

Strengths:

(1) This work is meticulous and meets a high standard of transparency and open science, with preregistration, code and data sharing, external resources such as a GUI with the task and material for the public.

(2) The writing is clear, balanced, and matter-of-fact.

(3) By injecting visually evoked empirical data into the simulation, many surface-level problems are avoided, such as biological plausibility and questions of signal-to-noise ratio.

(4) The investigation of sequenceness-to-cognition correlations is an especially useful add-on because much of the previous work uses this to make key claims about replay as a mechanism.

Weaknesses:

Many of the weaknesses are not so much flaws in the analyses, but shortcomings when it comes to interpretation and a lack of making these findings as useful as they could be.

(1) I found the bigger picture analysis to be lacking. Let us take stock: in other work, during active cognition, including at least one study from the Authors, TDLM shows significance sequenceness. But the evidence provided here suggests that even very strong localizer patterns injected into the data cannot be detected as replay except at implausible speeds. How can both of these things be true? Assuming these analyses are cogent, do these findings not imply something more destructive about all studies that found positive results with TDLM?

(2) All things considered, TDLM seems like a fairly 'vanilla' and low-assumption algorithm for finding event sequences. It is hard to see intuitively what the breaking factor might be; why do the authors think ground truth patterns cannot be detected by this GLM-based framework at reasonable densities?

(3) Can the authors sketch any directions for alternative methods? It seems we need an algorithm that outperforms TDLM, but not many clues or speculations are given as to what that might look like. Relatedly, no technical or "internal" critique is provided. What is it about TDLM that causes it to be so weak?

Addressing these points would make this manuscript more useful, workable, and constructive, even if they would not necessarily increase its scientific breadth or strength of evidence.

Reviewer #1 (Public review):

Summary:

The authors strived for an inventory of GPCRs and GPCR pathway component genes within the genomes of 23 choanoflagellates and other close relatives of metazoans.

Strengths:

The authors generated a solid phylogenetic overview of the GPCR superfamily in these species. Intriguingly, they discover novel GPCR families, novel assortments of domain combinations, novel insights into the evolution of those groups within the Opisthokonta clade. A particular focus is laid on adhesion GPCRs, for which the authors discover many hitherto unknown subfamilies based on Hidden Markov Models of the 7TM domain sequences, which were also reflected by combinations of extracellular domains of the homologs. In addition, the authors provide bioinformatic evidence that aGPCRs of choanoflagellates also contained a GAIN domain, which are self-cleavable thereby reflecting the most remarkable biochemical feat of aGPCRs.

Weaknesses:

The chosen classification scheme for aGPCRs may require reassessment and amendment by the authors in order to prevent confusion with previously issued classification attempts of this family.

Reviewer #1 (Public review):

Summary:

Rolland and colleagues investigated the interaction between Vibrio bacteria and Alexandrium algae. The authors found a correlation between the abundance of the two in the Thau Lagoon and observed in the laboratory that Vibrio grows to higher numbers in the presence of the algae than in monoculture. Time-lapse imaging of Alexandrium in coculture with Vibrio enabled the authors to observe Vibrio bacteria in proximity to the algae and subsequent algae death. The authors further determine the mechanism of the interaction between the two and point out similarities between the observed phenotypes and predator-prey behaviours across organisms.

Strengths:

The study combines field work with mechanistic studies in the laboratory and uses a wide array of techniques ranging from co-cultivation experiments to genetic engineering, microscopy and proteomics. Further, the authors test multiple Vibrio and Alexandria species and claim a wide spread of the observed phenotypes.

Weaknesses:

In my view, the presentation of the data is in some cases not ideal. The phrasing of some conclusions (e.g., group-attacks and wolf-pack-hunting by the bacteria) is in my opinion too strong based on the herein provided data.

Reviewer #1 (Public review):

Summary

In this manuscript, Singh, Wu and colleagues explore functional links between septins and the exocyst complex. The exocyst in a conserved octameric complex that mediates the tethering of secretory vesicles for exocytosis in eukaryotes. In fission yeast cells, the exocyst is necessary for cell division, where it localizes mostly at the rim of the division plane, but septins, which localize in a similar manner, are non-essential. The main findings of the work are that septins are required for the specific localization of the exocyst to the rim of the division plane, and the likely consequent localization of the glucanase Eng1 at this same location, where it is known to promote cell separation. In absence of septins, the exocyst still localizes to the division plane, but is not restricted to the rim. They also show some defect in the localization of secretory vesicles and glucan synthase cargo. They further show interactions between septins and exocyst subunits through coIP experiments.

Strengths

The septin, exocyst and Eng1 localization data are well supported, showing that the septin rim recruits the exocyst and (likely consequently) the Eng1 glucanase at this location. One important finding of the manuscript is that of a physical interaction between septins and exocyst subunits in co-immunoprecipitation experiments.

Weaknesses

While interactions are supported by coIP experiments, the AlphaFold-predicted septin-exocyst interactions are not very convincing and the predicted binding interfaces are not supported by mutation analysis. A further open question is whether septins interact with the intact exocyst complex or whether the interactions occur only with individual subunits. The two-hybrid and coIP data only show weak interactions with individual subunits, and some coIPs (for instance Sec3 and Exo70 with Spn1 and Spn4) are negative, suggesting that the exocyst complex may not remain intact in these experiments.

Reviewer #1 (Public review):

Summary:

The authors make a bold claim that a combination of repetitive transcranial magnetic stimulation (intermittent theta burst-iTBS) and transcranial alternating current stimulation (gamma tACS) causes slight improvements in memory in a face/name/profession task.

Strengths:

The idea of stimulating the human brain non-invasively is very attractive because, if it worked, it could lead to a host of interesting applications. The current study aims to evaluate one such exciting application.

Reviewer #1 (Public review):

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

Their studies have shown that KDM5 inhibition/loss mediates a viral mimicry and DNA damage response through the generation of R-loops in genomic repeats. This is a different mechanism from the more well studied double-stranded RNA-induced "viral mimicry" response.

More importantly, they have shown that KDM5 inhibition does not result in DNA damage or activation of the CGAS/STING pathway in normal breast epithelial cells, suggesting that KDM5 inhibitors may enable a wide therapeutic window in this setting, as compared to STING agonists or Type I Interferons.

Their findings provide new insights into the interplay between epigenetic regulation of genomic repeats, R-loop formation, innate immunity, and cell fitness in the context of cancer evolution and therapeutic vulnerability.

Comments on revised version:

The authors have satisfactorily addressed my comments and revised the manuscript accordingly.

Reviewer #1 (Public review):

Summary:

In this manuscript, Shen et al. have improved upon the mitotic clone analysis tool MAGIC that their lab previously developed. MAGIC uses CRISPR/Cas9-mediated double-stranded breaks to induce mitotic recombination. The authors have replaced the sgRNA scaffold with a more effective scaffold to increase clone frequency. They also introduced modifications to positive and negative clonal markers to improve signal-to-noise and mark the cytoplasm of the cells instead of the nuclei. The changes result in increase in clonal frequencies and marker brightness. The authors also generated the MAGIC transgenics to target all chromosome arms and tested the clone induction efficacy.

Strengths:

MAGIC is a mitotic clone generation tool that works without prior recombination to special chromosomes (e.g., FRT). It can also generate mutant clones for genes for which the existing FRT lines could not be used (e.g., the genes that are between the FRT transgene and the centromere).

This manuscript does a thorough job in describing the method and provides compelling data that support improvement over the existing method.

Weaknesses:

It would be beneficial to have a greater variety of clonal markers for nMAGIC. Currently, the only marker is BFP, which may clash with other genetic tools (e.g., some FRET probes) depending on the application. It would be nice to have far-red clonal markers.

Reviewer #1 (Public review):

Summary:

The study by Bobola et al reports single-nucleus expression analysis with some supporting spatial expression data of human embryonic and fetal cardiac outflow tracts compared to adult aortic valves. The transcription factor GATA6 is identified as a top regulator of one of the mesenchymal subpopulations, and potential interacting factors and downstream target genes are identified bioinformatically. Additional bioinformatic tools are used to describe cell lineage relationships and trajectories for developmental and adult cardiac cell types.

Strengths:

The studies of human tissue and extensive gene expression data will be valuable to the field.

Weaknesses:

(1) The expression data are largely confirmatory of previous studies in humans and mice. Thus, it is not clear what novel biological insights are being reported. While there is some novelty and impact in using human tissue, there are extensive existing publications and data sets in this area.

(2) Major conclusions regarding spatial localization, differential gene expression, or cell lineage relationships based on bioinformatic data are not validated in the context of intact tissues.

(3) The conclusions regarding lineage relationships are based on common gene expression in the current study and may not reflect cellular origins or lineage relationships that have previously been reported in genetic mouse models.

(4) An additional limitation is the exclusive examination of adult aortic valve leaflets that represent only a subset of outflow tract derivatives in the mature heart. The conclusion, as stated in the title regarding adult derivatives of the outflow tract, is not accurate based on the limited adult tissue evaluated, exclusive bioinformatic approach, and lack of experimental lineage analysis of cell origins.

Reviewer #1 (Public review):

Summary:

In the study by Wang et al. entitled "Dissecting organoid-bacteria interaction highlights decreased contractile force as a key factor for heart infection", a simple cardiac organoid (CO) model was established, by combining a heterologous mixture of patient-specific human induced pluripotent stem cells (hiPSC)-derived cardiomyocytes (CMs) in combination with primary HUVECs (Human Umbilical Vein Endothelial Cells) and human mesenchymal stem cells (MSCs, representing stromal cells). This model was applied for investigating the interplay of COs' bacterial infections in vitro, aiming at revealing pathological mechanisms of bacterial infections of the heart in vivo, which may induce myocarditis and consequently heart failure in affected patients.

Strengths:

The paper is systematic, well written, and easy to follow.

Based on their results, the authors state that: "In this study, by developing quantitative tools for analyzing bacterial-cardiac organoid interactions in a 3D, dynamic, clinically relevant setting, we discovered the significant role of cardiac contractility in preventing bacterial infection."

In principle, the idea of establishing a simple yet functionally and physiologically relevant in vitro model and relevant analytical tools for enabling the study of complex pathological mechanisms of cardiovascular diseases is intriguing.

Weaknesses:

However, despite the combination of numerous analytical tools established and applied in the study, the work has substantial experimental limitations, indicating that the bold conclusions may represent a misinterpretation or overinterpretation of the findings.

Key limitations and questions:

(1) It seems that iPSCs from only one patient ("dilated cardiomyopathy (DCM) cells were derived from a 47-year-old Asian male with an LMNA gene mutation") were used in the study. Moreover, it seems that only one iPSC-line/clone from that DCM patient was used and compared to a single control iPSC line from a "healthy donor". Therefore, despite the different assays and experimental controls used in the study, there is a high risk that the observed phenomena reflect iPSC-line-/ clone-dependent effects, rather than revealing general pathophysiologic mechanisms. Thus, key experiments must be shown by cardiomyocytes/ cardiac organoids derived from additional independent iPSC-lines representing different patients and other non-diseased control lines as well. Moreover, it is established good experimental practice in the iPS cell field to generate and include isogenic iPSC controls i.e. iPSC lines of the same genetic background but with corrections of the hypothesised gene mutation underlying the respective e.g., cardiovascular disease.

(2) In Figure 1 (A) immunohistochemical staining for cardiomyocytes for the cardiac marker Troponin is shown, apparently indicating successful cardiomyogenic differentiation of the applied hiPSC lines. In supplemental Figure S1, a flow cytometry analysis specific to cTnT is shown to reveal the CMs content resulting from the monolayer differentiation of respective iPSC lines. Already, the exemplified plots indicate that the CMs' content/ purity for DCM-CMs was notably lower compared to healthy cardiomyocytes (CM; control). This is an important issue, since the non-CMs ("contaminating bystander cells") may have a substantial effect on the functional (including contractile) properties of the COs.

Interestingly, based on the method description, it seems that COs were generated from cryopreserved iPSC-CMs and iPSC-DCMs, including intermediate seeding and culture on Matrigel before COs formation. However, it remains unclear whether the CMs FACS analysis, which is apparently: "Representative FACS plots for analysis of the cell types in DCM monolayer culture after 33 days of differentiation" shows a CMs purity relevant to CO formation, or something different.

The lineage phenotype of non-CMs in respective differentiations should also be clarified. Moreover, it should be noted in the results that the CMs content in COs is lower than the 6:2:2 (CM:ECs:MSC) ratio indicated by the authors, since the CMs purity is not 100%, and is particularly reduced in the iPSC-DCMs.

Finally, to investigate the important latter questions of the "real CMs content" in COs, systematic technologies should be applied to quantify the lineage composition in COs (e.g. by IF staining for the 3 lineages plus DAPI, followed by COs clearance, confocal microscopy "3D stags" and automated, ImageJ-based quantitative cell counts for total cell number definition (see e.g. doi: 10.1038/s41596-024-00976-2) per CO, and quantification of respective lineage content as well.

These questions are of key importance since the presence of non-CMs and their phenotype has profound consequences on the cardiac organoid model, its contractile/ biophysical properties, and, in general, on models' sensitivity to bacterial infections as well.

(3) Figure 2: (F) Why is this figure (Confocal Observations) showing only healthy cardiac organoids (HCOs) but not DCM-COs?

The overall quality of these pictures is poor and not informative regarding the structural identity and tissue composition of the COs, which actually is an important topic in the frame of the paper, as the 3D structure and tissue composition - and differences between HCOs and DCM-COs - are of key importance to their contractile properties.

Moreover, the expective overlay of the cardiac markers alpha-actinin and MHC is not obvious from Figure 2F (see also comments on Figure 7, below).

In Figure 2E: COs at later stages/days should be shown, in particular at that stage, which was used for the functional assays i.e., bacteria infections and contraction pattern monitoring.

(4) Figure 7 (A) (B) - In the IF sections, it seems that there is no overlay between the expression of the cardiac marker MHC (seems to be expressed in the centre of COs only) and the cardiac markers alpha-actinin (which seems to be unexpectedly expressed in all cells on the sections) and Troponin (which seems to be vocally expressed on the outside, excluding the area of MHC expression).

(F) Quantification of the mean area of gene expression, e.g., for MHC indicates a larger area after MHC expression; this seems to entirely contradict the IF pictures (in Figures 7 A-D) of MHC expression before and after infection. This contraction is deemed very critical to this reviewer as it may indicate that the IF staining, data analysis, and/or data interpretation in this part of the manuscript is poor, misleading, or simply wrong.

(5) Overall, from the perspective of this reviewer, the CO-derived results do not reflect in a meaningful way the contractile and hydrodynamic conditions in the mouse heart or the human heart. Thus, it seems that the conclusions may rather represent a hypothesised outcome bias.

Reviewer #1 (Public review):

Summary:

The authors aimed to investigate the cellular mechanisms underlying place field formation (PFF) in hippocampal CA1 pyramidal cells by performing in vivo two-photon calcium imaging in head-restrained mice navigating a virtual environment. Specifically, they sought to determine whether BTSP-like (behavioral time scale synaptic plasticity) events, characterized by large calcium transients, are the primary mechanism driving PFFs or if other mechanisms also play a significant role. Through their extensive imaging dataset, the authors found that while BTSP-like events are prevalent, a substantial fraction of new place fields are formed via non-BTSP-like mechanisms. They further observed that large calcium transients, often associated with BTSP-like events, are not sufficient to induce new place fields, indicating the presence of additional regulatory factors (possibly local dendritic spikes).

Strengths

The study makes use of a robust and extensive dataset collected from 163 imaging sessions across 45 mice, providing a comprehensive examination of CA1 place cell activity during navigation in both familiar and novel virtual environments. The use of two-photon calcium imaging allows the authors to observe the detailed dynamics of neuronal activity and calcium transients, offering insights into the differences between BTSP-like and non-BTSP-like PFF events. The study's ability to distinguish between these two mechanisms and analyze their prevalence under different conditions is a key strength, as it provides a nuanced understanding of how place fields are formed and maintained. The paper supports the idea that BTSP is not the only driving fore behind PFF, and other mechanisms are likely sufficient to drive PFF, and BTSP events may also be insufficient to drive PFF in some cases. The longer-than-usual virtual track used in the experiment allowed place cells to express multiple place fields, adding a valuable dimension to the dataset that is typically lacking in similar studies. Additionally, the authors took a conservative approach in classifying PFF events, ensuring that their findings were not confounded by noise or ambiguous activity.

Weaknesses

The stand out weakness of the paper is the lack of direct measures of BTSP events. Without direct confirmation that large calcium transients correspond to actual BTSP events (including associated complex spikes and calcium plateau potentials), concluding that BTSP is not necessary or sufficient for PFF formation is speculative (although I do believe it).

Reviewer #1 (Public review):

Summary:

In this manuscript, Lu & Cui et al. observe that adult male zebrafish are more resistant to infection and disease following exposure to Spring Viremia of Carp Virus (SVCV) than female fish. The authors then attempt to identify some of the molecular underpinnings of this apparent sexual dimorphism and focus their investigations on a gene called cytochrome P450, family 17, subfamily A, polypeptide 2 (cyp17a2) because it was among the genes that they found to be more highly expressed in kidney tissue from males than in females. Their investigations lead them to propose a direct connection between cyp17a2 and modulation of interferon signaling as the key underlying driver of the difference between male and female susceptibility to SVCV.

Strengths:

Strengths of this study include the interesting observation of a substantial difference between adult male and female zebrafish in their susceptibility to SVCV, and also the breadth of experiments that were performed linking cyp17a2 to infection phenotypes and molecularly to the stability of host and virus proteins in cell lines. The authors place the infection phenotype in an interesting and complex context of many other sexual dimorphisms in infection phenotypes in vertebrates. This study succeeds in highlighting an unexpected factor involved in antiviral immunity that will be an important subject for future investigations of infection, metabolism, and other contexts.

Weaknesses:

Weaknesses of this study include an indirect connection between the majority of experiments and the proposed mechanism underlying the sexual dimorphism phenotype, widespread reliance on over-expression when investigating protein-protein interaction and localization, and an insufficient amount of description of the data presented in the figures. Specific examples of areas for clarification or improvement include:

(1) Figure 10 outlines a mechanistic link between cyp17a2 and the sexual dimorphism the authors report for SVCV infection outcomes. The data presented on increased susceptibility of cyp17a2-/- mutant male zebrafish support this diagram, but this conclusion is fairly weak without additional experimentation in both males and females. The authors justify their decision to focus on males by stating that they wanted to avoid potential androgen-mediated phenotypes in the cpy17a2 mutant background (lines 152-156), but this appears to be speculation. It also doesn't preclude the possibility of testing the effects of increased cyp17a2 expression on viral infection in both males and females. This is of critical importance if the authors intend to focus the study on sexual dimorphism, which is how the introduction and discussion are currently structured.

(2) The authors present data indicating an unexpected link between cyp17a2 and ubiquitination pathways. It is unclear how a CYP450 family member would carry out such activities, and this warrants much more attention. One brief paragraph in the discussion (starting at line 448) mentions previous implications of CYP450 proteins in antiviral immunity, but given that most of the data presented in the paper attempt to characterize cyp17a2 as a direct interactor of ubiquitination factors, more discussion in the text should be devoted to this topic. For example, are there any known domains in this protein that make sense in this context? Discussion of this interface is more relevant to the study than the general overview of sexual dimorphism that is currently highlighted in the discussion and throughout the text.

(3) Figures 2-9 contain information that could be streamlined to highlight the main points the authors hope to make through a combination of editing, removal, and movement to supplemental materials. There is a consistent lack of clarity in these figures that could be improved by supplementing them with more text to accompany the supplemental figures. Using Figure 2 and an example, panel (A) could be removed as unnecessary, panel (B) could be exchanged for a volcano plot with examples highlighting why cyp17a2 was selected for further study and also the full dataset could be shared in a supplemental table, panel (C) could be modified to indicate why that particular subset was chosen for plotting along with an explanation of the scaling, panel (D) could be moved to supplemental because the point is redundant with panels (A) and (C), panel (E) could be presented as a heatmap, in panels (G) and (H) data from EPC cells could be moved to supplemental because it is not central to the phenotype under investigation, panels (J) to (L) and (N) to (P) could be moved to supplemental because they are redundant with the main points made in panels (M) and (Q). Similar considerations could be made with Figures 3-9

(4) The data in Figure 3 (A)-(C) do not seem to match the description in the text. That is, the authors state that cyp17a2 overexpression increases interferon signaling activity in cells, but the figure shows higher increases in vector controls. Additionally, the data in panel (H) are not described. What genes were selected and why, and where are the data on the rest of the genes from this analysis? This should be shared in a supplemental table.

(5) Some of the reagents described in the methods do not have cited support for the applications used in the study. For example, the antibody for TRIM11 (line 624, data in Figures 6 & 7) was generated for targeting the human protein. Validation for use of this reagent in zebrafish should be presented or cited. Furthermore, the accepted zebrafish nomenclature for this gene would be preferred throughout the text, which is bloodthirsty-related gene family, member 32.

Reviewer #1 (Public review):

Summary:

In their manuscript, Metz Reed and colleagues present an exceptionally thorough analysis of three-dimensional genome reorganization during breast cancer progression using the well-characterized MCF10 model system. The integration of high-resolution Micro-C contact maps with multi-omics profiling provides compelling insights into stage-specific dynamics of chromatin compartments, TAD boundaries, and looping events. The discovery that stable chromatin loops enable epigenetic reprogramming of cancer genes, while structural changes selectively drive metastasis-associated pathways, represents a significant conceptual advance. This work substantially deepens our understanding of genome topology in malignancy. To further enhance this impactful study, we offer the following constructive suggestions.

Strengths:

This work sets a benchmark for integrative 3D genomics in oncology. Its methodological sophistication and conceptual advances establish a new paradigm for studying nuclear architecture in disease.

Weaknesses:

Major Issues

(1) Functional tests would strengthen the observed links between structure and gene changes. For example, the COL12A1 gene loop formation correlates with its increased expression. Disrupting this loop using CRISPR-dCas9 at chr6 position 75280 kb could prove whether the loop causes COL12A1 activation. Such experiments would turn strong correlations into clear mechanisms.

(2) The H3K27ac looping idea needs deeper validation. Data suggests H3K27ac loss weakens loops without affecting CTCF. Testing how cohesin proteins interact with H3K27ac-modified sites would clarify this process. Degron systems could rapidly remove H3K27ac to observe real-time effects. Also, the AP-1 motifs found at dynamic loop sites deserve functional tests. Knocking down AP-1 factors might show if they control loop formation.

(3) Connecting findings to patient data would boost clinical relevance. The MCF10 model is excellent for controlled studies. Checking if TAD boundary weakening occurs in actual patient metastases would show real-world importance. Comparing primary and metastatic tumor samples from the same patients could reveal new structural biomarkers. If tissue is scarce, testing cancer cells with added stroma cells might mimic tumor environment effects.

Minor Issues

Adding a clear definition for static loops would help readers. For example, state that static loops show less than 10 percent contact change across replicates. In the ABC model analysis, removing promoter regions from the enhancer list would focus results on true long-range interactions. Briefly noting why this study sees TAD weakening while other cancer types show different patterns would provide useful context.

Reviewer #1 (Public review):

Summary:

The question of how central nervous system lamination defects affect functional integrity is an interesting yet debated topic. The authors investigated the role of afadin, a key adherens junction scaffolding protein, in retinal lamination and function using a retina-specific conditional knockout mouse model. Their findings show that the loss of Afadin caused severe outer retinal lamination defects, disrupting photoreceptor morphology, synapse numbers, and cell positioning, as demonstrated by histological analysis. Despite these structural impairments, retinal function was partially preserved: mERG detected small a- and b-waves, retinal ganglion cells responded to light, and behavioral tests confirmed residual visual function. This research offers new insights into the relationship between retinal lamination and neural circuit function, suggesting that altered retinal morphology does not completely eliminate the capacity for visual information processing.

Strengths:

The study effectively employs the well-organized laminar structure of the retina as an accessible model for investigating afadin's role in lamination within the central nervous system. High-quality histological, immunostaining, and electron microscopy images clearly reveal structural defects in the conditional knockout mice. The revised manuscript significantly enhances the findings by incorporating robust quantitative analyses of cell positioning, retinal thickness, and cell numbers, as well as new assessments of developmental defects. Additionally, new behavioral tests, including the optomotor response and visual cliff tests, have been introduced. Together with electrophysiological recordings, these additions compellingly demonstrate the partial preservation of visual function despite severe structural disruptions.

Weaknesses:

Overall, the study of the mechanisms remains weak. While the authors addressed concerns about molecular mechanisms by examining cell proliferation potentially related to Notch and Wnt signaling (Figure S6C, lines 868-870), the findings are largely negative (no significant changes in progenitor cell numbers), and the discussion of alternative pathways remains speculative.

Reviewer #1 (Public review):

I applaud the authors' for providing a thorough response to my comments from the first round of review. The authors' have addressed the points I raised on the interpretation of the behavioral results as well as the validation of the model (fit to the data) by conducting new analyses, acknowledging the limitations where required and providing important counterpoints. As a result of this process, the manuscript has considerably improved. I have no further comments and recommend this manuscript for publication.

Reviewer #2 (Public review):

Summary:

Septin caging has emerged as one of the innate immune response of eukaryotic cells to infections by intracellular bacteria. This fascinating assembly of eukaryotic proteins into complex structures restricts bacteria motility within the cytoplasm of host cells, thereby facilitating recognition by cytosolic sensors and components of the autophagy machinery. Given the different types of septin caging that have been described thus far, a single cell, unbiased approach to quantify and characterise septin recruitment at bacteria is important to fully grasp the role and function of caging. Thus, the authors have developed an automated image analysis pipeline allowing bacterial segmentation and classification of septin cages that will be very useful in the future, applied to study the role of host and bacterial factors, compare different bacterial strains or even compare infections by clinical isolates.

Strengths:

The authors developed a solid pipeline that has been thoroughly validated. When tested on infected cells, automated analysis corroborated previous observations and allowed the unbiased quantification of the different types of septin cages as well as the correlation between caging and bacterial metabolic activity. This approach will prove an essential asset in the further characterisation of septin cages for future studies.

Weaknesses:

As the main aim of the manuscript is to described the newly developed analysis pipeline, the results illustrated in the manuscript are essentially descriptive. The developed pipeline seems exceptionally efficient in recognising septin cages in infected cells but its application for a broader purpose or field of study remains limited.

Reviewer #1 (Public review):

Summary:

In this study, the authors attempt to devise general rules for aptamer design based on structure and sequence features. The main system they are testing is an aptamer targeting a viral sequence.

Strengths:

The method combines a series of well-established protocols, including docking, MD, and a lot of system-specific knowledge, to design several new versions of the Ta aptamer with improved binding affinity.

Weaknesses:

The approach requires a lot of existing knowledge and, importantly, an already known aptamer, which presumably was found with Selex. In addition, although the aptamer may have a stronger binding affinity, it is not clear if any of it has any additional useful properties such as stability, etc.

Reviewer #1 (Public review):

This is my first review of this manuscript. The authors included previous reviews for a different journal with a length of 90 and 39 pages; I did not review this reply in my assessment of the paper itself. Influenza prediction is not my area of expertise.

A major concern is that the model is trained in the midst of the COVID-19 pandemic and its associated restrictions and validated on 2023 data. The situation before, during, and after COVID is fluid, and one may not be representative of the other. The situation in 2023 may also not have been normal and reflective of 2024 onward, both in terms of the amount of testing (and positives) and measures taken to prevent the spread of these types of infections. A further worry is that the retrospective prospective split occurred in October 2020, right in the first year of COVID, so it will be impossible to compare both cohorts to assess whether grouping them is sensible.

The outcome of interest is the number of confirmed influenza cases. This is not only a function of weather, but also of the amount of testing. The amount of testing is also a function of historical patterns. This poses the real risk that the model confirms historical opinions through increased testing in those higher-risk periods. Of course, the models could also be run to see how meteorological factors affect testing and the percentage of positive tests. The results only deal with the number of positive (only the overall number of tests is noted briefly), which means there is no way to assess how reasonable and/or variable these other measures are. This is especially concerning as there was massive testing for respiratory viruses during COVID in many places, possibly including China.

(1) Although the authors note a correlation between influenza and the weather factors. The authors do not discuss some of the high correlations between weather factors (e.g., solar radiation and UV index). Because of the many weather factors, those plots are hard to parse.

(2) The authors do not actually compare the results of both methods and what the LSTM adds.

Minor comments:

(3) The methods are long and meandering. They could be cleaned up and shortened. E.g., there is no need for 30 lines on PCR testing; the study area should come before the study design. The authors discuss similar elements in multiple places; this whole section can be shortened considerably without affecting the content.

(4) How reliable is the "Our Word in Data" website for subnational coverage of restrictions? Some of the authors are from Putian and should be able to confirm the accuracy for both studied areas.

(5) Figure 2A is hard to parse; it would make more sense to plot these as line plots (y=count, x=month).

Reviewer #1 (Public review):

Summary:

Nahas et al. investigated the roles of herpes simplex virus 1 (HSV-1) structural proteins using correlative cryo-light microscopy and soft X-ray tomography. The authors generated nine viral variants with deletions or mutations in genes encoding structural proteins. They employed a chemical fixation-free approach to study native-like events during viral assembly, enabling observation of a wider field of view compared to cryo-ET. The study effectively combined virology, cell biology, and structural biology to investigate the roles of viral proteins in virus assembly and budding.

Strengths:

(1) The study presented a novel approach to studying viral assembly in cellulo.

(2) The authors generated nine mutant viruses to investigate the roles of essential proteins in nuclear egress and cytoplasmic envelopment.

(3) The use of correlative imaging with cryoSIM and cryoSXT allowed for the study of viral assembly in a near-native state and in 3D.

(4) The study identified the roles of VP16, pUL16, pUL21, pUL34, and pUS3 in nuclear egress.

(5) The authors demonstrated that deletion of VP16, pUL11, gE, pUL51, or gK inhibits cytoplasmic envelopment.

(6) The manuscript is well-written, clearly describing findings, methods, and experimental design.

(7) The figures and data presentation are of good quality.

(8) The study effectively correlated light microscopy and X-ray tomography to follow virus assembly, providing a valuable approach for studying other viruses and cellular events.

(9) The research is a valuable starting point for investigating viral assembly using more sophisticated methods like cryo-ET with FIB-milling.

(10) The study proposes a detailed assembly mechanism and tracks the contributions of studied proteins to the assembly process.

(11) The study includes all necessary controls and tests for the influence of fluorescent proteins.

Weaknesses:

Overall, the manuscript does not have any major weaknesses, just a few minor comments, which were mostly solved in the revised version of the manuscript.

Comments on the latest version:

I reviewed the responses and the updated manuscript, and I am very pleased with how the authors have revised it. The manuscript was already strong, but with the addition of the summary table and the separated images, it is now excellent.

Reviewer #1 (Public review):

Filamentous fungi are established work horses in biotechnology with Aspergillus oryzae as a prominent example with a thousand-year of history. Still the cell biology and biochemical properties of the production strains is not well understood. The paper of the Takeshita group describes the change in nuclear numbers and correlate it to different production capacities. They used microfluidic devices to really correlate the production with nuclear numbers. In addition, they used microdissection to understand expression profile changes and found an increase of ribosomes. The analysis of two genes involved in cell volume control in S. pombe did not reveal conclusive answers to explain the phenomenon. It appears that it is a multi-trait phenotype. Finally, they identified SNPs in many industrial strains and tried to correlate them to the capability of increasing their nuclear numbers.

The methods used in the paper range from high quality cell biology, Raman spectroscopy to atomic force and electron microscopy and from laser microdissection to the use of microfluidic devices to study individual hyphae.

This is a very interesting, biotechnologically relevant paper with the application of excellent cell biology.

Comments on revised version:

The authors addressed all suggestions satisfactorily.

Reviewer #1 (Public review):

Overall, the manuscript reveals the role for actin polymerization to drive fusion of myoblasts during adult muscle regeneration. This pathway regulates fusion in many contexts, but whether it was conserved in adult muscle regeneration remained unknown. Robust genetic tools and histological analyses were used to convincingly support the claims.

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

This revision of the computational study by Mondal et al addresses several issues that I raised in the previous round of reviews and, as such, is greatly improved. The manuscript is more readable, its findings are more clearly described, and both the introduction and the discussion sections are tighter and more to the point. And thank you for addressing the three timescales of half activation/inactivation parameters. It makes the mechanism clearer.

Some issues remain that I bring up below.

Comment:

I still have a bone to pick with the claim that "activity-dependent changes in channel voltage-dependence alone are insufficient to attain bursting". As I mentioned in my previous comment, this is also the case for the gmax values (channel density). If you choose the gmax's to be in a reasonable range, then the statement above is simply cannot be true. And if, in contrast, you choose the activation/inactivation parameters to be unreasonable, then no set of gmax's can produce proper activity. So I remain baffled what exactly is the point that the authors are trying to make.

Reviewer #1 (Public review):

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

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

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

Specific strengths:

(1) The interpretation of dMRS data in terms of cell-specific microstructure through advanced biophysical modelling (e.g. the sphere fraction, modelling the fraction of cell bodies versus neuronal or astrocytic processes) is a strong asset of the study, going beyond the more commonly used signal representation metrics such as the apparent diffusion coefficient, which lacks specificity to biological phenomena.

(2) The fairly good data quality despite the complexity of the experimental framework should be praised: diffusion-weighted MRS was acquired in two brain regions (although not in the same animals) and longitudinally, in neonates, including data at high b-values and multiple diffusion times, which altogether constitutes a large-scale dataset of high value for the diffusion-weighted MRS community.

(3) The authors have shared publicly data and codes used for processing and fitting, which will allow one to reproduce or extend the scope of this work to disease populations, and which goes in line with the current effort of the MR(S) community for data sharing.

Specific weaknesses:

Ligneul and coauthors have convincingly addressed and included my comments from the first and second round in their revised manuscript.

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

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

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

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

Reviewer #3 (Public review):

To summarize: The authors' overfilling hypothesis depends crucially on the premise that the very-quickly reverting paired-pulse depression seen after unusually short rest intervals of << 50 ms is caused by depletion of release sites whereas Dobrunz and Stevens (1997) concluded that the cause was some other mechanism that does not involve depletion. The authors now include experiments where switching extracellular Ca2+ from 1.2 to 2.5 mM increases synaptic strength on average, but not by as much as at other synapse types. They contend that the result supports the depletion hypothesis. I didn't agree because the model used to generate the hypothesis had no room for any increase at all, and because a more granular analysis revealed a mixed population with a subset where: (a) synaptic strength increased by as much as at standard synapses; and yet (b) the quickly reverting depression for the subset was the same as the overall population.

The authors raise the possibility of additional experiments, and I do think this could clarify things if they pre-treat with EGTA as I recommended initially. They've already shown they can do this routinely, and it would allow them to elegantly distinguish between pv and pocc explanations for both the increases in synaptic strength and the decreases in the paired pulse ratio upon switching Ca2+ to 2.5 mM. Plus/minus EGTA pre-treatment trials could be interleaved and done blind with minimal additional effort.

Showing reversibility would be a great addition too, because, in our experience, this does not always happen in whole-cell recordings in ex-vivo tissue even when electrical properties do not change. If the goal is to show that L2/3 synapses are less sensitive to changes in Ca2+ compared to other synapse types - which is interesting but a bit off point - then I would additionally include a positive control, done by the same person with the same equipment, at one of those other synapse types using the same kind of presynaptic stimulation (i.e. ChRs).

Specific points (quotations are from the Authors' rebuttal)

(1) Regarding the Author response image 1, I was instead suggesting a plot of PPR in 1.2 mM Ca2+ versus the relative increase in synaptic strength in 2.5 versus in 1.2 mM. This continues to seem relevant.

(2) "Could you explain in detail why two-fold increase implies pv < 0.2?"

a. start with power((2.5/(1 + (2.5/K1) + 1/2.97)),4) = 2*power((1.3/(1 + (1.3/K1) + 1/2.97)),4);

b. solve for K1 (this turns out to be 0.48);

c. then implement the premise that pv -> 1.0 when Ca2+ is high by calculating Max = power((C/(1 + (C/K1) + 1/2.97)),4) where C is [Ca] -> infinity.

d. pv when [Ca] = 1.3. mM must then be power((1.3/(1 + (1.3/K1) + 1/2.97)),4)/Max, which is <0.2.

Note that modern updates of Dodge and Rahamimoff typically include a parameter that prevents pv from approaching 1.0; this is the gamma parameter in the versions from Neher group.

(3) "If so, we can not understand why depletion-dependent PPD should lead to PPF."

When PPD is caused by depletion and pv < 0.2, the number of occupied release sites should not be decreased by more than one-fifth at the second stimulus so, without facilitation, PPR should be > 0.8. The EGTA results then indicate there should be strong facilitation, driving PPR to something like 1.2 with conservative assumptions. And yet, a value of < 0.4 is measured, which is a large miss.

(4) Despite the authors' suggestion to the contrary, I continue to think there is a substantial chance that Ca2+-channel inactivation is the mechanism underlying the very quickly reverting paired-pulse depression. However, this is only one example of a non-depletion mechanism among many, with the main point being that any non-depletion mechanism would undercut the reasoning for overfilling. And, this is what Dobrunz and Stevens claimed to show; that the mechanism - whatever it is - does not involve depletion. The most effective way to address this would be affirmative experiments showing that the quickly reverting depression is caused by depletion after all. Attempting to prove that Ca2+-channel inactivation does not occur does not seem like a worthwhile strategy because it would not address the many other possibilities.

(5) True that Kusick et al. observed morphological re-docking, but then vesicles would have to re-prime and Mahfooz et al. (2016) showed that re-priming would have to be slower than 110 ms (at least during heavy use at calyx of Held).

Reviewer #1 (Public review):

Summary:

The authors present a nanobody-based pulse-labeling system to track yeast NPCs. Transient expression of a nanobody targeting Nup84 (fused to NeonGreen or an affinity tag) permits selective visualization and biochemical capture of NPCs. Short induction effectively labels NPCs, and the resulting purifications match those from conventional Nup84 tagging. Crucially, when induction is repressed, dilution of the labeled pool through successive cell cycles allows the visualization of "old" NPCs (and potentially individual NPCs), providing a powerful view of NPC lifespan and turnover without permanently modifying a core scaffold protein.

Strengths:

(1) A brief expression pulse labels NPCs, and subsequent repression allows dilution-based tracking of older (and possibly single) NPCs over multiple cell cycles.

(2) The affinity-purified complexes closely match known Nup84-associated proteins, indicating specificity and supporting utility for proteomics.

Weaknesses:

(1) Reliance on GAL induction introduces metabolic shifts (raffinose → galactose → glucose) that could subtly alter cell physiology or the kinetics of NPC assembly. Alternative induction systems (e.g., β-estradiol-responsive GAL4-ER-VP16) could be discussed as a way to avoid carbon-source changes.

(2) While proteomics is solid, a comprehensive supplementary table listing all identified proteins (with enrichment and statistics) would enhance transparency.

(3) Importantly, the authors note that the method is particularly useful "in conditions where direct tagging of Nup84 interferes with its function, while sub-stoichiometric nanobody binding does not." After this sentence, it would be valuable to add concrete examples, such as experiments examining NPC integrity in aging or stress conditions where epitope tags can exacerbate phenotypes. These examples will help readers identify situations in which this approach offers clear advantages.

Reviewer #2 (Public review):

Summary:

In this contribution, the authors investigate the degree of alternative splicing across the evolutionary tree, and identify a trend of increasing alternative splicing as you move from the base of the tree (here, only prokaryotes are considered) towards the tips of the tree. In particular, the authors investigate how the degree of alternative splicing (roughly speaking, the number of different proteins made from a single ORF (open reading frame) via alternative splicing) relates to three genomic variables: the genome size, the gene content (meaning the fraction of the genome composed of ORFs), and finally, the coding percentage of ORFs, meaning the ratio between exons and total DNA in the ORF.

The revised manuscript addresses the problems identified in the first round of reviews and now serves as a guide to understand how alternative splicing has evolved within different phyla, as opposed to making unsubstantiated claims about overall trends.

Reviewer #1 (Public review):

Summary:

The authors investigate how methicillin-resistant (MRSA) and sensitive (MSSA) Staphylococcus aureus adapt to a new host (C. elegans) in the presence or absence of a low dose of the antibiotic oxacillin. Using an "Evolve and Resequence" design with 48 independently evolving populations, they track changes in virulence, antibiotic resistance, and other fitness-related traits over 12 passages. Their key finding is that selection from both the host and the antibiotic together, rather than either pressure alone, results in the evolution of the most virulent pathogens. Genomically, they find that this adaptation repeatedly involves mutations in a small number of key regulatory genes, most notably codY, agr, and saeRS.

Strengths:

The main advantage of the research lies in its strong and thoroughly replicated experimental framework, enabling significant conclusions to be drawn based on the concept of parallel evolution. The study successfully integrates various phenotypic assays (virulence, growth, hemolysis, biofilm formation) with whole-genome sequencing, offering an extensive perspective on the adaptive landscape. The identification of certain regulatory genes as common targets of selection across distinct lineages is an important result that indicates a level of predictability in how pathogens adapt.

Weaknesses:

(1) The main limitation of the paper is that its findings on the function of specific genes are based on correlation, not cause-and-effect evidence. While the parallel evolution evidence is strong, the authors have not yet performed the definitive tests (i.e., reconstruction of ancestral genes) to ensure that the mutations identified in isolation are enough to account for the virulence or resistance changes observed. This makes the conclusions more like firm hypotheses, not confirmed facts.

(2) In some instances, the claims in the text are not fully supported by the visual data from the figures or are reported with vagueness. For example, the display of phenotypic clusters in the PCA (Figure 6A) and the sweeping generalization about the effect of antibiotics on the mutation rates (Figure S5) can be more precise and nuanced. Such small deviations dilute the overall argument somewhat and must be corrected.

Reviewer #1 (Public review):

Summary:

This manuscript presents an extensive body of work and an outstanding contribution to our understanding of the IFN type I and III system in chickens. The research started with the innovative approach of generating KO chickens that lack the receptor for IFNα/β (IFNAR1) or IFN-λ (IFNLR1). The successful deletion and functional loss of these receptors was clearly and comprehensively demonstrated in comparison to the WT. Moreover, the homozygous KO lines (IFNAR1-/- or IFNLR1-/- ) were found to have similar body weights, and normal egg production and fertility compared to their WT counterparts. These lines are a major contribution to the toolbox for the study of avian/chicken immunology.

The significance of this contribution is further demonstrated by the use of these lines by the authors to gain insight into the roles of IFN type I and IFN-type III in chickens, by conducting in ovo and in vivo studies examining basic aspects of immune system development and function, as well as the responses to viral challenges conducted in ovo and in vivo.

Based on solid, state-of the-art methods and convincing evidence from studies comparing various immune system related functions in the IFNAR1-/- or IFNLR1-/- lines to the WT, revealed that the deletion of IFNAR1 and/or IFNLR1 resulted in:<br /> (1) impaired IFN signaling and induction of anti-viral state;<br /> (2) modulation of immune cell profiles in the peripheral blood circulation and spleen;<br /> (3) modulation of the cecum microbiome;<br /> (4) reduced concentrations of IgM and IgY in the blood plasma before and following immunization with model antigen KLH, whereby also line differences in the time-course of the antibody production were observed;<br /> (5) decrease in MHCII+ macrophages and B cells in the spleen of IFNAR1 KO chickens, although the MHCII-expression per cell was not affected in this line; and<br /> (6) reduction in the response of αβ1 TCR+ T cells of IFNAR1 KO chickens as suggested by clonal repertoire analyses.

These studies were then followed by examination of the role of type I and type III IFN in virus infection, using different avian influenza A virus strains as well as an avian gamma corona virus (IBV) in in ovo challenge experiments. These studies revealed: viral titers that reflect virus-species and strain-specific IFN responses; no differences in the secretion of IFN-α/β in both KO compared to the WT lines; a predominant role of type I IFN in inducing the interferon-stimulated gene (ISG) Mx; and that an excessive and unbalanced type I IFN response can harm host fitness (survival rate, length of survival) and contribute to immunopathology.

Based on guidance from the in ovo studies, comprehensive in vivo studies were conducted on host-pathogen interactions in hens from the three lines (WT, IFNAR1 KO, or IFNLR1 KO). These studies revealed the early appearance of symptoms and poor survival of hens from the IFNR1 KO line challenged with H3N1 avian influenza A virus; efficient H#N1 virus replication in IFNAR1 KO hens, increased plasma concentrations of IFNα/β and mRNA expression of IFN-λ in spleens of the IFNAR1 KO hens; a pro-inflammatory role of IFN-λ in the oviduct of hens infected with H3N1 virus; increased proinflammatory cytokine expression in spleens of IFNAR1 KO hens, and Impairment of negative feedback mechanisms regulating IFN-α/β secretion in IFNAR1-KO hens and a significant decrease in this group's antiviral state; additionally it was demonstrated that IFN-α/β can compensate IFN-λ to induce an adequate antiviral state in the spleen during H3N1 infection, but IFN-λ cannot compensate for IFN-α/β signaling in the spleen.

Strengths:

(1) Both the methods and results from the comprehensive, well-designed, and well-executed experiments are considered excellent. The results are well and correctly described in the result narrative and well presented in both the manuscript and supplement Tables and Figures. Excellent discussion/interpretation of results.

(2) The successful generation of the type I and type III IFN KO lines offers unprecedented insight and opens multiple new venues for exploring the IFN system in chickens. The new knowledge reported here is direct evidence of the high impact of this model system on effectively addressing a critical knowledge gap in avian immunology.

(3) The thoughtful selection of highly relevant viruses to poultry and human health for the in ovo and in vivo challenge studies to examine and assess host-pathogen interactions in the IFNR KO and WT lines.

(4) Making use of the unique opportunities in the chicken model to examine and evaluate the host's IFN system responses to various viral challenges in ovo, before conducting challenge studies in hens.

(5) The new knowledge gained from the IFNAR1 and IFNLR1 KO lines will find much-needed application in developing more effective strategies to prevent health challenges like avian influenza and its devastating effects on poultry, humans, and other mammals.

(6) The excellent cooperation and contributions of the co-authors and institutions.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors reveal that the availability of extracellular asparagine (Asn) represents a metabolic vulnerability for the activation and differentiation of naive CD4+ T cells. To deplete extracellular Asn, they employed two orthogonal approaches: activating naive CD4+ T cells in either PEGylated asparaginase (PEG-AsnASE)-treated medium or custom-formulated RPMI medium specifically lacking Asn. Importantly, they demonstrate that Asn depletion not only impaired metabolic reprogramming associated with CD4+ T cell activation but also reduced CD4+ helper T cell lineage-specific cytokine production, thereby ameliorating the severity of experimental autoimmune encephalomyelitis.

Strengths:

The experiments presented here are comprehensive and well-designed, providing compelling evidence for the conclusions. The conclusions will be important to the field.

Weaknesses:

(1) EAE is the prototypic T cell-mediated autoimmune disease model, and both Th1 and Th17 cells are implicated in its pathogenesis. In contrast, Th2 and Treg cells and their associated cytokines (such as IL-4 and IL-10) have been shown to play a role in the resolution of EAE, and potentially in the modulation of disease progression. Thus, it will be important to determine whether Asn depletion affects the differentiation of naive CD4+ T cells into corresponding subsets under Th2 and Treg polarization conditions, as well as the expression of lineage-specific transcription factors and cytokine production.

(2) EAE is characterized by inflammation and demyelination in the central nervous system (CNS), leading to neurological deficits. Myelin destruction is directly correlated with the severity of the disease. For Figure 6, did the authors perform spinal cord histological analysis by hematoxylin and eosin (H&E) or Luxol fast blue (LFB) staining? This is important to rigorously examine pathological EAE symptoms.

Reviewer #1 (Public review):

Summary:

The manuscript by Xu et al. reported base-resolution mapping of RNA pseudouridylation in five bacterial species, utilizing recently developed BID-seq. They detected pseudouridine (Ψ) in bacterial rRNA, tRNA, and mRNA, and found growth phase-dependent Ψ changes in tRNA and mRNA. They then focused on mRNA and conducted a comparative analysis of Ψ profiles across different bacterial species. Finally, they developed a deep learning model to predict Ψ sites based on RNA sequence and structure.

Strengths:

This is the first comprehensive Ψ map across multiple bacterial species, and systematically reveals Ψ profiles in rRNA, tRNA, and mRNA under exponential and stationary growth conditions. It provides a valuable resource for future functional studies of Ψ in bacteria.

Weaknesses:

Ψ is highly abundant on non-coding RNA such as rRNA and tRNA, while its level on mRNA is very low. The manuscript focuses primarily on mRNA, which raises questions about the data quality and the rigor of the analysis. Many conclusions in the manuscript are speculative, based solely on the sequencing data but not supported by additional experiments.

Reviewer #1 (Public review):

Summary:

Alveolar macrophages (AMs) are key sentinel cells in the lungs, representing the first line of defense against infections. There is growing interest within the scientific community in the metabolic and epigenetic reprogramming of innate immune cells following an initial stress, which alters their response upon exposure to a heterologous challenge. In this study, the authors show that exposure to extracellular ATP can shape AM functions by activating the P2X7 receptor. This activation triggers the relocation of the potassium channel TWIK2 to the cell surface, placing macrophages in a heightened state of responsiveness. This leads to the activation of the NLRP3 inflammasome and, upon bacterial internalization, to the translocation of TWIK2 to the phagosomal membrane, enhancing bacterial killing through pH modulation. Through these findings, the authors propose a mechanism by which ATP acts as a danger signal to boost the antimicrobial capacity of AMs.

Strengths:

This is a fundamental study in a field of great interest to the scientific community. A growing body of evidence has highlighted the importance of metabolic and epigenetic reprogramming in innate immune cells, which can have long-term effects on their responses to various inflammatory contexts. Exploring the role of ATP in this process represents an important and timely question in basic research. The study combines both in vitro and in vivo investigations and proposes a mechanistic hypothesis to explain the observed phenotype.

Weaknesses:

First, the concept of training or trained immunity refers to long-term epigenetic reprogramming in innate immune cells, resulting in a modified response upon exposure to a heterologous challenge. The investigations presented demonstrate phenotypic alterations in AMs seven days after ATP exposure; however, they do not assess whether persistent epigenetic remodeling occurs with lasting functional consequences. Therefore, a more cautious and semantically precise interpretation of the findings would be appropriate.

Furthermore, the in vivo data should be strengthened by additional analyses to support the authors' conclusions. The authors claim that susceptibility to Pseudomonas aeruginosa infection differs depending on the ATP-induced training effect. Statistical analyses should be provided for the survival curves, as well as additional weight curves or clinical assessments. Moreover, it would be appropriate to complement this clinical characterization with additional measurements, such as immune cell infiltration analysis (by flow cytometry), and quantification of pro-inflammatory cytokines in bronchoalveolar lavage fluid and/or lung homogenates.

Moreover, the authors attribute the differences in resistance to P. aeruginosa infection to the ATP-induced training effect on AMs, based on a correlation between in vivo survival curves and differences in bacterial killing capacity measured in vitro. These are correlative findings that do not establish a causal role for AMs in the in vivo phenotype. ATP-mediated effects on other (i.e., non-AM) cell populations are omitted, and the possibility that other cells could be affected should be, at least, discussed. Adoptive transfer experiments using AMs would be a suitable approach to directly address this question.

Joint Public Review:

Summary from an earlier round of review:

This paper summarises responses from a survey completed by around 5,000 academics on their manuscript submission behaviours. The authors find several interesting stylised facts, including (but not limited to):- Women are less likely to submit their papers to highly influential journals (e.g., Nature, Science and PNAS).

- Women are more likely to cite the demands of co-authors as a reason why they didn’t submit to highly influential journals.

- Women are also more likely to say that they were advised not to submit to highly influential journals.

The paper highlights an important point, namely that the submission behaviours of men and women scientists may not be the same (either due to preferences that vary by gender, selection effects that arise earlier in scientists’ careers or social factors that affect men and women differently and also influence submission patterns). As a result, simply observing gender differences in acceptance rates - or a lack thereof - should not be automatically interpreted as as evidence for or against discrimination (broadly defined) in the peer review process.

Editor’s note: This is the third version of this article.

Comments made during the peer review of the second version, along with author’s responses to these comments, are available below. Revisions made in response to these comments include changing the colour scheme used for the figures to make the figures more accessible for readers with certain forms of colour blindness.

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

Reviewer #1 (Public review):

Summary:

Chao et al. produced an updated version of the SpliceAI package using modern deep learning frameworks. This includes data preprocessing, model training, direct prediction, and variant effect prediction scripts. They also added functionality for model fine-tuning and model calibration. They convincingly evaluate their newly trained models against those from the original SpliceAI package and investigate how to extend SpliceAI to make predictions in new species. Their comparisons to the original SpliceAI models are convincing on the grounds of model performance and their evaluation of how well the new models match the original's understanding of non-local mutation effects. However, their evaluation of the new calibration functionality would benefit from a more nuanced discussion of the limitations of calibration.

Strengths

(1) They provide convincing evidence that their new implementation of SpliceAI matches the performance and mutation effect estimation capabilities of the original model on a similar dataset while benefiting from improved computational efficiencies. This will enable faster prediction and retraining of splicing models for new species as well as easier integration with other modern deep learning tools.

(2) They produce models with strong performance on non-human model species and a simple well well-documented pipeline for producing models tuned for any species of interest. This will be a boon for researchers working on splicing in these species and make it easy for researchers working on new species to generate their own models.

(3) Their documentation is clear and abundant. This will greatly aid the ability of others to work with their code base.

Weaknesses

(1) Their discussion of their package's calibration functionality does not adequately acknowledge the limitations of model calibration. This is problematic as this is a package intended for general use and users who are not experienced in modeling broadly and the subfield of model calibration specifically may not already understand these limitations. This could lead to serious errors and misunderstandings down the road. A model is not calibrated or uncalibrated in and of itself, only with respect to a specific dataset. In this case they calibrated with respect to the training dataset, a set of canonical transcript annotations. This is a perfectly valid and reasonable dataset to calibrate against. However, this is unlikely to be the dataset the model is applied to in any downstream use case, and this calibration is not guaranteed or expected to hold for any shift in the dataset distribution. For example, in the next section they use ISM based approaches to evaluate which sequence elements the model is sensitive to and their calibration would not be expected to hold for this set of predictions. This issue is particularly worrying in the case of their model because annotation of canonical transcript splice sites is a task that it is unlikely their model will be applied to after training. Much more likely tasks will be things such as predicting the effects of mutations, identification of splice sites that may be used across isoforms beyond just the canonical one, identification of regulatory sequences through ISM, or evaluation of human created sequences for design or evaluation purposes (such as in the context of an MPSA or designing a gene to splice a particular way), we would not expect their calibration to hold in any of these contexts. To resolve this issue, the authors should clarify and discuss this limitation in their paper (and in the relevant sections of the package documentation) to avoid confusing downstream users.

(2) The clarity of their analysis of mutation effects could be improved with some minor adjustments. While they report median ISM importance correlation it would be helpful to see a histogram of the correlations they observed. Instead of displaying (and calculating correlations using) importance scores of only the reference sequence, showing the importance scores for each nucleotide at each position provides a more informative representation. This would also likely make the plots in 6B clearer.

Reviewer #1 (Public review):

This is an important, interesting, and in-depth study examining the role of Sp5/8 transcription factors in maintaining the neuromesodermal progenitor (NMP) niche. The authors first used Sp5/8 double conditional KO mouse embryos to establish that these factors function in the NMP niche to promote trunk elongation. They then conducted extensive single-cell analyses on embryos of various genetic mutant backgrounds to unravel the complex and intricate interactions between Wnt signaling and Sp5/8. The key conclusion from these experiments is that Sp5/8 function within an autoregulatory loop crucial for maintaining the NMP niche. The authors went on to identify and characterize a novel enhancer element downstream of the Wnt3a coding sequence, which mediates the effects of Sp5/8 on Wnt3a expression. Overall, the data presented are compelling and of high quality, and the study offers a prime example of how a relatively small set of signaling pathways and transcription factors can function in concert to impart robustness to developmental processes.

Reviewer #1 (Public review):

Summary:

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

Strengths:

- The authors are addressing a very interesting question with respect to sampling of targets and distractors, using neurophysiological measurements to their advantage in order to parse out target and distractor processing.<br /> - The general EEG analysis pipeline is sensible and well-described.<br /> - The main result of rhythmic sampling of targets and distractors is striking and very clear even on a participant-level.<br /> - The authors have gone to quite a lot of effort to ensure the validity of their analyses, especially in the Supplementary Material.<br /> - It is incredibly striking how the phase of both target and distractor processing are so aligned across trials for a given participant. I would have thought that any endogenous fluctuation in attention or stimulus processing like that would not be so phase aligned. I know there is literature on phase resetting in this context, the results seem very strong here and it is worth noting. The authors have performed many analyses to rule out signal processing artifacts, e.g. the sideband and beating frequency analyses.

Weaknesses:

- In general, the representation of target and distractor processing is a bit of a reach. Target processing is represented by SSVEP amplitude, which is going to most likely be related to the contrast of the dots, as opposed to representing coherent motion energy which is the actual target. These may well be linked (e.g. greater attention to the coherent motion task might increase SSVEP amplitude) but I would call it a limitation of the interpretation. Decoding accuracy of emotional content makes sense as a measure of distractor processing, and the supplementary analysis comparing target SSVEP amplitude to distractor decoding accuracy is duly noted. Overall, this limitation remains and has been noted in the Limitations section.<br /> - Then comparing SSVEP amplitude to emotional category decoding accuracy feels a bit like comparing apples with oranges. They have different units and scales and reflect probably different neural processes. Is the result the authors find not a little surprising in this context? This relationship does predict performance and is thus intriguing, but I think this methodological aspect needs to be discussed further. For example, is the phase relationship with behaviour a result of a complex interaction between different levels of processing (fundamental contrast vs higher order emotional processing)? Again, this has been noted in the Limitations section, but changing the data to z-scores doesn't really take care of the conceptual issue, i.e. that on-screen contrast changes would necessarily be distracting during emotional category decision-making.