Reviewer #3 (Public Review):

Summary:

This manuscript details the characterization of ClpL from L. monocytogenes as a potent and autonomous AAA+ disaggregase. The authors demonstrate that ClpL has potent and DnaK-independent disaggregase activity towards a variety of aggregated model substrates, and that this disaggregase activity appears to be greater than that observed with the canonical DnaK/ClpB co-chaperone. Furthermore, LmClpL appears to have greater thermostability as compared to LmDnaK, suggesting that ClpL-expressing cells may be able to withstand more severe heat stress conditions. Interestingly, LmClpL can provide thermotolerance to E. coli that have been genetically depleted of either ClpB or in cells expressing a mutant DnaK103. The authors further characterized the mechanisms by which ClpL interacts with protein aggregates, identifying that the N-terminal domain of ClpL is essential for disaggregase function. Lastly, by EM and mutagenesis analysis the authors report that ClpL can exist in a variety of larger macromolecular complexes, including dimer or trimers of hexamers/heptamers, and they provide evidence that the N-terminal domains of ClpL prevent dimer ring formation, thus promoting an active and substrate-binding ClpL complex. Throughout this manuscript the authors compare LmClpL to ClpG, another potent and autonomous disaggregase found in gram-negative bacteria that has been reported on previously, demonstrating that these two enzymes share homologous activity and qualities. Taken together this report clearly establishes ClpL as a novel and autonomous disaggregase.

Analysis:

The work presented in this report amounts to a significant body of novel and significant work that will be of interest to protein chaperone community. Furthermore, by providing examples of how ClpL can provide in vivo thermotolerance to both E. coli and L. gasseri the authors have expanded the significance of this work and provides novel insight into potential mechanisms responsible for thermotolerance in food-borne pathogens. The figures are clearly depicted, well-labeled, and easy to understand, and the manuscript is well-written. Experimentally the work was performed to a high standard with excellent controls, aiding in the ability for the audience to understand the major findings and conclusions. Additionally, the authors have effectively and efficiently expanded on their work through the peer review process, further increasing the understandability and significance of their work. Overall, the data presented, and analysis thereof, support the authors' conclusions, and thus this study represents an important addition to our understanding of molecular chaperone biochemistry. Lastly, this study establishes new avenues for research into autonomous disaggregates, their role in in vivo thermotolerance, and the mechanisms by which AAA+ chaperones recognize and interact with substrate proteins.

Reviewer #3 (Public Review):

Summary:

In this article, Gao et. al. uses single-molecule FRET (smFRET) and position-specific labelling of RNA (PLOR) to dissect the folding and behavioral ligand sensing of the Guanidine-IV riboswitch in the presence and absence of the ligand guanidine and the cation Mg2+. The results provided valuable information on the mechanistic aspects of the riboswitch, including the confirmation of the kissing loop present in the structure as essential for folding and riboswitch activity. Co-transcriptional investigations of the system provided key information on the ligand-sensing behavior and ligand-binding window of the riboswitch. A plausible folding model of the Guanidine-IV riboswitch was proposed as a final result. The evidence presented here sheds additional light on the mode of action of transcriptional riboswitches.

Strengths:

The investigations were very thorough, providing data that supports the conclusions. The use of smFRET and PLOR to investigate RNA folding has been shown to be a valuable tool for the understanding of folding and behavior properties of these structured RNA molecules. The co-transcriptional analysis brought important information on how the riboswitch works, including the ligand-sensing and the binding window that promotes the structural switch. The fact that investigations were done with the aptamer domain, aptamer domain + terminator/anti-terminator region, and the full-length riboswitch were essential to inform how each domain contributes to the final structural state if in the presence of the ligand and Mg2+.

Weaknesses:

The system has its own flaws when compared to physiological conditions. The RNA polymerase used (the study uses T7 RNA polymerase) is different from the bacterial RNA polymerase, not only in complexity, but also in transcriptional speed, which can directly interfere with folding and ligand-sensing. Additionally, rNTPs concentrations were much lower than physiological concentrations during transcription, likely causing a change in the polymerase transcriptional speed. These important aspects and how they could interfere with results are important to be addressed to the broad audience. Another point of consideration to be aware of is that the bulky fluorophores attached to the nucleotides can interfere with folding to some extent.

Reviewer #3 (Public Review):

Summary:

Zeng and Stanley show that in yeast, intron-lariat intermediates that accumulated due to defects in pre-mRNA splicing, are transported to the cytoplasm using the canonical mRNA export pathway. Moreover, they demonstrate that export requires the nuclear basket, a sub-structure of the nuclear pore complex previously implicated with the retention of immature mRNAs. These observations are important as they put into question a longstanding model that the main role of the nuclear basket is to ensure nuclear retention of immature or faulty mRNAs.

Strengths:

The authors elegantly combine genetic, biochemical, and single-molecule resolution microscopy approaches to identify the cellular pathway that mediates the cytoplasmic accumulation of lariat intermediates. Cytoplasmic accumulation of such splicing intermediates had been observed in various previous studies but how these RNAs reach the cytoplasm had not yet been investigated. By using smFISH, the authors present compelling, and, for the first time, direct evidence that these intermediates accumulate in the cytoplasm and that this requires the canonical mRNA export pathway, including the RNA export receptor Mex67 as well as various RNA-binding proteins including Yra1, Npl3 and Nab2. Moreover, they show that the export of lariat intermediates, but not mRNAs, requires the nuclear basket (Mlp1) and basket-associated proteins previously linked to the mRNP rearrangements at the nuclear pore. This is a surprising and important observation with respect to a possible function of the nuclear basket in mRNA export and quality control, as it challenges a longstanding model that the role of the basket in mRNA export is primarily to act as a gatekeeper to ensure that immature mRNAs are not exported. As discussed by the authors, their finding suggests a role for the basket in promoting the export of certain types of RNAs rather than retention, a model also supported by more recent studies in mammalian cells. Moreover, their findings also collaborate with a recent paper showing that in yeast, not all nuclear pores contain a basket (PMID: 36220102), an observation that also questioned the gatekeeper model of the basket, as it is difficult to imagine how the basket can serve as a gatekeeper if not all nuclear pore contain such a structure.

Weaknesses:

One weakness of this study is that all their experiments rely on using synthetic splicing reporter containing a lacZ gene that produces a relatively long transcript compared to the average yeast mRNA.

The rationale for using a reporter containing the brG (G branch point) resulting in more stable lariat intermediates due to them being inefficient substrates for the debranching enzyme Dbr1 could be described earlier in the manuscript, as this otherwise only becomes clear towards the end, what is confusing.

Discussion of their observation in the context that, in yeast, not all pores contain a basket would be useful.

Reviewer #3 (Public Review):

Summary:

The authors provide the first image analysis by cryoET of toroids assembled by FtsZ crosslinked by ZapD. Previously toroids of FtsZ alone have been imaged only in projection by negative stain EM. The authors attempt to distinguish ZapD crosslinks from the underlying FtsZ filaments. I did not find this distinction convincing, especially because it seems inconsistent with the 1:1 stoichiometry demonstrated by pelleting. I was intrigued by one image showing straight filament pairs, which may suggest a new model for how ZapD crosslinks FtsZ filaments.

Strengths:

(1) The first image analysis of FtsZ toroids by cryoET.<br /> (2) The images are accompanied by pelleting assays that convincingly establish a 1:1 stoichiometry of FtsZ:ZapD subunits.<br /> (3) Fig. 5 shows an image of a pair of FtsZ filaments crosslinked by ZapD. This seems to have higher resolution than the toroids. Importantly, it suggests a new model for the structure of FtsZ-ZapD that resolves previously unrecognized conflicts. (This is discussed below under weaknesses, because it is so far only supported by a single image.)

Weaknesses:

This paper reports a study by cryoEM of polymers and bundles assembled from FtsZ plus ZapD. Although previous studies by other labs have focused on straight bundles of filaments, the present study found toroids mixed with these straight bundles, and they focused most of their study on the toroids. In the toroids they attempt to delineate FtsZ filaments and ZapD crosslinks. A major problem here is with the stoichiometry. Their pelleting assays convincingly established a stoichiometry of 1:1, while the mass densities identified as ZapD are sparse and apparently well below the number of FtsZ (FtsZ subunits are not resolved in the reconstructions, but the continuous sheets or belts seem to have a lot more mass than the identified crosslinks.) Apart from the stoichiometry I don't find the identification of crosslinks to be convincing. It is missing an important control - cryoET of toroids assembled from pure FtsZ, without ZapD.

However, if I ignore these and jump to Fig. 5, I think there is an important discovery that resolves controversies in the present study as well as previous ones, controversies that were not even recognized. The controversy is illustrated by the Schumacher 2017 model (their Fig. 7), which is repeated in a simplified version in Fig. 1a of the present mss. That model has a two FtsZ filaments in a plane facing ZapD dimers which bridge them. In this planar model the C-terminal linker, and the ctd of FtsZ that binds ZapD facing each other and the ZapD in the middle, with. The contradiction arises because the C-terminus needs to face the membrane in order to attach and generate a bending force. The two FtsZ filaments in the planar model are facing 90{degree sign} away from the membrane. A related contradiction is that Houseman et al 2016 showed that curved FtsZ filaments have the C terminus on the outside of the curve. In a toroid the C termini should all be facing the outside. If the paired filaments had the C termini facing each other, they could not form a toroid because the two FtsZ filaments would be bending in opposite directions.

Fig. 5 of the present mss seems to resolve this by showing that the two FtsZ filaments and ZapD are not planar, but stacked. The two FtsZ filaments have their C termini facing the same direction, let's say up, toward the membrane, and ZapD binds on top, bridging the two. The spacing of the ctd binding sites on the Zap D dimer is 6.5 nm, which would fit the ~8 nm width of the paired filament complex observed in the present cryoEM (Fig S13). In the Schumacher model the width would be about 20 nm. Importantly, the stack model has the ctd of each filament facing the same direction, so the paired filaments could attach to the membrane and bend together (using ctd's not bound by ZapD). Finally, the new arrangement would also provide an easy way for the complex to extend from a pair of filaments to a sheet of three or four or more.

A problem with this new model from Fig. 5 is that it is supported by only a single example of the paired FtsZ-ZapD complex. If this is to be the basis of the interpretation, more examples should be shown. Maybe examples could be found with three or four FtsZ filaments in a sheet.

What then should be done with the toroids? I am not convinced by the identification of ZapD as "connectors." I think it is likely that the ZapD is part of the belts that I discuss below, although the relative location of ZapD in the belts is not resolved. It is likely that the resolution in the toroid reconstructions of Fig. 4, S8,9 is less than that of the isolated pf pair in Fig. 5c.

Importantly, If the authors want to pursue the location of ZapD in toroids, I suggest they need to compare their ZapD-containing toroids with toroids lacking ZapD. Popp et al 2009 have determined a variety of solution conditions that favor the assembly of toroids by FtsZ with no added protein crosslinker. It would be very interesting to investigate the structure of these toroids by the present cryoEM methods, and compare them to the FtsZ-ZapD toroids. I suspect that the belts seen in the ZapD toroids will not be found in the pure FtsZ toroids, confirming that their structure is generated by ZapD.

Reviewer #3 (Public Review):

Summary:

In this paper, Wang et al. provide the most comprehensive description and comparison of the expression of the different genes required to synthesize, transport, and recycle the most common neurotransmitters (Glutamate, Acetylcholine, GABA, Serotonin, Dopamine, Octopamine, and Tyramine) used by hermaphrodite and male C. elegans. This paper will be a seminal reference in the field. Building and contrasting observations from previous studies using fosmid, multicopy reporters, and single-cell sequencing, they now describe CRISPR/Cas-9-engineered reporter strains that, in combination with the multicolor pan-neuronal labeling of all C. elegans neurons (NeuroPAL), allows rigorous elucidation of neurotransmitter expression patterns. These novel reporters also illuminate previously unappreciated aspects of neurotransmitter biology in C. elegans, including sexual dimorphism of expression patterns, co-transmission, and the elucidation of cell-specific pathways that might represent new forms of neurotransmission.

Strengths:

The authors set out to establish neurotransmitter identities in C. elegans males and hermaphrodites via varying techniques, including integration of previous studies, examination of expression patterns, and generation of endogenous CRISPR-labeled alleles. Their study is comprehensive, detailed, and rigorous, and achieves the aims. It is an excellent reference for the field, particularly those interested in biosynthetic pathways of neurotransmission and their distribution in vivo, in neuronal and non-neuronal cells.

Weaknesses:

No weaknesses were noted. The authors do a great job linking their characterizations with other studies and techniques, giving credence to their findings. As the authors note, there are sexually dimorphic differences across animals and varying expression patterns of enzymes. While it is unlikely there will be huge differences in the reported patterns across individual animals, it is possible that these expression patterns could vary developmentally, or based on physiological or environmental conditions. It is unclear from the study how many animals were imaged for each condition, and if the authors noted changes across individuals during development (could be further acknowledged in the discussion?)

Reviewer #3 (Public Review):

In the submitted manuscript, Dong and colleagues set out to dissect the role of the Rab10 small GTPase on the intracellular trafficking and exocytosis of dense core vesicles (DCVs). While the authors have already shown that Rab3 plays a central role in the exocytosis of DVC in mammalian neurons, the roles of several other Rab-members have been identified genetically, but their precise mechanism of action in mammalian neurons remains unclear. In this study, the authors use a carefully designed and thoroughly executed series of experiments, including live-cell imaging, functional calcium-imaging, proteomics, and electron microscopy, to identify that DCV secretion upon Rab10 depletion in adult neurons is primarily a result of dysregulated protein synthesis and, to a lesser extent, disrupted intracellular calcium buffering. Given that the full deletion of Rab10 has a deleterious effect on neurons and that Rab10 has a major role in axonal development, the authors cautiously employed the knock-down strategy from 7 DIV, to focus on the functional impact of Rab10 in mature neurons. The experiments in this study were meticulously conducted, incorporating essential controls and thoughtful considerations, ensuring rigorous and comprehensive results.

Reviewer #3 (Public Review):

Summary

The authors have made simultaneous recordings of the responses of large numbers of neurons from the primary visual cortex of macaque monkeys using optical two-photon imaging of calcium signals from the superficial layers of the cortex. Recordings were made to compare the responses of the cortical neurons under normal binocular viewing of a flat screen with both eyes open and monocular viewing of the same screen with one eye's view blocked by a translucent filter. The screen displayed visual stimuli comprising small contrast patches of Gabor function distributions of luminance, a stimulus that is known to excite cortical neurons.

Strengths

This is an important data set, given the large number of neurons recorded. The authors present a simple model to explain binocular combination of neuronal signals from the right and left eyes. The work advances the use of two-photon imaging in the cerebral neocortex. The research design adds valuable information to our understanding of the organization of binocular vision in macaque monkeys, which are the only realistic animal model of human vision for the study of binocular interactions.

Limitations and Weaknesses

(1) Given that these recordings are made optically, these results reflect primarily activations of neurons in the superficial layers of the cortex. This limitation arises from the usual constraints (depth of cortex, degree of myelination) on optical imaging in the macaque cortex. This means that the sample of neurons forming this data set is not fully representative of the population of binocular neurons within the visual cortex. This limitation is important in comparing the outcome of these experiments with the results from other studies of binocular combination, which have used single-electrode recording. Electrode recording will result in a sample of neurons that is drawn from many layers of the cortex, rather than just the superficial layers, noting that electrode recordings also carry different risks of sampling bias.

(2) Single neuron recording of binocular neurons in the primary visual cortex has shown that these neurons often have some spontaneous activity. Assessment of this spontaneous level of firing is important for accurate model fitting [1]. The present imaging approach works exclusively with differential measurements of neuronal signals, so assessment of the level of spontaneous activity is not feasible.

(3) The arrangements for visual stimulation and comparison of binocular and monocular responses mean that the stereoscopic disparity of the binocular stimuli is always at zero or close to zero. The consequence is that the experimental design does not test the cortical response over a range of different binocular depths.

The animal's fixation point is in the centre of a single display that is viewed binocularly. The fixation point is, by definition, at zero disparity.. Provided that the animals accurately converged their eyes on the binocular fixation point, then the disparity of the visual stimuli across the whole display will always be at or close to zero. However, we already know from earlier work that neurons in the visual cortex exhibit a range of selectivity for binocular disparity. Some neurons have their peak response at non-zero disparities, representing binocular depths nearer than the fixation depth or beyond it.

There are also other neurons whose response is maximally suppressed by disparities at the depth of the fixation point (so-called Tuned Inhibitory [TI] neurons). The simple model and analysis presented in the paper for the summation of monocular responses to predict binocular responses will perform adequately for neurons that are tuned to zero disparity, so-called tuned excitatory neurons [TE], but is necessarily compromised when applied to neurons that have other, different tuning profiles for binocular disparity. Specifically, when neurons are stimulated binocularly with a non-preferred disparity, the binocular response may be lower than the monocular response [2, 3]. The same limitation applies to another recent paper [4].

This more realistic view of binocular responses needs to be considered further to gain a full picture of the operation of the visual cortex in responding to binocular depth

Citations

1. Prince, S.J.D., Pointon, A.D., Cumming, B.G., and Parker, A.J., (2002). Quantitative analysis of the responses of V1 neurons to horizontal disparity in dynamic random-dot stereograms. Journal of Neurophysiology, 87: 191-208.

2. Prince, S.J.D., Cumming, B.G., and Parker, A.J., (2002). Range and mechanism of encoding of horizontal disparity in macaque V1. Journal of Neurophysiology, 87: 209-221.

3. Poggio, G.F. and Fischer, B., (1977). Binocular interaction and depth sensitivity in striate and prestriate cortex of behaving rhesus monkey. Journal of Neurophysiology, 40: 1392-1405 doi 10.1152/jn.1977.40.6.1392.

4. B. A. Mitchell, K. Dougherty, J. A. Westerberg, B. M. Carlson, L. Daumail, A. Maier, et al. (2022) Stimulating both eyes with matching stimuli enhances V1 responses.<br /> iScience 2022 Vol. 25 Issue 5 DOI: 10.1016/j.isci.2022.104182

Reviewer #3 (Public Review):

Strengths:

The authors present differences between ADHD and TD children in biological motion processing, and this question has not received as much attention as equivalent processing capabilities in autism. They use a task that appears well controlled. They raise some interesting mechanistic possibilities for differences in local and global motion processing, which are distinctions worth exploring. The group differences will therefore be of interest to those studying ADHD, as well as other developmental conditions, and those examining biological motion processing mechanisms in general.

Weaknesses:

The data are not strong enough to support claims about differences between global and lobal processing wrt social communication skills and age. The mechanistic possibilities for why these abilities may dissociate in such a way are interesting, but the crucial tests of differences between correlations do not present a clear picture. Further empirical work would be needed to test the authors' claims. Specifics:

The authors state frequently that it was the local BM task that related to social communication skills (SRS) and not the global tasks. However, the results section shows a correlation between SRS and all three tasks. The only difference is that when looking specifically within the ADHD group, the correlation is only significant for the local task. The supplementary materials demonstrate that tests of differences between correlations present an incomplete picture. Currently they have small samples for correlations, so this is unsurprising.

Theoretical assumptions. The authors make some statements about local vs global biological motion processing that should still be made more tentatively. They assume that local processing is specifically genetically whereas global processing is a product of experience. These data in newborn chicks are controversial and confounded - I cannot remember the specifics but I think there an upper vs lower visual field complexity difference here.

Readability. The manuscript needs very careful proofreading and correction for grammar. There are grammatical errors throughout.

"Il résulte donc de ce qui précède, qu’en l’absence d’obstacle juridique, l’organe délibératif de l’EPLE est parfaitement libre d’adopter le principe d’une répartition de l’année scolaire en deux semestres, au lieu de trois trimestres. Une fois cette résolution arrêtée, il conviendra également de modifier en conséquence le règlement intérieur de l’établissement."

Reviewer #3 (Public Review):

Summary:

This study aimed to investigate whether the development of functional connectivity (FC) is modulated by early physical growth and whether these might impact cognitive development in childhood. This question was investigated by studying a large group of infants (N=204) assessed in Gambia with fNIRS at 5 visits between 5 and 24 months of age. Given the complexity of data acquisition at these ages and following data processing, data could be analyzed for 53 to 97 infants per age group. FC was analyzed considering 6 ensembles of brain regions and thus 21 types of connections. Results suggested that: i) compared to previously studied groups, this group of Gambian infants have different FC trajectory, in particular with a change in frontal inter-hemispheric FC with age from positive to null values; ii) early physical growth, measured through weight-for-length z-scores from birth on, is associated with FC at 24 months. Some relationships were further observed between FC during the first two years and cognitive flexibility at 4-5 years of age, but results did not survive corrections for multiple comparisons.

Strengths:

The question investigated in this article is important for understanding the role of early growth and undernutrition on brain and behavioral development in infants and children. The longitudinal approach considered is highly relevant to investigate neurodevelopmental trajectories. Furthermore, this study targets a little-studied population from a low-/middle-income country, which was made possible by the use of fNIRS outside the lab environment. The collected dataset is thus impressive and it opens up a wide range of analytical possibilities.

Weaknesses:

- Analyzing such a huge amount of collected data at several ages is not an easy task to test developmental relationships between growth, FC, and behavioral capacities. In its present form, this study and the performed analyses lack clarity, unity and perhaps modeling, as it suggests that all possible associations were tested in an exploratory way without clear mechanistic hypotheses. Would it be possible to specify some hypotheses to reduce the number of tests performed? In particular, considering metrics at specific ages or changes in the metrics with age might allow us to test different hypotheses: the authors might clarify what they expect specifically for growth-FC-behaviour associations. Since some FC measures and changes might be related to one another, would it be reasonable to consider a dimensionality reduction approach (e.g., ICA) to select a few components for further correlation analyses?

- It seems that neurodevelopmental trajectories over the whole period (5-24 months) are little investigated, and considering more robust statistical analyses would be an important aspect to strengthen the results. The discussion mentions the potential use of structural equation modelling analyses, which would be a relevant way to better describe such complex data.

- Given the number of analyses performed, only describing results that survive correction for multiple comparisons is required. Unifying the correction approach (FDR / Bonferroni) is also recommended. For the association between cognitive flexibility and FC, results are not significant, and one might wonder why FC at specific ages was considered rather than the change in FC with age. One of the relevant questions of such a study would be whether early growth and later cognitive flexibility are related through FC development, but testing this would require a mediation analysis that was not performed.

- Growth is measured at different ages through different metrics. Justifying the use of weight-for-length z-scores would be welcome since weight-for-age z-scores might be a better marker of growth and possible undernutrition (this impacting potentially both weight and length). Showing the distributions of these z-scores at different ages would allow the reader to estimate the growth variability across infants.

- Regarding FC, clarifications about the long-range vs short-range connections would be welcome, as well as drawing a summary of what is expected in terms of FC "typical" trajectory, for the different brain regions and connections, as a marker of typical development. For instance, the authors suggest that an increase in long-range connectivity vs a decrease in short-range is expected based on previous fNIRS studies. However anatomical studies of white matter growth and maturation would suggest the reverse pattern (short-range connections developing mostly after birth, contrarily to long-range connections prenatally).

The authors test associations between FC and growth, but making sense of such modulation results is difficult without a clearer view of developmental changes per se (e.g., what does an early negative FC mean? Is it an increase in FC when the value gets close to 0? In particular, at 24m, it seems that most FC values are not significantly different from 0, Figure 2B). Observing positive vs negative association effects depending on age is quite puzzling. It is also questionable, for some correlation analyses with cognitive flexibility, to focus on FC that changes with age but to consider FC at a given age.

- The manuscript uses inappropriate terms "to predict", "prediction" whereas the conducted analyses are not prediction analyses but correlational.

Reviewer #3 (Public Review):

Summary:

Garcia et al., investigated whether the human left superior frontal sulcus (SFS) is involved in integrating evidence for decisions across either perceptual and/or value-based decision-making. Specifically, they had 20 participants perform two decision-making tasks (with matched stimuli and motor responses) in an fMRI scanner both before and after they received continuous theta burst transcranial magnetic stimulation (TMS) of the left SFS. The stimulation thought to decrease neural activity in the targeted region, led to reduced accuracy on the perceptual decision task only. The pattern of results across both model-free and model-based (Drift diffusion model) behavioural and fMRI analyses suggests that the left SLS plays a critical role in perceptual decisions only, with no equivalent effects found for value-based decisions. The DDM-based analyses revealed that the role of the left SLS in perceptual evidence accumulation is likely to be one of decision boundary setting. Hence the authors conclude that the left SFS plays a domain-specific causal role in the accumulation of evidence for perceptual decisions. These results are likely to add importance to the literature regarding the neural correlates of decision-making.

Strengths:

The use of TMS strengthens the evidence for the left SFS playing a causal role in the evidence accumulation process. By combining TMS with fMRI and advanced computational modelling of behaviour, the authors go beyond previous correlational studies in the field and provide converging behavioural, computational, and neural evidence of the specific role that the left SFS may play.

Sophisticated and rigorous analysis approaches are used throughout.

Weaknesses:

Though the stimuli and motor responses were equalised between the perception and value-based decision tasks, reaction times (according to Figure 1) and potential difficulty (Figure 2) were not matched. Hence, differences in task difficulty might represent an alternative explanation for the effects being specific to the perception task rather than domain-specificity per se.

No within- or between-participants sham/control TMS condition was employed. This would have strengthened the inference that the apparent TMS effects on behavioural and neural measures can truly be attributed to the left SFS stimulation and not to non-specific peripheral stimulation and/or time-on-task effects.

No a priori power analysis is presented.

Reviewer #3 (Public Review):

Summary:

In this very important study by Dantzer et al., 'Emerging role of oncogenic b-catenin in exosome biogenesis as a driver of immune escape in hepatocellular carcinoma' the authors define a role for oncogenic b-catenin on exosome biology and explore the link between reduce exosome secretion and tumor immune cell evasion. Using transcriptional and proteomic analysis of hepatocellular carcinoma cells with either oncogenic or wildtype b-catenin the authors find that oncogenic b-catenin negatively regulates exosome biogenesis.

The authors can provide compelling evidence that oncogenic b-catenin in different hepatocellular carcinoma cells negatively regulates exosome biogenesis and secretion, by downregulation of, amongst others, SDC4 and RAB27A, two proteins involved in exosome biogenesis. The authors corroborate these results by inducing b-catenin activation using CHIR99021 in a hepatocarcinoma cell line with non-oncogenic bCatenin (Huh7 cells). The authors can further demonstrate convincingly that a reduction in exosome release by hepatocarcinoma spheroids leads to a reduction in immune cell infiltration into the tumor spheroid.

Strengths:

This is a very important and well-conceived study, that appeals to a readership beyond the field of hepatocarcinoma. The authors demonstrate a compelling link between oncogenic bCatenin and exosome biogenesis. Their results are convincing and with well-designed control experiments. The authors included various complementary lines of investigation to verify their findings.

Weaknesses:

One limitation of this study is that the mechanistic relationship of exosome release and how they affect immune cells remains to be elucidated. In this context, the authors conclusions rest on the assumption that hepatocarcinoma immune evasion is based exclusively on the reduced number of exosomes. However, the authors do not analyze exosome composition between exosomes of wild type and oncogenic background, which could be different.

Reviewer #3 (Public Review):

Summary:

This study aims to understand gene regulation of the plant bacterial pathogen Pseudomonas syringae. Although the function of some TFs has been characterized in this strain, a global picture of the gene regulatory network remains elusive. The authors conducted a large-scale ChIP-seq analysis, covering 170 out of 301 TFs of this strain, and revealed gene regulatory hierarchy with functional validation of some previously uncharacterized TFs.

Strengths:

- This study provides one of the largest ChIP-seq datasets for a single bacterial strain, covering more than half of its TFs. This impressive resource enabled comprehensive systems-level analysis of the TF hierarchy.

- This study identified novel gene regulation and function with validations through biochemical and genetic experiments.

- The authors attempted on broad analyses including comparisons between different bacterial strains, providing further insights into the diversity and conservation of gene regulatory mechanisms.

Weaknesses:

(1) Some conclusions are not backed by quantitative or statistical analyses, and they are sometimes overinterpreted.

(2) Some figures and analyses are not well explained, and I was not able to understand them.

(3) The Method section lacks depth, especially in data analyses. It is strongly recommended that the authors share their analysis codes so that others can reproduce the analyses.

Reviewer #3 (Public Review):

When members of two related but diverged species mate, the resulting hybrids can produce offspring where parts of one species' genome replace those of the other. These "introgressions" often create regions with a much greater density of sequence differences than are normally found between members of the same species. Previous studies have shown that increased sequence differences, when heterozygous, can reduce recombination during meiosis specifically in the region of increased difference. However, most of these studies have focused on crossover recombination, and have not measured noncrossovers. The current study uses a pair of Saccharomyces uvarum crosses: one between two natural isolates that, while exhibiting some divergence, do not contain introgressions; the other is between two fermentation strains that, when combined, are heterozygous for 9 large regions of introgression that have much greater divergence than the rest of the genome. The authors wished to determine if introgressions differently affected crossovers and noncrossovers, and, if so, what impact that would have on the gene shuffling that occurs during meiosis.

While both crossovers and noncrossovers were measured, assessing the true impact of increased heterology (inherent in heterozygous introgressions) is complicated by the fact that the increased marker density in heterozygous introgressions also increases the ability to detect noncrossovers. The authors used a relatively simple correction aimed at compensating for this difference, and based on that correction, conclude that, while as expected crossovers are decreased by increased sequence heterology, counter to expectations noncrossovers are substantially increased. They then show that, despite this, genetic shuffling overall is substantially reduced in regions of heterozygous introgression. However, it is likely that the correction used to compensate for the effect of increased sequence density is defective, and has not fully compensated for the ascertainment bias due to greater marker density. The simplest indication of this potential artifact is that, when crossover frequencies and "corrected" noncrossover frequencies are taken together, regions of introgression often appear to have greater levels of total recombination than flanking regions with much lower levels of heterology. This concern seriously undercuts virtually all of the novel conclusions of the study.

Until this methodological concern is addressed, the work will not be a useful contribution to the field.

Reviewer #3 (Public Review):

While I am not a specialist in this field, I do have some knowledge of the subject matter and the computational aspects involved.

The authors employ simple machine learning techniques (such as SVM) for the following purposes:

a. Prediction of aversive valence.<br /> b. Predicting anti-repellent chemicals.<br /> c. Predicting calcium mobilization.

The approach is commonplace in chemoinformatics literature.

Weaknesses:

- All the above models are presented discretely, making it difficult to discern experiment design principles and connectedness.<br /> - The ML work is rudimentary, lacking adequate details. Chemoinformatics has reached great heights, and SVM does not seem contemporary.<br /> - There is significant existing research on finding repellents.

Strengths:

- Authors attempt to make a case for calcium mobilization in the context of repellency. This aspect sounds interesting but is not surprising.<br /> - Behavioral profiling of repellents could be useful.

Reviewer #3 (Public Review):

Summary:<br /> This work focuses on accessibility of scientific images for individuals with color vision deficiencies, particularly deuteranopia. The research involved an analysis of images from eLife published in 2012-2022. The authors manually reviewed nearly 5,000 images, comparing them with simulated versions representing the perspective of individuals with deuteranopia, and also evaluated several methods to automatically detect such images including training a machine-learning algorithm to do so, which performed the best. The authors found that nearly 13% of the images could be challenging for people with deuteranopia to interpret. There was a trend toward a decrease in problematic images over time, which is encouraging.

Strengths:<br /> The manuscript is well organized and written. It addresses inclusivity and accessibility in scientific communication, and reinforces that there is a problem and that in part technological solutions have potential to assist with this problem.

The number of manually assessed images for evaluation and training an algorithm is, to my knowledge, much larger than any existing survey. This is a valuable open source dataset beyond the work herein.

The sequential steps used to classify articles follow best practices for evaluation and training sets.

Weaknesses:<br /> I do not see any major issues with the methods. The authors were transparent with the limitations (the need to rely on simulations instead of what deuteranopes see), only capturing a subset of issues related to color vision deficiency, and the focus on one journal that may not be representative of images in other journals and disciplines.

Reviewer #3 (Public Review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

Another uncertainty in both the ChIP and immunofluorescence datasets is the accessibility of the epitope. This weakness is highlighted by the apparent loss of H1.2 and H1.4 in mitotic chromosomes that is revealed to be false by the detection of the phosphorylated species. The distributions relative to the surface of chromosomes in mitosis and the depletion of H1.2, H1.3, and H1.5 from the central regions of interphase nuclei reveals an unusual dissipation of the staining that is suggestive of antibody accessibility problems. The overall image quality of the immunofluorescence images is poor, further complicating analysis.

Reviewer #3 (Public Review):

In this study, Yang et al. address a fundamental question of the role of dorsal striatum in neural coding of gait. The authors study the respective role of D1 and D2 MSNs by linking their balanced activity to detailed gait parameters. In addition, they put in parallel the striatal activity related to whole-body measures such as initiation/cessation of movement or body speed. They are using an elegant combination of high-resolution single-limb motion tracking, identification of bouts of movements and electrophysiological recordings of striatal neurons to correlate those different parameters. Subpopulations of striatal output neurons (D1 and D2 expressing neurons) are identified in neural recordings with optogenetic tagging. Those complementary approaches show that a subset of striatal neurons have phase-locked activity to individual limbs. In addition, more than a third of MSNs appear to encode all three aspects of motor behavior addressed here, initiation/cessation of movement, body speed and gait. This activity is balanced between D1 and D2 neurons, with a higher activity of D1 neurons only for movement initiation. Finally, alterations of gait, and the associated striatal activity, is studied in a mouse model of Parkinson's Disease, using 6-OHDA lesions in the medial forebrain bundle (MFB). In the 6OHDA mice, there is an imbalance toward D2 activity.

Strengths:

The study combines elegant approaches to correlate cell-specific striatal activity with specific aspects of motion and how it is affected in a PD model. The results are convincing, and the methodology supports the conclusions presented here.

Weaknesses:

All the data were not fully exploited or explained in the first version of the manuscript and the present version has been significantly improved.

There is a long-standing debate on the respective role of D1 and D2 MSNs on the control of movement. This study goes beyond prior work by providing detailed quantification of individual limb kinematics, in parallel of whole-body motion, and showing high proportion of MSNs to be phase-locked to precise gait cycle and also encoding whole-body motion. The temporal resolution used here highlights preferential activity of D1 MSN at the movement starts, where previous studies described a more balanced involvement. Finally they reveal neural mechanisms of dopamine depletion induced gait alterations, with a preponderant phase-locked activity of D2 neurons.

Reviewer #3 (Public Review):

Summary:

Male fertility depends on both sperm and seminal plasma, but the functional effect of seminal plasma on sperm has been relatively understudied. The authors investigate the testosterone-dependent synthesis of seminal plasma and identify oleic acid as a key factor in enhancing sperm fertility.

Strengths:

The evidence for changes in cell proliferation and metabolism of seminal vesicle epithelial cells and the identification of oleic acid as a key factor in seminal plasma is solid.

Weaknesses:

The evidence that oleic acids enhance sperm fertility in vivo needs more experimental support, as the main phenotypic effect in vitro provided by the authors remains simply as an increase in the linearity of sperm motility, which does not necessarily correlate with enhanced sperm fertility.

Reviewer #3 (Public Review):

Summary:

The authors aimed to study the activation of gliogenesis and the role of newborn astrocytes in a post-ischemic scenario. Combining immunofluorescence, BrdU-tracing, and genetic cellular labelling, they tracked the migration of newborn astrocytes (expressing Thbs4) and found that Thbs4-positive astrocytes modulate the extracellular matrix at the lesion border by synthesis but also degradation of hyaluronan. Their results point to a relevant function of SVZ newborn astrocytes in the modulation of the glial scar after brain ischemia. This work's major strength is the fact that it is tackling the function of SVZ newborn astrocytes, whose role is undisclosed so far.

Strengths:

The article is innovative, of good quality, and clearly written, with properly described Materials and Methods, data analysis, and presentation. In general, the methods are designed properly to answer the main question of the authors, being a major strength. Interpretation of the data is also in general well done, with results supporting the main conclusions of this article.

Weaknesses:

However, there are some points of this article that still need clarification to further improve this work.

- As a first general comment, is it possible that the increase in Thbs4-positive astrocytes can also happen locally close to the glia scar, through the proliferation of local astrocytes or even from local astrocytes at the SVZ? As it was shown in published articles most of the newborn astrocytes in the adult brain actually derive from proliferating astrocytes, and a smaller percentage is derived from NSCs. How can the authors rule out a contribution of local astrocytes to the increase of Thbs4-positive astrocytes? The authors also observed that only about one-third of the astrocytes in the glial scar derived from the SVZ.

- It is known that the local, GFAP-reactive astrocytes at the scar can form the required ECM. The authors propose a role of Thbs4-positive astrocytes in the modulation, and perhaps maintenance, of the ECM at the scar, thus participating in scar formation likewise. So, this means that the function of newborn astrocytes is only to help the local astrocytes in the scar formation and thus contribute to tissue regeneration. Why do we need specifically the Thbs4-positive astrocytes migrating from the SVZ to help the local astrocytes? Can you discuss this further?

- The authors observed that the number of BrdU- and DCX-positive cells decreased 15 dpi in all OB layers (Fig. S5). They further suggest that ischemia-induced a change in the neuroblasts ectopic migratory pathway, depriving the OB layers of the SVZ newborn neurons. Are the authors suggesting that these BrdU/DCX-positive cells now migrate also to the ischemic scar, or do they die? In fact, they see an increase in caspase-3 positive cells in the SVZ after ischemia, but they do not analyse which type of cells are dying. Alternatively, is there a change in the fate of the cells, and astrogliogenesis is increased at the expense of neurogenesis? The authors should understand which cells are Cleaved-caspase-3 positive at the SVZ and clarify if there is a change in cell fate. Also please clarify what happens to the BrdU/DCX-positive cells that are born at the SVZ but do not migrate properly to the OB layers.

- The authors showed decreased Nestin protein levels at 15 dpi by western blot and immunostaining shows a decrease already at 7div (Figure 2). These results mean that there is at least a transient depletion of NSCs due to the promotion of astrogliogenesis. However, the authors show that at 30dpi there is an increase of slow proliferating NSCs (Figure 3). Does this mean, that there is a reestablishment of the SVZ cytogenic process? How does it happen, more specifically, how NSCs number is promoted at 30dpi? Please explain how are the NSCs modulated throughout time after ischemia induction and its impact on the cytogenic process.

- The authors performed a classification of Thbs4-positive cells in the SVZ according to their morphology. This should be confirmed with markers expressed by each of the cell subtypes.

- In Figure S6, the authors quantified HABP spots inside Thbs4-positive astrocytes. Please show a higher magnification picture to show how this quantification was done.

Reviewer #3 (Public Review):

In this manuscript, the authors investigated the effects of deletion of the ER-plasma membrane/Golgi tethering proteins tricalbins (Tcb1-3) on vacuolar morphology to demonstrate the role of membrane contact sites (MCSs) in regulating vacuolar morphology in Saccharomyces cerevisiae. Their data show that tricalbin deletion causes vacuolar fragmentation possibly in parallel with TORC1 pathway. In addition, their data reveal that levels of various lipids including ceramides, long-chain base (LCB)-1P, and phytosphingosine (PHS) are increased in tricalbin-deleted cells. The authors find that exogenously added PHS can induce vacuole fragmentation and by performing analyses of genes involved in sphingolipid metabolism, they conclude that vacuolar fragmentation in tricalbin-deleted cells is due to the accumulated PHS in these cells. Importantly, exogenous PHS- or tricalbin deletion-induced vacuole fragmentation was suppressed by loss of the nucleus vacuole junction (NVJ), suggesting the possibility that PHS transported from the ER to vacuoles via the NVJ triggers vacuole fission. Of note, the authors find that hyperosmotic shock increases intracellular PHS levels, suggesting a general role of PHS in vacuole fission in response to physiological vacuolar division-inducing stimuli.

This work provides valuable insights into the relationship between MCS-mediated sphingolipid metabolism and vacuole morphology. The conclusions of this paper are mostly supported by their results, but inclusion of direct evidence indicating increased transport of PHS from the ER to vacuoles via NVJ in response to vacuolar division-inducing stimuli would have strengthened this study.

There is another weakness in their claim that the transmembrane domain of Tcb3 contributes to the formation of the tricalbin complex which is sufficient for tethering ER to the plasma membrane and the Golgi complex. Their claim is based only on the structural simulation, but not on by biochemical experiments such as co-immunoprecipitation and pull-down.

Reviewer #3 (Public Review):

Summary: Irisin has previously been demonstrated to be a muscle-secreted factor that affects skeletal homeostasis. Through the use of different experimental approaches, such as genetic knockout models, recombinant Irisin treatment, or different cell lines, the role of Irisin on skeletal homeostasis has been revealed to be more complex than previously thought and this warrants further examination of its role. Therefore, the current study sought to rigorously examine the effects of global Irisin knockout (KO) in male and female mouse bone. Authors demonstrated that in calcium-demanding settings, such as lactation or low-calcium diet, female Irisin KO mice lose less bone compared to wildtype (WT) female mice. Interestingly male Irisin KO mice exhibited worse skeletal deterioration compared to WT male mice when fed low-calcium diet. When examined for transcriptomic profiles of osteocyte-enriched cortical bone, authors found that Irisin KO altered the expression of osteocytic osteolysis genes as well as steroid and fatty acid metabolism genes in males but not in females. These data support authors' conclusion that Irisin regulates skeletal homeostasis in a sex-dependent manner.

Strengths:

The major strength of the study is rigorous examination of the effects of Irisin deletion in the settings of skeletal maturity and increased calcium demands in female and male mice. Since many of the common musculoskeletal disorders are dependent on sex, examining both sexes in the preclinical setting is crucial. Had the investigators only examined females or males in this study, the conclusion from each sex would have contradicted each other regarding the role of Irisin on bone. Also, the approaches are thorough and comprehensive that assess the functional (mechanical testing), morphological (microCT, BSEM, and histology), and cellular (RNA-seq) properties of bone. Transcriptomic data deposited to NCBI GEO data repository will be a valuable resource to musculoskeletal researchers who aim to further assess the affects of Irisin on skeleton.

Weaknesses:

One of the weaknesses of this study is a lack of detailed mechanistic analysis of why Irisin has sex-dependent role on skeletal homeostasis. However, the osteocyte transcriptome comparisons between LC females vs. LC males lay a foundation for such future mechanistic studies.

Another weakness is authors did not present data that convincingly demonstrate that Irisin secretion is altered in the skeletal muscle between female vs. male WT mice in response to calcium restriction. The supplement skeletal muscle data only present functional and electrophysiological outcomes. Since Itgav or Itgb5 were not different in any of the experimental groups, it is assumed that the changes in the level of Irisin is responsible for the phenotypes observed in WT mice. Assessing Irisin expression will further strengthen the conclusion based on observing skeletal changes that occur in Irisin KO male and female mice.

Reviewer #3 (Public Review):

Summary:

The authors show that a GAN can learn to reproduce the distribution of outputs of a neuron endowed with Oja's plasticity rule throughout its learning process by learning a plasticity rule. The GAN does not, however, learn Oja's rule. Indeed, the plasticity dynamics it infers can differ dramatically from the true dynamics. The authors propose this approach as a way to uncover families of putative plasticity rules consistent with observed activity patterns in biological systems.

Oja's rule was a great choice for the comparison because it makes explicit, I think, the limitations of this approach. As is well known, Oja's rule allows a (linear) neuron to learn the first principal component of its inputs; the synaptic weights converge to the first eigenvector of the input covariance. After this learning process, the response of a neuron to a particular input sample measures the weighted angle between that input and that principal component.

The other, meta-learned plasticity rules that the authors' GAN uncovers notably do not learn the same computation as Oja's rule (Figure 2). This is, to me, the central finding of the paper and fleshed out nicely. It seems to me that this may be because the objective of the GAN is only to reproduce the marginal output statistics of the neuron. It is, if I understand correctly, blind to the input samples, the inputs' marginal statistics, and to correlations between the input and output. I wonder if a GAN that also had some knowledge of the correlation between input and outputs might be more successful at learning the underlying true dynamics.

The focus on reproducing output statistics has some similarity to some types of experiments (e.g., in vivo recordings) but also seems willfully blind to other aspects of these experiments. In my experience, experimentalists are well aware that the circuits they record receive external inputs. Those inputs are often recorded (perhaps in separate experiments or studies). The point being that I'm not sure that this is an entirely fair comparison to the field.

Finally, the plasticity models studied by theoreticians are not only constructed by intuition and hand-tuning. They also draw, often heavily, on biological data and principles. Oja's rule, for example, is simply the combination of Hebbian learning with a homeostatic constraint on the total synaptic weight amplitude (under the choice of a Euclidean norm).

To me, this study very nicely exposes the caveats and risks associated with a blind machine-learning approach to model specification in biology and highlights the need for understanding underlying biological mechanisms and principles. I agree with the authors that heterogeneity and degeneracy in plasticity rules deserve much more attention in the field.

Reviewer #3 (Public Review):

Summary:

This work provides insights into predictive coding models of visual cortex processing. These models predict that visual cortex neurons will show elevated responses when there are unexpected changes to learned sequential stimulus patterns. This model is currently controversial, with recent publications providing conflicting evidence. In this work, the authors test two types of unexpected pattern variations in layer 2/3 of the mouse visual cortex. They show that pattern omission evokes elevated responses, in favor of a predictive coding model, but find no evidence for prediction errors with substituted patterns, which conflicts with both prior results in L4, and with the expectations of a predictive coding model. They also report that with sequence training, responses sparsify and decorrelate, but surprisingly find no changes in the ability of an ideal observer to decode stimulus identity or timing.

These results are an important contribution to the understanding of how temporal sequences and expectations are encoded in the primary visual cortex. However, there are several methodological concerns with the study, and some of the authors' interpretations and conclusions are unsupported by data.

Major concerns:

(1) Experimental design using a block structure. The use of a block structure on test days (0 and 5) in which sequences were presented in 100 repetition blocks leads to several potential confounds. First, there is the potential for plasticity within blocks, which could alter the responses and induce learned expectations. The ability of the authors to clearly distinguish blocks 1 and 2 on Day 0 with a decoder suggests this change over time may be meaningful.

Repeating the experiments with fully interleaved sequences on test days would alleviate this concern. With the existing data, the authors should compare responses from the first trials in a block to the last trials in a block.

This block design likely also accounts for the ability of a decoder to readily distinguish stimulus A in ABCD from A in ABBD. As all ABCD sequences were run in a contiguous block separate from ABBD, the recent history of experience is different for A stimuli in ABCD versus ABBD. Running fully interleaved sequences would also address this point, and would also potentially mitigate the impact of drift over blocks (discussed below).

(2) The computation of prediction error differs significantly for omission as opposed to substitutions, in meaningful ways the authors do not address. For omission errors, PE compares the responses of B1 and B2 within ABBD blocks. These responses are measured from the same trial, within tens of milliseconds of each other. In contrast, substitution PE is computed by comparing C in ABCD to C in ACBD. As noted above, the block structure means that these C responses were recorded in different blocks, when the state of the brain could be different. This may account for the authors' detection of prediction error for omission but not substitution. To address this, the authors should calculate PE for omission using B responses from ABCD.

(3) The behavior of responses to B and C within the trained sequence ABCD differs considerably, yet is not addressed. Responses to B in ABCD potentiate from d0-> d5, yet responses to C in the same sequence go down. This suggests there may be some difference in either the representation of B vs C or position 2 vs 3 in the sequence that may also be contributing to the appearance of prediction errors in ABBD but not ACBD. The authors do not appear to consider this point, which could potentially impact their results. Presenting different stimuli for A,B,C,D across mice would help (in the current paper B is 75 deg and C is 165 deg in all cases). Additionally, other omissions or substitutions at different sequence positions should be tested (eg ABCC or ABDC).

(4) The authors' interpretation of their PCA results is flawed. The authors write "Experience simplifies activity in principal component space". This is untrue based on their data. The variance explained by the first set of PCs does not change with training, indicating that the data is not residing in a lower dimensional ("simpler") space. Instead, the authors show that the first 5 PCs better align with their a priori expectations of the stimulus structure, but that does not mean these PCs necessarily represent more information about the stimulus (and the fact that the authors fail to see an improvement in decoding performance argues against this case). Addressing such a question would be highly interesting, but is lacking in the current manuscript. Without such analysis, referring to the PCs after training as "highly discretized" and "untangled" are largely meaningless descriptions that lack analytical support.

(5) The authors report that activity sparsifies, yet provide only the fraction of stimulus-selective cells. Given that cell detection was automated in a manner that takes into account neural activity (using Suite2p), it is difficult to interpret these results as presented. If the authors wish to claim sparsification, they need to provide evidence that the total number of ROIs drawn on each day (the denominator for sparseness in their calculation) is unbiased. Including more (or less) ROIs can dramatically change the calculated sparseness.

The authors mention sparsification as contributing to coding efficiency but do not test this. Training a decoder on variously sized subsets of their data on days 0 and 5 would test whether redundant information is being eliminated in the network over training.

(6) The authors claim their results show representational drift, but this isn't supported in the data. Rather they show that there is some information in the structure of activity that allows a decoder to learn block ID. But this does not show whether the actual stimulus representations change, and could instead reflect an unrelated artifact that changes over time (responsivity, alertness, bleaching, etc). To actually assess representational drift, the authors should directly compare representations across blocks (one could train a decoder on block 1 and test on blocks 2-5). In the absence of this or other tests of representational drift over blocks, the authors should remove the statement that "These findings suggest that there is a measurable amount of representational drift".

(7) The authors allude to "temporal echoes" in a subheading. This term is never defined, or substantiated with analysis, and should be removed.

Reviewer #3 (Public Review):

Summary:

The study by Yao, Dai and colleagues successfully describes the design of a viral gene drive against herpes simplex virus 1. Gene drives are genetic modifications designed to spread efficiently in a population. Most applications have been developed in insects to eradicate diseases such as malaria, and the design of gene drives in viruses is an exciting recent development. A viral gene drive system was first described with human cytomegalovirus, another virus of the herpesvirus family (PMID: 32985507), and the authors followed similar methods to design a gene drive against HSV-1. While some key experiments lack rigorous controls, overall the authors convincingly showed that an HSV-1 gene drive could spread efficiently in the target population in cell culture experiments. Cytomegalovirus and HSV-1 have very different infection dynamics, and these new findings suggest that viral gene drives could be developed in a wide variety of herpesviruses. This significantly expands the potential of the technology and will be of interest to readers interested in gene drives, viral engineering, or biotechnology in general.

The most novel and interesting part of the study is the comparison of gene drives relying on spCas9 and Un1Cas12f1 nuclease. Most gene drives developed to date have relied on Cas9 or similar nucleases. Cleavage and repair of the target site by non-homologous end-joining (NHEJ) can lead to the formation of drive-resistant sequences, and, depending on the selective pressure on the wild-type, gene drive and drive-resistant alleles, prevent successful gene drive propagation. By contrast to most RNA-guided nucleases, Un1Cas12f1 cleaves outside of the RNA-recognition site. The authors hypothesized that it could prevent the appearance of drive-resistant sequences, since the target sequence would be preserved after NHEJ repair. Indeed, the study convincingly showed that Un1Cas12f1 induced fewer drive-resistant mutations, which led to almost complete penetrance of the drive. However, the claim in the abstract that an "Un1Cas12f1 gene drive yielded a greater conversion" rate than Cas9 appears unsupported. Together with its smaller size, this positions Un1Cas12f1 as an interesting alternative to Cas9 for gene drives in any organism. This development will be of great interest to researchers interested in gene drives.

Strengths:

Overall, this study is well done and the main conclusions are supported by the data. The authors used flow cytometry to follow gene drive propagation, detecting either fluorescent or cell surface proteins expressed by the different viral populations. This represents an indirect but adequate way of measuring the proportion of the different viral populations, assuming that each of the target BHK cells is infected with only one virus.<br /> In particular, the results in Fig 3 showing that Un1Cas12f1 induces fewer drive-resistant mutations than Cas9 are convincing.

Weaknesses:

The manuscript presents several conceptual and methodological weaknesses that could be discussed or addressed experimentally, which would improve the overall rigor of the study.

(1) In the abstract and the text, the author claims that "HSV1 emerges as a dependable and swift platform for gene drive assessment". It is unclear if the author believes that the main interest of their work with HSV-1 is to provide a platform for testing gene drive for other organisms, or whether a gene drive for HSV-1 could be useful by itself. While their findings with Un1Cas12f1 certainly warrant investigation in other systems, the dynamics of DNA cleavage, recombination, and selection of drive-resistant alleles will be very different between a viral infection where hundreds or thousands of genome copies co-exist in a cell nucleus, and during sexual reproduction where only one gene drive and wild-type allele are present in a fertilized egg. As such, it is unsure whether gene drive dynamics in HSV-1 will be informative for other organisms besides other herpesviruses. On the other hand, the authors provide little perspectives on the potential usage of an HSV-1 gene drive, beyond concluding that "Our study opens new possibilities for using the HSV1 gene drive for the prevention and treatment of diseases". The authors designed a drive against the important viral protein gE in an attempt to limit infectivity, but it is unclear from the data presented whether this was successful. An extended discussion on the potential use case of an HSV-1 gene drive would be informative.

(2) Unfortunately, the experiments presented lack rigorous controls to unambiguously show that gene drive propagation is mediated by CRISPR-directed recombination into the target genome. Gene drive-mediated recombination converts wild-type viruses into new recombinant viruses and the population of recombinants is expected to increase in frequency, as observed with the yellow population in Fig 2G and 3G. However, a rigorous experimental design would show that this population of recombinant viruses does not appear with a non-functional CRISPR system (for example if Cas9 is deleted in the gene drive virus) or if the target site is absent in the recipient virus. The comparison of Fig 2B and 2D does show that gene drive viruses do not increase in frequency when the target site is absent in the V19 virus, but these experiments could not distinguish between original and recombinant gene drive viruses. Thus, it is unknown if the increase in gene drive frequency in Fig 2B is because wild-type viruses have been converted to gene drive viruses, or because the WT and v23 viruses replicate with different dynamics (one could imagine for example that CRISPR cleavage of the WT genomes impaired the replication of the WT virus without inducing recombination, thus giving an advantage to v23). In Fig 2G and 3B, the authors do follow the population of recombinant viruses, in yellow, which increase in frequency as expected. However, in these experiments, either the donor or recipient viruses are mutated for gE, and the different viral populations might replicate with different dynamics, which confounds the interpretation of the results (see point 4. below). Overall, while the data presented suggests that CRISPR-mediated gene drive propagation is happening, it does not conclusively rule out other explanations, especially if viruses have different fitness.

(3) In Fig 2F-G-H, the authors designed a gene drive knocking out an important viral gene, gE, in an attempt to build a drive that reduces infectivity. gE knockout viruses V10 and V15 had smaller plaques but replicated with similar titers (Fig 1B, 1C). The gene drive against gE spread efficiently in Fig 2G. However, gE-KO viruses did not appear to have a meaningful disadvantage in the experimental system used, since the high MOI used in the co-infection experiments allowed to bypass the cell-to-cell defect of gE mutants. It would have been interesting to characterize the final population composed primarily of original and recombinant viruses (at P3 in Fig 2G), and in particular measure the plaque size of these viruses. Recombinant viruses should have smaller plaque sizes, and showing that the gene drive was able to propagate an attenuating phenotype would be a meaningful result that hints at potential therapeutic applications.

(4) Experiments presented in Fig 3 compared the dynamics of Cas9 and Un1Cas12f1 gene drives, but the experimental system used is a bit puzzling and makes the interpretation of the results challenging. In particular, the authors chose to use gE-knockout virus v10 as the recipient for the gene drive, which allowed them to use gE in their flow cytometry assay. Unfortunately, this added a confounding factor to the experiments, since gE- viruses might replicate with different dynamics than gE+ viruses (for example v10 titers are one log higher than WT at 12h in Fig 1C). In Fig 3B, gD+ gE- viruses (in blue) disappear and are replaced by gD+ GFP+ gE- recombinants (in yellow), which is suggestive of efficient gene drive recombination, as pointed out by the authors. However, the population of gD+ GFP+ virus (in green) representing the original gene drive virus also disappeared over time. At the end of the experiments in Fig 3B, the population of gE+ viruses is gone. This is unexpected and suggests that the gD+ GFP+ gE- (yellow) has a replicative advantage over gD+ GFP+ (green), and that the gE- mutation is actually positively selected in these viral competition assays. So in these experiments, both gene drive-mediated recombination and competition between viral genotypes appear to be happening at the same time, which makes interpretation of the results challenging. However, despite these limitations, the results presented convincingly suggested that Un1Cas12f1 gene drives achieved higher penetrance than Cas9's, which is one of the most important findings of the study.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors have used biochemical approaches to provide compelling evidence for the cleavage of TRMT1 by SARS-CoV-2 Nsp5 protease.<br /> This work is of wide interest to biochemists, cell biologists, and structural biologists in the coronavirus (CoV) field. Furthermore, it substantially advances the understanding of how CoV's interact with host factors during infection and modify cellular metabolism.

Strengths:<br /> The authors provide multiple lines of biochemical evidence to report a TRMT1-Nsp5 interaction during SARS-CoV-2 infection. They show that the host enzyme TRMT1 is cleaved at a specific site, and that it generates fragments that are incapable of functioning properly. This is an important result because TRMT1 is a critical player in host protein synthesis. This also advances our understanding of virus-host interactions during SARS-CoV-2 infections. Furthermore, this revised submission attempts to address the mechanistic role of TRMT1-Nsp5 interaction.

Weaknesses:<br /> The discussion on the enhanced viral infectivity upon expression of the non-cleavable TRMT1 is unclear. As presented, this is a bit contradictory to the suggested function of the TRMT1-Nsp5 interaction in diverting the host tRNA pools towards viral propagation. If the authors' model were correct, then one would expect a non-cleavable TRMT1 to inhibit viral infectivity because the virus would be unable to divert the host tRNA pools towards its propagation. I think this section needs to be written more clearly. But other than this, I have no further questions/suggestions for the authors.

Reviewer #3 (Public Review):

Human complex traits including common diseases are highly polygenic (influenced by thousands of loci). This observation is in need of an explanation. The authors of this manuscript propose a model that a competition for a single global resource (such as RNA polymerase II) may lead to a highly polygenic architecture of traits. Following an analytical examination the authors reject their hypothesis. This work is of clear interest to the field. It remains to be seen if the model covers the variety of possible competition models.

Reviewer #3 (Public Review):

The message conveyed by figure 1b is now clearer, but could still be improved. The authors explained the meaning of this figure well in their response to the reviewers: "For example, the results for CRISPR were obtained from 15 focus studies (original research) and 18 subsequent studies (papers citing focus articles). Those 15 studies identified 9,268 genes where loss-of-function changed phenotypes but, in their titles and abstracts, mentioned only 18 of those 9,268 genes. While the 9,268 hit genes have received similar research attention to the entirety of protein-coding genes, the 18 hit genes mentioned in the title or abstract are significantly more well studied. The articles citing the focus articles also only mentioned in their titles and abstracts 19 highly studied hit genes".<br /> The new Figure S8 is good.

Reviewer #3 (Public Review):

Summary:

Li et al investigated the initial target of the herbicidal caprilic acid (CAP). Using a combination of proteomic and metabolomic approaches, they generated a list of candidate targets for CAP and identified a Serine hydroxymethyl transferase (SHMT) as the best candidate.

CAP application to Conyza canadensis induces an early and brief increase in SHMT1 protein and transcript. Studies with purified recombinant CcSHMT1 indicate that enzymatic activity is inhibited by CAP. The authors suggest a kinetic mechanism of CAP inhibition but more data should be collected to reach a firm conclusion on this point.

Transgenic Arabidopsis and rice plants expressing CcSHMT1 show increased tolerance to CAP, as measured by biomass reduction 7 days after treatment with CAP. Similar results were obtained with Arabidopsis and rice plants overexpressing AtSHMT2 and OsSHMT1, respectively. OsSHMT1 single and double mutant rice plants showed increased tolerance to CAP. These results strongly link CAP tolerance to the level of SHMT, which can be manipulated by transgenesis, and suggest that engineered SHMT can also lead to higher CAP tolerance.

Finally, structural analysis allowed the identification of three residues close to the active site involved in the binding of CAP. Arabidopsis plants containing AtSHMT2 modified in these three residues are more sensitive to CAP.

Strengths:

The work of Li et al. includes a large number of assays using different methodologies. The evidence suggests that SHMT inhibition by CAP is effective in inhibiting plant growth. In addition, new technologies that manipulate SHMT levels or activity may improve crop yield by controlling weeds. Structural analysis can be the starting point for the design of more complex molecules that exceed the herbicidal activity of CAP.

Weaknesses:

The methods are rather incomplete, lacking many details necessary to fully understand the author's reasoning. It is not possible to reproduce the experiments on the basis of the information provided.

Although the conclusions are generally well supported, the results are presented in an incorrect or confusing manner. In the comparison of wild-type and transgenic plants, the control condition is missing in some experiments (Figures 4A and 5A). In some plots, the scales are not logical, making them difficult to interpret and fit into an equation (Figures 4B, 4C, 4E, 5E, 6E, 6F).

A final concern is the finding that some point mutations in the SHMT1 gene lead to more tolerant plants (Figures 6D, 6E, 6F). The authors could then explain whether this means that resistance to CAP could be easily acquired by weeds.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Wang et al. investigates the effects of B. velezensis HBXN2020 in alleviating S. Typhimurium-induced mouse colitis. The results showed that B. velezensis HBXN2020 could alleviate bacterial colitis by enhancing intestinal homeostasis (decreasing harmful bacteria and enhancing the abundance of Lactobacillus and Akkermansia) and gut barrier integrity and reducing inflammation. Overall, the manuscript is of potential interest to readers.

Strengths:<br /> B. velezensis HBXN2020 is a novel species of Bacillus that can produce a great variety of secondary metabolites and exhibit high antibacterial activity against several pathogens. B. velezensis HBXN2020 is able to form endospores and has strong anti-stress capabilities. B. velezensis HBXN2020 has a synergistic effect with other beneficial microorganisms, which can improve intestinal homeostasis.

Weaknesses:<br /> There are few studies about the clinical application of Bacillus velezensis. Thus, more studies are still needed to explore the effectiveness of Bacillus velezensis before clinical application.

Reviewer #3 (Public Review):

Summary:

Grattan and colleagues were trying to establish the neural mechanism underlying lactational infertility, in particular trying to establish the relative importance of the neurogenic effects of the suckling stimulus versus prolactin per se. They have shown that in the mouse it is rather prolactin and more specifically its action on the hypothalamic arcuate kisspeptin neuronal system, which is the key neural construct underlying gonadotrophin-releasing hormone (GnRH) pulse generation and central to the neuroendocrine control of reproduction, that mediates lactational infertility. The authors have taken a measured tone to emphasise the data pertaining to the mouse without extravagant extrapolation to humans. Nevertheless, the key findings provide a substantial foundation to facilitate interpretation of studies in other species.

Strengths:

The major strength of this study is the use of a combination of cutting-edge technologies, which of course underlie the majority of scientific advances rather than intellectual prowess favoured by the majority of scientists. Their approach avoided the major confounding effects of using pharmacological strategies to suppress prolactin action that has complicated the vast majority of previous studies. The study also provides an elegant and comprehensive contiguous description of GnRH pulse generator frequency across the ovarian cycle, through pregnancy and lactation, and into weaning in individual animals.

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

Reviewer #3 (Public Review):

In this manuscript, Nishi et al. propose a new model to explain the previously reported myeloid-biased hematopoiesis associated with aging. Traditionally, this phenotype has been explained by the expansion of myeloid-biased hematopoietic stem cell (HSC) clones during aging. Here, the authors question this idea and show how their Hoxb5 reporter model can discriminate long-term (LT) and short-term (ST) HSC and characterized their lineage output after transplant. From these analyses, the authors conclude that changes during aging in the LT/ST HSC proportion explain the myeloid bias observed.

Although the topic is appropriate and the new model provides a new way to think about lineage-biased output observed in multiple hematopoietic contexts, some of the experimental design choices, as well as some of the conclusions drawn from the results could be substantially improved. Also, they do not propose any potential mechanism to explain this process, which reduces the potential impact and novelty of the study. Specific concerns are outlined below.

Major

(1) As a general comment, there are experimental details that are either missing or not clear. The main one is related to transplantation assays. What is the irradiation dose? The Methods sections indicates "recipient mice were lethally irradiated with single doses of 8.7 or 9.1 Gy". The only experimental schematic indicating the irradiation dose is Figure 7A, which uses 8.7 Gy. Also, although there is not a "standard", 11 Gy split in two doses is typically considered lethal irradiation, while 9.5 Gy is considered sublethal. Is there any reason for these lower doses? Same question for giving a single dose and for performing irradiation a day before transplant.

(2) The manuscript would benefit from the inclusion of references to recent studies discussing hematopoietic biases and differentiation dynamics at a single-cell level (e.g., Yamamoto et. al 2018; Rodriguez-Fraticelli et al., 2020). Also, when discussing the discrepancy between studies claiming different biases within the HSC pool, the authors mentioned that Montecino-Rodriguez et al. 2019 showed preserved lymphoid potential with age. It would be good to acknowledge that this study used busulfan as the conditioning method instead of irradiation.

(3) When representing the contribution to PB from transplanted cells, the authors show the % of each lineage within the donor-derived cells (Figures 3B-C, 5B, 6B-D, 7C-E, and S3 B-C). To have a better picture of total donor contribution, total PB and BM chimerism should be included for each transplantation assay. Also, for Figures 2C-D and Figures S2A-B, do the graphs represent 100% of the PB cells? Are there any radioresistant cells?

(4) For BM progenitor frequencies, the authors present the data as the frequency of cKit+ cells. This normalization might be misleading as changes in the proportion of cKit+ between the different experimental conditions could mask differences in these BM subpopulations. Representing this data as the frequency of BM single cells or as absolute numbers (e.g., per femur) would be valuable.

(5) Regarding Figure 1B, the authors argue that if myeloid-biased HSC clones increase with age, they should see increased frequency of all components of the myeloid differentiation pathway (CMP, GMP, MEP). This would imply that their results (no changes or reduction in these myeloid subpopulations) suggest the absence of myeloid-biased HSC clones expansion with age. This reviewer believes that differentiation dynamics within the hematopoietic hierarchy can be more complex than a cascade of sequential and compartmentalized events (e.g., accelerated differentiation at the CMP level could cause exhaustion of this compartment and explain its reduction with age and why GMP and MEP are unchanged) and these conclusions should be considered more carefully.

(6) Within the few recipients showing good donor engraftment in Figure 2C, there is a big proportion of T cells that are "amplified" upon secondary transplantation (Figure 2D). Is this expected?

(7) Do the authors have any explanation for the high level of variability within the recipients of Hoxb5+ cells in Figure 2C?

(8) Can the results from Figure 2E be interpreted as Hoxb5+ cells having a myeloid bias? (differences are more obvious/significant in neutrophils and monocytes).

(9) Is Figure 2G considering all primary recipients or only the ones that were used for secondary transplants? The second option would be a fairer comparison.

(10) When discussing the transcriptional profile of young and aged HSCs, the authors claim that genes linked to myeloid differentiation remain unchanged in the LT-HSC fraction while there are significant changes in the ST-HSCs. However, 2 out of the 4 genes shown in Figure S4B show ratios higher than 1 in LT-HSCs.

(11) When determining the lymphoid bias in ST-HSCs, the authors focus on the T-cell subtype, not considering any other any other lymphoid population. Could the authors explain this?

(12) Based on the reduced frequency of donor cells in the spleen and thymus, the authors conclude "the process of lymphoid lineage differentiation was impaired in the spleens and thymi of aged mice compared to young mice". An alternative explanation could be that differentiated cells do not successfully migrate from the bone marrow to these secondary lymphoid organs. Please consider this possibility when discussing the data.

Reviewer #3 (Public Review):

Fister and colleagues use regeneration of the larval zebrafish caudal fin to compare the effects of two modes of tissue damage-transection and burn-on cutaneous sensory axon regeneration. The authors found that restoration of sensory axon density and function is delayed following burn injury compared to transection.

The authors hypothesized that thermal injury triggers signals within the wound microenvironment that impair sensory neuron regeneration. The authors identify differences in the responses of epithelial keratinocytes to the two modes of injury: keratinocytes migrate in response to burn but not transection. Inhibiting keratinocyte migration with the small-molecule inhibitor of Arp2/3 (CK666) resulted in decreased production of reactive oxygen species (ROS) at early, but not late, time points. Preventing keratinocyte migration by wounding in isotonic media resulted in increased sensory function 24 hours after burn.

Strengths of the study include the beautiful imaging and rigorous statistical approaches used by the authors. The ability to assess both axon density and axon function during regeneration is quite powerful. The touch assay adds a unique component to the paper and strengthens the argument that burns are more damaging to sensory structures and that different treatments help to ameliorate this.

A weakness of the study is the lack of genetic and cell-autonomous manipulations. Additional comparisons between transection and burns, in particular with manipulations that specifically modulate ROS generation or cell migration without potentially confounding effects on other cell types or processes would help to strengthen the manuscript. In terms of framing their results, the authors refer to "sensory neurons" and "sensory axons" throughout the text - it should be made clear what type of neuron(s)/axon(s) are being visualized/assayed. Along these lines, a broader discussion of how burn injuries affect sensory function in other systems - and how the authors' results might inform our understanding of these injury responses - would be beneficial to the reader.

In summary, the authors have established a tractable vertebrate system to investigate different sensory axon wound healing outcomes in vivo that may ultimately allow for the identification of improved treatment strategies for human burn patients. Although the study implicates differences in keratinocyte migration and associated ROS production in sensory axon wound healing outcomes, the links between these processes could be more rigorously established.

Reviewer #3 (Public Review):

Induced pluripotent stem cells, or iPSCs, are cells that scientists can push to become new, more mature cell types like neurons. iPSCs have a high potential to transform how scientists study disease by combining precision medicine gene editing with processes known as high-content imaging and drug screening. However, there are many challenges that must be overcome to realize this overall goal. The authors of this paper solve one of these challenges: predicting cell types that might result from potentially inefficient and unpredictable differentiation protocols. These predictions can then help optimize protocols.

The authors train advanced computational algorithms to predict single-cell types directly from microscopy images. The authors also test their approach in a variety of scenarios that one may encounter in the lab, including when cells divide quickly and crowd each other in a plate. Importantly, the authors suggest that providing their algorithms with just the right amount of information beyond the cells' nuclei is the best approach to overcome issues with cell crowding.

The work provides many well-controlled experiments to support the authors' conclusions. However, there are two primary concerns: (1) The model may be relying too heavily on the background and thus technical artifacts (instead of the cells) for making CNN-based predictions, and (2) the conclusion that their nucleocentric approach (including a small area beyond the nucleus) is not well supported, and may just be better by random chance. If the authors were to address these two concerns (through additional experimentation), then the work may influence how the field performs cell profiling in the future.

Additionally, the impact of this work will be limited, given the authors do not provide a specific link to the public source code that they used to process and analyze their data.

Reviewer #3 (Public Review):

Summary:

The mechanical properties of DNA wrapped in nucleosomes affect the stability of nucleosomes and may play a role in the regulation of DNA accessibility in eukaryotes. In this manuscript, Ngo and coworkers study how the stability of a nucleosome is affected by the introduction of a CC mismatched base pair, which has been reported to increase the flexibility of DNA. Previously, the group has used a sophisticated combination of single-molecule FRET and force spectroscopy with an optical trap to show that the more flexible half of a 601 DNA segment provides for more stable wrapping as compared to the other half. Here, it is confirmed with a single-molecule cyclization essay that the introduction of a CC mismatch increases the flexibility of a DNA fragment. Consistent with the previous interpretation, it also increased the unwrapping force for the half of the 601 segment in which the CC mismatch was introduced, as measured with single-molecule FRET and force spectroscopy. Enhanced stability was found up to 56 bp into the nucleosome. The intricate role of mechanical stability of nucleosomes was further investigated by comparing force-induced unwrapping profiles of yeast and Xenopus histones. Intriguingly, asymmetric unwrapping was more pronounced for yeast histones.

Strengths:

(1) High-quality single-molecule data.

(2) Novel mechanism, potentially explaining the increased prominence of mutations near the dyads of nucleosomes.

(3) A clear mechanistic explanation of how mismatches affect nucleosome stability.

Weaknesses:

(1) Disconnect between mismatches in nucleosomes and measurements comparing Xenopus and yeast nucleosome stability.

(2) Convoluted data in cyclization experiments concerning the phasing of mismatches and biotin site.

Reviewer #3 (Public Review):

Summary:

In this study, Wang et al. have demonstrated that TMC7, a testis-enriched multipass transmembrane protein, is essential for male reproduction in mice. Tmc7 KO male mice are sterile due to reduced sperm count and abnormal sperm morphology. TMC7 co-localizes with GM130, a cis-Golgi marker, in round spermatids. The absence of TMC7 results in reduced levels of Golgi proteins, elevated abundance of ER stress markers, as well as changes of Ca2+ and pH levels in the KO testis. However, further confirmation is required because the analyses were performed with whole testis samples in spite of the differences in the germ cell composition in WT and KO testis. In addition, the causal relationships between the reported anomalies await thorough interrogation.

Strengths:<br /> The microscopic images are of great quality, all figures are properly arranged, and the entire manuscript is very easy to follow.

Weaknesses:<br /> Tmc7 KO male mice show multiple anomalies in sperm production and morphogenesis, such as reduced sperm count, abnormal sperm head, and deformed midpiece. Thus, it is confusing that the authors focused solely on impaired acrosome biogenesis. Further investigations are warranted to determine whether the abnormalities reported in this manuscript (e.g., changes in protein, Ca2+, and pH levels) are directly associated with the molecular function of TMC7 or are the byproducts of partially arrested spermiogenesis. Please find additional comments in "Recommendations for the authors".

Reviewer #3 (Public Review):

Summary:

A known feature of cilia in vertebrates and many, if not all, invertebrates is the striking heterogeneity of their lengths among different cell types. The underlying mechanisms, however, remain largely elusive. In the manuscript, the authors addressed this question from the angle of intraflagellar transport (IFT), a cilia-specific bidirectional transportation machinery essential to biogenesis, homeostasis, and functions of cilia, by using zebrafish as a model organism. They conducted a series of experiments and proposed an interesting mechanism. Furthermore, they achieved in situ live imaging of IFT in zebrafish larvae, which is a technical advance in the field.

Strengths:

The authors initially demonstrated that ectopically expressed Ift88-GFP through a certain heat-shock induction protocol fully sustained the normal development of mutant zebrafish that would otherwise be dead by 7 dpf due to the lack of this critical component of IFT-B complex. Accordingly, cilia formations were also fully restored in the tissues examined. By imaging the IFT using Ift88-GFP in the mutant fish as a marker, they unexpectedly found that both anterograde and retrograde velocities of IFT trains varied among cilia of different cell types and appeared to be positively correlated with the length of the cilia.

For insights into the possible cause(s) of the heterogeneity in IFT velocities, the authors assessed the effects of IFT kinesin Kif3b and Kif17, BBSome, and glycylation or glutamylation of axonemal tubulin on IFT and excluded their contributions. They also used a cilia-localized ATP reporter to exclude the possibility of different ciliary ATP concentrations. When they compared the size of Ift88-GFP puncta in crista cilia, which are long, and spinal cord cilia, which are relatively short, by imaging with a cutting-edge super-resolution microscope, they noticed a positive correlation between the puncta size, which presumably reflected the size of IFT trains, and the length of the cilia.

Finally, they investigated whether it is the size of IFT trains that dictates the ciliary length. They injected a low dose (0.5 ng/embryo) of ift88 MO and showed that, although such a dosage did not induce the body curvature of the zebrafish larvae, crista cilia were shorter and contained less Ift88-GFP puncta. The particle size was also reduced. These data collectively suggested mildly downregulated expression levels of Ift88-GFP. Surprisingly, they observed significant reductions in both retrograde and anterograde IFT velocities. Therefore, they proposed that longer IFT trains would facilitate faster IFT and result in longer cilia.

Weaknesses:

The current manuscript, however, contains serious flaws that markedly limit the credibility of major results and findings. Firstly, important experimental information is frequently missing, including (but not limited to) developmental stages of zebrafish larvae assayed (Figures 1, 3, and 5), how the embryos or larvae were treated to express Ift88-GFP (Figures 3-5), and descriptions on sample sizes and the number of independent experiments or larvae examined in statistical results (Figures 3-5, S3, S6). For instance, although Figure 1B appears to be the standard experimental scheme, the authors provided results from 30-hpf larvae (Figure 3) that, according to Figure 1B, are supposed to neither express Ift88-GFP nor be genotyped because both the first round of heat shock treatment and the genotyping were arranged at 48 hpf. Similarly, the results that ovl larvae containing Tg(hsp70l:ift88 GFP) (again, because the genotype is not disclosed in the manuscript, one can only deduce) display normal body curvature at 2 dpf after the injection of 0.5 ng of ift88 MO (Fig 5D) is quite confusing because the larvae should also have been negative for Ift88-GFP and thus displayed body curvature. Secondly, some inferences are more or less logically flawed. The authors tend to use negative results on specific assays to exclude all possibilities. For instance, the negative results in Figures 4A-B are not sufficient to "suggest that the variability in IFT speeds among different cilia cannot be attributed to the use of different motor proteins" because the authors have not checked dynein-2 and other IFT kinesins. In fact, in their previous publication (Zhao et al., 2012), the authors actually demonstrated that different IFT kinesins have different effects on ciliogenesis and ciliary length in different tissues. Furthermore, instead of also examining cilia affected by Kif3b or Kif17 mutation, they only examined crista cilia, which are not sensitive to the mutations. Similarly, their results in Figures 4C-G only excluded the importance of tubulin glycylation or glutamylation in IFT. Thirdly, the conclusive model is based on certain assumptions, e.g., constant IFT velocities in a given cell type. The authors, however, do not discuss other possibilities.

Reviewer #3 (Public Review):

Summary:

The authors studied the function of Hsp110 co-chaperones (e.g. yeast Sse1) in Hsp70-dependent protein disaggregation reactions. The study builds on former work by the authors (Wyszkowski et al., 2021, PNAS), analyzing the binding of Hsp70 and J-domain protein (JDP) cochaperones to protein aggregates using bio-layer interferometry (BLI). It was shown before by other groups that Hsp110 enhances Hsp70 disaggregation activity. The mechanism of Hsp110-stimulated disaggregation activity, however, remained poorly defined. Here, the authors show that yeast Hsp110 increases Hsp70 recruitment to the surface of protein aggregates. The effect is largely dependent on J-domain protein (JDP) identity and is particularly pronounced for class B JDPs (e.g. yeast Sis1), which are also more effective in disaggregation reactions. The authors also confirm former results, showing inhibition by increased Hsp110 levels, and provide novel evidence that the inhibitory effect is caused by competition between Hsp110 and JDPs for Hsp70 binding.

Strengths:

The work represents a very thoroughly executed study, which provides novel insights into the mechanism of Hsp70-mediated protein disaggregation. Key findings established for yeast chaperones are also documented for human counterparts. The observation that Hsp110 might displace JDPs from Hsp70 during the disaggregation reaction is very appealing. It will now become important to validate this initial finding and dissect how it propels the disaggregation reaction.

Weaknesses:

How exactly the interplay between JDPs and Hsp110 orchestrates protein disaggregation remains largely speculative and further analysis is required for a deeper mechanistic understanding. Enhanced recruitment of Hsp70 in the presence of Hsp110 was shown for amyloid fibrils before (Beton et al., EMBO J 2022) and should be acknowledged. The assay reporting on the refolding activity of Hsp70 seems problematic due to the high spontaneous refolding of the substrate Luciferase and should be modified.

Reviewer #3 (Public Review):

Overall:

ExoIII has been described and commercialized as a dsDNA-specific nuclease. Several lines of evidence, albeit incomplete, have indicated this may not be entirely true. Therefore, Wang et al comprehensively characterize the endonuclease and exonuclease enzymatic activities of ExoIII on ssDNA. A strength of the manuscript is the testing of popular kits that utilize ExoIII and coming up with and testing practical solutions (e.g. the addition of SSB proteins ExoIII variants such as K121A and varied assay conditions).

Comments:

(1) The footprint of ExoIII on DNA is expected to be quite a bit larger than 5-nt, see structure in manuscript reference #5. Therefore, the substrate design in Figure 1A seems inappropriate for studying the enzymatic activity and it seems likely that ExoIII would be interacting with the FAM and/or BHQ1 ends as well as the DNA. Could this cause quenching? Would this represent real ssDNA activity? Is this figure/data necessary for the manuscript?

(2) Based on the descriptions in the text, it seems there is activity with some of the other nucleases in 1C, 1F, and 1I other than ExoIII and Cas12a. Can this be plotted on a scale that allows the reader to see them relative to one other?

(3) The sequence alignment in Figure 2N and the corresponding text indicates a region of ExoIII lacking in APE1 that may be responsible for their differences in substrate specificity in regards to ssDNA. Does the mutational analysis support this hypothesis?

Reviewer #3 (Public Review):

This study aimed to explore the computational mechanisms of view invariance, driven by the observation that in some regions of monkey visual cortex, neurons show comparable responses to (1) a given face and (2) to the same face but horizontally flipped. Here they study this known phenomenon using AlexNet and other shallow neural networks, using an index for mirror symmetric viewpoint tuning based on representational similarity analyses. They find that this tuning is enhanced at fully connected- or global pooling layers (layers which combine spatial information), and that the invariance is prominent for horizontal- but not vertical- or rotational transformations. The study shows that mirror tuning can be learned when a given set of images are flipped horizontally and given the same label, but *not* if they are flipped and given different labels. They also show that networks learn this tuning by focusing on local features, not global configurations.

I found the study to be a mixed read. Some analyses were fascinating: for example, it was satisfying to see the use of well-controlled datasets to increase or decrease the rate of mirror-symmetry tuning. The insertion- and deletion¬ experiments were elegant tests to probe the mechanisms of mirror symmetry, asking if symmetry could arise from (1) global feature configurations (in a holistic sense) vs. (2) local features, with stronger evidence for the latter. These two sets of results were successful and interpretable. They stand in contrast with the first analysis, which relies on observations that do not seem justified. Specifically, Figure 2D shows mirror-symmetry tuning across 11 stages of image processing, from pixels space to fully connected layers. It shows that images from different object categories evoke considerably different tuning index values. The explanation for this result is that some categories, such as "tools," have "bilaterally symmetric structure," but this is not explicitly measured anywhere. "Boats" are described as having "front-back symmetry," more so than flowers. One imagines flowers being extremely symmetric, but perhaps that depends on the metric. What is the metric? At first I thought it was the mirror-symmetric viewpoint tuning index in the image (pixel) space, but this cannot be, as the index for faces and flowers is negative, cars have no symmetry, and boats are positive. To support these descriptions, one must have an independent variable (for object class symmetry) that can be related to the dependent variable (the mirror-symmetric viewpoint tuning index). If it exists, it is not a part of the Results section. This omission undermines other parts of the Results section: "some car models have an approximate front-back symmetry...however, a flower typically does not..." "Some," "typically:" how many in the dataset exactly, and how often? The description of CIFAR-10 as having bilaterally symmetric categories - are all these categories equally symmetric? If not, would such variability matter in terms of these results? These assessments of object category symmetry values are made before experiments are presented, so they are not interpretations of the results, and it would be circular to write it otherwise.

Overall, my bigger concern is that the framing is misleading or at best incomplete. The manuscript successfully showed that if one introduces left-right symmetry to a dataset, the network will develop population-level representations that are also bilaterally symmetric. But the study does not explain that the model's architecture and random weight distribution are sufficient for symmetry tuning to emerge, without training, just to a much more limited degree. Baek et al. showed in 2021 that viewpoint-invariant face-selective units and mirror-symmetric units emerge in untrained networks ("Face detection in untrained deep neural networks"; this current manuscript cites this paper but does not mention that mirror symmetry is a feature of the 2021 study). This current study also used untrained networks as controls (Fig. 3), and while they were useful in showing that learning boosts symmetry tuning, the results also clearly show that horizontal-reflection invariance is far from zero. So, the simple learning-driven explanation for the mirror-symmetric viewpoint tuning for faces is wrong: while (1) network training and (2) pooling are mechanisms that charge the development of mirror-symmetric tuning, the lottery ticket hypothesis is enough for its emergence. Faces and numbers are simple patterns, so the overparameterization of networks is enough to randomly create units that are tuned to these shapes and to wire many of them together. How learning shapes this process is an interesting direction, especially now that this current study has outlined its importance.

Finally, it would help to cite other previous demonstrations of equivariance and mirror symmetry in neural networks. Chris Olah, Nick Cammarata, Chelsea Voss, Ludwig Schubert, and Gabriel Goh of OpenAI wrote of this phenomenon in 2020 (Distill journal).

Some other observations that might help:

- I am enthusiastic about the experiments using different datasets to increase or decrease the rate of mirror-symmetry tuning (sets including CIFAR10, SVHN, symSVHN, asymSVHN); it is worth noting, however, that the lack of a ground truth metric for category symmetry is a problem here too. In the asymSVHN dataset, images are flipped and given different labels. If some categories are naturally symmetric after horizontal flips, such as images containing "0" or "8", then changing the label is likely to disturb training. This would explain why the training loss is larger for this condition (Figure S4D).

- It is puzzling why greyscale 3D rendered images are used. By using greyscale 3D render (at least as shown in the figures) the study proceeds as if the units are invariant under color transformations. Unfortunately, this is not true and using greyscale images impact the activations of different layers of Alexnet in a way that is not fully defined. Moreover, many units in shallow networks focus on color and exactly these units could be invariant to other transformation like the mirror symmetry, but grey scaling the images makes them inactive.

Reviewer #3 (Public Review):

It has recently been demonstrated that bacteria in biofilms show changes in membrane potential in response to changes in their environment, and that these can propagate signals through the biofilm to coordinate bacterial behavior. Akabuogu et al. contribute to this exciting research area with a study of blue light-induced membrane potential dynamics in E. coli biofilms. They demonstrate that Thioflavin-T (ThT) intensity (a proxy for membrane potential) displays multiphasic dynamics in response to blue light treatment. They additionally use genetic manipulations to implicate the potassium channel Kch in the latter part of these dynamics. Mechanosensitive ion channels may also be involved, although these channels seem to have blue light-independent effects on membrane potential as well. In addition, there are challenges to the quantitative interpretation of ThT microscopy data which require consideration. The authors then explore whether these dynamics are involved in signaling at the community level. The authors suggest that cell firing is both more coordinated when cells are clustered and happens in waves in larger, 3D biofilms; however, in both cases evidence for these claims is incomplete. The authors present two simulations to describe the ThT data. The first of these simulations, a Hodgkin-Huxley model, indicates that the data are consistent with the activity of two ion channels with different kinetics; the Kch channel mutant, which ablates a specific portion of the response curve, is consistent with this. The second model is a fire-diffuse-fire model to describe wavefront propagation of membrane potential changes in a 3D biofilm; because the wavefront data are not presented clearly, the results of this model are difficult to interpret. Finally, the authors discuss whether these membrane potential changes could be involved in generating a protective response to blue light exposure; increased death in a Kch ion channel mutant upon blue light exposure suggests that this may be the case, but a no-light control is needed to clarify this.

In a few instances, the paper is missing key control experiments that are important to the interpretation of the data. This makes it difficult to judge the meaning of some of the presented experiments.

(1) An additional control for the effects of autofluorescence is very important. The authors conduct an experiment where they treat cells with CCCP and see that Thioflavin-T (ThT) dynamics do not change over the course of the experiment. They suggest that this demonstrates that autofluorescence does not impact their measurements. However, cellular autofluorescence depends on the physiological state of the cell, which is impacted by CCCP treatment. A much simpler and more direct experiment would be to repeat the measurement in the absence of ThT or any other stain. This experiment should be performed both in the wild-type strain and in the ∆kch mutant.

(2) The effects of photobleaching should be considered. Of course, the intensity varies a lot over the course of the experiment in a way that photobleaching alone cannot explain. However, photobleaching can still contribute to the kinetics observed. Photobleaching can be assessed by changing the intensity, duration, or frequency of exposure to excitation light during the experiment. Considerations about photobleaching become particularly important when considering the effect of catalase on ThT intensity. The authors find that the decrease in ThT signal after the initial "spike" is attenuated by the addition of catalase; this is what would be predicted by catalase protecting ThT from photobleaching (indeed, catalase can be used to reduce photobleaching in time lapse imaging).

(3) It would be helpful to have a baseline of membrane potential fluctuations in the absence of the proposed stimulus (in this case, blue light). Including traces of membrane potential recorded without light present would help support the claim that these changes in membrane potential represent a blue light-specific stress response, as the authors suggest. Of course, ThT is blue, so if the excitation light for ThT is problematic for this experiment the alternative dye tetramethylrhodamine methyl ester perchlorate (TMRM) can be used instead.

(4) The effects of ThT in combination with blue light should be more carefully considered. In mitochondria, a combination of high concentrations of blue light and ThT leads to disruption of the PMF (Skates et al. 2021 BioRXiv), and similarly, ThT treatment enhances the photodynamic effects of blue light in E. coli (Bondia et al. 2021 Chemical Communications). If present in this experiment, this effect could confound the interpretation of the PMF dynamics reported in the paper.

(5) Figures 4D - E indicate that a ∆kch mutant has increased propidium iodide (PI) staining in the presence of blue light; this is interpreted to mean that Kch-mediated membrane potential dynamics help protect cells from blue light. However, Live/Dead staining results in these strains in the absence of blue light are not reported. This means that the possibility that the ∆kch mutant has a general decrease in survival (independent of any effects of blue light) cannot be ruled out.

(6) Additionally in Figures 4D - E, the interpretation of this experiment can be confounded by the fact that PI uptake can sometimes be seen in bacterial cells with high membrane potential (Kirchhoff & Cypionka 2017 J Microbial Methods); the interpretation is that high membrane potential can lead to increased PI permeability. Because the membrane potential is largely higher throughout blue light treatment in the ∆kch mutant (Fig. 3AB), this complicates the interpretation of this experiment.

Throughout the paper, many ThT intensity traces are compared, and described as "similar" or "dissimilar", without detailed discussion or a clear standard for comparison. For example, the two membrane potential curves in Fig. S1C are described as "similar" although they have very different shapes, whereas the curves in Fig. 1B and 1D are discussed in terms of their differences although they are evidently much more similar to one another. Without metrics or statistics to compare these curves, it is hard to interpret these claims. These comparative interpretations are additionally challenging because many of the figures in which average trace data are presented do not indicate standard deviation.

The differences between the TMRM and ThT curves that the authors show in Fig. S1C warrant further consideration. Some of the key features of the response in the ThT curve (on which much of the modeling work in the paper relies) are not very apparent in the TMRM data. It is not obvious to me which of these traces will be more representative of the actual underlying membrane potential dynamics.

A key claim in this paper (that dynamics of firing differ depending on whether cells are alone or in a colony) is underpinned by "time-to-first peak" analysis, but there are some challenges in interpreting these results. The authors report an average time-to-first peak of 7.34 min for the data in Figure 1B, but the average curve in Figure 1B peaks earlier than this. In Figure 1E, it appears that there are a handful of outliers in the "sparse cell" condition that likely explain this discrepancy. Either an outlier analysis should be done and the mean recomputed accordingly, or a more outlier-robust method like the median should be used instead. Then, a statistical comparison of these results will indicate whether there is a significant difference between them.

In two different 3D biofilm experiments, the authors report the propagation of wavefronts of membrane potential; I am unable to discern these wavefronts in the imaging data, and they are not clearly demonstrated by analysis.

The first data set is presented in Figures 2A, 2B, and Video S3. The images and video are very difficult to interpret because of how the images have been scaled: the center of the biofilm is highly saturated, and the zero value has also been set too high to consistently observe the single cells surrounding the biofilm. With the images scaled this way, it is very difficult to assess dynamics. The time stamps in Video S3 and on the panels in Figure 2A also do not correspond to one another although the same biofilm is shown (and the time course in 2B is also different from what is indicated in 2B). In either case, it appears that the center of the biofilm is consistently brighter than the edges, and the intensity of all cells in the biofilm increases in tandem; by eye, propagating wavefronts (either directed toward the edge or the center) are not evident to me. Increased brightness at the center of the biofilm could be explained by increased cell thickness there (as is typical in this type of biofilm). From the image legend, it is not clear whether the image presented is a single confocal slice or a projection. Even if this is a single confocal slice, in both Video S3 and Figure 2A there are regions of "haze" from out-of-focus light evident, suggesting that light from other focal planes is nonetheless present. This seems to me to be a simpler explanation for the fluorescence dynamics observed in this experiment: cells are all following the same trajectory that corresponds to that seen for single cells, and the center is brighter because of increased biofilm thickness.

The second data set is presented in Video S6B; I am similarly unable to see any wave propagation in this video. I observe only a consistent decrease in fluorescence intensity throughout the experiment that is spatially uniform (except for the bright, dynamic cells near the top; these presumably represent cells that are floating in the microfluidic and have newly arrived to the imaging region).

3D imaging data can be difficult to interpret by eye, so it would perhaps be more helpful to demonstrate these propagating wavefronts by analysis; however, such analysis is not presented in a clear way. The legend in Figure 2B mentions a "wavefront trace", but there is no position information included - this trace instead seems to represent the average intensity trace of all cells. To demonstrate the propagation of a wavefront, this analysis should be shown for different subpopulations of cells at different positions from the center of the biofilm. Data is shown in Figure 8 that reflects the velocity of the wavefront as a function of biofilm position; however, because the wavefronts themselves are not evident in the data, it is difficult to interpret this analysis. The methods section additionally does not contain sufficient information about what these velocities represent and how they are calculated. Because of this, it is difficult for me to evaluate the section of the paper pertaining to wave propagation and the predicted biofilm critical size.

There are some instances in the paper where claims are made that do not have data shown or are not evident in the cited data:

(1) In the first results section, "When CCCP was added, we observed a fast efflux of ions in all cells"- the data figure pertaining to this experiment is in Fig. S1E, which does not show any ion efflux. The methods section does not mention how ion efflux was measured during CCCP treatment.

(2) In the discussion of voltage-gated calcium channels, the authors refer to "spiking events", but these are not obvious in Figure S3E. Although the fluorescence intensity changes over time, it's hard to distinguish these fluctuations from measurement noise; a no-light control could help clarify this.

(3) The authors state that the membrane potential dynamics simulated in Figure 7B are similar to those observed in 3D biofilms in Fig. S4B; however, the second peak is not clearly evident in Fig. S4B and it looks very different for the mature biofilm data reported in Fig. 2. I have some additional confusion about this data specifically: in the intensity trace shown in Fig. S4B, the intensity in the second frame is much higher than the first; this is not evident in Video S6B, in which the highest intensity is in the first frame at time 0. Similarly, the graph indicates that the intensity at 60 minutes is higher than the intensity at 4 minutes, but this is not the case in Fig. S4A or Video S6B.

Reviewer #3 (Public Review):

The authors present in this study the characterization of two mutant lines of the filasterean Capsaspora owczarzaki, a unicellular holozoan with a key phylogenetic position to understand multicellular development in animals. The present study is built on a previous work from the same research group, on the mutant of the orthologue of the Yorki gene in C. owczarzaki. By knocking out the two upstream kinases of the same pathway, coHpo-/- and coWts-/-, in single cell and aggregates of C. owkzarzaki, they now have mutated the entire pathway and in different cellular contexts.

The authors obtain results in the same direction as the previous work, demonstrating that the Hippo pathway of the unicellular holozoan C. owczarzaki, is not involved in the control of cell proliferation but is related with cytoskeletal dynamics through the actin-myosin mechanism.

In this revised version of the study, the authors have addressed my concerns by providing additional experiments, references and discussing further the points of controversy.

I think the authors have done a great job improving the robustness of the paper proving further some of the claims raised in the previous version of the manuscript.

Reviewer #3 (Public Review):

Summary:

The manuscript examined the role of large versus small prediction errors (PEs) in creating a state-based memory distinction between acquisition and extinction. The premise of the paper is based on theoretical claims and empirical findings that gradual changes between acquisition and extinction would lead to the potential overwriting of the acquisition memory with extinction, resulting in a more durable reduction in conditioned responding (i.e. more durable extinction effect). The paper tests the hypotheses in a series of elegant experiments in which the shock intensity is decreased across extinction sessions before non-reinforced CS presentations are given. Additional manipulations include context change, shock devaluation, and controlling for lower shock intensity exposure. The critical comparison was standard non-reinforced extinction training. The critical tests were done in spontaneous recovery and reinstatement.

Strengths:<br /> The findings are of tremendous importance in understanding how memories can be updated and reveal a well-defined role of PE in this process. It is well-established that PE is critical for learning, so delineating how PE is critical for generating memory states and the role it serves in keeping memories dissociable (or not) is exciting and clever. As such the paper addresses a fundamental question in the field.

The studies test clear and defined predictions derived from simulations of the state-belief model of Cochran & Cisler (2019). The designs are excellent: well-controlled and address the question.

The authors have done an excellent job of explaining the value of the latent state models.

The authors have studied both sexes in the study presented, providing generality across the sexes in their findings. However, depicting the individual data points in the bar graphs and noting which data represent males and which represent females would be of great value.

Weaknesses:

(1) While it seems obvious that delivering a lower intensity shock will generate a smaller PE than say no shock, it would have been nice to see data from say a compound testing procedure that confirms this.

(2) The devaluation experiment is quite clever, but it also would be strengthened if there was evidence in the paper that this procedure does indeed lead to shock devaluation.

(3) It would have been very exciting to see even more parametric examinations of this idea, like maintaining shock intensity but gradually reducing shock duration, which would have increased the impact of the paper.

(4) Individual data points should be represented in the test figures (see above also).

Reviewer #3 (Public Review):

Summary:<br /> This manuscript describes the symptoms of patients harboring KCNQ2 mutation G256W, functional changes of the mutant channel in exogenous expression, and phenotypes of G256W/+ mice. The patients presented seizures, the mutation reduced currents of the channel, and the G256W/+ mice showed seizures, increased firing frequency in neurons, reduced KCNQ2 expression,<br /> and altered subcellular distribution.

Strengths:

This is a large amount of work and all results corroborated the pathogenicity of the mutation in KCNQ2, providing an interesting example of KCNQ2-associated neurological disorder's impact on functions at all levels including molecular, cellular, tissue, animal model, and patients.

Weaknesses:

The manuscript described observations of changes in association with the mutation at molecular cellular functions and animal phenotype, but the results in some aspects are not as strong as in others. Nevertheless, the manuscript made overarching conclusions even when the evidence was not sufficiently strong.

yeah. but the actual problem is pacifism and overpopulation.<br /> all other problems, including world wars, are only symptoms of pacifism and overpopulation.<br /> this is just another intelligence test, and again, most people fail, most people are idiots

Reviewer #3 (Public Review):

Stout et al investigate the link between prefrontal-hippocampal (PFC-HPC) theta-band coherence and accurate decisions in spatial decision making tasks. Previous studies show that PFC-HPC theta coherence positively correlates with task learning and correct decisions but the nature of this relation relies on correlations that cannot show whether coherence leads, coincides or is a consequence of decision making. To investigate more precisely this link, the authors devise a novel paradigm. In this paradigm the rat is blocked during a delay period preceding its choice and they control on a trial-by-trial basis the level of PFC-HPC theta coherence prior to the decision by allowing the rat to access the choice point only at a time when coherence reaches above or below a threshold. The design of the paradigm is very well controlled in many ways. First, using the PFC-HPC theta coherence during the delay period to gate when the rat accesses the choice zone clearly separates this coherence from the behavioural decision itself. Moreover, the behaviour of the animal is similar during high and low coherence periods. Finally, control trials are matched trial-by-trial to the time spent waiting by the rat when gated on theta coherence, which is crucial given that working memory performance depends on delay duration. All these features bolster the specificity of the author's main finding which is that PFC-HPC theta coherence prior to choice making is strongly predictive of accuracy in two tasks : one that requires working memory and another in which behaviour is cue-guided. Although this paradigm does not provide direct causal evidence, it convincingly supports the idea that PFC-HPC theta coherence prior to the behavioural decision is related to correct decision making and is not simply temporally coincidental or a consequence of the decision output.

The authors also investigate the mechanisms behind the increase in PFC-HPC coherence during the task and show that it likely involves the recruitment of a small population of PFC neurons, via interactions with the Ventral Midline Thalamus that could mediate prefrontal/hippocampal dialogue.

A key point of interest is the unexpected result showing a link between theta coherence even in the cue-driven version of the task. As the authors point out, muscimol inhibition of neither PFC nor HPC, nor the ventral midline thalamus impacts performance in this task. This raises the question of why coherence between two areas is predictive of choice accuracy when neither area appears to be causally involved. The authors discuss various options and explanations for this discrepancy which clearly adds to the current debate. Moreover their novel paradigm provides new tools to interrogate when inter-area synchrony is associated with information transfer and when this information is then used to drive behavioural decisions.

"we have been winning battles... but losing the war

big environmentalist shifting toward anti-capitalism

Reviewer #3 (Public Review):

Summary and strengths:

In the manuscript, Abd El Hay et al investigate the role of thermally sensitive ion channels TRPM2 and TRPV1 in warm preference and their dynamic response features to thermal stimulation. They develop a novel thermal preference task, where both the floor and air temperature are controlled, and conclude that mice likely integrate floor with air temperature to form a thermal preference. They go on to use knockout mice and show that TRPM2-/- mice play a role in the avoidance of warmer temperatures. Using a new approach for culturing DRG neurons they show the involvement of both channels in warm responsiveness and dynamics. This is an interesting study with novel methods that generate important new information on the different roles of TRPV1 and TRPM2 on thermal behavior.

Open questions and weaknesses:

(1) Differences in the response features of cells expressing TRPM2 and TRPV1 are central and interesting findings but need further validation (Figures 3 and 4). To show differences in the dynamics and the amplitude of responses across different lines and stimulus amplitudes more clearly, the authors should show the grand average population calcium response from all responsive neurons with error bars for all 3 groups for the different amplitudes of stimuli (as has been presented for the thermal stimuli traces). The authors should also provide a population analysis of the amplitude of the responses in all groups to all stimulus amplitudes. Prior work suggests that thermal detection is supported by an enhancement or suppression of the ongoing activity of sensory fibers innervating the skin. The authors should present any data on cells with ongoing activity.

(2) The authors should better place their findings in context with the literature and highlight the novelty of their findings. The introduction builds a story of a 'disconnect' or 'contradictory' findings about the role of TRPV1 and TRPM2 in warm detection. While there are some disparate findings in the literature, Tan and McNaughton (2016) show a role for TRPM2 in the avoidance of warmth in a similar task, Paricio et al. (2020) show a significant reduction in warm perception in TRPM2 and TRPV1 knock out lines and Yarmolinksy et al. (2016) show a reduction in warm perception with TRPV1 inactivation. All these papers are therefore in agreement with the authors finding of a role for these channels in warm behavior. The authors should change their introduction and discussion to more correctly discuss the findings of these studies and to better pinpoint the novelty of their own work.

(3) The responses of 60 randomly selected cells are shown in Figure 2B. But, looking at the TRPM2-/- data, warm responses appear more obvious than in WTs and the weaker responders of the WT group appear weaker than the equivalent group in the TRPV1-/- and TRPM2-/- data. This does not necessarily invalidate the results, but it may suggest a problem in the data selection. Because the correct classification of warm-sensitive neurons is central to this part of the study more validation of the classifier should be presented. For example, the authors could state if they trained the classifier using equal amounts of cells, show some randomly selected cells that are warm-insensitive for all genotypes, and show the population average responses of warm-insensitive neurons.

(4) The interpretation of the main behavioral results and justification of the last figure is presented as the result of changes in sensing but differences in this behavior could be due to many factors and this needs clarification and discussion. (i) The authors mention that 'crucially temperature perception is not static' and suggest that there are fluctuating changes in perception over time and conclude that their modelling approach helps show changes in temperature detection. They imply that temperature perceptual threshold changes over time, but the mouse could just as easily have had exactly the same threshold throughout the task but their motivation (or some other cognitive variable) might vary causing them to change chamber. The authors should correct this. (ii) Likewise, from their fascinating and high-profile prior work the authors suggest a model of internal temperature sensing whereby TRPM2 expression in the hypothalamus acts as an internal sensory of body temperature. Given this, and the slow time course of the behavior in chambers with different ambient temperatures, couldn't the reason for the behavioral differences be due to central changes in hypothalamic processing rather than detection by skin temperature? If TRPM2-/- were selectively ablated from the skin or the hypothalamus (these experiments are not necessary for this paper) it might be possible to conclude whether sensation or body temperature is more likely the root cause of these effects but, without further experiments it is tough to conclude either way. (iii) Because the ambient temperature is controlled in this behavior, another hypothesis is that warm avoidance could be due to negative valence associated with breathing warm air, i.e. a result of sensation within the body in internal pathways, rather than sensing from the external skin. Overall, the authors should tone down conclusions about sensation and present a more detailed discussion of these points.

(5) It is an excellent idea to present a more in-depth analysis of the behavioral data collected during the preference task, beyond 'the mouse is on one side or the other'. However, the drift-diffusion approach is complex to interpret from the text in the results and the figures. The results text is not completely clear on which behavioral parameters are analyzed and terms like drift, noise, estimate, and evidence are not clearly defined. Currently, this section of the paper slightly confuses and takes the paper away from the central findings about dynamics and behavioral differences. It seems like they could come to similar conclusions with simpler analysis and simpler figures.

(6) In Figure 2D the % of warm-sensitive neurons are shown for each genotype. Each data point is a field of view, however, reading the figure legend there appear to be more FOVs than data points (eg 10 data points for the TRPV1-/- but 17 FOVs). The authors should check this.

(7) Can the authors comment on why animals with over-expression of TRPV1 spend more time in the warmest chamber to start with at 38C and not at 34C?

Reviewer #3 (Public Review):

Reviewing Editor's Summary:

The revised manuscript has clarified concerns raised by the reviewers concerning the analysis method in constructing the correlation matrix. These key results are now readily comprehensible. They have also added a final section to the Discussion, sketching some important questions for future research (e.g., number/resolution of channels and extension of the logic used here to look at number channels in other tasks).

Reviewer 1 was satisfied with these changes and has updated their review. Reviewer 2 did not think the revision tackled the theoretical issues raised in their initial review; as such, this reviewer has opted to leave their initial public review unchanged.

I also believe that the revision does not adequately address a major theoretical issue, namely whether the current data provide evidence of sensorimotor number channels, the central claim of the paper. The authors argue that since perception is noise free (stimuli were given symbolically), then the task variance comes from processes associated with sensorimotor transformation. Let's consider the task: A number is presented, the participant then attempts to produce that number of taps. To preclude counting, they are required to say the syllable "ba" as fast as possible while tapping. The sensorimotor channel idea would suppose that the symbolic stimulus activates a set of channels, each of which specifies the number of taps that should be produced. For example, a "6" channel likes to produce 6 outputs (with variability), a "10" channel 10 outputs (with variability), etc., with the actual production of the (weighted) integration of these outputs.

An alternative is that, since explicit counting is prevented by the secondary task, the participant makes an internal estimation of the number of produced taps. These judgments could be based on the output of amodal number channels. For example, the same process would be at play if the task were changed such that the participants watched a dot flash and had to estimate the number of flashes (while concurrently saying "ba"). The authors indicate in their response letter that they are conducting experiments along these lines and that the results are similar. They suggest that this provides support for the existence of both sensory and sensorimotor number channels. Extending this, if the experiment were tones instead of flashes, the argument would be that there are auditory, visual, and sensorimotor number channels. It seems more parsimonious to interpret such a pattern as reflective of amodal number channels.

I recognize there are other intriguing reasons to think there may be intimate links between our sense of number and movement, but I remain unconvinced that the current results provide evidence for sensorimotor number channels.

Reviewer #3 (Public Review):

Summary:

This manuscript reports two neuroimaging experiments assessing commonalities and differences in activation loci across mechanical problem-solving, technical reasoning, fluid cognition, and "mentalizing" tasks. Each task includes a control task. Conjunction analyses are performed to identify regions in common across tasks. As Area PF (a part of the supramarginal gyrus of the inferior parietal lobe) is involved across 3 of the 4 tasks, the investigators claim that it is the hub of technical cognition.

Strengths:

The aim of finding commonalities and differences across related problem-solving tasks is a useful and interesting one.

The experimental tasks themselves appear relatively well-thought-out, aside from the concern that they are differentially difficult.

The imaging pipeline appears appropriate.

Weaknesses:

(1) Methodological<br /> As indicated in the supplementary tables and figures, the experimental tasks employed differ markedly in 1) difficulty and 2) experimental trial time. Response latencies are not reported (but are of additional concern given the variance in difficulty). There is concern that at least some of the differences in activation patterns across tasks are the result of these fundamental differences in how hard various brain regions have to work to solve the tasks and/or how much of the trial epoch is actually consumed by "on-task" behavior. These difficulty issues should be controlled for by 1) separating correct and incorrect trials, and 2) for correct trials, entering response latency as a regressor in the Generalized Linear Models, 3) entering trial duration in the GLMs.

A related concern is that the control tasks also differ markedly in the degree to which they were easier and faster than their corresponding experimental task. Thus, some of the control tasks seem to control much better for difficulty and time on task than others. For example, the control task for the psychotechnical task simply requires the indication of which array contains a simple square shape (i.e., it is much easier than the psychotechnical task), whereas the control task for mechanical problem-solving requires mentally fitting a shape into a design, much like solving a jigsaw puzzle (i.e., it is only slightly easier than the experimental task).

(2) Theoretical<br /> The investigators seem to overlook prior research that does not support their perspective and their writing seems to lack scientific objectivity in places. At times they over-reach in the claims that can be made based on the present data. Some claims need to be revised/softened.

Reviewer #2 (Public Review):

Summary:

Hoogstraaten et al investigated the involvement of rabphilin-3A RPH3A in DCV fusion in neurons during calcium-triggered exocytosis at the synapse and during neurite elongation. They suggest that RPH3A acts as an inhibitory factor for LDV fusion and this is mediated partially via its interaction with SNAP25 and not Rab3A/Rab27. It is a very elegant study although several questions remain to be clarified.

Strengths:

The authors use state-of-the-art techniques like tracking NPY-PHluorin exocytosis and FRAP experiments to quantify these processes providing novel insight into LDCs exocytosis and the involvement of RPH3A.

Weaknesses:

At the current state of the manuscript, further supportive experiments are necessary to fully support the authors' conclusions.

Reviewer #3 (Public Review):

Summary:

In this work, the authors use a Hidden Markov Model (HMM) to describe dynamic connectivity and amplitude patterns in fMRI data, and propose to integrate these features with the Fisher Kernel to improve the prediction of individual traits. The approach is tested using a large sample of healthy young adults from the Human Connectome Project. The HMM-Fisher Kernel approach was shown to achieve higher prediction accuracy with lower variance on many individual traits compared to alternate kernels and measures of static connectivity. As an additional finding, the authors demonstrate that parameters of the HMM state matrix may be more informative in predicting behavioral/cognitive variables in this data compared to state-transition probabilities.

Strengths:

- Overall, this work helps to address the timely challenge of how to leverage high-dimensional dynamic features to describe brain activity in individuals.<br /> - The idea to use a Fisher Kernel seems novel and suitable in this context.<br /> - Detailed comparisons are carried out across the set of individual traits, as well as across models with alternate kernels and features.<br /> - The paper is well-written and clear, and the analysis is thorough.

Potential weaknesses:

- One conclusion of the paper is that the Fisher Kernel "predicts more accurately than other methods" (Section 2.1 heading). I was not certain this conclusion is fully justified by the data presented, as it appears that certain individual traits may be better predicted by other approaches (e.g., as shown in Figure 3) and I found it hard to tell if certain pairwise comparisons were performed -- was the linear Fisher Kernel significantly better than the linear Naive normalized kernel, for example?

- While 10-fold cross-validation is used for behavioral prediction, it appears that data from the entire set of subjects is concatenated to produce the initial group-level HMM estimates (which are then customized to individuals). I wonder if this procedure could introduce some shared information between CV training and test sets. This may be a minor issue when comparing the HMM-based models to one another, but it may be more important when comparing with other models such as those based on time-averaged connectivity, which are calculated separately for train/test partitions (if I understood correctly).

Reviewer #3 (Public Review):

Summary:

This paper seeks to understand the role of alveolar myofibroblasts in abnormal lung development after saccular stage injury.

Strengths:

Multiple models of neonatal injury are used, including hyperoxia and transgenic models that target alveolar myofibroblasts.

Weaknesses:

There are several weaknesses that leave the conclusions significantly undersupported by the data as presented:

(1) There is no validation of the decreased number of myofibroblasts suggested by flow cytometry/scRNAseq at the level of the tissue. Given that multiple groups have reported increased myofibroblasts (aSMA+ fibroblasts) in humans with BPD and in mouse models, demonstrating a departure from prior findings with tissue validation in the mouse models is essential. There are many reasons for decreased numbers of a subpopulation by flow cytometry, most notably that injured cells may be less likely to survive the cell sorting process.

(2) The hallmark genes used to define the subpopulations are not given in single-cell data. As the definition of fibroblast subtypes remains an area of unsettled discussion in the field, it is possible that the decreased number by classification and not a true difference. Tissue validation and more transparency in the methods used for single-cell sequencing would be critical here.

(3) There is an oversimplification of neonatal hyperoxia as a "BPD model" used here without a reference to detailed prior work demonstrating that the degree and duration of hyperoxia dramatically change the phenotype. For example, Morty et al have shown that hyperoxia of 85% or more x 14 days is required to demonstrate the septal thickening observed in severe human BPD. Other than one metric of lung morphometry (MLI), which is missing units on the y-axis and flexivent data, the authors have not fully characterized this model. Prior work comparing 75% O2 exposure for 5, 8, or 14 days shows that in the 8-day exposed group (similar to the model used here), much of the injury was reversible. What evidence do the authors have that hyperoxia alone is an accurate model of the permanent structural injury seen in human BPD?

(4) Thibeault et al published a single-cell analysis of neoantal hyperoxia in 2021, with seemingly contrasting findings. How does this dataset compare in context?

Reviewer #3 (Public Review):

Summary:

This is a well-prepared manuscript that presented interesting research results. The only defect is that the authors should further revise the English language.

Strengths:

The omics method produced unbiased results.

Weaknesses:

LPS neutralization is not a new method for treating leptospiral infection.

Reviewer #3 (Public Review):

Summary:<br /> This study provides a comparison of TCR gene segment usage between foetal and adult thymus.

Strengths:<br /> Interesting computational analyses was performed to find interesting differences in TCR gene usage within unpaired TCRa and TCRb chains between foetal and adult thymus.

Weaknesses:<br /> This study was significantly lacking insight and interpretation into what the data analysed actually means for the biology. The dataset discussed in the paper is from only two experiments. One comparing foetal and adult thymi from 4 mice per group and another which involved hydrocortisone treatment. The paper uses TCR sequencing methodology that sequences each TCR alpha and beta chains in an unpaired way, meaning that the true identity of the TCR heterodimer is lost. This also has the added problem of overestimating clonality, and underestimating diversity.<br /> Limited detail in the methods sections also limits the ability for readers to properly interpret the dataset. What sex of mice were used? Are there any sex differences? What were the animal ethics approvals for the study?

Reviewer #3 (Public Review):

This manuscript reports a detailed genetic and epigenomic analysis of diagnostic and relapsed AML. The study is mostly correlative and some of the initial findings, such as the stability of mutations in epigenetic regulators at diagnosis and relapse and in signaling pathway modulators such as FLT3 and NRAS being lost - not novel.

The authors show that in a large fraction (approximately half) of the relapsed AMLs they study, there are no alterations in the AML driver mutations. The authors conclude that this indicates that these patients show non-genetic mechanisms of relapse, for which the authors embark on a series of epigenomic experiments to try and pin down the correlative or causative epigenetic mechanisms. In 9 (out of 25) patient samples with stable driver mutations ( i.e. no change in clonality or novel AML driver mutation accumulation) the study shows that there is high epigenetic variability as measured by chromatin accessibility changes and that these changes resemble less differentiated state in the relapsed compared to the diagnostic sample. The manuscript makes some key observations: 1) non-genetic mechanisms are likely to account for relapse in a substantial proportion of patients. 2) some of the clones that emerge following relapse are likely present in prior diagnosis samples indicating that chemotherapy selects for them, 3) Of note, the authors also look at the LSC and non-LSC compartments and show that the LSC compartment is more rigid in terms of epigenetic evolution towards relapse than the non-LSC cells. 4) Using a small number of patients (but justifiable since the assays used are rigorous and demanding) - the authors present the most interesting finding of the study - that epigenetic evolution of relapse in several different AML patients seems to be convergent.<br /> This is based on the epigenetic similarities in clones (as defined by mitochondrial Atac-seq) between different epigenetic relapsed clones, even though they were distinct at diagnosis. Thus, this study has several important observations. Some of these observations are incremental - it has been shown that epigenetic mechanisms drive relapse in AML but several are not. I think this study - although descriptive and not showing causal relationships - is an important study for advancing our understanding of AML relapse.

Reviewer #3 (Public Review):

Summary:<br /> In the manuscript by Valenzisi et al., the authors report on the role of WRNIP1 to prevent R-loop and TRC-associated DNA damage. The authors claim WRNIP1 localizes to TRCs in response to replication stress and prevents R-loop accumulation, TRC formation, replication fork stalling, and subsequent DNA damage. While the findings are of potential significance to the field, the strength of evidence in support of the conclusions is lacking.

In the revised submission by Velenzisi et al., the manuscript is still missing the controls that were requested in the original review. One cannot conclude the D37A mutant is unable to rescue DNA damage unless it is shown in the same experiment that the WT is able to rescue it. This is also true for the fork speed, stalled forks, and restarting forks experiments. Below is a list of Figures missing key controls.

Figure 1B -missing the shWRNIP1WT control<br /> Figure 1C - missing the MRC5SV control<br /> Figure 1D - missing the shWRNIP1WT control<br /> Figure 3C - missing the shWRNIP1WT control<br /> Figure 5A - missing the shWRNIP1WT control<br /> Figure 5B - missing the shWRNIP1WT control<br /> Figure 5C - missing the shWRNIP1WT control<br /> Figure 5D - missing the shWRNIP1WT control<br /> Figure 6C - missing the shWRNIP1WT control

Also, the authors did not explain the result showing shWRNIP1 decreases DNA damage compared to MRC5SV in Figure 1D (compare lanes 4 and 8). Again, this suggests WRNIP1 actually increases DNA damage in response to Aph and DRB. This concern was raised in the original peer review, and it remains unaddressed in the revised manuscript.

The use of RNaseHIII increases the specificity of the S9.6 antibody and improves confidence in the DNA-RNA hybrid data throughout the manuscript.

Reviewer #3 (Public Review):

Summary:

The vesicular monoamine transporter is a key component in neuronal signaling and is implicated in diseases such as Parkinson's. Understanding of monoamine processing and our ability to target that process therapeutically has been to date provided by structural modeling and extensive biochemical studies. However, structural data is required to establish these findings more firmly.

Strengths:

Dalton et al resolved a structure of VMAT2 in the presence of an important inhibitor, tetrabenazine, with the protein in detergent micelles, using cryo-EM and with the aid of protein domains fused to its N- and C-terminal ends, including one fluorescent protein that facilitated protein screening and purification. The resolution of the maps allows clear assignment of the amino acids in the core of the protein. The structure is in good agreement with a wealth of experimental and structural prediction data, and provides important insights into the binding site for tetrabenazine and selectivity relative to analogous compounds. The authors provide additional biochemical analyses that further support their findings. The comparison with AlphaFold models is enlightening.

Reviewer #3 (Public Review):

Summary:

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

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

Strengths:

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

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

Weaknesses:

The study comes to a different conclusion about the olfactory tubercle regarding reward representations from several other prior works. Whether this stems from a difference in the experimental configurations such as behavioral paradigms used or indeed points to a conceptually different role for the olfactory tubercle remains to be seen.

Reviewer #3 (Public Review):

Summary:<br /> This study indicates that connections across human cortical pyramidal cells have identical latencies despite a larger mean dendritic and axonal length between somas in the human cortex. A precise demonstration combining detailed electrophysiology and modeling indicates that this property is due to faster propagation of signals in proximal human dendrites. This faster propagation is itself due to a slightly thicker dendrite, a larger capacitive load, and stronger hyperpolarizing currents. Hence, the biophysical properties of human pyramidal cells are adapted such that they do not compromise information transfer speed.

Strengths:<br /> The manuscript is clear and very detailed. The authors have experimentally verified a large number of aspects that could affect propagation speed and have pinpointed the most important one. This paper provides an excellent comparison of biophysical properties between rat and human pyramidal cells. Thanks to this approach a comprehensive description of the mechanisms underlying the acceleration of propagation in human dendrite is provided.

Weaknesses:<br /> Several aspects having an impact on propagation speed are highlighted (dendritic diameter, ionic channels, capacitive load) and there is no clear ranking of their impact on signal propagation speed. It seems that the capacitive load plays a major role, much more than dendritic diameter for which only a 10% increase is observed across species. Both aspects actually indicate that there is an increase in passive signal propagation speed with bigger cells at least close to the soma. This suggests that bigger cells are mechanically more rapid. An intuitive reason why capacitive load increases speed would also help the reader follow the demonstration.

Reviewer #3 (Public Review):

In this manuscript, Ma et al seek to identify stem cell niche factors. They perform an RNAi screen in glial cells and screen for candidates that support and maintain neuroblasts (NBs) in the developing fly brain. Through this, they identify two subunits of ferritin, which is a conserved protein that can store iron in cells in a non-toxic form and release it in a controlled manner when and where required. They present data to support the conclusion that ferritin produced in glia is released and taken up by NBs where it is utilised by enzymes in the Krebs cycle as well as in the electron transport chain. In its absence from glia, NBs are unable to generate sufficient energy for division and therefore prematurely differentiate via nuclear prospero resulting in small brains. The work will be of interest to those interested in neural stem cells and their non-cell autonomous control by niches.

The past decade has seen a growing appreciation of how glial cells support and maintain NBs during development. The authors' discovery of glial-derived ferritin providing essential iron atoms for energy production is interesting and important. They have employed a variety of genetic tools and assays to uncover how ferritin in glia might support NBs. This is particularly challenging because there are no direct ways of assaying for iron or energy consumption in a cell-specific manner.

There are however instances where conclusions are drawn to support the story being developed without considering the equally plausible alternative explanations that should ideally be addressed.

For example, the data supporting the transfer of ferritin from glia to NBs was weak given the misexpression system used; the Shi[ts] experiment was also not convincing (perhaps they have more representative images?).

The iron manipulation experiments are in the whole animal and it is likely that this affects general feeding behaviour, which is known to affect NB exit from quiescence and proliferative capacity. The loss of ferritin in the gut and iron chelators enhancing the NB phenotype are used as evidence that glia provide iron to NB to support their number and proliferation. Since the loss of NB is a phenotype that could result from many possible underlying causes (including low nutrition), this specific conclusion is one of many possibilities.

Similarly, knockdown of the FeS protein assembly components phenocopy glial ferritin knock down. Since iron is so important for the TCA and the ETC, this is not surprising, but the similarities in the two phenotypes seem insufficient to say that it's glial ferritin that's causing the lack of iron in the NB and therefore resulting in loss of NBs.

Pros RNAi will certainly result in an increase in NB numbers because the loss of pros results in an inability of NB progeny to differentiate. This (despite the slight increase in nuclear pros) is not sufficient to infer that glial ferritin knockdown results in premature differentiation of NBs via nuclear pros.

I recognise these are challenging to prove irrefutably, however, the frequency of such expansive interpretations of data is of concern.

Reviewer #3 (Public Review):

Summary:<br /> Loewinger et al., extend a previously described framework (Cui et al., 2021) to provide new methods for statistical analysis of fiber photometry data. The methodology combines functional regression with linear mixed models, allowing inference on complex study designs that are common in photometry studies. To demonstrate its utility, they reanalyze datasets from two recent fiber photometry studies into mesolimbic dopamine. Then, through simulation, they demonstrate the superiority of their approach compared to other common methods.

Strengths:<br /> The statistical framework described provides a powerful way to analyze photometry data and potentially other similar signals. The provided package makes this methodology easy to implement and the extensively worked examples of reanalysis provide a useful guide to others on how to correctly specify models.

Modeling the entire trial (function regression) removes the need to choose appropriate summary statistics, removing the opportunity to introduce bias, for example in searching for optimal windows in which to calculate the AUC. This is demonstrated in the re-analysis of Jeong et al., 2022, in which the AUC measures presented masked important details about how the photometry signal was changing.

Meanwhile, using linear mixed methods allows for the estimation of random effects, which are an important consideration given the repeated-measures design of most photometry studies.

Weaknesses:<br /> While the availability of the software package (fastFMM), the provided code, and worked examples used in the paper are undoubtedly helpful to those wanting to use these methods, some concepts could be explained more thoroughly for a general neuroscience audience.

While the methodology is sound and the discussion of its benefits is good, the interpretation and discussion of the re-analyzed results are poor:

In section 2.3, the authors use FLMM to identify an instance of Simpson's Paradox in the analysis of Jeong et al. (2022). While this phenomenon is evident in the original authors' metrics (replotted in Figure 5A), FLMM provides a convenient method to identify these effects while illustrating the deficiencies of the original authors' approach of concatenating a different number of sessions for each animal and ignoring potential within-session effects. The discussion of this result is muddled. Having identified the paradox, there is some appropriate speculation as to what is causing these opposing effects, particularly the decrease in sessions. In the discussion and appendices, the authors identify (1) changes in satiation/habitation/motivation, (2) the predictability of the rewards (presumably by the click of a solenoid valve) and (3) photobleaching as potential explanations of the decrease within days. Having identified these effects, but without strong evidence to rule all three out, the discussion of whether RPE or ANCCR matches these results is probably moot. In particular, the hypotheses developed by Jeong et al., were for a random (unpredictable) rewards experiment, whereas the evidence points to the rewards being sometimes predictable. The learning of that predictability (e.g. over sessions) and variation in predictability (e.g. by attention level to sounds of each mouse) significantly complicate the analysis. The FLMM analysis reveals the complexity of analyzing what is apparently a straightforward task design. If this paper is not trying to arbitrate between RPE and ANCCR, as stated in the text, the post hoc reasoning of the authors of Jeong et al 2022 provided in the discussion is not germane. Arbitrating between the models likely requires new experimental designs (removing the sound of the solenoid, satiety controls) or more complex models (e.g. with session effects, measures of predictability) that address the identified issues.

Of the three potential causes of within-session decreases, the photobleaching arguments advanced in the discussion and expanded greatly in the appendices are not convincing. The data being modeled is a processed signal (ΔF/F) with smoothing and baseline correction and this does not seem to have been considered in the argument. Furthermore, the photometry readout is also a convolution of the actual concentration changes over time, influenced by the on-off kinetics of the sensor, which makes the interpretation of timing effects of photobleaching less obvious than presented here and more complex than the dyes considered in the cited reference used as a foundation for this line of reasoning.

Within this discussion of photobleaching, the characterization of the background reward experiments used in part to consider photobleaching (appendix 7.3.2) is incorrect. In this experiment (Jeong et al., 2022), background rewards were only delivered in the inter-trial-interval (i.e. not between the CS+ and predicted reward as stated in the text). Both in the authors' description and in the data, there is a 6s before cue onset where rewards are not delivered and while not described in the text, the data suggests there is a period after a predicted reward when background rewards are not delivered. This complicates the comparison of this data to the random reward experiment.

The discussion of the lack of evidence for backpropagation, taken as evidence for ANCCR over RPE, is also weak. A more useful exercise than comparing FLMM to the methods and data of Jeong et al., 2022, would be to compare against the approach of Amo et al., 2022, which identifies backpropagation (data publicly available: DOI: 10.5061/dryad.hhmgqnkjw). The replication of a positive result would be more convincing of the sensitivity of the methodology than the replication of a negative result, which could be a result of many factors in the experimental design. Given that the Amo et al. analysis relies on identifying systematic changes in the timing of a signal over time, this would be particularly useful in understanding if the smoothing steps in FLMM obscure such changes.

Reviewer #3 (Public Review):

Summary:<br /> The authors present a Python tool, Heron, that provides a framework for defining and running experiments in a lab setting (e.g. in behavioural neuroscience). It consists of a graphical editor for defining the pipeline (interconnected nodes with parameters that can pass data between them), an API for defining the nodes of these pipelines, and a framework based on ZeroMQ, responsible for the overall control and data exchange between nodes. Since nodes run independently and only communicate via network messages, an experiment can make use of nodes running on several machines and in separate environments, including on different operating systems.

Strengths:<br /> As the authors correctly identify, lab experiments often require a hodgepodge of separate hardware and software tools working together. A single, unified interface for defining these connections and running/supervising the experiment, together with flexibility in defining the individual subtasks (nodes) is therefore a very welcome approach. The GUI editor seems fairly intuitive, and Python as an accessible programming environment is a very sensible choice. By basing the communication on the widely used ZeroMQ framework, they have a solid base for the required non-trivial coordination and communication. Potential users reading the paper will have a good idea of how to use the software and whether it would be helpful for their own work. The presented experiments convincingly demonstrate the usefulness of the tool for realistic scientific applications.

Weaknesses:<br /> In my opinion, the authors somewhat oversell the reproducibility and "self-documentation" aspect of their solution. While it is certainly true that the graph representation gives a useful high-level overview of an experiment, it can also suffer from the same shortcomings as a "pure code" description of a model - if a user gives their nodes and parameters generic/unhelpful names, reading the graph will not help much. Making the link between the nodes and the actual code is also not straightforward, since the code for the nodes is spread out over several directories (or potentially even machines), and not directly accessible from within the GUI. The authors state that "[Heron's approach] confers obvious benefits to the exchange and reproducibility of experiments", but the paper does not discuss how one would actually exchange an experiment and its parameters, given that the graph (and its json representation) contains user-specific absolute filenames, machine IP addresses, etc, and the parameter values that were used are stored in general data frames, potentially separate from the results. Neither does it address how a user could keep track of which versions of files were used (including Heron itself).

Another limitation that in my opinion is not sufficiently addressed is the communication between the nodes, and the effect of passing all communications via the host machine and SSH. What does this mean for the resulting throughput and latency - in particular in comparison to software such as Bonsai or Autopilot? The paper also states that "Heron is designed to have no message buffering, thus automatically dropping any messages that come into a Node's inputs while the Node's worker function is still running."- it seems to be up to the user to debug and handle this manually?

As a final comment, I have to admit that I was a bit confused by the use of the term "Knowledge Graph" in the title and elsewhere. In my opinion, the Heron software describes "pipelines" or "data workflows", not knowledge graphs - I'd understand a knowledge graph to be about entities and their relationships. As the authors state, it is usually meant to make it possible to "test propositions against the knowledge and also create novel propositions" - how would this apply here?

Reviewer #3 (Public Review):

Summary:

This paper reexamined large excitatory neurons in the stratum radiatum with optogenetics. The findings are valuable because prior studies of the circuitry were confounded by the use of stimulating electrodes placed in different layers where multiple inputs were stimulated at one time. The strength of the evidence for the conclusions is incomplete because of several concerns with the manuscript.

Strengths:

The strength of the study is the very nice presentation of data. Also, there is a nice combination of patching, LFPs, paired recordings, and microelectrode arrays.

Weaknesses:

The limitations are in the conclusions which don't seem fully justified.

Reviewer #3 (Public Review):

Summary:

Xiong et al. investigated the debated mechanism of PKA activation using hippocampal CA1 neurons under pharmacological and synaptic stimulations. Examining the two PKA major isoforms in these neurons, they found that a portion of PKA-C dissociates from PKA-R and translocates into dendritic spines following norepinephrine bath application. Additionally, their use of a non-dissociable form of PKC demonstrates its essential role in structural long-term potentiation (LTP) induced by two-photon glutamate uncaging, as well as in maintaining normal synaptic transmission, as verified by electrophysiology. This study presents a valuable finding on the activation-dependent re-distribution of PKA catalytic subunits in CA1 neurons, a process vital for synaptic functionality. The robust evidence provided by the authors makes this work particularly relevant for biologists seeking to understand PKA activation and its downstream effects essential for synaptic plasticity.

Strengths:

The study is methodologically robust, particularly in the application of two-photon imaging and electrophysiology. The experiments are well-designed with effective controls and a comprehensive analysis. The credibility of the data is further enhanced by the research team's previous works in related experiments. The conclusions of this paper are mostly well supported by data. The research fills a significant gap in our understanding of PKA activation mechanisms in synaptic functioning, presenting valuable insights backed by empirical evidence.

Weaknesses:

The physiological relevance of the findings regarding PKA dissociation is somewhat weakened by the use of norepinephrine (10 µM) in bath applications, which might not accurately reflect physiological conditions. Furthermore, the study does not address the impact of glutamate uncaging, a well-characterized physiologically relevant stimulation, on the redistribution of PKA catalytic subunits, leaving some questions unanswered.

Reviewer #3 (Public Review):

Summary:

Nguyen et al show data indicating that the vomeronasal organ (VNO) and ventromedial hypothalamus (VMH) are part of a circuit that elicits defensive responses induced by predator odors. They also show that using fresh or old predator saliva may be a method to change the perceived imminence of predation. The authors also identify a family of VNO receptors that are activated by cat saliva. Next, the authors show how different components of this defensive circuit are activated by saliva, as measured by fos expression. Though interesting, the findings are not all integrated into a single narrative, and some of the results are only replications of earlier findings using modern methods. Overall, these findings provide incremental advance.

Strengths:

(1) Predator saliva is a stimulus of high ethological relevance

(2) The authors performed a careful quantification of fos induction across the anterior-posterior axis in figure 6

Weaknesses:

(1) It is unclear if fresh and old saliva indeed alter the perceived imminence of predation, as claimed by the authors. Prior work indicates that lower imminence induces anxiety-related actions, such as re-organization of meal patterns and avoidance of open spaces, while slightly higher imminence produces freezing. Here, the authors show that fresh and old predator saliva only provoke different amounts of freezing, rather than changing the topography of defensive behaviors, as explained above. Another prediction of predatory imminence theory would be that lower imminence induced by old saliva should produce stronger cortical activation, while fresh saliva would activate amygdala, if these stimuli indeed correspond to significantly different levels of predation imminence.

(2) It is known that predator odors activate and require AOB, VNO and VMH, thus replications of these findings are not novel, decreasing the impact of this work.

(3) There is a lack of standard circuit dissection methods, such as characterizing the behavioral effects of increasing and decreasing neural activity of relevant cell bodies and axonal projections, significantly decreasing the mechanistic insights generated by this work

(4) The correlation shown in Figure 5c may be spurious. It appears that the correlation is primarily driven by a single point (the green square point near the bottom left corner). All correlations should be calculated using Spearman correlation, which is non-parametric and less likely to show a large correlation due to a small number of outliers. Regardless of the correlation method used, there are too few points in Figure 5c to establish a reliable correlation. Please add more points to 5c.

(5) Please cite recent relevant papers showing VMH activity induced by predators, such as https://pubmed.ncbi.nlm.nih.gov/33115925/ and https://pubmed.ncbi.nlm.nih.gov/36788059/

(6) Add complete statistical information in the figure legends of all figures, which should include n, name of test used and exact p values.

(7) Some of the findings are disconnected from the story. For example, the authors show V2R-A4-expressing cells are activated by predator odors. Are these cells more likely to be connected to the rest of the predatory defense circuit than other VNO cells?

(8) Please paste all figure legends directly below their corresponding figure to make the manuscript easier to read

(9) Were there other behavioral differences induced by fresh compared to old saliva? Do they provoke differences in stretch-attend risk evaluation postures, number of approaches, average distance to odor stimulus, velocity of movements towards and away the odor stimulus, etc?

Reviewer #3 (Public Review):

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

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

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

Reviewer #3 (Public Review):

Summary:

This study studied the neural mechanisms underlying the shift of ocular dominance induced by "dichoptic-backward-movie" adaptation. The study is self-consistent.

Strengths:

The experimental design is solid and progressive (relationship among three studies), and all of the raised research questions were well answered.<br /> The logic behind the neural mechanisms is solid.<br /> The findings regarding the cTMS (especially the position/site can be useful for future medical implications).<br /> The updated Exp4 eliminates some concerns and thus makes the results even more solid.

Reviewer #3 (Public Review):

Summary:

This manuscript reveals an important mechanism of KCNQ1/IKs channel gating such that the open state of the pore is unstable and undergoes intermittent closed and open conformations. PUFA enhances the maximum open probability of IKs by binding to a crevice adjacent to the pore and stabilizing the open conformation. This mechanism is supported by convincing single-channel recordings that show empty and open channel traces and the ratio of such traces is affected by PUFA. In addition, mutations of the pore residues alter PUFA effects, convincingly supporting that PUFA alters the interactions among these pore residues.

Strengths:<br /> The data are of high quality and the description is clear.

Weaknesses:<br /> Some comments about the presentation.

(1) The structural illustrations in this manuscript in general need to be more clarified.

(2) The manuscript heavily relies on the comparison between the S4-down and S4-up structures (Figures 3, 4, and 7) to illustrate the difference between the extracellular side of the pore and to lead to the hypothesis of open-state stability being affected by PUFA. This may mislead the readers to think that the closed conformation of the channel in the up-state is the same as that in the down-state.

Reviewer #3 (Public Review):

Summary:<br /> The authors demonstrate the activation of Polycystin-1 (PC1), a G-protein coupled receptor, using small peptides derived from its original agonist, the stalk TA protein. In the experimental part of the study, the authors performed cellular assays to check the peptide-induced reactivation of a mutant form of PC1 which does not contain the stalk agonist. The experimental data is supported by computational studies using state-of-the-art Gaussian accelerated Molecular Dynamics (GaMD) and bioinformatics analysis based on sequence covariance. The computer simulations revealed the mechanistic details of the binding of the said peptides with the mutant PC1 protein and discovered different bound, unbound, and intermediate conformations depending on the peptide size and sequence. The use of reliable and well-established molecular simulation algorithms and the physiological relevance of this protein autosomal dominant polycystic kidney disease (ADPKD) make this work particularly valuable.

Strengths:<br /> This work is exploratory and its goal is to establish that small peptides can be used to probe the PC1 signaling process. The authors have provided sufficient evidence to justify this claim. Their GaMD simulations have produced free-energy landscapes that differentiate the interaction of PC1 with three different synthetic peptides and demonstrate the associated conformational dynamics of the receptor protein. Their trajectory analysis and sequence covariance analysis could identify residue-specific interactions that facilitate this process.

Weaknesses:<br /> The following minor weaknesses should be taken into account by the reader when interpreting the results:

(1) No control has been used for the computational (GaMD) study as the authors only report the free energy surface for 3 highly agonistic peptides but for none of the other peptides that did not induce an agonistic effect. Therefore, in the current version, the reliability of the computational results is not foolproof.

(2) All discussions about the residue level interactions focused only on geometric aspects (distance, angle, etc) but not the thermodynamic aspect (e.g. residue-wise interaction energy). Considering they perform a biased simulation, the lack of interaction energy analysis only provides a qualitative picture of the mechanism.

(3) It is not mentioned clearly whether the reader should interpret the free energy landscapes quantitatively or qualitatively. Considering no error analysis or convergence plots are reported for the GaMD free energy surfaces, it may be assumed the results are qualitative. The readers should consider this caveat and not try to quantitatively reproduce these free energy landscapes with other comparable techniques.

Reviewer #3 (Public Review):

Summary:

Jojoa-Cruz et al provide a new structure of At-OSCA3.1. The structure of OSCA 3.1 is similar to previous OSCA cryo-em structures of both OSCA3.1 and other homologues validating the new structure. Using the novel structure of OSCA3.1 as a guide they created several point mutations to investigate two different mechanosensitive modalities: poking and stretching. To investigate the ability of OSCA channels to gate in response to poking they created point mutations in OSCA1.2 to reduce sensitivity to poking based on the differences between the OSCA1.2 and 3.1 structures. Their results suggest that two separate regions are responsible for gating in response to poking and stretching.

Strengths:

Through a detailed structure based analysis, the authors identified structural differences between OSCA3.1 and OSCA1.2. The use of technically sound data supports the hypothesis that poking and stretching are sensed by two unique regions in the protein. These subtle structural changes between homologues identify regions in the amphipathic helix and near the pore that are essential for gating of OSCA1.2 in response to poking and stretching. Mutations in the AH of OSCA1.2 decrease the sensitivity to poking stimulus however these mutations have similar stretch activated currents to the WT. The point mutations described in the manuscript will set the foundation for investigations into how these two channels sense tension using different regions of structurally similar proteins.

Weaknesses:

Mutations in the amphipathic helix at W75 and L80 show reduced gating in response to poking stimuli. The gating observed occurs at poking depths similar to cellular rupture, the similarity in depths suggests that these mutations could be a complete loss of functions.

Reviewer #3 (Public Review):

In their manuscript, Schneider et al. aim to develop voyAGEr, a web-based tool that enables the exploration of gene expression changes over age in a tissue- and sex-specific manner. The authors achieved this goal by calculating the significance of gene expression alterations within a sliding window, using their unique algorithm, Shifting Age Range Pipeline for Linear Modelling (ShARP-LM), as well as tissue-level summaries that calculated the significance of the proportion of differentially expressed genes by the windows and calculated enrichments of pathways for showing biological relevance. Furthermore, the authors examined the enrichment of cell types, pathways, and diseases by defining the co-expressed gene modules in four selected tissues. Although their algorithm ShARP-LM has limited statistical power due to its calculation within a 16-year window, the voyAGEr was developed as a discovery tool, giving researchers easy access to the vast amount of transcriptome data from the GTEx project. Overall, the research design is unique and well-performed in simulating age-dependent changes in gene expression. The interesting results provide useful resources for the field of human genetics of aging.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, entitled "Telomere length sensitive regulation of Interleukin Receptor 1 type 1 (IL1R1) by the shelterin protein TRF2 modulates immune signalling in the tumour microenvironment", Dr. Mukherjee and colleagues pointed out clarifying the extra-telomeric role of TRF2 in regulating IL1R1 expression with consequent impact on TAMs tumor-infiltration.

Strengths:<br /> Upon careful manuscript evaluation, I feel that the presented story is undoubtedly well conceived. At the technical level, experiments have been properly performed and the obtained results support the authors' conclusions.

Weaknesses:<br /> Unfortunately, the covered topic is not particularly novel. In detail, the TRF2 capability of binding extratelomeric foci in cells with short telomeres has been well demonstrated in a previous work published by the same research group. The capability of TRF2 to regulate gene expression is well-known, the capability of TRF2 to interact with p300 has been already demonstrated and, finally, the capability of TRF2 to regulate TAMs infiltration (that is the effective novelty of the manuscript) appears as an obvious consequence of IL1R1 modulation (this is probably due to the current manuscript organization).

Reviewer #3 (Public Review):

Summary:

The work submitted by Dr. Jeong-Oh Shin and co-workers aims to investigate the therapeutic efficacy of rhPTH(1-34) and R25CPTH(1-34) on bone regeneration and osseointegration of titanium implants using a postmenopausal osteoporosis animal model.<br /> In my opinion the findings presented are not strongly supported by the provided data since the methods utilized do not allow to significantly support the primary claims.

Strengths:

Strengths include certain good technologies utilized to perform histological sections (i.e. the EXAKT system).

Weaknesses:

Certain weaknesses significantly lower the enthusiasm for this work. Most important: the limited number of samples/group. In fact, as presented, the work has an n=4 for each treatment group. This limited number of samples/group significantly impairs the statistical power of the study. In addition, the implants were surgically inserted following a "conventional implant surgery", implying that no precise/guided insertion was utilized. This weakness is, in my opinion, particularly significant since the amount of bone osteointegration may greatly depend on the bucco-lingual positioning of each implant at the time of the surgical insertion (which should, therefore, be precisely standardized across all animals and for all surgical procedures).<br /> On a minor note: not sure why the authors present a methodology to evaluate the dynamic bone formation (line 272) but do not present results (i.e. by means of histomorphometrical analyses) utilizing this methodology.

Reviewer #3 (Public Review):

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

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

Reviewer #3 (Public Review):

Summary:

In this manuscript, Lim and colleagues use an innovative CDRA chip platform to derive and mechanistically elucidate the molecular wiring of doxorubicin-resistant (DOXR) MDA-MB-231 cells. Given their enlarged morphology and polyploidy, they termed these cells as Large-DOXR (L-DORX). Through comparative functional omics, they deduce the NUPR1/HDAC11 axis to be essential in imparting doxorubicin resistance and, consequently, genetic or pharmacologic inhibition of the NUPR1 to restore sensitivity to the drug.

Strengths:

The study focuses on a major clinical problem of the eventual onset of resistance to chemotherapeutics in patients with triple-negative breast cancer (TNBC). They use an innovative chip-based platform to establish as well as molecularly characterize TNBC cells showing resistance to doxorubicin and uncover NUPR1 as a novel targetable driver of the resistant phenotype.

Weaknesses:

Critical weaknesses are the use of a single cell line model (i.e., MDA-MB-231) for all the phenotypic and functional experiments and absolutely no mechanistic insights into how NUPR1 functionally imparts resistance to doxorubicin. It is imperative that the authors demonstrate the broader relevance of NUPR1 in driving dox resistance using independent disease models.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Yujiro Umezaki and colleagues aims to describe how taste stimuli influence temperature preference in Drosophila. Under starvation flies display a strong preference for cooler temperatures than under fed conditions that can be reversed by refeeding, demonstrating the strong impact of metabolism on temperature preference. In their present study, Umezaki and colleagues observed that such changes in temperature preference are not solely triggered by the metabolic state of the animal but that gustatory circuits and peptidergic signalling play a pivotal role in gustation-evoked alteration in temperature preference.

The study of Umezaki is definitively interesting and the findings in this manuscript will be of interest to a broad readership.

Strengths:<br /> The authors demonstrate interesting new data on how taste input can influence temperature preference during starvation. They propose how gustatory pathways may work together with thermosensitive neurons, peptidergic neurons and finally try to bridge the gap between these neurons and clock genes. The study is very interesting and the data for each experiment alone are very convincing.

Weaknesses:<br /> In my opinion, the authors have opened many new questions but did not fully answer the initial question - how do taste-sensing neurons influence temperature preferences? What are the mechanisms underlying this observation? Instead of jumping from gustatory neurons to thermosensitive neurons to peptidergic neurons to clock genes, the authors should have stayed within the one question they were asking at the beginning. How does sugar sensing influence the physiology of thermos-sensation in order to change temperature preference? Before addressing all the following questions of the manuscript the authors should first directly decipher the neuronal interplay between these two types of neurons.

Reviewer #3 (Public Review):

Summary:<br /> The authors examined the effects of glutamate release from PMv LepR neurons in the regulation of puberty and reproduction in female mice.

Strengths:<br /> Multiple genetic mouse models were utilized to either manipulate PMv LepR neuron activities, or to delete glutamate vesicle transporters from LepR neurons. The authors have been quite rigorous in validating these models and exploring potential contaminations. Most of the data presented are solid and convincing and support the conclusion.

Weaknesses:<br /> Some results are hard to interpret.

Reviewer #3 (Public Review):

This work is carried out by the research group led by Shuiqiao Yuan, who has a long interest and significant contribution in the field of male germ cell development. The authors study a protein for which limited information existed prior to this work, a component of the E3 ubiquitin ligase complex, FBXO24. The authors generated the first FBXO24 KO mouse model reported in the literature using CRISPR, which they complement with HA-tagged FBXO24 transgenic model in the KO background. The authors begin their study with a very careful examination of the expression pattern of the FBXO24 gene at the level of mRNA and the HA-tagged transgene, and they provide conclusive evidence that the protein is expressed exclusively in the mouse testis and specifically in post-meiotic spermatids of stages VI to IX, which include early stages of spermatid elongation and nuclear condensation. The authors report a fully sterile phenotype for male mice, while female mice are normal. Interestingly, the testis size and the populations of spermatogenic cells in the KO mutant mice show small (but significant) reduction compared to the WT testis. Importantly, the mature sperm from KO animals show a series of defects that were very thoroughly documented in this work by scanning and transmission electron microscopy; this data constitutes a very strong point in this paper. FBXO24 KO sperm have severe defects in the mitochondrial sheath with missing mitochondria near the annulus, and missing outer dense fibers. Collectively these defects cause abnormal bending of the flagellum and severely reduced sperm motility. Moreover, defects in nuclear condensation are observed with faint nuclear staining of elongating and elongated spermatids, and reduction of protein levels of protamine 2 combined with increased levels of histones and transition protein 1. All the above are in line with the observed male sterility phenotype.

The authors also performed RNASeq in the KO animal, and found profound changes in the abundance of thousands of mRNAs; changes in mRNA splicing patterns were noted as well. This data reveals deeply affected gene expression patterns in the FBXO24 KO testis, which further supports the essential role that this factor serves in spermiogenesis. Unfortunately, a molecular explanation of what causes these changes is missing; it is still possible that they are an indirect consequence of the absence of FBXO24 and not directly caused by it.

The finding that Miwi protein levels are increased in the FBXO24 KO testis is an important point in this work, and it is in agreement with the observed increased size of the chromatoid body, where most of Miwi protein is accumulated in round spermatids. This finding is well supported with experiments performed in 293T cells showing that Miwi ubiquitination is FBXO24 dependent in this ectopic system. Moreover, the authors detect reduced ubiquitination of endogenous Miwi protein immunoprecipitated from FBXO24 KO testis. Consistent with an increase in Miwi protein levels, Miwi-sized piRNAs show increased abundance in total RNA from FBXO24 KO testis. It has been documented that Piwi proteins stabilize their piRNA cargo, so the increase in piRNA levels in 29-32 nt sizes is most likely not a result of altered biogenesis, but increased half-life of the piRNAs as a result of Miwi upregulation. piRNAs have been involved in the regulation of mRNAs in the post-meiotic spermatid, but it is unclear how increased Miwi protein and its piRNA cargo at the levels observed in this study contribute to the complete infertility phenotype of the FBXO24 KO male mice.

Therefore, a well-reasoned narrative on if and how the absence of FBXO24 as an E3 ubiquitin ligase is responsible for the observed mRNA and protein differential expression is largely absent. If FBXO24-mediated ubiquitination is required for normal protein degradation during spermiogenesis, protein level increase should be the direct consequence of genuine FBXO24 targets in the KO testis. Apart from Miwi, the possible involvement of ubiquitination was not shown for any other proteins that the authors found interact with FBXO24 such as splicing factors SRSF2, SRSF3, SRSF9, or any of the other proteins whose levels were found to be changed (reduced, thus the change in the KO is less likely due to absence of ubiquitination) such as ODF2, AKAP3, TSSK4, PHF7, TSSK6 and RNF8. Interestingly, the authors do observe increased amounts of histones and transition proteins, but reduced amounts of protamines, which directly shows that histone to protamine transition is indeed affected in the FBXO24 KO testis, consistent with the observed less condensed nuclei of spermatozoa. Could histones and transition proteins be targets of the proposed ubiquitin ligase activity of FBXO24, and in its absence, histone replacement is abrogated? Providing experimental evidence to address this possibility would greatly expand our understanding on why FBXO24 is essential during spermiogenesis.

Reviewer #3 (Public Review):

Summary:

The authors used a novel technique to treat male infertility. In a proof-of-concept study, the authors were able to rescue the phenotype of a knockout mouse model with immotile sperm using this technique. This could also be a promising treatment option for infertile men.

Strengths:

In their proof-of-concept study, the authors were able to show that the novel technique rescues the infertility phenotype in vivo.

Weaknesses:

Some minor weaknesses, especially in the discussion section, could be addressed to further improve the quality of the manuscript.

It is very convincing that the phenotype of Armc2 KO mice could (at least in part) be rescued by injection of Armc2 RNA. However, a central question remains about which testicular cell types have been targeted by the constructs. From the pictures presented in Figures 7 and 8, this issue is hard to assess. Given the more punctate staining of the DNA construct a targeting of Sertoli cells is more likely, whereas the more broader staining of seminiferous tubules using RNA constructs is talking toward germ cells.

Further, the staining for up to 119 days (Figure 5) would point toward an integration of the DNA construct into the genome of early germ cells such as spermatogonia and/or possibly to Sertoli cells. Given the expression after RNA transfection for up to 21 days (Figure 4) and the detection of motile sperm after 21 days (Figure 11), this would point to either round spermatids or spermatocytes.

These aspects need to be discussed more carefully (discussion section: lines 549-574).

It would also be very interesting to know in which testicular cell type Armc2 is endogenously expressed (lines 575-591).

Reviewer #3 (Public Review):

Summary:<br /> This work uses tools and concepts from co-phylogenetic analyses to reconstruct the evolutionary and diversification history of coronaviruses in mammals. It concludes that cross-species transmissions from bats to humans are a relatively common event (compared to bats to other species). Across all mammals, the diversification history of coronaviruses suggests that there is potential for further evolutionary diversification.

Strengths:<br /> The article uses an interesting approach based on jointly looking at the extant network of coronaviruses-mammals interactions, and the phylogenetic history of both these organisms. The authors do an impressive job of explaining the challenges of reconstructing evolutionary dynamics for RNA viruses, and this helps readers appraise the relevance of their approach.

Weaknesses:<br /> I remain unconvinced by the argument that sampling does not introduce substantial biases in the analyses. As the authors highlight, incomplete knowledge of the extant interactions would lead to a biased reconstruction of the diversification history. In a recent paper (Poisot et al. 2023, Patterns), we look at sampling biases in the virome of mammals and suggest that is a fairly prominent issue, that is furthermore structured by taxonomy, space, and phylogenetic position. Case in point, even for betacoronaviruses, there have been many newly confirmed hosts in recent years. For organisms that have received less intense scrutiny, I think a thorough discussion of potential gaps in data would be required (see for example Cohen et al. 2022, Nat. Comms).

I was also surprised to see little discussion of the differences between alpha and beta coronaviruses - there is evidence that they may differ in their cross-species transmission (see Caraballo et al. 2022 Micr. Spectr.), which could call into question the relevance of treating all coronaviruses as a single, homogeneous group.

Some of the discussions in this paper also echo previous work by e.g. Geoghegan et al. (see 2017, PLOS Pathogens), which I was surprised to not see discussed, as it is a much earlier investigation of the relative frequencies of co-divergence and host switches for different viral families, with a deep discussion of how this may structure future evolutionary dynamics.

Reviewer #3 (Public Review):

Summary:

This work describes a new pathway by which malaria parasites, P. falciparum, may regulate their growth and virulence (i.e. their expression of virulence-linked cytoadhesins). This is a topic of considerable interest in the field - does this important parasite sense factor(s) in its host bloodstream and regulate itself accordingly? Several fragments of evidence have come out on this topic in the past decade, showing, for example, reduced parasite growth under calorie restriction (in mice); parasite dormancy in response to amino acid starvation (in culture and in mice), and also reduced virulence in dry-season, low-parasitaemia infections in humans. The molecular mechanisms that may underlie this interesting biology remain only poorly understood.

Here, the authors show that dry-season P. falciparum parasites have reduced expression of Pol3-transcribed tRNAs and ncRNAs that positively regulate virulence gene expression. They link the level of Pol3 activity to PfMaf1, a remnant of the largely-absent nutrient-sensing TOR pathway in this parasite. They propose that in the dry season, human hosts may be calorie-restricted, leading to Maf1 moving to the nucleus and suppressing Pol3, thus downregulated growth and virulence of parasites. The evidence is intriguing and the idea is conceptually elegant.

Strengths:

The use of dry/wet-season field samples from The Gambia is a strength, showing potential real-world relevance. The generation of an inducible knockdown of Maf1 in lab-cultured parasites is also a strength, allowing this pathway to be studied somewhat in isolation.

Weaknesses:

(1) The signals upstream of Maf1 remain rather a black box. 4 are tested - heat shock and low-glucose, which seem to suppress ALL transcription; low-Isoleucine and high magnesium, which suppress Pol3. Therefore the authors use Mg supplementation throughout as a 'starvation type' stimulus. They do not discuss why they didn't use amino acid limitation, which could be more easily rationalised physiologically. It may be for experimental simplicity (no need for dropout media) but this should be discussed, and ideally, sample experiments with low-IsoLeu should be done too, to see if the responses (e.g. cytoadhesion) are all the same.

(2) The proteomics, conducted to seek partners of Maf1, is probably the weakest part. From Figure S3: the proteins highlighted in the text are clearly highly selected (as ones that might be relevant, e.g. phosphatases), but many others are more enriched. It would be good to see the whole list, and which GO terms actually came top in enrichment.

(3) Figure 3 shows the Maf1-low line has very poor growth after only 5 days but it is stated that no dead parasites are seen even after 8 cycles and the merozoites number is down only ~18 to 15... is this too small to account for such poor growth (~5-fold reduced in a single cycle, day 3-5)? It would additionally be interesting to see a cell-cycle length assessment and invasion assay, to see if Maf1-low parasites have further defects in growth.

Reviewer #3 (Public Review):

Liang and colleagues set out to test whether the human brain uses distance and grid-like codes in social knowledge using a design where participants had to navigate in a two-dimensional social space based on competence and warmth during an fMRI scan. They showed that participants were able to navigate the social space and found distance-based codes as well as grid-like codes in various brain regions, and the grid-like code correlated with behavior (reaction times).

On the whole, the experiment is designed appropriately for testing for distant-based and grid-like codes, and is relatively well powered for this type of study, with a large amount of behavioral training per participant. They revealed that a number of brain regions correlated positively or negatively with distance in the social space, and found grid-like codes in the frontal polar cortex and posterior medial entorhinal cortex, the latter in line with prior findings on grid-like activity in entorhinal cortex. The current paper seems quite similar conceptually and in design to previous work, most notably Park et al., 2021, Nature Neuroscience.

(1) The authors claim that this study provides evidence that humans use a spatial / grid code for abstract knowledge like social knowledge.

This data does specifically not add anything new to this argument. As with almost all studies that test for a grid code in a similar "conceptual" space (not only the current study), the problem is that, when the space is not a uniform, square/circular space, and 2-dimensional then there is no reason the code will be perfectly grid like, i.e., show six-fold symmetry. In real world scenarios of social space (as well as navigation, semantic concepts), it must be higher dimensional - or at least more than two dimensional. It is unclear if this generalizes to larger spaces where not all part of the space is relevant. Modelling work from Tim Behrens' lab (e.g., Whittington et al., 2020) and Bradley Love's lab (e.g., Mok & Love, 2019) have shown/argued this to be the case. In experimental work, like in mazes from the Mosers' labs (e.g., Derdikman et al., 2009), or trapezoid environments from the O'Keefe lab (Krupic et al., 2015), there are distortions in mEC cells, and would not pass as grid cells in terms of the six-fold symmetry criterion.

The authors briefly discuss the limitations of this at the very end but do not really say how this speaks to the goal of their study and the claim that social space or knowledge is organized as a grid code and if it is in fact used in the brain in their study and beyond. This issue deserves to be discussed in more depth, possibly referring to prior work that addressed this, and raise the issue for future work to address the problem - or if the authors think it is a problem at all.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, Salazar-Lázaro et al. presented interesting data that C-terminal half of the Syx1 SNARE domain is responsible for clamping of spontaneous release, stabilizing RRP, and also Ca2+-evoked release. The authors routinely utilized the chimeric approach to replace the SNARE domain of Syx1 with its paralogue Syx2 and analyzed the neuronal activity through electrophysiology. The data are straightforward and fruitful. The conclusions are reasonable.

Strengths:<br /> The electrophysiology data that illustrate the important functions of Syx1 in clamping of spontaneous release, stabilizing RRP, and also Ca2+-evoked release were clear and convincing.

Weaknesses:<br /> One weakness is that the authors did not go deep into the underlying molecular mechanisms experimentally, either because of a variety of complicated possibilities or limited space of the manuscript.

Reviewer #3 (Public Review):

Summary: The authors aim to solve how landscape context impacts the community BEF relationship. They found habitat loss and fragmentation per se have inconsistent effects on biodiversity and ecosystem function. And habitat loss rather than fragmentation per se can weaken the positive BEF relationship by decreasing the degree of habitat specialization of the community.

Strengths: The authors provide a good background, and they have a good grasp of habitat fragmentation and BEF literature.<br /> A major strength of this study is separating the impacts of habitat loss and fragmentation per se using the convincing design selection of landscapes with different combinations of habitat amount and fragmentation per se.<br /> Another strength is considering the role of specialists and generalists in shaping the BEF relationship.

Weaknesses:<br /> No<br /> In the revised manuscript, the authors have provided more detailed information about the ecological significance of these fragmentation indices. and also integrated two environmental factors related to water and temperature (soil water content and land surface temperature) into the data analysis to control their potential impact.

Reviewer #3 (Public Review):

Summary:

Using a combination of approaches, including automated feature selection and hierarchical clustering, the author identified a set of genes persistently associated with extrachromosomal DNA (ecDNA) presence across cancer types. The authors further validated the gene set identified using gene ontology enrichment analysis and identified that upregulated genes in extrachromosomal DNA-containing tumors are enriched in biological processes like DNA damage and cell proliferation, whereas downregulated genes are enriched in immune response processes.

Comments for the previous version:

Major comments:

(1) The authors presented a solid comparative analysis of ecDNA-containing and ecDNA-free tumors. An established automated feature selection approach, Boruta, was used to select differentially expressed genes (DEG) in ecDNA(+) and ecDNA(-) TCGA tumor samples, and the iterative selection process and two-tier multiple hypothesis testing ensured the selection of reliable DEGs. The author showed that the DEG selected using Boruta has stronger predictive power than genes with top log-fold changes.

(2) The author performed a thorough interpretation of the findings with GO enrichment analysis of biological processes enriched in the identified DEG set and presented interesting findings, including the enrichment in DNA damage process among the genes upregulated in ecDNA(+) tumors.

(3) Overall, the authors achieved their aims with solid data mining and analysis approaches applied to public data tumor data sets.

(4) While it may not be the scope of this study, it will be interesting to at least have some justification for choosing Boruta over other feature selection methods, such as Recursive Feature Elimination (RFE) and backward stepwise selection.

(5) The authors showed that DESEQ-selected DEGs with top log-fold changes have less strong predictive power and speculated that this may be due to the fact that genes with top log-fold changes (LFC) are confined only to a small subset of samples. It will be interesting to select DEGs with top log-fold changes after first partitioning the tumor samples. For example, randomly partition the tumor samples, identify the DEGs with top LFC, combine the DEGs identified from each partition, then evaluate the predictive power of these DEGs against the Boruta-selected DEGs.

(6) While the authors showed that the presence of mutations was not able to classify ecDNA(+) and (-) tumor samples, it will be interesting to see if variant allele frequencies of the genes containing these mutations have predictive power.

Comments for the revised version:

The authors addressed the comments and recommendations with solid analysis and explanations in the revision. The added analysis using GLM is especially appreciated and provides convincing evidence for the predicting power of the Boruta-selected genes. The only comment is at this point is that it is recommended that the author provide some justification for choosing Boruta over other feature selection methods. It is not necessary to provide benchmarking results - justification based on the review of previous literature is sufficient, as it is not well explained in the paper why Boruta was chosen in the first place. Is it state-of-the-art? Has it demonstrated better performance in other settings? A few sentences answering these questions should suffice.

Reviewer #3 (Public Review):

In this manuscript, the authors define the developmental trajectory resulting in a diverse mTEC compartment. Using a variety of approaches, including a novel CCL21-fate mapping model, data is presented to argue that embryonic CCL21-expressing thymocyte attracting mTECs naturally convert to into self-antigen displaying mTEC subsets, including Aire+ mTECs and thymic tuft cells. Perhaps somewhat surprisingly, a large fraction of cTECs were also marked for having expressed CCL21, suggesting that there exists some conversion of mTEC (progenitors) into cTEC, a developmentally interesting observation that could be followed up later. Overall, the experimental setup, writing, and conclusions, are all outstanding. The one question I have, which may be more of a curiosity of this reviewer than a requirement for the manuscript, is whether thymocytes themselves are required for the conversion/maturation of attracting TECs to mTECs? For example, in CD3e-/- (or Rag-/-) mice, are mTECs arrested at the thymocyte attracting stage, or is the conversion process 'pre-programed'? In the same vein, do cTECs (or the immature cTECs) maintain CCL21 expression in the absence of mature thymocytes? These are not critical studies but are fairly straightforward (effort- and time-wise) that would aid in placing this process in the overall scope of thymus development.

Reviewer #3 (Public Review):

I very much like this approach and the idea of incorporating hypervariable markers. The method is intriguing, and the ability to e.g. estimate recombination rates, the size of DMRs, etc. is a really nice plus. I am not able to comment on the details of the statistical inference, but from what I can evaluate it seems reasonable and in principle the inclusion of highly mutable sties is a nice advance. This is an exciting new avenue for thinking about inference from genomic data. I remain a bit concerned about how well this will work in systems where much less is understood about methylation,

The authors include some good caveats about applying this approach to other systems, but I think it would be helpful to empiricists outside of thaliana or perhaps mammalian systems to be given some indication of what to watch out for. In maize, for example, there is a non-bimodal distribution of CG methlyation (35% of sites are greater than 10% and less than 90%) but this may well be due to mapping issues. The authors solve many of the issues I had concerns with by using gene body methylation, but this is only briefly mentioned on line 659. I'm assuming the authors' hope is that this method will be widely used, and I think it worth providing some guidance to workers who might do so but who are not as familiar with these kind of data.

Reviewer #3 (Public Review):

Summary: The paper "Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction" reports the combination of prior knowledge signaling networks, multiparametric cell-based data on the activation status of 14 crucial proteins emblematic of the cell state downstream of FLT3 obtained under a variety of perturbation conditions and Boolean logic modeling, to gain mechanistic insight into drug resistance in acute myeloid leukemia patients carrying the internal tandem duplication in the FLT3 receptor tyrosine kinase and predict drug combinations that may reverse pharmacoresistant phenotypes. Interestingly, the utility of the approach was validated in vitro and using real-world data.

Strengths:

The model predictions have been validated in vitro and using external data.

This is a complex study, but readability is enhanced by the inclusion of a section that summarizes the study design, plus relevant figures. The availability of data as supplementary material and the availability of code in GitHub are also high points.

Weaknesses:

There are some apparent discrepancies between predicted and observed data that have been seemingly overlooked.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors collected a large set of data on root traits and root-associated microbes in the root endosphere and rhizosphere in order to integrate these important organisms in the root economics spectrum. By sampling a relatively large set of species from the subtropics along an elevation gradient, they tested whether microbial functions covary with root traits and root trait axes and if so, aimed to discuss what this could tell us about the (belowground) functioning of trees and forests.

Strengths:<br /> The strengths of this study lie mostly in the impressive dataset set the authors compiled: they sampled belowground properties of a relatively large number of tree species from an understudied region: i.e., the subtropics, where species-level root data are notoriously scarce. Secondly, their extensive sampling of associated microbes to integrate them in the root economics space is an important quality, because of the strong associations between roots and fungi and bacteria: soil microbes are directly related to root form (e.g., mycorrhizal fungi and root diameter and SRL), and function (e.g., taking up soil nutrients from various sources). Thirdly, the PCA figures (Figures 2 and 3) look very nice and intuitive and the paper is very well written.

Weaknesses:<br /> That said, this study also has several methodological weaknesses that make the results, and therefore the impact of this study difficult to evaluate and interpret.

(1) Design: The design of this study needs further explanation and justification in the Introduction and Methods sections in order to understand the ecological meaning of the results. Root traits and microbial community composition differ with their environment, and therefore (likely) also with elevation. Elevation is included in the redundancy analysis as a main effect, but without further environmental information, its impact is not ecologically meaningful. What is the rationale for including an elevation gradient in the design and as a main effect in the analyses? Do environmental conditions vary across altitudes and how, and if so, how would this impact the data?

What is the rationale behind sampling endosphere and rhizosphere microbial communities - why do both? And why also include pathogens - what are their expected roles in the RES? What do we know about this already? The introduction needs a more extensive literature review of these additional variables that are included in the analyses.

(2) Units of replication and analysis in the model: What are the units of replication and analyses, e.g., how many trees were sampled per species, how many species or trees per elevation, and how many plots per elevation? Were all 11 plots at different elevations and if so, which ones? The level of analysis for the redundancy analyses is not entirely clear: L. 404 mentions that the analyses were done 'across the rhizosphere and root tissue samples', but is that then at the individual-tree level? If so, it seems that these analyses should then also account for dependencies between trees from the same species and phylogeny (as (nested) covariates or random factors). With the information provided, I cannot tell whether there was sufficient replication for statistical interpretations.

(3) PCA: The results of the parallel analyses are not described: which components were retained? Because the authors aim to integrate microbial functions in a root economics space, I recommend first demonstrating the existence of a root economics space across the 52 subtropical species before running a PCA that includes the microbial traits. The PCA shown in this study does not exactly match the RES and this could be because traits of these species covary differently, but may also simply result from including additional traits to the PCA.

Also, the PCA's shown are carried out at the individual-tree level. I would recommend, however, including the species-level PCA's in the main text, because the individual-level PCA may not only reflect species-inherent ecological strategies (that e.g., the RES by Bergmann et al. 2020 describe) but also plasticity (Figures 2 and 3 both show an elevation effect that may be partly due to plasticity). While the results here are rather similar, intraspecific differences in root traits may follow different ecological principles and therefore not always be appropriate to compare with an interspecific RES (see for example Weemstra & Valverde-Barrantes, 2022, Annals of Botany).

I could not deduce whether tree species in the "fungal PCA" (Figure 2) were assigned as AM or EcM based on Table 1, or based on their observed fungal community composition. In the former case, the fungal functional guild gradient (from EcM to saprotrophs and AM) is partially an artificial one, because EcM tree species are not AM species (according to Table 1) and therefore, by definition, constitute a tradeoff or autocorrelation. And, as the authors also discuss, AM tree species may host EcM fungal species. Before I can evaluate the ecological meaning of PC1, and whether or not it really represents a mineral/organic nutrient gradient, information is needed on which data are used here.

I do not agree with the term 'gradient of bacterial guilds' (i.e., PC1 in Figure 3). All but 1 bacterial 'function' positively loaded on PC1 and 'fermentation' was only weakly negatively correlated with PC1. I do not think this constitutes a 'bacterial gradient'.

(4) Soil samples: Were they collected from the surrounding soil of each tree (L. 341), or from the root zone (L. 110). The former seems to refer to bulk soil samples, but the latter could be interpreted as rhizosphere soils. It is therefore not entirely clear whether these are the same soil samples, and if so, where they were sampled exactly.

Aims:<br /> The authors aimed to integrate endospheric and rhizospheric microbial and fungal community composition in the root economics space. Owing to statistical concerns (i.e., lacking parallel analysis results and the makeup of the PCs (AM versus EcM classification), I am not sure the authors succeeded in this. Besides that, the interpretation of the axes seems rather oversimplified and needs some consideration.

Root N is discussed as an important driver of fungal functional composition. Indeed, it was one of the significant variables in the redundancy models predicting microbial community composition, but its contribution to community composition was small (2 - 3 %), and the mechanistic interpretation was rather speculative. Specifically, the role of root N in root (and tree) functioning remains highly uncertain: the link with respiration and exudation is increasingly demonstrated but its actual meaning for nutrient uptake is not well understood (Freschet et al. 2021. New Phytologist). If and how root economics (represented by root N) and the fungal-driven nutrient economy (EcM versus AM, saprotrophs) can indeed be integrated into a unified framework (L. 223 - 224) seems a relevant question that is worth pursuing based on this paper, but in my opinion, this study does not clearly answer it, because the statistical analyses might need further work (or explanation) and underlying mechanisms are not well explained and supported by evidence.

In addition, the root morphology axis was indeed independent of the "fungal gradient", but this is in itself not an interesting finding. What is interesting, but not discussed is that, generally, AM species are expected to have thicker roots than EcM tree species (Gu et al. 2014 Tree Physiology; Kong et al. 2014 New Phytologist). I am therefore curious to see why this is not the case here? Did the few EcM species sampled just happen to have very thick roots? Or is there a phylogenetic effect that influences both mycorrhizal type and root thickness that is not accounted for here (Baylis, 1975; Guo et al., 2008 New Phytologist; Kubisch et al., 2015 Frontiers in Plant Science; Valverde-Barrantes et al., 2015 Functional Ecology; 2016 Plant and Soil)?

I also do not agree with the conclusion that this integrated framework 'explained' tree distributions along the elevation gradient. First of all, it is difficult to interpret because the elevation gradient is not well explained (e.g., in terms of environmental variation). Secondly, the framework might coincide with the framework, but the framework does not explain it: an environmental gradient probably underlies the elevation gradient that may be selected for species with certain root traits or mycorrhizal types, but this is not tested nor clearly demonstrated by the data. It thus remains rather speculative, and it should be more thoroughly explained based on the data observed. Similarly, I do not understand from this study how root traits like root N can influence the abundance of EcM and pathogenic fungi (L. 242 - 243). Which data show this causality? It seems a strong statement, but not well supported (or explained).

Impact:<br /> The data collected for this study are timely, valuable, and relevant. Soilborne microbes (fungi and bacteria; symbionts and pathogens) play important roles in root trait expressions (e.g., root diameter) and below-ground functioning (e.g., resource acquisition). They should therefore not be excluded from studies into the belowground functioning of forests, but they mostly are. This dataset therefore has the potential to improve our understanding of this subject. Making these data publicly available in large-scale datasets that have recently been initiated (e.g., FRED) will also allow further study in comparative (with other biomes) or global (across biomes) studies.

Technically, the methodology seems sound, although I lack the expertise to judge the Molecular Methods (L. 349 - 397). However, owing to some statistical uncertainties mentioned above (that the authors might well clarify or improve) and the oversimplified discussion, I am hesitant to determine the impact of the contents of this work. Statistical improvements and/or clearer explanation/justification of statistical choices made can make this manuscript highly interesting and impact, however.

Context:<br /> As motivated above, I am not sure to what extent the EcM - AM/saprotroph presents a true ecological tradeoff. However, if it does, this work would fit very well in the context of the mycorrhizal-associated nutrient economy (Phillips et al. 2013 New Phytology). This theory postulates that EcM trees generally produce low-quality litter (associated with 'slow traits') that can be more readily accessed by EcM but not AM fungi, thereby slowing down nutrient cycling rates at their competitive advantage, and vice versa for AM tree species. This study did not aim to test the MANE, so it was beyond its scope to study litter quality, and the number of EcM and AM species was unbalanced (8 EcM versus 44 AM species): nonetheless, the denser roots of EcM species and higher root N of AM species indicates that the MANE may also apply to this subtropical forest and may be an interesting impetus for future work on this topic. It might also offer one way to bridge the root economics space and the MANE.

What I also found interesting is the sparse observations of EcM fungal taxa in the root endosphere of species typically identified as AM hosts (L. 212 - 214). While their functionality remains to be tested (fungal structures in the endosphere were not studied here), this observation might call for renewed attention to classifying species as AM, EcM, or both.

Reviewer #3 (Public Review):

This paper uses behavior and functional brain imaging to understand how neural and cognitive representations of visual and auditory stimuli change as participants learn associations among them. Prior work suggests that areas in the anterior temporal (ATL) and perirhinal cortex play an important role in learning/representing cross-modal associations, but the hypothesis has not been directly tested by evaluating behavior and functional imaging before and after learning cross-modal associations. The results show that such learning changes both the perceived similarities amongst stimuli and the neural responses generated within ATL and perirhinal regions, providing novel support for the view that cross-modal learning leads to a representational change in these regions.

This work has several strengths. It tackles an important question for current theories of object representation in the mind and brain in a novel and quite direct fashion, by studying how these representations change with cross-modal learning. As the authors note, little work has directly assessed representational change in ATL following such learning, despite the widespread view that ATL is critical for such representation. Indeed, such direct assessment poses several methodological challenges, which the authors have met with an ingenious experimental design. The experiment allows the authors to maintain tight control over both the familiarity and the perceived similarities amongst the shapes and sounds that comprise their stimuli so that the observed changes across sessions must reflect learned cross-modal associations among these. I especially appreciated the creation of physical objects that participants can explore and the approach to learning in which shapes and sounds are initially experienced independently and later in an associated fashion. In using multi-echo MRI to resolve signals in ventral ATL, the authors have minimized a key challenge facing much work in this area (namely the poor SNR yielded by standard acquisition sequences in ventral ATL). The use of both univariate and multivariate techniques was well-motivated and helpful in testing the central questions. The manuscript is, for the most part, clearly written, and nicely connects the current work to important questions in two literatures, specifically (1) the hypothesized role of the perirhinal cortex in representing/learning complex conjunctions of features and (2) the tension between purely embodied approaches to semantic representation vs the view that ATL regions encode important amodal/crossmodal structure.

There are some places in the manuscript that would benefit from further explanation and methodological detail. I also had some questions about the results themselves and what they signify about the roles of ATL and the perirhinal cortex in object representation.

A) I found the terms "features" and "objects" to be confusing as used throughout the manuscript, and sometimes inconsistent. I think by "features" the authors mean the shape and sound stimuli in their experiment. I think by "object" the authors usually mean the conjunction of a shape with a sound---for instance, when a shape and sound are simultaneously experienced in the scanner, or when the participant presses a button on the shape and hears the sound. The confusion comes partly because shapes are often described as being composed of features, not features in and of themselves. (The same is sometimes true of sounds). So when reading "features" I kept thinking the paper referred to the elements that went together to comprise a shape. It also comes from ambiguous use of the word object, which might refer to (a) the 3D-printed item that people play with, which is an object, or (b) a visually-presented shape (for instance, the localizer involved comparing an "object" to a "phase-scrambled" stimulus---here I assume "object" refers to an intact visual stimulus and not the joint presentation of visual and auditory items). I think the design, stimuli, and results would be easier for a naive reader to follow if the authors used the terms "unimodal representation" to refer to cases where only visual or auditory input is presented, and "cross-modal" or "conjoint" representation when both are present.

B) There are a few places where I wasn't sure what exactly was done, and where the methods lacked sufficient detail for another scientist to replicate what was done. Specifically:

(1) The behavioral study assessing perceptual similarity between visual and auditory stimuli was unclear. The procedure, stimuli, number of trials, etc, should be explained in sufficient detail in methods to allow replication. The results of the study should also minimally be reported in the supplementary information. Without an understanding of how these studies were carried out, it was very difficult to understand the observed pattern of behavioral change. For instance, I initially thought separate behavioral blocks were carried out for visual versus auditory stimuli, each presented in isolation; however, the effects contrast congruent and incongruent stimuli, which suggests these decisions must have been made for the conjoint presentation of both modalities. I'm still not sure how this worked. Additionally, the manuscript makes a brief mention that similarity judgments were made in the context of "all stimuli," but I didn't understand what that meant. Similarity ratings are hugely sensitive to the contrast set with which items appear, so clarity on these points is pretty important. A strength of the design is the contention that shape and sound stimuli were psychophysically matched, so it is important to show the reader how this was done and what the results were.

(2) The experiences through which participants learned/experienced the shapes and sounds were unclear. The methods mention that they had one minute to explore/palpate each shape and that these experiences were interleaved with other tasks, but it is not clear what the other tasks were, how many such exploration experiences occurred, or how long the total learning time was. The manuscript also mentions that participants learn the shape-sound associations with 100% accuracy but it isn't clear how that was assessed. These details are important partly b/c it seems like very minimal experience to change neural representations in the cortex.

(3) I didn't understand the similarity metric used in the multivariate imaging analyses. The manuscript mentions Z-scored Pearson's r, but I didn't know if this meant (a) many Pearson coefficients were computed and these were then Z-scored, so that 0 indicates a value equal to the mean Pearson correlation and 1 is equal to the standard deviation of the correlations, or (b) whether a Fisher Z transform was applied to each r (so that 0 means r was also around 0). From the interpretation of some results, I think the latter is the approach taken, but in general, it would be helpful to see, in Methods or Supplementary information, exactly how similarity scores were computed, and why that approach was adopted. This is particularly important since it is hard to understand the direction of some key effects.

C) From Figure 3D, the temporal pole mask appears to exclude the anterior fusiform cortex (or the ventral surface of the ATL generally). If so, this is a shame, since that appears to be the locus most important to cross-modal integration in the "hub and spokes" model of semantic representation in the brain. The observation in the paper that the perirhinal cortex seems initially biased toward visual structure while more superior ATL is biased toward auditory structure appears generally consistent with the "graded hub" view expressed, for instance, in our group's 2017 review paper (Lambon Ralph et al., Nature Reviews Neuroscience). The balance of visual- versus auditory-sensitivity in that work appears balanced in the anterior fusiform, just a little lateral to the anterior perirhinal cortex. It would be helpful to know if the same pattern is observed for this area specifically in the current dataset.

D) While most effects seem robust from the information presented, I'm not so sure about the analysis of the perirhinal cortex shown in Figure 5. This compares (I think) the neural similarity evoked by a unimodal stimulus ("feature") to that evoked by the same stimulus when paired with its congruent stimulus in the other modality ("object"). These similarities show an interaction with modality prior to cross-modal association, but no interaction afterward, leading the authors to suggest that the perirhinal cortex has become less biased toward visual structure following learning. But the plots in Figures 4a and b are shown against different scales on the y-axes, obscuring the fact that all of the similarities are smaller in the after-learning comparison. Since the perirhinal interaction was already the smallest effect in the pre-learning analysis, it isn't really surprising that it drops below significance when all the effects diminish in the second comparison. A more rigorous test would assess the reliability of the interaction of comparison (pre- or post-learning) with modality. The possibility that perirhinal representations become less "visual" following cross-modal learning is potentially important so a post hoc contrast of that kind would be helpful.

E) Is there a reason the authors did not look at representation and change in the hippocampus? As a rapid-learning, widely-connected feature-binding mechanism, and given the fairly minimal amount of learning experience, it seems like the hippocampus would be a key area of potential import for the cross-modal association. It also looks as though the hippocampus is implicated in the localizer scan (Figure 3c).

F) The direction of the neural effects was difficult to track and understand. I think the key observation is that TP and PRh both show changes related to cross-modal congruency - but still it would be helpful if the authors could articulate, perhaps via a schematic illustration, how they think representations in each key area are changing with the cross-modal association. Why does the temporal pole come to activate *less* for congruent than incongruent stimuli (Figure 3)? And why do TP responses grow less similar to one another for congruent relative to incongruent stimuli after learning (Figure 4)? Why are incongruent stimulus similarities *anticorrelated* in their perirhinal responses following cross-modal learning (Figure 6)?

This work represents a key step in our advancing understanding of object representations in the brain. The experimental design provides a useful template for studying neural change related to the cross-modal association that may prove useful to others in the field. Given the broad variety of open questions and potential alternative analyses, an open dataset from this study would also likely be a considerable contribution to the field.

Reviewer #3 (Public Review):

D-type retroviruses, which include M-PMV assemble in the cytosol, however, do not efficiently start their maturation before membrane binding. There is very little known about the structural changes leading to maturation of D-type retroviruses and this manuscript presents compelling structural changes of the M-PMV matrix domain in mutations abrogating the myristol exposure or mutation which reasonably argue that myristol group is exposed (The relationship between these mutants and myristol exposure is argued based on structure of the matrix and liposome binding, however is not directly shown in structure). Assuming that the authors are correct about their mutations affect on myristol exposure, they have measured very interesting M-PMV matrix domain conformational changes which exposes the MAPP site to the protease.

Oligomerization of the matrix is probed by formation of disulfide bridges in a matrix mutant on liposomes with engineered cystine where authors suspect monomers of the matrix would be touching each other. The oligomerization data is very weak, does not directly support trimer formation and since 2D diffusion on liposomes would increase matrix-matrix interactions, can be non-specific, a point supported by presence of a stronger dimer band than trimer and tetramer. The main issue with the manuscript is that the authors do not show any evidence that the proposed mechanism actually works in the context of full M-PMV assembled particles.

Reviewer #3 (Public Review):

The study by Li et al investigates the role of type I interferon in suppressing ADAM17-mediated release of EGFR, the pathway previously implicated by this group in photosensitive skin reactions. Understanding the relevance of lupus murine models to the human disease is very important and the studies address this important gap in the knowledge. The most significant findings are: 1) the same high IFN and low Langerhans cell (LC) signatures seen in a lupus patient's skin, exist in the non-lesional skin of lupus mouse models; 2) IFN-Is and IFN-I signaling suppress ADAM17 activity in LCs in vitro and in vivo; 3) Blocking IFN-I signaling ameliorates photosensitive reactions, in an EGFR-dependent manner. These three conclusions are largely supported by the presented evidence but could be distilled as well as strengthened by additional data.

One of the strengths of the study is that the authors defined the relevance of lupus skin mouse models to human disease in the context of the Interferon-LC axis. The extensive computational approaches represent useful tools to compare cellular and molecular signatures across samples as well as species. This is highly relevant to the studies of lupus, a highly complex disease, for which the relevance of murine models has remained undefined. Major strengths related to the Aims of the study are that the authors established a role of interferon in suppressing Adam17 activity in the skin and showed that blocking interferon can reduce sunlight-induced skin inflammation in the lupus murine models. Interestingly, the authors observed that blocking IFN signaling in the absence of a high IFN-signature worsened sunlight-induced skin injury. The specificity of Adam17 in LCs for TNFR1 shedding provides an elegant approach to probing Adam17 activity in these cells.

While the three conclusions stated above are largely supported by the presented evidence, the data supporting a direct role of ADAM17 in IFN-triggered photosensitive reactions could be strengthened. Some of the concerns are outlined below:<br /> (1) Computational analyses in Figures 1 and 2 emphasize the co-occurrence of a high IFN-I signature and a low LC and/or DC signatures. It is not clear if the downregulation of the DC gene set indicates diminished presence of LCs in the non-lesional skin of the lupus mouse models or "reflects decreased LC function" as the authors suggest.

(2) Given the hypothesis that IFN-I may be the cause of a decreased DC signature in the mouse skin, it would be relevant to ask if this signature is also decreased in the IMQ model, which is a known model of IFN-induction as confirmed by the authors. Likewise, asking how anti-IFNAR treatment affects the DC signature / LC numbers would be important, in the absence and presence of UV. The authors indicate in Fig. 5I that IMQ reduces LC numbers.

(3) Decreased inflammation in LCad17 mice in the IMQ+UV model is unexpected. Previous studies by this group showed increased UV-induced inflammation in the absence of LC-ADAM17 (Shipman et al 2018). Therefore, it is not surprising that anti-IFNAR did not have an impact in these mice as ADAM17 deficiency appears to have normalized the response. These results are not addressed in the context of the previously published findings.

(4) Including the data that demonstrate the specificity of LCs for Adam17 expression in the epidermis and shedding of TNFR1 as a readout of LC-ADAM17-specific activity in the main figures would be important.

(5) UV light is an important inducer of IFN. Authors have previously shown that UV also induces Adam17 expression. Therefore, the question remains whether a high baseline IFN signature in lupus skin suppresses UV-induced Adam17 expression?

(6) A direct mechanistic link between high IFN-I and loss of Adam17 activity driving photosensitive reactions could be strengthened. Would blocking Adam17 with a blocking antibody suppress photosensitive reactions in lupus mouse models? Would treating LCAd17 mice with IFN fail to enhance or diminish UV-induced inflammation?

Reviewer #3 (Public Review):

This study used novel ingestible pills to measure pH and other gastric signals, and related these measures to self-report ratings of emotions induced by video clips. The main finding was that when participants viewed videos of disgust, there was an association between gastric pH and feelings of disgust and fear, and (in the opposite direction) happiness. These findings may be the first to relate objective measures of gastric physiology to emotional experience. The methods open up many new questions that can be addressed by future studies and are thus likely to have an impact on the field.

My main concern is with the reliability of the results. The study associates many measures (pH, temperature, pressure, EGG) in stomach, small bowel, and large bowel with multiple emotion ratings. This amounts to many statistical tests. Only one of these measures (pH in the stomach) shows a significant effect. Furthermore, the key findings, as displayed in Figure 4 do not look particularly convincing. Perhaps this is a display issue, but the relations between stomach pH and Vas ratings of disgust, fear, and happiness were not apparent from the scatter plot and may be influenced by outliers (e.g., happiness).

Reviewer #3 (Public Review):

In this manuscript, the authors seek to shed light on the role of awake hippocampal replay during memory tasks that are claimed to be short-term memory. For this, they make use of a real-time detection and disruption system of awake hippocampal ripples, which are used as a proxy for awake neuronal replay. The manuscript describes extensively the tasks as well as the disruption system and controls used during the experiments. The authors present numerous and solid analyses of the behavioral data acquired during the tasks. Nonetheless, the current version of the manuscript is lacking a more complete discussion in which the results are contrasted to previous similar findings, as well as mentioning the role of the awake ripple in the stabilization of hippocampal maps. Some extra analyses are also suggested below. The manuscript would also be enriched if the authors suggested alternative mechanisms for memory rehearsal. Finally, some claims of "we are first" seem inappropriate when compared to the previous literature.

Major comments:

How does one define short-term memory (STM) in rodents? The examples and papers cited in the first paragraphs refer mostly to human working memory tasks, from which it is known that a non-rehearsed STM lasts typically 20-30 seconds. Could the authors mention how this concept is translated to rodents? Could you clarify until what point memory is considered STM and what is the criteria to consider it has turned into long-term memory or when is it simply working memory or habit/skill? Further, why should these tasks be classified as testing STM while Jadhav et al. tasks are working memory or as they now mention in this article rule learning? In humans, the retention of memory after a certain time is achieved by retrieving a long-term memory. How do we know if the considerable training the rats received has not allowed the use of a long-term memory strategy which allows the rats to perform well even in the absence of rehearsal (replay)? These are conceptual explanations that would help understand the key concept of STM in greater detail.

Further, claims of "first" should be adjusted, since I do not see a large difference between the w (m) maze of Jadhav and these tasks. The main difference between the two projects would rather be that Jadhav tests when animals are still newer to the task while here overtrained animals are used. In Jadhav, it's unlikely that just rule learning is affected since the inbound component is not affected by disruption, which also tests rule learning. Therefore, it is still likely that the effect seen in Jadhav et al is a deficit in working memory/short-term memory. And here it is more likely, that no effect was seen since with overtrained animals other strategies (cortical, striatal, etc) were used. The authors should compare in more detail how overtrained animals were in these different projects as well as in the articles they cite for replay analysis.

The main conclusion of the authors is that hippocampal replay is not the rehearsal mechanism expected in STM given that its disruption doesn't lead to behavioral changes. Could the authors hypothesize in their discussion what other neural mechanisms different from hippocampal replay may be involved in this rehearsal? The discussion also lacks closure with respect to how the findings fit in the study of STM in human memory. This would make the article more interesting to a larger audience and highlight its translational aspect.

The results describe deeply the behavioral performance of the rats and the validation of the ripple detection/disruption system. However, one important aspect missing is how the hippocampal activity and its encoding of space may be affected by the awake ripple disruption. The authors don't cite the work by Roux et al., Nature Neuroscience. 2017 where optogenetic stimulation of hippocampal neurons provided evidence that neuronal activity associated with awake hippocampal ripples during goal-directed behavior is required for both stabilizing and refining hippocampal place fields, while memory performance was not affected during ripple-locked stimulations compared to a ripple-delayed stimulation control (See supplementary Figure 7 of the mentioned article). I would like the authors to comment on their own findings and contrast them with those of Roux et al.

Line 64: Could the authors clarify what they mean by "indirect" causal evidence when discussing the contribution of papers by Jadhav, Igata, and Fernandez? Is it the fact that rodents' learning speed changed instead of showing a complete absence of learning? Or is it the fact that the disruption/prolongation is done on the hippocampal ripple and not strictly in the replay sequence? I would also highlight this latter difference, given that the above-mentioned authors describe their methodological approaches in terms of ripples and not in terms of replay content. For example, the use of "replay" instead of "ripple" in Line 61 results in methodological inaccurate terms such as replay disruption and replay prolongation.

Despite its apparent lack of statistical significance, the reported mean ripple detection rate during the trial and non-trial periods tend to be always higher in the disruption condition of all tasks by observing the median of the boxplots in Figure 1J, Figure 2H, and Figure 3J. It is worth investigating this further using the same linear regression method as Girardeau et al. Journal of Neuroscience, 2014 which may reduce the variability and allow comparing slopes of a cumulative number of ripples over time. This may reveal a compensatory homeostatic-like increase in the rate of ripples during the disrupted sessions, which may suggest a need for the ripple/replay occurrence in spite of it not having an effect on the rats' performance during the task.

In line 425, the authors report a median relative delay of 52.9 of their disruption system. Such a value would indicate that only around 47% of the ripple is being blocked. Is there any data from the authors or others that could reassure the reader that the 52.9% of the ripple that "leaks" is not enough for the replay phenomenon to occur? Considering the findings of Fernandez-Ruiz et al. 2019 on large-duration ripples, could the authors report the relative delay for both short and long ripples (>100 ms) separately? Line 494: The authors define long ripples as (>120 ms) but this doesn't coincide with the 100ms threshold from Fernandez Ruiz et al. 2019.

The online ripple detector used filtered the traces in the 135-255 Hz range. This is a narrower frequency range compared to online detectors used by Jadhav et al. 2012 (100-400 Hz) and Fernandez-Ruiz et al. 2019 (80-300 Hz). What motivated the use of this narrow range? Would the omittance of ripples below 135 Hz have implications in the results? Could the authors add to the supplement a figure similar to Figure 4B (FDR vs TPR) using a wider frequency range similar to the authors above in the offline detection of ripples?

It is unclear what criterion was used to train the rats in the NMTS task. Line 216 specifies a learning criterion of 80% fully correct trials in one session for three days in a row, while the methods in line 852 mention an average performance below 50% for at least three days in a row.

In the methods section, it is not mentioned if there was a specific region in the cortex where the tetrode was placed (Line 908). The detections in this tetrode were used to mark events as "false positives". The authors should be careful in line 933 when they make the statement "ripples are not present in the cortex". There have been recent publications that challenge this affirmation. See Khodagholy, Science. 2017, Nitzan, Nature Comm. 2020.

Reviewer #3 (Public Review):

This is a potentially quite interesting paper that defines E2 and E3 genes in Drosophila that can impact the accumulation of the Q72-GFP protein in the fly eye. The authors then focus on the eff gene, showing which human homolog can rescue fly knockdown. They extend to skeletal muscle, from the htt protein, to show that eff by TMT mass spec decreases with age normally in the fly muscle and that there is a significant overlap of proteins that are disrupted with eff knockdown in young animals in muscle vs aged animals normally in muscle.

Overall these data suggest eff decrease with age may contribute to the increase in ubiquitinated proteins in muscle with age, and that upregulation of eff activity might be of interest to extending lifespan. Because eff function can be performed by a human homologue, the findings may also apply to human situations of aging.

These data are overall interesting and are of relevance for those interested in neurodegenerative disease and aging, although a number of points from the figures seem confusing and need more explanation or clarity.

Reviewer #3 (Public Review):

Summary: The paper aims at providing a neurocomputational account on how social perception translates in prosocial behaviors. Participants first completed a novel social perception task during fMRI scanning, in which were asked to judge the merit or need of people depicted in different situations. Second , a separate altruistic choice task was used to examine how the perception of merit and need influences the weights people place on themselves, others and fairness when deciding to provide help. Finally, a link between perception and action was drawn in those participants who completed both tasks.

Strengths: The paper is overall very well written and presented, leaving the reader at ease when describing complex methods and results. The approach used by the author is very compelling, as it combines computational modeling of behavior and neuroimaging data analyses. Despite not being able to comment on the computational model, I find the approach used (to disentangle sensitivity and biases, for merit and need) very well described and derived from previous theoretical work. Results are also clearly described and interpreted.

Weaknesses: in the social perception task, merit and need are evaluated by means of very different cues that rely on different cognitive processes (more abstract thinking for merit than need). Despite this limitation of the task, the authors were able to argue convincingly in the revised version about the solidity of their findings. Sample size is quite small for study 2, nevertheless the results provide convincing evidence.

Reviewer #3 (Public Review):

Summary:

Amacrine cells are a heterogeneous collection of retinal interneurons. Most are inhibitory, and like inhibitory neurons in other neural circuits, strongly shape retinal function. With a few exceptions, the role of amacrine cells in retinal signaling is poorly understood. This paper introduces an approach to study a set of wide-field amacrine cells that extend processes over large regions of the retina.

Strengths:

A substantial strength of the paper is the combination of genetic manipulations, electrophysiology, optogenetics and electron microscopy used to study these cells. As a result of that broad set of techniques, the results cover many properties of how the cells work and provide a nice overview. The paper is also (with a few exceptions below) clearly presented and the experiments look to be carefully executed with clean results.

Weaknesses:

My largest concern with the paper is that overall the results provided an initial view of an interesting set of issues about the function of these cells, but the interesting initial results are not pursued in more depth.

Spatial spread of signals in neurites<br /> An immediate question about axonless WACs is the extent of spread of signals along their processes, and hence whether they act as a collection of independent or semi-independent elements. This bears directly on interpretation of the responses to oriented stimuli for example. Did you do any experiments that might provide additional information about this issue? For example, if you stimulate one of the WACs peripherally do you see a strong modulation of the somatic voltage? Or in the imaging experiments, if you mask a region of the processes so that it is not receiving a stimulus, do you see responses "leak" into that occluded region from surrounding stimulated regions?

Orientation tuning and connectivity<br /> The most developed functional results in the paper relate to the sensitivity of the WAC processes to oriented stimuli. Interpretation of these results depends on a few factors. First is the spread of signals in the WAC processes - as noted above. Second is connectivity. The paper shows that the B/K WAC activity increases inhibitory input to Off-delta and On-alpha ganglion cells. These cells, as noted in the paper, are not orientation tuned. But the orientation tuned ganglion cells stratify in a similar location within the IPL, and hence are situated in an appropriate place to receive input from the B/K WACs. Did you focus exclusively on connections to the Off-delta and On-alpha cells (along with the Off-alpha) or did you look at any other ganglion cell types? This should at least get discussed in more detail.

In several places it is unclear whether the paper intends to be a methods paper or a basic research paper. One example is the last sentence of the abstract. If it is intended to be a basic research paper (which is my overall impression) then I suggest shifting the emphasis in some of those key locations towards results and away from methods.

Reviewer #3 (Public Review):

Summary:<br /> In the current work, Howell et al studied the connectivity between the cortex and thalamus using DTI tractorgraphy per parcel to all voxels in the thalamus. Following they performed various dimensional reduction techniques to uncover how differences in connectivity to the thalamus vary across cortical parcels. Following they explore the spatial correlation of these variations with cortical myelin and functional organization, thalamic nuclei, gene expression derived core-matrix cell differentiation, and extend the model towards macaques. Overall, the authors find a differentiation between sensory and association areas in terms of the association with the thalamus, which reflects differences in cortical microstructure and function, and links to core-matrix differences and can be replicated in macaques.

Strengths:<br /> A clear strength of the current work is the combination of different models and approaches to study the link between the cortex and the thalamus. This approach nicely bridges different approaches to describe the role of the thalamus in cortical organisation using a diffusion-based approach. Especially the extension of the model to the macaque is quite nice.

Weaknesses:<br /> Potential weaknesses of the study are that it seems to largely integrate aspects of the thalamus that have been already described before. The differentiation between sensory and association systems across thalamic subregions is something that has been described before (see: Oldham and Ball, 2023; Zheng et al., 2023; Yang et al., 2020 Mueller, 2020; Behrens, 2003).

Appraisal:<br /> However, the aim of the study: 'to investigate the spatial extent of anatomical connectivity patterns within the thalamus in both humans and non-human primates and determine if such patterns differ between sensorimotor and association cortical areas' has been met.

Discussion:<br /> Overall, I think the study is a nice addition to the growing literature studying the anatomical connectivity between the thalamus and cortex and its functional implications.

Reviewer #3 (Public Review):

Summary:<br /> The authors proposed a normative principle for how the brain's internal estimate of an observed sensory variable should be updated during each individual observation. In particular, they propose that the update size should be inversely proportional to the variance of the variable. They then proposed a microcircuit model of how such an update can be implemented, in particularly incorporating two types of interneurons and their subtractive and divisive inhibition onto pyramidal neurons. One type should represent the estimated mean while another represents the estimated variance. The authors used simulations to show that the model works as expected.

Strengths:<br /> The paper addresses two important issues: how uncertainty is represented and used in the brain, and the role of inhibitory neurons in neural computation. The proposed circuit and learning rules are simple enough to be plausible. They also work well for the designated purposes. The paper is also well-written and easy to follow.

Weaknesses:<br /> I have concerns with two aspects of this work.

(1) The optimality analysis leading to Eq (1) appears simplistic. The learning setting the authors describe (estimating the mean of a stationary Gaussian variable from a stream of observations) is a very basic problem in online learning/streaming algorithm literature. In this setting, the real "optimal" estimate is simply the arithmetic average of all samples seen so far. This can be implemented in an online manner with \hat{\mu}_{t} = \hat{\mu}_{t-1} +(s_t-\hat{\mu}_{t-1})/t. This is optimal in the sense that the estimator is always the maximum likelihood estimator given the samples seen up to time t. On the other hand, doing gradient descent only converges towards the MLE estimator after a large number of updates. Another critique is that while Eq (1) assumes an estimator of the mean (\hat{mu}), it assumes that the variance is already known. However, in the actual model, the variance also needs to be estimated, and a more sophisticated analysis thus needs to take into account the uncertainty of the variance estimate and so on. Finally, the idea that the update should be inverse to the variance is connected to the well-established idea in neuroscience that more evidence should be integrated over when uncertainty is high. For example, in models of two-alternative forced choices it is known to be optimal to have a longer reaction time when the evidence is noisier.

(2) While the incorporation of different inhibitory cell types into the model is appreciated, it appears to me that the computation performed by the circuit is not novel. Essentially the model implements a running average of the mean and a running average of the variance, and gates updates to the mean with the inverse variance estimate. I am not sure about how much new insight the proposed model adds to our understanding of cortical microcircuits.

Reviewer #3 (Public Review):

Summary:

Heer and Sheffield provide a well-written manuscript that clearly articulates the theoretical motivation to investigate specific catecholaminergic projections to dorsal CA1 of the hippocampus during a reward-based behavior. Using 2-photon calcium imaging in two groups of cre transgenic mice, the authors examine the activity of VTA-CA1 dopamine and LC-CA1 noradrenergic axons during reward seeking in a linear track virtual reality (VR) task. The authors provide a descriptive account of VTA and LC activities during walking, approach to reward, and environment change. Their results demonstrate LC-CA1 axons are activated by walking onset, modulated by walking velocity, and heighten their activity during environment change. In contrast, VTA-CA1 axons were most activated during the approach to reward locations. Together the authors provide a functional dissociation between these catecholamine projections to CA1. A major strength of their approach is the methodological rigor of 2-photon recording, data processing, and analysis approaches. These important systems neuroscience studies provide solid evidence that will contribute to the broader field of learning and memory. The conclusions of this manuscript are mostly well supported by the data, but some additional analysis and/or experiments may be required to fully support the author's conclusions.

Weaknesses:

(1) During teleportation between familiar to novel environments the authors report a decrease in the freezing ratio when combining the mice in the two experimental groups (Figure 3aiii). A major conclusion from the manuscript is the difference in VTA and LC activity following environment change, given VTA and LC activity were recorded in separate groups of mice, did the authors observe a similar significant reduction in freezing ratio when analyzing the behavior in LC and VTA groups separately?

(2) The authors satisfactorily apply control analyses to account for the unequal axon numbers recorded in the LC and VTA groups (e.g. Figure 1). However, given the heterogeneity of responses observed in Figures 3c, 4b and the relatively low number of VTA axons recorded (compared to LC), there are some possible limitations to the author's conclusions. A conclusion that LC-CA1 axons, as a general principle, heighten their activity during novel environment presentation, would require this activity profile to be observed in some of the axons recorded in most all LC-CA1 mice. Additionally, if the general conclusion is that VTA-CA1 axons ramp activity during the approach to reward, it would be expected that this activity profile was recorded in the axons of most all VTA-CA1 mice. Can the authors include an analysis to demonstrate that each LC-CA1 mouse contained axons that were activated during novel environments and that each VTA-CA1 mouse contained axons that ramped during the approach to reward?

(3) A primary claim is that LC axons projecting to CA1 become activated during novel VR environment presentation. However, the experimental design did not control for the presentation of a familiar environment. As I understand, the presentation order of environments was always familiar, then novel. For this reason, it is unknown whether LC axons are responding to novel environments or environmental change. Did the authors re-present the familiar environment after the novel environment while recording LC-CA1 activity?

Reviewer #3 (Public Review):

Summary:<br /> In the manuscript titled "Large pan-cancer cell screen coupled to (phospho-)proteomics underscores high-dose vitamin C (VitC) as a potent anti-cancer agent," the authors use a combination of proteomics and cell viability assays to understand the effect of Vitamin C on different solid tumor models in 51 different cancer cell lines. They found that many cancer cell lines are sensitive to high-dose Vitamin C, with IC50 values in the micromolar to millimolar range. Given that Vitamin C, when administered intravenously, can reach 20mM, this suggests that Vitamin C could provide some benefits to patients. The authors also generate and analyze bulk proteomic data for all 51 cell lines. They perform statistical analysis of these data to identify proteins that are up or downregulated in sensitive vs resistant cell lines in the same tumor and commonly across tumors. They then focus on PDAC cell lines and measure bulk and phosphoproteomics of PDAC cell lines 2, 4 and 24 hours after Vitamin C treatment.

Strengths: The strengths of the study are the rather large datasets accumulated on bulk proteomics of 51 different cancer cell lines. The IC50 values of these cell lines in response to Vitamin C is also useful.

Weaknesses:<br /> Though identifying targets to sensitize cancer cells to Vitamin C treatment is interesting, I felt the manuscript delved too much into listing off genes they found, with speculation on why the particular protein would be enriched in sensitive or resistant cell lines without testing any key claims experimentally.

Major Issues

(1) The overall premise of the study is that proteins that are enriched in Vitamin C-sensitive cell lines point to mechanisms of sensitivity and those enriched in Vitamin C resistant lines underlie mechanisms of resistance. Yet this is never directly tested. To show that the authors would need to knockdown/knockout a gene enriched in resistant lines and show this sensitizes cells to Vitamin C treatment or overexpress a protein associated with resistance and show that this leads to resistance in an otherwise sensitive cell line.

(2) One of the key strengths of this study is the large datasets generated, namely the proteomics data for 51 different cell lines. Yet the data is not included as a supplement or uploaded to a public repository.

Reviewer #3 (Public Review):

Summary:<br /> In this study, Brenes and colleagues carried out proteomic analysis of several human induced pluripotent (hiPSC) and human embryonic stem cell (hESC) lines. The authors found quantitative differences in the expression of several groups of cytoplasmic and mitochondrial proteins. Overall, hiPSC expressed higher levels of proteins such as glutamine transporters, mitochondrial metabolism proteins, and proteins related to lipid synthesis. Based on the protein expression differences, the authors propose that hiPSC lines differ from hESC in their growth and metabolism.

Strengths:<br /> The number of generated hiPSC and hESC lines continues to grow, but potential differences between hiPSC and hESC lines remain to be quantified and explained. This study is a promising step forward in understanding of the differences between different hiPSC and hESC lines.

Weaknesses:<br /> It is unclear whether changes in protein levels relate to any phenotypic features of cell lines used. For example, the authors highlight that increased protein expression in hiPSC lines is consistent with the requirement to sustain high growth rates, but there is no data to demonstrate whether hiPSC lines used indeed have higher growth rates.

The authors claim that the cell cycle of the lines is unchanged. However, no details of the method for assessing the cell cycle were included so it is difficult to appreciate if this assessment was appropriately carried out and controlled for.

Details and characterisation of iPSC and ESC lines used in this study were overall lacking. The lines used are merely listed in methods, but no references are included for published lines, how lines were obtained, what passage they were used at, their karyotype status, etc. For details of basic characterisation, the authors should refer to the ISSC Standards for the use of human stem cells in research. In particular, the authors should consider whether any of the changes they see may be attributed to copy number variants in different lines.

The expression data for markers of undifferentiated state in Figure 1a would ideally be shown by immunocytochemistry or flow cytometry as it is impossible to tell whether cultures are heterogeneous for marker expression.

TEM analysis should ideally be quantified.

All figure legends should explicitly state what graphs are representing (e.g. average/mean; how many replicates (biological or technical), which lines)? Some data is included in Methods (e.g. glutamine uptake), but not for all of the data (e.g. TEM).

Validation experiments were performed typically on one or two cell lines, but the lines used were not consistent (e.g. wibj_2 versus H1 for respirometry and wibj_2, oaqd_3 versus SA121 and SA181 for glutamine uptake). Can the authors explain how the lines were chosen?

The authors should acknowledge the need for further functional validation of the results related to immunosuppressive proteins.

Differences in H1 histone abundance were highlighted. Can the authors speculate as to the meaning of these differences?

Reviewer #3 (Public Review):

This reviewer appreciates the responses to previous notes. The authors attempted to address concerns mostly in writing, avoiding performing some of the experiments suggested in my previous review. Although some of the points were clarified, and the revised manuscript presents valuable insights into the implications of YBR238C and RMD9 on cellular function and yeast aging, my major concern still needs to be addressed. The gene expression signature significantly changes under different metabolic conditions. The media condition under which samples are collected for RNAseq analyses should match the media condition under which the lifespans of those KO strains are tested. This is the major confounding effect, and the conclusions are not informative based on the analysis done in this study.

To avoid experiments, the authors responded that yeast culture results in low optical density and does not reach the stationary phase under rapamycin treatment conditions; however, the simple solution is to grow the yeast cells until they reach the stationary phase and then rapamycin treatment can be done for certain hours - collect the cells for transcriptomics analysis then it can be compared to the CLS gene set.

Another example is chromosome copy number alteration, which can be easily analyzed using transcriptome data, and it is an important aspect to understand whether observed expression changes are also affected by this alteration in YBR238C KO cells. However, the authors ignore this important point as well.

After all, this is an interesting study "limited by subfield" and will be of general interest in the yeast aging field, again considering the lack of homology of the genes of interest in higher eukaryotes.

Reviewer #3 (Public Review):

Summary:<br /> Kobayashi et al identify MER21C as a common promoter of GPR1-AS/Liz in Euarchontoglires, which establishes a somatic DMR that controls ZFDB2 imprinting. In mice, MER21C appears to have diverged significantly from its primate counterparts and is no longer annotated as such.

Strengths:<br /> The authors used high-quality cross-species RNA-seq data to characterise GPR1-AS-like transcripts, which included generating new data in five different species. The association between MER21C/B elements and the promoter of GPR1-AS in most species is clear and convincing. The expression pattern of MER21C/B elements overall further supports their role in enabling correct temporal expression of GPR1-AS during embryonic development.

Weaknesses:<br /> A deeper comparison of syntenic regions to the GPR1-AS promoter could be performed to provide a clearer picture of how the MER21C/B element evolved. The use of alternative TE annotation software may also be helpful. These analyses would be particularly useful to drive home the conclusion that the mouse (Liz) promoter is derived from the same insertion.

Reviewer #3 (Public Review):

Summary:<br /> The authors use several quantitative approaches to characterize the feeding ecologies of bohaiornithid enantiornithines, including allometric data, mechanical advantage and finite element analyses of the jaw, and morphometric analyses of the claws. The authors combine their results with data for other enantiornithines collected from the literature to shed new insight on the ecological evolution of Enantiornithes as a clade.

Although the authors have taken steps to improve their paper, I generally find improvements unsatisfying, especially regarding my comments.

My remaining concerns:

Teeth: My concern here is not whether having teeth limits available niche space compared to having a keratinous beak. Rather, my concern regards how exploitation of the same niche space might be differently reflected in parameter space between birds with teeth and birds with beaks. Can we reliably expect two species that both eat seeds to occupy the same parameter space if, for example, distribution of stress/strain is across a series of teeth vs. across a more uniform beak? In this manuscript, the authors are clearly making this assumption, but that assumption is not made explicit, let alone justified. The authors should discuss this.

Cranial kinesis: As with teeth, my concern here regards our ability to compare data between birds with and without a flexible beak to mitigate forces when foraging. I appreciate that the functional complexity of the kinetic neognath skull precludes our ability to account for it in analyses such as these, but when comparisons are made using these analyses *specifically among neognaths*, we can reliably assume that we are comparing like to like - that is, we can assume that both have kinetic skulls, and so kinesis is reflected similarly in the data for each bird. Similarly, even if a comparison between two neognaths focuses exclusively on the mandible - in which cranial kinesis is not directly reflected - we can assume that those mandibles serve as comparisons between functionally similar systems. However, we cannot necessarily make those same assumptions when comparing the kinetic skull of a neognath to the akinetic skull of an enantiornithine. Indeed, even when focusing just on the mandible, can we reliably assume that data collected from an akinetic enantiornithine reflect the same comparative context as data collected from kinetic neognaths? I appreciate that the authors added a call for better functional understanding of bird cranial kinesis - a call I enthusiastically endorse - but the authors should still discuss how that current lack of understanding impacts interpretations of the comparisons they draw.

Finally, I still find the discussion to be overly long and lacking clear focus and organization. I again urge the authors to minimally consider adding subheadings to better allow the reader to follow the flow of ideas, and I second Reviewer #1's suggestion to add a "Conclusions" section.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Coberski et al describes a combined experimental and computational study aimed to shed light on the catalytic mechanism in a methyltransferase that transfers a methyl group from S-adenosylmethionine (SAM) to a substrate adenosine to form N6-methyladenosine (m6A).

Strengths:<br /> The authors determine crystal structures in complex with so-called bi-substrate analogs that can bridge across the SAM and adenosine binding sites and mimic a transition state or intermediate of the methyl-transfer reaction. The crystal structures suggest dynamical motions of the substrate(s) that are examined further using classical MD simulations. The authors then use QM/MM calculations to study the methyl-transfer process. Together with biochemical assays of ligand/substrate binding and enzyme turnover, the authors use this information to suggest what the key steps are in the catalytic cycle. The manuscript is in most places easy to read.

Weaknesses:<br /> After revising the manuscript, there are few weaknesses beyond those listed in the paper.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors use inhibitors and mimetics of juvenile hormone (JH) to demonstrate that JH has a key role in late embryonic development in Thermobia, specifically in gut and eye development but also resorption of the extraembryonic fluid and hatching. They then exogenously apply JH early in development (when it is not normally present) to examine the biological effects of JH at these stages. This causes a plethora of defects including developmental arrest, deposition of chitin, limb development, and enhanced muscle differentiation. The authors interpret these early effects on development as JH being important for the shift from morphogenetic growth to differentiation - a role that they speculate may have facilitated the evolution of metamorphosis (hemi- and holo-metaboly). This paper will be of interest to insect evo-devo researchers, particularly those with interests in the evolution of metamorphosis.

Strengths:

The experiments are generally conducted very well with appropriate controls and the authors have included a very detailed analysis of the phenotypes.<br /> The manuscript significantly advances our understanding of Thermobia development and the role of JH in Thermobia development.<br /> The authors interpret this data to present some hypotheses regarding the role of JH in the evolution of metamorphosis, some aspects of which can be addressed by future studies.

Weaknesses:

The results are based on using inhibitors and mimetics of JH and there was no attempt to discern immediate effects of JH from downstream effects. The authors show, for instance, that the transcription of myoglianin is responsive to JH levels, it would have been interesting to see if any of the phenotypic effects are due to myoglianin upregulation/suppression (using RNAi for example). These kinds of experiments will be necessary to fully work out if and how the JH regulatory network has been co-opted into metamorphosis.

The results generally support the authors' conclusions. However, the discussion contains a lot of speculation and some far-reaching conclusions are made about the role of JH and how it became co-opted into controlling metamorphosis. There are some interesting hypotheses presented and the author's speculations are consistent with the data presented. However, it is difficult to make evolutionary inferences from a single data point as although Thermobia is a basally branching insect, the lineage giving rise to Thermobia diverged from the lineages giving rise to the holo- and hemimetabolous insects approx.. 400 mya and it is possible that the effects of JH seen in Thermobia reflect lineage-specific effects rather than the 'ancestral state'. The authors ignore the possibility that there has been substantial rewiring of the networks that are JH responsive across these 400 my. I would encourage the authors to temper some of the discussion of these hypotheses and include some of the limitations of their inferences regarding the role of JH in the evolution of metamorphosis in their discussion.