One of the things to optimize sleep is to take care of meal timing. Author eats: - Breakfast at 8 - Lunch at noon (12) - Dinner between 5 and 6.30

Discipline and consistency is important here.

Essential is to eat dinner 3+ hours before you go to sleep.

Food increases core body temperature which negatively impacts sleep.

Reviewer #1 (Public Review):

This manuscript addresses the important and understudied issue of circuit-level mechanisms supporting habituation, particularly in pursuit of the possible role of increases in the activity of inhibitory neurons in suppressing behavioral output during long-term habituation. The authors make use of many of the striking advantages of the larval zebrafish to perform whole brain, single neuronal calcium imaging during repeated sensory exposure, and high throughput screening of pharmacological agents in freely moving, habituating larvae. Notably, several blockers/antagonists of GABAA(C) receptors completely suppress habituation of the O-bend escape response to dark flashes, suggesting a key role for GABAergic transmission in this form of habituation. Other substances are identified that strikingly enhance habituation, including melatonin, although here the suggested mechanistic insight is less specific. To add to these findings, a number of functional clusters of neurons are identified in the larval brain that have divergent activity through habituation, with many clusters exhibiting suppression of different degrees, in line with adaptive filtration during habituation, and a single cluster that potentiates during habituation. Further assessment reveals that all of these clusters include GABAergic inhibitory neurons and excitatory neurons, so we cannot take away the simple interpretation that the potentiating cluster of neurons is inhibitory and therefore exerts an influence on the other adapting (depressing) clusters to produce habituation. Rather, a variety of interpretations remain in play.

Overall, there is great potential in the approach that has been used here to gain insight into circuit-level mechanisms of habituation. There are many experiments performed by the authors that cannot be achieved currently in other vertebrate systems, so the manuscript serves as a potential methodological platform that can be used to support a rich array of future work. While there are several key observations that one can take away from this manuscript, a clear interpretation of the role of GABAergic inhibitory neurons in habituation has not been established. This potential feature of habituation is emphasized throughout, particularly in the introduction and discussion sections, meaning that one is obliged as a reader to interrogate whether the results as they currently stand really do demonstrate a role for GABAergic inhibition in habituation. Currently, the key piece of evidence that may support this conclusion is that picrotoxin, which acts to block some classes of GABA receptors, prevents habituation. However, there are interpretations of this finding that do not specifically require a role for modified GABAergic inhibition. For instance, by lowering GABAergic inhibition, an overall increase in neural activity will occur within the brain, in this case below a level that could cause a seizure. That increase in activity may simply prevent learning by massively increasing neural noise and therefore either preventing synaptic plasticity or, more likely, causing indiscriminate synaptic strengthening and weakening that occludes information storage. Sensory processing itself could also be disrupted, for instance by altering the selectivity of receptive fields. Alternatively, it could be that the increase in neural activity produced by the blockade of inhibition simply drives more behavioral output, meaning that more excitatory synaptic adaptation is required to suppress that output. The authors propose two specific working models of the ways in which GABAergic inhibition could be implemented in habituation. An alternative model, in which GABAergic neurons are not themselves modified but act as a key intermediary between Hebbian assemblies of excitatory neurons that are modified to support memory and output neurons, is not explored. As yet, these or other models in which inhibition is not required for habituation, have not been fully tested.

This manuscript describes a really substantial body of work that provides evidence of functional clusters of neurons with divergent responses to repeated sensory input and an array of pharmacological agents that can influence the rate of a fundamentally important form of learning.

Reviewer #1 (Public Review):

In this manuscript, the authors aimed to compare, from testis tissues at different ages from mice in vivo and after culture, multiple aspects of Leydig cells. These aspects included mRNA levels, proliferation, apoptosis, steroid levels, protein levels, etc. A lot of work was put into this manuscript in terms of experiments, systems, and approaches. The technical aspects of this work may be of interest to labs working on the specific topics of in vitro spermatogenesis for fertility preservation.

Second review:

The authors should be commended for substantial improvement in their manuscript for resubmission.

Sleep is the absolute foundation for top-performance.

Measure it. Track it. Optimize it.

After that, results WILL go into the sky.

Reviewer #1 (Public Review):

The authors managed to show the broad botanical landscape and not only the main crops. This unique achievement is based on decades of establishing an excellent collection of a full comparative seed collection of the current flora. This allows the identification of species that usually are not identifiable. The authors were able to compare the crops that were grown there and identify the contribution of the Roman period with that of the Arab one. This excellent study is a landmark in how such studies should be done. The list of identified species will be used for many other studies on this subject.

Reviewer #1 (Public Review):

The paper proposes a novel approach, named ModCRE, which utilizes structure-based learning to predict the DNA binding preferences of transcription factors (TFs). The authors integrate both experimental knowledge of the structures of TF-DNA complexes and large amounts of high-throughput TF-DNA interaction data. Additionally, the authors have developed a server that automatically produces these characteristics for other TFs and their complexes with co-factors.

Strengths: The paper's integration of experimental knowledge and high-throughput data to develop statistical knowledge-based potentials to score the binding capability of TFs in cis-regulatory elements is a powerful strategy. The proposed approach can be applied to more than 80% of TF sequences, making it a general method for characterizing binding preferences.

Weaknesses: The paper is difficult to follow, as it contains many technical details and implementation details. The method applied is not always clear, and the paper focuses on implementation rather than the message. The results indicate that the nearest neighbors approach in Figure 4 outperforms the proposed method in many cases, and the proposed method seems to perform better only when similarity with the target is low. The same applies in Fig. 5 when using normalized ranked scores.

It appears that the authors have successfully developed a structure-based learning approach for predicting DNA binding preferences of transcription factors. However, the paper's technical language and implementation focus make it challenging to follow at times.

It seems the authors have successfully achieved most of their aims in improving predictions for TF-DNA interaction, and the results support their conclusions.

This work has the potential to significantly impact the field of TF-DNA binding and gene regulation, particularly for those interested in predicting PWMs for TFs with limited or unreliable experimental data.

Reviewer #1 (Public Review):

Summary:<br /> Rai1 encodes the transcription factor retinoic acid-induced 1 (RAI1), which regulates expression of factors involved in neuronal development and synaptic transmission. Rai1 haploinsufficiency leads to the monogenic disorder Smith-Magenis syndrome (SMS), which is associated with excessive feeding, obesity and intellectual disability. Consistent with findings in human subjects, Rai1+/- mice and mice with conditional deletion of Rai1 in Sim+ neurons, which are abundant in the paraventricular nucleus (PVN), exhibit hyperphagia, obesity and increased adiposity. Furthermore, RAI1-deficient mice exhibit reduced expression of brain-derived neurotrophic factor (BDNF), a satiety factor essential for the central control of energy balance. Notably, overexpression of BDNF in PVN of RAI1-deficient mice mitigated their obesity, implicating this neurotrophin in the metabolic dysfunction these animals exhibit. In this follow up study, Javed et al. interrogated the necessity of RAI1 in BDNF+ neurons promoting metabolic health.

Consistent with previous reports, the authors observed reduced BDNF expression in the hypothalamus of Rai1+/- mice. Moreover, proteomics analysis indicated impairment in neurotrophin signaling in the mutants. Selective deletion of Rai1 in BDNF+ neurons in the brain during development resulted in increased body weight, fat mass and reduced locomotor activity and energy expenditure without changes in food intake. There was also a robust effect on glycemic control, with mutants exhibiting glucose intolerance. Selective depletion of RAI1 in BDNF+ neurons in PVN in adult mice also resulted in increased body weight, reduced locomotor activity, and glucose intolerance without affecting food intake. Blunting RAI1 activity also leads to increases and decreases in the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN.

Strengths:<br /> Overall, the experiments are well designed and multidisciplinary approaches are employed to demonstrate that RAI1 deficits in BDNF+ neurons diminish hypothalamic BDNF signaling and produce metabolic dysfunction. The most significant advance relative to previous reports is the finding from electrophysiological studies showing that blunting RAI1 activity leads to increases and decreases the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN. Furthermore, that intact RAI1 function is required in BDNF+ neurons for the regulation of glucose homeostasis.

Weaknesses:<br /> Some of the data need to be reconciled with previous findings by others. For example, the authors report that more than 50% of BDNF+ neurons in PVN also express pTrkB whereas about 20% of pTrkB+ cells contain BDNF, raising the possibility that autocrine mechanisms might be at play. This is in conflict with a previous study by An et al, (2015) showing that these cell populations are largely non-overlapping in the PVN.

Another issue that deserves more in depth discussion is that diminished BDNF function appears to play a minor part driving deficits in energy balance regulation. Accordingly, both global central depletion of Rai1 in BDNF+ neurons during development and deletion of Rai1 in BDNF+ neurons in the adult PVN elicited modest effects on body weight (less than 18% increase) and did not affect food intake. This contrasts with mice with selective Bdnf deletion in the adult PVN, which are hyperphagic and dramatically obese (90% heavier than controls). Therefore, the results suggest that deficits in RAI1 in PVN or the whole brain only moderately affect BDNF actions influencing energy homeostasis and that other signaling cascades and neuronal populations play a more prominent role driving the phenotypes observed in Rai1+/- mice, which are hyperphagic and 95% heavier than controls. The results from the proteomic analysis of hypothalamic tissue of Rai1 mutant mice and controls could be useful in generating alternative hypotheses.

Depleting RAI1 in BDNF+ neurons had a robust effect compromising glycemic control. However, as the approach does not necessarily impact BDNF exclusively, there should be a larger discussion of alternative mechanisms.

Reviewer #1 (Public Review):

Summary:<br /> This paper reported a protocol of using human-induced pluripotent stem cells to generate cells expressing microglia-enriched genes and responding to LPS by drastic upregulation of proinflammatory cytokines. Upon subretinal transplantation in mice, hiPSC-derived cells integrated into the host retina and maintained retinal homeostasis, while they responded to RPE injury by migration, proliferation and phagocytosis. The findings revealed the potential of using hiPSC-derived cell transplantation for microglia replacement as a therapeutic strategy for retinal diseases.

Strengths:<br /> The paper demonstrates a method of consistently generating a significant quantity of hiPSC-derived microglia-like cells for in vitro study or for in vivo transplantation. RNAseq analysis offers an opportunity for comprehensive transcriptome profiling of the derived cells. It is impressive that following transplantation, these cells integrated into the retina well, migrated to the corresponding layers, adopted microglia-like morphologies, and survived long term without generating apparent harm. The work has laid a foundation for future utilization of hiPSC-derived microglia in lab and clinical applications.

Weaknesses:<br /> 1. The primary weakness of the paper concerns its conclusion of having generated "homogenous mature microglia", partly based on the RNAseq analysis. However, the comparison of gene profiles was carried out only between "hiPSC-derived mature microglia" and the proliferating myeloid progenitors. While the transcriptome profiles revealed a trend of enrichment of microglia-like gene expression in "hiPSC-derived mature microglia" compared to proliferating myeloid progenitors, this is not sufficient to claim they are "mature microglia". It is important that one carries out a comparative analysis of the RNAseq data with those of primary human microglia, which may be done by leveraging the public database. To convincingly claim these cells are mature microglia, questions need to be addressed including how similar the molecular signatures of these cells are compared with the fully differentiated primary microglia cell or if they remain progenitor-like or take on mosaic properties, and how they distinguish from macrophages.

2. While the authors attempted to demonstrate the functional property of "hiPSC-derived mature microglia" in culture, they used LPS challenge, which is an inappropriate assay. This is because human microglia respond poorly to LPS alone but need to be activated by a combination of LPS with other factors, such as IFNγ. Their data that "hiPSC-derived mature microglia" showed robust responses to LPS indeed implicates that these cells do not behave like mature human microglia.

3. The resolution of Figs. 4 - 6 is so low that even some of the text and labels are hardly readable. Based on the morphology shown in Fig. 4 and the statement in line 147, these hiPSC-derived "cells altered their morphology to a rounded shape within an hour of incubation and rapidly internalized the fluorescent-labeled particles". This is a peculiar response. Usually, microglia do not respond to fluorescent-labeled zymosan by turning into a rounded shaped within an hour when they internalize them. Such a behavior usually implicates weak phagocytotic capacity.

4. Data presented in Fig. 5 are not very convincing to support that transplanted cells were immunopositive for "human CD11b (Fig.5C), as well as microglia signature markers P2ry12 and TMEM119 (Fig.5D)" (line 167). The resolution and magnification of Fig. 5D is too low to tell the colocalization of tdT and human microglial marker immunolabeling. In the flat-mount images (C, I), hCD11b immunolabeling is not visible in the GCL or barely visible in the IPL. This should be discussed.

5. Microglia respond to injury by becoming active and lose their expression of the resting state microglial marker, such as P2ry12, which is used in Fig. 6 for detection of migrated microglia. To confirm that these cells indeed respond to injury like native microglia, one should check for activated microglial markers and induction of pro-inflammatory cytokines in the sodium iodate-injury model.

Reviewer #1 (Public Review):

The inferior colliculus (IC) is the central auditory system's major hub. It integrates ascending brainstem signals to provide acoustic information to the auditory thalamus. The superficial layers of the IC ("shell" IC regions as defined in the current manuscript) also receive a massive descending projection from the auditory cortex. This auditory cortico-collicular pathway has long fascinated the hearing field, as it may provide a route to funnel "high-level" cortical signals and impart behavioral salience upon an otherwise behaviorally agnostic midbrain circuit.

Accordingly, IC neurons can respond differently to the same sound depending on whether animals engage in a behavioral task (Ryan and Miller 1977; Ryan et al., 1984; Slee & David, 2015; Saderi et al., 2021; De Franceschi & Barkat, 2021). Many studies also report a rich variety of non-auditory responses in the IC, far beyond the simple acoustic responses one expects to find in a "low-level" region (Sakurai, 1990; Metzger et al., 2006; Porter et al., 2007). A tacit assumption is that the behaviorally relevant activity of IC neurons is inherited from the auditory cortico-collicular pathway. However, this assumption has never been tested, owing to two main limitations of past studies:

1) Prior studies could not confirm if data were obtained from IC neurons that receive monosynaptic input from the auditory cortex.

2) Many studies have tested how auditory cortical inactivation impacts IC neuron activity; the consequence of cortical silencing is sometimes quite modest. However, all prior inactivation studies were conducted in anesthetized or passively listening animals. These conditions may not fully engage the auditory cortico-collicular pathway. Moreover, the extent of cortical inactivation in prior studies was sometimes ambiguous, which complicates interpreting modest or negative results.

Here, the authors' goal is to directly test if auditory cortex is necessary for behaviorally relevant activity in IC neurons. They conclude that surprisingly, task relevant activity in cortico-recipient IC neuron persists in absence of auditory cortico-collicular transmission. To this end, a major strength of the paper is that the authors combine a sound-detection behavior with clever approaches that unambiguously overcome the limitations of past studies.

First, the authors inject a transsynaptic virus into the auditory cortex, thereby expressing a genetically encoded calcium indicator in the auditory cortex's postsynaptic targets in the IC. This powerful approach enables 2-photon Ca2+ imaging from IC neurons that unambiguously receive monosynaptic input from auditory cortex. Thus, any effect of cortical silencing should be maximally observable in this neuronal population. Second, they abrogate auditory cortico-collicular transmission using lesions of auditory cortex. This "sledgehammer" approach is arguably the most direct test of whether cortico-recipient IC neurons will continue to encode task-relevant information in absence of descending feedback. Indeed, their method circumvents the known limitations of more modern optogenetic or chemogenetic silencing, e.g. variable efficacy.

I also see three weaknesses which limit what we can learn from the authors' hard work, at least in the current form. I want to emphasize that these issues do not reflect any fatal flaw of the approach. Rather, I believe that their datasets likely contain the treasure-trove of knowledge required to completely support their claims.

1. The conclusion of this paper requires the following assumption to be true: That the difference in neural activity between Hit and Miss trials reflects "information beyond the physical attributes of sound." The data presentation complicates asserting this assumption. Specifically, they average fluorescence transients of all Hit and all Miss trials in their detection task. Yet, Figure 3B shows that mice's d' depends on sound level, and since this is a detection task the smaller d' at low SPLs presumably reflects lower Hit rates (and thus higher Miss rates). As currently written, it is not clear if fluorescence traces for Hits arise from trials where the sound cue was played at a higher sound level than on Miss trials. Thus, the difference in neural activity on Hit and Miss trials could indeed reflect mice's behavior (licking or not licking). But in principle could also be explained by higher sound-evoked spike rates on Hit compared to Miss trials, simply due to louder click sounds. Indeed, the amplitude and decay tau of their indicator GCaMP6f is non-linearly dependent on the number and rate of spikes (Chen et al., 2013), so this isn't an unreasonable concern.

2. The authors' central claim effectively rests upon two analyses in Figures 5 and 6. The spectral clustering algorithm of Figure 5 identifies 10 separate activity patterns in IC neurons of control and lesioned mice; most of these clusters show distinct activity on averaged Hit and Miss trials. They conclude that although the proportions of neurons from control and lesioned mice in certain clusters deviates from an expected 50/50 split, neurons from lesioned mice are still represented in all clusters. A significant issue here is that in addition to averaging all Hits and Miss trials together, the data from control and lesioned mice are lumped for the clustering. There is no direct comparison of neural activity between the two groups, so the reader must rely on interpreting a row of pie charts to assess the conclusion. It's unclear how similar task relevant activity is between control and lesioned mice; we don't even have a ballpark estimate of how auditory cortex does or does not contribute to task relevant activity. Although ideally the authors would have approached this by repeatedly imaging the same IC neurons before and after lesioning auditory cortex, this within-subjects design may be unfeasible if lesions interfere with task retention. Nevertheless, they have recordings from hundreds to thousands of neurons across two groups, so even a small effect should be observable in a between-groups comparison.

3. In Figure 6, the authors show that logistic regression models predict whether the trial is a Hit or Miss from their fluorescence data. Classification accuracy peaks rapidly following sound presentation, implying substantial information regarding mice's actions. The authors further show that classification accuracy is reduced, but still above chance in mice with auditory cortical lesions. The authors conclude from this analysis task relevant activity persists in absence of auditory cortex. In principle I do not disagree with their conclusion.

The weakness here is in the details. First, the reduction in classification accuracy of lesioned mice suggests that auditory cortex does nevertheless transmit some task relevant information, however minor it may be. I feel that as written, their narrative does not adequately highlight this finding. Rather one could argue that their results suggest redundant sources of task-relevant activity converging in the IC. Secondly, the authors conclude that decoding accuracy is impaired more in partially compared to fully lesioned mice. They admit that this conclusion is at face value counterintuitive, and provide compelling mechanistic arguments in the Discussion. However, aside from shaded 95% CIs, we have no estimate of variance in decoding accuracy across sessions or subjects for either control or lesioned mice. Thus we don't know if the small sample sizes of partial (n = 3) and full lesion (n = 4) groups adequately sample from the underlying population. Their result of Figure 6B may reflect spurious sampling from tail ends of the distributions, rather than a true non-monotonic effect of lesion size on task relevant activity in IC.

Reviewer #1 (Public Review):

Summary:<br /> This paper presents a cognitive model of out-of-distribution generalisation, where the representational basis is grid-cell codes. In particular, the authors consider the tasks of analogies, addition, and multiplication, and the out-of-distribution tests are shifting or scaling the input domain. The authors utilise grid cell codes, which are multi-scale as well as translationally invariant due to their periodicity. To allow for domain adaptation, the authors use DPP-A which is, in this context, a mechanism of adapting to input scale changes. The authors present simulation results demonstrating that this model can perform out-of-distribution generalisation to input translations and re-scaling, whereas other models fail.

Strengths:<br /> This paper makes the point it sets out to - that there are some underlying representational bases, like grid cells, that when combined with a domain adaptation mechanism, like DPP-A, can facilitate out-of-generalisation. I don't have any issues with the technical details.

Weaknesses:<br /> The paper does leave open the bigger questions of 1) how one learns a suitable representation basis in the first place, 2) how to have a domain adaptation mechanism that works in more general settings other than adapting to scale. Overall, I'm left wondering whether this model is really quite bespoke or whether there is something really general here. My comments below are trying to understand how general this approach is.

COMMENTS<br /> This work relies on being able to map inputs into an appropriate representational space. The inputs were integers so it's easy enough to map them to grid locations. But how does this transfer to making analogies in other spaces? Do the inputs need to be mapped (potentially non-linearly) into a space where everything is linear? In general, what are the properties of the embedding space that allows the grid code to be suitable? It would be helpful to know just how much leg work an embedding model would have to do.

It's natural that grid cells are great for domain shifts of translation, rescaling, and rotation, because they themselves are multi-scaled and are invariant to translations and rotations. But grid codes aren't going to be great for other types of domain shifts. Are the authors saying that to make analogies grid cells are all you need? If not then what else? And how does this representation get learned? Are there lots of these invariant codes hanging around? And if so how does the appropriate one get chosen for each situation? Some discussion of the points is necessary as otherwise, the model seems somewhat narrow in scope.

For effective adaptation of scale, the authors needed to use DPP-A. Being that they are relating to brains using grid codes, what processes are implementing DPP-A? Presumably, a computational module that serves the role of DPP-A could be meta-learned? I.e. if they change their task set-up so it gets to see domain shifts in its training data an LSTM or transformer could learn to do this. The presented model comparisons feel a bit of a straw man.

I couldn't see it explained exactly how R works.

Reviewer #1 (Public Review):

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder leading to the loss of innervation of skeletal muscles, caused by the dysfunction and eventual death of lower motor neurons. A variety of approaches have been taken to treat this disease. With the exception of three drugs that modestly slow progression, most therapeutics have failed to provide benefit. Replacing lost motor neurons in the spinal cord with healthy cells is plagued by a number of challenges, including the toxic environment, inhibitory cues that prevent axon outgrowth to the periphery, and proper targeting of the axons to the correct muscle groups. These challenges seem to be well beyond our current technological approaches. Avoiding these challenges altogether, Bryson et al. seek to transplant the replacement motor neurons into the peripheral nerves, closer to their targets. The current manuscript addresses some of the challenges that will need to be overcome, such as immune rejection of the allograft and optimizing maturation of the neuromuscular junction.

Bryson et al. begin by examining the survival of mESC-derived motor neurons allografted into SOD1 mice. The motor neurons, made on a 129S1/SvImJ, were transplanted into the tibial nerve of SOD1 mice on a C57BL/6J background. Without immunosuppression, most cells were lost between 14 and 35 days, suggesting an immune response had eliminated them. Tacrolimus prevented cell loss, but it also inhibited innervation of the muscle. It also uncovered the tumorigenic potential of contaminating pluripotent cells. In contrast, immunosuppression using H57-597, an antibody targeting T-cell receptor beta, prevented graft rejection while permitting some innervation of muscle. Pretreatment of the cells with mitomycin-C eliminated pluripotent cells, preventing tumor formation. The authors noted that this combination only innervated ~10% of endplates, likely due to the fact that the implanted motor neurons are not active.

The authors then began the process of optimizing the cells themselves, using measurements taken in late-stage SOD1 mice. Fast-firing and slow-firing populations of neurons were first compared. Using optical stimulation, these two cell types appeared to be similar. The authors opted to use slow-firing neurons in the subsequent experiments. Recognizing that neuromuscular junction (NMJ) innervation and maintenance are dependent on motor neuron activity, implantable optical stimulators were also evaluated. 14 days after transplanting the cells, optical stimulation training was initiated for one hour each day. This training led to a nearly 13-fold increase in force generation, although this still remained well below the force generated by electrical stimulation. The enhanced innervation also prevented the atrophy of muscle fibers caused by denervation.

Overall, the data for the function of the implanted cells are convincing. The dCALMS technique that the authors have developed is quite interesting and will likely be applicable to analyze muscles for other therapeutics. The identification of calcineurin inhibitors as inhibitors of reinnervation will also be important for the development of other cell-based therapeutics for ALS.

However, there are some issues that should be addressed. These include some common misconceptions about ALS. While ALS is split into familial and sporadic forms based on the presence or absence of a family history of the disease, mutations in the known ALS-associated genes are found in both forms. The authors also state that exercise programs are likely to accelerate degeneration in ALS. This is incorrect. Moderate exercise is part of the current guidelines for treating ALS, and mouse studies have demonstrated a therapeutic effect of moderate exercise. Regarding the experimental design, there are some important details missing. The animals do not appear to have been operated on at the same age, and the criteria for when to perform the operation were not described. A similar problem exists for when the animals were determined to reach endpoint. The authors also do not seem to address a potential pitfall of this approach: acceleration of the disease process. Indeed, some of the data comparing the ipsilateral side to the contralateral side suggest that the implantation of the cells and/or the light source increase the denervation of the muscle. Finally, there is a fairly large difference between the motor output provided by optical stimulation relative to electrical stimulation. It is currently unclear what level needs to be reached to provide an effective response in the intact animal. Thus, it is difficult to determine if the level of reinnervation that this study has achieved will be sufficient to improve a patient's quality of life.

Reviewer #1 (Public Review):

This is a key paper examining the evolution of an important structure (pillars) in the shell architecture of organo-phosphatic brachiopods. The advantages of these structures are adequately discussed and the evolution of the pillars is described and illustrated. There is much that is of fundamental significance here in understanding the ecology and evolution of these groups as a whole.

1) In several places the biological control on the development of the pillars is noted. This is explained in terms of their relationship to the growth and evolution of epithelial cells. It would be useful and make the paper more understandable if this link was mentioned early on in the paper and developed during the narrative.

2) The Cambrian Explosion is mentioned a number of times. Are these changes driven by the Cambrian Explosion, i.e. the expansion of major new body plans, or are the changes merely coincident with the long duration of the 'Explosion'?

3) I have no doubt the process is one of adaptive innovation but it would be useful to expand on this. Why is it adaptive?

4) Are pillars present in living Lingula?

Reviewer #1 (Public Review):

The present study examines whether one can identify kinematic signatures of different motor strategies in both humans and non-human primates (NHP). The Critical Stability Task (CST) requires a participant to control a cursor with complex dynamics based on hand motion. The manuscript includes datasets on performance of NHPs collected from a previous study, as well as new data on humans performing the same task. Further human experiments and optimal control models highlight how different strategies lead to different patterns of hand motion. Finally, classifiers were developed to predict which strategy individuals were using on a given trial. There are several strengths to this manuscript. I think the CST task provides a useful behavioural task to explore the neural basis of voluntary control. While reaching is an important basic motor skill, there is much to learn by looking at other motor actions to address many fundamental issues on the neural basis of voluntary control. I also think the comparison between human and NHP performance is important as there is a common concern that NHPs can be overtrained in performing motor tasks leading to differences in their performance as compared to humans. The present study highlights that there are clear similarities in motor strategies of humans and NHPs. While the results are promising, I would suggest that the actual use of these paradigms and techniques likely need some improvement/refinement. Notably, the threshold or technique to identify which strategy an individual is using on a given trial needs to be more stringent given the substantial overlap in hand kinematics between different strategies.

The most important goal of this study is to set up future studies to examine how changes in motor strategies impact neural processing. I have a few concerns that I think need to be considered. First, a classifier was developed to identify whether a trial reflected Position Control with success deemed to be a probability of >70% by the classifier. In contrast, a probability of <30% was considered successfully predicting Velocity Control (Uncertain bandwidth middle 40%). While this may be viewed as acceptable for purposes of quantifying behaviour, I'm not sure this is strict enough for interpreting neural data. Figure 7A displays the OFC Model results for the two strategies and demonstrates substantial overlap for RMS of Cursory Position and Velocity at the lowest range of values. In this region, individual trials for humans and NHP are commonly identified as reflecting Position Control by the classifier although this region clearly also falls within the range expected for Velocity Control, just a lower density of trials. The problem is that neural data is messy enough, but having trials being incorrectly labelled will make it even messier when trying to quantify differences in neural processing between strategies. A further challenge is that trials cannot be averaged as the patterns of kinematics are so different from trial-to-trial. One option is to just move up the threshold from >70%/<30% to levels where you have a higher confidence that performance only reflects one of the two strategies (perhaps 95/5% level). Another approach would be to identify the 95% confidence boundary for a given strategy and only classify a trial as reflecting a given strategy when it is inside its 95% boundary, but outside the other strategies 95% boundary (or some other level separation). A higher threshold would hopefully also deal with the challenge of individuals switching strategies within a trial. Admittedly, this more stringent separation will likely drop the number of trials prohibitively, but there is a clear trade-off between number of trials and clean data. For the future, a tweak to the task could be to lengthen the trial as this would certainly increase separation between the two conditions.

While the paradigm creates interesting behavioural differences, it is not clear to me what one would expect to observe neurally in different brain regions beyond paralleling kinematic differences in performance. Perhaps this could be discussed. One extension of the present task would be to add some trials where visual disturbances are applied near the end of the trial. The prediction is that there would be differences in the kinematics of these motor corrections for different motor strategies. One could then explore differences in neural processing across brain regions to identify regions that simply reflect sensory feedback (no differences in the neural response after the disturbance), versus those involved in different motor strategies (differences in neural responses after the disturbance).

It seems like a mix of lambda values are presented in Figure 5 and beyond. There needs to be some sort of analysis to verify that all strategies were equally used across lambda levels. Otherwise, apparent differences between control strategies may simply reflect changes in the difficulty of the task. It would also be useful to know if there were any trends across time? Strategies used for blocks of trials or one used early when learning and then changing later.

Figure 2 highlights key features of performance as a function of task difficulty. Lines 187 to 191 highlight similarities in motor performance between humans and NHPs. However, there is a curious difference in hand/cursor Gain for Monkey J. Any insight as to the basis for this difference?

Reviewer #1 (Public Review):

This paper falls in a long tradition of studies on the costs of reproduction in birds and its contribution to understanding individual variation in life histories. Unfortunately, the meta-analyses only confirm what we know already, and the simulations based on the outcome of the meta-analysis have shortcomings that prevent the inferences on optimal clutch size, in contrast to the claims made in the paper.

There was no information that I could find on the effect sizes used in the meta-analyses other than a figure listing the species included. In fact, there is more information on studies that were not included. This made it impossible to evaluate the data-set. This is a serious omission, because it is not uncommon for there to be serious errors in meta-analysis data sets. Moreover, in the long run the main contribution of a meta-analysis is to build a data set that can be included in further studies.

The main finding of the meta-analysis of the brood size manipulation studies is that the survival costs of enlarging brood size are modest, as previously reported by Santos & Nakagawa on what I suspect to be mostly the same data set. The paper does a very poor job of critically discussing whether we should take this at face value or whether instead there may be short-comings in the general experimental approach. A major reason why survival cost estimates are barely significantly different from zero may well be that parents do not fully adjust their parental effort to the manipulated brood size, either because of time/energy constraints, because it is too costly and therefore not optimal, or because parents do not register increased offspring needs. Whatever the reason, as a consequence, there is usually a strong effect of brood size manipulation on offspring growth and thereby presumably their fitness prospects. In the simulations (Fig.4), the consequences of the survival costs of reproduction for optimal clutch size were investigated without considering brood size manipulation effects on the offspring. Effects on offspring are briefly acknowledged in the discussion, but otherwise ignored. Assuming that the survival costs of reproduction are indeed difficult to discern because the offspring bear the brunt of the increase in brood size, a simulation that ignores the latter effect is unlikely to yield any insight in optimal clutch size. It is not clear therefore what we learn from these calculations.

There are other reasons why brood size manipulations may not reveal the costs of reproduction animals would incur when opting for a larger brood size than they produced spontaneously themselves. Firstly, the manipulations do not affect the effort incurred in laying eggs (which also biases your comparison with natural variation in clutch size). Secondly, the studies by Boonekamp et al on Jackdaws found that while there was no effect of brood size manipulation on parental survival after one year of manipulation, there was a strong effect when the same individuals were manipulated in the same direction in multiple years. This could be taken to mean that costs are not immediate but delayed, explaining why single year manipulations generally show little effect on survival. It would also mean that most estimates of the fitness costs of manipulated brood size are not fit for purpose, because typically restricted to survival over a single year.

Details of how the analyses were carried out were opaque in places, but as I understood the analysis of the brood size manipulation studies, manipulation was coded as a covariate, with negative values for brood size reductions and positive values for brood size enlargements (and then variably scaled or not to control brood or clutch size). This approach implicitly assumes that the trade-off between current brood size (manipulation) and parental survival is linear, which contrasts with the general expectation that this trade-off is not linear. This assumption reduces the value of the analysis, and contrasts with the approach of Santos & Nakagawa.

The observational study selection is not complete and apparently no attempt was made to make it complete. This is a missed opportunity - it would be interesting to learn more about interspecific variation in the association between natural variation in clutch size and parental survival.

Reviewer #1 (Public Review):

The authors present a scRNAseq study describing the transcriptomes of the tendon enthesis during postnatal development. This is an important topic that has major implication for the care of common clinical problems such as rotator cuff repair. The results are a valuable addition to the literature, providing a descriptive data set reinforcing other, more comprehensive studies. There are weaknesses, however, in the scRNAseq analyses.

1.The authors should provide additional rationale for the PCA analysis shown in Fig 1d. It is uncommon to use PCA for histomorphologic parameters. These results do not convincingly demonstrate that P7 is as a critical developmental timepoint.

2. According to the methods, it appears that the entire humeral head-supraspinatus tendon was used for cell isolation for scRNAseq. This results in the inclusion of cells from a variety of tissues, including bone, growth plate, enthesis and tendon. As such, only a very small percentage of cells in the analysis came from the enthesis. Inclusion of such a wide range of cells makes interpretation of enthesis cells difficult.

3. The differentiation/pseudotime analysis described in Fig 3 is difficult to follow. This map includes cell transcriptomes from vastly different tissues. Presumably, embedded in these maps are trajectories for osteoblast differentiation, chondrocyte differentiation, tenocyte differentiation, etc. With so many layers of overlapping information, it is difficult to (algorithmically) deduce a differentiation path of a particular cell type.

4. The authors uses the term "function" throughout the paper (e.g., "functional definition of fibrocartilage subpopulations"). However, this is a descriptive scRNAseq study, and "function" can therefore only theoretically be inferred from the algorithms used to analyze the data. A functional role for any of the identified pathways or processes can only be defined with gain- and/or loss-of-function studies.

5. "C2 highly expressed biomineralization-related genes (Clec3a, Tnn, Acan)". The three example genes are not related to biomineralization.

6. The functional characterization of the three enthesis cell clusters is not convincing. For example, activation of metabolism-related processes can mean a lot of things (including changes in differentiation), yet the authors interpret it very specifically as "role in postnatal fibrochondrocyte formation and growth".

7. The pseudotime analysis of the enthesis cell clusters is not convincing. The three clusters are quite close and overlapping on the UMAP. Furthermore, the authors focus on Tnn as a novel and unique gene, yet the expression pattern shown in Fig 5g implies even expression of this gene across all three clusters.

8. The TC1 markers (Ly6a, Dlk3, Clec3b) imply a non-tendon-specific cell population. Perhaps a tendon progenitor pool or an endothelial cell phenotype is more appropriate.

9. Pseudotime analyses assume that your data set includes cells from progenitor through mature cell populations. It is unclear that the timepoints studied here included cells from early progenitor states.

10. The CellChat analysis is difficult to follow, as the authors included 18 cell types. The number of possible interactions among so many cell types is enormous, and deducing valid connections between any two cell types in this case should be justified. Is the algorithm robust to so many possible interactions?

Reviewer #1 (Public Review):

1. My primary concern relates to how meaningful the human-rodent comparisons are, and whether these comparisons really advance our understanding of AxCaliber estimates in MS.

I applaud the aim to conduct "matched" experiments in both rodent models and human disease. It is a strength that the experiments are aligned with respect to the MRI measurements (although there are some caveats to this mentioned below). But beyond that, the overlap is not what one might hope for: the pathology would seem to be very distinct in humans and rodents, and the histological validation is not specific to what the MRI measurements claim to estimate.

To summarize the main findings: (i) in a rat model of general axonal degeneration, axon calibre estimates correlate with neurofilaments; (ii) in MS in humans, axon calibre estimates correlate with demyelinating lesions. This gives a picture of AxCalibre estimates correlating with neuropathology, but is this something that has not already been established in the literature?

If the aim is to validate AxCaliber, then there is a logic in using a rodent model that isolates alterations to axonal radius, but what then does this add to the existing literature in that space? If the aim is to study MS (for which AxCaliber results have been previously reported in Huang et al), then why not use a rodent model of MS?

2. I appreciate that both rodent and patient studies are time intensive, major endeavors. Neverthless, the number of subjects is very low in both rodent (n=9) and human (MS=10, control=6) studies. At the very least, this should be more openly acknowledged. But I'm concerned that this is a major weakness of the paper. Related to this, I find it hard to tell how carefully multiple comparison correction was performed throughout. It seems reasonably clear for the TBSS analyses, but then other analyses were performed in ROIs. Are these multiple comparisons corrected as well? Similarly, in Methods, I am confused by the statement that: "post hoc t tests corrected for multiple comparisons whenever a significant effect was detected". What does this mean?

3. While I do not think the text is in any sense deliberately misleading, I think the authors would do well to either tone down their claims or consider more carefully the implications of the text in many places. Some that stuck out for me are:

(a) Throughout, language in the paper (e.g., "Paired t tests were used to assess differences in the axonal diameter") presumes that the AxCaliber estimates specifically reflect axon diameter. I think the jury is out over whether this is true, particularly for measurements conducted with limited hardware specs. At the very least, I would encourage the author to refer to these measurements throughout as "estimates" of axon diameter.

(b) The authors suggest that their results provide "new tools for patient stratification" based on differences in lesion type, but it isn't clear what new information these markers would confer given that the lesions are differentiated based on T1w hypo/hyperintensities. In other words, these lesions are by definition already differentiable from a much simpler MRI marker.

(c) The authors note in the Discussion that: "sensitive to early stages of axonal degeneration, even before alterations in the myelin sheet are detected". Whether intentional or not, the implication in the context of this study is that this would hold for MS (that these markers would detect axonal degeneration preceding demyelination). While there is some discussion of alterations to axonal diameter in MS, the authors do not discuss whether these are the same mechanisms thought to occur in the IBO intervention used here.

(d) In the Discussion, the authors note the lack of evidence for a relationship with disability or disease duration, but nevertheless, go on to interpret the "trends" they do observe. I would advise strongly against this: the authors acknowledge that their numbers are low, so I would avoid the temptation to speculate here.

(e) In the Discussion state that "the use of neurofilaments has also been well validated in MS". Well validated for what? MS is a complex disease with a broad range of pathology, so this statement could be read to mean "neurofilaments are known to be altered in MS". However, in the context of this paragraph, the implication would seem to be that neurofilaments are a well-established proxy for axonal diameter. Is that the implication, and if so what general evidence is there for this?

Reviewer #1 (Public Review):

This study examines the factors underlying the assembly of MreB, an actin family member involved in mediating longitudinal cell wall synthesis in rod-shaped bacteria. Required for maintaining rod shape and essential for growth in model bacteria, single molecule work indicates that MreB forms treadmilling polymers that guide the synthesis of new peptidoglycan along the longitudinal cell wall. MreB has proven difficult to work with and the field is littered with artifacts. In vitro analysis of MreB assembly dynamics has not fared much better as helpfully detailed in the introduction to this study. In contrast to its distant relative actin, MreB is difficult to purify and requires very specific conditions to polymerize that differ between groups of bacteria. Currently, in vitro analysis of MreB and related proteins has been mostly limited to MreBs from Gram-negative bacteria which have different properties and behaviors from related proteins in Gram-positive organisms.

Here, Mao and colleagues use a range of techniques to purify MreB from the Gram-positive organism Geobacillus stearothermophilus, identify factors required for its assembly, and analyze the structure of MreB polymers. Notably, they identify two short hydrophobic sequences-located near one another on the 3-D structure-which are required to mediate membrane anchoring.

With regard to assembly dynamics, the authors find that Geobacillus MreB assembly requires both interactions with membrane lipids and nucleotide binding. Nucleotide hydrolysis is required for interaction with the membrane and interaction with lipids triggers polymerization. These experiments appear to be conducted in a rigorous manner, although the salt concentration of the buffer (500mM KCl) is quite high relative to that used for in vitro analysis of MreBs from other organisms. The authors should elaborate on their decision to use such a high salt buffer, and ideally, provide insight into how it might impact their findings relative to previous work.

Additionally, this study, like many others on MreB, makes much of MreB's relationship to actin. This leads to confusion and the use of unhelpful comparisons. For example, MreB filaments are not actin-like (line 58) any more than any polymer is "actin-like." As evidenced by the very beautiful images in this manuscript, MreB forms straight protofilaments that assemble into parallel arrays, not the paired-twisted polymers that are characteristic of F-actin. Generally, I would argue that work on MreB has been hindered by rather than benefitted from its relationship to actin (E.g early FP fusion data interpreted as evidence for an MreB endoskeleton supporting cell shape or depletion experiments implicating MreB in chromosome segregation) and thus such comparisons should be avoided unless absolutely necessary.

Reviewer #1 (Public Review):

In this paper, the authors tried to elucidate specific neuronal microRNAs which play an important role in the assembly of hippocampal networks. Using expression screening, they narrowed down on the microRNA miR-218, which is abundantly expressed at early postnatal stages of hippocampal development. Using different loss-of-function tools (antisense oligonucleotides, conditional microRNA knockout mice), they found that miR-218 inhibition early in life leads to a higher susceptibility of mice to develop epileptic seizures, as well as subtle behavioural alterations. These phenotypes were accompanied by disruption of early depolarizing GABAergic signaling, structural defects in dendritic spines, and altered intrinsic membrane excitability. An important role for miR-218 specifically in GABAergic interneurons is supported by the use of mice with an interneuron-specific loss of miR-218. However, the authors do not directly address which of the cellular phenotypes is causally involved in seizure susceptibility and behavioural alterations. Moreover, the authors describe molecular changes in interneurons and pyramidal neurons which are resulting from miR-218 inhibition in the mouse hippocampus. However, the identity of molecular pathways downstream of miR-218 in the context of epileptic seizures and behaviour remains unexplored.

Altogether, this study has a potentially high impact on the field of neuronal microRNA research and more specifically neuronal circuit assembly. The methods will be of high relevance for the microRNA community studying microRNA function in the context of early neural circuit development in mice in vivo. From a clinical point of view, these results could also increase our knowledge about the mechanisms of epileptic seizure development.

Reviewer #1 (Public Review):

The authors design a peptide, PITCR, that is similar to the transmembrane domain of the TCR zeta, but is rendered soluble by adding an additionally charged residue to the TM domain and changing basic residues in the cytoplasmic juxtamembrane sequence to acidic residues. Some other bulky hydrophobic resides were made smaller. The strategy was based on earlier work with EphA2 sequences reported in elife in 2018. The TCRzeta conditional TM peptide was then tested for effects on T cell receptor signalling, co-localisation, and effects on TCR stability in biochemical assays. Significant effects were detected and these were eliminated by a strong helix-breaking mutation. There are currently some limitations with the interpretation of the signaling and co-localization studies. The results will be of interest to those studying the TCR as well as those seeking to use the TCR or its derivatives in synthetic biology studies and immunotherapy.

Reviewer #1 (Public Review):

This paper accomplishes the authors' goal of using two complementary CRISPR approaches to identify novel determinants of CTL killing in vitro. Through these screens, the authors identify two new genes, ILKAP and ICAM1, that both modulate CTL killing across different cancer cell types. The dissection of how different ICAM1 proteins (membrane-bound and secreted) was also performed in a rigorous fashion. The use of multiple unrelated cancer cell lines greatly increases the strength of the findings and potential future applicability. Major weaknesses of the manuscript first include how ILKAP is connected to the control of ICAM1, which is unclear from the data presented in the paper. Secondly, while the authors use many different mutational variants of ICAM1 to dissect its function, the specific role of each of these mutations is not well described. A rigorous examination of secreted ICAM1 on CTL killing is not presented, and since membrane-bound and secreted ICAM1 have opposing functions on CTL killing, the clinical relevance of modulating ICAM1 is unclear. Finally, the authors do not consider how ICAM1 may affect antigen-presenting cells and other myeloid cells in the tumor which are critical intermediaries in the antitumor immune response. Overall, once these points of weakness are addressed, this work is expected to have a high impact in the field, as it presents new targets outside the PD-L1 / PD-1 axis that may aid in CTL killing of tumors across multiple cancer types.

Reviewer #1 (Public Review):

This paper uses a series of flight initiation "challenges" conducted both prior to and during COVID-19-related restrictions on human movement to estimate the degree to which avian escape responses to humans changed during the "anthropause". This technique is suitable for understanding avian behavioral responses with a high degree of repeatability. The study collects an impressive dataset over multiple years across five cities on two continents. Overall the study finds no effect of lockdown on avian escape distance (the distance at which the "target" individual flees the approaching observer). The study considers the variable of interest as both binary (during lockdown or prior to lockdown) and continuous, using the Oxford Stringency Index (with neither apparently affecting escape distance).

Overall this paper presents interesting results which may suggest that behavioral responses to humans are rather inflexible over "short" (~2 year) timespans. The anthropause represents a unique opportunity to disentangle the mechanistic drivers of myriad hypothesized impacts humans have on the behavior, distribution, and abundance of animals. Indeed, this finding would provide important context to the larger body of literature aimed at these ends. However, the paper could do more to carefully fit this finding into the broader literature and, in so doing, be a bit more careful about the conclusions they are able to draw given the study design and the measures used. Taking some of these points (in no particular order):

1) Oxford Stringency Index is a useful measure of governmental responses to the pandemic and it's true that in some scenarios (including the (Geng et al. 2021) study cited by this paper) it can correlate with human mobility. However, it is far from a direct measure of human mobility (even in the Geng study, to my reading, the index only explained a minority of the variation). Moreover, particular sub-components of the index are wholly unrelated to human mobility (e.g., would changes to a country's public information campaign lead to concomitant changes in urban human mobility?). Finally, compliance with government restrictions can vary geographically and over time (i.e., we might expect lower compliance in 2021 than in 2020) and the index is calculated at the scale of entire countries and may not be very reflective of local conditions. Overall this paper could do more to address the potential shortcomings of the Oxford Stringency Index as a measure of human mobility including attempting to validate the effect on human mobility using other datasets (e.g., the google dataset and/or those discussed in (Noi et al. 2022). This is of critical importance since the fundamental logic of the experimental design relies on the assumption that stringency ~ mobility.

2) The interpretation of the primary finding (that behavioral responses to humans are inflexible) could use a bit more contextualization within the literature. Specifically, the study offers three potential explanations for the observed invariance in escape response: 1) these behaviors are consistent within individuals and this study provides evidence that there was no population turnover as a result of lockdowns; 2) escape response is linked to other urban adaptations such that to be an urban-dwelling species dictates escape response; and/or 3) these populations already exhibit maximum habituation and the reduction in human mobility would only have increased that habituation but that trait is already at a boundary condition. Some comments on each of these respectively:

a) Even had these populations turned over as a result of a massive rural-to-urban dispersal event, it's not clear that the escape distance in those individuals would be different because this paper does not establish that these hypothetical rural birds have a different behavioral response which would be constant following dispersal. Thus the evidence gathered here is insufficient to tell us about possible relocations of the focal species. Additionally, the paper cites several papers that found no changes in abundance or movements of animals in response to lockdowns but ignore others that do. For example: (Wilmers et al. 2021), (Warrington et al. 2022) (though this may have been published after this was submitted...), and (Schrimpf et al. 2021). There is a missed opportunity to consider the drivers of some of these results - the findings in this paper are interesting in light of studies that *did* observe changes in space use or abundance - i.e., changes in space use could arise precisely *because* responses to humans are non-plastic but the distribution and activities of humans changed. To wit, the primary finding here would imply that the reaction norm to human presence is apparently fixed over such timescales - however, and critically, the putative reduction in human activity/mobility combined with fixed responses at the individual level might then imply changes in avian abundance/movement/etc.

b) If this were the case, wouldn't this be then measurable as a function of some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here? Site accounted for ~15% of the total variation in escape distance but was treated as a random effect - perhaps controlling for the nature of the urban environment using some e.g., remotely sensed variable would provide additional context here.

c) Because it's not clear the extent to which the populations tested had turned over between years, the paper could do with a bit more caution in interpreting these results as behavioral. This study spans several years so any response (or non-response) is not necessarily a measure of behavioral change because the sample at each time point could (likely does) represent different individuals. In fact, there may be an opportunity here to leverage the one site where pre-pandemic measures were taken several years prior to the pandemic. How much variance in the change in escape distance is observed when the gap between time points far exceeds the lifetime of the focal taxa versus measures taken close in time?

d) Finally, I think there are a few other potential explanations not sufficiently accounted for here:

i) These behaviors might indeed be plastic, but not over the timescales observed here.<br /> ii) Time of year - this study took place during the breeding season. The focal behavior here varies with the time of year, for example, escape distance for many of these species could be tied up in nest defense behaviors, tradeoffs between self-preservation and e.g., nest provisioning, etc.<br /> iii) Escape behaviors from humans are adaptively evolved, strongly heritable, and not context dependent - thus we would only expect these behaviors to change on evolutionary timescales.<br /> iv) See point one above - it's possible that the lockdown didn't modify human activity sufficiently to trigger a behavioral response or that the reaction norm to human behavior is non-linear (e.g. a threshold effect).

LITERATURE CITED<br /> Geng DC, Innes J, Wu W, Wang G. 2021. Impacts of COVID-19 pandemic on urban park visitation: a global analysis. J For Res 32:553-567. doi:10.1007/s11676-020-01249-w

Noi E, Rudolph A, Dodge S. 2022. Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework. Int J Geogr Inf Sci.

Schrimpf MB, Des Brisay PG, Johnston A, Smith AC, Sánchez-Jasso J, Robinson BG, Warrington MH, Mahony NA, Horn AG, Strimas-Mackey M, Fahrig L, Koper N. 2021. Reduced human activity during COVID-19 alters avian land use across North America. Sci Adv 7:eabf5073. doi:10.1126/sciadv.abf5073

Warrington MH, Schrimpf MB, Des Brisay P, Taylor ME, Koper N. 2022. Avian behaviour changes in response to human activity during the COVID-19 lockdown in the United Kingdom. Proc Biol Sci 289:20212740. doi:10.1098/rspb.2021.2740

Wilmers CC, Nisi AC, Ranc N. 2021. COVID-19 suppression of human mobility releases mountain lions from a landscape of fear. Curr Biol 31:3952-3955.e3. doi:10.1016/j.cub.2021.06.050

Reviewer #1 (Public Review):

Blanch-Lombarte and colleagues demonstrated that the expression of certain inhibitory receptors (IRGs) on CD8 T cells is elevated in people living with HIV (PLWH) and they remain elevated despite years of viral suppression on antiretroviral therapy (ART). A comprehensive single-cell analysis by multiparametric flow cytometry demonstrated that TGIT+ CD8 T cells have a skewed phenotype following HIV infection. Blocking of TGIT partially restores the ability of CD8 T cells to produce CD107a but not the other functions.

Strengths of the current study include the comprehensive analysis of IRGs on CD8 T cells of a well-characterized group of individuals with and without HIV. Additionally, they have confirmed that blocking of TGIT should be evaluated further as a potential therapy for PLWH. The conclusions seem well justified from the presented data.

Weaknesses include the cross-sectional data and minor confusion stemming in part from the lack of clarity and rationale for some of the experiments.

Reviewer #1 (Public Review):

Anderson, Henikoff, Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high-quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila. Some new analyses and a few new experiments are suggested here, which hopefully further take advantage of these data sets and make some results more conclusive.

Major comments:

1). The step-wise accumulation of H3K4me2 in bam, aly and wt testes are interesting. Is it possible to analyse the cis-acting sequences of different groups of genes with distinct H3K4me2 features, in order to examine whether there is any shared motif(s), suggesting common trans-factors that potentially set up the chromatin state for activating gene expression in a sequential manner?

2). Pg. 4, line 141-142: "we cannot measure H3K4me2 modification at the bam promoter in bam mutant testes or at the aly promoter in aly mutant testes", what are the allelic features of the bam mutant and aly mutant? Are the molecular features of these mutations preventing the detection of H3K4me2 at the endogenous genes' promoters? Also, the references cited (Chen et al., 2011) and (Laktionov et al., 2018) are not the original research papers where these two mutants were characterized.

3). The original paper that reported the Pc-GFP line and its localization is: Chromosoma 108, 83 (1999). The Pc-GFP is ubiquitously expressed and almost present in all cell types. In Figure 6B, there is no Pc-GFP signals in bam and aly mutant cells. According to the Method "one testis was dissected", does it mean that only one testis was prepared for immunostaining and imaging? If so, definitely more samples should be used for a more confident conclusion. Also, why use 3rd instar larval testes instead of adult testes? Finally, it is better to compare fixed tissue and live tissue, as the Pc-GFP signal could be lost during fixation and washing steps. Please refer to the above paper [Chromosoma 108, 83 (1999)] for Pc-GFP in spermatogonial cells and Development 138, 2441-2450 (2011) for Pc-GFP localization in aly mutant.

4). Ubiquitinylation of histone H2A is typically associated with gene silencing, here it has been hypothesized that ubH2A contributes to the activation of Y chromosome. This conclusion is strenuous, as it entirely depends on correlative results. For example, the lack of co-localization of ubH2A immunostaining and Pc-GFP are not convincing evidence that ubH2A is not resulting from PRC1 dRing activity. It would be a lot stronger conclusion by using genetic tools to show this. For example, if dRing is knocked down (using RNAi driven by a late-stage germline driver such as bam-Gal4) or mutated in spermatocytes (using mitotic clonal analysis), would they detect changes of ubH2A levels?

5). Regarding "X chromosome of males is thought to be upregulated in early germline cells", it has been shown that male-biased genes are deprived on the X chromosome [Science 299:697-700 (2003); Genome Biol 5:R40 (2004); Nature 450:238-241 (2007)], so are the differentiation genes of spermatogenesis [Cell Research 20:763-783 (2010)]. It would be informative to discuss the X chromatin features identified in this work with these previous findings. For example, the lack of RNAPII on X chromosome in spermatocytes could be due to a few differentiation genes expressed in spermatocytes located on the X chromosome.

Reviewer #1 (Public Review):

This is an intriguing and creative paper that examines whole brain cfos induction, a measure of brain activity, during mating and the formation of pair bonding. This contrasts with the classical reductionistic approach of focusing on a few individual brain regions in the monogamous and pair-bonding prairie vole. By taking this whole-brain approach following mating and then bond formation, several findings are revealed. (1) Using hierarchical cluster analysis some clusters were consistent with previously well-identified brain regions/circuits involved in bonding. The bed nucleus of the stria terminalis was identified as an important hub for bonding behavior but, importantly, the study also identified newer brain circuits likely involved in pair bond maintenance. (2) Rates of ejaculation best predicted the consistency of cfos activation that characterized a pair. (3) once the pair bond has stabilized, an amygdala cluster emerged potentially representing the coordination of a new cluster of brain regions that allow for pair bond maintenance. (4) There was a surprising lack of sexual dimorphism in active brain clusters identified during mating and pair bonding, but perhaps characteristic of a monogamous species.

While the approach used in this study cannot identify cause and effect, the whole brain approach identified clusters representing circuits of potential importance and a series of new hypotheses to explore.

The importance of the role of sexual behavior, specifically ejaculation rates, is worth emphasizing for the formation of pair bonds in prairie voles. It suggests that the role of sexual behavior in contributing to the strength of pair bonds should be explored more. It is also important to add that males and females in the study were screened for sexual receptivity. It would therefore be important to identify characteristics of animals that did not mate under the laboratory conditions used that may add depth and complexity to what was identified in the current study. The identification of brain regions for pair bond maintenance centered around the amygdala was also intriguing.

The issue of the lack of a strong presence of the reward circuitry (nucleus accumbens) in the final models is also worth more discussion. Perhaps it has been overly emphasized in the past, but there are strong results from other studies pointing to the importance of reward circuitry.

The design involved a nice time series for collecting behavioral and neural data at four time points: 0 hr (mating), 2.5 hr (mating huddling, investigation). 6 (early unstable bond) and 22 hours after mating.

Please discuss the consequences of creating the behavioral data for pair bond formation by subtracting same-sex pairs interactions from the opposite-sex interactions. What sources of information are removed by using this approach?

Time 0 is when the barrier is removed after a two-hour exposure. Please speculate on what is going on during the two-hour exposure. Time zero is potentially more than the time of mating. Is it possible that aggression is being decreased during this time point that represents mating? Could it also be a measure of the outcome of an initial compatibility assessment by the male and female?

Reviewer #1 (Public Review):

The manuscript by Maio and colleagues looks at the impact of the heightened glycolytic activity induced by Mtb in monocytes, and its impact on Hif1- dependent migration of DCs.

Data concerning the biological significance of the impact of enhanced glycolysis on DC migration is strong and convincing. While Hif1-a is obviously a key factor, the evidence that it is a linear component in the cascade falls a little short as the main inhibitor used PX-478 does not have a clear, single mode of action. Additional characterization with the alternative inhibitor (Echinomycin) would make the argument more convincing.

Reviewer #1 (Public Review):

Summary:<br /> The article written by Kazdaghli et al. proposes a modification of imputation methods, to better account for and exploit the variability of the data. The aim is to reduce the variability of the imputation results. The authors propose two methods, one that still includes some imputation variability, but accounts for the distribution of the data points to improve the imputation. The other one proposes a determinantal sampling, that presents no variation in the imputation data, at least no variation in the classification task. As these methods grow easily in computation requirements and time, they also propose an algorithm to run these methods in quantum processors.

Strengths:<br /> The sampling method for imputing missing values that accounts for the variability of the data seems to be accurate.

Weaknesses:<br /> While the proposed method seems accurate and should improve the imputation task, I think that the authors must explain a little better some parts of the algorithm that they are using. Although I think the authors could have evaluated the imputations directly, as they mention in the introduction, I understand that the final goal in the task is to have a better classification. The problem is that they do not explain what the classification is, or how is it trained. In a real situation, they would have data that would be used for training the algorithm, and then new data that needs to be imputed and classified. In this article, I do not see any train, plus test or validation data. I wonder if there could be some interaction between the imputation and the classification methods, that leads to overfitting the data; in particular when the deterministic DPP is used.

In its current state, I do not think this article brings not very much value to the community that could benefit from it. I did not find an implementation of the method available to other scientists, nor the data used to evaluate it (while one data set is public, the simulated data is not available). This not only hinders the use of the method by the scientific community, but also makes it impossible to reproduce the results or test the algorithm in similar databases.

Reviewer #1 (Public Review):

Shoemaker and Grilli analyze publicly available sequencing data to quantify how the microbial diversity of ecosystems changes with the taxonomic scale considered (e.g., diversity of genera vs diversity of families). This study builds directly on Grilli's 2020 paper which used this data to show that for many different microbial species, the distribution of abundances of the species across sampling sites belongs to a simple one-parameter family of gamma distributions. In this work, they show that the gamma distribution also describes the distribution of abundances of higher taxonomic levels. The distribution now requires two parameters, but the second parameter can be approximately derived by treating the distributions of lower-level taxonomic units as being independent. The difference between the species-level result and the result at higher taxonomic levels suggests that in some sense microbial species are ecologically meaningful units.

While the higher-level taxon abundance distributions can be well-approximated assuming independence of the constituent species, this approach substantially underestimates variation in community richness and diversity among sampling sites. Much of this extra variability appears to be driven by variability in sample size across sites. It is not clear to me how much this variation in sample size is itself due to variation in sampling effort versus variation in overall microbial densities. This variation in sample size also produces correlations between taxon richness at lower and higher taxonomic levels. For instance, sites with large samples are likely to have both many species within a genus and many genera. The authors also consider taxon diversity (Shannon index, i.e. entropy), which is constructed from frequencies and is therefore less sensitive to sample size. In this case, correlations between diversity across taxonomic scales instead appear to depend on the idiosyncratic correlations among species abundances.

This paper's results are presented in a fairly terse manner, even when they are describing summary statistics that require a lot of thought to interpret. I don't think it would make sense to try to understand it without having first worked through the 2020 paper. But everyone interested in a general understanding of microbial ecology should read the 2020 paper, and once one has done that, this paper is worth reading as well simply for seeing how the major pattern in that paper shifts as one moves up in the taxonomic scale.

Joint Public Review:

Previous findings by authors show that heliomycin induces autophagy to inhibit cancer progression, while its water-soluble analogs induce apoptosis. Here, they show that one of the analogs, 4-dmH, binds to tNOX, a NADH oxidase which supports SirT1 activity, in addition to SirT1, while heliomycin only binds to SirtT1 but not tNOX, using CETSA and in silico molecular docking studies, in human oral cancer cells. The additional binding activity of 4-dmH to tNOX might explain the different biological outcome from heliomycin. 4-dmH induces ubiquitination and degradation of tNOX protein, in dependent of p53 status. The tumor suppressive effect of 4-dmH (by intra-tumoral injections) is better than heliomycin. TCGA data base analysis suggests that high tNOX mRNA expression is correlated with poor prognosis of oral cancer patients.

This group has been a leading lab of chemical and biological characterization of heliomycin and its analogs. Although their findings are interesting and advance their previous findings, they arbitrarily focus on tNOX as a potential new target of 4-dmH without clear rationale. Moreover, it remains unclear if the different biological outcomes caused by heliomycin and 4-dmH are indeed due to 4-dmH's ability to bind to tNOX in addition to SirT1. Moreover, molecular biological analyses to establish the proposed tNOX-SirT1 axis on inducing autophagy vs apoptosis are insufficiently performed.

Comments on the current version:

1. The rationale of selecting tNOX/ENOX2 as a potential target of 4-dmH, but not heliomycin, is unclear by taking a biased approach. Thus, there is high possibility that 4-dmH binds to other proteins involved in apoptosis inhibition. An unbiased screen to identify 4-dmH-binding proteins would be a better approach unless there is a clear and logical rationale.

2. The authors should show whether heliomycin indeed does not induce apoptosis, while 4-dmH cannot induce autophagy.

3. They should demonstrate whether genetic knockdown of tNOX, SirT1, or both tNOX and SirT1 induces apoptosis or autophagy and also reduces malignant properties of oral cancer cells.

4. The authors should examine whether overexpression of SirT1 or tNOX in cells treated with heliomycin or 4-dmH could nullify heliomycin-induced autophagy and 4-dmH-induced apoptosis. Also, instead of overexpressing tNOX, they can supplement NAD into cells treated with 4-dmH.

5. Related to Fig. 5C and 6a, the authors should examine the effects of heliomycin and 4-dmH on the cell cycle profiles, Annexin V positivity, and colony formation.

6. They should also examine whether either or both heliomycin and 4-dmH induce reactive oxygen species (ROS).

7. Related to Fig. 9d, they should mutate amino acid residue(s) in tNOX that are crucial for the 4-dmH-tNOX binding, including Ile 90, Lys98, Pro111, Pro113, Leu115, Pro117, and Pro118, to examine whether these mutants lose the binding to 4-dmH and fail to rescue 4-dmH-induced apoptosis, unlike wild-type tNOX.

8. Related to Fig. 10a, heliomycin appears to also reduce tNOX levels (although the extent is not as robust as 4-dmH), which is not expected since heliomycin does not bind to tNOX. They should compare the effects of heliomycin and 4-dmH on reducing the protein levels of tNOX. If heliomycin does not change the tNOX protein levels, then they need to discuss why heliomycin reduces tNOX levels in vivo.

9. Related to Fig. 10F, if tNOX is an upstream regulator of SirT1 and both heliomycin and 4-dmH ultimately target SirT1, it is unclear why heliomycin and 4-dmH cause different biological outcomes. One explanation is that tNOX has apoptosis-inhibiting function other than supporting (or independent of) SirT1 and hence 4-dmH-mediated tNOX inhibition causes apoptosis rather than autophagy. They should explain and discuss more about whether tNOX-inhibiting/binding function of 4-dmH is sufficient to explain the different biological outcomes from heliomycin.

10. They should examine the effects of heliomycin and 4-dmH on cell viability of non-tumor cells to examine their toxicities.

11. They should consistently use either tNOX or ENOX2 to avoid confusion.

Reviewer #1 (Public Review):

Summary:<br /> Heitmann et al introduce a novel method for predicting the potential of drug candidates to cause Torsades de Pointes using simulations. Despite the fact that a multitude of such methods have been proposed in the past decade, this approach manages to provide novelty in a way that is potentially paradigm-shifting. The figures are beautiful and manage to convey difficult concepts intuitively.

Strengths:<br /> (1) Novel combination of detailed mechanistic simulations with rigorous statistical modeling

(2) A method for predicting drug safety that can be used during drug development

(3) A clear explication of difficult concepts.

Weaknesses:<br /> (1) In this reviewer's opinion, the most important scientific issue that can be addressed is the fact that when a drug blocks multiple channels, it is not only the IC50 but also the Hill coefficient that can differ. By the same token, two drugs that block the same channel may have identical IC50s but different Hill coefficients. This is important to consider since concentration-dependence is an important part of the results presented here. If the Hill coefficients were to be significantly different, the concentration-dependent curves shown in Figure 6 could look very different.

(2) The curved lines shown in Figure 6 can initially be difficult to comprehend, especially when all the previous presentations emphasized linearity. But a further issue is obscured in these plots, which is the fact that they show a two-dimensional projection of a 4-dimensional space. Some of the drugs might hit the channels that are not shown (INaL & IKs), whereas others will not. It is unclear, and unaddressed in the manuscript, how differences in the "hidden channels" will influence the shapes of these curves. An example, or at least some verbal description, could be very helpful.

Reviewer #1 (Public Review):

This manuscript conducts a classic QTL analysis to identify the molecular basis of natural variation in disease resistance. This identifies a pair of glycosyltransferases that contribute to steroidal glycoalkaloid production. Specifically altering the final hexose structure of the compound. This is somewhat similar to the work in tomatine showing that the specific hexose structure mediates the final potential bioactivity. Using the resulting transgenic complementation lines that show that the gene leads to a strong resistance phenotype to one isolate of Alternaria solani and the Colorado potato beetle. This is solid work showing the identification of a new gene and compound influencing plant biotic interactions. The authors have improved the introduction and discussion to better show the breadth of knowledge in pathogen-defense metabolite interactions involving plants.

Reviewer #1 (Public Review):

Henault et al build on their own previous work investigating the longstanding hypothesis that hybridization between divergent populations can activate transposable element mobilization (transposition). Previously they created crosses of increasing sequence divergence, using both intra- and inter-species hybrids, and passaged them neutrally for hundreds of generations. Their previous work showed that neither hybrids isolated from natural environments nor hybrids from their mutation accumulation lines showed consistent evidence of increased transposable element content. Here, they sequence and assemble long-read genomes of 127 of their mutation-accumulation lines and annotate all existing and de novo transposable elements. They find only a handful of de novo transposition events, and instead demonstrate that structural variation (ploidy, aneuploidy, loss of heterozygosity) plays a much larger role in the transposable element load in a given strain. They then created transposable element reporter constructs using two different Ty1 elements from S. paradoxus lineages and measured the transposition rate in a number of intraspecific crosses. They demonstrate that the transposition rate is dependent on both the Ty1 sequence and the copy number of genomic transposable elements, the latter of which is consistent with what has been observed in the literature on transposable element copy number control in Saccharomyces. To my knowledge, others have not directly tested the effect of Ty1 sequence itself (have not created diverse Ty1 reporter constructs), and so this is an interesting advance. Finally, the authors show that mitotype has a moderate effect on transposition rate, which is an intriguing finding that will be interesting to explore in future work.

This study represents a large effort to investigate how genetic background can influence transposable element load and transposition rate. The long read sequencing, assembly, and annotation, and the creation of these reporter constructs are non-trivial. Their results are straightforward, well supported, and a nice addition to the literature.

The authors state that the results from their current work support results taken from their previous study using short-read sequencing data of the same lines. The argument that follows is whether the authors gained anything novel from long-read sequencing. I would like to see the authors make a stronger argument for why this new work was necessary, and a more detailed view of similarities or differences from their previous study (when should others choose to do long read vs. short read of evolved lines?). Relatedly, the authors should report the rates of structural variants that they observe. How are these results similar/different from other mutation-accumulation work in S. cerevisiae?

Since the authors show a small, but consistent influence of mitotype on transposition rates, adding further evidence for the role of mtDNA in regulating transposition, I'm curious what the transposition rate of a p0 strain is. I think including these results could make this observation more compelling.

Reviewer #1 (Public Review):

The work in this paper is in general done carefully. Reconstructions are done appropriately and the effects of statistical uncertainty are quantified properly. My only slight complaint is that I couldn't find statistics about posterior probabilities anywhere and that the sequences and trees do not seem to be deposited. I would also have preferred to have the actual phylogeny in the main text. This is a crucial piece of data that the reader needs to see to understand what exactly is being reconstructed.<br /> The paper identifies which mutations are crucial for the functional differences between the ancestors tested. This is done quite carefully - the authors even show that the same substitutions also work in extant proteins. My only slight concern was the authors' explanation of what these substitutions do. They show that these substitutions lower the affinity of the C-terminal peptide to the alpha-crystallin domain - a key oligomeric interaction. But the difference is very small - from 4.5 to 7 uM. That seems so small that I find it a bit implausible that this effect alone explains the differences in hydrodynamic radius shown in Figure S8. From my visual inspection, it seems that there is also a noticeable change in the cooperativity of the binding interaction. The binding model the authors use is a fairly simple logarithmic curve that doesn't appear to consider the number of binding sites or potential cooperativity. I think this would have been nice to see here.

Lastly, the authors use likelihood methods to test for signatures of selection. This reviewer is not a fan of these methods, as they are easily misled by common biological processes (see PMID 37395787 for a recent critique). Perhaps these pitfalls could simply be acknowledged, as I don't think the selection analysis is very important to the impact of the work.

Reviewer #1 (Public Review):

Summary:<br /> This study develops and applies a coarse-grained model for nucleosomes with explicit ions. The authors perform several measurements to explore the utility of a coarse-grained simulation method to model nucleosomes and nucleosome arrays with explicit ions and implicit water. 'Explicit ions' means that the charged ions are modeled as particles in simulation, allowing the distributions and dynamics of ions to be measured. Since nucleosomes are highly charged and modulated by charge modifications, this innovation is particularly relevant for chromatin simulation.

Strengths:<br /> This simulation method produces accurate predictions when compared to experiments for the binding affinity of histones to DNA, counterion interactions, nucleosome DNA unwinding, nucleosome binding free energies, and sedimentation coefficients of arrays. The variety of measured quantities makes both this work and the impact of this coarse-grained methodology compelling.

The comparison between the contributions of sodium and magnesium ions to nucleosome array compaction, presented in Figure 3, was exciting and a novel result that this simulation methodology can assess.

Weaknesses:<br /> The presentation of experimental data as representing in vivo systems is a simplification that may misrepresent the results of the simulation work. In vivo, in this context, typically means experimental data from whole cells. What one could expect for in vivo experimental data is measurements on nucleosomes from cell lysates where various and numerous chemical modifications are present. On the contrary, some of the experimental data used as a comparison are from in vitro studies. In vitro in this context means nucleosomes were formed 'in a test tube' or under controlled conditions that do not represent the complexity of an in vivo system. The simulations performed here are more directly compared to in vitro conditions. This distinction likely impacts to what extent these simulation results are biologically relevant. In vivo and in vitro differences could be clarified throughout and discussed.

Reviewer #1 (Public Review):

Summary:<br /> This paper by Schommartz and colleagues investigates the neural basis of memory reinstatement as a function of both how recently the memory was formed (recent, remote) and its development (children, young adults). The core question is whether memory consolidation processes as well as the specificity of memory reinstatement differ with development. A number of brain regions showed a greater activation difference for recent vs. remote memories at the long versus shorter delay specifically in adults (cerebellum, parahippocampal gyrus, LOC). A different set showed decreases in the same comparison, but only in children (precuneus, RSC). The authors also used neural pattern similarity analysis to characterize reinstatement, though I have substantive concerns about how this analysis was performed and as such will not summarize the results. Broadly, the behavioural and univariate findings are consistent with the idea that memory consolidation differs between children and adults in important ways, and takes a step towards characterizing how.

Strengths:<br /> The topic and goals of this paper are very interesting. As the authors note, there is little work on memory consolidation over development, and as such this will be an important data point in helping us begin to understand these important differences. The sample size is great, particularly given this is an onerous, multi-day experiment; the authors are to be commended for that. The task design is also generally well controlled, for example as the authors include new recently learned pairs during each session.

Weaknesses:<br /> As noted above, the pattern similarity analysis for both item and category-level reinstatement was performed in a way that is not interpretable given concerns about temporal autocorrelation within the scanning run. Below, I focus my review on this analytic issue, though I also outline additional concerns.

1. The pattern similarity analyses were not done correctly, rendering the results uninterpretable (assuming my understanding of the authors' approach is correct).

a. First, the scene-specific reinstatement index: The authors have correlated a neural pattern during a fixation cross (delay period) with a neural pattern associated with viewing a scene as their measure of reinstatement. The main issue with this is that these events always occurred back-to-back in time. As such, the two patterns will be similar due simply to the temporal autocorrelation in the BOLD signal. Because of the issues with temporal autocorrelation within the scanning run, it is always recommended to perform such correlations only across different runs. In this case, the authors always correlated patterns extracted from the same run, which moreover have temporal lags that are perfectly confounded with their comparison of interest (i.e., from Fig 4A, the "scene-specific" comparisons will always be back-to-back, having a very short temporal lag; "set-based" comparisons will be dispersed across the run, and therefore have a much higher lag). The authors' within-run correlation approach also yields correlation values that are extremely high - much higher than would be expected if this analysis was done appropriately. The way to fix this would be to restrict the analysis to only cross-run comparisons, but I don't believe this is possible unfortunately given the authors' design; I believe the target (presumably reinstated) scene only appears once during scanning, so there is no separate neural pattern during the presentation of this picture that they can use. For these reasons, any evidence for "significant scene-specific reinstatement" and the like is completely uninterpretable and would need to be removed from the paper.

b. From a theoretical standpoint, I believe the way this analysis was performed considering the fixation and the immediately following scene also means that the differences between recent and remote could have to do with either the reactivation (processes happening during the fixation, presumably) or differences in the processing of the stimulus itself (happening during the scene presentation). For example, people might be more engaged with the more novel scenes (recent) and therefore process those scenes more; such a difference would be interpreted in this analysis as having to do with reinstatement, but in fact could be just related to the differential scene processing/recognition, etc. It would be important when comparing scene-specific neural patterns as templates for reinstatement across conditions that, at the time of scene presentation itself, the two conditions are equal (e.g., no difference in familiarity and so on); otherwise, we do not know which trial period (and therefore which underlying process) is driving the differences.

c. For the category-based neural reinstatement: (1) This suffers from the same issue of correlations being performed within the run. Again, to correct this the authors would need to restrict comparisons to only across runs (i.e., patterns from run 1 correlated with patterns for run 2 and so on). With this restriction, it may or may not be possible to perform this analysis, depending upon how the same-category scenes are distributed across runs. However, there are other issues with this analysis, as well. (2) This analysis uses a different approach of comparing fixations to one another, rather than fixations to scenes. The authors do not motivate the reason for this switch. Please provide reasoning as to why fixation-fixation is more appropriate than fixation-scene similarity for category-level reinstatement, particularly given the opposite was used for item-level reinstatement. Even if the analyses were done properly, it would remain hard to compare them given this difference in approach. (3) I believe the fixation cross with itself is included in the "within category" score. Is this not a single neural pattern correlated with itself, which will yield maximal similarity (pearson r=1) or minimal dissimilarity (1-pearson r=0)? Including these comparisons in the averages for the within-category score will inflate the difference between the "within-category" and "between-category" comparisons. These (e.g., forest1-forest1) should not be included in the within-category comparisons considered; rather, they should be excluded, so the fixations are always different but sometimes the comparisons are two retrievals of the same scene type (forest1-forest2), and other times different scene types (forest1-field1). (4) It is troubling that the results from the category reinstatement metric do not seem to conceptually align with past work; for example, a lot of work has shown category-level reinstatement in adults. Here the authors do not show any category-level reinstatement in adults (yet they do in children), which generally seems extremely unexpected given past work and I would guess has to do with the operationalization of the metric.

2. I did not see any compelling statistical evidence for the claim of less robust consolidation in children. Specifically in terms of the behavioural results of retention of the remote items at 1 vs 14 days, shown in Figure 2B, the authors conclude that memory consolidation is less robust in children (line 246). Yet they do not report statistical evidence for this point, as there was no interaction of this effect with the age group. Children had worse memory than adults overall (in terms of a main effect - i.e. across recent and remote items). If it were consolidation-specific, one would expect that the age differences are bigger for the remote items, and perhaps even most exaggerated for the 14-day-old memories. Yet this does not appear to be the case based on the data the authors report. Therefore, the behavioural differences in retention do not seem to be consolidation specific, and therefore might have more to do with differences in encoding fidelity or retrieval processes more generally across the groups. This should be taken into account when interpreting the findings.

3. Please clarify which analyses were restricted to correct retrievals only. The univariate analyses states that correct and incorrect trials were modelled separately, but does not say which were considered in the main contrast (I assume correct only?). The item specific reinstatement analysis states that only correct trials were considered, but the category-level reinstatement analysis does not say. Please include this detail.

4. To what extent could performance differences be impacting the differences observed across age groups? I think (see prior comment) that the analyses were probably limited to correct trials, which is helpful, but still yields pretty big differences across groups in terms of the amount of data going into each analysis. In general, children showed more attenuated neural effects (e.g., recent/remote or session effects); could this be explained by their weaker memory? Specifically, if only correct trials are considered that means that fewer trials would be going into the analysis for kids, especially for the 14-day remote memories, and perhaps pushing the remove > recent difference for this condition towards 0. The authors might be able to address this analytically; for example, does the remote > recent difference in the univariate data at day 14 correlate with day 14 memory?

5. Some of the univariate results reporting is a bit strange, as they are relying upon differences between retrieval of 1- vs. 14-day memories in terms of the recent vs. report difference, and yet don't report whether the regions are differently active for recent and remote retrieval. For example in Figure 3A, neither anterior nor posterior hippocampus seem to be differentially active for recent vs. remote memories for either age group (i.e., all data is around 0). This difference from zero or lack thereof seems important to the message - is that correct? If so, can the authors incorporate descriptions of these findings?

6. Please provide more details about the choices available for locations in the 3AFC task. (1) Were they different each time, or always the same? If they are always the same, could this be a motor or stimulus/response learning task? (2) Do the options in the 3AFC always come from the same area - in which case the participant is given a clue as to the gist of the location/memory? Or are they sometimes randomly scattered across the image (in which case gist memory, like at a delay, would be sufficient for picking the right option)? Please clarify these points and discuss the logic/impact of these choices on the interpretation of the results.

7. Often p values are provided but test statistics, effect sizes, etc. are not - please include this information. It is at times hard to tell whether the authors are reporting main effects, interactions, pairwise comparisons, etc.

8. There are not enough methodological details in the main paper to make sense of the results. For example, it is not clear from reading the text that there are new object-location pairs learned each day.

9. The retrieval task does not seem to require retrieval of the scene itself, and as such it would be helpful for the authors to both explain their reasoning for this task to measure reinstatement. Strictly speaking, participants could just remember the location of the object on the screen. Was it verified that children and adults were recalling the actual scene rather than just the location (e.g. via self-report)? It's possible that there may be developmental differences in the tendency to reinstate the scene depending on e.g., their strategy.

10. In general I found the Introduction a bit difficult to follow. Below are a few specific questions I had.

a. At points findings are presented but the broader picture or take-home point is not expressed directly. For example, lines 112-127, these findings can all be conceptualized within many theories of consolidation, and yet those overarching frameworks are not directly discussed (e.g., that memory traces go from being more reliant on the hippocampus to more on the neocortex). Making these connections directly would likely be helpful for many readers.

b. Lines 143-153 - The comparison of the Tompary & Davachi (2017) paper with the Oedekoven et al. (2017) reads like the two analyses are directly comparable, but the authors were looking at different things. The Tompary paper is looking at organization (not reinstatement); while the Oedekoven et al. paper is measuring reinstatement (not organization). The authors should clarify how to reconcile these findings.

c. Line 195-6: I was confused by the prediction of "stable involvement of HC over time" given the work reviewed in the Introduction that HC contribution to memory tends to decrease with consolidation. Please clarify or rephrase.

d. Lines 200-202: I was a bit confused about this prediction. Firstly, please clarify whether immediate reinstatement has been characterized in this way for kids versus adults. Secondly, don't adults retain gist more over long delays (with specific information getting lost), at least behaviourally? This prediction seems to go against that; please clarify.

Reviewer #1 (Public Review):

Koumoundourou et al., identify a pathway downstream of Bcl11b that controls synapse morphology and plasticity of hippocampal mossy fiber synapses. Using an elegant combination of in vivo, ex vivo, and in vitro approaches, the authors build on their previous work that indicated C1ql2 as a functional target of Bcl11b (De Bruyckere et al., 2018). Here, they examine the functional implications of C1ql2 at MF synapses in Bcl11b cKO mice and following C1ql2 shRNA. The authors find that Bcl11b KO and shRNA against C1ql2 significantly reduces the recruitment of synaptic vesicles and impairs LTP at MF synapses. Importantly, the authors test a role for the previously identified C1ql2 binding partner, exon 25b-containing Nrxn3 (Matsuda et al., 2016), as relevant at MF synapses to maintain synaptic vesicle recruitment. To test this, the authors developed a K262E C1ql2 mutant that disrupts binding to Nrxn3. Curiously, while Bcl11b KO and C1ql2 KD largely phenocopy (reduced vesicle recruitment and impaired LTP), only vesicle recruitment is dependent on C1ql2-Nrxn3 interactions. These findings provide new insight into the functional role of C1ql2 at MF synapses. While the authors convincingly demonstrate a role for C1ql2-Nrxn3(25b+) interaction for vesicle recruitment and a Nrxn3(25b+)-independent role for C1ql2 in LTP, the underlying mechanisms remain inconclusive. Additionally, a discussion of how these findings relate to previous work on C1ql2 at mossy fiber synapses and how the findings contribute to the biology of Nrxn3 would increase the interpretability of this work.

这和我手动实现的,自定义顺序的比较器的功能非常类似; 通过范型生成不同类型的比较器;我的那个工具类,也应该叫 CustomOrderComparatorFactory 比较合适

Joint Public Review:

The authors report the first use of the bacterial Tus-Ter replication block system in human cells. A single plasmid containing two divergently oriented five-fold TerB repeats was integrated on chromosome 12 of MCF7 cells. ChIP and PLA experiments convincingly demonstrate the occupancy of Tus at the Ter sites in cells. Using an elegant Single Molecule Analysis of Replicated DNA (SMARD) assay, compelling data demonstrate the replication block at Ter sites dependent on the presence of the protein. As an orthogonal method to demonstrate fork stalling, ChIP data show the accumulation of the replicative helicase component MCM3 and the repair protein FANCM around the Ter sites. Previous published work from the Scully and Hickson laboratories showed that Ter sites do not perturb replication fork progression and consistently the data show that the observed effects are dependent on expression of the Tus protein. The SMARD data reveal that about one third of the forks are arrested at Tus/Ter but it is unclear for how long forks remain stalled. Fork stalling led to a highly localized gammaH2AX response, as monitored by ChIP using primer pairs spread along the integrated plasmid carrying the Ter sites. This response was shown to be dependent on ATR using the ATR inhibitor VE-822. This contrasts with a single Cas9-induced DSB between the two Ter sites, which causes a more spread gammaH2AX response measured at two sites flanking the DSB. The difference between the DSB and the Tus-induced stall is very significant. Interestingly, despite evidence for ATR activation through the gammaH2AX response, no evidence for phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 could be found under fork stalling conditions. The global replication inhibitor hydroxyurea (HU) elicited phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33. In this context, it would have been of interest to examine if a single DSB in the Ter region leads to phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 and cell cycle arrest. The replication inhibitor HU led to an increase in gamma H2AX foci consistent with a global replication stress response. Overall, this is a well written manuscript, and the data provide convincing evidence that the Tus-Ter system poses a site-specific replication fork block in MCF7 cells leading to a localized ATR-dependent DNA damage checkpoint response that is distinct from the more global response to HU or DSBs.

Reviewer #1 (Public Review):

The authors aimed to determine the mechanisms that underpin metabolic influences, particularly via the use of leucine which has been implicated in protection in lipopolysaccharide-induced cytokine storm syndrome.

The strength of the work is in establishing the clear relationship between the macrophage subtype and the severity of cytokine storm syndrome which occurs in severe inflammation and infection. They have undertaken a solid analysis of the cellular polarization of macrophage subtypes, identifying leucine suppresses M1 polarization and promotes M2 polarization. Subsequently, the authors confirmed this polarization via examination of signal transduction was mediated through the mTORC1 pathway. Pharmacological manipulation of mTORC was shown to influence arginase 1, a hallmark of M2 polarization. In addition, the authors show that leucine promoted the expression of LXRa required for arginase induction. While these studies identify how leucine might shape M2 cellular metabolism and polarization, the studies were all performed in vitro and do not examine other cellular or molecular changes that might influence the level of cytokine storm that might occur. Thus the specific contributions in cytokine storm syndrome are correlative requiring further analysis in the disease setting. These include features such as localization influencing other immune or stromal cells that might release cytokines and contribute to the syndrome, or molecular pathways not previously described. The statistical reporting and representation of data should be provided in greater detail. The data provides an interesting direction for consideration of the manipulation of immune cells in the context of inflammation and opens further discussion on how this might be practically applied in the clinical setting.

Joint Public Review:

Summary:<br /> Cook, Watt, and colleagues previously reported that a mouse model of Spinocerebellar ataxia type 6 (SCA6) displayed defects in BDNF and TrkB levels at an early disease stage. Moreover, they have shown that one month of exercise elevated cerebellar BDNF expression and improved ataxia and cerebellar Purkinje cell firing rate deficits. In the current work, they attempt to define the mechanism underlying the pathophysiological changes occurring in SCA6. For this, they carried out RNA sequencing of cerebellar vermis tissue in 12-month-old SCA6 mice, a time when the disease is already at an advanced stage, and identified widespread dysregulation of many genes involved in the endo-lysosomal system. Focusing on BDNF/TrkB expression, localization, and signaling they found that, in 7-8 month-old SCA6 mice early endosomes are enlarged and accumulate BDNF and TrkB in Purkinje cells. Curiously, TrkB appears to be reduced in the recycling endosomes compartment, despite the fact that recycling endosomes are morphologically normal in SCA6. In addition, the authors describe a reduction in the Late endosomes in SCA6 Purkinje cells associated with reduced BDNF levels and a probable deficit in late endosome maturation.

Strengths:<br /> The article is well written, and the findings are relevant for the neuropathology of different neurodegenerative diseases where dysfunction of early endosomes is observed. The authors have provided a detailed analysis of the endo-lysosomal system in SCA6 mice. They have shown that TrkB recycling to the cell membrane in recycling endosomes is reduced, and the late endosome transport of BDNF for degradation is impaired. The findings will be crucial in understanding underlying pathology. Lastly, the deficits in early endosomes are rescued by chronic administration of 7,8-DHF.

Weaknesses:<br /> The specificity of BDNF and TrkB immunostaining requires additional controls, as it has been very difficult to detect immunostaining of BDNF. In addition, in many of the figures, the background or outside of Purkinje cell boundaries also exhibits a positive signal.

One important concern about the conclusions is that the RNAseq experiment was conducted in 12-month-old SCA6 mice suggesting that the defects in the endo-lysosomal system may be caused by other pathophysiological events and, likewise, the impairment in BDNF signaling may also be indirect, as also noted by the authors. Indeed, Purkinje cells in SCA6 mice have an impaired ability to degrade other endocytosed cargo beyond BDNF and TrkB, most likely because of trafficking deficits that result in a disruption in the transport of cargo to the lysosomes and lysosomal dysfunction. Moreover, the beneficial effects of 7,8-DHF treatment on motor coordination may be caused by 7,8-DHF properties other than the putative agonist role on TrkB. Indeed, many reservations have been raised about using 7,8-DHF as an agonist of TrkB activity. Several studies have now debunked (Todd et al. PlosONE 2014, PMID: 24503862; Boltaev et al. Sci Signal 2017, PMID: 28831019) or at the very least questioned (Lowe D, Science 2017: see Discussion: https://www.science.org/content/blog-post/those-compounds-aren-t-what-you-think-they-are Wang et al. Cell 2022 PMID: 34963057). Another interpretation is that 7,8-DHF possesses antioxidant activity and neuroprotection against cytotoxicity in HT-22 and PC12 cells, both of which do not express TrkB (Chen et al. Neurosci Lett 201, PMID: 21651962; Han et al. Neurochem Int. 2014, PMID: 24220540). Thus, while this flavonoid may have a beneficial effect on the pathophysiology of SCA6, it is most unlikely that mechanistically this occurs through a TrkB agonistic effect considering the potent anti-oxidant and anti-inflammatory roles of flavonoids in neurodegenerative diseases (Jones et al. Trends Pharmacol Sci 2012, PMID: 22980637).

Reviewer #1 (Public Review):

Summary:<br /> People with Parkinson's disease often experience a variety of nonmotor symptoms, the biological bases of which remain poorly understood. Johansson et al began to study the potential roles of the dorsal raphe nucleus (DRN) degeneration in the pathophysiology of neuropsychiatric symptoms in PD.

Strengths:<br /> Johansson et al validated a transgenic reporter mouse line that can reliably label dopaminergic neurons in the DRN. This brain region shows severe neurodegeneration and has been proposed to contribute to the manifestation of neuropsychiatric symptoms in PD. Using this mouse line (and others), Johansson and colleagues characterized electrophysiological and morphological phenotypes of dopaminergic and serotoninergic neurons in the raphe nucleus. This study involved very careful topographical registration of recorded neurons to brain slices for post hoc immunohistochemical validation of cell identification, making it an elegant and thorough piece of work.

In relevance to PD pathophysiology, the authors evaluated the physiological and morphological changes of DRN serotoninergic and dopaminergic neurons after a partial loss of nigrostriatal dopamine neurons, which serves as a mouse model of early parkinsonian pathology. Importantly, the authors identified a series of physiological and morphological changes of subtypes of DRN neurons that depend on nigral dopaminergic neurodegeneration, LC adrenergic neurodegeneration, or both.

Overall, the study was well-designed, and the data were well-presented in this well-written manuscript.

Weaknesses:<br /> Caveats that should be mentioned include:

1) While desipramine experiments provide clues about the potential role of adrenaline loss in electrophysiological and morphological changes in the Figs. 3-5, a complementary set of experiments is needed to confirm these findings. For example, how might selective LC adrenergic neurodegeneration affect cellular physiology and morphology in the DRN? Can the observed phenotypes in Figs 3-4 be rescued by adrenergic receptor agonists?

2) It should be kept in mind that the key experiments of this study were conducted using mouse models of parkinsonism. Thus, these models cannot recapitulate the complexity of PD pathology and circuit dysfunction.

Reviewer #1 (Public Review):

This reviewed preprint is a bit of Frankenstein monster, as it crams together three quite different sets of data. It is essentially three papers combined into one-one paper focused on the role of CIB2/CIB3 in VHCs, one on the role of CIB2/CIB3 in zebrafish, and one on structural modeling of a CIB2/3 and TMC1/2 complex. The authors try to combine the three parts with the overarching theme of demonstrating that CIB2/3 play a functionally conserved role across species and hair cell types, but given the previous work on these proteins, especially Liang et al. (2021) and Wang et al. (2023), this argument doesn't work very well. My sense is that the way the manuscript is written now, the sum is less than the individual parts, and the authors should consider whether the work is better split into three separate papers.

The most important shortcoming is the novelty of the work presented here. In line 89 of the introduction the authors state "However, whether CIB2/3 can function and interact with TMC1/2 proteins across sensory organs, hair-cell types, and species is still unclear." They make a similar statement in the first sentence of the discussion and generally use this claim throughout the paper as motivation for why they performed the experiments. Given the data presented in the Liang et al. (2021) and Wang et al. (2023 papers), however, this statement is not well supported. Those papers clearly demonstrate a role for CIB2/CIB3 in auditory and vestibular cells in mice. Moreover, there is also data in Riazuddin et al. (2012) paper that demonstrates the importance of CIB2 in zebrafish and Drosophila. I think the authors are really stretching to describe the data in the manuscript as novel. Conceptually, it reads more as solidifying knowledge that was already sketched out in the field in past studies.

There is one exception, however, and that is the last part of the manuscript. Here structural studies (AlphaFold 2 modeling, NMR structure determination, and molecular dynamics simulations) bring us closer to the structure of the mammalian TMCs, alone and in complex with the CIB proteins. Moreover, the structural work supports the assignment of the TMC pore to alpha helices 4-7.

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

• for: quote, quote - W2W, quote - inequality, quote - jane goodall
• quote
  • there's the unsustainable lifestyle of so many of us
  • and I include myself
  • I have far more than I need and
  • some people take this to excess and they have way way way more than they could ever possibly need and
  • this is something that somehow we have to change
• comment
  • this supports the need for the W2W program

Reviewer #1 (Public Review):

Kraus et al. investigated transcriptional responses to transient exposure to infectious hematopoietic necrosis virus in the brain of adult zebrafish using single cell RNA-Seq methods. The authors discovered valuable evidence for immune responses in microglial clusters within minutes of viral exposure, and longer term changes in neuronal populations one day after viral treatment. The strength of the study is the RNA-Seq data which will act as a valuable resource for the zebrafish community. Their discoveries from the RNA-Seq studies are convincing, where they find a neuropeptide called PACAP enriched in neuronal populations a day after viral exposure, which exhibit antiviral activity. 

The authors select the 1 day time point post-infection based on initial behavioral experiments, the evidence for which is modest at best. While the experiments with larval animals are more substantiated, they use adults for their RNA-Seq experiments. The behavioral phenotype in adults is a marginal decrease in velocity 1 day after infection. The authors could have performed other tests associated with sickness behaviors, or even characterized the locomotion in the open field experiment with more in-depth analysis (for example, the larval experiments had more information regarding turning angles).

Joint Public Review:

In this manuscript, the authors challenge the fundamental concept that all neurons are derived from ectoderm. The key points of the authors argument are as follows:

1) Roughly half of the cells in the small intestinal longitudinal muscle-myenteric plexus (LM-MP) that express a pan-neuronal marker do not, by lineage tracing, appear to be derived from the neural crest.

2) Lineage tracing and marker gene imaging suggest that these non-neural crest derived neurons originate in the mesoderm, leading to their designation as mesodermal-derived enteric neurons (MENs).

3) Single-cell sequencing of LM-MP tissues confirms the mesodermal origin of MENs.

4) MENs progressively replace neural crest derived enteric neurons as mice age, eventually representing the bulk of the EN population.

There is broad agreement among the reviewers that the identification and description of this cell population is important, and that the failure of these cells to be labeled by neural crest lineage tracers is not artifactual. The work with transgenic lines is convincing that some presumptive neurons in the enteric nervous system (ENS) likely originate from an alternative source in the postnatal intestine and that this population increases in aging mice.

There is, however, ongoing disagreement between the authors and reviewers about whether the authors' provocative and potentially paradigm-changing proposal that these are neurons of mesodermal origin has been established. While the authors believe they have addressed the reviewers' concerns in multiple rounds of review (much of this prior to submission), the reviewers remain unconvinced and continue to request additional data and analyses.

A key premise of the preprint review system is that the best interests of science are not served by endlessly litigating disagreements around papers by either compelling the authors to do extensive and expensive additional experiments that they do not believe to be necessary or by treating the authors' claim as established in the face of continued skepticism. Accordingly the editor believes it is time to present this work, which everyone agrees contains important observations and valuable data, along with the following editor's synthesis of the reviewers' concerns and author responses about the question of these cells' origins. We encourage anyone interested in the details to review the already posted reviews and authors' response.

The following key issues have been raised during review:

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin?

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments?

* Does the genomic data establish that the sub-population of cells the authors focus on are of mesodermal origin?

* Are there alternative explanations for the lineage tracing and genomic observations than a mesodermal origin?

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin? *

The proximal evidence that the authors present for a mesodermal origin of the non-NC derived cells is presented in Figure 2, which establishes the presence, via lineage tracing of Tek+ and Mesp1+ (and therefore mesoderm derived) and Hu+ (and therefore neuronal) cells. The fraction of lineage labeled cells in each case (~50%) corresponds roughly to the fraction of cells that do not appear to be NC derived.

The reviewers raise several technical questions about the lineage tracing experiments, including issues of incomplete labeling, ectopic labeling and toxicity. The authors have addressed each of these with data and/or citations, and the editor believes they have demonstrated, subject to the broader limits of lineage tracing experiments, that there are Hu+ cells in the tissue that are derived from cells that do not express NC markers and that do express mesodermal markers.

One reviewer raised the question of whether these cells are neurons. This appears to the editor to be a valid question, in that specific neuronal activity of these cells has not been established. But the authors' argument is persuasive that their Hu+ state would have led them to be designated neurons and that changing that designation based on not being derived from NC is circular. However the possibility that, despite this accepted designation, these cells are not functionally neurons should be noted by readers.

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments, and does this data establish mesodermal origin? *

To provide orthogonal evidence for the presence of mesodermally derived enteric neurons, the authors carried out single-cell sequencing of dissociated cells from hand-dissected longitudinal muscle - myenteric plexus (LM-MP) tissue. They use standard methods to identify clusters of cells with similar transcriptomes, and designate, based on marker gene expression, two clusters to be neural crest derived enteric neurons (NENs) and mesoderm derived enteric neurons (MENs). However the reviewers raised several issues about the designation of the cells MENs, and therefore their equation with the cells identified in lineage tracing.

While the logic behind specific choices made in the single-cell analysis is not always clear in the manuscript, such as why genes not-specific to MENs were used to identify the MEN cluster and how genes were selected for subsequent analysis (although both issues are explained better in the authors' response to reviewers), they in the end identify a single large cluster that has the characteristics of MENs (it expresses both neuronal and mesodermal markers) that is (by immunohistochemistry) broadly associated with the previously described tissue MENs.

The standard methods for the delineation of clusters in single-cell sequencing data (which the authors use) are stochastic and defy statistical interpretation, and the way these data and analyses are used is often subjective. The editor shares the reviewers' confusion about aspects of the analysis, but also finds the authors' assertions that they have described a cluster of cells that express both neuronal and mesodermal genes, and that this cluster corresponds to the tissue MENs described in lineage tracing, to be broadly sound.

The biggest weakness in the single-cell data and analysis - identified by all reviewers - is the massive overrepresentation of MENs relative to NENs. The authors' explanation - that some cells are more sensitive to manipulations required to prepare cells for sequencing - is certainly well-represented in the literature and is therefore plausible. But it isn't fully satisfactory, especially because it undermines the notion that the MENs and NENs are functionally equivalent (though one could argue in response that increased fragility of NENs is why they are progressively replaced by MENs).

There are many additional questions about the single cell analysis that are difficult to resolve with the data in hand. I think everyone would agree that an ideal analysis would have more cells, deeper sequencing, and comprehensive validation of the identity of each cluster of cells. But given the time and expense required to carry out such experiments, we cannot demand them, and must take the data for what they are rather than what they could be. And in the end, it is the editors' view that these data and analyses bolster the authors' claims, without conclusively establishing them. That is, these data should neither be dismissed nor, on their own, considered definitive.

* Are there alternative explanations for the data than that they are mesodermally derived neurons? *

As discussed above, the reviewers generally agree that the lineage tracing experiments are careful and well-executed, and the authors have provided data that demonstrates that the data are highly unlikely to be due to either incomplete or ectopic lineage marking. The reviewers raise several possible alternative hypotheses, some based on the literature and some based on the genomic data. The authors discuss each in detail in their response. The editor would note that, at this stage in the history of single-cell analysis, the criteria for using single cell sequencing data to establish cell type and cell origin is are not well established, and that neither the presence nor absence of specific sets of genes in single cells should not, for both technical and biological reasons, be considered dispositive as to identity.

* Additional aspects of paper: *

There are additional intriguing aspects of the paper, especially the increase in the number of MENs relative to NENs over time, suggesting functional replacement of one population with the other, and some evidence for and speculation about what might be regulating this evolution. However these are somewhat secondary points relative to the central question at hand of whether the authors have discovered a population of mesodermally derived neurons.

* Editor's summary and comment: *

The editor believes it is a fair summary to say that the authors believe they have gone to great lengths to provide multiple lines of evidence that support their hypothesis, but that these reviewers, while appreciating the potential importance of the authors' discovery of an unusual cell type, are not yet convinced of its origin.

In an ideal world, the authors, reviewers and editor would all ultimately agree on what claims the data presented in a paper supports, and indeed this is what the traditional journal publishing system tries to achieve. But the system fails in cases like this where no consensus between authors and reviewers can be reached, as it neither makes sense to "accept" the paper and imply that it has been endorsed by the reviewers, nor to "reject" it and keep the work in peer review limbo.

There is certainly enough here to warrant the idea and the data and arguments behind it being digested and considered by people in the field. It may very well be that the authors - who have spent years working on this problem and likely know more about this population of cells than anyone on Earth - are right that they have discovered something that changes how we think about the development of the nervous system. To the extent the reviewers are representative, people are likely to need additional data to be convinced. But it is time to put that to the test.

Reviewer #1 (Public Review):

Summary:<br /> The study by Fang et al. reports a 3D MERFISH method that enables spatial transcriptomics for tissues up to 200um in thickness. MERFISH, as well as other spatial transcriptomics technologies, have been mainly used for thin (e.g, 10um) tissue slices, which limits the dimension of spatial transcriptomics technique. Therefore, expanding the capacity of MERFISH to thick tissues represents a major technical advance to enable 3D spatial transcriptomics. Here the authors provide detailed technical descriptions of the new method, troubleshooting, optimization, and application examples to demonstrate its technical capacity, accuracy, sensitivity, and utility. The method will likely have a major impact on future spatial transcriptomics studies to benefit diverse biomedical fields.

Strengths:<br /> The study was well-designed, executed, and presented. Extensive protocol optimization and quality assessments were carried out and conclusions are well supported by the data. The methods were sufficiently detailed and the results are solid and compelling.

Weaknesses:<br /> The biological application examples were limited to cell type/subtype classification in two brain regions. Additional examples of how the data could be used to address important biological questions will enhance the impact of the study.

Reviewer #1 (Public Review):

The authors explain that an action potential that reaches an axon terminal emits a small electrical field as it "annihilates". This happens even though there is no gap junction, at chemical synapses. The generated electrical field is simulated to show that it can affect a nearby, disconnected target membrane by tens of microvolts for tenths of a microsecond. Longer effects are simulated for target locations a few microns away.

To simulate action potentials (APs), the paper does not use the standard Hodgkin-Huxley formalism because it fails to explain AP collision. Instead, it uses the Tasaki and Matsumoto (TM) model which is simplified to only model APs with three parameters and as a membrane transition between two states of resting versus excited. The authors expand the strictly binary, discrete TM method to a Relaxing Tasaki Model (RTM) that models the relaxation of the membrane potential after an AP. They find that the membrane leak can be neglected in determining AP propagation and that the capacitive currents dominate the process.

The strength of the work is that the authors identified an important interaction between neurons that is neglected by the standard models. A weakness of the proposed approach is the assumptions that it makes. For instance, the external medium is modeled as a homogeneous conductive medium, which may be further explored to properly account for biological processes.

The authors provide convincing evidence by performing experiments to record action potential propagation and collision properties and then developing a theoretical framework to simulate the effect of their annihilation on nearby membranes. They provide both experimental evidence and rigorous mathematical and computer simulation findings to support their claims. The work has the potential of explaining significant electrical interaction between nerve centers that are connected via a large number of parallel fibers.

Reviewer #1 (Public Review):

This study provides valuable imaging evidence for the connectopic mapping of the locus coeruleus where a rostro-caudal gradient was linked to heterogeneous functional organisations of the structure. The functional gradient of the LC changes over ageing and reflects capacities of related brain functions. The gradient approach is well-established and solid results were obtained and validated using large 3T and 7T fMRI dataset. The work highlights the importance of using more specific spatial definition of the LC based on distinct connectivity patterns in future resting-state fMRI studies.

Reviewer #1:

The authors have addressed all the comments raised in the previous reviews.

Reviewer #1 (Public Review):

Overall, I quite enjoyed reading the manuscript and found it very well-structured and organized. I congratulate the authors for building this nice research. I do have a few major points to raise, but probably they would not affect the general message of the manuscript.

I was confused about how IUCN data were used. The IUCN predictors are not mentioned in the model equations presented in the manuscript, but their effect size is reported in Figure 2. In the manuscript Methods, it is said that IUCN data was classified into 3 categories. I believe there was a mix of mechanisms in measuring it this way since at least two processes might be underlying IUCN data. First, one can inspect whether there is an effect on "scientific/societal interest" for assessed vs non-assessed species. This would not have any relationship with the assessed status itself. Assessed species are any with LC, NT, VU, EN, CR, EW, EX statuses, whereas non-assessed species might include DD and NE. Second, one may observe an effect of threat status itself, with threatened species being more researched than non-threatened species, this would only be possible for assessed species, although there are methods out there to impute missing statuses. By inspecting Figure 2, I got the feeling that only the second option was explored, but this would need to be confirmed.

In Figure 2, I was confused about the presence of three categories of domain. In the text, it states that four categories have been used. I believe these domains are non-mutually exclusive, that's why there is a fourth category. Would it not be better to assess the influence of domain through three dummy variables (terrestrial, marine, freshwater), where multiple presences (1's) would indicate the "multiple" category?

At present, I felt that the spatial components of your data were unexplored. Since you have centroids representing species distribution, it could be interesting to explore the presence of the species within protected areas or biodiversity hotspots. That might be something triggering at least scientific interest. Also, one can derive information about the major habitat of species occurrence (either using IUCN Major Habitat classification) or extracting overlap of species centroids with WWF biomes (e.g., simplified to just forested vs non-forested habitats; https://ecoregions.appspot.com/). Another point very common to research exploring biodiversity shortfalls is the proximity to research institutions (https://doi.org/10.1111/2041-210X.13152). And since societal interest is also being explored, what about the proximity to major cities (doi:10.1038/nature25181). Finally, other metrics derived from species centroids could inform "tropicality", if the species is tropical or not. Most often, the tropics species are neglected in comparison with those occurring in temperate regions.

I was also thinking about the influence of time on the models. Species described long ago are often more known to people and scientists and had more "time" to be researched. Although metrics of societal interest were restricted to the last decade here, that does not necessarily mean that peoples' interest is not affected by their accumulated experiences. Similar reasoning applies to scientific interests, which have a lengthier time frame (~80 years). That said, the year of description or time since description could be added to capture some metric of time.

Model residuals could be checked for phylogenetic or spatial autocorrelation. I am aware there is no phylogenetic tree used, but the hierarchical taxonomy could be used (Phylum / Class / Order / Family / Genus) as a proxy for phylogenetic relationship. Concerning the spatial autocorrelation, one could check whether model residuals and their respective coordinate centroids of each species range. It is stated that GLMM has been used to avoid these non-independence issues, but it would be interesting to check whether residuals remained free of them.

A last point, it would be interesting to provide some sort of inset plots, such as barplots or donut plots (within the current plots), showing the proportion of species with respect to major clades and biogeographical regions.

Reviewer #1 (Public Review):

This manuscript presents SAVEMONEY, a computational tool designed to enhance the utilization of Oxford Nanopore Technologies (ONT) long-read sequencing for the design and analysis of plasmid sequencing experiments. In the past few years, with the improvement in both sequencing length and accuracy, ONT sequencing is being rapidly extended to almost all omics analyses which are dominated by short-read sequencing (e.g., Illumina). However, relatively higher sequencing errors of long-read sequencing techniques including PacBio and ONT is still a major obstacle for plasmid/clone-based sequencing service that aims to achieve single base/nucleotide accuracy. This work provides a guideline for sequencing multiple plasmids together using the same ONT run without molecular barcoding, followed by data deconvolution. The whole algorithm framework is well-designed, and some real data and simulation data are utilized to support the conclusions. The tool SAVEMONEY is proposed to target users who have their own ONT sequencers and perform library preparation and sequencing by themselves, rather than relying on commercial services. As we know and discussed by the authors, in the real world, to ensure accuracy, the researchers will routinely pick up multiple colonies in the same plasmid construction and submit for Sanger sequencing. However, SAVEMONEY is not able to support the simultaneous analysis of multiple colonies in the same run, as compared to the barcoding-based approaches. This is a major limitation in the significance of this work. Encouraging computational efforts in ONT data debarcoding for mixed-plasmid or even single-cell sequencing would be more valuable in the field.

1. To provide more comprehensive information for users who care about the cost, the Introduction section should include a cost comparison between Sanger and ONT, with more details, such as different ONT platforms (MinION, PromethION, FlongIe), chemistries (flow cells) and kits. This additional information will be more helpful and informative for the users who have their own sequencers and are the target audience for SAVEMONEY.

2. In "Overview of the algorithm" (Pages 3-4) under the Results section, instead of stating "However, coverage varies from ~100-1000 and is difficult to predict because each nanopore flow cell has different properties.", it will be beneficial to provide more detailed information, such as sequencing length, yield/read count per flow cell of different platforms. This information will assist users in designing their own experiments effectively.

3. While this study optimized and evaluated the tool using a total of 14 plasmids, it may not provide sufficient power to represent the diversity of the plasmid world. Consideration should be given to expanding the dataset to include a broader range of plasmids in future studies to enhance the robustness and generalizability of the tool.

4. If applicable and feasible, including a comparison or benchmark of SAVEMONEY against other similar tools would further strengthen the manuscript. This comparison would allow users to evaluate the advantages and disadvantages of different tools for their specific needs.

5. The importance of pre-filtering raw sequencing reads should be emphasized as noisy reads can significantly impact the overall performance of the tool. It is essential to clarify whether any pre-filtering steps were performed in this study, such as filtering based on quality scores, read length, or other relevant factors.

6. The statement regarding the number of required reads per plasmid (20-30) and the maximum number of plasmids (up to six) that can be mixed in a single run may become outdated due to the rapid advancements in ONT technology. In the Discussion section, instead of assuming specific numbers, it would be more beneficial to provide information based on the current state of ONT sequencing, such as the number of reads per MinION flow cell that can be produced.

Reviewer #1 (Public Review):

This study aims to identify gene expression differences exclusively caused by cis-regulatory genetic changes by utilizing hybrid cell lines derived from human and chimpanzee. While previous attempts have focused on specific tissues, this study expands the comparison to six different tissues to investigate tissue specificity and derive insights into the evolution of gene expression.

One notable strength of this work lies in the use of composite cell lines, enabling a comparison of gene expression between human and chimpanzee within the same nucleus and shared trans factors environment. However, a potential weakness of the methodology is the use of bulk RNA-seq in diverse tissues, which limits the ability to determine cell-type-specific gene expression and chromatin accessibility regions.

Another concern is the use of two replicates derived from the same pair of individuals. While the authors produced cell lines from two pairs of individuals in a previous study (Agloglia et al., 2021), I wonder why only one pair was used in this study. Incorporating interindividual variation would enhance the robustness of the species differences identified here.

Furthermore, the study offers the opportunity to relate inter-species differences to trends in molecular evolution. The authors discovered that expression variance and haploinsufficiency score do not fully account for the enrichment of divergence in cell-type-specific genes. The reviewer suggests exploring this further by incorporating external datasets that bin genes based on interindividual transcriptomics variation as a measure of extant transcriptomics constraint (e.g., GTEx reanalysis by Garcia-Perez et al., 2023 - PMID: 36777183). Additionally, stratifying sequence conservation on ASCA regions, which exhibit similar enrichment of cell-type-specific features, using the Zoonomia data mentioned also in the text (Andrews et al., 2023 -- PMID: 37104580) could provide valuable insights.

Another potential strength of this study is the identification of specific cases of paired allele-specific expression (ASE) and allele-specific chromatin accessibility (ASCA) with biological significance. Prioritizing specific variants remains a challenge, and the authors apply a machine-learning approach to identify potential causative variants that disrupt binding sites in two examples (FABP7 and GAD1 in motor neurons). However, additional work is needed to convincingly demonstrate the functionality of these selected variants. Strengthening this section with additional validation of ASE, ASCA, and the specific putative causal variants identified would enhance the overall robustness of the paper.

Additionally, the authors support the selected ASE-ASCA pairs by examining external datasets of adult brain comparative genomics (Ma et al., 2022) and organoids (Kanton et al., 2019). While these resources are valuable for comparing observed species biases, the analysis is not systematic, even for the two selected genes. For example, it would be beneficial to investigate if FABP7 exhibits species bias in any cell type in Kanton et al.'s organoids or if GAD1 is species-biased in adult primate brains from Ma et al. Comparing these datasets with the present study, along with the Agoglia et al. reference, would provide a more comprehensive perspective.

The use of the term "human-derived" in ASE and ASCA should be avoided since there is no outgroup in the analysis to provide a reference for the observed changes.

Finally, throughout the paper, the authors refer to "hybrid cell lines." It has been suggested to use the term "composite cell lines" instead to address potential societal concerns associated with the term "hybrid," which some may associate with reproductive relationships (Pavlovic et al., 2022 -- PMID: 35082442). It would be interesting to know the authors' perspective on these concerns and recommendations presented in Pavlovic et al., given their position as pioneers in this field.

Reviewer #1 (Public Review):

The manuscript by Hariani et al. presents experiments designed to improve our understanding of the connectivity and computational role of Unipolar Brush Cells (UBCs) within the cerebellar cortex, primarily lobes IX and X. The authors develop and cross several genetic lines of mice that express distinct fluorophores in subsets of UBCs, combined with immunocytochemistry that also distinguishes subtypes of UBCs, and they use confocal microscopy and electrophysiology to characterize the electrical and synaptic properties of subsets of so-labelled cells, and their synaptic connectivity within the cerebellar cortex. The authors then generate a computer model to test the possible computational functions of such interconnected UBCs.

Using these approaches, the authors report that:

1) GRP-driven TDtomato is expressed exclusively in a subset (20%) of ON-UBCs, defined electrophysiologically (excited by mossy fiber afferent stimulation via activation of UBC AMPA and mGluR1 receptors) and immunocytochemically by their expression of mGluR1.

2) UBCs ID'd/tagged by mCitrine expression in Brainbow mouse line P079 are expressed in a similar minority subset of OFF-UBCs defined electrophysiologically (inhibited by mossy fiber afferent stimulation via activation of UBC mGluR2 receptors) and immunocytochemically by their expression of Calretinin. However, such mCitrine expression was also detected in some mGluR1 positive UBCs, which may not have shown up electrophysiologically because of the weaker fluorophore expression without antibody amplification.

3) Confocal analysis of crossed lines of mice (GRP X P079) stained with antibodies to mGluR1 and calretinin documented the existence of all possible permutations of interconnectivity between cells (ON-ON, ON-OFF, OFF-OFF, OFF-ON), but their overall abundance was low, and neither their absolute nor relative abundance was quantified.

4) A computational model (NEURON ) indicated that the presence of an intermediary UBC (in a polysynaptic circuit from MF to UBC to UBC) could prolong bursts (MF-ON-ON), prolong pauses (MF-ON-OFF), cause a delayed burst (MF-OFF-OFF), cause a delayed pause (MF-OFF-ON) relative to solely MF to UBC synapses which would simply exhibit long bursts (MF-ON) or long pauses (MF-OFF).

The authors thus conclude that the pattern of interconnected UBCs provides an extended and more nuanced pattern of firing within the cerebellar cortex that could mediate longer-lasting sensorimotor responses.

The cerebellum's long-known role in motor skills and reflexes, and associated disorders, combined with our nascent understanding of its role in cognitive, emotional, and appetitive processing, makes understanding its circuitry and processing functions of broad interest to the neuroscience and biomedical community. The focus on UBCs, which are largely restricted to vestibular lobules of the cerebellum reduces the breadth of likely interest somewhat. The overall design of specific experiments is rigorous and the use of fluorophore expressing mouse lines is creative. The data that is presented and the writing are clear. However, the overall experimental design has issues that reduce overall interpretation (please see specific issues for details), which combined with a lack of thorough analysis of the experimental outcomes severely undermines the value of the NEURON model results and the advance in our understanding of cerebellar processing in situ (again, please see specific issues for details).

Specific issues:<br /> 1) All data gathered with inhibition blocked. All of the UBC response data (Fig. 1) was gathered in the presence of GABAAR and Glycine R blockers. While such an approach is appropriate generally for isolating glutamatergic synaptic currents, and specifically for examining and characterizing monosynaptic responses to single stimuli, it becomes problematic in the context of assaying synaptic and action potential response durations for long-lasting responses, and in particular for trains of stimuli, when feed-forward and feed-back inhibition modulates responses to afferent stimulation. That is, even for single MF stimuli, given the >500ms duration of UBC synaptic currents, there is plenty of time for feedback inhibition from Golgi cells (or feedforward, from MF to Golgi cell excitation) to interrupt AP firing driven by the direct glutamatergic synaptic excitation. This issue is compounded further for all of the experiments examining trains of MF stimuli. Beyond the impact of feedback inhibition on the AP firing of any given UBC, it would also obviously reduce/alter/interrupt that UBC's synaptic drive of downstream UBCs. This issue fundamentally undermines our ability to interpret the simulation data of Vm and AP firing of both the modeled intermediate and downstream UBC, in terms of applying it to possible cerebellar cortical processing in situ.

2) No consideration for the involvement of polysynaptic UBCs driving UBC responses to MF stimulation in electrophysiology experiments. Given the established existence (in this manuscript and Dino et al. 2000 Neurosci, Dino et al. 2000 ProgBrainRes, Nunzi and Mugnaini 2000 JCompNeurol, Nunzi et al. 2001 JCompNeurol) of polysynaptic connections from MFs to UBCs to UBCs, the MF evoked UBC responses established in this manuscript, especially responses to trains of stimuli could be mediated by direct MF inputs, or to polysynaptic UBC inputs, or possibly both (to my awareness not established either way). Thus the response durations could already include extension of duration by polysynaptic inputs, and so would overestimate the duration of monosynaptic inputs, and thus polysynaptic amplification/modulation, observed in the NEURON model.

3) Lack of quantification of subtypes of UBC interconnectivity. Given that it is already established that UBCs synapse onto other UBCs (see refs above), the main potential advance of this manuscript in terms of connectivity is the establishment and quantification of ON-ON, ON-OFF, OFF-ON, and OFF-OFF subtypes of UBC interconnections. But, the authors only establish that each type exists, showing specific examples, but no quantification of the absolute or relative density was provided, and the authors' unquantified wording explicitly or implicitly states that they are not common. This lack of quantification and likely small number makes it difficult to know how important or what impact such synapses have on cerebellar processing, in the model and in situ.

4) Lack of critical parameters in NEURON model.<br /> A) The model uses # of molecules of glutamate released as the presumed quantal content, and this factor is constant. However, no consideration of changes in # of vesicles released from single versus trains of APs from MFs or UBCs is included. At most simple synapses, two sequential APs alters release probability, either up or down, and release probability changes dynamically with trains of APs. It is therefore reasonable to imagine UBC axon release probability is at least as complicated, and given the large surface area of contact between two UBCs, the number of vesicles released for any given AP is also likely more complex.<br /> B) the model does not include desensitization of AMPA receptors, which in the case of UBCs can paradoxically reduce response magnitude as vesicle release and consequent glutamate concentration in the cleft increases (Linney et al. 1997 JNeurophysiol, Lu et al. 2017 Neuron, Balmer et al. 2021 eLIFE), as would occur with trains of stimuli at MF to ON-UBCs.

5) Lack of quantification of various electrophysiological responses. UBCs are defined (ON or OFF) based on inward or outward synaptic response, but no information is provided about the range of the key parameter of duration across cells, which seems most critical to the current considerations. There is a similar lack of quantification across cells of AP duration in response to stimulation or current injections, or during baseline. The latter lack is particularly problematic because, in agreement with previous publications, the raw data in Fig. 1 shows ON UBCs as quiescent until MF stimulation and OFF UBCs firing spontaneously until MF stimulation, but, for example, at least one ON UBC in the NEURON model is firing spontaneously until synaptically activated by an OFF UBC (Fig. 11A), and an OFF UBC is silent until stimulated by a presynaptic OFF UBC (Fig. 11C). This may be expected/explainable theoretically, but then such cells should be observed in the raw data.

Reviewer #1 (Public Review):

This study is one of several around the world to investigate how urban wildlife responded to changes in human activity during the lockdowns associated with the COVID-19 pandemic. Unlike several other studies on the topic that used observational data from citizen science programs, this project relied on passive acoustic monitoring to record bird vocalizations during and after stringent lockdown periods in an urban environment. The authors focused on three species that differ in their level of adaptation to human presence, providing an ecologically relevant comparison that highlights the importance of micro-habitats for species living in close proximity to humans.

Strengths:

The element that most sets this study apart from previous studies examining responses to COVID-19 lockdowns is the use of passive acoustic monitoring. As the authors describe, this method offers several advantages over other methods (though, it does come with some limitations on what questions can be addressed). Perhaps the most relevant advantage is that it offers the ability to concurrently measure anthropogenic noise in the environment, which is one of the most likely mechanisms for human activity changes effects on wildlife. To my knowledge, only one other study (Derryberry et al. Science. 2020) has used recordings of vocalizations to examine the influence of COVID-19 lockdowns on birds. (Note, while these authors do reference Derryberry et al., I thought that there could have been much more direct comparison between the results of the two approaches).

It was encouraging to see a study that focused on local-scale impacts of lockdowns, with methods that could investigate effects within microhabitats. Logistics prevented many other projects from operating at such fine scales. These data also came from a country/municipality that had very defined lockdown periods known with certainty to the day (as opposed to a gradual shift in voluntary human activity, as occurred in much of North America), making the results from this study particularly useful for the examination of rapid changes in bird behavior.

Weaknesses:

One important drawback of the approach, which potentially calls into question the authors' conclusions, is that the acoustic sampling only occurred during the pandemic: for several lockdown periods and then for a period of 10 days immediately after the end of the final lockdown period in May of 2020. Several relevant things changed from March to May of 2020, most notably the shift from spring to summer, and the accompanying shift into and through the breeding season (differing for each of the three focal species). Although the statistical methods included an attempt to address this, neither the inclusion of the "count down" variable nor the temperature variable could account for any non-linear effects of breeding phenology on vocal activity. I found the reliance on temperature particularly troubling, because despite the authors' claims that it was "a good proxy of seasonality", an examination of the temperature data revealed a considerable non-linear pattern across much of the study duration. In addition, using a period immediately after the lockdowns as a "no-lockdown" control meant that any lingering or delayed effects of human activity changes in the preceding two months could still have been relevant (not to mention the fact that despite the end of an official lockdown, the pandemic still had dramatic effects on human activity during late May 2020).

Another weakness of the current version of the manuscript is the use of a supposed "contradiction" in the existing literature to create the context for the present study. Although the various studies cited do have many differences in their results, those other papers lay out many nuanced hypotheses for those differences. Almost none of the studies cited in this manuscript actually reported blanket increases or decreases in urban birds, as suggested here, and each of those papers includes examples of species that showed different responses. To suggest that they are on opposite sides of a supposed dichotomy is a misrepresentation. Many of those other studies also included a larger number of different species, whereas this study focused on three. Finally, this study was completed at a much finer spatial scale than most others and was examining micro-habitat differences rather than patterns apparent across landscapes. I believe that highlighting differences in scale to explain nuanced differences among studies is a much better approach that more accurately adds to the body of literature.

Reviewer #1 (Public Review):

The manuscript is very-well written. Although the study is well-conducted the authors should be more convincing on how bacteria residing in tissues do not induce death. The association with IL-10 cytokine production appears weak and more experiments are needed to make it more robust.

Reviewer #1 (Public Review):

The goal of this study is to understand the allosteric mechanism of overall activity regulation in an anaerobic ribonucleotide reductase (RNR) that contains an ATP-cone domain. Through cryo-EM structural analysis of various nucleotide-bound states of the RNR, the mechanism of dATP inhibition is found to involve order-disorder transitions in the active site. These effects appear to prevent substrate binding and a radical transfer needed to initiate the reaction.

Strengths of the manuscript include the comprehensive nature of the work - including numerous structures of different forms of the RNR and detailed characterization of enzyme activity to establish the parameters of dATP inhibition. The manuscript could be improved, however, by performing additional experiments to establish that the mechanism of inhibition can be observed in other contexts and it is not an artifact of the structural approach. Additionally, some of the presentations of biochemical data could be improved to comply with standard best practices.

The work is impactful because it reports initial observations about a potentially new mode of allosteric inhibition in this enzyme class. It also sets the stage for future work to understand the molecular basis for this phenomenon in more detail.

General comments:

1) It would be ideal to perform an additional experiment of some type to confirm the order-disorder phenomena observed in the cryo-EM structures to rule out the possibility that it is an artifact of the structure determination approach. Circular dichroism might be a possibility?

2) Does the disordering phenomenon of one subunit in the ATP-bound structures have any significance - could it be related to half-of-sites activity? Does this RNR exhibit half-of-sites activity?

3) Does the disordering of the GRD with dATP bound have any long-term impact on the stability of the Gly radical? I realize that the authors tested the ability to form the Gly radical in the presence of dATP in Fig. 4 of the manuscript. But it looks like they only analyzed the samples after 20 min of incubation. Were longer time points analyzed?

4) Did the authors establish whether the effect of dATP inhibition on substrate binding is reversible? If dATP is removed, can substrates rebind?

5) In some figures (Fig. 6e, for example), the cryo-EM density map for the nucleotide component of the model is not continuous over the entire molecule. Can the authors comment on the significance of this phenomenon? Were the ligands validated in any way to ensure that the assignments were made correctly?

Reviewer #1 (Public Review):

In this work, the authors have investigated the relationship between Carotenoid pigment depletion in the photosynthesis-related light harvesting complex, the assembly of the prokaryotic reaction center LH complex, and quinone exchange in Roseiflexus castenholzii, a chlorosome-less filamentous anoxygenic phototroph that forms the deepest branch of photosynthetic bacteria. By means of different biochemical and biophysical techniques, including cryo-electron microscopy of the purified RC-LH complexes with or depleted of carotenoids, the authors provide evidence of the structural basis by which Carotenoid assembly regulates the architecture and quinone exchange of bacterial RC-LH 40 complexes. Although most of the experiments described in this manuscript are structural, by analyzing Cryo-MS results, the authors also propose some predictions about the functional roles of proteins/pigments in LH complex, such as the role of the gap in the ring that persists without a canonical subunit X. Together, the results presented are important to understand the evolution and diversity of prokaryotic photosynthetic apparatus.

Reviewer #1 (Public Review):

A modelling study was conducted to estimate how disruption of a school-based HPV vaccination program due to COVID-19 restrictive measures might affect lifetime HPV-related cancers in women and men in Australia. The authors used the Policy 1-Cervix model, which has been validated and widely used for modelling and evaluation of interventions to prevent HPV- related disease. The study shows that a large part of the negative effect of disrupting the vaccination program (in terms of HPV-related cancers) can be overcome by a catch-up campaign, if this is undertaken rapidly. Delays in the catch-up campaign or no catch-up lead, according to the model, to a significant increase in the number of cases, of which a proportion could be prevented by cervical cancer screening, provided that this is carried out for cohorts that receive HPV 9 without alterations.

1. Strengths:<br /> Well-designed modelling study, comparing several scenarios: baseline (no interruption of vaccination), catch-up with two modalities, and no catch-up vaccination, with a comparator (no vaccination at all), aiming to predict the number of HPV-related cancers for the various scenarios. Indeed, the study investigates the potential impact of disruptions, broken down into types of cancers, in both men and women. However, as always in modelling studies, the strength of the findings depends on the appropriateness and completeness of the assumptions used.

2. Weaknesses:<br /> Although the authors claim to have considered sexual behaviour they fail to show how they exactly did this. It is very likely that restrictive measures have had an impact on sexual behaviour (i.e. transmission of HPV), but the authors did not consider this in the model. Furthermore, the baseline scenario uses a higher 2-dose vaccination uptake than the figures they present for 2020, which might have overestimated the impact of HPV vaccination in that year.

Reviewer #1 (Public Review):

Gosh and colleagues report on their multidisciplinary effort to improve cervical cancer screening attendance in the East Boston Neighborhood Health Center (March-August 2021). Specifically, the authors 1) identified using electronic medical records overdue follow-up visits, 2) scheduled screening appointments during regular clinic hours and weekends/evenings, and 3) surveyed patients on their experience. These objectives were clearly defined (although not consistently so throughout the manuscript) and data analyses/presentation were simple and straightforward, appropriate to the study design and methodology used.

Overall, it is unclear to what extent the overdue appointments were backlogs created by the COVID-19 pandemic or due to pre-pandemic factors that could have been exacerbated by the pandemic. In order to contextualize the current study and its findings, an elaboration is needed on whether the pandemic created the delays in cervical cancer screening or simply compounded the problem. For example, the authors report on page 8, lines 196-197 that in 30% of encounters (not clear how many of the 118 reviewed charts were overdue appointments) the healthcare provider did note the overdue appointments. A breakdown of the "time delays" (i.e., beyond x number of months) would also inform the analyses and study implications. In addition, a brief description of the cervical cancer screening program in place would be informative. Table 1 provides an effort versus value summary, however, these constructs are ill-defined, with few inconsistencies with what is reported in the text.

Comments specific to Aim 1:<br /> The methodology is missing information on key elements, mainly relating to the decision-making process of establishing and defining the "validated" patient chart list (1375 overdue patients out of 6126 reviewed charts). A chart of the 1375 approached study population is also warranted (459 patients were screened, 622 could not be reached, and 203 cancelled/missed their appointments, what about the remaining 91 patients). A description of the characteristics of the study population and a comparison of the different groups (screened, not reached, cancelled/missed appointment) along these characteristics are missing.

Comments specific to Aim 2:<br /> About 63% of the 459 scheduled screenings were done during the evening/weekend clinics, which represents a substantial gain and clearly indicates a window of opportunity to increase screening rates by pinpointing the importance of offering a convenient time to women attend screening visits. In general, and as expected, offering additional screening clinics was effective in addressing the backlog of patients, although with significant investment and resources as mentioned by the authors. How significant is significant?

Comments specific to Aim 3:<br /> A more structured and detailed presentation/description of the survey instrument, its administration, response rate, and significance of results are warranted in the manuscript, albeit the joint reporting of this in the appended material.

Reviewer #1 (Public Review):

Tian et al impressively record from two motor areas at once in singing birds to test if a premotor cortical area, LMAN, covaries with activity in a primary one, RA, in a way that would support learning. They find that LMAN activity covaries with RA activity at a lag consistent with driving a premotor bias and, moreover, that this covariation is significantly increased in the specific time window of the song where bias is being most strongly driven. Disruptive microstimulation of LMAN in this window reduced learning-associated bias. Though the main results in this paper are consistent with dominant models of birdsong production and learning going back decades (e.g. Kao et al, 2005; Olveczky et al, 2005; Andalman et al, 2008; Charlesworth et al, 2009; Fee and Goldberg, 2011), these results provide methodologically impressive confirmation that LMAN drives RA activity to drive adaptive bias. It's also meaningful that these covariations were strong enough to be picked up by a pair of randomly targeted LMAN and RA sites. This feature of their dataset is not emphasized by the authors but invites more attention, consideration, and discussion, as detailed below.

(1) Song is complex with many varying acoustic parameters, such as amplitude, entropy, and pitch. It is thought that pitch is controlled by only a subset of the syringeal muscles, and also that there is topography in the LMAN-RA-MN-muscle pathway. Thus, one might expect only a small fraction of neurons/sites in the LMAN-RA pathway to be associated with pitch with enough strength that one would pick it up in single unit recordings from order ~100 syllables. Indeed a past study (Sober et al, ) found that activity in a small fraction of RA neurons was weakly correlated with pitch variation. So it's really surprising that a pitch-contingent learning paradigm produced significant co-variance changes in the LMAN-RA pathway that could be picked up in the present study. Three possible explanations are with consideration. First, one wonders if they were recording specifically from pitch-associated sites. Can the authors please elaborate on what fraction of LMAN and RA recording sites in the present study exhibited significant covariance with pitch? Second, if an LMAN-RA recording site pair does not exhibit a significant correlation with pitch but nonetheless exhibits enhanced co-variation in the pre-target window in a pitch shift paradigm, this would support a different interpretation of the results. For example, it's possible that the extent by which LMAN can drive RA is gated by cholinergic inputs from VP, which might signal predicted uncertainty in the song in the precise moment preceding the target time (e.g. Chen and Goldberg, 202; Chen et al, 2019; Puzerey et al, 2018). No new experiments are required here, but these possibilities (or other considerations of the mechanisms by which LMAN-RA covariance is temporally gated) could, in the discussion or elsewhere, motivate future studies. (For example, if Ach-mediated predicted uncertainty is the key to promoting LMAN-RA covariance, then photoactivation of Ach inputs to RA at a moment in song might increase LMAN drive and, secondly, non-pitch-contingent DAF that does not drive explicitly learning associated bias would also be sufficient to promote temporally precise increases in LMAN-RA covariance. Finally, related to these questions, can the authors please check if their recording sites exhibited correlations with pitch (e.g. as in Sober et al, 2008)?

2. Multiple recording sites in both RA and LMAN provide sensible internal controls for the cross-covariance and its increase in the window before bias production in pitch-shift experiments. Can the authors analyze at LMAN-LMAN co-variance in the same way to test for LMAN-RA co-variance to examine intra-LMAN activity co-flucutations? A negative result would support the specificity of the LMAN-RA covariance but a positive result would indicate that within-LMAN dynamics also exhibit interesting learning-related changes.

Reviewer #1 (Public Review):

Pentz et al experimentally evolve yeast populations starting from two different strains that each differ in one locus compared to the wild-type. They show that these small differences - which result in one strain forming clonal groups, while the other forms multi-strain aggregates of different genotypes - can change the evolutionary fate of the strain under their selection regime. In their evolutionary experiment, they select for growth (an individual trait) and then sedimentation (a group trait) and show that the strain that makes clonal groups evolves a greater improvement in their group trait, while the strain that forms genetically diverse groups evolves a greater improvement in their individual trait. This provides experimental evidence for the hypothesis that clonality is key to the evolution of group traits, and potentially, multicellularity. They support their findings with genomic analysis of the mutants and use a mathematical model to explain some of the interesting observations from this analysis: that selection is stronger in genotypically mixed groups, while clonal groups suffer more from drift and bottlenecking effects. The study presents solid evidence for the findings, the methods are simple and clear, the scale of the experiment is impressive, the data analyses support the conclusions and are very complete and convincing, and the paper is very clearly written and a pleasure to read.

Reviewer #1 (Public Review):

In this manuscript, Yang et al. investigated the mechanisms by which a high-sugar diet induces transgenerational changes in sweet sensitivity and feeding behavior. The authors identified an epigenetic mechanism that involves H3K27me3 reprogramming. Moreover, the authors found that such transgenerational behavioural change was transmitted through maternal epigenetic mechanisms. Through sequencing, the authors identified the specific genetic target of such epigenetic modification and further revealed a key neural target that is influenced by such genetic change and is critical for sweet-sensing. Together, this manuscript provided a significant advance in understanding food-induced transgenerational changes in Drosophila. The experiments were carefully designed with proper controls and well executed. The data is convincing and the findings are novel.

Reviewer #1 (Public Review):

This is an interesting paper that shows disruption of thalamocortical communication in anesthesia, and enhancement under 5-MeO-DMT in an animal model, combined with a model to establish that these changes can be understood as a displacement from a critical point of a neural mass model. Overall, these results are exciting as they constitute evidence that very different brain states can be understood as two different points of a continuum of states, with a critical transition point in the middle.

These are my main detailed comments about this manuscript:

1. Psychedelic drug dosage: 5 mg/kg is possibly a low dose of 5-MeO-DMT, which exhibits nonlinear pharmacokinetics presenting a transition in drug serum concentration between 2 mg/kg and 10 mg/kg. (Shen, H. W., Jiang, X. L., & Yu, A. M. (2011). Nonlinear pharmacokinetics of 5-methoxy-N, N-dimethyltryptamine in mice. Drug Metabolism and Disposition, 39(7), 1227-1234.)

2. Novelty of the neural mass approach to establish critical dynamics. The neural mass model is interesting but it is also well established that the features of LFPs during anesthesia can be captured using these kinds of models, including phenomenology such as burst suppression, emergence of high amplitude synchronized oscillations, etc.; see for instance Kuhlmann, L., Freestone, D. R., Manton, J. H., Heyse, B., Vereecke, H. E., Lipping, T., ... & Liley, D. T. (2016). Neural mass model-based tracking of anesthetic brain states. NeuroImage, 133, 438-456.). The same applies to the modeling of wakefulness LPF using neural masses to show that alpha oscillations emerge in thalamocortical systems at the edge of a dynamic phase transition, which can be reproduced by the dynamics of a Hopf bifurcation.

3. Is it possible that some of the results in the essential tremor group were influenced by the disease and its effects on the LPF dynamics, as it is known that tremors and seizures are associated by themselves with departures from critical dynamics?

4. Table 1 and other parts of the manuscript: multiple independent tests were conducted, does this require a correction for multiple comparisons to avoid the reporting of false positive results or its control by FDR or related approaches?

Reviewer #1 (Public Review):

Davies et al. examined the role of the malaria parasite's FIKK4.1 protein kinase in trafficking and host membrane insertion of key proteins that are exported by the intracellular P. falciparum parasite. FIKK4.1 is one of 18 FIKK serine/threonine kinases exported into the host erythrocyte; these kinases phosphorylate both host proteins and exported parasite proteins. FIKK4.1 has previously been implicated in rigidification of the erythrocyte cytoskeleton. It is also known to affect trafficking and insertion of PfEMP1, the parasite's primary cytoadherence ligand, on the host cell surface. In the present studies, the authors perform sophisticated gene-editing experiments that combine conditional knockout of FIKK4.1 with tagging of two kinase targets with the TurboID proximity biotin-labeling enzyme to explore phosphorylation-dependent changes in target protein localization, structure, or protein-protein interactions. Using conditional knockout of each exported FIKK kinase, they determine that FIKK4.1 is the only kinase that regulates PfEMP1 surface exposure and that it does not appear to modulate surface translocation of RIFINs, a family of parasite antigens involved in immune evasion. The combination of gene-editing, proximity labeling and mass spectrometry, and biochemical studies in the paper is to be lauded. These findings identify key targets of exported kinases and will guide future studies of host cell remodeling.

Key limitations of the study:

1. TurboID tagging of FIKK4.1 followed by proximity labeling and mass spectrometry of biotinylated proteins revealed parasite-stage dependent labeling of 101 parasite proteins and 39 human proteins that come in contact with FIKK4.1. Although TurboID is a more efficient biotin ligase produced through directed evolution, nonspecific biotinylation of proteins that do not form biologically relevant interactions remains an issue. Biotin addition for 4 hours, as used here and in most studies using this ligase, allows for labeling of proteins that undergo random collisions with the TurboID-tagged protein. While there was clear enrichment of exported proteins in the FIKK4.1-tagged parasite at mature schizont stages when FIKK4.1 is in the host cytosol, only 66% of the proteins labeled were exported, consistent with labeling and recovery of irrelevant proteins. As the authors performed appropriate controls and interpreted their findings cautiously, this limitation results primarily from finite efficiency of TurboID, trace levels of endogenous biotin within cells, and other complexities associated with the technology.

2. The production of dual-edited parasites carrying conditional knockout of FIKK4.1 and TurboID tagging of either KAHRP or PTP4 permitted examination of changes in localization of exported proteins upon their phosphorylation by FIKK4.1. KAHRP and PTP4 are excellent choices for these experiments because they are established targets of the kinase and good candidates for effectors involved in PfEMP1 membrane insertion. Some 30-40 proteins exhibited significant changes in biotinylation by these TurboID-tagged proteins, suggesting altered localization or structure upon loss of FIKK4.1 kinase activity. PfEMP1 trafficking proteins (PTPs), Maurer's cleft proteins, exported heat shock proteins, and components of PSAC, a parasite-associated nutrient uptake channel, all exhibited changes. Although FIKK4.1 is not essential for in vitro parasite propagation, altered localization could result either directly from changes in phosphorylation status of the protein itself or could reflect indirect effects on the cell from loss of FIKK4.1.

3. As a consequence of these two limitations, these experiments could not conclusively implicate either KAHRP or a specific PTP in PfEMP1 surface translocation. Whether specific Maurer's cleft proteins or the nutrient channel components contribute to PfEMP1 surface translocation could also not be addressed. The authors' Discussion section is appropriately cautious in interpreting changes in biotinylation upon FIKK4.1 disruption. Although a large amount of data has been generated in this sophisticated study, the precise mechanism of PfEPM1 trafficking and membrane insertion remains elusive.

• for: W2W, carbon inequality, carbon footprint - 1%, carbon emissions - 1%, luxury advertising, luxury advertising contracts, carbon emissions - luxury goods
• key insight
  • the elites are often the main popularizers, influencers and propagandists of the fantasy of overconsumption
  • culture of overconsumption
  • such elites have a close tie to the luxury industry via large advertising contracts
  • Media posts critical of the carbon air travel emissions of famous DJ named DJ Snake offers a prime example of a common attitude of privilege and self-righteousness found amongst a number of elites

Reviewer #1 (Public Review):

The authors set out to develop an organoid model of the junction between early telecephalic and ocular tissues to model RGC development and pathfinding in a human model. The authors have succeeded in developing a robust model of optic stalk(OS) and optic disc(OD) tissue with innervating retinal ganglion cells. The OS and OD have a robust pattern with distinct developmental and functional borders that allow for a distinct pathway for pathfinding RGC neurites.

Future work targeting RGC neurite outgrowth mechanisms will be exciting.

Reviewer #1 (Public Review):

Summary<br /> In this study, Xu et al. provide insights into the substrate divergence of CASP3 and CASP7 for GSDME cleavage and activation during vertebrate evolution vertebrates. Using biochemical assays, domain swapping, site-directed mutagenesis, and bioinformatics tools, the authors demonstrate that the human GSDME C-terminal region and the S234 residue of human CASP7 are the key determinants that impede the cleavage of human GSDME by human CASP7.

Strengths<br /> The authors made an important contribution to the field by demonstrating how human CASP7 has functionally diverged to lose the ability to cleave GSDME and showing that reverse-mutations in CASP7 can restore GSDME cleavage. The use of multiple methods to support their conclusions strengthens the authors' findings. The unbiased mutagenesis screen performed to identify S234 in huCASP7 as the determinant of its GSDME cleavability is also a strength.

Weaknesses<br /> While the authors utilized an in-depth experimental setup to understand the CASP7-mediated GSDME cleavage across evolution, the physiological relevance of their findings are not assessed in detail. Additional methodology information should also be provided.

Specific recommendations for the authors<br /> 1. The authors should expand their evaluation of the physiological relevance by assessing GSDME cleavage by the human CASP7 S234N mutant in response to triggers such as etoposide or VSV, which are known to induce CASP3 to cleave GSDME (PMID: 28045099). The authors could also test whether the human CASP7 S234N mutation affects substrate preference beyond human GSDME by testing cleavage of mouse GSDME and other CASP3 and CASP7 substrates in this mutant.<br /> 2. It would also be interesting to examine the GSDME structure in different species to gain insight into the nature of mouse GSDME, which cannot be cleaved by either mouse or human CASP7.<br /> 3. The evolutionary analysis does not explain why mammalian CASP7 evolved independently to acquire an amino acid change (N234 to S234) in the substrate-binding motif. Since it is difficult to experimentally identify why a functional divergence occurs, it would be beneficial for the authors to speculate on how CASP7 may have acquired functional divergence in mammals; potentially this occurred because of functional redundancies in cell death pathways, for example.<br /> 4. For the recombinant proteins produced for these analyses, it would be helpful to know whether size-exclusion chromatography was used to purify these proteins and whether these purified proteins are soluble. Additionally, the SDS-PAGE in Figure S1B and C show multiple bands for recombinant mutants of TrCASP7 and HsCASP7. Performing protein ID to confirm that the detected bands belong to the respective proteins would be beneficial.<br /> 5. For Figures 3C and 4A, it would be helpful to mention what parameters or PDB files were used to attribute these secondary structural features to the proteins. In particular, in Figure 3C, residues 261-266 are displayed as a β-strand; however, the well-known α-model represents this region as a loop. Providing the parameters used for these callouts could explain this difference.<br /> 6. Were divergent sequences selected for the sequence alignment analyses (particularly in Figure 6A)? The selection of sequences can directly influence the outcome of the amino acid residues in each position, and using diverse sequences can reduce the impact of the number of sequences on the LOGO in each phylogenetic group.<br /> 7. For clarity, it would help if the authors provided additional rationale for the selection of residues for mutagenesis, such as selecting Q276, D278, and H283 as exosite residues, when the CASP7 PDB structures (4jr2, 3ibf, and 1k86) suggest that these residues are enriched with loop elements rather than the β sheets expected to facilitate substrate recognition in exosites for caspases (PMID: 32109412). It is possible that the inability to form β-sheets around these positions might indicate the absence of an exosite in CASP7, which further supports the functional effect of the exosite mutations performed.

Reviewer #1 (Public Review):

In the present manuscript, Abele et al use Salmonella strains modified to robustly induce one of two different types of regulated cell death, pyroptosis or apoptosis in growth phases (when SPI2 T3SS is expressed) and cell types to assess the role of pyroptosis versus apoptosis in systemic versus intestinal epithelial pathogen clearance. They demonstrate that in systemic spread, which requires growth in macrophages, pyroptosis is required to eliminate Salmonella, while in intestinal epithelial cells (IEC), extrusion of the infected cell into the intestinal lumen induced by apoptosis or pyroptosis is sufficient for early pathogen restriction. The methods used in these studies are thorough and well-controlled and lead to robust results, that mostly support the conclusions. The impact on the field is considered minor as the observations are somewhat redundant with previous observations and not generalizable due to cited evidence of different outcomes in other models of infection and a relatively artificial study system that does not permit the assessment of later time points in infection due to rapid clearance. This excludes the study of later effects of differences between pyroptosis and apoptosis in IEC such as i.e. IL-18 and eicosanoid release, which are only observed in the former and can have effects later in infection.

Reviewer #1 (Public Review):

Induction of beta cell regeneration is a promising approach for the treatment of diabetes. In this study, Massoz et.al., identified calcineurin (CaN) as a new potential modulator of beta cell regeneration by using zebrafish as model. They also showed that calcineurin (CaN) works together with Notch signaling calcineurin (CaN) to promote the beta cell regeneration. Overall, the paper is well organized, and technically sound. However, some evidence seems weak to get the conclusion.

Reviewer #1 (Public Review):

Iversen et al. performed middle cerebral artery occlusion in rats to evaluate microscopic changes in the blood flow in the ischemic region. By using measures for global (laser speckle) and local capillary blood flow (two-photon imaging), their results show that the capillary transient time/directionality is affected in this model of ischemic stroke. There are several points that need to be addressed, including what vessels authors considered as capillaries and how they controlled/compensated for the capillary blood flow heterogeneity in their analysis. The authors also proposed that the pericytes are not contributing to these functional deficits by doing morphological analysis, more functional studies are needed to confirm this conclusion.

Reviewer #1 (Public Review):

In this study by Yaghmaeian Salmani et al., the authors performed single-nuclei RNA sequencing of a large number of cells (>70,000) in the ventral midbrain. The authors focused on cells in the ventral tegmental area (VTA) and substantia nigra (SN), which contain heterogeneous cell populations comprising dopaminergic, GABAergic, and glutamatergic neurons. Dopamine neurons are known to consist of heterogeneous subtypes, and these cells have been implicated in various neuropsychiatric diseases. Thus, identifying specific marker genes across different dopamine subpopulations may allow researchers in future studies to develop dopamine subtype-specific targeting strategies that could have substantial translational implications for developing more specific therapies for neuropsychiatric diseases.

A strength of the authors' approach compared to previous work is that a large number of cells were sequenced, which was achieved using snRNA-seq, which the authors found to be superior compared to scRNA-seq for reducing sampling bias. A weakness of the study is that relatively little new information is provided as the results are largely consistent with previous studies (e.g., Poulin et al., 2014). Nevertheless, it should be noted that the authors found some more nuanced subdivisions in several genetically identified DA subtypes.

Lastly, the authors performed molecular analysis of ventral midbrain cells in response to 6-OHDA exposure, which leads to the degeneration of SN dopamine neurons, whereas VTA dopamine neurons are largely unaffected. Based on this analysis, the authors identified several candidate genes that may be linked to neuronal vulnerability or resilience.

Overall, the authors present a comprehensive mouse brain atlas detailing gene expression profiles of ventral midbrain cell populations, which will be important to guide future studies that focus on understanding dopamine heterogeneity in health and disease.

Reviewer #1 (Public Review):

This manuscript from Zaman et al., investigates the role of cKit and Kit ligand in inhibitory synapse function at molecular layer interneuron (MLI) synapses onto cerebellar Purkinje cells (PC). cKit is a receptor tyrosine kinase expressed in multiple tissues, including select populations of neurons in the CNS. cKIt is activated by Kit ligand, a transmembrane protein typically expressed at the membrane of connected cells. A strength of this paper is the use of cell-specific knockouts of cKit and Kit ligand, in MLIs and PCs, respectively. In both cases, the frequency of spontaneous or miniature (in the presence of TTX) IPSCs was reduced. This suggests either a reduction in the number of functional inhibitory release sites or reduced release probability. IPSCs evoked by electrical stimulation in the molecular layer showed no change in paired-pulse ratio, indicating release probability is not changed in the cKit KO, and favoring a reduction in the number of release sites. Changes in IPSC amplitude were more subtle, with some analyses showing a decrease and others not. These data suggest that disruption of the cKit-Kit ligand complex reduces the number of functional synapses with only minor changes in synapse strength. However, immunolabelling of inhibitory synapses in cKit KO mice using VGAT and Gephyrin antibodies revealed no change in the number of puncta, but reduced size of puncta. This result is more consistent with reduced synapse strength (size) without a change in synapse number. The apparent contradiction of these results is not resolved. It would be interesting to know if immunolabeling of inhibitory synapses in Kit ligand KO mice would produce similar results.

In separate experiments, the authors used viral expression of Cre (driven by the PC-specific L7 promotor) to sparsely KO Kit ligand in PCs. In recordings from neighboring Cre+ (Kit ligand KO) and Cre - (kit ligand intact) PCs, the spontaneous IPSC frequency and amplitude were reduced. Using a similar viral approach, they also overexpressed Kit ligand in wild-type PCs. Here the results are more difficult to interpret. The frequency and amplitude of spontaneous IPSCs were significantly greater in Cre+ PCs compared to Cre- cells. However, the effect appears to be primarily due to a drastic reduction in IPSC amplitude and frequency in the control Cre- cells rather than an increase in Cre+ cells. This puzzling result is interpreted as evidence that cKit influences the proportion of synapses that are functional for neurotransmission, but not the number of release sites. Though this interpretation is not described in detail.

Overall, this paper makes great use of genetic and viral approaches to examine the function of cKit and Kit ligand at MLI-PC synapses. Measurements are generally limited to immunolabeling and spontaneous IPSC recordings, a wider variety of approaches, such as EM imaging or recording from connected MLI-PC pairs would likely provide more detail on specific pre- or postsynaptic phenotypes and more clearly determine whether the number or strength of synapses is changing.

Reviewer #1 (Public Review):

The authors examine the fascinating question of how T lymphocytes regulate proteome expression during the dramatic cell state change that accompanies the transition from the resting quiescent state to the activated, dividing state. Orthogonal, complementary assays for translation (RPM/RTA, metabolic labeling) are combined with polyribosome profiling and quantitative, biochemical determinations of protein and ribosome content to explore this question, primarily in the OT-I T lymphocyte model system. The authors conclude that the ratio of protein levels to ribosomes/protein synthesis capacity is insufficient to support activation-coupled T cell division and cell size expansion. The authors hint at cellular mechanisms to explain this apparent paradox, focusing on protein acquisition strategies, including emperipolesis and entosis, though these remain topic areas for future study.

The strengths of the paper include the focus on a fundamental biological question - the transcriptional/translational control mechanisms that support the rapid, dramatic cell state change that accompanies lymphocyte activation from the quiescent to activated state, the use of orthogonal approaches to validate the primary findings, and the creative proposal for how this state change is achieved.

The weakness of the work is that several cellular regulatory processes that could explain the apparent paradox are not explored, though they are accessible for experimental analysis. In the accounting narrative that the authors highlight, a thorough accounting of the cellular process inventory that could support the cell state change should be further explored before committing to the proposal, provocative as it is, that protein acquisition provides a principal mechanism for supporting lymphocyte activation cell state change.

Appraisal and Discussion:<br /> 1) relating to the points raised above, two recent review articles explore this topic area and highlight important areas of study in RNA biology and translational control that likely contribute to the paradox noted by the authors: Choi et al. 2022,<br /> doi.org/10.4110/in.2022.22.e39 ("RNA metabolism in T lymphocytes") and Turner 2023, DOI: 10.1002/bies.202200236 ("Regulation and function of poised mRNAs in lymphocytes"). These should be cited, and the broader areas of RNA biology discussed by these authors integrated into the current manuscript.

2) The authors cite the Wolf et al. study from the Geiger lab (doi.org/10.1038/s41590-020-0714-5, ref. 41) though largely to compare determined values for ribosome number. Many other elements of the Wolf paper seem quite relevant, for example, the very high abundance of glycolytic enzymes (and whose mRNAs are quite abundant as well), where (and as others have reported) there is a dramatic activation of glycolytic flux upon T cell activation that is largely independent of transcription and translation, the evidence for "pre-existing, idle ribosomes", the changes in mRNA copy number and protein synthesis rate Spearman correlation that accompanies activation, and that the efficiencies of mRNA translation are heterogeneous. These data suggest that more accounting needs to be done to establish that there is a paradox.

As one example, what if glycolytic enzyme protein levels in the resting cell are in substantial excess of what's needed to support glycolysis (likely true) and so translational upregulation can be directed to other mRNAs whose products are necessary for function of the activated cell? In this scenario, the dilution of glycolytic enzyme concentration that would come with cell division would not necessarily have a functional consequence. And the idle ribosomes could be recruited to key subsets of mRNAs (transcriptionally or post-transcriptionally upregulated) and with that a substantial remodeling of the proteome (authors ref. 44). The study of Ricciardi et al. 2018 (The translational machinery of human CD4+ T cells is poised for activation and controls the switch from quiescence to metabolic remodeling (doi.org/10.1016/j.cmet.2018.08.009) is consistent with this possibility. That study, and the short reviews noted above, are useful in highlighting the contributions of selective translational remodeling and the signaling pathways that contribute to the cell state change of T cell activation. From this perspective, an alternative view can be posited, where the quiescent state is biologically poised to support activation, where subsets of proteins and mRNAs are present in far higher levels than that necessary to support basal function of the quiescent lymphocyte. In such a model, the early stages of lymphocyte activation and cell division are supported by this surplus inventory, with transcriptional activation, including ribosomal genes, primarily contributing at later stages of the activation process. An obvious analogy is the developing Drosophila embryo where maternal inheritance supports early-stage development and zygotic transcriptional contributions subsequently assuming primary control (e.g. DOI 10.1002/1873-3468.13183 , DOI: 10.1126/science.abq4835). To pursue that biological logic would require quantifying individual mRNAs and their ribosome loading states, mRNA-specific elongation rates, existing individual protein levels, turnover rates of both mRNAs and proteins, ribosome levels, mean ribosome occupancy state, and how each of these parameters is altered in response to activation. Such accounting could go far to unveil the paradox. This is a considerable undertaking, though, and outside the scope of the current paper.

Reviewer #1 (Public Review):

The manuscript by Geurrero and colleagues introduces two new metrics that extend the concept of "druggability"- loosely speaking, the potential suitability of a particular drug, target, or drug-target interaction for pharmacological intervention-to collections of drugs and genetic variants. The study draws on previously measured growth rates across a combinatoriality complete mutational landscape involving 4 variants of the TEM-50 (beta lactamase) enzyme, which confers resistance to commonly used beta-lactam antibiotics. To quantify how growth rate - in this case, a proxy for evolutionary fitness - is distributed across allelic variants and drugs, they introduce two concepts: "variant vulnerability" and "drug applicability".

Variant vulnerability is the mean vulnerability (1-normalized growth rate) of a particular variant to a library of drugs, while drug applicability measures the mean across the collection of genetic variants for a given drug. The authors rank the drugs and variants according to these metrics. They show that the variant vulnerability of a particular mutant is uncorrelated with the vulnerability of its one-step neighbors, and analyze how higher-order combinations of single variants (SNPs) contribute to changes in growth rate in different drug environments.

The work addresses an interesting topic and underscores the need for evolution-based metrics to identify candidate pharmacological interventions for treating infections. The authors are clear about the limitations of their approach - they are not looking for immediate clinical applicability - and provide simple new measures of druggability that incorporate an evolutionary perspective, an important complement to the orthodoxy of aggressive, kill-now design principles. I think the ideas here will interest a wide range of readers, but I think the work could be improved with additional analysis - perhaps from evolutionary simulations on the measured landscapes - that tie the metrics to evolutionary outcomes.

Reviewer #1 (Public Review):

Papazian et al. demonstrate that human peripheral blood mononuclear cells (PBMCs) can be successfully and stably grafted into immunodeficient mice. They demonstrate that the adoptive transfer of PBMCs from multiple sclerosis (MS) patients is capable of inducing damage to the central nervous system (CNS). Furthermore, they demonstrate that the CNS inflammatory properties of these transferred cells are more dependent on HLA restriction rather than the disease status of the donor. Specifically, T cells restricted by HLA-DR15 (from both an MS patient and a healthy control) showed a greater propensity to induce neuroinflammation than T cells transferred from an MS patient that are restricted by a different MHC haplotype. This observation suggests that the differences in the peptide repertoire presented by this MHC haplotype biases adaptive immune responses toward encephalitogenic T cell generation. The conclusions of this paper are partially supported by their data, but the lack of important considerations and various controls limits the overall impact of this study. Major weaknesses of this study include:

1) The extent to which various immune cell quantification is performed. Two of the reasons the authors cite for the use of this model rather than a traditional EAE model are: i) the lack of involvement of CD8 T cells in the pathogenesis of EAE and ii) the marginal importance of B cells in EAE pathogenesis. However, throughout their paper, the authors never quantify the difference in CD4 vs CD8 T cell infiltration into the CNS. While repeatedly claiming that there are fewer CD4 T cells present than CD8 T cells within the CNS, this data is not included. Further, spinal cord numbers of CD4 and CD8 are not provided in lieu of CD3 T cell characterization. Given that there are far more hCD4 T cells in the periphery in these mice than CD8 T cells as well as the fact that the lack of B2m expression in this mouse model biases cells towards a CD4 fate, the omission of these data is concerning. Additionally, B cells don't make up any significant component of the cells transferred from HLA-DR15 donors. While the cells transferred from the HLA-DR13 donor are composed of a considerable number of B cells, the mice that received these cells didn't develop any signs of neurologic disease.

2) Incomplete exploration of potential experimental autoimmune encephalomyelitis (EAE) modeling. The authors justify the use of an extremely high amount of myelin peptide when immunizing their mice by citing that another humanized mouse model had such a requirement to induce clinical EAE. However, a demonstration of this technical requirement in their own model is not provided. Rather, they show that C57BL/6 mice get milder disease when such large doses of peptides are administered, leading to speculation that this is due to a tolerizing immune response that occurs at such high doses. Comparison of the susceptibility of B2m-NOG mice to EAE dependent on various peptide doses would be highly informative. Given that the number of hCD45+ in the periphery of NOG mice decreases following this immunization it would be prudent for the authors to determine if such a high peptide dose is truly ideal for EAE development in this mouse model.

3) The degree of myelin injury is not presented. The statement is repeatedly made that "demyelination was not observed in the brain or spinal cord" but no quantification of myelin staining is shown. A central feature of multiple sclerosis and related diseases is demyelination of the CNS. Hence, while compartmentalized inflammatory responses are detailed in this report, the utility of the humanized model for the exploration of human CNS demyelinating diseases remains unclear and in doubt.

Minor points:

- Method of quantification (e.g. cells per brain slice in figures 2E; 4E) is not very quantitative and should be justified or more appropriately updated to be more rigorous in methodology.

- Fig. 4 data should be shown from un-immunized DR15 MS and DR15 HI mice.

The premise of this work carries great potential. Namely, developing a humanized mouse system in which features of adaptive immunity that contribute to inflammatory demyelination can be interrogated will allow for traction into therapeutics currently unavailable to the field. Immediate questions stemming from the current study include the potential effect of ex vivo activation of PBMCs (or individual T and B cells) in vitro prior to transfer as well as the TCR and BCR repertoire of CNS vs peripheral lymphocytes before and after immunization. This group has been thoughtful and clever about their approach (e.g. use of subjects treated with natalizumab), which gives hope that fundamental aspects of pathogenesis will be uncovered by this form of modeling MS disease. Overall, while the current study makes several unique observations, the data collection is incomplete and the impact of this study could be greatly improved by addressing the limitations noted.

Reviewer #1 (Public Review):

Gehr and colleagues used an elegant method, using neuropixels probes, to study retinal input integration by mouse superior collicular cells in vivo. Compared to a previous report of the same group, they opto-tagged inhibitory neurons and defined the differential integration onto each group. Through these experiments, the author concluded that overall, there is no clear difference between the retina connectivity to excitatory and inhibitory superior colliculus neurons. The exception to that rule is that excitatory neurons might be driven slightly stronger than inhibitory ones. Technically, this work is performed at a high level, and the plots are beautifully conceived, but I have doubts if the interpretation given by the authors is solid. I will elaborate below.

Some thoughts about the interpretation of the results.

My main concern is the "survivor bias" of this work, which can lead to skewed conclusions. From the data set acquired, 305 connections were measured, 1/3 inhibitory and 2/3 excitatory. These connections arise from 83 RGC onto 124 RGC (I'm interpreting the axis of Fig.2 C). Here it is worth mentioning that different RGC types have different axonal diameters (Perge et al., 2009). Here the diameter is also related to the way cells relay information (max frequencies, for example). It is possible that thicker axons are easier to measure, given the larger potential changes would likely occur, and thus, selectively being picked up by the neuropixels probe. If this is the case, we would have a clear case of "survival bias", which should be tested and discussed. One way to determine if the response properties of axonal termini are from an unbiased sample is to make a rough functional characterization as generally performed (see Baden et al. 2006). This is fundamental since all other conclusions are based on unbiased sampling.

One aspect that is not clear to me is to measure of connectivity strength in Figure 2. Here it seems that connectivity strength is directly correlated with the baseline firing rate of the SC neuron (see example plots). If this is a general case, the synaptic strength can be assumed but would only differ in strength due to the excitability of the postsynaptic cell. This should be tested by plotting the correlation coefficient analysis against the baseline firing rate.

My third concern is the assessment of functional similarity in Fig. 3. It is not clear to me why the similarity value was taken by the arithmetic mean. For example, even if the responses are identical for one connected pair that exclusively responds either to the ON or OFF sparse noise, the maximal value can only be 0.67. Perhaps I misunderstood something. Secondly, correlations in natural(istic) movies can differ dramatically depending on the frame rate that the movie was acquired and the way it is displayed to the animal. What looks natural to us will elicit several artifacts at a retinal level, e.g., due to big jumps between frames (no direction-selective response) or overall little modulation (large spatial correlations). I would rather opt for uniform stimuli, as suggested previously. Of course, these are also approximations but can be easily reproduced by different labs and are not subjected to the intricacies of the detailed naturalistic stimulus used.

Fourth. It is important to control the proportion of inhibitory cells activated optogenetically across the recording probe. Currently, it is not possible to assess if there are false negatives. One way of controlling for this would be to show that the number of inhibitory interneurons doesn't vary across the probe.

Fifth. In Fig. 4, the ISI had a minimal bound of 5 ms. Why? This would cap the firing rate at 200Hz, but we know that RGC in explants can fire at higher frequencies for evoked responses. I would set a lower bound since it should come naturally from the after-depolarization block. Another aspect that remains unclear is to what extent the paired-spike ratio depends on the baseline firing rate. This would change the interpretation from the particular synaptic connection to the intrinsic properties of the cell and is plausible since the bassline firing rate varies tremendously. One related analysis would be to plot the change of PSR depending on the ISI. It would be intuitive to make a scatter plot for all paired spikes of all recorded neurons (separated into inhibitory and excitatory) of ISI vs. PSR.

Panel 4E is confusing to me. Here what is plotted is efficacy 1st against PSR (which is efficacy 2nd/efficacy 1st). Given that you have a linear relation between efficacy 1st and efficacy 2nd (panel 4C), you are essentially re-plotting the same information, which should necessarily have a hyperbolic relationship: [ f(x) = y/x ]. Thus, fitting this with a linear function makes no sense and it has to be decaying if efficacy 2nd > efficacy1st as shown in 4C.

Finally, in Figure 5, the perspective is inverted, and the spike correlations are seen from the perspective of SC neurons. Here it would also be good to plot the cumulative histograms and not look at the averages. Regarding the similarity index and use of natural stats, please see my previous comments. Also, would it be possible to plot the contribution v/s the firing rate with the baseline firing rate with no stimulation or full-field stimulation? This is important since naturalistic movies have too many correlations and dependencies that make this plot difficult to interpret.

Overall, the paper only speaks from excitatory and inhibitory differences in the introduction and results. However, it is known that there are three clear morphologically distinct classes of excitatory neurons (wide-field, narrow-field, and stellate). This topic is touched in the discussion but not directly in the context of these results. Smaller cells might likely be driven much stronger. Wide-field cells would likely not be driven by one RGC input only and will probably integrate from many more cells than 6.

Reviewer #1 (Public Review):

In the manuscript entitled "A theory of hippocampal theta correlations", the authors propose a new mechanism for phase precession and theta-time scale generation, as well as their interpretation in terms of navigation and neural coding. The authors propose the existence of extrinsic and intrinsic sequences during exploration, which may have complementary functions. These two types of sequences depend on external input and network interactions, but differ on the extent to which they depend on movement direction. Moreover, the authors propose a novel interpretation for intrinsic sequences, namely to signal a landmark cue that is independent of direction of traversal. Finally, a readout neuron can be trained to distinguish extrinsic from intrinsic sequences.

The study puts forward novel computational ideas related to neural coding, partly based on previous work from the authors, including published (Leibold, 2020, Yiu et al., 2022) and unpublished (Ahmedi et al., 2022. bioRxiv) work. The manuscript will contribute to the understanding of the mechanisms behind phase precession, as well as to how we interpret hippocampal temporal coding for navigation and memory.

Reviewer #1 (Public Review):

This well written and designed study by Broca-Brisson et al describes the generation of a new in vitro model for creatine transporter deficiency (CTD), making use of human brain organoid cultures derived from CTD patients. This new model will certainly prove itself very useful to better understand this genetic disease essentially affecting CNS. As CTD has no satisfactory treatment so far (despite more than 20 years of research), this new model will also be very useful to design and develop new treatments.

In particular, through the use of immunohistochemistry, real time PCR, and proteomics combined with integrative bioinformatic and statistical analysis, authors provide very interesting new information on the brain pathways affected in CTD (e.g. neurogenesis with down-regulation of SOX2 and PAX6 but up-regulation of GSK3b; and proteins involved in autistic spectrum, epilepsies or intellectual disabilities).

Reviewer #1 (Public Review):

The authors were seeking to improve understanding of how wind and wave action affect the use of energetically demanding wing flapping and running by albatross engaged in takeoff flight. To accomplish this in the complex and challenging environment in which albatross live, the authors sought to use accelerometry and geographic positioning to infer patterns of locomotion, flight orientation relative to the prevailing wind, and wave height during takeoff.

The major strength of the methods and results is that the use of accelerometry and novel interpretations of data from a geographic positioning system provides new insight into the use of waves by albatross and how the effects of wave magnitude interact with the wind to modulate energy demands during takeoff. Weaknesses of the approach are due to the challenging environmental conditions in which albatross live. The interpretation of accelerometry data was not validated using a subset of the sample synchronized with video (prior validation was cited for shearwaters). The interpretation of wind direction relative to flight path is based on the behavior of the bird without concurrent measures of local wind velocity.

The authors achieved their aims, and their results support their conclusions.

Although it is generally understood that albatross and many other birds choose to takeoff into the wind to reduce energetic costs, the authors provide novel quantitative data on this behavior. Their results on the effects of wave height and the interactions between wave height and wind provide novel insight into how albatross harvest energy from their complicated and dynamic environment to reduce the energy they must output to get into the air. In particular, the new insight into the effects of wave height should revise understanding among ornithologists, ocean ecologists and those who study the mechanics of animal locomotion. The use of accelerometry and geographic positioning systems to measure flight behavior and ocean ecology should inspire other researchers to adopt similar methods.

Albatross live in a complex and poorly understood environment that is likely to be threatened by climate change. This research provides worthwhile new insight into how wind and wave action affect takeoff in albatross, and can therefore improve insight into how changes in these variables with climate change may affect the distribution of albatross populations.

Reviewer #1 (Public Review):

This article is interested in how butterfly, or more precisely, butterfly wing scale precursor cells, each make precisely patterned ultrastructures made of chitin.

To do this, the authors sought to use the butterfly Parides eurimedes, a papilionid swallowtail, that carries interesting, unusual structures made of 1) vertical ridges, that lack a typical layered stacking arrangement; and 2) deep honeycomb-like pores. These two features make the organism chosen a good point of comparison with previous studies, including classic papers that relied on electronic microscopy (SEM/TEM), and more recent confocal microscopy studies.

The article shows good microscopy data, including detailed, dense developmental series of staining in the Parides eurimedes model. The mix of cell membrane staining, chitin precursor, and F-actin staining is well utilized and appropriately documented with the help of 3D-SIM, a microscopy technique considered to provide super-resolution (here needed to visualize sub-cellular processes).

The key message from this article is that F-actin filaments are later repurposed, in papilionid butterflies, to finish the patterning of the inter-ridge space, elaborating new structures (this was not observed so far in other studies and organisms). The model proposed in Figure 6 summarized these findings well, with F-actin reshaping it itself into a tulip that likely pulls down a chitin disk to form honeycombs. These interpretations of the microscopy data are interesting and novel.

There are two other points of interest, that deserve future investigation:<br /> 1) The authors performed immunolocalizations of Arp2 and pharmacological inhibitions of Arp2/3, and found some possible effect on honeycomb lattice development. The inter-ridge region of the butterfly Papilio polytes, which lacks these structures, did not seem to be affected by drug treatments. Effects where time-dependent, which makes sense. These data provide circumstantial evidence that Arp2/3 is involved in the late role of F-actin formation or re-organisation.<br /> 2) The authors perform a comparative study in additional papilionids (Fig. 6 in particular). I find these data to be quite limited without a dense sampling, but they are nonetheless interesting and support a second-phase role of F-actin re-organisation.

The article is dense, well produced and succinctly written. I believe this is an interesting and insightful study on a complex process of cell biology, that inspires us to look at basic phenomena in a broader set of organisms.

Reviewer #1 (Public Review):

Sekulovski et al present an interesting and timely manuscript describing the temporal transition from epiblast to amnion. The manuscript builds on their previous work describing this process using stem cell models.

They suggest a multi-step process initiated by BMP induction of GATA3, followed by expression of TFAP2A, followed by ISL1/HAND1 in parallel with loss of pluripotency markers. This transition was reproduced through IF analysis of CS6/7 NHP embryo.

There are significant similarities in the expression of trophectoderm and the amnion. There are also ample manuscripts showing trophoblast induction following BMP stimulation of primed pluripotent stem cells. The authors should ensure that the amnion indeed is only amnion and not trophectoderm (or the amount of contribution to trophectoderm). As an extension, does the amnion character remain after the 48h BMP4 treatment, and is a trophectoderm-like state adopted as suggested by Ohgushi et al 2022?

The functional data does not support a direct function of GATA3 prior to TFAP2A and the authors suggest compensatory mechanisms from other GATAs. If so, which GATAs are expressed in this system, with and without GATA3 targeting? Would it not be equally likely that the other early genes could be the key drivers of amnion initiation, such as ID2?

The targeting of TFAP2A displays a very interesting phenotype which suggests that amnion and streak share an initial trajectory but where TFAP2A is necessary to adopt amnion fate. It would again be important to ensure that this alternative fate is indeed in streak and not misannotated alternative lineages, including trophoblast.

Is TBXT induced in this setting as well as in the wt situation during amnion induction? This should be displayed as in Figure 3D and would be nice to be complimented by NHP IF analysis.

The authors should address why they get different results from Castillo-Venzor et al 2023 DOI 10.26508/lsa.202201706

Reviewer #1 (Public Review):

In this manuscript, Kipfer et al describe a method for a fast and accurate SARS-CoV2 rescue and mutagenesis. This work is based on a published method termed ISA (infectious subgenomic amplicons), in which partially overlapping DNA fragments covering the entire viral genome and additional 5' and 3' sequences are transfected into mammalian cell lines. These DNA fragments recombine in the cells, express the full length viral genomic RNA and launch replication and rescue of infectious virus.

CLEVER, the method described here significantly improves on the ISA method to generate infectious SARS-CoV2, making it widely useful to the virology community.

Specifically, the strengths of this method are:<br /> 1) The successful use of various cell lines and transfection methods.<br /> 2) Generation of a four-fragment system, which significantly improves the method efficiency due to lower number of required recombination events.<br /> 3) Flexibility in choice of overlapping sequences, making this system more versatile.<br /> 4) The authors demonstrated how this system can be used to introduce point mutations as well as insertion of a tag and deletion of a viral gene.<br /> 5) Fast-tracking generation of infectious virus directly from RNA of clinical isolates by RT-PCR, without the need for cloning the fragments or using synthetic sequences.<br /> One weakness of the latter point, which is also pointed out by the authors, is that the direct rescue of clinical isolates was not tested for sequence fidelity.

The manuscript clearly presents the findings, and the proof-of-concept experiments are well designed.

Overall, this is a very useful method for SARS-CoV2 research. Importantly, it can be applicable to many other viruses, speeding up the response to newly emerging viruses than threaten the public health.

Joint Public Review:

Using computational modeling, this manuscript explores the effect of growth feedback on the performance of gene networks capable of adaptation. The authors selected 425 hypothetical synthetic circuits that were shown to achieve nearly perfect adaptation in two earlier computational studies (see Ma et al. 2009, and Shi et al. 2017). They examined the effects of cell growth feedback by introducing additional terms to the ordinary differential equation-based models, and performed numerical simulations to check the retainment and the loss of the adaptation responses of the circuits in the presence of growth feedback. The authors show that growth feedback can disrupt the gene network adaptation dynamics in different ways, and report some exceptional core motifs which allow for robust performance in the presence of growth feedback. They also used a metric to establish a scaling law between a circuit robustness measure and the strength of growth feedback. These results have important implications in the field of synthetic biology, where unforeseen interactions between designed gene circuits and the host often disrupt the desired behavior. The paper's conclusions are supported by their simulation results, although these are presented in their summary formats and it would be useful for the community if the detailed results for each topology were available as a supplementary file or through the authors' GitHub repository.

Strengths<br /> - This work included a detailed investigation of the reasons for adaptation failure upon introducing cell growth to the systems. The comprehensiveness of the analysis makes the work stand out among studies of functional screening of network topologies of gene regulation.

- The authors' approaches for assessment of robustness, such as the survival ratio Q, can be useful for a wide range of topologies beyond adaptation. The scaling law obtained with those approaches is interesting.

Weaknesses<br /> - The title suggests that the work investigates the 'effects of growth feedback on gene circuits'. However, the performance of 'nearly perfect adaptation' was chosen for the majority of the work, leaving the question of whether the authors' conclusion regarding the effects of growth feedback is applicable to other functional networks.

- This work relies extensively on an earlier study, evaluating only a selected set of 425 topologies that were shown to give adaptive responses (Shi et al., 2017). This limited selection has two potential issues. First, as the authors mentioned in the introduction, growth feedback can also induce emerging dynamics even without existing function-enabling gene circuits, as an example of the "effects of growth feedback on gene circuits". Limiting the investigation to only successful circuits for adaptation makes it unclear whether growth feedback can turn the circuits that failed to produce adaptation by themselves into adaptation-enabling circuits. Secondly, as the Shi et al. (2017) study also used numerical experiments to achieve their conclusions about successful topologies, it is unclear whether the numerical experiments in the present study are compatible with the earlier work regarding the choice of equation forms and ranges of parameter values. The authors also assumed that all readers have sufficient understanding of the 425 topologies and their derivation before reading this paper.

- The authors' model does not describe the impact of growth via a biological mechanism: they model growth as an additional dilution rate and calculate growth rate based on a phenomenological description with growth rate occurring at a maximum (k_g) scaled by the circuit 'burden' b(t). Therefore, the authors' model does not capture potential growth rate changes in parameter values (e.g., synthetic protein production falls with increasing growth rate; see Scott & Hwa, 2023).

- The authors made several claims about the bifurcations (infinite-period, saddle-node, etc) underlying the abrupt changes leading to failures of adaptations. There is a lack of evidence supporting these claims. Both local and global bifurcations can be demonstrated with semi-analytic approaches such as numerical continuation along with investigations of eigenvalues of the Jacobian matrix. The claims based on ODE solutions alone are not sound.

- The impact of biochemical noise is not evaluated in this work; the author's analysis is only carried out in a deterministic regime.

Reviewer #1 (Public Review):

This paper describes RNA-sensing guide RNAs for controlled activation of CRISPR modification. This works by having an extended guide RNA with a sequence that folds back onto the targeting sequence such that the guide RNA cannot hybridise to its genomic target. The CRISPR is "activated" by the introduction of another RNA, referred to as a trigger, that competes with this "back folding" to make the guide RNA available for genome targeting. The authors first confirm the efficacy of the approach using several RNA triggers and a GFP reporter that is activated by dCas9 fused to transcriptional activators. A major potential application of this technique is the activation of CRISPR in response to endogenous biomarkers. As these will typically be longer than the first generation triggers employed by the authors they test some extended triggers, which also work though not always to the same extent. They then introduce MODesign which may enable the design of bespoke or improved triggers. After that, they determine that the mode of activation by the RNA trigger involves cleavage of the RNA complexes. Finally, they test the potential for their system to work in a developmental setting - specifically zebrafish embryos. There is some encouraging evidence, though the effects appear more subtle than those originally obtained in cell culture.

Overall, the potential of a CRISPR system that can be activated upon sensing an RNA is high and there are a myriad of opportunities and applications for it. This paper represents a reasonable starting point having developed such a system in principle.

The weakness of the study is that it does not demonstrate that the system can be used in a completely natural setting. This would require an endogenous transcript as the RNA trigger with a clear readout. Such an experiment would clearly strengthen the paper and provide strong confidence that the method could be employed for one of the major applications discussed by the authors. The zebrafish data relied on exogenous RNA triggers whereas the major applications (as I understood them) would use endogenous triggers.

Related, most endogenous RNAs are longer than the various triggers tested and may require extensive modification of the system to be detected or utilised effectively.<br /> While additional data would clearly be beneficial, there should nevertheless be a more detailed discussion of these caveats and/or the strengths and applications of the system as it is presented (i.e. utility with synthetic triggers).

Reviewer #1 (Public Review):

In this manuscript, the authors investigate whether enhancers use a common regulatory paradigm to modulate transcriptional bursting in both endogenous and ectopic domains using cis-regulatory mutant reporters of the eve transcriptional locus in early Drosophila embryogenesis.

The authors create a series of cis-regulatory BAC mutants of the eve stripe 1 and 2 enhancers by mutating the binding sites for the transcriptional repressor Giant in the stripe 2 minimal response element (MRE) independently or in combination with deletion of the stripe 1 enhancer sequence. With these enhancer mutations, they are able to generate conditions in which eve is ectopically expressed. Next, the authors investigate if nuclei in these "ectopic" regions have similar transcriptional kinetics to the "endogenous"-expressing eve+ nuclei. They show that bursting parameters are unchanged when comparing endogenous and ectopic gene expression regions. Under a scheme of a 2-state model, the eveS1Δ-EveS2Gt- reporter modulates transcription by increasing the active state switching rate (kon) and the initiation rate (r) while maintaining a constant inactive state switching rate.

Based on these results, the authors support a model whereby kinetic regimes are encoded in the cis-regulatory sequences of a gene instead of imposed by an evolving trans-regulatory environment.

The question asked in this manuscript is important and the eve locus represents an ideal paradigm to address it in a quantitative manner. Most of the results are correctly interpreted and well-presented. However, the main conclusion pointing towards a potential "unified theory" of burst regulation during Drosophila embryogenesis should be nuanced or cross-validated.

In addition to the lack of novelty (some results concerning the fact that koff does not change along the A/P axis/the idea of a 'unified regime' were already obtained in Berrocal et al 2020), Note i) the limited manipulation of TF environment; ii) the simplicity with which bursting is analyzed (only a two-state model is considered, and not cross-validated with an alternative approach than cpHMM) and iii) the lack of comparisons with published work.

Reviewer #1 (Public Review):

Strengths:

The innovative method is the biggest strength of this article. Moreover, the method can be implemented across fields and disciplines. I myself would like to see this method implemented in a grander scale. The author invested a lot of effort in data collection and I especially commend that ChatGPT assessed the reviews twice, to ensure greater objectivity.

Weaknesses:

I have several concerns regarding the methodology of the article. The first relates to the fact that the sample is not random. The selection of journal and inclusion and exclusion criteria do not contribute well to the strength of the evidence.

An important methodological fact is that the correlation between the two assessments of peer reviews was actually lower than we would expect (around 0.72 and 0.3 for the different linguistic characteristics). If the ChatGPT gave such different scores based on two assessments, should it not be sound to do even more assessments and then take the average?

Reviewer #1 (Public Review):

Summary<br /> This manuscript reports preliminary evidence of successful optogenetic activation of single retinal ganglion cells (RGCs) through the eye of a living monkey using adaptive optics (AO).

Strengths<br /> The eventual goals of this line of research have enormous potential impact in that they will probe the perceptual impact of activating single RGCs. While I think more data should be included, the four examples shown look quite convincing.

Weaknesses<br /> While this is undoubtedly a technical achievement and an important step along this group's stated goal to measure the perceptual consequences of single-RGC activations, the presentation lacks the rigor that I would expect from what is really a methods paper. In my view, it is perfectly reasonable to publish the details of a method before it has yielded any new biological insights, but in those publications, there is a higher burden to report the methodological details, full data sets, calibrations, and limitations of the method. There is considerable room for improvement in reporting those aspects. Specifically, more raw data should be shown for activations of neighboring RGCs to pinpoint the actual resolution of the technique, and more than two cells (one from each field of view) should be tested. Some information about the density of labeled RGCs in these animals would also be helpful to provide context for how many well-isolated target cells exist per animal.

Reviewer #1 (Public Review):

Summary:<br /> Ahn and Amrein characterize the expression of members of the Gr28 family of gustatory receptors in taste neurons in the Drosophila melanogaster larva, define the behaviorally-relevant ligands for these receptors, and use chemogenetic experiments to show, strikingly, that different neurons have opposite behavioral responses to the chemogenetic ligand. They go on to show what neurons need to be silenced to lose responses to bitters, and very nicely show what subunits of the Gr28 bitter receptors are necessary and sufficient for responses to bitters. This is a nice piece of work, rigorously carried out, that tackles the neurons and receptors that drive innate responses to tastants in Drosophila larvae.

Strengths:<br /> 1. The chemogenetic experiments in Figure 2 are cleanly done with very clear results, and the subsetting in Figure 2B further clarifies the cellular requirements for the behavior.<br /> 2. The rescue experiments with different Gr28 subunits in the Gr28 mutant are creative and clear.

Weaknesses:<br /> 1. The authors should define early and clearly that expression of Gr28 genes studied in this paper relies not on looking at the endogenous gene but at the expression of Gal4 under the control of enhancers from these loci. The Gal4 drivers are useful and important tools, but the possibility exists that their expression is not 100% congruent with the endogenous expression of these receptors. I would not require a comprehensive validation of the lines by RNA in situ hybridization compared to the Gal4 driver lines but would recommend the disclaimer be made and that the authors are more precise in talking about the expression of the marker rather than the expression of the specific receptor gene.

2. The important chemogenetic behavioral data would benefit from a clearer presentation including a cartoon to explain what the behavior is and how it is scored. Figure 2 is the key figure in this paper and it would be helpful if the figure were re-organized to guide the non-expert reader to the key result. I recommend labeling the positive controls Gr43a as "sweet" and Gr66a as "bitter" and perhaps organize the presentation to have the negative control at the left, then Gr28ba that had no effect, then group Gr28a with Gr43a for positive valence and Gr28bc with Gr66a for negative valence. I'm not sure what the value is of showing both 0.1 mM and 0.5 mM capsaicin, the text does not explain. The experiment in Figure 2B is important but non-experts will not understand what is being done here - can the authors please provide a cartoon like those in Figure 1 showing what cells are being subjected to chemogenetics and how this differs from Figure 2A?

3. The AlphaFold ligand docking in Figure 8 is conducted with Gr28bc monomers, which are unlikely to be the in vivo relevant structure, given that the related OR/ORCO ancestor structures are tetramers. I recommend that this component of the paper either be removed entirely or that the authors redo the in silico work using the AlphaFold-Multimer package reported by Hassabis and Jumper in 2022 https://www.biorxiv.org/content/10.1101/2021.10.04.463034v2. It will be interesting to see what a tetramer structure looks like with the ligand.

Reviewer #1 (Public Review):

In this manuscript, Yao et al. explored the transcriptomic characteristics of neural stem cells (NSCs) in the human hippocampus and their changes under different conditions using single-nucleus RNA sequencing (snRNA-seq). They generated single-nucleus transcriptomic profiles of human hippocampal cells from neonatal, adult, and aging individuals, as well as from stroke patients. They focused on the cell groups related to neurogenesis, such as neural stem cells and their progeny. They revealed genes enriched in different NSC states and performed trajectory analysis to trace the transitions among NSC states and towards astroglial and neuronal lineages in silico. They also examined how NSCs are affected by aging and injury using their datasets and found differences in NSC numbers and gene expression patterns across age groups and injury conditions. One major issue of the manuscript is questionable cell type identification. For example, in Figure 2C, more than 50% of the cells in the astroglial lineage clusters are NSCs, which is extremely high and inconsistent with classic histology studies.

Reviewer #1 (Public Review):

This remarkable and creative study from the Asbury lab examines the extent to which mechanical coupling can coordinate the growth of two microtubules attached to isolated kinetochores. The concept of mechanical coupling in kinetochores was proposed in the mid-1990s and makes sense intuitively (as shown in Fig. 1B). But intuitive concepts still need experimental validation, which this study at long last provides. The experiments described in this paper will serve as a foundation for the transition of an intuitive concept into a robust, quantitative, and validated model.

The introduction cites at least 5 papers that proposed mechanical coupling in kinetochores, as well as 5 theoretical studies on mechanical coupling within microtubule bundles, so it's clear that this manuscript will be of considerable interest to the field. The intro is very well written (as is the manuscript in general), but I recommend that the authors include a brief review of the variable size of k-fibers across species, to help the reader contextualize the problem. For example, budding yeast kinetochores are built around a single microtubule (Winey 1995), so mechanical coupling is not relevant for this species.

Indeed, the use of yeast kinetochores to study mechanical coupling is an odd fit, because these structures did not evolve to support such coupling. There is no doubt that yeast kinetochores are useful for demonstrating mechanical coupling and for measuring the stiffnesses necessary to achieve coupling, but I recommend that the authors include a caveat somewhere in the manuscript, perhaps in the place where they discuss their use of simple elastic coupling as compared to viscoelastic coupling or strain-stiffening. It's easy to imagine that kinetochores with large k-fibers might require complex coupling mechanisms, for example. And is mechanical coupling relevant for holocentric kinetochores like those found in C. elegans?

The paper shows considerable rigour in terms of experimental design, statistical analysis, and presentation of results. My only comment on this topic relates to the bandwidth of the dual-trap assay, which I recommend describing in the main text in addition to the methods. For example, the authors note that the stage position is updated at 50 Hz. The authors should clearly explain that this bandwidth is sufficiently fast relative to microtubule growth speeds.

After describing their measurements, the authors use Monte Carlo simulations to show that pauses are essential to a quantitative explanation of their coupling data. Apparently, there is a history of theoretical approaches to coupling, as the introduction cites 5 theoretical studies. I would have appreciated it if the authors had engaged with this literature in the Results section, e.g. by describing which previous study most closely resembles their own and/or comparing and contrasting their approach with the previous work.

Overall, this paper is rigorous, creative, and thought-provoking. The unique experimental approach developed by the Asbury lab shows great promise, and I very much look forward to future iterations.

Reviewer #1 (Public Review):

The authors succeeded in establishing experimental and mathematical models for the formation of new blood vessels. The experimental model relies on temporal imaging of multilcellular projections and lumen formation from a single blood vessel embedded in an engineered extracellular matrix. The mathematical model combines both discrete and continuum elements. It would be helpful to understand how the authors came up with phenotypic classes for analyzing their live imaging data. On the modeling side, it would be useful to see whether the claims about Turing patterns could be supported by either a mean-field model or a more thorough parametric analysis of the discreet continuum model. The authors did a good job in comparing their VEGF/Notch mechanism to the EGF/Notch vulval patterning mechanism in C. elegans. The authors might want to look into the literature from studies of the tracheal patterning system in Drosophila when the combined actions of the FGF and Notch signaling specify tip and stalk cells. The similarities are quite striking and are worth noting.

Reviewer #1 (Public Review):

This study investigates the role of microtubules in regulating insulin secretion from pancreatic islet beta cells. This is of great importance considering that controlled secretion of insulin is essential to prevent diabetes. Previously, it has been shown that KIF5B plays an essential role in insulin secretion by transporting insulin granules to the plasma membrane. High glucose activates KIF5B to increase insulin secretion resulting in the cellular uptake of glucose. In order to prevent hypoglycemia, insulin secretion needs to be tightly controlled. Notably, it is known that KIF5B plays a role in microtubule sliding. This is important, as the authors described previously that beta cells establish a peripheral sub-membrane microtubule array, which is critical for the withdrawal of excessive insulin granules from the secretion sites. At high glucose, the sub-membrane microtubule array is destabilized to allow for robust insulin secretion. Here the authors aim to answer the question of how the peripheral array is formed. Based on the previously published data the authors hypothesize that KIF5B organizes the sub-membrane microtubule array via microtubule sliding.

General comment:<br /> This manuscript provides data that indicate that KIF5B, like in many other cells, mediates microtubule sliding in beta cells. This study is limited to in vitro assays and one cell line. Furthermore, the authors provide no link to insulin secretion and glucose uptake and the overall effects described are moderate. Finally, the overall effect of microtubule sliding upon glucose stimulation is surprisingly low considering the tight regulation of insulin secretion. Moreover, the authors state "the amount of MT polymer on every glucose stimulation changes only slightly, often undetectable.....In fact, we observe a prominent effect of peripheral MT loss only after a long-term kinesin depletion (three-four days)". This challenges the view that a KIF5B-dependent mechanism regulating microtubule sliding plays a major role in controlling insulin secretion.

Specific comments:<br /> 1) Notably, the authors have previously reported that high glucose-induced remodeling of microtubule networks facilitates robust glucose-stimulated insulin secretion. This remodeling involves the disassembly of old microtubules and the nucleation of new microtubules. Using real-time imaging of photoconverted microtubules, they report that high levels of glucose induce rapid microtubule disassembly preferentially in the periphery of individual β-cells, and this process is mediated by the phosphorylation of microtubule-associated protein tau. Here, they state that the sub-membrane microtubule array is destabilized via microtubule sliding. What is the relevance of the different processes?

2) On one hand the authors describe how KIF5B depletion prevents sliding and the transport of microtubules to the plasma membrane to form the sub-membrane microtubule array. This indicates KIF5B is required to form this structure. On the other hand, they describe that at high glucose concentration, KIF5B promotes microtubule sliding to destabilize the sub-membrane microtubule array to allow robust insulin secretion. This appears contradictory.

3) Previously, it has been shown that KIF5B induces tubulin incorporation along the microtubule shaft in a concentration-dependent manner. Moreover, running KIF5B increases microtubule rescue frequency and unlimited growth of microtubules. Notably, KIF5B regulates microtubule network mass and organization in cells (PMID: 34883065). Consequently, it appears possible that the here observed phenomena of changes in the microtubule network might be due to alterations in these processes.

4) The authors provide data that indicate that microtubule sliding is enhanced upon glucose stimulation. They conclude that these data indicate that microtubule sliding is an integral part of glucose-triggered microtubule remodeling. Yet, the authors fail to provide any evidence that this process plays a role in insulin secretion or glucose uptake.

5) The authors speculate that the sub-membrane microtubule array prevents the over-secretion of insulin. Would one not expect in this case a change in the distribution of insulin granules at the plasma membrane when this array is affected? Or after glucose stimulation? Notably, it has been reported that "the defects of β-cell function in KIF5B mutant mice were not coupled with observable changes in islet morphology, islet cell composition, or β-cell size" and "the subcellular localization of insulin vesicles was found to not be affected significantly by the decreased Kif5b level. The cytoplasm of both wild-type and mutant β-cells was filled with insulin vesicles. Insulin vesicle numbers per square μm were determined by counting all insulin vesicles in randomly photographed β-cells. More insulin granules were found in Kif5b knockout β-cells compared with control cells. This phenomenon is consistent with the observation that insulin secretion by β-cells is affected" whereby "Insulin vesicles (arrowheads) were distributed evenly in both mutant and control cells" (PMID: 20870970).

6) Does the sub-membrane microtubule array exist in primary beta cells (in vitro and/or in vivo) and how it is affected in KIF5B knockout mice?

Reviewer #1 (Public Review):

Recently discovered extrachromosomal DNA (ecDNA) provides an alternative non-chromosomal means for oncogene amplification and a potent substrate for selective evolution of tumors. The current work aims to identify key genes whose expression distinguishes ecDNA+ and ecDNA- tumors and the associated processes to shed light on the biological mechanisms underlying ecDNA genesis and their oncogenic effects. While this is clearly an important question, the analysis and the evidence supporting the claims are weak. The specific machine learning approach seems unnecessarily convoluted, insufficiently justified and explained, and the language used by the authors conflates correlation with causality. This work points to specific GO processes associated (up and down) with ecDNA+ tumors, many of which are expected but some seem intriguing, such as association with DSB pathways. My specific comments are listed below.

A. The claim of identifying genes required to 'maintain' ecDNA+ status is not justified - predictive features are not necessarily causal.<br /> B. The methods and procedures to identify the key genes is hyperparameterized and convoluted and casts doubt on the robustness of the findings given the size and heterogeneity of the data.<br /> a. In the first two paragraphs of Boruta Analysis Methods section, authors describe an iterative procedure where in each iteration, a binomial p-value is computed for each gene based on number of iterations thus far in which the gene was selected (higher GINI index than max of shadow features). But then in the third paragraph they simply perform Random Forest in 200 random 80% of samples and pick a gene if it is selected in at least 10/200. It is ultimately not clear what was done. Why 10/200? Also "the probability that a gene is a "hit" or "non-hit" in each iteration is 0.5" is unclear. That probability is of a gene achieving GINI index higher than the max of shadow features. How can it be 0.5?<br /> b. The approach of combining genes with clusters is arbitrary. Why not start with clusters and evaluate each cluster (using some gene set summary score) for their ability to discriminate? Ultimately, one needs additional information to disambiguate correlated genes (i.e. in a co-expression cluster) in terms of causality.<br /> c. The cross-validation procedure is not clear at all. There is a mention of 80-20 split but exactly how/if the evaluation is done on the 20% is muddled. The way precision-recall procedure is also a bit convoluted - why not simply use the area under the PR curve?<br /> d. The claim is that Boruta genes are different from differentially expressed genes but the differential expression seems to be estimated without regards to cancer type, which would certainly be highly biased and misleading. Why not do a simple regression of gene expression by ecDNA status, cancer type and select the genes that show significant coefficient for ecDNA status?<br /> C. After identifying key features (which the authors inappropriate imply to be causal) they perform a series of enrichment/correlative analysis.<br /> a. It is known that ecDNA status associates with poor survival, and so are cell cycle related signal. Then the association between Boruta genes and those processes is entirely expected. Is it not? The same goes for downregulation of immune processes.<br /> b. The association with DSB specifically is interesting. Further analysis or discussion of why this should be would strengthen the work.<br /> c. On page 15, second paragraph, when providing the up versus down CorEx genes, please also provide up versus down for non-CorEx genes as well to get a sense of magnitude.<br /> d. The finding that Boruta genes are associated with high mutation burden is intriguing because in general mutation burden is associated with better survival and immunotherapy response. This counter-intuitive result should be scrutinized more to strengthen the work.<br /> e. On page 17 "12 of the 47 genes not specifically enriching any known GO biological Process" is confusing. How can individual gene enrich for a GO process?

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors generate a Drosophila model to assess disease-linked allelic variants in the UBA5 gene. In humans, variants in UBA5 have been associated with DEE44, characterized by developmental delay, seizures, and encephalopathy. Here, the authors set out to characterize the relationship between 12 disease-linked variants in UBA5 using a variety of assays in their Drosophila Uba5 model. They first show that human UBA5 can substitute all essential functions of the Drosophila Uba5 ortholog, and then assess phenotypes in flies expressing the various disease variants. Using these assays, the authors classify the alleles into mild, intermediate, and severe loss-of-function alleles. Further, the authors establish several important in vitro assays to determine the impacts of the disease alleles on Uba5 stability and function. Together, they find a relatively close correlation between in vivo and in vitro relationships between Uba5 alleles and establish a new Drosophila model to probe the etiology of Uba5-related disorders.

Strengths:<br /> Overall, this is a convincing and well-executed study. There is clearly a need to assess disease-associated allelic variants to better understand human disorders, particularly for rare diseases, and this humanized fly model of Uba5 is a powerful system to rapidly evaluate variants and relationships to various phenotypes. The manuscript is well written, and the experiments are appropriately controlled.

Reviewer #1 (Public Review):

This work describes the induction of SIV-specific NAb responses in rhesus macaques infected with SIVmac239, a neutralization-resistant virus. Typically, host NAb responses are not detected in animals infected with SIVmac239. In this work, seventy SIVmac239-infected macaques were retrospectively screened for NAb responses and a subset of nine animals were identified as NAb-inducers. The viral genomes from 7/9 animals that induced NAb responses were found to encode nonsynonymous mutation in the Nef gene (amino acid G63E). In contrast, Nef G63E mutation was found only in 2/19 NAb non-inducers - implicating that the Nef G63E mutation is selected in NAb inducers. Measurement of Nef G63E frequencies in plasma viruses suggested that Nef G63E selection preceded NAb induction. Nef G63E mutation was found to mediate escape from Nef-specific CD8+ T-cell responses. To examine the functional phenotype of Nef G63E mutant, its effect on downmodulation of Nef-interacting host proteins was examined. Infection of rhesus and cynomolgus macaque CD4+ T cell lines with WT or Nef G63E mutant SIV suggested that Nef mutant reduces S473 phosphorylation of AKT. Using flow cytometry-based proximity ligation assay, it was shown that Nef G63E mutation reduced binding of Nef to PI3K p85/p110 and mTORC2 GβL/mLST8 and MTOR components - kinase complex responsible AKT-S473 phosphorylation. In vitro B-cell Nef invasion and in vivo imaging/flow cytometry-based assays were employed to suggest that Nef from infected cells can target Env-specific B cells. Lastly, it was determined that NAb inducers have significantly higher Env-specific B-cells responses after Nef G63E selection when compared to NAb non-inducers. Finally, a corollary was drawn between the Nef G63E-associated B-cell/NAb induction phenotype and activated PI3K delta syndrome (APDS), which is caused by activating GOF mutations in PI3K, to suggest that Nef G63E-meidated induction of NAb response is reciprocal to APDS.

Strengths:<br /> This study aims to understand the viral-host interaction that governs NAb induction in SIVmac239-infected macaques - this could enable identification of determinants important for induction of NAb responses against hard-to-neutralize tier-2/3 HIV variants. The finding that SIV-specific B-cell responses are induced following Nef G63E CD8+ T-cell escape mutant selection argue for an evolutionary trade-off between CTL escape and NAb induction. Exploitation of such a cellular-humoral immune axis could be important for HIV/AIDS vaccine efforts.

Although more validation and mechanistic basis are needed, the corollary between PI3K hyperactive signaling during autoimmune disorders and Nef-mediated abrogated PI3K signaling could help identify novel targets and modalities for targeting immune disorders and viral infections.

Weaknesses:<br /> Although the paper does have strengths in principle, the weaknesses of the paper are that the mechanistic basis of Nef-mediated induction of NAb responses are not directly examined. For example, it remains unclear whether SIVmac239 with engineered G63E mutation in Nef would induce faster and potent NAb responses. A macaque challenge study is needed to address this point.

As presented, the central premise of the paper involves infected cell-generated Nef (WT or G63E mutant) being targeted to adjacent Env-specific B cells. However, it remains unclear how this is transfer takes place. A direct evidence demonstrating CD4+ T cell-associated and/or cell-free Nef being transferred to B-cell is needed to address this concern.

The interaction between Nef and PI3K signaling components (p85, p110, GβL/mLST8, and MTOR) has been explored using PLA assay, however, this requires validation using additional biochemical and/or immunoprecipitation-based approaches. For example, is Nef (WT or mutant form) sufficient to affect PI3K-induced phosphorylation of Akt in an in vitro kinase assay? Moreover, the details regarding the binding events of WT vs mutant Nef with PI3K signaling components is lacking in this study. Lastly, it is unclear whether the interaction of Nef with PI3K signaling components is a conserved function of all primate lentiviruses or is this SIV-specific phenotype.

It has been previously reported that the region of Nef encoding glycine at position 63 is not conserved in HIV-1 (Schindler et al, Journal of Virology 2004). Thus, does HIV-1 Nef also function in induction of NAb responses in humans? or the observed phenotype specific to SIV?

Joint Public Review

In this manuscript, Karl et al. explore mechanisms underlying the activation of the receptor tyrosine kinase FGFR1 and stimulation of intracellular signaling pathways in response to FGF4, FGF8, or FGF9 binding to the extracellular domain of FGFR1. Quantitative binding experiments presented in the manuscript demonstrate that FGF4, FGF8, and FGF9 exhibit distinct binding affinities towards FGFRs. It is also proposed that FGF8 exhibits "biased ligand" characteristics that is manifested via binding and activation FGFR1 mediated by "structural differences in the FGF- FGFR1 dimers, which impact the interactions of the FGFR1 trans membrane helices, leading to differential recruitment and activation of the downstream signaling adapter FRS2".

In the absence of any structural experimental data of different forms of FGFR dimers stimulated by FGF ligands the model presents in the manuscript is speculative and misleading.

Reviewer #1 (Public Review):

The present study examined the physiological mechanisms through which impaired TG storage capacity in adipose tissues affects systemic energy homeostasis in mice. To accomplish this, the authors deleted DGAT1 and DGAT2, crucial enzymes for TG synthesis, in an adipocyte-specific manner. The authors found that ADGAT DKO mice substantially lost the adipose tissues and developed hypothermia when fasted; however, surprisingly, ADGAT KO mice were metabolically healthy on a high-fat diet. The authors found that it was accompanied by elevated energy expenditure, enhanced glucose uptake by the BAT, and enhanced browning of white adipose tissues. This unique animal model provided exciting opportunities to identify new mechanisms to maintain systemic energy homeostasis even in a compromised energy storage capacity. Overall, the data are compelling and support the conclusions of the paper. The manuscript is also clearly written.

Reviewer #1 (Public Review):

The manuscript presents a framework for studying biomechanical principles and their links to morphology and provides interesting insights into a particular question regarding terrestrial locomotion and speed. The goal of the paper is to derive general principles of directed terrestrial locomotion, speed, and symmetry.

Major strengths:<br /> The manuscript is a unique and creative work that explores performance spaces of a complicated question through computational modeling. Overall, the paper is well written and well crafted and was a pleasure to read.

The methods presented here (variable agents used to represent ultra-simplified body configurations that are not inherently constrained) are interesting and there's significant potential in them for a properly constrained question. For the data that is present here their hypotheses (while they can be anticipated from first principles) are very well validated and serve as a robust validation of these expectations and can help.

Of particular interest was the discussion of the transferability of morphologies designed under one system and moving to another. From a deep-time perspective, of particular interest is the transition from subaqueous to terrestrial locomotion which we know was a major earth life transition. The results of this study show that the best-suited morphologies for subaqueous movement are ill-suited (from a locomotor speed standpoint at least) to fully terrestrial locomotion which begs the question of if there are a suite of forms that have balanced performance in both and how that would differ from aquatic morphologies.

Major weaknesses:<br /> 1. There is a major disagreement between the target and parameters.

From a biomechanics perspective the target of this study, Directed Locomotion, is a fairly broad behavioral mode. However, what the authors are ultimately evaluating their model organisms on is a single performance parameter (speed, or distance traveled after 30s). Statements such as "bilateral symmetry showed to be a law-like pattern in animal evolution for efficient directed locomotion purposes" (p 12 line 365-366) are problematic for this reason.

Attaining the highest possible speed is a relevant but limited subset of ways one might interpret performance for directed locomotion. Efficiency, power generation, and limb loading/strain are equally relevant components.

The focus on speed coupled with selection for only the highest performing morphologies, rather than setting a minimum performance threshold, fundamentally restricts the dynamics of the system in a way that is not representative of their specified target and pulls the simulations toward a specific, anticipatable, result.

Locomotor efficiency is alluded to later in the manuscript as one of the observed outcomes, but speed is not equivalent to locomotor efficiency (in much the same way that it is not the sole metric for describing performance with respect to directed locomotion). Energy/work/power have not been accounted for in the manuscript so this is not a parameter this study weighs in on.

The data and analyses the others present do show an interesting validation of these methods in assessing first-order questions relating the shape of a single performance surface to a theoretical morphology, which has significant potential value.

2. There is a significant population and/or sample size and biasing.

Thirty simulations of a population of 101 morphologies seems small for a study of this kind, particularly looking to investigate such a broad question at an abstract level. Particularly when the top 50% of morphologies are chosen to mutate. It would be very easy for artificial biases to rapidly propagate through this system depending on the parameters bounding the formation of the initial generation.

This strong selection choosing the best 50 morphologies and mutating them enforces an aggressive effect that simulates an even more potent phylogenetic inertia than one might anticipate for an actual evolutionary history (it's no surprise then that all of the simulations were able to successfully retrieve a suite of morphotypes that recovered the performance peak for this system within 1500 generations).

Similarly, why is it that a 4^3 voxel limit was chosen? One can imagine that an increase in this voxel limit would allow for the development of more extreme geometries, which might be successful. It is likely that there might be computational resource constraints involved in this, it would be useful for the authors to add additional context here.

Reviewer #1 (Public Review):

Tomasi et al. performed a combination of bioinformatic, next-generation tRNA sequencing experiments to predict the set of tRNA modifications and their corresponding genes in the tRNAs of the pathogenic bacteria Mycobacterium tuberculosis. Long known to be important for translation accuracy and efficiency, tRNA modifications are now emerging as having regulatory roles. However, the basic knowledge of the position and nature of the modifications present in a given organism is very sparse beyond a handful of model organisms. Studies that can generate the tRNA modification maps in different organisms along the tree of life are good starting points for further studies. The focus here on a major human pathogen that is studied by a large community raises the general interest of the study. Finally, deletion of the gene mnmA responsible for the insertion of s2U at position 34 revealed defects in growth in macrophage but in test tubes suggesting regulatory roles that will warrant further studies. The conclusions of the paper are mostly supported by the data but the partial nature of the bioinformatic analysis and absence of Mass-Spectrometry data make it incomplete. The authors do not take advantage of the Mass spec data that is published for Mycobacterium bovis (PMID: 27834374) to discuss what they find.

Reviewer #1 (Public Review):

This manuscript represents an elegant bioinformatics approach to addressing causal pathways in vascular and liver tissue related to atherosclerosis/coronary artery disease, including those shared by humans and mice and those that are specific to only one of these species. The authors constructed co-expression networks using bulk transcriptome data from human (aorta, coronary) and mouse (aorta) vascular and liver tissue. They mapped human CAD GWAS data onto these modules, mapped GWAS SNPs to putatively causal genes, identified pathways and modules enriched in CAD GWAS hits, assessed those shared between vascular and liver tissues and between humans and mice, determined key driver genes in CAD-associated supersets, and used mouse single-cell transcriptome data to infer the roles of specific vascular and liver cell types. The overall approach used by the authors is rigorous and provides new insights into potentially causal pathways in vascular tissue and liver involved in atherosclerosis/CAD that are shared between humans and mice as well as those that are species-specific. This approach could be applied to a variety of other common complex conditions.

The conclusions are largely supported by the analyses. Some specific comments:

1. It appears that GWAS SNPs were mapped to genes solely through the use of eQTLs. Current methods involve a number of other complementary approaches to map GWAS SNPs to effector genes/transcripts and there is the thought that eQTLs may not necessarily be the best way to map causal genes.<br /> 2. Given the critical causal role of circulating apoB lipoproteins in atherosclerosis in both mice and humans and the central role of the liver in regulating their levels, perhaps the authors could use the 'metabolism of lipids and lipoproteins' network in Fig 3B as a kind of 'positive control' to illustrate the overlap between mice and humans and the driver genes for this network.<br /> 3. Is it possible to infer the directionality of effect of key driver genes and pathways from these analyses? For example, ACADM was found to be a KD gene for a human-specific liver CAD superset pathway involving BCAA degradation. Are the authors able to determine or predict the effect of genetically increased expression of ACADM on BCAA metabolism and on CAD? Or the directionality of the effect of the hepatic KD gene OIT3 on hepatic and plasma lipids and atherosclerosis.<br /> 4. While likely beyond the scope of this manuscript, the substantial amount of publicly available plasma proteomic and metabolomic data could be incorporated into this multiomic bioinformatic analysis. Many of the pathways involve secreted proteins or metabolites that would further inform the biology and the understanding of how these pathways relate to atherosclerosis.

The findings here will motivate the community of atherosclerosis investigators to pursue additional potential causal genes and pathways through computational and experimental approaches. It will also influence the approach around the use of the mouse model to test specific pathways and therapeutic approaches in atherosclerosis. In addition, the computational approach is robust and could (and likely will) be applied to a variety of other common complex conditions.

Reviewer #1 (Public Review):

First, I agree with the authors of this manuscript that conformational changes in the XFEL structures with 2.8 A resolution are not reliable enough for demonstrating the subtle changes in the electron transfer events in this bacterial photosynthesis system. Actually, the data statistics in the paper by Dods et al. showed that the high-resolution range of some of the XFEL datasets may include pretty high noise (low CC1/2 and high Rsplit) so the comparison of the subtle conformational changes of the structures is problematic.

The manuscript by Gai Nishikawa investigated time-dependent changes in the energetics of the electron transfer pathway based on the structures by Dods et al. by calculating redox potential of the active and inactive branches in the structures and found no clear link between the time-dependent structural changes and the electron transfer events in the XFEL structures published by Dods, R.et al. (2021). This study provided validation for the interpretation of the structures of those electron-transferring proteins.

The paper was well prepared.

Reviewer #1 (Public Review):

In this manuscript, Kubori and colleagues characterized the manipulation of the host cell GTPase Rab10 by several Legionella effector proteins, specifically members of the SidE and SidC family. They show that Rab10 undergoes both conventional ubiquitination and noncanonical phosphoribose-ubiquitination, and that this posttranslational modification contributes to the retention of Rab10 around Legionella vacuoles.

Strengths<br /> Legionella is an emerging pathogen of increasing importance, and dissecting its virulence mechanisms allows us to better prevent and treat infections with this organism. How Legionella and related pathogens exploit the function of host cell vesicle transport GTPases of the Rab family is a topic of great interest to the microbial pathogenesis field. This manuscript investigates the molecular processes underlying Rab10 GTPase manipulation by several Legionella effector proteins, most notably members of the SidE and SidC families. The finding that MavC conjugates ubiquitin to SdcB to regulate its function is novel, and sheds further light into the complex network of ubiquitin-related effectors from Lp. The manuscript is well written, and the experiments were performed carefully and examined meticulously.

Weaknesses<br /> Unfortunately, in its current form this manuscript offers only little additional insight into the role of effector-mediated ubiquitination during Lp infection beyond what has already been published. The enzymatic activities of the SidC and SidE family members were already known prior to this study, as was the importance of Rab10 for optimal Lp virulence. Likewise, it had previously been shown that SidE and SidC family members ubiquitinate various host Rab GTPases, like Rab33 and Rab1. The main contribution of this study is to show that Rab10 is also a substrate of the SidE and SidC family of effectors. What remains unclear is if Rab10 is indeed the main biological target of SdcB (not just 'a' target), and how exactly Rab10 modification with ubiquitin benefits Lp infection.

Reviewer #1 (Public Review):

This manuscript describes the transient proteolysis of several Nups during myogenesis due to activation of caspase 3, and how this "trimming" leads to defects in nuclear export. The authors show the NPC-related course of events during cellular differentiation and suggest mechanistic insights into exactly why this limited proteolysis is needed for myogenesis. In addition, the authors introduce a novel concept for caspase cellular function that might be worth investigating in the future. Overall, the authors present an elegant and interesting piece of work, performed at the usual superb quality of this group, and indeed the figures throughout the manuscript clearly show a very high level of experimental expertise.

Reviewer #1 (Public Review):

The authors revealed that spermatogonia-related genes (e.g., Plzf, Id4, Setdb1, Stra8, Tial1/Tiar, Bcas2, Ddx5, Srsf10, Uhrf1, and Bud31) were bound by SRSF1 in the mouse testes by Crosslinking immunoprecipitation and sequencing (CLIP-seq). Using Vasa-cre mouse line, the authors successfully evidenced that SRSF1 in the testis is essential for homing and self-renewal in mouse spermatogonial stem cells. Further evidence showed that SRSF1 directly binds and regulates the expression of Tial1/Tiar via AS to implement SSC homing and self-renewal. Immunoprecipitation mass spectrometry (IP-MS) data showed that the AS of SSC is regulated by SRSF1 coordinated with other RNA splicing-related proteins (e.g., SRSF10, SART1, RBM15, SRRM2, SF3B6, and SF3A2). The authors revealed the critical role of SRSF1-mediated AS in SSC homing and self-renewal, which may provide a framework to elucidate the molecular mechanisms of the posttranscriptional network underlying the formation of SSC pools and the establishment of niches. The experiments are well-designed and conducted, the overall conclusions are convincing. This work will be of interest to stem cell and reproductive biologists.

Reviewer #1 (Public Review):

The authors assess the accuracy of AlphaFold2 (AF2) structures for small molecule ligand pose prediction versus the accuracy with traditional template-based homology models and experimental crystal structures (with a different ligand). They take a careful, rigorous approach leveraging the wealth of structural data around the GPCR protein family and using state-of-the-art docking methods. They find that binding sites are significantly more accurately modeled by AF2 compared to traditional template-based approaches, but this does not translate to greater accuracy in small-molecule docking pose prediction. The important findings around this conclusion have broad implications for the use of AF2 models in ligand binding pose prediction for proteins and drug design.

Strengths:<br /> The strength of the work is the rigor and careful, thoughtful comparison that cleverly leverages the cut-off date of April 30th, 2018 used in the training of AF2. While the authors list their limited number of docking methods as a caveat, the fact that they use three state-of-the-art ligand docking methods is a strength of the work; many studies use just one. The rigorous analysis of the binding site RMSD and docked ligand pose RMSD is novel to my knowledge and is particularly insightful.

Weaknesses:<br /> The authors are rigorous in their approach by using state-of-the-art workflows that are high-throughput in nature. However, human expert-refined models and expert selection from multiple models could improve the results of ligand pose prediction when using protein models. The authors alluded to this for traditional models but this can also be true when starting from AF2 models. This is difficult to test systematically and rigorously, however. One possible experiment is to explore whether using multiple AF2 models (there are five by default) would have an effect on pose accuracy, perhaps for selected examples such as NK1R, 5HT2A, and DRD1 to help build out the discussion further. Another possible weakness is that the authors focus only on GPCRs for reasons they state but make a good argument as to why the conclusions are likely to extend to other protein classes.

Context:<br /> One of the most common and impactful uses of protein structures is in small molecule therapeutic chemical tool design. When no experimental structure is available, models are frequently used and such models include traditional template-based homology models and, more recently, AF2 models. AF2 is widely recognized as an inflection point in protein structure prediction due to the unprecedented accuracy of the protein structure models produced automatically. However, understanding whether this unprecedented accuracy translates to better small molecule ligand pose prediction has been an open question, and this study directly addresses the question in a systematic, rigorous approach.