Reviewer #2 (Public Review):

Summary:

This study by Park and Gross investigates the spatiotemporal neural representation of semantic information most pertinent to the gist of speech materials presented to subjects as magnetoencephalography was recorded. Participants heard and saw naturalistic continuous speech recordings (with the auditory component presented to one ear), while also presented with distractor auditory speech (presented in the other ear). Participants were instructed to attend to the speech stream that matched the video of the speaker. The stimuli were semantically parsed to create short segments to which topic probabilities were assigned. These segments were then organized into high and low topic probabilities for each of the four topics (determined using Latent Dirichlet Allocation (LDA) analysis). The results suggest clear differences in the fidelity of neural encoding of the speech envelope during high-topic probability segments, which is interpreted as the brain representing key information for a story whether that information is explicitly attended to.

Strengths:<br /> The use of LDA analysis makes possible the quantification of whether a particular speech segment is relevant to a particular topic and enables analysis based on this high-temporal resolution of semantic salience. The authors show clear differences between attended and unattended speech conditions, as well as, surprisingly, differences between semantically salient unattended speech and attended, less semantically relevant speech.

Weaknesses:<br /> Though the effect sizes of the results of this study show clear differences between stimulus conditions, clarification of the experimental methods is needed to appreciate their interpretation. Broadly, I would suggest adding a clearer description of the task during data collection, even though it has been published elsewhere.

One key piece of information that is missing is how semantically relevant topics are assigned, so that salient semantic information can be compared between attended and unattended stories. It's unclear to me how results are combined across topics and stories. If a particular speech segment is assigned 4 topic probabilities, that segment has both a high probability of belonging to one topic and a low probability of belonging to another. I understand how this can be used to create the experimental conditions for a single topic, but how are results combined across topics?

I think some discussion of using the encoding and decoding of the speech envelope as a measure of what is semantically relevant is warranted. The fidelity with which the speech envelop is represented has been used as a proxy for how well that speech is attended to, but it is unclear to me whether we should expect to see high-fidelity encoding of speech envelop outside of the primary and secondary auditory regions of the brain, or how it relates to the semantic information contained in the speech signal.

Additionally, I wonder if it might be more informative to decode the topic labels themselves directly by building a model to predict the topic probabilities from the neural data? This might give a more direct measure of where and when semantically relevant information is represented.

Reviewer #1 (Public Review):

This is a clear account of some interesting work. The experiments and analyses seem well done and the data are useful. It is nice to see that VSDI results square well with those from prior extracellular recordings. But the work may be less original than the authors propose, and their overall framing strikes me as odd. Some additional clarifications could make the contribution more clear.

My reading is that this is primarily a study of surround suppression with results that follow pretty directly from what we already know from that literature, and although they engage with some of the literature they do not directly mention surround suppression in the text. Their major effect - what they repeatedly describe as a "paradoxical" result in which the responses initially show a stronger response to matched targets and backgrounds and then reverse - seems to pretty clearly match the expected outcome of a stimulus that initially evokes additional excitation due to increased center contrast followed by slightly delayed surround suppression tuned to the same peak orientation. Their dynamics result seems entirely consistent with previous work, e.g. Henry et al 2020, particularly their Fig. 3 https://elifesciences.org/articles/54264, so it seems like a major oversight to not engage with that work at all, and to explain what exactly is new here.

- In the discussion (lines 315-316), they state "in order to account for the reduced neural sensitivity with target-background similarity in the second phase of the response, the divisive normalization signal has to be orientation selective." I wonder whether they observed this in their modeling. That is, how robust were the normalization model results to the values of sigma_e and sigma_n? It would be useful to know how critical their various model parameters were for replicating the experimental effects, rather than just showing that a good account is possible.

- The majority of their target/background contrast conditions were collected only in one animal. This is a minor limitation for work of this kind, but it might be an issue for some.

- The authors point out (line 193-195) that "Because the first phase of the response is shorter than the second phase, when V1 response is integrated over both phases, the overall response is positively correlated with the behavioral masking effect." I wonder if this could be explored a bit more at the behavioral level - i.e. does the "similarity masking" they are trying to explain show sensitivity to presentation time?

- From Fig. 3 it looks like the imaging ROI may include some opercular V2. If so, it's plausible that something about the retinotopic or columnar windowing they used in analysis may remove V2 signals, but they don't comment. Maybe they could tell us how they ensured they only included V1?

- In the discussion (lines 278-283) they say "The positive correlation between the neural and behavioral masking effects occurred earlier and was more robust at the columnar scale than at the retinotopic scale, suggesting that behavioral performance in our task is dominated by columnar scale signals in the second phase of the response. To the best of our knowledge, this is the first demonstration of such decoupling between V1 responses at the retinotopic and columnar scales, and the first demonstration that columnar scale signals are a better predictor of behavioral performance in a detection task." I am having trouble finding where exactly they demonstrate this in the results. Is this just by comparison of Figs. 4E,K and 5E,K? I may just be missing something here, but the argument needs to be made more clearly since much of their claim to originality rests on it.

Reviewer #1 (Public Review):

This manuscript by Leibinger et al describes their results from testing an interesting hypothesis that microtubule detyrosination inhibits axon regeneration and its inhibitor parthenolide could facilitate axon regeneration and perhaps functional recovery. Overall, the results from in vitro studies are largely well performed. However, the in vivo data are less convincing.

Interpretation of the findings in this study are limited by several gaps:<br /> 1. It is unclear whether microtubule detyrosination a primary effect of hIL-6 and PTEN deletion or secondary to the increased axon growth?

2. Is there any direct evidence for Akt and/or JAK/Stat3 to promote microtubule detyrosination?

3. What is the impact of parthenolide on cell soma of neurons and other cell types?

4. Direct evidence that parthenolide augments PTEN deletion in optic nerve or spinal cord is not provided.

5. Serotonergic neurotoxin DHT ablates both regenerating and non-regenerating serotonergic axons, which makes spinal cord findings it difficult to interpret.

6. DMAPT was given by i.p. injection. What happens to microtubule detyrosination in other cells within and outside of CNS?

Reviewer #2 (Public Review):

In the current study, Fischer and colleagues extensively examined the role of parthenolide in inhibiting microtubule detyrosination and making the mechanistic link for the compound to facilitate the role of IL6 and PTEN/KO in promoting neurite outgrowth and axon regeneration. The in vitro and mechanistic work laid the foundation for the authors to reach several key predictions that such detyrosination can be applied for in vivo applications. Thus the authors extended the work to optic nerve regeneration and spinal cord recovery. The in vivo compound that the authors utilized is DMAPT, which plays a synergistic role with existing pro-regeneration therapies, such as Il6 treatment.

The major strength of the work is the first half of the mechanistic inquiries, where the authors combined cell biology and biochemistry approaches to dissect the mechanistic link from parthenolide to microtube dynamics. The shortcoming is that the in vivo data is limited, and the effects might be considered mild, especially by benchmarking with other established and effective strategies.

The work is solid and prepares a basis for others to test the role of DMAPT in other settings, especially in the setting of other effective pro-regenerative approaches. With the goal of comprehensive and functional recovery in vivo, the impact of the work and the utilities of the methods remain to be tested broadly in other models in vivo.

Reviewer #3 (Public Review):

The primary goal of this paper is to examine microtubule detyrosination as a potential therapeutic target for axon regeneration. Using dimethylamino-parthenolide (DMAPT), this study extensively examines mechanistic links between microtubule detyrosination, interleukin-6 (IL-6), and PTEN in neurite outgrowth in retinal ganglion cells in vitro. These findings provide convincing evidence that parthenolide has a synergistic effect on IL-6- and PTEN-related mechanisms of neurite outgrowth in vitro. The potential efficacy of systemic DMAPT treatment to promote axon regeneration in mouse models of optic nerve crush and spinal cord injury was also examined.

Strengths<br /> 1. The examination of synergistic activities between parthenolide, hyperIL-6, and PTEN knockout is leveraged not only for potential therapeutic value, but also to validate and delineate mechanism of action.<br /> 2. The in vitro studies, including primary human retinal ganglion cells, utilize a multi-level approach to dissect the mechanistic link from parthenolide to microtubule dynamics.<br /> 3. The studies provide a basis for others to test the role of DMAPT in other settings, particularly in the context of other effective pro-regenerative approaches.

Weaknesses<br /> 1. In vivo studies are limited to select outcomes of recovery and do not validate or address mechanism of action in vivo.

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 #2 (Public Review):

Place cells fire sequentially during hippocampal theta oscillations, forming a spatial representation of behavioral experiences in a temporally-compressed manner. The firing sequences during theta cycles are widely considered as essential assemblies for learning, memory, and planning. Many theoretical studies have investigated the mechanism of hippocampal theta firing sequences; however, they are either entirely extrinsic or intrinsic. In other words, they attribute the theta sequences to external sensorimotor drives or focus exclusively on the inherent firing patterns facilitated by the recurrent network architectures. Both types of theories are inadequate for explaining the complexity of the phenomena, particularly considering the observations in a previous paper by the authors: theta sequences independent of animal movement trajectories may occur simultaneously with sensorimotor inputs (Yiu et al., 2022).

In this manuscript, the authors concentrate on the CA3 area of the hippocampus and develop a model that accounts for both mechanisms. Specifically, the model generates extrinsic sequences through the short-term facilitation of CA3 cell activities, and intrinsic sequences via recurrent projections from the dentate gyrus. The model demonstrates how the phase precession of place cells in theta sequences is modulated by running direction and the recurrent DG-CA3 network architecture. To evaluate the extent to which firing sequences are induced by sensorimotor inputs and recurrent network architecture, the authors use the Pearson correlation coefficient to measure the "intrinsicity" and "extrinsicity" of spike pairs in their simulations.

I find this research topic to be both important and interesting, and I appreciate the clarity of the paper. The idea of combining intrinsic and extrinsic mechanisms for theta sequences is novel, and the model effectively incorporates two crucial phenomena: phase precession and directionality of theta sequences. I particularly commend the authors' efforts to integrate previous theories into their model and conduct a systematic comparison. This is exactly what our community needs: not only the development of new models, but also understanding the critical relationships between different models.

Reviewer #1 (Public Review):

The authors present a study of visuo-motor coupling primarily using wide-field calcium imaging to measure activity across the dorsal visual cortex. They used different mouse lines or systemically injected viral vectors to allow imaging of calcium activity from specific cell-types with a particular focus on a mouse-line that expresses GCaMP in layer 5 IT (intratelencephalic) neurons. They examined the question of how the neural response to predictable visual input, as a consequence of self-motion, differed from responses to unpredictable input. They identify layer 5 IT cells as having a different response pattern to other cell-types/layers in that they show differences in their response to closed-loop (i.e. predictable) vs open-loop (i.e. unpredictable) stimulation whereas other cell-types showed similar activity patterns between these two conditions. Surprisingly, they find that presentation of a visual grating actually decreases the responses of L5 IT cells in V1. They interpret their results within a predictive coding framework that the last author has previously proposed. The response pattern of the L5 IT cells leads them to propose that these cells may act as 'internal representation' neurons that carry a representation of the brain's model of its environment. Though this is rather speculative. They subsequently examine the responses of these cells to anti-psychotic drugs (e.g. clozapine) with the reasoning that a leading theory of schizophrenia is a disturbance of the brain's internal model and/or a failure to correctly predict the sensory consequences of self-movement. They find that anti-psychotic drugs strongly enhance responses of L5 IT cells to locomotion while having little effect on other cell-types. Finally, they suggest that anti-psychotics reduce long-range correlations between (predominantly) L5 cells and reduce the propagation of prediction errors to higher visual areas and suggest this maybe a mechanism by which these drugs reduce hallucinations/psychosis.

This is a large study containing a screening of many mouse-lines/expression profiles using wide-field calcium imaging. Wide-field imaging has its caveats, including a broad point-spread function of the signal and susceptibility to hemodynamic artifacts, which can make interpretation of results difficult. The authors acknowledge these problems and directly address the hemodynamic occlusion problem. It was reassuring to see supplementary 2-photon imaging of soma to complement this data-set, even though this is rather briefly described in the paper. Overall the paper's strengths are its identification of a very different response profile in the L5 IT cells compared other layers/cell-types which suggests an important role for these cells in handling integration of self-motion generated sensory predictions with sensory input. The interpretation of the responses to anti-psychotic drugs is more speculative but the result appears robust and provides an interesting basis for further studies of this effect with more specific recording techniques and possibly behavioral measures.

Reviewer #2 (Public Review):

Summary:<br /> This work investigates the effects of various antipsychotic drugs on cortical responses during visuomotor integration. Using wide-field calcium imaging in a virtual reality setup, the researchers compare neuronal responses to self-generated movement during locomotion-congruent (closed loop) or locomotion-incongruent (open loop) visual stimulation. Moreover, they probe responses to unexpected visual events (halt of visual flow, sudden-onset drifting grating). The researchers find that, in contrast to a variety of excitatory and inhibitory cell types, genetically defined layer 5 excitatory neurons distinguish between the closed and the open loop condition and exhibit activity patterns in visual cortex in response to unexpected events, consistent with unsigned prediction error coding. Motivated by the idea that prediction error coding is aberrant in psychosis, the authors then inject the antipsychotic drug clozapine, and observe that this intervention specifically affects closed loop responses of layer 5 excitatory neurons, blunting the distinction between the open and closed loop conditions. Clozapine also leads to a decrease in long-range correlations between L5 activity in different brain regions, and similar effects are observed for two other antipsychotics, aripripazole and haloperidol, but not for saline or the stimulant amphetamine. The authors suggest that altered prediction error coding in layer 5 excitatory neurons due to reduced long-range correlations in L5 neurons might be a major effect of antipsychotic drugs and speculate that this might serve as a new biomarker for drug development.

Strengths:<br /> - Relevant and interesting research question:<br /> The distinction between expected and unexpected stimuli is blunted in psychosis but the neural mechanisms remain unclear. Therefore, it is critical to understand whether and how antipsychotic drugs used to treat psychosis affect cortical responses to expected and unexpected stimuli. This study provides important insights into this question by identifying a specific cortical cell type and long-range interactions as potential targets. The authors identify layer 5 excitatory neurons as a site where functional effects of antipsychotic drugs manifest. This is particularly interesting as these deep layer neurons have been proposed to play a crucial role in computing the integration of predictions, which is thought to be disrupted in psychosis. This work therefore has the potential to guide future investigations on psychosis and predictive coding towards these layer 5 neurons, and ultimately improve our understanding of the neural basis of psychotic symptoms.

- Broad investigation of different cell types and cortical regions:<br /> One of the major strengths of this study is quasi-systematic approach towards cell types and cortical regions. By analysing a wide range of genetically defined excitatory and inhibitory cell types, the authors were able to identify layer 5 excitatory neurons as exhibiting the strongest responses to unexpected vs. expected stimuli and being the most affected by antipsychotic drugs. Hence, this quasi-systematic approach provides valuable insights into the functional effects of antipsychotic drugs on the brain, and can guide future investigations towards the mechanisms by which these medications affect cortical neurons.

- Bridging theory with experiments<br /> Another strength of this study is its theoretical framework, which is grounded in the predictive coding theory. The authors use this theory as a guiding principle to motivate their experimental approach connecting visual responses in different layers with psychosis and antipsychotic drugs. This integration of theory and experimentation is a powerful approach to tie together the various findings the authors present and to contribute to the development of a coherent model of how the brain processes visual information both in health and in disease.

Weaknesses:<br /> - Unclear relevance for psychosis research<br /> From the study, it remains unclear whether the findings might indeed be able to normalise altered predictive coding in psychosis. Psychosis is characterised by a blunted distinction between predicted and unpredicted stimuli. The main results of this study indicate that antipsychotic drugs further blunt the distinction between predicted and unpredicted stimuli, which would suggest that antipsychotic drugs would deteriorate rather than ameliorate the predictive coding deficit found in psychosis. However, these findings were based on observations in wild-type mice at baseline. Given that antipsychotics are thought to have little effects in health but potent antipsychotic effects in psychosis, it seems possible that the presented results might be different in a condition modelling a psychotic state, for example after a dopamine-agonistic or a NMDA-antagonistic challenge. Therefore, future work in models of psychotic states is needed to further investigate the translational relevance of these findings.

- Incomplete testing of predictive coding interpretation<br /> While the investigation of neuronal responses to different visual flow stimuli is interesting, it remains open whether these responses indeed reflect internal representations in the framework of predictive coding. While the responses are consistent with internal representation as defined by the researchers, i.e., unsigned prediction error signals, an alternative interpretation might be that responses simply reflect sensory bottom-up signals that are more related to some low-level stimulus characteristics than to prediction errors. Moreover, this interpretational uncertainty is compounded by the fact that the used experimental paradigms were not suited to test whether behaviour is impacted as a function of the visual stimulation which makes it difficult to assess what the internal representation of the animal actually was. For these reasons, the observed effects might reflect simple bottom-up sensory processing alterations and not necessarily have any functional consequences. While this potential alternative explanation does not detract from the value of the study, future work would be needed to explain the effect of antipsychotic drugs on responses to visual flow. For example, experimental designs that systematically vary the predictive strength of coupled events or that include a behavioural readout might be more suited to draw from conclusions about whether antipsychotic drugs indeed alter internal representations.

Conclusion:<br /> Overall, the results support the idea that antipsychotic drugs affect neural responses to predicted and unpredicted stimuli in deep layers of cortex. Although some future work is required to establish whether this observation can indeed be explained by a drug-specific effect on predictive coding, the study provides important insights into the neural underpinnings of visual processing and antipsychotic drugs, which is expected to guide future investigations on the predictive coding hypothesis of psychosis. This will be of broad interest to neuroscientists working on predictive coding in health and disease.

Reviewer #3 (Public Review):

The study examines how different cell types in various regions of the mouse dorsal cortex respond to visuomotor integration and how antipsychotic drugs impacts these responses. Specifically, in contrast to most cell types, the authors found that activity in Layer 5 intratelencephalic neurons (Tlx3+) and Layer 6 neurons (Ntsr1+) differentiated between open loop and closed loop visuomotor conditions. Focussing on Layer 5 neurons, they found that the activity of these neurons also differentiated between negative and positive prediction errors during visuomotor integration. The authors further demonstrated that the antipsychotic drugs reduced the correlation of Layer 5 neuronal activity across regions of the cortex, and impaired the propagation of visuomotor mismatch responses (specifically, negative prediction errors) across Layer 5 neurons of the cortex, suggesting a decoupling of long-range cortical interactions.<br /> The data when taken as a whole demonstrate that visuomotor integration in deeper cortical layers is different than in superficial layers and is more susceptible to disruption by antipsychotics. Whilst it is already known that deep layers integrate information differently from superficial layers, this study provides more specific insight into these differences. Moreover, this study provides a first step into understanding the potential mechanism by which antipsychotics may exert their effect.<br /> Whilst the paper has several strengths, the robustness of its conclusions is limited by weaknesses in statistical analyses. A summary of the paper's strengths and weaknesses follow.

Strengths:

The authors perform an extensive investigation of how different cortical cell types (including Layer 2/3, 4 , 5, and 6 excitatory neurons, as well as PV, VIP, and SST inhibitory interneurons) in different cortical areas (including primary and secondary visual areas as well as motor and premotor areas), respond to visuomotor integration. This investigation provides strong support to the idea that deep layer neurons are indeed unique in their computational properties. This large data set will be of considerable interest to neuroscientists interested in cortical processing.<br /> The authors also provide several lines of evidence that visuomotor information is differentially integrated in deep vs. superficial layers. They show that this is true across experimental paradigms of visuomotor processing (open loop, closed loop, mismatch, drifting grating conditions) and experimental manipulations, with the demonstration that Layer 5 visuomotor integration is more sensitive to disruption by the antipsychotic drug clozapine, compared with cortex as a whole.

The study further uses multiple drugs (clozapine, aripiprazole and haloperidol) to bolster its conclusion that antipsychotic drugs disrupt correlated cortical activity in Layer 5 neurons, and further demonstrates that this disruption is specific to antipsychotics, as the psychostimulant amphetamine shows no such effect.

In widefield calcium imaging experiments, the authors effectively control for the impact of hemodynamic occlusions in their results, and try to minimize this impact using a crystal skull preparation, which performs better than traditional glass windows. Moreover, they examine key findings in widefield calcium imaging experiments with two-photon imaging.

Weaknesses:

A critical weakness of the paper is its statistical analysis and data representations. The study does not use mice as its independent unit for statistical comparisons but rather relies on other definitions (see authors' Tabe S1), without appropriate justification, which results in an inflation of sample sizes. For example, in Figure 2, the independent statistical unit is defined as sessions instead of mice, and in Figures 6 and 7 its pairs of cortical regions of interest. This greatly inflates N by at least 1-2 orders of magnitude compared to using N = number of mice. With such inflated sample sizes, it becomes more likely to find spurious differences between groups as significant.

It should be noted, however, that the authors have redone some analyses in their revision, specifically for Figure 1L, in which mice are used as independent units (shown in Figure S4) without any change in conclusion. However, this is not done for all other problematic figures in the manuscript.

Furthermore - and related to the previous comment - trace averages and SEMs across the figures of the manuscript come from hundreds to thousands of data points (e.g. locomotion onsets or cells) repeatedly measured from only a handful of mice. This can be visually misleading for the reader (even if statistics are not being formally performed on these traces) as it artificially reduces the size of the SEM masking the true variability (and size) of the effects portrayed in the paper. Again, this practice is only justified if the data (e.g. locomotion onsets) within a mouse is actually statistically independent, which the authors do not test for or justify.

It should be noted that the authors do show some trace averages and SEMs for a some of their data (Figure S2), in which N = individual mice, without any change in conclusion. However, this is not done for all other problematic figures in the manuscript.

The above statistical problems are apparent throughout the manuscript. The more disciplined approach would be to average the data within a mouse, and then use the mouse as an independent unit for statistical comparison and/or for the purposes of presenting means and SEMs for aggregate data. Alternatively, the authors should provide clear justification in the manuscript for opting for other definitions of N.

Finally, it is important to note that whilst the study demonstrates that antipsychotics may selectively impact visuomotor integration in L5 neurons, it does not show that this effect is necessary or sufficient for the action of antipsychotics; though this is likely beyond the scope of the study it is something for readers to keep in mind.

Reviewer #1 (Public Review):

In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.

They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial surface and a tRG that contacts the ventricular surface. They find that the tRGs consist of three distinct subpopulations two of which are committed to ependymal and astroglial fates.

By integrating these data with publicly available data of developing human brains and human brain organoids they make some important observations. Human and ferret tRGs have very similar transcriptional states, suggesting that the human tRGs too give rise to ependymal and astroglial fates. They also find that the current culture conditions of human brain organoids seem to lack tRGs, something that will need to be addressed if they are to be used to study tRGs. While the primary human data set did contain tRGs, the stage or the region sampled were likely not appropriate, and therefore, the number of cells they could retrieve was low.

The authors have spent considerable efforts in improving gene modeling of the ferret genome, which will be important for the field. They've generated valuable time series data for the developing ferret brain, and have proposed the lineal progeny for the tRGs in the human brain. Whether tRGs actually do give rise to the ependymal and astrogial fates needs to be validated in future studies.

Reviewer #2 (Public Review):

Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.

Reviewer #2 (Public Review):

Summary:<br /> In this article, the authors provide a method of evaluating the safety of orthopedic implants in relation to radiofrequency-induced heating issues. The authors provide an open-source computational heterogeneous human model and explain computational techniques in a finite element method solver to predict the RF-induced temperature increase due to an orthopedic implant while being exposed to MRI RF fields at 1.5 T.

Strengths:<br /> The open-access computational human model along with their semiautomatic algorithm to position the implant can help realistically model the implant RF exposure in patients avoiding over- or under-estimation of RF heating measured using rectangular box phantoms such as ASTM phantom. Additionally, using numerical simulation to predict radiofrequency-induced heating will be much easier compared to the experimental measurements in an MRI scanner, especially when the scanner availability is limited.

Weaknesses:<br /> The proposed method only used radiofrequency (RF) field exposure to evaluate the heating around the implant. However, in the case of bulky implants, the rapidly changing gradient field can also produce significant heating due to large eddy currents. So the gradient-induced heating still remains an issue to be evaluated to decide on the safety of the patient. Moreover, the method is limited to a single human model and might not be representative of patients with different age, sex, and body weights. Additionally, the authors compare the temperature rise predicted by their method to an earlier study. However, there is no information about how they controlled the input power in their simulation testbed compared to the earlier study in showing validation of the method.

Reviewer #1 (Public Review):

Summary:<br /> In this work, the authors are trying to satisfy a real need in MR safety, when concerns can arise about the thermal increase due to metallic materials in patients carrying orthopedic implants. The "MR conditional" labeling of the implant obtained by ASTM in-vitro tests may help to plan the MR scan, but it is normally limited to a single specific MR sequence and a B0 value, and it is not always available. The adoption of an in-silico simulation testbed overcomes this limitation, providing a fast and reliable prediction of temperature increase from RF, in real-life scan conditions on human-like digital models. The FDA is pushing this approach.

Strengths:<br /> The presented in-silico testbed looks valuable and validated. It is based on the widely available Visible Human Project (VHP) datasets, and the testbed is available online. The approval of the testbed by the FDA as a medical device development tool (MDDT) is a good premise for the large-scale adoption of this kind of solution.

Weaknesses:<br /> There are a couple of limitations in the study that must be clearly highlighted to the readers.

While the RF-related heating is very well modeled, the gradients-related heating is out of the scope of this paper and not considered. Readers must be warned that RF causes only a part of the heating, and literature is reporting cases where also gradient switching can contribute, as correctly mentioned in this work. A cautious attitude should consider this as a significant limitation of the study.

Moreover, the way the implant is embedded in the VHP model is shortly documented in the materials and methods and mostly focuses on implant registration on bone tissue. It is not clear how to manage the empty space and the soft tissue stretching/reshaping generated by the simulated surgery (for example, by the cut of the femoral head in total hip arthroplasty). It is reported by literature that the level of accuracy in the simulated surgery can impact in some cases (RF vs. gradients heating, massive vs. thin or elongated implants) on temperature predictions.

Reviewer #2 (Public Review):

This paper illustrates that PSCs can model myogenesis in vitro by mimicking the in vivo development of the somite and dermomyotome. The advantages of this 3D system include (1) better structural distinctions, (2) the persistence of progenitors, and (3) the spatial distribution (e.g. migration, confinement) of progenitors. The finding is important with the implication in disease modeling. Indeed the authors tried DMD model although it suffered the lack of deeper characterization.

The differentiation protocol is based on a current understanding of myogenesis and is compelling. They characterized the organoids in depth (e.g. many time points and immunofluorescence). The evidence is solid.

Reviewer #1 (Public Review):

The authors aimed to establish a cell culture system to investigate muscle tissue development and homeostasis. They successfully developed a complex 3D cell model and conducted a comprehensive molecular and functional characterization. This approach represents a critical initial step towards using human cells, rather than animals, to study muscular disorders in vitro. Although the current protocol is time-consuming and the fetal cell model may not be mature enough to study adult-onset diseases, it nonetheless provides a valuable foundation for future disease modeling studies using isogenic iPSC lines or patient-derived cells with specific mutations. The manuscript does not explore whether or how this stem cell model can advance our understanding of muscular diseases, which would be an exciting avenue for future research. Overall, the detailed protocol presented in this paper will be useful for informing future studies and provide a valuable resource to the stem cells community. Future work could focus on disease modeling using isogenic iPSC lines or patient-derived cells.

Reviewer #1 (Public Review):

The authors investigate the roles of ACOT12/8 in the production of acetate by the liver. They observe that acetate concentration parallels ketone concentrations during fasting and T1DM. They show that acetate is produced from fatty acids in hepatocytes, but though described as a novel "ketone body", this acetate is not a product of ketogenesis or acetoacetate. They also provide serum acetate data from human subjects who were classified as either "healthy" or "diabetic,". These subjects are noted as T2DM patients, but there is no other characterization or description, making it difficult to ascertain the context in which they were studied or their relevance to the mouse studies. Although the function of ACOT12/8 is reported in the literature, they are not widely studied, and there also remains surprising uncertainties regarding the mechanism of acetate production by the liver. In this regard, the manuscript provides some important insight. The authors use ShACOT12/8 and ACOT12/8 knockout mice to demonstrate that these acetyl-CoA hydrolases are largely necessary for acetate production. Using a 3H-palmitate assay, the authors then find that loss of these ACOTs inhibit fatty acid oxidation and propose that the mechanism involves scavenging CoA, analogous to the canonical role of ketogenesis. The idea is plausible but not proven. A related finding is that loss of these ACOTs inhibit ketogenesis, which the authors attribute to the loss of function of HMGC2S, partially through acetylation. These mechanisms suffer some limitations based on the cytosolic and mitochondrial compartmentation of the two processes, but the observations appear sound. Interestingly, the loss of the ACOTs have a more profound effect on lowering ketones than acetate, which may have parallel effects but they are not investigated. Finally, the authors try to demonstrate that hepatic ACOT-mediated acetate production is necessary for normal motor function in STZ treated mice, ostensibly as compensation for impaired glucose utilization by the CNS. Injections of 13C acetate and 13C enrichment in downstream metabolites of brain are used to support the importance of acetate metabolism, but the experiment was not performed in loss of function models. In addition, the resulting 13C enrichment data is reported generically as "relative intensity" without further elaboration on how this data was generated and should not be taken at face value by the reader. Conceptually, one may also be skeptical of the rather dramatic loss of motor function in the context of a relatively minor circulating nutrient. Nevertheless, this finding may be important if more supporting evidence with proper controls for ketone concentrations can be provided. Overall, there are important data in the manuscript, but the reader may find it difficult to navigate the 20+ figure panels. The most important findings are that ACOT12/8 are critical for hepatic acetate production in mice, which will be helpful for the field, but the ramifications require more rigorous investigation.

Reviewer #2 (Public Review):

Catabolic conditions lead to increased formation of ketone bodies in the liver, which under these conditions play an important role in supplying energy to metabolically active organs. In this manuscript, the authors explore the concept of whether and to what extent hepatic formation of acetate might contribute to energy supply under metabolic stress conditions. The authors show that patients with diabetes have increased acetate levels, which is explained as a consequence of the increased fatty acid flux from adipose tissue to the liver. This is confirmed in a preclinical model for type 1 diabetes, where acetate concentrations are in a similar range to ketone bodies. Acetate concentrations also increase under physiological conditions of fasting. Using stable isotopes, the authors show that palmitate is used as the primary source for acetate production in primary hepatocytes. Using cell culture studies and adenoviral-mediated knockdown in mice, it can be shown that the conversion of acetyl-CoA to acetate is catalyzed in peroxisomes by acyl-CoA thioesterase8 (ACOT8) and after transport of citrate from mitochondria and subsequent conversion to acetyl-CoA in the cytosol by ACOT12. Remarkably, ACOT8/12 not only regulates the formation of acetate but plays a crucial role in the maintenance of cellular CoA concentration. Accordingly, depletion of ACOT8/12 activity leads to a reduction of other CoA derivatives such as HMG-CoA, which resulted in the inhibition of ketone body synthesis. In diabetic mice, ACOT 8 or ACOT12 knockdown appears to lead to some limitations in strength and behavior.

In summary, the authors clearly demonstrate that hepatic release-mediated by ACOT8 and ACOT12-determines the plasma concentration of acetate. This is a very remarkable observation since most studies assume that short-chain fatty acids in plasma are primarily generated by fermentation of dietary fiber by intestinal bacteria. The authors demonstrate in very well performed studies the metabolic changes that result from impaired thiolysis. On the other hand, the ACOT12 phenotype has been demonstrated in a recently published study (PMID: 34285335). In this study, ACOT12 deficiency caused NAFLD, thus it would be worth determining whether deficiency of ACOT12 and/or ACOT8 promotes de novo lipogenesis under the conditions of the present study. As a further limitation, it should be noted that the relevance of acetate production for the energy supply of peripheral organs including the central nervous system could not be clearly demonstrated. For instance, impaired ketone body production due to impaired CoA availability could affect the metabolic activity of various organs. Moreover, the human cohort is not very well described, e.g. it is unclear whether the patients have type 1 or type 2 diabetes.

Reviewer #3 (Public Review):

Wang et al. investigated the role of acetate production, a byproduct of fatty acid oxidation, in the context of metabolic stressors, including diabetes mellitus and prolonged fasting. Mechanistically, they show the importance of the liver enzymes ACOT8 (peroxisome) and ACOT12 (cytoplasm) in converting FFA-derived acetyl-CoA into acetate and CoA. The regeneration of CoA allows for subsequent fatty acid oxidation. Inhibiting the generation of acetate has negative motor consequences in streptozocin-treated mice, which are mitigated with acetate injection.

This paper's strengths include using multiple mouse models, metabolic stressors (db/db-/-, streptozocin, and prolonged starvation), numerous cell lines, precise knockout and rescue experiments, and complimentary use of mass spectrometry and nuclear magnetic resonance analytical platforms. The presented data support the conclusions of this paper and highlight the role of acetate in energy stress conditions.

In clinical medicine, common ketones that are measured are acetoacetate, beta-hydroxybutyrate, and acetone which can help determine the severity of illness. However, the data presented here suggest the potential importance of measuring acetate as another biomarker when patients present with ketoacidosis in uncontrolled diabetes or starvation. This requires further investigation.

Reviewer #1 (Public Review):

Summary:<br /> This is a follow-up study to the authors' previous report about the roles of an alpha-arrestin called protein thioredoxin interacting protein (Txnip) in cone photoreceptors and in the retinal pigment epithelium. The findings are important because they provide new information about the mechanism of glucose and lactate transport to cone photoreceptors and because they may become the basis for therapies for retinal degenerative diseases.

Strengths:<br /> Overall, the study is carefully done and, although the analysis is fairly comprehensive with many different versions of the protein analyzed, it is clearly enough described to follow. Figure 4 greatly facilitated my ability to follow, understand and interpret the study.

Weaknesses:<br /> I have just one concern that I would like the authors to address. It is about the text that begins at line 133: "We assayed their ability to clear GLUT1 from the RPE surface (Figure 2A)". Please provide more details about this. From the figure it appears that n = 1 for this experiment, but given how careful the authors are with these types of studies that seems unlikely. How did the authors quantify the ability to clear GLUT1 from the surface? Was it cleared from both the apical and basal surface? (It is hard to resolve the apical and basal surfaces in the images provided). The experiments shown in Fig. 1H and Fig. 1I of PMID 31365873 shows how GLUT1 disappears only from the apical surface (under the conditions of that experiment and through the mechanism described in their text). It would be helpful for the authors to discuss their current results in the context of that experiment.

Reviewer #2 (Public Review):

The hard work of the authors is much appreciated. With overexpression of a-arrestin Txnip in RPE, cones and the combined respectively, the authors show a potential gene agnostic treatment that can be applied to retinitis pigmentosa. Furthermore, since Txnip is related to multiple intracellular signaling pathway, this study is of value for research in the mechanism of secondary cone dystrophy as well.

There are a few areas in which the article may be improved through further analysis and application of the data, as well as some adjustments that should be made in to clarify specific points in the article.

Reviewer #3 (Public Review):

Summary:

Xue et al. extended their groundbreaking discovery demonstrating the protective effect of Txnip on cone photoreceptor survival. This was achieved by investigating the protection of cone degeneration through the overexpression of five distinct mutated variants of Txnip within the retinal pigment epithelium (RPE). Moreover, the study explored the roles of two proteins, HSP90AB1 and Arrdc4, which share similarities or associations with Txnip. They found the protection of Txnip in RPE cells and its mechanism is different from its protection in cone cells. These discoveries have significant implications for advancing our understanding of the mechanisms underlying Txnip's protection on cone cells.

Strengths:<br /> 1. Identify the roles of different Txnip mutations in RPE and their effects on the expression of glucose transporter<br /> 2. Dissect the mechanism of Txnip in RPE vs Cone photoreceptors in retinal degeneration models.<br /> 3. Explore the functions of ARrdc4, a protein similar to Txnip and HSP90AB1 in cone degeneration.

Weaknesses:<br /> 1. Arrdc4 has deleterious effect on cone survival but no discussion on its mechanism.<br /> 2. Inhibition of HSP90 is known to cause retinal generation. It is unclear why inhibition enhances the protection of Txnip.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

Host blood meal source, temperature, and photoperiod were all examined together.

Weaknesses:

The study was conducted in laboratory conditions with a local population of Cx. quinquefasciatus from Argentina. I'm not sure if there is any evidence for a seasonal shift in the host use pattern in Cx. quinquefasciatus populations from the southern latitudes.

Reviewer #2 (Public Review):

Summary:

Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness in birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used a generalized linear mixed model to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity and fertility and a null model analysis via data randomization for hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite of that hypothesized. While this finding is interesting and worth reporting, there are significant issues with the experimental design and the conclusions that are drawn from the results, which are described below. These issues should be addressed to make the findings trustworthy.

Strengths:

1. Using a combination of laboratory feedings and incubators to simulate seasonal environmental conditions is a good, controlled way to assess the potentially interactive impact of host species and seasonality on the fitness of Culex quinquefasciatus in the lab.<br /> 2. The driving hypothesis is an interesting and creative way to think about a potential driver of host switching observed in the field.

Weaknesses:

1. There is no replication built into this study. Egg lay is a highly variable trait, even within treatments, so it is important to see replication of the effects of treatment across multiple discrete replicates. It is standard practice to replicate mosquito fitness experiments for this reason. Furthermore, the sample size was particularly small for some groups (e.g. 15 egg rafts for the second gonotrophic cycle of mice in the autumn, which was the only group for which a decrease in fecundity and fertility was detected between 1st and 2nd gonotrophic cycles). Replicates also allow investigators to change around other variables that might impact the results for unknown reasons; for example, the incubators used for fall/summer conditions can be swapped, ensuring that the observed effects are not artifacts of other differences between treatments. While most groups had robust sample sizes, I do not trust the replicability of the results without experimental replication within the study.<br /> 2. Considering the hypothesis is driven by the host switching observed in the field, this phenomenon is discussed very little. I do not believe Cx. quinquefasciatus host switching has been observed in Argentina, only in the northern hemisphere, so it is possible that the species could have an entirely different ecology in Argentina. It would have been helpful to conduct a blood meal analysis prior to this experiment to determine whether using an Argentinian population was appropriate to assess this question. If the Argentinian populations don't experience host switching, then an Argentinian colony would not be the appropriate colony to use to assess this question. Given that this experiment has already been conducted with this population, this possibility should at least be acknowledged in the discussion. Or if a study showing host switching in Argentina has been conducted, it would be helpful to highlight this in the introduction and discussion.<br /> 3. The impacts of certain experimental design decisions are not acknowledged in the manuscript and warrant discussion. For example, the larvae were reared under the same conditions to ensure adults of similar sizes and development timing, but this also prevents mechanisms of action that could occur as a result of seasonality experienced by mothers, eggs, and larvae.<br /> 4. There are aspects of the data analysis that are not fully explained and should be further clarified. For example, there is no explanation of how the levels of categorical variables were compared.<br /> 5. The results show the opposite trend as was predicted by the authors based on observed feeding switches from birds to mammals in the autumn. However, they only state this once at the end of the discussion and never address why they might have observed the opposite trend as was hypothesized.<br /> 6. Generally speaking, the discussion has information that isn't directly related to the results and/or is too detailed in certain parts. Meanwhile, it doesn't dig into the meaning of the results or the ways in which the experimental design could have influenced results.<br /> 7. Beyond the issue of lack of replication limiting trust in the conclusions in general, there is one conclusion reached at the end of the discussion that would not be supported, even if additional replicates are conducted. The results do not show that physiological changes in mosquitoes trigger the selection of new hosts. Host selection is never measured, so this claim cannot be made. The results don't even suggest that fitness might trigger selection because the results show that physiological changes are in the opposite direction as what would be hypothesized to produce observed host switches. Similarly, the last sentence of the abstract is not supported by the results.<br /> 8. Throughout the manuscript, there are grammatical errors that make it difficult to understand certain sentences, especially for the results.

This study is driven by an interesting question and has the potential to be a valuable contribution to the literature.

Reviewer #1 (Public Review):

Summary:<br /> The goal of this study was to develop and validate novel molecules to selectively activate a cell signaling pathway, the Wnt pathway in this case, in target cells expressing a specific receptor. This was achieved through a two-component system that the authors call BRAID, where each component simultaneously binds the target cell-specific marker BKlotho and a Wnt co-receptor. These components, called SWIFT molecules, bring together the Wnt co-receptors LRP and FZD, activating the pathway specifically in cells that express BKlotho. Results presented in the study demonstrate the desired activity of SWIFT molecules; the binding assays support the simultaneous association of SWIFT with BKlotho and a Wnt co-receptor, and the Wnt reporter and qPCR assays support pathway activation in cell lines and primary cells in a BKlotho-dependent manner. In the future, the BRAID approach could be applied to activate Wnt signaling or another pathway initiated by a co-receptor complex in a cell type-specific manner, and/or in a FZD subtype-specific manner to activate distinct branches of Wnt signaling.

Strengths:<br /> • This study successfully demonstrates a novel way to activate Wnt signaling in target cells expressing a specific marker. Given the role of the Wnt signaling pathway in key processes such as cell proliferation and tissue renewal and the value of modulating cell signaling in a cell type-specific manner, the cell targeting system developed here holds great therapeutic and research potential. It will be curious to see whether the BRAID design can be applied to other cell surface markers for Wnt activation, or for activation of other signaling pathways that require co-receptor association.

• Octet assay results show simultaneous binding of SWIFT molecules to both the Wnt co-receptor FZD/LRP and BKlotho, while negative control molecules without the FZD/LRP or BKlotho-binding module show neither receptor binding nor Wnt pathway activation. These results indicate that SWIFT molecules function through the intended mechanism.

Weaknesses:<br /> • Here, the activity of SWIFT molecules was assessed in single cell types with or without BKlotho expression. Ultimately, the ability of the SWIFT molecules to activate Wnt signaling in a cell type-specific manner should be tested in the context of many different cellular identities that express BKlotho to different extents. It would be good to demonstrate that Wnt activation by SWIFT correlates with BKlotho expression level in multiple cell types - such data would strengthen the claim of cell-type specificity.

• The study does not address whether the targeted cells express FGFR1c/2c/3c and whether the FGF21 full-length moiety or the 39F7 IgG moiety of SWIFT molecules could unintentionally activate FGF signaling in these cells.

Reviewer #2 (Public Review):

Summary:<br /> The study introduces BRAID, a novel approach for targeting drugs to specific cell types, addressing the challenges of pleiotropic drug actions. Unlike existing methods, this one involves breaking a protein drug molecule into inactive parts that are then put back together using a bridging receptor on the target cell. The individual components of this assembly are not required to be together, thereby affording it a degree of flexibility. The authors applied this idea to the WNT/-catenin signaling pathway by splitting a WNT mimic into two parts with FZD and LRP binding domains and bridging receptors. This combined method, which is called SWIFT, showed that WNT signaling was turned on in target cells, showing cell-specific targeting. The technique shows promise for the development of therapeutics, as it provides a way to more precisely target signaling pathways.

The authors have effectively elucidated their strategy through visually appealing diagrams, providing clear and thorough visual aids that facilitate comprehension of the concept. In addition, the authors have provided convincing evidence that the C-terminal region of FGF21 is essential for the binding process. Their meticulous and thorough presentation of experimental results emphasizes the significance of this specific binding domain and validates their findings.

Strengths:<br /> BRAID, a novel cell targeting method, divides an active drug molecule into inactive components formed by a bridging receptor. This novel approach to cell-specific drug action may reduce systemic toxicity.

The SWIFT approach successfully targets cells in the WNT/β-catenin signaling pathway. The approach activates WNT signaling only in target cells (hepatocytes), proving its specificity.

The study indicates that the BRAID approach can target various signaling systems beyond WNT/β-catenin, indicating its versatility. Therapeutic development may benefit from this adaptability.

Weaknesses:<br /> The study shows the SWIFT approach works in vitro using cell lines, primary human hepatocytes, and human intestinal organoids, but it lacks an in vivo animal model or clinical validation. The applicability of this approach to therapy is still unknown.

The success of SWIFT depends on the presence and expression of the bridging receptor (βKlotho) on target cells. The approach may fail if the target receptor is not expressed or available.

Reviewer #1 (Public Review):

This work continues a series of recent publications from the Grigorieff lab (https://doi.org/10.7554/eLife.25648, https://doi.org/10.7554/eLife.68946, https://doi.org/10.7554/eLife.79272, https://doi.org/10.1073/pnas.2301852120) showcasing the development of high-resolution 2D template matching (2DTM) for detection and reconstruction of macromolecules in cryo-electron microscopy (cryo-EM) images of crowded cellular environments. It is well known in the field of cryo-EM that searching noisy images with a template can result in retrieval of the template itself when averaging the candidate particles detected, an effect known as "Einstein-from-noise" (https://doi.org/10.1073/pnas.1314449110). Briefly, this occurs because it is statistically likely to find a match to an arbitrary motif over a large noisy dataset just by chance. The effect can be mitigated for example by limiting the resolution of the template, but this prevents the accurate detection of macromolecules in a crowded environment, as their "fingerprint" lies in the high-resolution range (https://doi.org/10.7554/eLife.25648). Here, the authors show through several experiments on in vitro and in situ data that features as small as drug compounds and water molecules can be reliably retrieved by 2DTM if they are searched by a template (the "bait") that contains expected neighboring features but not the targets themselves.

The ideas are generally clearly presented with appropriate references to related work, and claims are well supported by the data. In particular, the experiments for verifying the density of the ribosomal protein L7A as well as the systematic removal of residuals from the template model to assess bias are particularly clever.

One key point that could use further clarification is how to interpret densities in the reconstruction that do overlap with the template. If the omitted regions can be reliably reconstructed, and the density is smooth throughout, it implies the detected particles are not only (mostly) true positives but also their poses must be essentially correct. Therefore, why cannot the entire reconstruction be trusted, including portions overlapping with the template? In the "Future applications" section, the authors state that in order to obtain a reconstruction that is entirely devoid of template bias, it would be necessary to successively omit parts of the template structure through its entirety. I wonder if that is really necessary and if the presented approach of omitting template portions could be better framed as a "gold-standard" validation procedure.

In other words, given the compelling evidence provided by the reconstructions in the omitted areas, I find it hard to imagine how the procedure would be "hallucinating" features in the rest of the structure, as the entire reconstruction depends on the same pose and defocus parameters. A possible experiment to test this hypothesis would be to go the opposite way, deliberately adding an unrealistic feature to the bait and checking whether it comes up in the reconstruction, while at the same time checking how it behaves in omitted parts.

When assessing their approach to in situ data (the yeast ribosome), it is intriguing to see that the resolution downgraded from 3.1 to 8 Å when refinement of the particle poses against the current reconstruction was attempted. The authors do provide some possible explanations, such as the reduced signal of the reconstruction at high resolution and the crowded background, but it leaves one to wonder if this means that a 3.1 Å reconstruction could never be obtained from these data by conventional single-particle analysis procedures.

Furthermore, in the section "Quantifying template bias", the authors make the intriguing statement that there can still be some overfitting of noise even in true positives. I understand this overfitting would occur in the form of errors in the pose and defocus estimation, but a clarification would be helpful.

In the Discussion, the claim that "it is not necessary to use tomography to generate high-resolution reconstructions of macromolecular complexes in cells" is a misconception, at least in part. As demonstrated in works by the same group and others (https://doi.org/10.1016/j.xinn.2021.100166, https://doi.org/10.1038/s41467-023-36175-y, https://doi.org/10.1038/s41586-023-05831-0), 2D imaging of native cellular environments does offer a faster and better way to obtain high-resolution reconstructions compared to tomography. However, tomography provides the entire 3D context of the macromolecules, such as their localization to membranes and the cellular architecture, which can be readily visualized in a tomogram even at low resolution, so methods for structure determination from tilt series data such as subtomogram averaging remain of paramount importance. Most likely, a combination of 2D and 3D imaging approaches will be necessary to retrieve both the highest structural resolution and their cellular context to address biological questions.

The "Materials and Methods" section lacks a description of transmission electron microscopy data collection.

Finally, the preprint version of this work posted on bioRxiv (https://doi.org/10.1101/2023.07.03.547552) contains the following competing interests statement, which is missing from the submitted version:<br /> "The authors are listed as inventors on a closely related patent application named "Methods and Systems for Imaging Interactions Between Particles and Fragments", filed on behalf of the University of Massachusetts."

Reviewer #2 (Public Review):

This paper by Lucas et al follows on from earlier work by the same group. They use high-resolution 2D template matching (2DTM) to find particles of a given target structure in 2D cryo-EM images, either of in vitro single-particle samples or of more complicated samples, such as FIB-milled cells (which would otherwise perhaps be used for 3D electron tomography). One major concern for high-resolution template matching has been the amount of model bias that gets introduced into a reconstruction that is calculated straight from the orientations and positions identified by the projection matching algorithm. This paper assesses the amount of model bias that gets introduced in high-resolution features of such maps.

For a high-signal-to-noise in vitro single-particle cryo-EM data set, the authors show that their approach does not yield much model bias. This is probably not very surprising, as their method is basically a low false-positive particle picker, which works very well on such data. Still, I guess that is the whole point of it, and it is good to see that they can reconstruct density for a small-molecule compound that was not present in the original template.

For FIB-milled lamella of yeast cells with stalled ribosomes, the SNR is much lower and the dangers of model bias will be higher. This is also evidenced by the observation that further refinement of initial 2DTM-identified orientations and positions worsens the map. This is obviously a more relevant SNR regime to assess their method. Still, they show convincing density for the GHX compound that was not present in the template but was there in the reconstruction from the identified particles.

Quantification of the amount of model bias is then performed using omit maps, where every 20th residue is removed from the template and corresponding reconstructions are compared (for those residues) with the full-template reconstructions. As expected, model bias increases with lower thresholds for the picking. Some model bias (Omega=8%) remains even for very high thresholds. The authors state this may be due to overfitting of noise when template-matching true particles, instead of introducing false positives. Probably, that still represents some sort of problem. Especially because the authors then go on to show that their expectation of the number of false positives does not always match the correct number of false positives, probably due to inaccuracies in the noise model for more complicated images. This may warrant further in-depth discussion in a revised manuscript.

Overall, I think this paper is well written and it has made me think differently (again) about the 2DTM technique and its usefulness in various applications, as outlined in the Discussion. Therefore, it will be a constructive contribution to the field.

Reviewer #3 (Public Review):

The authors evaluate the effect of high-resolution 2D template matching on template bias in reconstructions, and provide a quantitative metric for overfitting. It is an interesting manuscript that made me reevaluate and correct some mistakes in my understanding of overfitting and template bias, and I'm sure it will be of great use to others in the field. However, its main point is to promote high-resolution 2D template matching (2DTM) as a more universal analysis method for in vitro and, more importantly, in situ data. While the experiments performed to that end are sound and well-executed in principle, I fail to make that specific conclusion from their results.

The authors correctly point out that overfitting is largely enabled by the presence of false-positives in the data set. They go on to perform their in situ experiments with ribosomes, which provide an extremely favorable amount of signal that is unrealistic for the vast majority of the proteome. This seems cherry-picked to keep the number of false-positives and false-negatives low. The relationship between overfitting/false-positive rate and the picking threshold will remain the same for smaller proteins (which is a very useful piece of knowledge from this study). However, the false-negative rate will increase a lot compared to ribosomes if the same high picking threshold is maintained. This will limit the applicability of 2DTM, especially for less-abundant proteins.

I would like to see an ablation study: Take significantly smaller segments of the ribosome (for which the authors already have particle positions from full-template matching, which are reasonably close to the ground-truth), e.g. 50 kDa, 100 kDa, 200 kDa etc., and calculate the false-negative rate for the same picking threshold. If the resulting number of particles does plummet, it would be very helpful to discuss how that affects the utility of 2DTM for non-ribosomes in situ.

Another point of concern is the dramatic resolution decrease to 8 A after multiple iterations of refinement against experimental reconstructions described in line 159. Was this a local search from the poses provided by 2DTM, or something more global? While this is not a manifestation of overfitting as the authors have conclusively shown, I think it adds an important point to the ongoing "But do we really need tomograms, or can we just 2D everything?" debate in the field, which is also central to the 2D part of 2DTM. Reaching 8 A with 12k ribosome particles would be considered a rather poor subtomogram averaging result these days. Being in the "we need tilt series to be less affected by non-Gaussian noise" camp myself, I wonder if this indicates 2D images are inherently worse for in situ samples. If they are, the same limitations would extend to template matching. In that case, shouldn't the authors advocate for 3DTM instead of 2DTM? It may not be needed for ribosomes, but could give smaller proteins the necessary edge.

Right now, this study is also an invitation to practitioners who do not understand the picking threshold used here and cannot relate it to other template-matching programs to do a lot of questionable template matching and claim that the results are true because templates are "unoverfittable". I think such undesirable consequences should be discussed prominently.

Reviewer #1 (Public Review):

Koesters and colleagues investigated the role of the presynaptic small GTPase Rab3A in homeostatic scaling of miniature synaptic transmission in primary mouse cortical cultures using electrophysiology and immunohistochemistry. The major finding is that TTX incubation for 48 hours does not induce an increase in the amplitude of excitatory synaptic miniature events in neuronal cultures derived from Rab3A KO and Rab3A Earlybird mutant mice. NASPM application had comparable effects on mEPSC amplitude in control and after TTX, implying that Ca2+-permeable glutamate receptors are unlikely modulated during synaptic scaling. Immunohistochemical analysis revealed an increase in GluA2 puncta size and intensity in wild type, but not Rab3A KO cultures. Finally, they provide evidence that loss of Rab3A in neurons, but not astrocytes, blocks homeostatic scaling. Based on these data, the authors propose a model in which presynaptic Rab3A is required for homeostatic scaling of synaptic transmission through GluA2-dependent and independent mechanisms.

While the title of the manuscript is mostly supported by data of solid quality, many conclusions, as well as the final model, cannot be derived from the results presented. Importantly, the results do not indicate that Rab3A modulates quantal size on both sides of the synapse. Moreover, several analysis approaches seem inappropriate.

The following points should be addressed:

1. The model shown in Figure 10 is not supported by the data. The authors neither provide evidence for two different functional states of Rab3A being involved in mEPSC amplitude modulation, nor for a change in glutamate content of vesicles. Furthermore, the data do not fully support the conclusion of a presynaptic role for Rab3A in homeostatic scaling.<br /> 2. The analysis of mEPSC data using quantile sampling followed by ratio calculation is not meaningful under the tested experimental conditions because of the following reasons: (i) The analysis implicitly assumes that all events have been detected. The prominent mEPSC frequency increase after TTX suggests that this is not the case, i.e., many (small) mEPSCs are likely missed under control conditions. (ii) The analysis is used to conclude how events of a certain size are altered by TTX treatment. However, this analysis compares the smallest mEPSCs of the TTX condition with the smallest control mEPSCs, but this is not a pre-post experimental design. Variation between cells and between coverslips will markedly affect the results and lead to misleading interpretations. (iii) The ratio (TTX/control) vs. control plots seem to suffer from a division by small value artifact (see Figure 6F). Correspondingly, ratio-analysis differs considerably for different control conditions (Fig. 1Giii, Fig. 2Giii, Fig. 6C, Fig. 9A).<br /> 3. As noted by the authors in a previous publication (Hanes et al. 2020), statistical analysis of CDFs suffers from n-inflation. In addition, the quantile sampling method chosen violates an important assumption of the K-S test. Indeed, p-values for these comparisons are typically several orders of magnitude smaller. Given that the statistical N most likely corresponds to the number of cultures (see, e.g., https://doi.org/10.1371/journal.pbio.2005282), CDF comparisons are not informative and should thus not be used to draw conclusions from the data. The plots can be informative, though.<br /> 4. How does recoding noise and the mEPSC amplitude threshold affect "divergent scaling"?<br /> 5. What is the justification for the line fits of the ratio data/how was the fit range chosen?<br /> 6. TTX application induces a significant increase in mEPSC amplitude in Rab3A-/- mice in two out of three data sets (Figs. 1 and 9). Hence, the major conclusion that Rab3A is required for homeostatic scaling is only partially supported by the data.<br /> 7. Line 289: A comparison of p-values between conditions does not allow any meaningful conclusions.<br /> 8. There is a significant increase in baseline mEPSC amplitude in Rab3AEbd/Ebd (15 pA) vs. Rab3Aebd/+ (11 pA) cultures, but not in Rab3A-/- (13.6 pA) vs. Rab3A+/- (13.9 pA). Although the nature of scaling was different between Rab3AEbd/Ebd vs. Rab3AEbd/+, and Rab3AEbd/Ebd with vs. without TTX, the question arises whether the increase in mEPSC amplitude in Rab3AEbd/Ebd is Rab3A dependent. Could a Rab3A independent mechanism occlude scaling?<br /> 9. Figure 4: NASPM appears to have a stronger effect on mEPSC frequency in the TTX condition vs. control (-40% vs. -15%). A larger sample size might be necessary to draw definitive conclusions on the contribution of Ca2+-permeable AMPARs.<br /> 10. The authors discuss previous papers showing changes in VGLUT1 intensity. Was VGLUT intensity altered in the stainings presented in the manuscript?<br /> 11. The change in GluA2 area or fluorescence intensity upon TTX treatment in controls is modest. How does the GluA2 integral change?<br /> 12. The quantitative comparison between physiology and microscopy data is problematic. The authors report a mismatch in ratio values between the smallest mEPSC amplitudes and smallest GluA2 receptor cluster sizes (l. 464; Figure 8). Is this comparison affected by the fluorescence intensity threshold? What was the rationale for a threshold of 400 a.u. or 450 a.u.? How does this threshold compare to the mEPSC threshold of 3 pA? The conclusion that an increase in AMPAR levels is not fully responsible for the observed mEPSC increase is mainly based on the rank-order analysis of GluA2 intensity, yielding a slope of ~0.9. There are several points to consider here: (i) GluA2 fluorescence intensity did increase on average, as did GluA2 cluster size. (ii) The increase in GluA2 cluster size is very similar to the increase in mEPSC amplitude (each approx. 18-20%). (iii) Are there any reports that fluorescence intensity values are linearly reporting mEPSC amplitudes (in this system)? Antibody labelling efficiency, and false negatives of mEPSC recordings may influence the results. The latter was already noted by the authors. (iv) It is not entirely clear if their imaging experiments will sample from all synapses. Other AMPAR subtypes than GluA2 could contribute, as could kainate or NMDA receptors.<br /> Furthermore, the statement "complete lack of correspondence of TTX/CON ratios" is not supported by the data presented (l. 515ff). First, under the assumption that no scaling occurs in Rab3A-/- , the TTX/CON ratios show a 20-30% change, which indicates the variation of this readout. Second, the two examples shown in Figure 8 for Rab3A+/+ are actually quite similar (culture #1 and #2), particularly when ignoring the leftmost section of the data, which is heavily affected by the raw values approaching zero.<br /> 13. Figure 7A: TTX CDF was shifted to smaller mEPSC amplitude values in Rab3A-/- cultures. How can this be explained?

Reviewer #2 (Public Review):

In this study, Koesters et al. investigated whether Rab3A, a small GTPase that regulates synaptic vesicle fusion pore opening, is required for excitatory synaptic scaling in response to TTX-induced activity suppression in dissociated mouse cortical neuronal culture. They first show that, while pyramidal neurons from wild-type (WT) littermates show normal synaptic scaling in response to 48h of TTX treatment (~30% increase in the mean mEPSC amplitude), those from two different mouse lines with either deletion (Rab3A-/-) or loss-of-function mutation of Rab3A (Rab3AEbd/Ebd) fail to engage this homeostatic compensation. They perform cumulative distribution analysis to show that the mEPSC population has gone through divergent scaling in WT neurons. Similarly, this phenomenon is absent in neurons from the two Rab3A mouse lines. They further demonstrate that GluA2-containing AMPARs likely account for the increase in mEPSC amplitudes by comparing measurements before and after washing in blockers specific for GluA2-lacking AMPARs. Subsequently, they perform electrophysiology and immunohistochemistry side by side for WT neurons from the same culture following TTX treatment, and find that both mEPSC amplitudes and GluA2 cluster sizes have shifted towards higher values, while GluA2 cluster intensity remains unchanged. Importantly, all these homeostatic compensations are absent in Rab3A-/- neurons. Finally, they mix neurons and astrocyte feeders either from WT or Rab3A-/- mice, which reveals that neuronal but not astrocytic Rab3A knockout leads to impaired scaling up of mEPSCs. They conclude that Rab3A is required for homeostatic scaling up of mEPSC amplitude in cortical neurons, most likely from the presynaptic side.

Although the authors have raised an interesting question, their conclusion is not well supported by the data presented. I list my technical and conceptual concerns below.

Technical concerns:

1. The culture condition is questionable. The authors saw no NMDAR current present during spontaneous recordings, which is worrisome since NMDARs should be active in cultures with normal network activity (Watt et al., 2000; Sutton et al., 2006). It is important to ensure there is enough spiking activity before doing any activity manipulation. Similarly, it is also unknown whether spiking activity is normal in Rab3A KO/Ebd neurons.

2. Selection of mEPSC events is not conducted in an unbiased manner. Manually selecting events is insufficient for cumulative distribution analysis, where small biases could skew the entire distribution. Since the authors claim their ratio plot is a better method to detect the uniformity of scaling than the well-established rank-order plot, it is important to use an unbiased population to substantiate this claim.

3. Immunohistochemistry data analysis is problematic. The authors only labeled dendrites without doing cell-fills to look at morphology, so it is questionable how they differentiate branches from pyramidal neurons and interneurons. Since glutamatergic synapses on these two types of neuron scale in the opposite directions, it is crucial to show that only pyramidal neurons are included for analysis.

Conceptual concerns:

The only novel finding here is the implicated role for Rab3A in synaptic scaling, but insights into mechanisms behind this observation are lacking. The author claims that Rab3A likely regulates scaling from the presynaptic side, yet there is no direct evidence from data presented. In its current form, this study's contribution to the field is very limited.

1. Their major argument for this is that homeostatic effects on mEPSC amplitudes and GluA2 cluster sizes do not match. This is inconsistent with reports from multiple labs showing that upscaling of mEPSC amplitude and GluA2 accumulation occur side by side during scaling (Ibata et al., 2008; Pozo et al., 2012; Tan et al., 2015; Silva et al., 2019). Further, because the acquisition and quantification methods for mEPSC recordings and immunohistochemistry imaging are entirely different (each with its own limitations in signal detection), it is not convincing that the lack of proportional changes must signify a presynaptic component.

2. The authors also speculate in the discussion that presynaptic Rab3A could be interacting with retrograde BDNF signaling to regulate postsynaptic AMPARs. Without data showing Rab3A-dependent presynaptic changes after TTX treatment, this argument is not compelling. In this retrograde pathway, BDNF is synthesized in and released from dendrites (Jakawich et al., 2010; Thapliyal et al., 2022), and it is entirely possible for postsynaptic Rab3A to interfere with this process cell-autonomously.

3. The authors propose that a change in AMPAR subunit composition from GluA2-containing ones to GluA1 homomers may account for the distinct changes in mEPSC amplitudes and GluA2 clusters. However, their data from the Naspm wash-in experiments clearly show that GluA1 homomer contributions have not changed before and after TTX treatment.

Ibata K, Sun Q, Turrigiano GG (2008) Rapid synaptic scaling induced by changes in postsynaptic firing. Neuron 57:819-826.

Jakawich SK, Nasser HB, Strong MJ, McCartney AJ, Perez AS, Rakesh N, Carruthers CJL, Sutton MA (2010) Local Presynaptic Activity Gates Homeostatic Changes in Presynaptic Function Driven by Dendritic BDNF Synthesis. Neuron 68:1143-1158.

Pozo K, Cingolani LA, Bassani S, Laurent F, Passafaro M, Goda Y (2012) β3 integrin interacts directly with GluA2 AMPA receptor subunit and regulates AMPA receptor expression in hippocampal neurons. Proceedings of the National Academy of Sciences 109:1323-1328.

Silva MM, Rodrigues B, Fernandes J, Santos SD, Carreto L, Santos MAS, Pinheiro P, Carvalho AL (2019) MicroRNA-186-5p controls GluA2 surface expression and synaptic scaling in hippocampal neurons. Proceedings of the National Academy of Sciences 116:5727-5736.

Sutton MA, Ito HT, Cressy P, Kempf C, Woo JC, Schuman EM (2006) Miniature Neurotransmission Stabilizes Synaptic Function via Tonic Suppression of Local Dendritic Protein Synthesis. Cell 125:785-799.

Tan HL, Queenan BN, Huganir RL (2015) GRIP1 is required for homeostatic regulation of AMPAR trafficking. Proceedings of the National Academy of Sciences 112:10026-10031.

Thapliyal S, Arendt KL, Lau AG, Chen L (2022) Retinoic acid-gated BDNF synthesis in neuronal dendrites drives presynaptic homeostatic plasticity. eLife 11:e79863.

Watt AJ, Rossum MCW van, MacLeod KM, Nelson SB, Turrigiano GG (2000) Activity Coregulates Quantal AMPA and NMDA Currents at Neocortical Synapses. Neuron 26:659-670.

Reviewer #3 (Public Review):

Summary: The authors clearly demonstrate the Rab3A plays a role in HSP at excitatory synapses, with substantially less plasticity occurring in the Rab3A KO neurons. There is also no apparent HSP in the Earlybird Rab3A mutation, although baseline synaptic strength seems already elevated. In this context, it is unclear if the plasticity is absent or just occluded by a ceiling effect due the synapses already being strengthened. The authors do appropriately discuss both options. There are also differences in genetic background between the Rab3A KO and Earlybird mutants that could also impact the results, which are also noted. The authors have solid data showing that Rab3A is unlikely to be active in astrocytes, Finally, they attempt to study the linkage between synaptic strength during HSP and AMPA receptor trafficking, and conclude that trafficking is largely not responsible for the changes in synaptic strength.

Strengths: This work adds another player into the mechanisms underlying an important form of synaptic plasticity. The plasticity is only reduced, suggesting Rab3A is only partially required and perhaps multiple mechanisms contribute. The authors speculate about some possible novel mechanisms.

Weaknesses: However, the rather strong conclusions on the dissociation of AMPAR trafficking and synaptic response are made from somewhat weaker data. The key issue is the GluA2 immunostaining in comparison with the mESPC recordings. Their imaging method involves only assessing puncta clearly associated with a MAP2 labeled dendrite. This is a small subset of synapses, judging from the sample micrographs (Fig 5). To my knowledge, this is a new and unvalidated approach that could represent a particular subset of synapses not representative of the synapses contributing to the mEPSC change (they are also sampling different neurons for the two measurements; an additional unknown detail is how far from the cell body were the analyzed dendrites for immunostaining). While the authors acknowledge that a sampling issue could explain the data, they still use this data to draw strong conclusions about the lack of AMPAR trafficking contribution to the mEPSC amplitude change. This apparent difference may be a methodological issue rather than a biological one, and at this point it is impossible to differentiate these. It will unfortunately be difficult to validate their approach. Perhaps if they were to drive NMDA-dependent LTD or chemLTP, and show alignment of the imaging and ephys, that would help. More helpful would be recordings and imaging from the same neurons but this is challenging. Sampling from identified synapses would of course be ideal, perhaps from 2P uncaging combined with SEP-labeled AMPARs, but this is more challenging still. But without data to validate the method, it seems unwarranted to make such strong conclusions such as that AMPAR trafficking does not underlie the increase in mEPSC amplitude, given the previous data supporting such a model.

Other questions arise from the NASPM experiments, used to justify looking at GluA2 (and not GluA1) in the immunostaining. First, there is a frequency effect that is quite unclear in origin. One would expect NASPM to merely block some fraction of the post-synaptic current, and not affect pre-synaptic release or block whole synapses. It is also unclear why the authors argue this proves that the NASPM was at an effective concentration (lines 399-400). Further, the amplitude data show a strong trend towards smaller amplitude. The p value for both control and TTX neurons was 0.08 - it is very difficult to argue that there is no effect. And the decrease is larger in the TTX neurons. Considering the strong claims for a pre-synaptic locus and the use of this data to justify only looking at GluA2 by immunostaining, these data do not offer much support of the conclusions. Between the sampling issues and perhaps looking at the wrong GluA subunit, it seems premature to argue that trafficking is not a contributor to the mEPSC amplitude change, especially given the substantial support for that hypothesis. Further, even if trafficking is not the major contributor, there could be shifts in conductance (perhaps due to regulation of auxiliary subunits) that does not necessitate a pre-synaptic locus. While the authors are free to hypothesize such a mechanism, it would be prudent to acknowledge other options and explanations.

The frequency data are missing from the paper, with the exception of the NASPM dataset. The mEPSC frequencies should be reported for all experiments, particularly given that Rab3A is generally viewed as a pre-synaptic protein regulating release. Also, in the NASPM experiments, the average frequency is much higher in the TTX treated cultures. Is this statistically above control values?

Unaddressed issues that would greatly increase the impact of the paper:<br /> 1) Is Rab3A acting pre-synaptically, post-synaptically or both? The authors provide good evidence that Rab3A is acting within neurons and not astrocytes. But where it is acting (pre or post) would aid substantially in understanding its role (and particularly the hypothesized and somewhat novel idea that the amount of glutamate released per vesicle is altered in HSP). They could use sparse knock-down of Rab3A, or simply mix cultures from KO and WT mice (with appropriate tags/labels). The general view in the field has been that HSP is regulated post-synaptically via regulation of AMPAR trafficking, and considerable evidence supports this view. The more support for their suggestion of a pre-synaptic site of control, the better.

2) Rab3A is also found at inhibitory synapses. It would be very informative to know if HSP at inhibitory synapses is similarly affected. This is particularly relevant as at inhibitory synapses, one expects a removal of GABARs and/or a decrease of GABA-packaging in vesicles (ie the opposite of whatever is happening at excitatory synapses). If both processes are regulated by Rab3A, this might suggest a role for this protein more upstream in the signaling; an effect only at excitatory synapses would argue for a more specific role just at these synapses.

Reviewer #1 (Public Review):

Summary:

This valuable study analyzes the contribution of fungal and bacterial microbiota species to the growth and development of Drosophila. The authors use bacterial and fungal species associated with Drosophila in the wild to analyze their respective contributions in promoting larval growth in a decaying banana, mimicking the natural niche of fruit flies. They found that some fungal species and some fungus/bacteria combinations effectively promote growth by supplementing key branched amino acids in the food substratum. Production of these amino acids by Drosophila itself is not sufficient, and only fungal species that secrete these amino acids into the medium can sustain Drosophila growth. Thus, the authors clarify how facultative symbionts contribute to host growth in a natural setting by changing the food substratum in a dynamic manner.

Strengths:

The natural setting developed by the authors to analyze the impact of the microbiota is clearly valuable, as is the focus on the role of fungal microbiota species. This complements studies of Drosophila microbiota that have previously focused on bacterial species and used a lab setting. While there has been an extensive focus on obligate endosymbionts or gut symbionts, this study analyzes how facultative symbionts shape the food substratum and influence host growth. A last strength of this study is that it analyzes the contribution of Drosophila microbiota over a dynamic timeframe, analyzing how microbial species change in decaying fruit over time.

Weaknesses:

1) The authors should better review what we know of fungal Drosophila microbiota species as well as the ecology of rotting fruit. Are the microbiota species described in this article specific to their location/setting? It would have been interesting to know if similar species can be retrieved in other locations using other decaying fruits. The term 'core' in the title suggests that these species are generally found associated with Drosophila but this is not demonstrated. The paper is written in a way that implies the microbiota members they have found are universal. What is the evidence for this? Have the fungal species described in this paper been found in other studies? Even if this is not the case, the paper is interesting, but there should be a discussion of how generalizable the findings are.

2) Can the authors clearly demonstrate that the microbiota species that develop in the banana trap are derived from flies? Are these species found in flies in the wild? Did the authors check that the flies belong to the D. melanogaster species and not to the sister group D. simulans?

3) Did the microarrays highlight a change in immune genes (ex. antibacterial peptide genes)? Whatever the answer, this would be worth mentioning. The authors described their microarray data in terms of fed/starved in relation to the Finke article. They should clarify if they observed significant differences between species (differences between species within bacteria or fungi, and more generally differences between bacteria versus fungi).

4) The whole paper - and this is one of its merits - points to a role of the Drosophila larval microbiota in processing the fly food. Are these bacterial and fungal species found in the gut of larvae/adults? Are these species capable of establishing a niche in the cardia of adults as shown recently in the Ludington lab (Dodge et al.,)? Previous studies have suggested that microbiota members stimulate the Imd pathway leading to an increase in digestive proteases (Erkosar/Leulier). Are the microbiota species studied here affecting gut signaling pathways beyond providing branched amino acids?

Reviewer #2 (Public Review):

Summary:

In this manuscript, Mure et al investigated host-microbe interactions in wild-mimicked settings. They analyzed microbiome composition using bananas that had been fed on by wild larvae and found that the microbiota composition shifted from the early stage of feeding to the later stage of the fermentation process. They isolated several yeast and bacterial species from the food, and examined larval growth on banana-based food, mimicking a natural setting where germ-free larvae cannot grow on it. The authors found that a yeast, Hanseniaspora uvarum, can support larval growth sufficiently, and insisted that branched-chain amino acids (BCAAs) provided by the yeast may partly account for the growth support. Interestingly, in other isolated yeast species, some were non-supportive strains in terms of larval growth, which can assist larval development when they are heat-killed. Besides, they showed that acetic acid bacteria, isolated from well-fermented banana (later-stage food), is sufficiently supportive but their presence depended on other microbes, lactic acid bacteria or yeast.

Strengths:

So far, host-microbe studies using Drosophila melanogaster have focused relatively less on the roles of fungi, and many studies used only "model" yeasts. In the experimental setting where natural conditions may be well mimicked, the authors successfully isolated wild yeast species and convincingly showed that wild yeast plays a critical role in promoting host growth. In addition, the authors provided intriguing observations that all of the heat-killed yeast promoted larval growth even though some of the yeast never supported the development when they were alive, suggesting that wild yeasts produce the necessary nutrients for larval development, but the nutrients of non-supportive yeasts are not accessible to the host. This might be an interesting indication for further studies revealing host-fungi interactions.

Weaknesses:

The experimental setting that, the authors think, reflects host-microbe interactions in nature is one of the key points. However, it is not explicitly mentioned whether isolated microbes are indeed colonized in wild larvae of Drosophila melanogaster who eat bananas. Another matter is that this work is rather descriptive and a few mechanical insights are presented. The evidence that the nutritional role of BCAAs is incomplete, and molecular level explanation is missing in "interspecies interactions" between lactic acid bacteria (or yeast) and acetic acid bacteria that assure their inhabitation. Apart from these matters, the future directions or significance of this work could be discussed more in the manuscript.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Mure et al. describe interactions between diet, microbiome, and host development using Drosophila as a model. By characterizing microbial communities in food sources and animals, the authors showed that microbial community dynamics in the food source are critical for host development.

Strengths:

This is a very interesting study where the authors managed to tackle a difficult question in an elegant manner. How the interactions between different microbial species within the microbiome shape host physiology is an area of great interest but equally challenging due to the complexity of intercellular interactions in complex, host-associated microbial communities. By using a simplified model and interrogating not only microbe-microbe and host-microbe interactions, but also the role played by diet, authors were able to identify significant interactions during fly development.

Weaknesses:

Despite describing important findings, I believe that a more thorough explanation of the experimental setup and the steps expected to occur in the exposed diet over time, starting with natural "inoculation" could help the reader, in particular the non-specialist, grasp the rationale and main findings of the manuscript. When exactly was the decision to collect early-stage samples made? Was it when embryos were detected in some of the samples? What are the implications of bacterial presence in the no-fly traps? These samples also harbored complex microbial communities, as revealed by sequencing. Were these samples colonized by microbes deposited with air currents? Were they the result of flies that touched the material but did not lay eggs? Could the traps have been visited by other insects? Another interesting observation that could be better discussed is the fact that adult flies showed a microbiome that more closely resembles that of the early-stage diet, whereas larvae have a more late-stage-like microbiome. It is easy to understand why the microbiome of the larvae would resemble that of the late-stage foods, but what about the adult microbiome? Authors should discuss or at least acknowledge the fact that there must be a microbiome shift once adults leave their food source. Lastly, the authors should provide more details about the metabolomics experiments. For instance, how were peaks assigned to leucine/isoleucine (as well as other compounds)? Were both retention times and MS2 spectra always used? Were standard curves produced? Were internal, deuterated controls used?

Reviewer #1 (Public Review):

Taking advantage of a publicly available dataset, neuronal responses in both the visual and hippocampal areas to passive presentation of a movie are analyzed in this manuscript. Since the visual responses have been described in a number of previous studies (e.g., see Refs. 11-13), the value of this manuscript lies mostly on the hippocampal responses, especially in the context of how hippocampal neurons encode episodic memories. Previous human studies show that hippocampal neurons display selective responses to short (5 s) video clips (e.g. see Gelbard-Sagiv et al, Science 322: 96-101, 2008). The hippocampal responses in head-fixed mice to a longer (30 s) movie as studied in this manuscript could potentially offer important evidence that the rodent hippocampus encodes visual episodes.

The analysis strategy is mostly well designed and executed. A number of factors and controls, including baseline firing, locomotion, frame-to-frame visual content variation, are carefully considered. The inclusion of neuronal responses to scrambled movie frames in the analysis is a powerful method to reveal the modulation of a key element in episodic events, temporal continuity, on the hippocampal activity. The properties of movie fields are comprehensively characterized in the manuscript.

Comments on latest version:

The new analysis on how behavioral states and hippocampal ripples impacted the tuning of movie fields makes the main finding substantially more convincing. Other relatively minor concerns on the methodology and interpretation are also improved. I do not have further concerns.

Reviewer #3 (Public Review):

In their study, Purandare & Mehta analyze large-scale single unit recordings from the visual system (LGN, V1, extrastriate regions AM and PM) and hippocampal system (DG, CA3, CA1 and subiculum) while mice monocularly viewed repeats of a 30s movie clip. The data were part of a larger release of publicly available recordings from the Allen Brian Observatory. The authors found that cells in all regions exhibited tuning to specific segments of the movie (i.e. "movie fields") ranging in duration from 20ms to 20s. The largest fractions of movie-responsive cells were in visual regions, though analyses of scrambled movie frames indicated that visual neurons were driven more strongly by visual features of the movie images themselves. Cells in the hippocampal system, on the other hand, tended to exhibit fewer "movie fields", which on average were a few seconds in duration, but could range from >50ms to as long as 20s. Unlike the visual system "movie fields" in the hippocampal system disappeared when the frames of the movie were scrambled, indicating that the cells encoded more complex (episodic) content, rather than merely passively reading out visual input.

The paper is conceptually novel since it specifically aims to remove any behavioral or task engagement whatsoever in the head-fixed mice, a setup typically used as an open-loop control condition in virtual reality-based navigational or decision making tasks (e.g. Harvey et al., 2012). Because the study specifically addresses this aspect of encoding (i.e. exploring effects of pure visual content rather than something task-related), and because of the widespread use of video-based virtual reality paradigms in different sub-fields, the paper should be of interest to those studying visual processing as well as those studying visual and spatial coding in the hippocampal system.

Comments on latest version:

The revised manuscript by Purandare et al. has been improved with the inclusion of additional analyses and discussion, and the changes mainly satisfy the concerns raised in the initial version of the manuscript.

Regarding the methods, it was particularly helpful that the authors took measures to consider the impact of different states of arousal (pupil diameter), mobility, and SWRs on the expression and significance of movie field tuning, considering the lack of a task structure or behavioral report. Relatedly, the additional metrics applied (information rate and depth of movie field modulation) substantiate the results as based on z-scored sparsity. The explanation of lifetime sparseness as used here vs. in the work of de Vries et al. 2020 was also helpful.

The addition of more clearly tuned cells also helps the study feel more rooted in solid ground. For clarity, and consistency with the rest of the paper, it would be helpful to add the sparseness metrics above the newly added neural data in the Figure supplements.

The Discussion also contains elements that help balance both it and the paper as a whole. It draws a clearer distinction between the representation of visual scenes rather than encoding the contents of episodic memory, clarifying that hippocampal neurons were more likely doing the former than the latter. It is also appreciated that the authors added discussion acknowledging that the cortical processing did not quite follow an apparent hierarchical order.

As a last observation, though the authors assert in their rebuttal that analysis of the visual content encoded in the movie fields is beyond the scope of the study, this would add an interesting dimension to the work. Because, to my awareness, much less is known regarding how the visual and hippocampal systems in rodents encode visual information when the visual input is dynamic and chunked, as with movies. It would prove an interesting addition to the more extensive work on the processing of static visual scenes.

Reviewer #1 (Public Review):

With this work, the authors address a central question regarding the potential consequences of post-translational modifications for the pathogenesis of neurodegenerative diseases. Phosphorylation and mislocalization of the RNA binding protein TDP43 are characteristic of ~50% of frontotemporal lobar degeneration (FTLD), as well as >95% of amyotrophic lateral sclerosis (ALS). To determine if acetylation is a primary, disease-driving event, they generated a TDP-43 mutant harboring an acetylation-mimicking mutation (K145Q). Animals carrying the acetylation-mimic mutation (K145Q) displayed key pathological features of disease, including more cytoplasmic TDP43 and impaired TDP43 splicing activity, together with behavioral phenotypes reminiscent of FTLD.

This is a well-written and well-illustrated manuscript, with clear and convincing findings. The observations are significant and emphasize the importance of post-translational modifications to TDP-43 function and disease phenotypes. In addition, the TDP43(K145Q) mice may prove to be a valuable model for studying TDP-43-related mechanisms of neurodegeneration and therapeutic strategies.

Comments on the latest version:

The authors have addressed most concerns. The additional analysis demonstrating a lack of neuron loss is quite different from the original study -- it is good that the authors pursued this question. In addition, new data focusing on native TDP-43 splice targets, rather than the splicing reporter, are excellent.

Reviewer #2 (Public Review):

This paper extends prior work demonstrating the importance of K145 acetylation of TDP-43 as a post-translational modification that impacts its RNA-binding capacity and may contribute to pathology in FTLD-ALS. The main strengths of this paper are the generation of a novel mouse model, using CRISPR gene editing, in which an acetylation-mimetic mutation (K to Q) is introduced at position 145. Behavioral, biochemical, and genetic analyses indicate that these mice display phenotypes relevant to TDP-43-associated disease and will be a valuable contribution to the field.

Reviewer #3 (Public Review):

Numerous experimental models are phenotyped in this manuscript including mouse neurons, iPSC-derived human neurons, knock-in mice, and knock-in iPSCs. Expression of acetylation-mimic or acetylation-null TDP-43 protein is achieved either with overexpression or CRISPR-Cas9-based knock-in. A complex phenotype is observed including loss of TDP-43 function (reduced autoregulation, increased cryptic splicing) and a gain of TDP-43 (increased insoluble TDP-43 protein). These correlate with downstream neurobehavioral changes which are most consistent with a cortical/hippocampal phenotype without a motor phenotype. Post-translational modifications of disease-associated proteins are thought to contribute to neurodegenerative disease pathogenesis, and this study succeeds in demonstrating that TDP-43 acetylation results in downstream molecular and behavioral phenotypes.

TDP-43 acetylation is a post-translational modification that is known to be associated with TDP-43 inclusions that are characteristic of human diseases. An important strength is the rigorous use of multiple different experimental models (rodent cells, iPSC-derived neurons, mice, overexpression, knock-in) with overall consistent results. Moreover, multiple orthogonal endpoints are presented including histology/cytology/immunostaining, biochemistry, molecular biology, and neurobehavioral assays. As TDP-43 acetylation is known to block RNA binding, these novel cellular and mouse models represent interesting albeit complex tools to study the functional consequences of a partial loss of function. As TDP-43 regulates its own expression (i.e. autoregulation), the complexity lies at least in part due to the loss of RNA binding leading to a functional loss of TDP-43 function which includes the increased expression of the TARDBP transcript and TDP-43 protein.

Conceptually, there is a disconnect in that the mouse model exhibits primarily a cortical/hippocampal phenotype more akin to frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP), while TDP-43 acetylation is only seen in ALS tissues and not in FTLD-TDP tissues because most of the pathologic protein in the latter is N-terminally truncated (i.e. the acetylation site is not present). That being said, there is no mouse model which completely and faithfully recapitulates the human disease, and this mouse model avoids overt overexpression (increased TDP-43 protein expression stemming from altered autoregulation) and avoids the use of synthetic/artificial mutation (such as mutation of the TDP-43 nuclear localization signal).

This revision addresses most of my prior comments including documenting the lack of neurodegeneration in this model, the use of more appropriate statistical methods, and the use of more robust/quantitative aberrant splicing measures. The one thing which would still be helpful is sequencing the top predicted off target genomic loci for their various CRISPR'd models irrespective of whether these loci are exonic or noncoding. Having actual sequencing verification of the lack of mutations at these loci is preferable over relying only on computational likelihood estimates.

Reviewer #1 (Public Review):

Summary:

This is an important study that tests the effects of using neurofeedback, in the form of reward delivery when large sharp wave-ripples (SWRs) are detected, on neurophysiological and behavioral measures. The authors report that the rate of SWRs ripples increased prior to reward delivery, but this increased rate of SWRs had no significant effect on memory performance. They also found that compensatory decreases in SWR rate occurred in the period after reward delivery such that the overall SWR rate remained stable.

Strengths:

The study has many strengths. The paradigm of closed loop detection of SWRs and reward delivery is powerful and provides an innovative way to causally test the effects of increasing SWR rates. Other studies could adopt this method to test other hypotheses or to assess the effects of increasing SWR rates prior to reward delivery in rodent models of brain disorders. The methods and results are clearly explained. The results are presented in a transparent way.

Weaknesses:

In the linear mixed effects model analysis used in Figure 2, and statistics reported in the figure legend, an interaction effect showing that neurofeedback differentially affected the SWR rate and count pre- and post-award seems to be missing in the reported statistics.

In the Discussion, the authors write, "Further, because subjects learn to modulate SWR rate, rather than simply generating a single suprathreshold event on command, it is likely that they learn to engage a SWR-permissive state during the targeted interval in which brain-wide neural activity and neuromodulatory tone also enter a SWR-permissive realm". This seems to imply that the neurofeedback is directly modulating neural activity. However, it is unclear from the paper exactly how the neurofeedback is modulating the SWR rate. Considering that SWRs occur during immobility, is it possible that the animals are learning to remain more immobile and modulating the SWR rate in that way?

Reviewer #2 (Public Review):

Gillespie et al. introduced a novel neurofeedback (NF) procedure to train rats in enhancing their sharp-wave ripple (SWR) rate within a short duration, a key neural mechanism associated with memory consolidation. The training, embedded within a spatial memory task, spanned 20-30 days and utilized food rewards as positive reinforcement upon SWR detection. Rats were categorized into NF and control groups, with the NF group further divided into NF and delay trials for within-subject control. While single trial differences were elusive due to the variability of SWR occurrence, the study revealed that statistically rats in NF trials exhibited a notably higher SWR rate before receiving rewards compared to delay trials. This difference was even more pronounced when juxtaposed with rats not exposed to NF training (control group). The unique design of blending the NF phase with the memory dependent spatial task enabled the authors to analyze whether the NF training influence the task performance and replay content during SWRs across three different conditions (NF trials, delay trials and control group). Interestingly, despite the NF training, there was no significant improvement or decline in the performance of the spatial memory task, and the replay content remained consistent across all three conditions. Hence, the operant conditioning only amplified the SWR rate before reward in NF trials without altering the task performance and the replay content during SWR. Moreover, considering the post-reward period, the total SWR count was consistent across all conditions as well, meaning the NF training also do not affect the total SWR count. The study concludes with the hypothesis of a potential homeostatic mechanism governing the total SWR production in rats. This research significantly extends previous work by Ishikawa et al. (2014), offering insights into the NF training with external reward on the SWR rate/counts, replay content and task performance.

Strengths:

- Integration of NF task and spatial memory task in a single trial<br /> The integration of NF training within a spatial memory task poses significant challenges. Gillespie and colleagues overcame this by seamlessly blending the NF task and the spatial memory task into a single trial. Each trial involved a rat undergoing three steps: First, initiating a trial. Second, moving to either the NF port or the delay trial port, as indicated by an LED, and then maintaining a nosepoke at one of the center ports. During this step, the rat had to keep its nose (in the NF port) until a sharp-wave ripple (SWR) exceeding a set threshold was detected, which then triggered a reward, or until a variable time elapsed (in the delay port). Third, the rat would choose one of eight arms to explore before starting the next trial. This integration of the two tasks (step two as the NF task and step three as the spatial memory task) facilitated a direct analysis of the impact of NF training on behaviorally relevant replay content during SWRs and the performance in the spatial memory task.

- Clear Group Separation<br /> A robust study design necessitates clear distinctions between experimental conditions to ensure that observed differences can be attributed to the variable under investigation. This study meticulously categorized rats into three distinct conditions: NF trials, delay trials (for within-subject control), and a control group (for across-subject control). Furthermore, for each trial, the times of interest (TOI) were separated into pre-reward and post-reward periods. This clear separation ensures that any observed differences in SWR rates and other outcomes can be confidently attributed to the effects of neurofeedback training during specific time periods, minimizing potential confounding factors.

- Evidence of SWR rate modulation<br /> The study's results offer compelling evidence that rats can be trained to modulate their SWR rates during the pre-reward period. This is evident from the observation that rats in the NF trials consistently displayed a higher SWR rate before receiving rewards compared to those in delay trials or the control group (Fig. 2). Such findings not only validate the efficacy of the NF paradigm but also underscore the potential of operant conditioning in influencing neural mechanisms. The observation that rats were able to produce larger SWR events by modulating their occurrence rate, rather than merely waiting for these events, suggests a learned strategy to generate them more efficiently.

- Evidence of SWR count homeostasis<br /> A notable finding from the study was the observation of a consistent total SWR count during both pre-reward and post-reward periods across all conditions, despite the evident increase in SWR rates during the pre-reward period in NF trials. This points to a potential homeostatic mechanism governing SWR production in rats. This balance suggests that while NF training can modulate the timing and rate of SWRs over a short duration, it doesn't influence the overall count of SWRs over a longer period. Such a mechanism might be essential in ensuring that the brain neither overcompensates nor depletes its capacity for SWRs, maintaining the overall neural balance and functionality. This discovery deepens our understanding of neural mechanisms and highlights potential avenues for future research into the regulatory processes governing neural activity.

Weaknesses:

- Misleading Title<br /> The title, "Neurofeedback training can modulate task-relevant memory replay in rats," implies that through neurofeedback training, rats can learn to modulate the content of their memory replay. However, the study's findings contradict this implication. Particularly, one of the subtitles of this paper is "Neurofeedback training preserves replay content during SWRs," which directly contrasts with the main title's suggestion. The authors conclusively demonstrated that there was no discernible difference in the replay content between animals that underwent NF training and those that did not. The current title easily leads to misinterpretations about the study's primary outcomes, especially for readers who might not delve into the detailed findings.

- Lack of control analysis baseline for each animal<br /> While the authors meticulously categorized trial types into three distinct conditions: NF trials, delay trials, and control groups, they did not clearly establish a baseline for each animal. The animal could have a total different baseline SWR rates. The paper appears to operate under the assumption that each animal possesses a consistent SWR rate baseline, leading to only the final comparisons being presented.

- Vagueness of what animal really control during NF trials after training<br /> The authors state that, "Moreover, although we did observe a slightly lower mean speed during the pre-reward period on neurofeedback trials compared to delay trials and trials from the control cohort (Supplementary Figure 2F), movement differences could not explain the difference in SWR rates (Supplementary Figure 2G, H)." This assertion raises questions about the underlying mechanisms at play. In a typical operant conditioning scenario, training could result in direct neural modulation, behavioral changes, or a combination of both. For instance, rats might adopt a more stationary posture during the pre-reward period on NF trials compared to other conditions, or they might actively influence the occurrence rate of SWRs during this period. The paper would benefit from a clearer delineation of what the animals are specifically controlling or modulating during the NF trials, ensuring a more comprehensive understanding of the observed effects.

- Clinical Implications<br /> The study was conducted on healthy, young animals but suggests potential benefits for older, cognitively impaired animals. However, it's possible that older or deficit animals might not respond to the NF protocol in the same way.

Reviewer #3 (Public Review):

Summary:

This study implements an innovative neurofeedback procedure in rats, providing food reward upon detection of a sharp wave-ripple event (SWR) in the hippocampus. The elegant experimental design enables a within-animal comparison of the effects of this neurofeedback procedure as compared to a control condition in which an equivalent reward is provided in a non-contingent manner. The neurofeedback procedure was found to increase SWR rate, followed by a compensatory reduction in SWR rate. These changes in SWR rate were not accompanied by any changes in memory performance on the memory-guided task.

Strengths:

The scientific premise for the study is outstanding. It addresses an issue of high importance, of developing ways to not merely describe correlations between SWRs (and their content) and memory performance, but to manipulate them. The authors argue clearly and convincingly that even studies that have performed causal manipulations of SWRs have important confounds and limitations, and most importantly for translational purposes, they are all invasive. So, the idea of developing a potentially non-invasive neurofeedback procedure for modulating SWRs is compelling both as an innovative new experimental manipulation in studies of SWRs, and as a potentially impactful therapeutic avenue.

In addition to addressing an important issue with an innovative approach, the study has many other strengths. The data unambiguously show that the method is effective at increasing SWR rate in each individual subject. The experimental design allows within-subject comparison of neurofeedback and control trials, where the subjects wait an equivalent amount of time. The careful analyses of SWR properties and their content establish that neurofeedback SWRs are comparable to control SWRs. The data add further evidence to the notion that SWR rate is subject to homeostatic control. The paper is also exceptionally well written, and was a pleasure to read. So, there is a clear technical advance, in that there is now a method for increasing SWR rate non-invasively, which is rigorously established and characterized.

Weaknesses:

The one overall limitation I find with this study is that it is unclear to what extent the same (or better) results could have been obtained using behavior-feedback instead of neuro-feedback. Because SWR rates are generally higher during states of quiescence compared to active movement or task engagement, it is possible that reinforcing behaviorally detected quiescent states (e.g. low movement) would indirectly increase SWR rates. The observation that all 4 subjects had lower movement speeds during neurofeedback compared to control trials supports this interpretation. This is an important issue that would help clarify whether the neurofeedback approach is worth the additional effort and expense compared to behavioral feedback.

Reviewer #1 (Public Review):

Summary:<br /> The paper presents a nice study investigating differences in biological motion perception in participants with ADHD in comparison with controls. Motivated by the idea that there is a relationship between biological motion perception and social capabilities, the authors investigated local and global (holistic) biological motion perception, the group, and several additional behavioral variables that are affected in ADHS (IQ, social responsiveness, and attention/impulsivity). As well as local global biological motion perception is reduced in ADHD participants. In addition, the study demonstrates a significant correlation between local biological motion perception skills and the social responsiveness score in the ADHD group, but not the controls. A path analysis in the ADHD data suggests that general performance in biological motion perception is influenced mainly by global biological motion perception performance and attentional and perceptual reasoning skills.

Strengths:<br /> It is true that there exists not much work on biological motion perception and ADHD. Therefore, the presented study contributes an interesting new result to the biological motion literature and adds potentially also new behavioral markers for this clinical condition. The design of the study is straightforward and technically sound, and the drawn conclusions are supported by the presented results.

Weaknesses:<br /> Some of the claims about the relationship between genetic factors and ADHD and the components of biological motion processing have to remain speculative at this point because genetic influences were not explicitly tested in this paper.

Reviewer #2 (Public Review):

Summary:<br /> Tian et al. aimed to assess differences in biological motion (BM) perception between children with and without ADHD, as well as relationships to indices of social functioning and possible predictors of BM perception (including demographics, reasoning ability and inattention). In their study, children with ADHD showed poorer performance relative to typically developing children in three tasks measuring local, global, and general BM perception. The authors further observed that across the whole sample, performance in all three BM tasks was negatively correlated with scores on the social responsiveness scale (SRS), whereas within groups a significant relationship to SRS scores was only observed in the ADHD group and for the local BM task. Local and global BM perception showed a dissociation in that global BM processing was predicted by age, while local BM perception was not. Finally, general (local & global combined) BM processing was predicted by age and global BM processing, while reasoning ability mediated the effect of inattention on BM processing.

Strengths:<br /> Overall, the manuscript is presented in a relatively clear fashion and methods and materials are presented with sufficient detail so the study could be reproduced by independent researchers. The study uses an innovative, albeit not novel, paradigm to investigate two independent processes underlying BM perception. The results are novel and have the potential to have wide-reaching impact on multiple fields.

Weaknesses:<br /> Except for the main analysis, it is unclear what the authors' specific predictions are regarding the three different tasks they employ. The three BM tasks are used to probe different processes underlying BM perception, but it is difficult to gather from the introduction why these three specific tasks were chosen and what predictions the authors have about the performance of the ADHD group in these tasks. Relatedly, the authors do not report whether (and if so, how) they corrected for multiple comparisons in their analyses. As the number of tests one should control for depends on the theoretical predictions (http://daniellakens.blogspot.com/2016/02/why-you-dont-need-to-adjust-you-alpha.html), both are necessary for the reader to assess the statistical validity of the results and any inferences drawn from them. The same is the case for the secondary analyses exploring relationships between the 3 individual BM tasks and social function measured by the social responsivity scale (SRS).

In relation to my prior point, the authors could provide more clarity on how the conclusions drawn from the results relate to their predictions. For example, it is unclear what specific conclusions the authors draw based on their findings that ADHD show performance differences in all three BM perception tasks, but only local BM is related to social function within this group. Here, the claim is made that their results support a specific hypothesis, but it is unclear to me what hypothesis they are actually referring to (see line 343 & following). This lack of clarity is aggravated by the fact that throughout the rest of the discussion, in particular when discussing other findings to support their own conclusions, the authors often make no distinction between the two processes of interest. Lastly, some of the authors' conclusions related to their findings on local vs global BM processing are not logically following from the evidence: For instance, the authors conclude that their data supports the idea that social atypicalities are likely to reduce with age in ADHD individuals. However, according to their own account, local BM perception - the only measure that was related to social function in their study - is understood to be age invariant (and was indeed not predicted by age in the present study).

Results reported are incomplete, making it hard for the reader to comprehensively interpret the findings and assess whether the conclusions drawn are valid. Whenever the authors report negative results (p-values > 0.05), the relevant statistics are not reported, and the data not plotted. In addition, summary statistics (group means) are missing for the main analysis.

Some of the conclusions/statements in the article are too strong and should be rephrased to indicate hypotheses and speculations rather than facts. For example, in lines 97-99 the authors state that the finding of poor BM performance in TD children in a prior study 'indicated inferior applicability' or 'inapplicable experimental design'. While this is one possibility, a perhaps more plausible interpretation could be that TD children show 'poor' performance due to outstanding maturation of the underlying (global) BM processes (as the authors suggest themselves that BM perception can improve with age). There are several other examples where statements are too strong or misleading, which need attention.

Reviewer #3 (Public Review):

Summary:<br /> The authors presented point light displays of human walkers to children (mean = 9 years) with and without ADHD to compare their biological motion perception abilities and relate them to IQ, social responsiveness scale (SRS) scores and age. They report that children with ADHD were worse at all three biological motion tasks, but that those loading more heavily on local processing related to social interaction skills and global processing to age. The important and solid findings are informative for understanding this complex condition, as well as biological motion processing mechanisms in general. However, I am unsure that these differences between local and global skills are truly supported by the data and suggest some further analyses.

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

Weaknesses:<br /> I am unsure that the data are strong enough to support claims about differences between global and local processing wrt social communication skills and age. The mechanistic possibilities for why these abilities may dissociate in such a way are interesting, but do not seem so plausible to me. I am also concerned about gender, and possible autism, confounds when examining the effect of ADHD. Specifics:

Gender confound. There are proportionally more boys in the ADHD than TD group. The authors appear to attempt to overcome this issue by including gender as a covariate. I am unsure if this addresses the problem. The vast majority of participants in the ADHD group are male, and gender is categorically, not continuously, defined. I'm pretty sure this violates the assumptions of ANCOVA.

Autism. Autism and ADHD are highly comorbid. The authors state that the TD children did not have an autism or ADHD diagnosis, but they do not state that the ADHD children did not have an autism diagnosis. Given the nature of the claims, this seems crucial information for the reader.

Conclusions. The authors state frequently that it was the local BM task that related to social communication skills (SRS) and not the global tasks. However, the results section shows a correlation between SRS and all three tasks. The only difference is that when looking specifically within the ADHD group, the correlation is only significant for the local task. I think that if the authors wish to make strong claims here they must show inferential stats supporting (1) a difference between ADHD and TD SRS-Task 1 correlations, and (2) a difference in those differences for Task 2 and 3 relative to Task 1. I think they should also show a scatterplot of this correlation, with separate lines of best fit for the two groups, for Tasks 2 and 3 as well. I.e. Figure 4 should have 3 panels. I would recommend the same type of approach for age. Currently, they have small samples for correlations, and are reading much of theoretical significance between some correlations passing significance threshold and others not. It would be incredibly interesting if the social skills (as measured by SRS) only relate to local BM abilities, and age only to global, but I think the data are not so clear with the current information. I would be surprised if all BM abilities did not improve with age. Even if there is some genetic starter kit (and that this differs according to particular BM component), most abilities improve with learning/experience/age.

Theoretical assumptions. The authors make some sweeping statements about local vs global biological motion processing that need to be toned down. They assume that local processing is specifically genetically whereas global processing is a product of experience. The fact their global, but not local, task performance improves with age would tend to suggest there could be some difference here, but the existing literature does not allow for this certainty. The chick studies showing a neonatal preference are controversial and confounded - I cannot remember the specifics but I think there an upper vs lower visual field complexity difference here.

Reviewer #1 (Public Review):

This work describes a new and powerful approach to a central question in ecology: what are the relative contributions of resource utilisation vs interactions between individuals in the shaping of an ecosystem? This approach relies on a very original quantitative experimental set-up whose power lies in its simplicity, allowing an exceptional level of control over ecological parameters and of measurement accuracy.

In this experimental system, the shared resource corresponds to 10^12 copies of a fixed single-stranded target DNA molecule to which 10^15 random single-stranded DNA molecules (the individuals populating the ecosystem) can bind. The binding process is cycled, with a 1000x-PCR amplification step between successive binding steps. The composition of the population is monitored via high-throughput DNA sequencing. Sequence data analysis describes the change in population diversity over cycles. The results are interpreted using estimated binding interactions of individuals with the target resource, as well as estimated binding interactions between individuals and also self-interactions (that can all be directly predicted as they correspond to DNA-DNA interactions). A simple model provides a framework to account for ecosystem dynamics over cycles. Finally, the trajectory of some individuals with high frequency in late cycles is traced back to the earliest cycles at which they are detected by sequencing. Their propensities to bind the resource, to form hairpins, or to form homodimers suggest how different interaction modes shape the composition of the population over cycles.

The authors report a shift from selection for binding to the resource to interactions between individuals and self-interactions over the course of cycles as the main drivers of their ecosystem. The outcome of the experiment is far from trivial as the individual-resource binding energy initially determines the relative enrichment of individuals, and then seems to saturate. The richness of the population dynamics observed with this simple system is thus comparable to that found in some natural ecosystems. The findings obtained with this new approach will likely guide the exploration of natural ecosystems in which parameters and observables are much less accessible.

My review focuses mainly on the experimental aspects of this work given my own expertise. The introduction exposes very convincingly the scientific context of this work, justifying the need for such an approach to address questions pertaining to ecology. The manuscript describes very clearly and rigorously the experimental set-up. The main strengths of this work are (i) the outstanding originality of the experimental approach and (ii) its simplicity. With this setup, central questions in ecology can be addressed in a quantitative manner, including the possibility of running trajectories in parallel to generalize the findings, as reported here. Technical aspects have been carefully implemented, from the design of random individuals bearing flanking regions for PCR amplification, binding selection and (low error) amplification protocols, and sequencing read-out whose depth is sufficient to capture the relevant dynamics. One missing aspect in the data analysis is the quantification of the effect of PCR amplification steps in shaping the ecosystem (to be modeled if significant). In addition, as it stands the current work does not fully harness the power of the approach. For instance, with this setup, one can tune the relative contributions of binding selection vs amplification for instance (to disentangle forces that shape the ecosystem). One can also run cycles with new DNA individuals, designed with arbitrarily chosen resource binding vs self-binding, that are predicted to dominate depending on chosen ecological parameters.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors introduced ADSE, a SELEX-based protocol to explore the mechanism of emergency of species. They used DNA hybridization (to the bait pool, "resources") as the driving force for selection and quantitatively investigated the factors that may contribute to the survival during generation evolution (progress of SELEX cycle), revealing that besides individual-resource binding, the inter- and intra-individual interactions were also important features along with mutualism and parasitism.

Strengths:<br /> The design of using pure biochemical affinity assay to study eco-evolution is interesting, providing an important viewpoint to partly explain the molecular mechanism of evolution.

Weaknesses:<br /> Though the evidence of the study is somewhat convincing, some aspects still need to be improved, mostly technical issues.

Reviewer #1 (Public Review):

In this study, the authors obtained multiple, novel and compelling datasets to better understand the relationship between histone H1 and RNA-directed DNA methylation in plants. Most of the authors' claims concerning H1 and RNA polymerase V (Pol V) are backed by convincing and independent lines of evidence. However, the authors also make some overly broad conclusions, for which additional experiments/data analyses should be explored to improve confidence in their findings. Furthermore, Pol V produces noncoding transcripts that act as scaffold RNAs, which AGO4-bound siRNAs recognize in plant chromatin to mediate RNA-directed DNA methylation. Detection of Pol V transcript products at sites of Pol V redistribution in h1 mutants would significantly enhance the impact of this manuscript. Below I have listed several strengths and weaknesses of the manuscript.

Strengths<br /> 1. The authors report high-quality NRPE1 ChIP-seq data, allowing them to directly test how and where Pol V occupancy depends on histone H1 function in Arabidopsis.<br /> 2. nrpe1 mutants generated via CRISPR/Cas9 in the h1 mutant background (nrpe1 h1.1-1 h1.2-1 triple mutants), allow the authors to study the role of Pol V in ectopic DNA methylation in H1-deficient plants.<br /> 3. Pol V recruitment via ZincFinger-DMS3 expression (a modified version of Pol V's DMS3 recruitment factor) sends Pol V to new genomic loci and thus provides the authors with an innovative dataset for understanding H1 function at these sites.

Weaknesses<br /> 1. The manuscript does not include detection or quantification of Pol V transcripts generated at ectopic sites in the h1 mutant background.<br /> 2. Statistical tests are missing throughout and are needed to support several of the authors' claims.<br /> 3. The SUVH1-3xFLAG ChIP-seq analyses in Fig. 6 require additional controls and are not fully explained in the results. The broad conclusions drawn (based on those experiments) are thus not convincing.

Previous studies have charted the relationship between H1 function and RNA-directed DNA methylation (RdDM) via analyses of Pol IV-dependent 24 nt siRNAs and factors that recruit Pol IV (Choi et al., 2021 and Papareddy et al., 2020). Harris and colleagues have extended this work and shown that histone H1 function also antagonizes Pol V occupancy in the context of constitutive heterochromatin. The authors thus provide important evidence to show that H1 limits the encroachment of both polymerases Pol IV and Pol V into plant heterochromatin.

Reviewer #2 (Public Review):

Summary:<br /> The main conclusion of the manuscript is that the presence of linker Histone H1 protects Arabidopsis pericentromeric heterochromatic regions and longer transposable elements via chromatin compaction from encroachment by other repressive pathways. The manuscript focuses on the RNA-dependent DNA-methylation (RdDM) pathway but indirectly finds that other pathways must also be ectopically enriched.

Strengths:<br /> The authors present diverse sets of genomic data comparing Arabidopsis wild-type and h1 mutant background allowing an analysis of differential recruitment of RdDM component NPRE1, which is related to changes in DNA methylation and H1 coverage. As an addendum, the manuscript also contains recruitment data for SUVH1 in wild-type and h1 mutant backgrounds.

Furthermore, the authors make use of a line that recruits NRPE1 ectopically to show that H1 occupancy is not altered because of this recruitment. These are negative data, but well supported.

Weaknesses:<br /> The manuscript mostly confirms earlier observations but shows very limited novelty. It has already been reported that different classes of TEs show a differential response with respect to DNA methylation in absence of H1. Furthermore, the fact that loss of H1 affect global chromatin accessibility was recently published by Teano et al. in Cell reports (Volume 42, Issue 8, 29 August 2023). The authors have neither cited this report (that had been available since 2021 in BioRxiv), nor set their work in context to this study. The study by Teano showed that for some TEs, loss of H1 is related to a switch from DNA-methylation dependent repressive pathways to Polycomb Group-dependent pathways. The current manuscript could have looked at overlapping classes and integrated information from both studies, which would be particularly interesting for the examples illustrated in Figure 5b, showing examples of TEs that lose NRPE1 targeting and methylation in all contexts in H1 deletion mutants.

The proposed mechanism is that RdDM along with many other chromatin factors re-distribute to heterochromatic regions in h1 mutants because these regions are more accessible. There is a general problem with measuring the "difference in chromatin compaction" with methods that mostly resolve highly accessible chromatin in contrast to any other chromatin, such as ATAC-seq or DNAse-seq (employed in this manuscript). The changes in the regions of interest are so subtle that they are not easily detected at the level of individual genes, although they become usually more obvious in metagene plots. The general question is if this inadequate method is sufficient to draw strong conclusions on chromatin compaction, but to be fair, the current manuscript is not alone in using this method without pointing out certain caveats.

As a consequence of redistribution to heterochromatic sites, the authors postulate that there are also sites that lose RdDM coverage in h1, but these sites are not really evidenced in the report.<br /> Unfortunately, another weakness is that it is not possible to make easy use of the analysis from the available material as the current manuscript does not contain supplemental data indicating which TEs were and DMRs were considered in classes such as "long", "short", "heterochromatic", "euchromatic", "Class A", "Class B", "CMT2 dependent hypo-CHH", "DRM2 dependent CHH", "dynamic RdDM" etc. Since the bioinformatics pipelines are poorly documented (absence of dedicated script archive), the analysis cannot be easily recapitulated.

Reviewer #1 (Public Review):

People can perform a wide variety of different tasks, and a long-standing question in cognitive neuroscience is how the properties of different tasks are represented in the brain. The authors develop an interesting task that mixes two different sources of difficulty, and find that the brain appears to represent this mixture on a continuum, in the prefrontal areas involved in resolving task difficulty. While these results are interesting and in several ways compelling, they overlap with previous findings and rely on novel statistical analyses that may require further validation.

Strengths<br /> 1. The authors present an interesting and novel task for combining the contributions of stimulus-stimulus and stimulus-response conflict. While this mixture has been measured in the multi-source interference task (MSIT), this task provides a more graded mixture between these two sources of difficulty.

2. The authors do a good job triangulating regions that encoding conflict similarity, looking for the conjunction across several different measures of conflict encoding. These conflict measures use several best-practice approaches towards estimating representational similarity.

3. The authors quantify several salient alternative hypothesis and systematically distinguish their core results from these alternatives.

4. The question that the authors tackle is important to cognitive control, and they make a solid contribution.

Concerns<br /> 1. The evidence from this previous work for mixtures between different conflict sources makes the framing of 'infinite possible types of conflict' feel like a strawman. The authors cite classic work (e.g., Kornblum et al., 1990) that develops a typology for conflict which is far from infinite. I think few people would argue that every possible source and level of difficulty will have to be learned separately. This work provides confirmatory evidence that task difficulty is represented parametrically (e.g., consistent with the n-back, MOT, and random dot motion literature).

2. The degree of Stroop vs Simon conflict is perfectly negatively correlated across conditions. This limits their interpretation of an integrated cognitive space, as they cannot separately measure Stroop and Simon effects. The author's control analyses have limited ability to overcome this task limitation. While these results are consistent with parametric encoding, they cannot adjudicate between combined vs separated representations.

Reviewer #2 (Public Review):

This study examines the construct of "cognitive spaces" as they relate to neural coding schemes present in response conflict tasks. The authors use a novel experimental design in which different types of response conflict (spatial Stroop, Simon) are parametrically manipulated. These conflict types are hypothesized to be encoded jointly, within an abstract "cognitive space", in which distances between task conditions depend only on the similarity of conflict types (i.e., where conditions with similar relative proportions of spatial-Stroop versus Simon conflicts are represented with similar activity patterns). Authors contrast such a representational scheme for conflict with several other conceptually distinct schemes, including a domain-general, domain-specific, and two task-specific schemes. The authors conduct a behavioral and fMRI study to test which of these coding schemes is used by prefrontal cortex. Replicating the authors' prior work, this study demonstrates that sequential behavioral adjustments (the congruency sequence effect) are modulated as a function of the similarity between conflict types. In fMRI data, univariate analyses identified activation in left prefrontal and dorsomedial frontal cortex that was modulated by the amount of Stroop or Simon conflict present, and representational similarity analyses (RSA) that identified coding of conflict similarity, as predicted under the cognitive space model, in right lateral prefrontal cortex.

This study tackles an important question regarding how distinct types of conflict might be encoded in the brain within a computationally efficient representational format. The ideas postulated by the authors are interesting ones and the statistical methods are generally rigorous. The evidence supporting the authors claims, however, is limited by confounds in the experimental design and by lack of clarity in reporting the testing of alternative hypotheses within the method and results.

(1) Model comparison

The authors commendably performed a model comparison within their study, in which they formalized alternative hypotheses to their cognitive space hypothesis. We greatly appreciate the motivation for this idea and think that it strengthened the manuscript. Nevertheless, some details of this model comparison were difficult for us to understand, which in turn has limited our understanding of the strength of the findings.

The text indicates the domain-general model was computed by taking the difference in congruency effects per conflict condition. Does this refer to the "absolute difference" between congruency effects? In the rest of this review, we assume that the absolute difference was indeed used, as using a signed difference would not make sense in this setting. Nevertheless, it may help readers to add this information to the text.

Regarding the Stroop-Only and Simon-Only models, the motivation for using the Jaccard metric was unclear. From our reading, it seems that all of the other models --- the cognitive space model, the domain-general model, and the domain-specific model --- effectively use a Euclidean distance metric. (Although the cognitive space model is parameterized with cosine similarities, these similarity values are proportional to Euclidean distances because the points all lie on a circle. And, although the domain-general model is parameterized with absolute differences, the absolute difference is equivalent to Euclidean distance in 1D.) Given these considerations, the use of Jaccard seems to differ from the other models, in terms of parameterization, and thus potentially also in terms of underlying assumptions. Could authors help us understand why this distance metric was used instead of Euclidean distance? Additionally, if Jaccard must be used because this metric seems to be non-standard in the use of RSA, it would likely be helpful for many readers to give a little more explanation about how it was calculated.

When considering parameterizing the Stroop-Only and Simon-Only models with Euclidean distances, one concern we had is that the joint inclusion of these models might render the cognitive space model unidentifiable due to collinearity (i.e., the sum of the Stroop-Only and Simon-Only models could be collinear with the cognitive space model). Could the authors determine whether this is the case? This issue seems to be important, as the presence of such collinearity would suggest to us that the design is incapable of discriminating those hypotheses as parameterized.

(2) Issue of uniquely identifying conflict coding

We certainly appreciate the efforts that authors have taken to address potential confounders for encoding of conflict in their original submission. We broach this question not because we wish authors to conduct additional control analyses, but because this issue seems to be central to the thesis of the manuscript and we would value reading the authors' thoughts on this issue in the discussion.

To summarize our concerns, conflict seems to be a difficult variable to isolate within aggregate neural activity, at least relative to other variables typically studied in cognitive control, such as task-set or rule coding. This is because it seems reasonable to expect that many more nuisance factors covary with conflict --- such as univariate activation, level of cortical recruitment, performance measures, arousal --- than in comparison with, for example, a well-designed rule manipulation. Controlling for some of these factors post-hoc through regression is commendable (as authors have done here), but such a method will likely be incomplete and can provide no guarantees on the false positive rate.

Relatedly, the neural correlates of conflict coding in fMRI and other aggregate measures of neural activity are likely of heterogeneous provenance, potentially including rate coding (Fu et al., 2022), temporal coding (Smith et al., 2019), modulation of coding of other more concrete variables (Ebitz et al., 2020, 10.1101/2020.03.14.991745; see also discussion and reviews of Tang et al., 2016, 10.7554/eLife.12352), or neuromodulatory effects (e.g., Aston-Jones & Cohen, 2005). Some of these origins would seem to be consistent with "explicit" coding of conflict (conflict as a representation), but others would seem to be more consistent with epiphenomenal coding of conflict (i.e., conflict as an emergent process). Again, these concerns could apply to many variables as measured via fMRI, but at the same time, they seem to be more pernicious in the case of conflict. So, if authors consider these issues to be germane, perhaps they could explicitly state in the discussion whether adopting their cognitive space perspective implies a particular stance on these issues, how they interpret their results with respect to these issues, and if relevant, qualify their conclusions with uncertainty on these issues.

(3) Interpretation of measured geometry in 8C

We appreciate the inclusion of the measured similarity matrices of area 8C, the key area the results focus on, to the supplemental, as this allows for a relatively model-agnostic look at a portion of the data. Interestingly, the measured similarity matrix seems to mismatch the cognitive space model in a potentially substantive way. Although the model predicts that the "pure" Stroop and Simon conditions will have maximal self-similarity (i.e., the Stroop-Stroop and Simon-Simon cells on the diagonal), these correlations actually seem to be the lowest, by what appears to be a substantial margin (particularly the Stroop-Stroop similarities). What should readers make of this apparent mismatch? Perhaps authors could offer their interpretation on how this mismatch could fit with their conclusions.

Reviewer #3 (Public Review):

Yang and colleagues investigated whether information on two task-irrelevant features that induce response conflict is represented in a common cognitive space. To test this, the authors used a task that combines the spatial Stroop conflict and the Simon effect. This task reliably produces a beautiful graded congruency sequence effect (CSE), where the cost of congruency is reduced after incongruent trials. The authors measured fMRI to identify brain regions that represent the graded similarity of conflict types, the congruency of responses, and the visual features that induce conflicts. They applied univariate, multivariate, and connectivity analyses to fMRI data to identify brain regions that represent the graded similarity of conflict types, the congruency of responses, and the visual features that induce conflicts. They further directly assessed the dimensionality of represented conflict space.

The authors identified the right dlPFC (right 8C), which shows 1) stronger encoding of graded similarity of conflicts in incongruent trials and 2) a positive correlation between the strength of conflict similarity type and the CSE on behavior. The dlPFC has been shown to be important for cognitive control tasks. As the dlPFC did not show a univariate parametric modulation based on the higher or lower component of one type of conflict (e.g., having more spatial Stroop conflict or less Simon conflict), it implies that dissimilarity of conflicts is represented by a linear increase or decrease of neural responses. Therefore, the similarity of conflict is represented in multivariate neural responses that combine two sources of conflict.

The strength of the current approach lies in the clear effect of parametric modulation of conflict similarity across different conflict types. The authors employed a clever cross-subject RSA that counterbalanced and isolated the targeted effect of conflict similarity, decorrelating orientation similarity of stimulus positions that would otherwise be correlated with conflict similarity. A pattern of neural response seems to exist that maps different types of conflict, where each type is defined by the parametric gradation of the yoked spatial Stroop conflict and the Simon conflict on a similarity scale. The similarity of patterns increases in incongruent trials and is correlated with CSE modulation of behavior.

The main significance of the paper lies in the evidence supporting the use of an organized "cognitive space" to represent conflict information as a general control strategy. The authors thoroughly test this idea using multiple approaches and provide convincing support for their findings. However, the universality of this cognitive strategy remains an open question.

The task presented in the study involved two sources of conflict information through a single salient visual input, which might have encouraged the utilization of a common space. The similarity space was analyzed at the level of between-individuals (i.e., cross-subject RSA) to mitigate potential confounds in the design, such as congruency and the orientation of stimulus positions. This approach makes it challenging to establish a direct link between the quality of conflict space representation and the patterns of behavioral adaptations within individuals.

Furthermore, it remains unclear at which cognitive stages during response selection such a unified space is recruited. Can we effectively map any sources of conflict into a single scale? Is this unified space adaptively adjusted within the same brain region? Additionally, does the amount of conflict solely define the dimensions of this unified space across many conflict-inducing tasks? These questions remain open for future studies to address.

Taken together, this study presents an exciting possibility that information requiring high levels of cognitive control could be flexibly mapped into cognitive map-like representations that both benefit and bias our behavior. Further characterization of the representational geometry and generalization of the current results look promising ways to understand representations for cognitive control.

Reviewer #1 (Public Review):

Summary:<br /> The authors developed computational models that capture the electrical and Ca2+ signaling behavior in mesenteric arterial cells from male and female mice. A baseline model was first formulated with eleven transmembrane currents and three calcium compartments. Sex-specific differences in the L-type calcium channel and two voltage-gated potassium channels were then tuned based on experimental measurements. To incorporate the stochastic ion channel openings seen in smooth muscle cells under physiological conditions, noise was added to the membrane potential and the sarcoplasmic Ca2+ concentration equations. Finally, the models were assembled into 1D vessel representations and used to investigate the tissue-level electrical response to an L-type calcium channel blocker.

Strengths:<br /> A major strength of the paper is that the modeling studies were performed on three different scales: individual ionic currents, whole-cell, and 1D tissue. This comprehensive computational framework can help provide mechanistic insight into arterial myocyte function that might be difficult to achieve through traditional experimental methods.

The authors aimed to develop sex-specific computational models of mesenteric arterial myocytes and demonstrate their use in drug-testing applications. Throughout the paper, model behavior was both validated by experimental recordings and supported by previously published data. The main findings from the models suggested that sex-specific differences in membrane potential and Ca2+ handling are attributable to variability in the gating of a small number of voltage-gated potassium channels and L-type calcium channels. This variability contributes to a higher Ca2+ channel blocker sensitivity in female arterial vessels. Overall, the study successfully met the aims of the paper.

Weaknesses:<br /> A main weakness of the paper, as addressed by the authors, is the simplicity of the 1D vessel model; it does not take into account various signaling pathways or interactions with other cell types which could impact smooth muscle electrophysiology. Another potential shortcoming is the use of mouse data for optimizing the model, as there could be discrepancies in signaling behavior that limit the translatability to human myocyte predictions.

Reviewer #2 (Public Review):

In this study, Hernandez-Hernandez et al developed a gender-dependent mathematical model of arterial myocytes based on a previous model and new experimental data. The ionic currents of the model and its sex difference were formulated based on patch-clamp experimental data, and the model properties were compared with single-cell and tissue scale experimental results. This is a study that is of importance for the modeling field as well as for experimental physiology.

Reviewer #3 (Public Review):

Summary:<br /> This hybrid experimental/computational study by Hernandez-Hernandez sheds new light on sex-specific differences between male and female arterial myocytes from resistance arteries. The authors conduct careful experiments in isolated myocytes from male and female mice to obtain the data needed to parameterize sex-specific models of two important ionic currents (i.e., those mediated by CaV1.2 and KV2.1). Available experimental data suggest that KV1.5 channel currents from male and female myocytes are similar, but simulations conducted in the novel Hernandez-Hernandez sex-specific models provide a more nuanced view. This gives rise to the first of the authors' three key scientific claims: (1) In males, KV1.5 is the dominant current regulating membrane potential; whereas, in females, KV2.1 plays a primary role in voltage regulation. They further show that this (2) the latter distinction drives drive sex-specific differences in intracellular Ca2+ and cellular excitability. Finally, working with one-dimensional models comprising several copies of the male/female myocyte models linked by resistive junctions, they use simulations to (3) predict that the sensitivity of arterial smooth muscle to Ca2+ channel-blocking drugs commonly used to treat hypertension is heightened in female compared to male cells.

Strengths:<br /> • The Methodology is described in exquisite detail in straightforward language that will be easy to understand for most if not all peer groups working in computational physiology. The authors have deployed standard protocols (e.g., parameter fitting as described by Kernik et al., sensitivity analysis as described by Sobie et al.) and appropriate brief explanations of these techniques are provided. The manoeuvre used to represent stochastic effects on voltage dynamics is particularly clever and something I have not personally encountered before. Collectively, these strengthen the credibility of the model and greatly enrich the manuscript.

• Broadly speaking, the Results section describes findings that robustly support the three key scientific claims outlined in my summary. While there is certainly room for further discussion of some nuanced points as outlined below, it is evident these experiments were carefully designed and carried out with care and intentionality. In the present version of the manuscript, there are a few figures in which experimental data is shown side-by-side with outputs from the corresponding models. These are an excellent illustration of the power of the authors' novel sex-specific computational simulation platform. I think these figures will benefit from some modest additional quantitative analysis to substantiate the similarities between experimental and computational data, but there is already clear evidence of a good match.

Areas for Improvement:<br /> • The authors used experimental data from a prior publication to calibrate their model of the BKCa current. As indicated in the manuscript, these data are for channel activity measured in a heterologous expression system (Xenopus oocytes). A similar principle applies to other major ion channels/pumps/etc. Is it possible there might be relevant sex-specific differences in these players as well? In the context of the present work, this feels like an important potential caveat to highlight, in case male/female differences in the activity of BKCa or other currents might influence model-predicted differences (e.g., the relative importance of KV1.5 and KV2.1). This should be discussed, and, if possible, related to the elegant sensitivity analysis presented in Fig. 5C (which shows, for example, that the models are relatively insensitive to variation in GBK).

• The authors state that their model can be expanded to 2D/3D applications, "transitioning seamlessly from single-cell to tissue-level simulations". I would like to see more discussion of this. For example, given the modest complexity of the cell-scale model, how considerable would the computational burden be to implement a large network model of a subset of the human female or male arterial system? Are there sex-specific differences in vessel and/or network macro-structure that would need to be considered? How would this influence feasibility? Rather than a 1D cable as implemented here, I imagine a multi-scale implementation would involve the representation of myocytes wrapped around vessels. How would the behaviour of such a system differ from the authors' presented work using a 1D representation of 100 myocytes coupled end-to-end? Could these differences partially explain why the traces in Fig. 8D are smoother than those in Fig. 8C? From my standpoint, discussing these points would enrich the paper.

• The nifedipine data presented in Fig. 9 are quite compelling, and a nice demonstration of the potential power of the new models. How does this relate to what is known about the clinical male/female responses to nifedipine? Are there sex differences in drug efficacy?

Reviewer #1 (Public Review):

The authors previously showed in cell culture that Su(H), the transcription factor mediating Notch pathway activity, was phosphorylated on S269 and they found that a phospho-deficient Su(H) allele behaves as a moderate gain of Notch activity in flies, notably during blood cell development. Since a downregulation of Notch signaling was proposed to be important for the production of a specialized blood cell types (lamellocytes) in response to wasp parasitism, the authors hypothesized that Su(H) phosphorylation might be involved in this cellular immune response.

Consistent with their hypothesis, the authors show that Su(H)S269A knock-in flies display a reduced response to wasp parasitism and that Su(H) is phosphorylated upon infestation. Using in vitro kinase assays and a genetic screen, they identify the PKCa family member Pkc53E as the putative kinase involved in Su(H) phosphorylation and they show that Pkc53E can bind Su(H). They further show that Pkc53E deficit or its knock-down in larval blood cells results in similar blood cell phenotypes as Su(H)S269A, including a reduced response to wasp parasitism, and their epistatic analyses indicate that Pkc53E acts upstream of Su(H).

Strengths<br /> The manuscript is well presented and the experiments are sound, with a good combination of genetic and biochemical approaches and several clear phenotypes which back the main conclusions. Notably Su(H)S269A mutation or Pkc53E deficiency strongly reduces lamellocyte production and the epistatic data are convincing.

Weaknesses<br /> The phenotypic analysis of larval blood cells remains rather superficial. Looking at melanized cells is a crude surrogate to quantify crystal cell numbers as it is biased toward sessile cells (with specific location) and does not bring information concerning the percentage of blood cells differentiated along this lineage.

In Su(H)S269A knock-in or Pkc53E zygotic mutants, the increase in crystal cells in uninfected conditions and the decreased capacity to induce lamellocytes following infection could have many origins which are not investigated. For instance, premature blood cell differentiation could promote crystal cell differentiation and reduce the pool of lamellocytes progenitors. These mutations could also affect the development and function of the posterior signaling center in the lymph gland, which plays a key role in lamellocyte induction. Similarly, the mild decrease on resistance to wasp infestation (Fig. 2A) could reflect a constitutive reduction in blood cell numbers in Su(H)S269A larvae rather than a defective down-regulation of Notch activity.<br /> Whereas the authors also present targeted-knock down/inhibition of Pkc53E suggesting that this enzyme is required in blood cells to control crystal cell fate (Fig. 6), it is somehow misleading to use lz-GAL4 as a driver in the lymph gland and hml-GAL4 in circulating hemocytes as these two drivers do not target the same blood cell populations/steps in the crystal cell development process.

In addition, the authors do not present evidence that Pkc55E function (and Su(H) phosphorylation) is required specifically in blood cells to promote lamellocyte production in response to infestation.

Finally, the conclusion that Pkc53E is (directly) responsible for Su(H) phosophorylation needs to be strengthened. Most importantly, the authors do not demonstrate that Pkc53E is required for Su(H) phosphorylation in vivo (i.e. that Su(H) is not phosphorylated in the absence of Pkc53E following infestation). In addition, the in vitro kinase assays with bacterially purified Pkc53E (in the presence of PMA or using an activated variant of Pkc53E) only reveal a weak activity on a Su(H) peptide encompassing S269 (Fig. 4). Moreover, while the authors show a coIP between an overexpressed Pkc53E and endogenous Su(H) (Fig. 7) (in the absence of infestation), it has recently been reported that Pkc53E is a cytoplasmic protein in the eye (Shieh et al. 2023), calling for a direct assessment of Pkc53E expression and localization in larval blood cells under normal conditions and upon infestation. Furthermore, the effect of the PKCa agonist PMA on Su(H)-induced reporter gene expression in cell culture and crystal cell number in vivo is somehow consistent with the authors hypothesis, but some controls are missing (notably western blots to show that PMA/Staurosporine treatment does not affect Su(H)-VP16 level) and it is unclear why STAU treatment alone promotes Su(H)-VP16 activity (in their previous reports, the authors found no difference between Su(H)S269A-VP16 and Su(H)-VP16) or why PMA treatment still has a strong impact on crystal cell number in Su(H)S269A larvae.

Reviewer #2 (Public Review):

Summary: The current draft by Deischel et.al., entitled "Inhibition of Notch activity by phosphorylation of CSL in response to parasitization in Drosophila" decribes the role of Pkc53E in the phosphorylation of Su(H) to downregulate its transcriptional activity to mount a successful immune response upon parasitic wasp-infection. Overall, I find the study interesting and relevant especially the identification of Pkc53E in phosphorylation of Su(H) is very nice. However, I have a number of concerns with the manuscript which are central to the idea that link the phosphorylation of Su(H) via Pkc53E to implying its modulation of Notch activity. I enlist them one by one subsequently.

Strengths: I find the study interesting and relevant especially because of the following:<br /> 1. The identification of Pkc53E in phosphorylation of Su(H) is very interesting.<br /> 2. The role of this interaction in modulating Notch signaling and thereafter its requirement in mounting a strong immune response to wasp infection is also another strong highlight of this study.

Weaknesses:1. Epistatic interaction with Notch is needed: In the entire draft, the authors claim Pkc53E role in the phosphorylation of Su(H) is down-stream of notch activity. Given the paper title also invokes Notch, I would suggest authors show this in a direct epistatic interaction using a Notch condition. If loss of Notch function makes many more lamellocytes and GOF makes less, then would modulating Pkc53E (and SuH)) in this manifest any change? In homeostasis as well, given gain of Notch function leads to increased crystal cells the same genetic combinations in homeostasis will be nice to see.<br /> While I understand that Su(H) functions downstream of Notch, but it is now increasingly evident that Su(H) also functions independent of Notch. An epistatic relationship between Notch and Pkc will clarify if this phosphorylation event of Su(H) via Pkc is part of the canonical interaction being proposed in the manuscript and not a non-canoncial/Notch pathway independent role of Su(H).

This is important, as I worry that in the current state, while the data are all discussed inlight of Notch activity, any direct data to show this affirmatively is missing. In our hands we do find Notch independent Su(H) function in immune cells, hence this is a suggestion that stems from our own personal experience.

2. Temporal regulation of Notch activity in response to wasp-infection and its overlapping dynamics of Su(H) phosphorylation via Pkc is needed: First, I suggest the authors to show how Notch activity post infection in a time course dependent manner is altered. A RT-PCR profile of Notch target genes in hemocytes from infected animals at 6, 12, 24, 48 HPI, to gauge an understanding of dynamics in Notch activity will set the tone for when and how it is being modulated. In parallel, this response in phospho mutant of Su(H) will be good to see and will support the requirement for phosphorylation of Su(H) to manifest a strong immune response. Second, is the dynamics of phosphorylation in a time course experiment is missing. While the increased phosphorylation of Su(H) in response to wasp-infestation shown in Fig.2B is using whole animal, this implies a global down-regulation of Su(H)/Notch activity. The authors need to show this response specifically in immune cells. The reader is left to the assumption that this is also true in immune cells. Given the authors have a good antibody, characterizing this same in circulating immune cells in response to infection will be needed. A time course of the phosphorylation state at 6, 12, 24, 48 HPI, to guage an understanding of this dynamics is needed. The authors suggest, this mechanism may be a quick way to down-regulate Notch, hence a side by side comparison of the dynamics of Notch down-regulation (such as by doing RT-PCR of Notch target genes following different time point post infection) alongside the levels of pS269 will strengthen the central point being proposed. Last, in Fig7. the authors show Co-immuno-precipitation of Pkc53EHA with Su(H)gwt-mCh 994 protein from Hml-gal4 hemocytes. I understand this is in homeostasis but since this interaction is proposed to be sensitive to infection, then a Co-IP of the two in immune cells, upon infection should be incorporated to strengthen their point.

3. In Fig 5B, the authors show the change in crystal cell numbers as read out of PMA induced activation of Pkc53E and subsequent inhibition of Su(H) transcriptional activity, I would suggest the authors use more direct measures of this read out. RT-PCR of Su(H) target genes, in circulating immune cells, will strengthen this point. Formation of crystal cells is not just limited to Notch, I am not convinced that this treatment or the conditions have other affect on immune cells, such as any impact on Hif expression may also lead to lowering of CC numbers. Hence, the authors need to strengthen this point by showing that effects are direct to Notch and Su(H) and not non-specific to any other pathway also shown to be important for CC development.

4. In addition to the above mentioned points, the data needs to be strengthened to further support the main conclusions of the manuscript. I would suggest the authors present the infection response with details on the timing of the immune response. Characterization of the immune responses at respective time points (as above or at least 24 and 48 HPI, as norms in the field) will be important. Also, any change in overall cell numbers, other immune cells, plasmatocytes or CC post infection is missing and is needed to present the specificity of the impact. The addition of these will present the data with more rigor in their analysis.

5. Finally, what is the view of the authors on what leads to activation of Pkc53E, any upstream input is not presented. It will be good to see if wasp infection leads to increased Pkc53 kinase activity.

Overall, I think the findings in the current state are interesting and fill an important gap, but the authors will need to strengthen the point with more detailed analysis that includes generating new data and also presenting the current data with more rigor in their approach. The data have to showcase the relationship with Notch pathway modulation upon phosphorylation of CSL in a much more comprehensive way, both in homeostasis and in response to infection which is entirely missing in the current draft.

Reviewer #3 (Public Review):

Diechsel et al. provide important and valuable insights into how Notch signalling is shut down in response to parasitic wasp infestation in order to suppress crystal cell fate and favour lamellocyte production. The study shows that CSL transcription factor Su(H) is phosphorylated at S269A in response to parasitic wasp infestation and this inhibitory phosphorylation is critical for shutting down Notch. The authors go on to perform a screen for kinases responsible for this phosphorylation and have identified Pkc53E as the specific kinase acting on Su(H) at S269A. Using analysis of mutants, RNAi and biochemistry-based approaches the authors convincingly show how Pkc53E-Su(H) interaction is critical for remodelling hematopoiesis upon wasp challenge. The data presented supports the overall conclusions made by the authors. There are a few points below that need to be addressed by the authors to strengthen the conclusions:

1) The authors should check melanized crystal cells in Su(H)gwt and Su(H)S269A in presence of PMA and Staurosporine?<br /> 2) Data for number of dead pupae, flies eclosed, wasps emerged post infestation should be monitored for the following genotypes and should be included: Pkc53EΔ28, Su(H)S269A, Pkc53EΔ28 Su(H)S269A, Su(H)S269D, Su(H)S269D Pkc53EΔ28<br /> 3) The exact molecular trigger for activation of Pkc53E upon wasp infestation is not clear.<br /> 4) The authors should check if activating ROS alone or induction of Calcium pulses/DUOX activation can mimic this condition and can trigger activation of Pkc53E and thereby cause phosphorylation of Su(H) at S269<br /> 5) Does Pkc53E get activated during sterile inflammation?

Joint Public Review:

The study has many limitations which need to be addressed and there is a lack of functional explanation of carriage. These limitations are: a) the lack of inclusion of non-Black patients; and b) the lack of appropriate explanation if results are false-positive since APOL1 provides risk for chronic renal disease (CRD) and patients with CRD are predisposed to sepsis. Sepsis occurred in 565 Black subjects, of whom 105 (29% ) had APOL1 high-risk genotype and 460 had-low risk genotype. Importantly, the risk for sepsis associated with APOL1 HR variants was no longer significant after adjusting for subjects pre-existing severe renal disease or after excluding these subjects. Thus, the susceptibility pathway seems to be: APOL1 variants > CKD > sepsis diathesis.

Reviewer #1 (Public Review):

In this study, Fang H et al. describe a potential pathway, ITGB4-TNFAIP2-IQGAP1-Rac1, that may involve in the drug resistance in triple negative breast cancer (TNBC). Mechanistically, it was demonstrated that TNFAIP2 bind with IQGAP1 and ITGB4 activating Rac1 and the following drug resistance. The present study focused on breast cancer cell lines with supporting data from mouse model and patient breast cancer tissues. The study is interesting. The experiments were well controlled and carefully carried out. The conclusion is supported by strong evidence provided in the manuscript. The authors may want to discuss the link between ITGB4 and Rac 1, between IQGAP1 and Rac1, and between TNFAIP2 and Rac1 as compared with the current results obtained. This is important considering some recent publications in this area (Cancer Sci 2021, J Biol Chem 2008, Cancer Res 2023). In addition, some key points need to be addressed in order to support their conclusion in full.

Reviewer #2 (Public Review):

Breast cancer is the most common malignant tumor in women. One of subtypes in breast cancer is so called triple-negative breast cancer (TNBC), which represents the most difficult subtype to treat and cure in the clinic. Chemotherapy drugs including epirubicin and cisplatin are widely used for TNBC treatment. However, drug resistance remains as a challenge in the clinic. The authors uncovered a molecular pathway involved in chemotherapy drug resistance, and molecular players in this pathway represent as potential drug targets to overcome drug resistance. The experiments are well designed and the conclusions drawn mostly were supported by the data. The findings have potential to be translated into the clinic.

Reviewer #3 (Public Review):

A summary of what the authors were trying to achieve:<br /> - TNFAIP2 promotes TNBC drug resistance and DNA damage repair.<br /> - Mechanistically, TNFAIP2 interacts with IQGAP1 and Integrin β4 to mediate RAC1 activation and thus promotes TNBC drug resistance.<br /> - Clinically, TNFAIP2 expression levels positively correlated with ITGB4 in TNBC tissues.<br /> - ITGB4 and TNFAIP2 might serve as promising therapeutic targets for TNBC.<br /> -An account of the major strengths and weaknesses of the methods and results.<br /> The authors performed numerous rescue experiments in vitro to confirm the relationship among ITGB4, TNFAIP2, IQGAP1 and Rac1. However, clinical relevance is somehow limited. Additional experiments are needed to demonstrate the above conclusions in clinical samples.<br /> -An appraisal of whether the authors achieved their aims, and whether the results support their conclusions.<br /> To most extent, the authors achieved their aims, and the results demonstrate their conclusions "TNFAIP2 interacts with IQGAP1 and ITGB4. ITGB4 promotes TNBC drug resistance via the TNFAIP2/IQGAP1/RAC1 axis by promoting DNA damage repair".<br /> -A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community.<br /> Drug resistance is always a challenge for TNBC treatment. This paper found that TNFAIP2 interacts with IQGAP1 and ITGB4 to activate Rac1, thus conferring DNA chemo-resistance to TNBC cells. In addition, positive correlation between the expression of TNFAIP2 and ITGB4 in TNBC tissues were presented. This paper suggests that the ITGB4/TNFAIP2/IQGAP1/Rac1 axis provides potential therapeutic targets to overcome chemo-resistance (DNA damage drugs) in fighting with TNBC.

Additional context to help readers interpret or understand the significance of the work:<br /> This work reported a new mechanism related to TNBC chemo-resistance, which mainly depends on ordered interactions among ITGB4/TNFAIP2/IQGAP1/Rac1 and the following activation of pathways. Thus micro-peptide targeting technique, which is widely used to develop targeted drugs for protein-protein interactions, could show extraordinary potentials and application significance.<br /> At present, cell penetrating peptide, a type of micro-peptide targeting technique, makes functional micro-peptides more stable by cross-linking some amino acid side chains. In recent years, it has been found that binding peptides can not only stabilize peptides, make them easier to enter cells, but also not easy to be hydrolyzed by proteases. At the same time, they have high affinity for targets and can target protein interactions, thus becoming a new way to develop protein interaction targeting inhibitors. To make it easier to enter cells, cell-penetrating peptides can be used in combination, such as HIV TAT. Cell-penetrating peptides can carry a variety of biologically active substances into the cell, is a good targeting drug carrier, with low toxicity, not limited by cell type, into the cell speed and high transduction efficiency. Based on the mechanism reported here, researchers can explore new micro-peptides targeting the interactions between ITGB4 and TNFAIP2 or TNFAIP2 and IQGAP1 to enhance the sensitivity of TNBC cells to drugs by cell-penetrating peptide technology.

Reviewer #1 (Public Review):

Proposed significance: Targeted therapy in general has miraculous results.<br /> Good and detailed study of molecular characteristics and microenvironment of tumor of PCCs .However molecular classification system based on limited number of cases is not acceptable.<br /> Early diagnosis is of utmost importance in patient care and the next important is classification of tumor for treatment purposes.<br /> Further research is needed to develop Molecular signature of tumor types . This will help in targeted therapy and precision medicine.

Strength: Molecular characterisation of tumor

Weakness: The sample size is very small from a statistical point of view to derive a conclusion. Only Observations can be recorded<br /> Transcriptome profiles of 11 tumor tissues were studied but they belong to the same 5 patients.

Validation of tumor tissue: comparison is made with adjacent normal tissue (n=5 )<br /> Chromogranin IHC marker is used for identifying tumor cells. However, chromogranin marker positivity is also seen in normal adrenal medulla /chromaffin cells.<br /> Any better evidence of Validation of tumor tissue?

Tumor microenvironment:<br /> CD8+T cells: it is mentioned in the article that there is lack of CD8+ Tcells in both types of PCC, (Page 5, line 16)

However Figures 7 D, E and F show presence of CD8+T cells. Needs clarification or quantification.

Tumor heterogeneity : Page 7 Line 5<br /> PASS system is used by authors for predicting malignant potential and tumor heterogeneity.<br /> Molecular methods need to be used for evaluating tumor heterogeneity rather than histomorphology.

Ground of comparision is not valid. PASS system is based on histomorphology and present study/attempt at classification is based on molecular studies. So they cannot be compared .

Page 5 ,Line 18: HLA downregulation is observation and its regulation by RET is a possibility. Its involvement in tumor progression needs solid proof. So targeting kinase pathway for therapy is only a possibility.

Reviewer #2 (Public Review):

Pheochromocytoma (PCC), a rare neuroendocrine tumor, is currently considered malignant, but non-surgical treatment options are very limited and there is an urgent need for more basic research to support the development of new therapeutic approaches. In the present work, the authors described the intra- and inter-tumor heterogeneity by performing scRNA-seq on tumor samples from five patients with PCC, and evaluated the corresponding PASS scores.

Strengths: The tumor microenvironment of PCC was characterized and potential molecular classification criteria based on single-cell transcriptomics were proposed, offering new theoretical possibilities for the treatment of PCC. The article is logically written and the results are clearly presented.

Weaknesses: I still have concerns about some of the article's content. My main concerns are: In this study, the authors seem to have demonstrated the inaccuracy of a subjective score (PASS) by another objective means (scRNA-seq). In fact, the multiparametric scoring systems such as PASS are no longer endorsed in the 2022 WHO guidelines. The PASS scoring system does not have a high positive predictive value for risk stratification of PCC metastasis, but "rule-out" of metastasis risk with a PASS score of <4 seems to be fairly reliable. Could the authors please explain why the PASS scores were chosen rather than the GAPP, m-GAPP, or COPPS scoring systems? If possible, please try to emphasize the importance and necessity of using the PASS scoring system, either by replacing it with a more acceptable scoring system or by deleting the relevant part, which does not seem to be very relevant to the subject of the article.

Moreover, I noted the following statement in the text "There are no studies reporting the composition of immune cells in PCCs. The few published studies investigating the immune microenvironment of PCCs have been limited to the expression of PDL1 at the histological level and to assessment of the tumor mutation burden (TMB) at the genomic level, and these results only seem to suggest that PCCs are immune-cold (Bratslavsky et al, 2019; Guo et al, 2019; Pinato et al, 2017)." This statement is very wrong. The reason for this error may be that the authors did not adequately search and read the relevant literature. I noticed that almost all references in this paper are dated 2021 and earlier, which is surprising. Please update the references cited in this paper in a comprehensive and detailed manner; referring to literature published too early may lead to inadequate discussion or even one-sided or incorrect conclusions and conjectures.

For example, the text statement "Combined with previously reported negative regulatory effects of kinases (such as RET, ALK, and MEK) on HLA-I expression on tumor cells (Brea et al., 2016; Oh et al., 2019), we speculate that the possible reason for inability in recruiting CD8+ T cells of kinase-type PCCs is the downregulation of HLA-I in tumor cells regulated by RET, while the mechanism of immune escape in metabolism-type PCCs (with antigen presentation ability) needs to be further explored. Our results also indicate that the application of immunotherapy to metabolism-type PCCs is likely unsuitable, while kinase-type PCCs may have the potential of combined therapy with kinase inhibitors and immunotherapy." is rather one-sided; in fact, the presence of immune escape in PCC, as the malignancy with the lowest tumor mutation compliance, has been well characterized, and the low number of infiltrating T cells in tumor tissue may be influenced by a variety of factors, such as the release of catecholamines, the expression of inhibitory receptors on the surface of T cells, and so on, although genetic mutation still plays the most crucial role. The Discussion section also has a lot of information that needs to be updated or corrected and expanded, so please rewrite the above section with sufficiently updated references.

Below I have listed some references for the authors to read:<br /> Tufton N, Hearnden RJ, Berney DM, et al. The immune cell infiltrate in the tumour microenvironment of phaeochromocytomas and paragangliomas. Endocr Relat Cancer. 2022;29(11):589-598. Published 2022 Sep 19. doi:10.1530/ERC-22-0020<br /> Jin B, Han W, Guo J, et al. Initial characterization of immune microenvironment in pheochromocytoma and paraganglioma. Front Genet. 2022;13:1022131. Published 2022 Dec 7. doi:10.3389/fgene.2022.1022131<br /> Celada L, Cubiella T, San-Juan-Guardado J, et al. Pseudohypoxia in paraganglioma and pheochromocytoma is associated with an immunosuppressive phenotype. J Pathol. 2023;259(1):103-114. doi:10.1002/path.6026<br /> Calsina B, Piñeiro-Yáñez E, Martínez-Montes ÁM, et al. Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma. Nat Commun. 2023;14(1):1122. Published 2023 Feb 28. doi:10.1038/s41467-023-36769-6

Reviewer #3 (Public Review):

The main findings of this study are as follows: (1) The authors defined "metabolism-type" and "kinase-type" in unclassified sporadic PCC patients through the single-cell transcriptomics-based differentially expressed genes and functional enrichment analyses. (2) They identified the limitation of Pheochromocytoma of the Adrenal gland Scaled Score (PASS) system and suggested the combination of molecular diagnostic methods like scRNA-seq with pathological tools like PASS in aiding the clinical evaluation of PCCs. (3) Analysis of the PCC microenvironment revealed a lack of immune cell infiltration in both metabolism-type and kinase-type PCCs, while only the kinase-type PCC patient exhibited the low expression of HLA-Ⅰ that potentially regulated by RET, providing clues for the combined therapy with kinase inhibitors and immunotherapy in kinase-type PCC patients.

The main strength of this manuscript is that it involves scRNA-seq analysis of an extremely rare tumor type-PCCs, which presents a single-cell transcriptomics-based molecular classification and microenvironment characterization of PCCs and further provides clues for potential therapeutic strategies to treat PCCs. The authors also validated the scRNA-seq analysis results (such as the expression levels of marker genes and the distribution of immune cells in the PCC microenvironment) with immunocytochemistry and multispectral immunofluorescent staining. In summary, the findings in this manuscript are quite interesting and significant, which will potentially be valuable for the molecular classification of PCCs.

Reviewer #1 (Public Review):

This manuscript proposes a complex unclear model involving Ca2+ signaling in inflammasome activation. The experimental approaches used to study the calcium dynamics are problematic and the results shown are of inadequate quality. The major claims of this manuscript are not adequately substantiated.

Major concerns:

1. The analysis of lysosomal Ca2+release is being carried out after many hours of treatment. Such evidence is not meaningful to claim that PA activates Ca2+ efflux from lysosome and even if this phenomenon was robust, it is not doubtful that such kinetics are meaningful for the regulation of inflammasome activation. Furthermore, the evidence for lysosomal Ca2+ release is indirect and relies on a convoluted process that doesn't make any conceptual sense to me. In addition to these major shortcomings, the indirect evidence of perilysosomal Ca2+ elevation is also of very poor quality and from the standpoint of my expertise in calcium signaling, the data are incredulous. The use of GCaMP3-ML1, *transiently transfected* into BMDMs is highly problematic. The efficiency of transfection in BMDMs is always extremely low and overexpression of the sensor in a few rare cells can lead to erroneous observations. The overexpression also results in gross mislocalization of such membrane-bound sensors. The accumulation of GCaMP3-ML1 in the ER of these cells would prevent any credible measurements of perilysosomal Ca2+ signals. A meaningful investigation of this process in primary macrophages requires the generation of a mouse line wherein the sensor is expressed at low levels in myeloid cells, and shown to be localized almost exclusively in the lysosomal membrane. The mechanistic framework built around these major conceptual and technical flaws is not especially meaningful and since these are foundational results, I cannot take the main claims of this study seriously.

2. The cytosolic Ca2+ imaging shown in Figure 1C doesn't make any sense. It looks like a snapshot of basal Ca2+ many hours after PA treatment - calcium elevations are highly dynamic. Snapshot measurements are not helpful and analyses of Calcium dynamics requires a recording over a certain timespan. Unfortunately, this technical approach has been used throughout the manuscript. Also, BAPTA-AM abrogates IL-1b secretion because IL-1b transcription is Ca2+ dependent - the result shown in figure 1D does not shed light on anything to do with inflammasome activation and it is misleading to suggest that.

3. Trpm2-/- macrophages are known to be hyporesponsive to inflammatory stimuli - the reduced secretion of IL-1b by these macrophages is not novel. From a mechanistic perspective, this study does not add much to that observation and the proposed role of TRPM2 as a lysosomal Ca2+ release channel is not substantiated by good quality Ca2+ imaging data (see point 3 above). Furthermore, the study assumes that TRPM2 is a lysosomal ion channel. One paper reported TRPM2 in the lysosomes but this is a controversial claim, with no replication or further development in the last 14 years. This core assumption can be highly misleading to readers unfamiliar with TRPM2 biology and it is necessary to present credible evidence that TRPM2 is functional in the lysosomal membrane of macrophages. Ideally, this line of investigation should rest on robust demonstration of TRPM2 currents in patch-clamp electrophysiology of lysosomes. If this is not technically feasible for the authors, they should at least investigate TRPM2 localization on lysosomal membranes of macrophages.

4. Apigenin and Quercetin are highly non-specific and their effects cannot be attributed to CD38 inhibition alone. Such conclusions need strong loss of function studies using genetic knockouts of CD38 - or at least siRNA knockdown. Importantly, if indeed TRPM2 is being activated downstream of CD38, this should be easily evident in whole cell patch clamp electrophysiology. TRPM2 currents can be resolved using this technique and authors have Trpm2-/- cells for proper controls. Authors attempted these experiments but the results are of very poor quality. If the TRPM2 current is being activated through ADPR generated by CD38 (in response to PA stimulation), then it is very odd that authors need to include 200 uM cADPR to see TRPM2 current (Fig. 3A). Oddly, even these data cast great doubt on the technical quality of the electrophysiology experiments. Even with such high concentrations of cADPr, the TRPM2 current is tiny and Trpm2-/- controls are missing. The current-voltage relationship is not shown, and I feel that the results are merely reporting leak currents seen in measurements with substandard seals. Also 20 uM ACA is not a selective inhibitor of TRPM2 - relying on ACA as the conclusive diagnostic is problematic.

5. TRPM2 is expressed in many different cell lines. The broad metabolic differences observed by the authors in the Trpm2-/- mice cannot be attributed to macrophage-mediated inflammation. Such a conclusion requires the study of mice wherein Trpm2 is deleted selectively in macrophages or at least in the cells of the myeloid lineage.

6. The ER-Lysosome Ca2+ refilling experiments rely on transient transfection of organelle-targeted sensors into BMDMs. See point #1 to understand why I find this approach to be highly problematic. Furthermore, the data procured are also not convincing and lack critical controls (localization of sensors has not been demonstrated and their response to acute mobilization of Ca2+ has not been shown to inspire any confidence in these results).

7. Authors claim that SCOE is coupled to K+ efflux. But there is no credible evidence that SOCE is activated in PA stimulated macrophages. The data shown in Fig 4 supp 1 do not investigate SOCE in a reliable manner - the conclusion is again based on snapshot measurements and crude non-selective inhibitors. The correct way to evaluate SOCE is to record cytosolic Ca2+ elevations over a period of time in absence and presence of extracellular Ca2+. However, even such recordings can be unreliable since the phenomenon is being investigated hours after PA stimulation. So, the only definitive way to demonstrate that Orai channels are indeed active during this process is through patch clamp electrophysiology of PA stimulated cells.

Reviewer #2 (Public Review):

In this manuscript by Kang et. al., the authors investigated the mechanisms of K+-efflux-coupled SOCE in NLRP3 inflammasome activation by LP（LPS+PA, and identified an essential role of TRPM2-mediated lysosomal Ca2+ release and subsequent IP3Rs-mediated ER Ca2+ release and store depletion in the process. K+ efflux is shown to be mediated by a Ca2+-activated K+ channel (KCa3.1). LP-induced cytosolic Ca2+ elevation also induced a delayed activation of ASK1 and JNK, leading to ASC oligomerization and NLRP3 inflammasome activation. Overall, this is an interesting and comprehensive study that has identified several novel molecular players in metabolic inflammation. The manuscript can benefit if the following concerns could be addressed:

1. The expression of TRPM2 in the lysosomes of macrophages needs to be more definitively established. For instance, the cADPR-induced TRPM2 currents should be abolished in the TRPM2 KO macrophages. Can you show the lysosomal expression of TRPM2, either with an antibody if available or with a fluorescently-tagged TRPM2 overexpression construct?

2. Can you use your TRPM2 inhibitor ACA to pharmacologically phenocopy some results, e.g., about [Ca2+]ER, [Ca2+]LY, and [Ca2+]i from the TRPM2 knockout?

3. In Fig. S4A, bathing the cells in zero Ca2+ for three hours might not be ideal. Can you use a SOCE inhibitor, e.g, YM-58483, to make the point?

4. In Fig. 1A, you need a positive control, e.g., ionomycin, to show that the GPN response was selectively reduced upon LP treatment.

Reviewer #1 (Public Review):

Summary:<br /> The authors of this manuscript characterize new anion conducting that is more red-shifted in its spectrum than prior variants called MsACR1. An additional mutant variant of MsACR1 that is renamed raACR has a 20 nm red-shifted spectral response with faster kinetics. Due to the spectral shift of these variants, the authors proposed that it is possible to inhibit the expression of MsACR1 and raACR with lights at 635 nm in vivo and in vitro. The authors were able to demonstrate some inhibition in vitro and in vivo with 635 nm light. Overall the new variants with unique properties should be able to suppress neuronal activities with red-shifted light stimulation.

Strengths:<br /> The authors were able to identify a new class of anion conducting channelrhodopsin and have variants that respond strongly to lights with wavelength >550 nm. The authors were able to demonstrate this variant, MsACR1, can alter behavior in vivo with 635 nm light. The second major strength of the study is the development of a red-shifted mutant of MsACR1 that has faster kinetics and 20 nm red-shifted from a single mutation.

Weaknesses:<br /> The red-shifted raACR appears to work much less efficiently than MsACR1 even with 635 nm light illumination both in vivo (Figure 4) and in vitro (Figure 3E) despite the 20 nm red-shift. This is inconsistent with the benefits and effects of red-shifting the spectrum in raACR. This usually would suggest raACR either has a lower conductance than MsACR1 or that the membrane/overall expression of raACR is much weaker than MsACR1. Neither of these is measured in the current manuscript.

There are limited comparisons to existing variants of ACRs under the same conditions in the manuscript overall. There should be more parallel comparison with gtACR1, ZipACR, and RubyACR in identical conditions in cultured cell lines, cultured neurons, and in vivo. This should be in terms of overall performance, efficiency, and expression in identical conditions. Without this information, it is unclear whether the effects at 635 nm are due to the expression level which can compensate for the spectral shift.

There should be more raw traces from the recordings of the different variants in response to short pulse stimulation and long pulse stimulation to different wavelengths. It is difficult to judge what the response would be like when these types of information are missing.

Despite being able to activate the channelrhodopsin with 635 nm light, the main utility of the variant should be transcranial stimulation which was not demonstrated here.

Figure 3B is not clearly annotated and is difficult to match the explanation in the figure legend to the figure. The action potential spikings of neurons expressing raACR in this panel are inhibited as strongly as MsACR1.

For many characterizations, the number of 'n's are quite low (3-7).

Reviewer #2 (Public Review):

Summary:<br /> The authors identified a new chloride-conducting Channelrhodopsin (MsACR1) that can be activated at low light intensities and within the red part of the visible spectrum. Additional engineering of MsACR1 yielded a variant (raACR1) with increased current amplitudes, accelerated kinetics, and a 20nm red-shifted peak excitation wavelength. Stimulation of MsACR1 and raACR1 expressing neurons with 635nm in mice's primary motor cortices inhibited the animals' locomotion.

Strengths:<br /> The in vitro characterization of the newly identified ACRs is very detailed and confirms the biophysical properties as described by the authors. Notably, the ACRs are very light sensitive and allow for efficient in vitro inhibition of neurons in the nano Watt/mm^2 range. These new ACRs give neuroscientists and cell biologists a new tool to control chloride flux over biological membranes with high temporal and spatial precision. The red-shifted excitation peaks of these ACRs could allow for multiplexed application with blue-light excited optogenetic tools such as cation-conducting channelrhodopsins or green-fluorescent calcium indicators such as GCaMP.

Weaknesses:<br /> The in-vivo characterization of MsACR1 and raACR1 lacks critical control experiments and is, therefore, too preliminary. The experimental conditions differ fundamentally between in vitro and in vivo characterizations. For example, chloride gradients differ within neurons which can weaken inhibition or even cause excitation at synapses, as pointed out by the authors. Notably, the patch pipettes for the in vitro characterization contained low chloride concentrations that might not reflect possible conditions found in the in vivo preparations, i.e., increasing chloride gradients from dendrites to synapses.

Interestingly, the authors used soma-targeted (st) MsACR1 and raACR1 for some of their in vitro characterization yielding more efficient inhibition and reduction of co-incidental "on-set" spiking. Still, the authors do not seem to have utilized st-variants in vivo.

Most importantly, critical in vivo control experiments, such as negative controls like GFP or positive controls like NpHR, are missing. These controls would exclude potential behavioral effects due to experimental artifacts. Moreover, in vivo electrophysiology could have confirmed whether targeted neurons were inhibited under optogenetic stimulations.

Some of these concerns stem from the fact that the pulsed raACR stimulation at 635 nm at 10Hz (Fig. 3E) was far less efficient compared to MsACR1, yet the in vivo comparison yielded very similar results (Fig. 4D).

Also, the cortex is highly heterogeneous and comprises excitatory and inhibitory neurons. Using the synapsin promoter, the viral expression paradigm could target both types and cause differential effects, which has not been investigated further, for example, by immunohistochemistry. An alternative expression system, for example, under VGLUT1 control, could have mitigated some of these concerns.

Furthermore, the authors applied different light intensities, wavelengths, and stimulation frequencies during the in vitro characterization, causing varying spike inhibition efficiencies. The in vivo characterization is notably lacking this type of control. Thus, it is unclear why the 635nm, 2s at 20Hz every 5s stimulation protocol, which has no equivalent in the in vitro characterization, was chosen.

In summary, the in vivo experiments did not confirm whether the observed inhibition of mouse locomotion occurred due to the inhibition of neurons or experimental artifacts.

In addition, the author's main claim of more efficient neuronal inhibition would require them to threshold MsACR1 and raACR1 against alternative methods such as the red-shifted NpHR variant Jaws or other ACRs to give readers meaningful guidance when choosing an inhibitory tool.

The light sensitivity of MsACR1 and raACR1 are impressive and well characterized in vitro. However, the authors only reported the overall light output at the fiber tip for the in vivo experiments: 0.5 mW. Without context, it is difficult to evaluate this value. Calculating the light power density at certain distances from the light fiber or thresholding against alternative tools such as NpHR, Jaws, or other ACRs would allow for a more meaningful evaluation.

Reviewer #1 (Public Review):

In this paper, the authors attempt to overcome the "fundamental limitations" of Lempel-Ziv complexity by developing and testing a complexity estimator based on state-space modelling (CSER) that they argue allows higher temporal resolution and spectral decomposition of entropy directly. They test the performance of this approach using MEG, EEG, and ECoG data from monkeys and humans. Although in principle, these developments might be useful for those already using LZ complexity in their analyses, these developments ignore much of the non-LZ entropy community which has already developed related solutions to the same issues. It is thus not clear currently whether this approach is necessary or unique per se:

• As the authors intimate, LZ is a relatively crude but efficient estimator; it leverages a simple binarization of time points above and below the time series mean to look at patterns (in turn disregarding the magnitude of the signal itself). The unique benefit of LZ in and of itself is not at all clear to this reviewer. It is nearly guaranteed that LZ will be extremely highly correlated with various other common measures of "discrete" entropy (especially permutation entropy, which ranks all time-series points prior to computing motifs/patterns rather than anchor anything by the mean (as does LZ), but nevertheless ignores the value range of the signal). The general appeal of the authors' intended developments to further improve LZ specifically would dramatically boost should they be able to make a case that LZ is somehow special, to begin with.

• Beyond this, we can now turn to the authors' rationale for the LZ developments proposed. Despite the authors' statement in the abstract that LZ complexity is "the most widely used approach complexity of neural dynamics," to my knowledge, sample entropy (and its multiscale variant, MSE) is much more commonly used in cognitive neuroscience. Such measures of entropy already enjoy several benefits over LZ. First, the continuous magnitude of the signal is relevant in sample entropy (i.e., it is not discrete in the same way as LZ because the values of each data point matter prior to the estimation of patterns). This is important for people in that community because electrophysiologists/neuroimagers often assume the values of the signal to matter (e.g., for ERPs, the magnitude of power, etc.). Ignoring the magnitude of signal values altogether, as in LZ, is a somewhat dramatic choice, especially if the authors then end up arguing that the spectral decomposition of entropy itself is valuable (after signal value ranges have been ignored!). In any case, as far as I know, LZ has never been shown the be more sensitive than e.g., sample entropy/MSE in relation to any outcome variable, but perhaps the authors can provide evidence for this and argue what LZ should practically do that is unique. Second, the use of MSE more easily allows (although not without its challenges) to directly compare spectral power and single/multiscale entropy straight away, which has been done in quite some depth already without the need for a state-space model of any kind (e.g., Kosciessa et al., 2020, PLOS CB). Instead of using a standard spectral power approach and comparing to entropy, the authors propose the spectrally decompose CSER entropy time series directly. Why? What should this do over standard multi-scale entropy approaches (like MSE, which estimate "fast" and "slow" complexity dynamics), which do not require a Fourier? And if they already believe that the spectrum cannot capture entropy (hence rationalizing the use of LZ-type measures in general), why do they want to invoke spectral estimation assumptions into the estimation of entropy when they could just compare the standard spectrum to entropy to begin with, without any complex modelling in between? I just don't see the need for a lot of what is proposed here; the authors provide solutions to problems that (at least for several in this community) may not exist at all.

• Figure 2: the authors show results descriptively comparing LZ and CSER, but without comparing the two measures directly. The patterns overall look extremely similar; why not correlate the values from the two measures in each dataset to make a case for what CSER is adding here? By eye test, it appears they will be extremely highly correlated, which leaves the reader wondering what CSER (with all of its model complexities and assumptions) has added.

• On the logic of and evidence for the use of CSER: The use of a state space model to allow estimation of "prediction errors" appears to be akin to a latent autocorrelation model with a lag/step size of 1 time-point, and trained only on prestim baseline data. When a successive time point is "deviant" from that autocorrelative function, the authors argue that this provides a measure of instantaneous entropy. This seems simple at first glance, but it is very difficult for this reviewer to wrap their head around. This approach anchors stim-related entropy estimation to prestim entropy for every subject, disallowing the direct comparison of values across subjects during the stimulus phase itself. This does not directly provide a measure of instantaneous task-related entropy, but a mixture of pre and post stim sources based on a state-space model. Does it need to be this complicated? Why does a simple window-based function not suffice to generate temporal dynamics of entropy without coupling the task-based signal to the prestim period? There are many such approaches already existing in the field.

• Figure 3: The authors show that gamma-band CSER is the most sensitive. Isn't it true that this is the exact inverse of the dominance of typical spectral effects under such conditions (that across the literature in psychedelics, sleep, and anaesthesia, there are dominant shifts in low-frequency spectral power)? Although low-frequency power is expected to be a dominant determinant of entropy in the entire signal (see Kosciessa et al., 2020, PLOS CB), something else appears to be happening here. At face value, because gamma is the spectral band with the lowest power in every imaging modality we know of, there is inherently less repeatability/autocorrelation in that same signal, which necessarily should produce more "prediction error/instantaneous entropy" in any condition. When the authors then take the "mean difference" of gamma-based entropy values from each of the two conditions in each sample, any condition-based shift in entropy should inherently be easier to detect. In any case, why not simply show these CSER spectral results next to a standard spectrum over the same conditions and then directly compare the unique utility of e.g., gamma power to CSER gamma? And if you compute something like the percent change between conditions for each spectral band, do you maintain gamma dominance?

Reviewer #2 (Public Review):

This paper presents a novel measure of complexity that can be applied to recorded neurophysiological time series. The paper first introduces an existing measure, Lempel-Ziv complexity, reviewing its computation, application, and potential issues. They then present their new metric: CSER. They show CSER values change similarly to LZ under psychedelics, sleep, and general anaesthesia. A key advantage of CSER is that it can be decomposed in both time and frequency. They give example applications for each of these. They show the differences in CSER in the previous examples are mostly located in the gamma band. For a temporal example, they consider monkey ecog in an oddball task and so CSER changes between oddballs and deviants.

Major comments<br /> Most of the technical details are rightly in the methods, but it would be nice as a reader to have more of a concrete idea of the type of state space model used in the main text, the assumptions underlying this, and typical orders used perhaps with a schematic diagram etc. I appreciate they have written the paper to appeal to a broad general audience, but it seems like this is an important part of the method that anyone using the method should understand in more detail.

It might be nice to cover some other methods of signal variation e.g. as reviewed in Washke et al. Neuron 2021 and how CSER fits into the broader taxonomy of measures of neural variability (even if restricted to information-theoretic ones e.g. multi-scale entropy and permutation entropy, which have also been linked to prediction in the brain Washke et al. elife 2019).

While the examples are clear and well-motivated, the novel parts could be more developed in terms of interpretation, or linking to existing measures. For example, the frequency results show the complexity changes in "gamma" which is defined as >25Hz. From a biological point of view, it would be nice to understand this better, perhaps splitting low gamma (including 40Hz oscillations) from high gamma (ie MUA). How is the frequency measure affected by the width of the frequency band considered? I understand the sum of the shown terms equals the broadband result but e.g. in Figure 3 if the values were normalised by the bandwidth of each band, gamma might not stand out so much (as it is by far the widest band, 75Hz vs 3Hz for the delta). So if gamma is not contributing more per-unit of frequency, the interpretation might be different. What is it about the gamma band activity that is changing between the conditions: autocorrelation of power, more variability in phase procession? What would this measure give for simulated systems with known changes (for example, changes in oscillatory power, or changes in 1/f slope). What sort of system would give the profiles in Figure 3?

For the temporal example, the result is a nice proof of concept. It looks quite reminiscent of "novel mutual information" time-course (e.g. compare the absolute value of CSER difference to Figure 13, Ince et al HBM 2017, which also showed two peaks of novel information at the time where the gradient of the ERP starts to change, 20-30ms prior to the ERP peak, but in a task with no predictive component). It might be nice to explicitly compare the statistical power to this existing method (conditional mutual information between signal+gradient and experimental condition, conditioning out the selection of previous time points with peak conditional MI). Deviant stimuli initially seem to decrease entropy - by eye, it's surprising this isn't significant (stands out a lot from baseline). Was a two-sided or one-sided (matching the prior hypothesis) test performed here? Could it be that the change in entropy rate is a property of any ERP signal (ie it looks like the change in CSER reflects the following difference in peak ERP - for the first negative peak, the deviant amplitude is lower, for the second positive peak the deviant amplitude is higher), and a lower level signal interpretation (ie amplitude of CSER difference is related to the difference in ERP amplitude, rather than directly reflecting neural mechanisms of prediction).

Reviewer #2 (Public Review):

DeKraker et al. propose a new method for hippocampal registration using a novel surface-based approach that preserves the topology of the curvature of the hippocampus and boundaries of hippocampal subfields. The surface-based registration method proved to be more precise and resulted in better alignment compared to traditional volumetric-based registration. Moreover, the authors demonstrated that this method can be performed across image modalities by testing the method with seven different histological samples. This work has the potential to be a powerful new registration technique that can enable precise hippocampal registration and alignment across subjects, datasets, and image modalities.

Reviewer #3 (Public Review):

Summary:<br /> In the current manuscript, Dekraker and colleagues have demonstrated the ability to align hippocampal subfield parcellations across disparate 3D histology samples that differ in contrast, resolution, and processing/staining methods. In doing so, they validated the previously generated Big-Brain atlas by comparing across seven different ground-truth subfield definitions. This is an impressive effort that provides important groundwork for future in vivo multi-atlas methods.

Strengths:<br /> DeKraker and colleagues have provided novel evidence for the tremendously complicated curvature/gyrification of the hippocampus. This work underscores the challenge that this complicated anatomy presents in our ability to co-register other types of hippocampal data (e.g. MRI data) to appropriately align and study a structure in which the curvature varies considerably across individuals.

This paper is also important in that it highlights the utility of using post-mortem histological datasets, where ground truth histology is available, to inform our rigorous study of the in vivo brain.

This work may encourage readers to consider the limitations of the current methods that they currently use to co-register and normalize their MRI data and to question whether these methods are adequate for the examination of subfield activity, microstructure, or perfusion in the hippocampal head, for example. Thus the implications of this work could have a broad impact on the study of hippocampal subfield function in humans.

Weaknesses:<br /> As the authors are well aware, hippocampal subfield definitions vary considerably across laboratories. For example, some neuroanatomists (Ding, Palomero-Gallagher, Augustinack) recognize that the prosubiculum is a distinct region from subiculum and CA1 but others (e.g. Insausti, Duvernoy) do not include this as a distinct subregion. Readers should be aware that there is no universal consensus about the definition of certain subfields and that there is still disagreement about some of the boundaries even among the agreed upon regions.

Reviewer #1 (Public Review):

In this manuscript, "Diminishing neuronal acidification by channelrhodopsins with low proton conduction" by Hayward and colleagues, the authors report on the properties of novel optogenetic tools, PsCatCh2.0 and ChR2-3M, that minimize photo-induced acidification. The authors point out that acidification is an undesirable side-effect of many optogenetic approaches that could be minimized using the new tools. ChRs are known to acidify cells, while Arch are known to alkalize cells. This becomes particularly important when optical stimulation is prolonged and pH changes can become significant. pH is known to affect neuronal excitability, vesicular release, and more. To develop novel optogenetic tools with minimal proton conductances, the authors combined channelrhodopsin stimulation with a red-shifted pH sensor to measure pH during optogenetic stimulation. The authors report that optogenetic activation of CheRiff caused slow cellular acidification. 150 seconds of illumination caused a 3-fold increase in protons or approximately a 0.6 unit pH change that returned to baseline very slowly. They also found that pH changes occurred more rapidly, and recovered more rapidly, in dendrites. The authors go on to robustly characterize PsCatCh2.0 and ChR2-3M in terms of their proton conductances, photocurrent, kinetics, and more. They convincingly show that these constructs induced reduced acidification while maintaining robust photocurrents. In sum, this manuscript shows important findings that convincingly characterizes 2 optogenetic tools that have reduced pH artifacts that may be of broad interest to the field of neuroscience research and optogenetic therapies.

Reviewer #2 (Public Review):

In this paper, the authors utilize optogenetic stimulation and imaging techniques with fluorescent reporters for pH and membrane voltage to examine the extent of intracellular acidification produced by different ion-conducting opsins. The commonly used opsin CheRiff is found to conduct enough protons to alter intracellular pH in soma and dendrites of targeted neurons and in monolayers of HEK293T cells, whereas opsins ChR2-3M and PsCatCh2.0 are shown to produce negligible changes in intracellular pH as their photocurrents are mostly carried by metal cations. The conclusion that ChR2-3M and PsCatCh2.0 are more suited than proton conducting opsins for optogenetic applications is well supported by the data.

Reviewer #1 (Public Review):

Summary:

The work studies functional connectivity gradients using advanced resting-state analyses in fetuses and sheds light on pre-existing functional topographies and their continued development during the third trimester of gestation.

Strengths:

The work is novel, and applies state of the art connectomic mapping techniques to study fetal brain organization. The work capitalizes on the existence of large, open access datasets, and shows interesting and impactful findings on the presence of functional topographies from 25GW onwards.

Weaknesses:

To better understand underlying factors in cortical functional organization, the authors could add additional exploratory analyses to assess the role of cortical microstructure/myelin and thalamic connectivity.

Reviewer #2 (Public Review):

In this study, Moore et al. utilise resting-state fMRI data from the Developing Human Connectome Project, applying a recently developed technique ("connectopic mapping") to identify gradients of functional connectivity within resting-state networks in the human foetal brain. Whilst such gradients have previously been identified in adults, this is the first study to explore the topographic organisation of functional connectivity in the foetal brain. Furthermore, the authors describe localised changes within these gradients over the course of gestation, particularly in brain regions implicated in multisensory processing. Together, these results imply that topographic gradients of brain function are present within the developing foetal brain, and continue to develop through gestation. However, the study does not consider critical confounds inherent in the connectopic mapping technique, and as such I do not believe that the data as presented are sufficient to support the conclusions.

Recent evidence (Watson & Andrews, 2023, Neuroimage) has indicated that the connectopic mapping technique employed here can be substantially confounded by spatial autocorrelations present within the data (for instance, occurring naturally due to the inherent smoothness of the BOLD response, and/or introduced artificially during standard data pre-processing steps such as spatial smoothing or interpolation between co-ordinate spaces). These confounds allow connectopic gradients to be obtained even from random data, and which appear highly similar to those obtained from real data, suggesting that these gradients are strongly influenced by such confounds. Consequently, the resulting gradients may be an inevitability of the way the connectopic mapping technique works, rather than reflecting underlying brain functions per se.

In the current study, all of the gradients flow smoothly and continuously along a single axis within every network region, typically oriented relative to the long axis of the region. To put it another way - the connectopic mapping gives fundamentally the same answer in every network region. Such an organisation does feel a bit biologically implausible, and could be more consistent with the gradients representing an inevitable solution of the analysis technique, rather than necessarily reflecting brain function. Indeed, in some cases the gradients do not correspond well to known organisational principles of the regions. For instance, the primary gradient in the principal visual network flows smoothly along a superior to inferior axis, which the authors suggest corresponds to retinotopic polar angle maps - however, polar angle maps would be expected to reverse direction between each visual region, yet such reversals are not present in this connectopic map. The authors note that the foetal gradients appear highly similar to those previously obtained within similar regions in adult participants - this could be indicative of a consistent organisation across development, but would also be consistent with the same confound affecting foetal and adult participants. The reported changes in the gradients across gestation could reflect changes in the extent of these spatial autocorrelations or in the shape of the regions of interest (perhaps in turn resulting from changes in the underlying brain geometry) rather than necessarily reflecting development of brain function or specialisation. None of this precludes the possibility that these connectopic gradients may (at least partially) also reflect genuine brain functions, but it does obfuscate the extent to which they do so. It would be useful for the authors to give some consideration to this issue.

On a different note, could the authors comment on their reason for studying these gradients at the network level. The authors argue (and I agree) that brain function is likely to be organised topographically, rather than split into discrete parcellated regions. Nevertheless, the brain networks the authors choose to use are themselves discrete regions of interest (albeit fairly large ones). Other groups (e.g., Margulies et al, 2016, PNAS) have described coarser-scale connectopic gradients spanning the whole brain. Is there a reason that the authors have chosen to extract network-level gradients, rather than say coarser-scale whole-brain gradients? Have the authors considered examining how whole-brain gradients change over gestation?

Lastly, the correlated changes between gradients and gestation week appear to occur within small localised clusters. Does this reflect local perturbations of the gradient, or is there perhaps a wider change in the gradient as a whole and these clusters reflect extreme points within this that have changed the most (for instance corresponding to an expansion/contraction of the gradient)?

Reviewer #1 (Public Review):

Summary: Direction selectivity (DS) in the visual system is first observed in the radiating dendrites of starburst amacrine cells (SACs). Studies over the last two decades have aimed to understand the mechanisms that underlie these unique properties. Most recently, a 'space-time' model has garnered special attention. This model is based on two fundamental features of the circuit. First, distinct anatomical types of bipolar cells (BCs) are connected to proximal/distal regions of each of the SAC dendritic sectors (Kim et al., 2014). Second, that input across the length of the starburst is kinetically diverse, a hypothesis that has been only recently demonstrated experimentally using iGluSnFR imaging (Srivastava et al., 2022). However, the stark kinetic distinctions, i.e., the sustained/transient nature of BC input to SACs dendrites appear to be present mainly in responses to stationary stimuli. When BC receptive field properties are probed using white noise stimuli, the kinetic differences between BCs are relatively subtle or nonexistent (Gaynes et al., 2022; Strauss et al., 2022, Srivastava et al., 2022). Thus, if and how BCs contribute to direction selectivity driven by moving spots that are commonly used to probe the circuit remains to be clarified. To address this issue, Gaynes et al., combine evolutionary computational modeling (Ankri et al., 2020) with two-photon iGluSnFR imaging to address to what degree BCs contribute to the generation of direction selectivity in the starburst dendrites in response to stimuli that are commonly used experimentally.

Strengths:

Combining theoretical models and iGluSnFR imaging is a powerful approach as it first provides a basic intuition on what is required for the generation of robust DS, and then tests the extent to which the experimentally measured BC output meets these requirements.

The conclusion of this study builds on the previous literature and comprehensively considers the diverse BC receptive field properties that may contribute to DS (e.g. size, lag, rise time, decay time).

By 'evolving' bipolar inputs to produce robust DS in a model network, these authors provide a sound framework for understanding which kinetic properties could potentially be important for driving downstream DS. They suggest that response delay/decay kinetics, rather than the center/surround dynamics are likely to be most relevant (albeit the latter could generate asymmetric responses to radiating/looming stimuli).

Weaknesses: Finally, these authors report that the experimentally measured BC responses are far from optimal for generating DS. Thus, the BC-based DS mechanism does not appear to explain the robust DS observed experimentally (even with mutual inhibition blocked). Nevertheless, I feel the comprehensive description of BC kinetics and the solid assessment of the extent to which they may shape DS in SAC dendrites, is a significant advancement in the field.

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors sought to understand how the receptive fields of bipolar cells contribute to direction selectivity in starburst amacrine cell (SAC) dendrites, their post synaptic partners. In previous literature, this contribution is primarily conceptualized as the 'space-time wiring model', whereby bipolar cells with slow-release kinetics synapse onto proximal dendrites while bipolar cells with faster kinetics synapse more distally, leading to maximal summation of the slow proximal and fast distal depolarizations in response to motion away from the soma. The space-time wiring contribution to SAC direction selectivity has been extensively tested in previous literature using connectomic, functional, and modeling approaches. However, the authors argue that previous functional studies of bipolar cell kinetics have focused on static stimuli, which may not accurately represent the spatiotemporal properties of the bipolar cell receptive field in response to movement. Moreover, this group and others have recently shown that bipolar cell signal processing can change directionally when visual stimuli starts within the receptive field rather than passing through it, complicating the interpretation of moving stimuli that start within a bipolar cell of interest's receptive field (e.g. stimulating only one branch of a SAC or expanding/contracting rings). Thus, the authors choose to focus on modeling and functionally mapping bipolar cell kinetics in response to moving stimuli across the entire SAC dendritic field.

General Comments<br /> There have been several studies that have addressed the contribution of space-time wiring to SAC process direction selectivity. The impact of this project is to show that this contribution is limited. First, the optimal solution obtained by the evolutionary algorithm to generate DS processes is slow proximal and fast distal inputs - exactly what is predicted by space-time wiring, which is exactly what is required of the HRC model. Hence, this result seems expected and it's not clear what the alternative hypothesis is. Second, the experimental results based on glutamate imaging to assess the kinetics of glutamate release under conditions of visual stimulation across a large region of retina confirm previous observations but were important to test. Third, by combining their model model with this experiment data, they conclude that even the optimal space-time wiring is not sufficient to explain the SAC process DS. The results of this approach might be more impactful if the authors come to some conclusion as to what factors do determine the direction selectivity of the SAC process since they have argued that all the current models are not sufficient.

Reviewer #3 (Public Review):

Gaynes et al. investigated the presynaptic and postsynaptic mechanisms of starburst amacrine cell (SAC) direction selectivity in the mouse retina by computational modeling and glutamate sensitivity (iGluSnFR) imaging methods. Using the SAC computational simulation, the authors initially tested bipolar cell contributions (space-time wiring model, presynaptic effect) and SAC axial resistance contributions (postsynaptic effect) to the SAC DS. Then, the authors conducted two-photon iGluSnFR imaging from SACs to examine the presynaptic glutamate release, and found seven clusters of ON-responding and six clusters of OFF-responding bipolar cells. They were categorized based on their response kinetics: delay, onset phase, decay time, and others. Finally, the authors generated a model consisting of multiple clusters of bipolar cells on proximal and distal SAC dendrites. When the SAC DS was measured using this model, they found that the space-time wiring model accounted for only a fraction of SAC DS.

The article has many interesting findings, and the data presentation is superb. Strengths and weaknesses are summarized below.

Major Strengths:<br /> • The authors utilized solid technology to conduct computational modeling with Neuron software and a machine-learning approach based on evolutionary algorithms. Results are effectively and thoroughly presented.

• The space-time wiring model was evaluated by changing bipolar cell response properties in the proximal and distal SAC dendrites. Many response parameters in bipolar cells are compared, and DSI was compared in Figure 3.

• Two-photon microscopy was used to measure the bipolar cell glutamate outputs onto SACs by conducting iGluSnFR imaging. All the data sets, including images and transients, are elegantly presented. The authors analyzed the response based on various parameters, which generated more than several response clusters. The clustering is convincing.

Major Weaknesses:<br /> • In Figure 9, the authors generated the bipolar cell cluster alignment based on the space-time wiring model. The space-time wiring model has been proposed based on the EM study that distinct types of bipolar cells synapse on distinct parts of SAC dendrites (Green et al 2016, Kim et al 2014). While this is one of the representative Reicardt models, it is not fully agreed upon in the field (see Stincic et al 2016). While the authors' approach of testing the space-time wiring model and conclusions is interesting and appreciated, the authors could address more issues: mainly two clusters were used to generate the model, but more numbers of clusters should be applied. Although the location of each cluster on the SAC dendrites is unknown, the authors should know the populations of clusters by iGluSnFR experiments. Furthermore, the authors could provide more suggestive mechanisms after declining postsynaptic factors and the space-time wiring model.<br /> • The computational modeling demonstrates intriguing results: SAC dendritic morphology produces dendritic isolation, and a massive input overcomes the dendritic isolation (Figure 1). This modeling seems to be generated by basic dendritic cable properties. However, it has been reported that SAC dendrites express Kv3 and voltage-gated Ca channels. It seems to be that these channels are not incorporated in this model.

• In Figure 5B, representative traces are shown responding to moving bars in horizontal directions. These did not show different responses to two directional stimuli. It is unclear whether directional preference was not detected, which was shown by Yonehara's group recently (Matsumoto et al 2021). Or that was not investigated as described in the Discussion.

• The authors found seven ON clusters and six OFF clusters, which are supposed to be bipolar cell terminals. However, bipolar cells reported to provide synaptic inputs are T-7, T-6, and multiple T-5s for ON SACs and T-1, T-2, and T-3s for OFF SACs. The number of types is less than the number of clusters. Potentially, clusters might belong to glutamatergic amacrine cells. These points are not fully discussed.

Reviewer #1 (Public Review):

Guglielmo et al. characterized addiction-like behaviors in more than 500 outbred heterogeneous stock (HS) rats using extended access to cocaine self-administration (6 h/daily) and analyzed individual differences in escalation of intake, progressive-ratio (PR) responding, continued use despite adverse consequence (contingent foot shocks), and irritability-like behavior during withdrawal. By principal component analysis, they found that escalation of intake, progressive ratio responding, and continued use despite adverse consequences loaded onto the same factor, whereas irritability-like behaviors loaded onto a separate factor. Characterization of rats in four categories of resilient, mild, moderate, and severe addiction-like phenotypes showed that females had higher addiction-like behaviors, particularly due to a lower number of resilient individuals, than males. The authors suggest that escalation of intake, continued use despite adverse consequences, and progressive ratio responding are highly correlated measures of the same psychological construct and that a significant proportion of males, but not females may be resilient to addiction-like behaviors. The amount of work in this study is impressive, and the results are interesting. However, there are several issues that need to be addressed to improve their manuscript. In particular, the language should be toned down and the statistical analysis approach could be improved.

Strengths: Large dataset. Males and females included.

Weaknesses: Language and statistical analysis can be improved.

Reviewer #2 (Public Review):

Summary:<br /> In this paper by de Guglielmo and colleagues, the authors were interested in analyzing addiction-like behaviors using a very large number of heterogeneous outbred rats in order to determine the relationships among these behaviors. The paper used both males and females on the order of hundreds of rats, allowing for detailed and complex statistical analyses of the behaviors. The rats underwent cocaine self-administration, first via 2-hour access and then via 6-hour access. The rats also underwent a test of punishment resistance in which footshocks were administered a portion of the time a lever was pressed. The authors also conducted a progressive ratio test to determine the break point for "giving up" pressing the lever and a bottle-brush test to determine the rats' "irritability". Ultimately, principal component analysis revealed that escalation of intake during 6-hour access, punishment resistance, and breakpoint all loaded onto the same principal component. Moreover, the authors also identified a subgroup of "resilient" rats that qualitatively differed from the "vulnerable" rats and also identified sex differences in their work.

Strengths:<br /> The use of heterogeneous rats and the use of so many rats are major strengths of this paper. Moreover, the statistical analyses are particular strengths as they enabled the identification of the three measures as likely reflecting a single underlying construct. The behavioral methods themselves are also strong, as the authors used behavioral measures commonly used in the field that will enable comparison with the field at large. In general, the results support most of the conclusions and provide a wealth of data to the field.

Weaknesses:<br /> Because the authors used so many rats (~600), it is not clear how strong the effects are. That is, a large n makes it easy to identify small effect sizes, but no effect sizes are presented regarding the findings.

The Discussion includes parts that argue that the extended access model is a better model of addiction than short access and suggests that this paper provides support for that. However, there were no rats given short-access for the same period of time as the rats in this paper - i.e., no comparison group. Rather, the only comparison that can be made is as the rats transition from short to long access. The data in Figure 1B appear to show that the rats continue their increase in cocaine intake when they transition from short access to long access. The authors do not provide any statistical analyses about this escalation of intake during short access. However, they claim that "measures related to short-term cocaine intake" were orthogonal to those collected during longer access periods, yet it is not clear to me what measures those are. Nonetheless, as indicated in Figure 1H, it appears that the rats consistently shift from PC1 to PC2 across self-administration, regardless of whether they are in the short or long access period. That is, the long-access measures appear to simply be a continuation of the pattern begun during short access. As a result, notwithstanding the lack of a true short-access control group, it is difficult to see how the authors can draw conclusions about short vs. long access in this paper.

Moreover, as illustrated in Figure 3A, the resilient vs. vulnerable subtypes are apparent during short access self-administration (i.e., they do not require long-access self-administration to develop or be revealed). This suggests, if anything, that short access would be sufficient for identifying such groups. Similarly, Figure 5 shows that short access would be sufficient to identify the "low" vulnerability quartile vs. the other three groups.

During the discussion, the authors briefly discuss gender differences with regard to cocaine use disorder, with the authors trying to claim that women may be more vulnerable to cocaine use disorder. However, the two papers cited do not support that, as they are papers with rodents. A recent comprehensive review on humans with regard to cocaine craving and relapse noted no reliable gender differences (Nicolas et al., 2022, Pharmacological Reviews) and, as the authors themselves noted, men suffer from cocaine use disorder at higher rates than women.

The authors noted that the rats received 0.5 mg/kg/infusion of cocaine but provided no explanation for how this dosing was maintained (or whether it was maintained) across the length of the study. Considering that rats, especially males, increase in size quite a bit during this stage, this could affect measures like intake as well as skew sex difference results. Likewise, the data are presented strictly in the number of cocaine infusions, which does not allow for consideration of body weight.

In the Introduction, the authors make a number of arguments in the second paragraph that have no citations and, therefore, are unsupported.

Reviewer #3 (Public Review):

Summary: The manuscript by de Guglielmo et al. presents data demonstrating that escalation of drug intake, increased motivation for drug under a progressive ratio, and drug-seeking despite adverse consequence can be explained by the same construct, while irritability-like behavior during withdrawal is statistically unrelated to an addiction-like phenotype.

Strengths: It is commendable that the authors used large cohorts of heterogenous male and female rats to mitigate common preclinical limitations that can hinder the translational relevance of research findings. The overall question is important and the authors provide a large amount of data to support their claim.

Weaknesses: However, there are a number of factors - such as behavioral rate - that are not considered and likely co-vary with other measures. This is critical as previous work has shown that rate of behavior in reinforcement tasks is a large determinant of sensitivity to both drug effects on that behavior and punishers. This is not considered and but additional information and tempering the interpretation of the data would further strengthen the manuscript.

Reviewer #1 (Public Review):

The present work establishes 14-3-3 proteins as binding partners of Spastin and suggests that this binding is positively regulated by phosphorylation of Spastin. The authors show evidence that 14-3-3 - Spastin binding prevents Spastin ubiquitination and final proteasomal degradation, thus increasing the availability of Spastin. The authors measured microtubule severing activity in cell lines and axon regeneration and outgrowth as a prompt to Spastin activity. By using drugs and peptides that separately inhibit 14-3-3 binding or Spastin activity, they show that both proteins are necessary for axon regeneration in cell culture and in vivo models in rats.

The following is an account of the major strengths and weaknesses of the methods and results.

Major strengths<br /> -The authors performed pulldown assays on spinal cord lysates using GST-spastin, then analyzed pulldowns via mass spectrometry and found 3 peptides common to various forms of 14-3-3 proteins. In co-expression experiments in cell lines, recombinant Spastin co-precipitated with all 6 forms of 14-3-3 tested.<br /> -By protein truncation experiments they found that the Microtubule Binding Domain of Spastin contained the binding capability to 14-3-3. This domain contained a putative phosphorylation site, and substitutions that cannot be phosphorylated cannot bind to Spastin.<br /> -Spastin overexpression increased neurite growth and branching, and so did the phospho null spastin. On the other hand, the phospho mimetic prevents all kinds of neurite development.<br /> -Overexpression of GFP-Spastin shows a turn-over of about 12 hours when protein synthesis is inhibited by cycloheximide. When 14-3-3 is co-overexpressed, GFP-Spastin does not show a decrease by 12 hours. When S233A is expressed, a turn-over of 9 hours is observed, indicating that the ability to be phosphorylated increases the stability of the protein.<br /> -In support of that notion, the phospho-mimetic S233D makes it more stable, lasting as much as the over-expression of 14-3-3.<br /> -Authors show that Spastin can be ubiquitinated, and that in the presence of ubiquitin, Spastin-MT severing activity is inhibited.<br /> -By combining FCA with Spastazoline, the authors claim that FCA increased regeneration is due to increased Spastin Activity in various models of neurite outgrowth and regeneration in cell culture and in vivo, the authors show impressive results on the positive effect of FCA in regeneration, and that this is abolished when Spastin is inhibited.

Major weaknesses<br /> -However convincing the pull-downs of the expressed proteins, the evidence would be stronger if a co-immunoprecipitation of the endogenous proteins were included.<br /> -To better establish the impact of Spastin phosphorylation in the interaction, there is no indication that the phosphomimetic (S233D) can better bind Spastin, and this result is contradicting to the conclusion of the authors that Spastin-14-3-3 interaction is necessary for (or increases) Spastin function<br /> -To fully support the authors' suggestion that 14-3-3 and Spastin work in the same pathway to promote regeneration, I believe that some key observations are missing.<br /> 1-There is no evidence showing that 14-3-3 overexpression increases the total levels of Spastin, not only its turnover.<br /> 2- There is no indication that increasing the ubiquitination of Spastin decreases its levels. To suggest that proteasomal activity is affecting the levels of a protein, one would expect that proteasomal inhibition (with bortezomib or epoxomycin), would increase its levels.<br /> 3- Authors show that S233D increases MT severing activity, and explain that it is related to increased binding to 14-3-3. An alternative explanation is that phosphorylation at S233 by itself could increase MT severing activity. The authors could test if purified Spastin S233D alone could have more potent enzymatic activity.<br /> -Finally, I consider that there are simpler explanations for the combined effect of FC-A and spastazoline. FC-A mechanism of action can be very broad, since it will increase the binding of all 14-3-3 proteins with presumably all their substrates, hence the pathways affected can rise to the hundreds. The fact that spastazoline abolishes FC-A effect, may not be because of their direct interaction, but because Spastin is a necessary component of the execution of the regeneration machinery further downstream, in line with the fact that spastizoline alone prevented outgrowth and regeneration, and in agreement with previous work showing that normal Spastin activity is necessary for regeneration.

In summary, the evidence of the interaction of 14-3-3 and Spastin is solid, but it is weak with respect to showing evidence for the binding of endogenous proteins in neurons. Another strength of the manuscript is the important recovery of function after spinal cord injury after stimulation of 14-3-3 interactions. Although it is experimentally difficult to demonstrate that the effect of FC-A is due to the prevention of Spastin ubiquitination, the effect itself is very robust and remarkable in vivo.

Reviewer #2 (Public Review):

Summary:<br /> The idea of harnessing small molecules that may affect protein-protein interactions to promote axon regeneration is interesting and worthy of study. In this manuscript, Liu et al. explore a 14-3-3-Spastin complex and its role in axon regeneration.

Strengths:<br /> Some of the effects of FC-A on locomotor recovery after spinal cord contusion look interesting.

Weaknesses:<br /> The manuscript falls short of establishing that a 14-3-3-Spastin complex is important for any FC-A-dependent effects and there are several issues with data quality that make it difficult to interpret the results. Importantly, the effects of the Spastin inhibitor have a major impact on neurite outgrowth suggesting that cells simply cannot grow in the presence of the inhibitor and raising serious questions about any selectivity for FC-A - dependent growth. Aspects of the histology following spinal cord injury were not convincing.

Reviewer #3 (Public Review):

Summary:<br /> The current manuscript claims that 14-3-3 interacts with Spastin and that the 14-3-3/spastin interaction is important to regulate axon regeneration after spinal cord injury.

Strengths:<br /> In its present form, this reviewer identified no clear strengths for this manuscript.

Weaknesses:<br /> In general, most of the figures lack sufficient quality to allow analyses and support the author's claims (detailed below). The legends also fail to provide enough information on the figures which makes it hard to interpret some of them. Most of the quantifications were done based on pseudo-replication. The number of independent experiments (that should be defined as n) is not shown. The overall quality of the written text is also low and typos are too many to list. The original nature of the spinal cord injury-related experiments is unclear as the role of 14-3-3 (and Spastin) in axon regeneration has been extensively explored in the past.

Reviewer #1 (Public Review):

Summary: In this study, Franke et al. explore and characterize the color response properties across the primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake-behaving 2P imaging to define the spectral response properties of visual interneurons in Layer 2/3. They find that opponent responses are more prominent at photopic light levels, and diversity in color opponent responses exists across the visual science, with green ON/ UV OFF responses being stronger represented in the upper visual field. This is argued to be relevant for detecting certain features that are more salient when the chromatic space is used, possibly due to noise reductions.

Strengths: The work is well crafted and written and provides a thorough characterization that reveals an uncharacterized diversity of visual properties in V1. I find this characterization important because it reveals how strongly chromatic information can modulate the response properties in V1. In the upper visual field, 25% of the cells differentially relay chromatic information, and one may wonder how this information will be integrated and subsequently used to aid vision beyond the detection of color per see. I personally like the last paragraph of the discussion that highlights this fact.

Weaknesses:

One major point highlighted in this paper is the fact that Green ON/UV OFF responses are not generated in the retina. But glancing through the literature, I saw this is not necessarily true. Fig 1. of Joesch & Meister, a paper cited, shows this can be the case. Thus, I would not emphasize that this wasn't present in the retina. This is a minor point, but even if the retina could not generate these signals, I would be surprised if the diversity of responses would only arise through feed-forward excitation, given the intricacies of cortical connectivity. Thus, I would argue that the argument holds for most of the responses seen in V1; they need to be further processed by cortical circuitries. This takes me to my second point, defining center and surround. The center spot is 37.5 deg of visual angle, more than 1 mm of the retinal surface. That means that all retinal cells, at least half and most likely all of their surrounds will also be activated. Although 37.5 deg is roughly the receptive field size previously determined for V1 neurons, the one-to-one comparison with retinal recording, particularly with their center/surround properties, is difficult. This should be discussed. I assume that the authors tried a similar approach with sparse or dense checker white noise stimuli. If so, it would be interesting if there were better ways of defining the properties of V1 neurons on their complex/simple receptive field properties to define how much of their responses are due to an activation of the true "center" or a coactivation of the surround. Interestingly, at least some of the cells (Fig. 1d, cells 2 and 5) don't have a surround. Could it be that in these cases, the "center" and "surround" are being excited together? How different would the overall statistics change if one used a full-filed flicker stimulus instead of a center/surround stimulus? How stable are the results if the center/surround flicker stimulus is shifted? These results won't change the fact that chromatic coding is present in the VC and that there are clear differences depending on their position, but it might change the interpretation. Thus, I would encourage you to test these differences and discuss them.

Reviewer #2 (Public Review):

Summary: Franke et al. characterize the representation of color in the primary visual cortex of mice and how it changes across the visual field, with a particular focus on how this may influence the ability to detect aerial predators. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet were presented in random combinations. Using a clustering approach, a set of functional cell-types were identified based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have varying spatial distributions in V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:<br /> The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

Weaknesses:<br /> While the study presents solid evidence a few weaknesses exist, including the size of the dataset, clarity regarding details of data included in each step of the analysis and discussion of caveats of the work. The results presented here are based on recordings of 3 mice. While the number of neurons recorded is reasonably large (n > 3000) an analysis that tests for consistency across animals is missing. Related to this, it is unclear how many neurons at each stage of the analysis come from the 3 different mice (except for Suppl. Fig 4). Finally, the paper would greatly benefit from a more in depth discussion of the caveats related to the conclusion drawn at each stage of the analysis. This is particularly relevant regarding the caveats related to using spike triggered averages to assess the response preferences of ON-OFF neurons, and the conclusions drawn about the contribution of retinal color opponency.

The authors provide solid evidence to support an asymmetric distribution of color opponent cells in V1 and a reduced color contrast representation in lower light levels. Some statements would benefit from more direct evidence such as the integration of upstream visual signals for color opponency in V1.

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Reviewer #3 (Public Review):

This paper studies chromatic coding in mouse primary visual cortex. Calcium responses of a large collection of cells are measured in response to a simple spot stimulus. These responses are used to estimate chromatic tuning properties - specifically sensitivity to UV and green stimuli presented in a large central spot or a larger still surrounding region. Cells are divided based on their responses to these stimuli into luminance or chromatic sensitive groups. Several technical concerns limit how clearly the data support the conclusions. If these issues can be fixed, the paper would make a valuable contribution to how color is coded in mouse V1.

Analysis<br /> The central tool used to analyze the data is a "spike triggered average" of the responses to randomly varying stimuli. There are several steps in this analysis that are not documented, and hence evaluating how well it works is difficult. Central to this is that the paper does not measure spikes. Instead, measured calcium traces are converted to estimated spike rates, which are then used to estimate STAs. There are no raw calcium traces shown, and the approach to estimate spike rates is not described in any detail. Confirming the accuracy of these steps is essential for a reader to be able to evaluate the paper. Further, it is not clear why the linear filters connecting the recorded calcium traces and the stimulus cannot be estimated directly, without the intermediate step of estimating spike rates.

A further issue about the STAs is that the inclusion criterion (correlation of predicted vs measured responses of 0.25) is pretty forgiving. It would be helpful to see a distribution of those correlation values, and some control analyses to check whether the STA is providing a sufficiently accurate measure to support the results (e.g. do the central results hold for the cells with the highest correlations).

Limitations of stimulus choice<br /> The paper relies on responses to a large (37.5 degree diameter) modulated spot and surrounding region. This spot is considerably larger than the receptive fields of both V1 cells and retinal ganglion cells. As a result, the spot itself is very likely to strongly activate both center and surround mechanisms, and responses of cells are likely to depend on where the receptive fields are located within the spot (and, e.g., how much of the true neural surround samples the center spot vs the surround region). The impact of these issues on the conclusions is considered briefly at the start of the results but needs to be evaluated in considerably more detail. This is particularly true for retinal ganglion cells given the size of their receptive fields (see also next point).

Comparison with retina<br /> A key conclusion of the paper is that the chromatic tuning in V1 is not inherited from retinal ganglion cells. This conclusion comes from comparing chromatic tuning in a previously-collected data set from retina with the present results. But the retina recordings were made using a considerably smaller spot, and hence it is not clear that the comparison made in the paper is accurate. This issue may be handled by the analysis presented in the paper, but if so it needs to be described more clearly.<br /> The paper from which the retina data is taken argues that rod-cone chromatic opponency originates largely in the outer retina. This mechanism would be expected to be shared across retinal outputs. Thus it is not clear how the Green-On/UV-Off vs Green-Off/UV-On asymmetry could originate. This should be discussed.

Residual chromatic cells at low mesopic light levels<br /> The presence of chromatically tuned cells at the lowest light level probed is surprising. The authors describe these conditions as rod-dominated, in which case chromatic tuning should not be possible. This again is discussed only briefly. It either reflects the presence of an unexpected pathway that amplifies weak cone signals under low mesopic conditions such that they can create spectral opponency or something amiss in the calibrations or analysis. Data collected at still lower light levels would help resolve this.

Reviewer #1 (Public Review):

In this work, Dasguta et al. have dissected the role of Sema7a in fine tuning of a sensory microcircuit in the posterior lateral line organ of zebrafish. They attempt to also outline the different roles of a secreted verses membrane-bound form of Sema7a in this process. Using genetic perturbations and axonal network analysis, the authors show that loss of both Sema7a isoforms causes abnormal axon terminal structure with more bare terminals and fewer loops in contact with presynaptic sensory hair cells. Further, they show that loss of Sema7a causes decreased number and size of both the pre- and post-synapse. Finally, they show that overexpression of the secreted form of Sema7a specifically can elicit axon terminal outgrowth to an ectopic Sema7a expressing cell. Together, the analysis of Sema7a loss of function and overexpression on axon arbor structure is fairly thorough and revealed a novel role for Sema7a in axon terminal structure. However, the connection between different isoforms of Sema7a and the axon arborization needs to be substantiated. Furthermore, an autocrine role for Sema7a on the presynaptic cell is not ruled out as a contributing factor to the synaptic and axon structure phenotypes. Finally, critical controls are absent from the overexpression paradigm. These issues weaken the claims made by the authors including the statement that they have identified differential roles for the GPI-anchored verses secreted forms of Sema7a on synapse formation and as a chemoattractant for axon arborization respectively. The manuscript itself would benefit from the inclusion of details in the text to help the reader interpret the figures, tools, data, and analysis.

Reviewer #2 (Public Review):

In this work, Dasgupta et al. investigates the role of Sema7a in the formation of peripheral sensory circuit in the lateral line system of zebrafish. They show that Sema7a protein is present during neuromast maturation and localized, in part, to the base of hair cells (HCs). This would be consistent with pre-synaptic Sema7a mediating formation and/or stabilization of the synapse. They use sema7a loss-of-function strain to show that lateral line sensory terminals display abnormal arborization. They provide highly quantitative analysis of the lateral line terminal arborization to show that a number of specific topological parameters are affected in mutants. Next, they ectopically express a secreted form of Sema7a to show that lateral line terminals can be ectopically attracted to the source. Finally, they also demonstrate that the synaptic assembly is impaired in the sema7a mutant. Overall, the data are of high quality and properly controlled. The availability of Sema7a antibody is a big plus, as it allows to address the endogenous protein localization as well to show the signal absence in the sema7a mutant. The quantification of the arbor topology should be useful to people in the field who are looking at the lateral line as well as other axonal terminals. I think some results are overinterpreted though. The authors state: "Our findings demonstrate that Sema7A functions both as a juxtracrine and as a secreted cue to pattern neural circuitry during sensory organ development." However, they have not actually demonstrated which isoform functions in HCs (also see comments below). In addition, they have to be careful in interpreting their topology analysis, as they cannot separate individual axons. Thus, such analysis can generate artifacts. They can perform additional experiments to address these issues or adjust their interpretations.

Reviewer #3 (Public Review):

Summary:

This study demonstrates that the axon guidance molecule Sema7a patterns the innervation of hair cells in the neuromasts of the zebrafish lateral line, as revealed by quantifying gain- and loss-of function effects on the three-dimensional topology of sensory axon arbors over developmental time. Alternative splicing can produce either a diffusible or membrane-bound form of Sema7a, which is increasingly localized to the basolateral pole of hair cells as they develop (Figure 1). In sema7a mutant zebrafish, sensory axon arbors still grow to the neuromast, but they do not form the same arborization patterns as in controls, with many arbors overextending, curving less, and forming fewer loops even as they lengthen (Figure 2,3). These phenotypes only become significant later in development, indicating that Sema7a functions to pattern local microcircuitry, not the gross wiring pattern. Further, upon ectopic expression of the diffusible form of Sema7a, sensory axons grow towards the Sema7a source (Figure 4). The data also show changes in the synapses that form when mutant terminals contact hair cells, evidenced by significantly smaller pre- and post-synaptic punctae (Figure 5). Finally, by replotting single cell RNA-sequencing data (Figure 6), the authors show that several other potential cues are also produced by hair cells and might explain why the sema7a phenotype does not reflect a change in growth towards the neuromast. In summary, the data strongly indicate that Sema7a plays a role in shaping connectivity within the neuromast.

Strengths:

The main strength of this study is the sophisticated analysis that was used to demonstrate fine-level effects on connectivity. Rather than asking "did the axon reach its target?", the authors asked "how does the axon behave within the target?". This type of deep analysis is much more powerful than what is typical for the field and should be done more often. The breadth of analysis is also impressive, in that axon arborization patterns and synaptic connectivity were examined at 3 stages of development and in three-dimensions.

Weaknesses:

The main weakness is that the data do not cleanly distinguish between activities for the secreted and membrane-bound forms of Sema7a, which the authors speculate may influence axon growth and synapse formation respectively. The authors do not overstate the claims, but it would have been nice to see some additional experimentation along these lines, such as the effects of overexpressing the membrane-bound form, some analysis of the distance over which the "diffusible" form of Sema7a might act (many secreted ligands are not in fact all that diffusible), or some live-imaging of axons before they reach the target (predicted to be the same in control and mutants) and then within the target (predicted to be different). Clearly, although the gain-of-function studies show that Sema7a can act at a distance, other cues are sufficient. Although the lack of a phenotype could be due to compensation, it is also possible that Sema7a does not actually act in a diffusible manner within its natural context.

Overall, the data support the authors' carefully worded conclusions. While certain ideas are put forward as possibilities, the authors recognize that more work is needed. The main shortcoming is that the study does not actually distinguish between the effects of the two forms of Sema7a, which are predicted but not actually shown to be either diffusible or membrane linked (the membrane linkage can be cleaved). Although the study starts by presenting the splice forms, there is no description of when and where each splice form is transcribed. Additionally, since the mutants are predicted to disrupt both forms, it is a bit difficult to disentangle the synaptic phenotype from the earlier changes in circuit topology - perhaps the change at the level of the synapse is secondary to the change in topology. Further, the authors do not provide any data supporting the idea that the membrane bound form of Sema7a acts only locally. Without these kinds of data, the authors are unable to attribute activities to either form.

The main impact on the field will be the nature of the analysis. The field of axon guidance benefits from this kind of robust quantification of growing axon trajectories, versus their ability to actually reach a target. This study highlights the value of more careful analysis and as a result, makes the point that circuit assembly is not just a matter of painting out paths using chemoattractants and repellants, but is also about how axons respond to local cues. The study also points to the likely importance of alternative splice forms and to the complex functions that can be achieved using different forms of the same ligand.

Reviewer #4 (Public Review):

Summary:<br /> The work by Dasgupta et al identifies Sema7a as a novel guidance molecule in hair cell sensory systems. The authors use the both genetic and imaging power of the zebrafish lateral-line system for their research. Based on expression data and immunohistochemistry experiments, the authors demonstrate that Sema7a is present in lateral line hair cells. The authors then examine a sema7a mutant. In this mutant, Sema7a proteins levels are nearly eliminated. Importantly, the authors show that when Sema7a is absent, afferent terminals show aberrant projections and fewer contacts with hair cells. Lastly the authors show that ectopic expression of the secreted form of Sema7a is sufficient to recruit aberrant terminals to non-hair cell targets. The sema7a innervation defects are well quantified. Overall, the paper is extremely well written and easy to follow.

Strengths:<br /> 1. The axon guidance phenotypes in sema7a mutants are novel, striking and thoroughly quantified.<br /> 2. By combining both loss of function sema7a mutants and ectopic expression of the secreted form of Sema7a the authors demonstrate the Sema7a is both necessary and sufficient to guide sensory axons

Weaknesses:<br /> 1. Control. There should be an uninjected heatshock control to ensure that heatshock itself does not cause sensory afferents to form aberrant arbors. This control would help support the hypothesis that exogenously expressed Sema7a (via a heatshock driven promoter) is sufficient to attract afferent arbors.<br /> 2. Synapse labeling. The numbers obtained for postsynaptic labeling in controls do not match up with the published literature - they are quite low. Although there are clear differences in postsynaptic counts between sema7a mutants and controls, it is worrying that the numbers are so low in controls. In addition, the authors do not stain for complete synapses (pre- and post-synapses together). This staining is critical to understand how Sema7a impacts synapse formation.<br /> 3. Hair cell counts. The authors need to provide quantification of hair cell counts per neuromast in mutant and control animals. If the counts are different, certain quantification may need to be normalized.<br /> 4. Developmental delay. It is possible that loss of Sema7a simply delays development. The latest stage examined was 4 dpf, an age that is not quite mature in control animals. The authors could look at a later age, such as 6 dpf to see if the phenotypes persist or recover.

Reviewer #1 (Public Review):

Summary:<br /> The authors report an fMRI investigation of the neural mechanisms by which selective attention allows capacity-limited perceptual systems to preferentially represent task-relevant visual stimuli. Specifically, they examine competitive interactions between two simultaneously-presented items from different categories, to reveal how task-directed attention to one of them modulates the activity of brain regions that respond to both. The specific hypothesis is that attention will bias responses to be more like those elicited by the relevant object presented on its own, and further that this modulation will be stronger for more dissimilar stimulus pairs. This pattern was confirmed in univariate analyses that measured the mass response of a priori regions of interest, as well as multivariate analyses that considered the patterns of evoked activity within the same regions. The authors follow these neuroimaging results with a simulation study that favours a "tuning" mechanism of attention (enhanced responses to highly effective stimuli, and suppression for ineffective stimuli) to explain this pattern.

Strengths:<br /> The manuscript clearly articulates a core issue in the cognitive neuroscience of attention, namely the need to understand how limited perceptual systems cope with complex environments in the service of the observer's goals. The use of a priori regions of interest, and the inclusion of both univariate and multivariate analyses as well as a simple model, are further strengths. The authors carefully derive clear indices of attentional effects (for both univariate and multivariate analyses) which makes explication of their findings easy to follow.

Weaknesses:<br /> There are some relatively minor weaknesses in presentation, where the motivation behind some of the procedural decisions could be clearer. There are some apparently paradoxical findings reported -- namely, cases in which the univariate response to pairs of stimuli is greater than to the preferred stimulus alone -- that are not addressed. It is possible that some of the main findings may be attributable to range effects: notwithstanding the paradox just noted, it seems that a floor effect should minimise the range of possible attentional modulation of the responses to two highly similar stimuli. One possible limitation of the modelled results is that they do not reveal any attentional modulation at all under the assumptions of the gain model, for any pair of conditions, implying that as implemented the model may not be correctly capturing the assumptions of that hypothesis.

Reviewer #2 (Public Review):

Summary:<br /> In an fMRI study requiring participants to attend to one or another object category, either when the object was presented in isolation or with another object superimposed, the authors compared measured univariate and multivariate activation from object-selective and early visual cortex to predictions derived from response gain and tuning sharpening models. They observed a consistent result across higher-level visual cortex that more-divergent responses to isolated stimuli from category pairs predicted a greater modulation by attention when attending to a single stimulus from the category pair presented simultaneously, and argue via simulations that this must be explained by tuning sharpening for object categories.

Strengths:<br /> - Interesting experiment design & approach - testing how category similarity impacts neural modulations induced by attention is an important question, and the experimental approach is principled and clever.

- Examination of both univariate and multivariate signals is an important analysis strategy.

- The acquired dataset will be useful for future modeling studies.

Weaknesses:<br /> - The experimental design does not allow for a neutral 'baseline' estimate of neural responses to stimulus categories absent attention (e.g., attend fixation), nor of the combination of the stimulus categories. This seems critical for interpreting results (e.g., how should readers understand univariate results like that plotted in Fig. 4C-D, where the univariate response is greater for 2 stimuli than one, but the analyses are based on a shift between each extreme activation level?).

- Related, simulations assume there exists some non-attended baseline state of each individual object representation, yet this isn't measured, and the way it's inferred to drive the simulations isn't clearly described.

- Some of the simulation results seem to be algebraic (univariate; Fig. 7; multivariate, gain model; Fig. 8).

- Cross-validation does not seem to be employed - strong/weak categories seem to be assigned based on the same data used for computing DVs of interest - to minimize the potential for circularity in analyses, it would be better to define preferred categories using separate data from that used to quantify - perhaps using a cross-validation scheme? This appears to be implemented in Reddy et al. (2009), a paper implementing a similar multivariate method and cited by the authors (their ref 6).

- Multivariate distance metric - why is correlation/cosine similarity used instead of something like Euclidean or Mahalanobis distance? Correlation/cosine similarity is scale-invariant, so changes in the magnitude of the vector would not change distance, despite this likely being an important data attribute to consider.

- Details about simulations implemented (and their algebraic results in some cases) make it challenging to interpret or understand these results. E.g., the noise properties of the simulated data aren't disclosed, nor are precise (or approximate) values used for simulating attentional modulations.

- Eye movements do not seem to be controlled nor measured. Could it be possible that some stimulus pairs result in more discriminable patterns of eye movements? Could this be ruled out by some aspect of the results?

- A central, and untested/verified, assumption is that the multivariate activation pattern associated with 2 overlapping stimuli (with one attended) can be modeled as a weighted combination of the activation pattern associated with the individual stimuli. There are hints in the univariate data (e.g., Fig. 4C; 4D) that this might not be justified, which somewhat calls into question the interpretability of the multivariate results.

- Throughout the manuscript, the authors consistently refer to "tuning sharpening", an idea that's almost always used to reference changes in the width of tuning curves for specific feature dimensions (e.g., motion direction; hue; orientation; spatial position). Here, the authors are assaying tuning to the category (across exemplars of the category). The link between these concepts could be strengthened to improve the clarity of the manuscript.

Reviewer #1 (Public Review):

Jafarinia et al. have made an interesting contribution to unravelling the molecular mechanisms underlying pathological phenotypes of repeat expansion of the C9orf72 gene. The repeat expression leads to the expression of polyPR proteins. Using coarse-grained molecular dynamics simulations, the authors identify putative binding partners involved in nucleocytoplasmic transport (NCT), and that conjecture that polyPR affects essential processes by binding to NCT-related proteins. The results are well-reported, but only putative, and need experimental support to be more conclusive. Also, a comparison with results from all-atom MD simulations in explicit water could help verify the results. But even without these, the work is very useful as a first step to unravel the role of polyPR and related peptides.

Reviewer #2 (Public Review):

This study used coarse-grained molecular dynamics simulation to explain how the binding of polyPR might interfere with distinct stages of the transport cycle. This finding shows that the interaction between polyPR and transport components is driven by electrostatic interactions and is correlated with the salt concentration and the length of polyPR, providing an important basis for subsequent exploration of the impact of C9orf72 R-DPRs on NCT disruption.

Reviewer #3 (Public Review):

Onck and co-workers present in this work the identification of binding partners and sites of polyPR on various nuclear transport components and elucidate how polyPR might potentially influence the transport process. It's interesting to note that some interaction sites on transport components also serve as their inherent/functional binding sites. The difference in the effects between short polyPR (PR7) and long polyPR (PR50) is also evident, although the authors might need to clarify the mechanisms better. Overall, the manuscript is well organized and concisely written, and it would greatly enhance our understanding of the toxicity induced by polyPR. In general, the 1-bead per atom force field model used in the study is well-tuned for studying the interactions between polyPR and proteins, as the essential cation-pi interactions (between Arg and Phe/Tyr/Trp) were included using an 8-6 LJ model.

Reviewer #1 (Public Review):

The goal of the current study was to evaluate the effect of neuronal activity on blood-brain barrier permeability in the healthy brain, and to determine whether changes in BBB dynamics play a role in cortical plasticity. The authors used a variety of well-validated approaches to first demonstrate that limb stimulation increases BBB permeability. Using in vivo-electrophysiology and pharmacological approaches, the authors demonstrate that albumin is sufficient to induce cortical potentiation and that BBB transporters are necessary for stimulus-induced potentiation. The authors include a transcriptional analysis and differential expression of genes associated with plasticity, TGF-beta signaling, and extracellular matrix were observed following stimulation. Overall, the results obtained in rodents are compelling and support the authors' conclusions that neuronal activity modulates the BBB in the healthy brain and that mechanisms downstream of BBB permeability changes play a role in stimulus-evoked plasticity. These findings were further supported with fMRI and BBB permeability measurements performed in healthy human subjects performing a simple sensorimotor task. While there are many strengths in this study, there is literature to suggest that there are sex differences in BBB dysfunction in pathophysiological conditions. The authors only used males in this study and do not discuss whether they would also expect to sex differences in stimulation-evoked BBB changes in the healthy brain. Another minor limitation is the authors did not address the potential impact of anesthesia which can impact neurovascular coupling in rodent studies. The authors could have also better integrated the RNAseq findings into mechanistic experiments, including testing whether the upregulation of OAT3 plays a role in cortical plasticity observed following stimulation. Overall, this study provides novel insights into how neurovascular coupling, BBB permeability, and plasticity interact in the healthy brain.

Reviewer #2 (Public Review):

Summary:<br /> This study builds upon previous work that demonstrated that brain injury results in leakage of albumin across the blood-brain barrier, resulting in activation of TGF-beta in astrocytes. Consequently, this leads to decreased glutamate uptake, reduced buffering of extracellular potassium, and hyperexcitability. This study asks whether such a process can play a physiological role in cortical plasticity. They first show that stimulation of a forelimb for 30 minutes in a rat results in leakage of the blood-brain barrier and extravasation of albumin on the contralateral but not ipsilateral cortex. The authors propose that the leakage is dependent upon neuronal excitability and is associated with an enhancement of excitatory transmission. Inhibiting the transport of albumin or the activation of TGF-beta prevents the enhancement of excitatory transmission. In addition, gene expression associated with TGF-beta activation, synaptic plasticity, and extracellular matrix are enhanced on the "stimulated" hemisphere. That this may translate to humans is demonstrated by a breakdown in the blood-brain barrier following activation of brain areas through a motor task.

Strengths:<br /> This study is novel and the results are potentially important as they demonstrate an unexpected breakdown of the blood-brain barrier with physiological activity and this may serve a physiological purpose, affecting synaptic plasticity.

The strengths of the study are:<br /> 1) The use of an in vivo model with multiple methods to investigate the blood-brain barrier response to a forelimb stimulation.<br /> 2) The determination of a potential functional role for the observed leakage of the blood-brain barrier from both a genetic and electrophysiological viewpoint.<br /> 3) The demonstration that inhibiting different points in the putative pathway from activation of the cortex to transport of albumin and activation of the TGF-beta pathway, the effect on synaptic enhancement could be prevented.<br /> 4) Preliminary experiments demonstrating a similar observation of activity-dependent breakdown of the blood-brain barrier in humans.

Weaknesses:<br /> There are both conceptual and experimental weaknesses.

1) The stimulation is in an animal anesthetized with ketamine, which can affect critical receptors (ie NMDA receptors) in synaptic plasticity.

2) The stimulation protocol is prolonged and it would be helpful to know if briefer stimulations have the same effect or if longer stimulations have a greater effect ie does the leakage give a "readout" of the stimulation intensity/length.

3) For some of the experiments (see below), the numbers of animals are low and the statistical tests used may not be the most appropriate, making the results less clear cut.

4) The experimental paradigms are not entirely clear, especially the length of time of drug application and the authors seem to try to detect enhancement of a blocked SEP.

4) It is not clear how long the enhancement lasts. There is a remark that it lasts longer than 5 hours but there is no presentation of data to support this.

5) It is not clear if this enhancement of synaptic transmission has any physiological role.

6) The spatial and temporal specificity of this effect is unclear (other than hemispheric in rats) and even less clear in humans.

7) It is not clear to what extent the experimenters and those doing the analysis were blinded to group. If neither were blind to group, then considerable biases could be introduced.

8) The experimenters rightly use separate controls for most of the experiments but this is not always the case, also raising the possibility that the application of drugs was not done randomly or interleaved, but possibly performed in blocks of animals, which can also affect results.

9) Methyl-beta-cyclodextrin clears cholesterol so the effect on albumin transport is not specific, it could be mediating its effect through some other pathway.

10) Since the breakdown of the blood-brain barrier can be inhibited by a TGF-beta inhibitor, then this implies that TGF-beta is necessary for the breakdown of the blood-brain barrier. This does not sit well with the hypothesis that TGF-beta activation depends upon blood-brain barrier leakage.

Reviewer #3 (Public Review):

Summary:<br /> This study used prolonged stimulation of a limb to examine possible plasticity in somatosensory evoked potentials induced by the stimulation. They also studied the extent that the blood-brain barrier (BBB) was opened by prolonged stimulation and whether that played a role in the plasticity. They found that there was potentiation of the amplitude and area under the curve of the evoked potential after prolonged stimulation and this was long-lasting (>5 hrs). They also implicated extravasation of serum albumin, caveolae-mediated transcytosis, and TGFb signalling, as well as neuronal activity and upregulation of PSD95. Transcriptomics was done and implicated plasticity-related genes in the changes after prolonged stimulation, but not proteins associated with the BBB or inflammation. Next, they address the application to humans using a squeeze ball task. They imaged the brain and suggested that the hand activity led to an increased permeability of the vessels, suggesting modulation of the BBB.

Strengths:<br /> The strengths of the paper are the novelty of the idea that stimulation of the limb can induce cortical plasticity in a normal condition, and it involves the opening of the BBB with albumin entry. In addition, there are many datasets and both rat and human data.

Weaknesses:<br /> The conclusions are not compelling however because of a lack of explanation of methods and quantification. It also is not clear whether the prolonged stimulation in the rat was normal conditions. To their credit, the authors recorded the neuronal activity during stimulation, but it seemed excessive excitation. Since seizures open the BBB this result calls into question one of the conclusions. that the results reflect a normal brain. The authors could either conduct studies with stimulation that is more physiological or discuss the caveats of using a supraphysiological stimulus to infer healthy brain function.

Reviewer #1 (Public Review):

Summary:

Exposure to cranial irradiation (IR) leads to cognitive deficits in the survivors of brain cancer. IR upregulates miR-206-3p, which in turn reduces the PAK3-LIMK1 axis leading to the loss of F and G-actin ratio and, thereby, mature dendritic spine loss. Silencing miR-206-3p reverses these degenerative consequences.

Strengths:<br /> The authors show compelling data indicating a clear correlation between PAK3 knockdown and the loss of mature dendritic spine density. In contrast, overexpression of PAK3 in the irradiated neurons restored mature spine types and recovered the F/G ratio. These in vitro results support the authors' hypotheses that PAK3 and LIMK1-mediated downstream signaling impact neuronal structure and reorganization in vitro. These data were supported by similar experiments using differentiated human neurons. Importantly, silencing miR-206-30 using antagonist miR also reverses IR-induced downregulation of the PAK3-LIMK1 axis, preventing spine loss and cognitive deficits.

Weaknesses:

All the miR-206-3p data are presented from in vitro cortical neurons or human stem cell-derived neuron cultures. This data (IR-induced elevation of miR-206-3p) should also be confirmed in vivo using an irradiated mouse brain to correlate the cognitive dysfunction timepoint.

Antago-miR-206-3p reversed Ir-induced upregulation of miR-206 (in vitro), and prevent reductions in PAK3 and downstream markers. Importantly, it reversed cognitive deficits induced by IR. This data should be supported by in vivo staining for important dendritic markers, including cofillin, p-cofilin, PSD-95, F- and G-actin within the hippocampal and PFC regions.

Other neuronal and non-neuronal targets of miR-206-3p should be discussed and looked into as a downstream impact of IR-induced functional and physiological impairments in the brain.

Reviewer #2 (Public Review):

Summary:<br /> The paper entitled "PAK3 downregulation induces cognitive 1 impairment following cranial irradiation" by Lee et al. aimed at investigating the functional impact of cranial irradiation in mouse and propose PAK3 as molecular element involved in radiation-induced cognitive decrement. The results provided in this paper are problematic as both the irradiation paradigm (5X2 Gy) as well as the timing of investigation (3 to 8 days post-IR) are completely irrelevant to investigate radiation induced neurocognitive impairment. This testifies to the team's lack of knowledge in radiobiology/radiotherapy and the methodology to explore radiation induced neurocognitive damages. It precludes any further relevance of the molecular results.

Weaknesses:<br /> First and according to the BED equation a single dose of 10 Gy cannot not be approximated by 5 fractions of 2 Gy, as fractionation is known to decrease normal tissue toxicity. Note that in radiobiology/radio-oncology, the BED stands for "Biologically Effective Dose." This equation is used to compare the effects of different radiation treatments on biological tissues, taking into account the dose, fractionation, and the overall biological response of the tissue to radiation.<br /> The BED equation is commonly used to calculate the equivalent dose of a fractionated radiation treatment, which is the dose that would produce the same biological effect as a single, higher dose delivered in a single fraction.<br /> The general formula for BED is:BED = D * (1 + d / α/β)<br /> D is the total physical dose of radiation delivered in Grays (Gy)<br /> d is the dose per fraction in Gy<br /> α/β is the tissue-specific ratio of the linear (α) and quadratic (β) components of the radiation response. It is measured in Gy and describes how the tissue responds to different fractionation schedules (usually equal to 3 for the normal brain).<br /> Please refers to radiobiology/radiotherapy textbooks by Hall or Joiner.

Second, the brain is a late responding organ. GBM patients treated with 60 Gy exhibit progressive and debilitating impairments in memory, attention and executive function several month post-irradiation. In mice, neurocognitive decrements after a single dose of 10 Gy delivered to the whole brain does occur at late time point, usually > 2 months post-exposure. Multiple publications such as the one by Limoli C lab, Rossi S lab, Britten R lab or earlier Fike J lab and Robin M lab support this. Next, 5 fractions of 2 Gy will be more protective than a single dose of 10 Gy and neurocognitive decrements will require at least 5-6 months to occur if they ever occur. In Figure 1, the decrement reported is marginal, the number of animals included (4 to 5 at most?) The number of animals is not specified) is too low to draw any significant conclusions. In addition to the timing issue, the strategy described for NOR analysis shows methodological issues with the habituation period being too short and exploration level being very low.

Reviewer #1 (Public Review):

The authors investigate pleiotropy in the genetic loci previously associated to a range of neuropsychiatric disorders: Alzheimer's disease, amyotrophic lateral sclerosis (ALS), frontotemporal dementia, Parkinson's disease, and schizophrenia. The local statistical fine-mapping and variant colocalisation approaches they use have the potential to uncover not only shared loci but also shared causal variants between these disorders. There is existing literature describing the pleiotropy between ALS and these other disorders but here the authors apply state of the art, local genetic correlation approaches to further refine any relationships.

Complex disease and GWAS is not my area of expertise but the authors managed to present their methods and results in a clear, easy to follow manner. Their results statistically support several correlations between the disorders and, for ALS and AD, a shared variant in the vicinity of the lead SNP from the original ALS GWAS. Such findings could have important implications for our understanding of the mechanisms of such disorders and eventually the possibility of managing and treating them.

The authors have built a useful pipeline that plugs together all the gold-standard, existing software to perform this analysis and made it openly available which is commendable. However, there is little discussion of what software is available to perform global and local correlation analysis and, if there are multiple tools available, why they consider the ones they selected to be the gold-standard.

There is some mention of previous findings of genetic pleiotropy between ALS and these other disorders in the introduction, and discussion of their improved ALS-AD evidence relative to previous work. However, detailed comparisons of their other correlations to what was described before for the same pairs of disorders (if any) is missing. Adding this would strengthen the impact of this paper.

Finally, being new to this approach I found the abstract a little confusing. Initially, the shared causal variant between ALS and AD is mentioned but immediately in the following sentence they describe how their study "suggested that disease- implicated variants in these loci often differ between traits". After reading the whole paper I understood that the ALS-AD shared variant was the exception but it may be best to restructure this part of the abstract. Additionally, in the abstract the authors state that different variants "suggests the role of distinct mechanisms across diseases despite shared loci". Is it not possible that different variants in the same regulatory region or protein-coding parts of a gene could be having the same effect and mechanism? Or does the methodology to establish that different variants are involved automatically mean that the variants are too distant for this to be possible?

Reviewer #2 (Public Review):

Summary:

Spargo and colleagues present an analysis of the shared genetic architectures of Schizoprehnia and several late-onset neurological disorders. In contrast to many polygenic traits for which global genetic correlation estimates are substantial, global genetic correlation estimates for neurological conditions are relatively small, likely for several reasons. One is that assortative mating, which will spuriously inflate genetic correlation estimates, is likely to be less salient for late-onset conditions. Another, which the authors explore in the current manuscript, is that some loci affecting two or more conditions (i.e., pleiotropic loci) may have effects in opposite directions, or shared loci are sparse, such that the global genetic correlation signal washes out.

The authors apply a local genetic correlation approach that assesses the presence and direction of pleiotropy in much smaller spatial windows across the genome. Then, within regions evidencing local genetic correlations for a given trait pair, they apply fine-mapping and colocalization methods to attempt to differentiate between two scenarios: that the two traits share the same causal variant in the region or that distinct loci within the region influence the traits. Interestingly, the authors only discover one instance of the former: an SNP in the HLA region appearing to confer risk for both AD and ALS. This is in contrast to six regions with distinct causal loci, and twenty regions with no clear shared loci.

Finally, the authors have published their analysis pipeline such that other researchers might easily apply the same techniques to other collections of traits.

Strengths:<br /> - All such analysis pipelines involve many decision points where there is often no clear correct option. Nonetheless, the authors clearly present their reasoning behind each such decision.<br /> - The authors have published their analytic pipeline such that future researchers might easily replicate and extend their findings.

Weaknesses:<br /> - The majority of regions display no clear candidate causal variants for the traits, whether shared or distinct. Further, despite the potential of local genetic correlation analysis to identify regions with effects in opposing directions, all of the regions for causal variants were identified for both traits evidenced positive correlations. The reasons for this aren't clear and the authors would do well to explore this in greater detail.<br /> - The authors very briefly discuss how their findings differ from previous analyses because of their strict inclusion for "high-quality" variants. This might be the case, but the authors do not attempt to demonstrate this via simulation or otherwise, making it difficult to evaluate their explanation.

Reviewer #1 (Public Review):

Summary: Chang et al. provide glutamate co-expression profiles in the central noradrenergic system and test the requirement of Vglut2-based glutamatergic release in respiratory and metabolic activity under physiologically relevant gas challenges. Their experiments show that conditional deletion of Vglut2 in NA neurons does not impact steady-state breathing or metabolic activity in room air, hypercapnia, or hypoxia. Their observations challenge the importance of glutamatergic signaling from Vglut2 expressing NA neurons in normal respiratory homeostasis in conscious adult mice.

Strengths: The comprehensive Vglut1, Vglut2, and Vglut3 co-expression profiles in the central noradrenergic system and the combined measurements of breathing and oxygen consumption are two major strengths of this study. Observations from these experiments provide previously undescribed insights into (1) expression patterns for subtypes of the vesicular glutamate transporter protein in the noradrenergic system and (2) the dispensable nature of Vglut2-dependent glutamate signaling from noradrenergic neurons to breathing responses to physiologically relevant gas challenges in adult conscious mice.

Weaknesses: Although the cellular expression profiles for the vesicular glutamate transporters are provided, the study fails to document that glutamatergic-based signaling originating from noradrenergic neurons is evident at the cellular level under normal, hypoxic, and/or hypercapnic conditions. This limits the reader's understanding of why conditional Vglut2 knockdown is dispensable for breathing under the conditions tested.

Reviewer #2 (Public Review):

The authors characterized the recombinase-based cumulative fate maps for vesicular glutamate transporters (Vglut1, Vglut2 and Vglut3) expression and compared those maps to their real-time expression profiles in central NA neurons by RNA in situ hybridization in adult mice. Authors have revealed a new and intriguing expression pattern for Vglut2, along with an entirely uncharted co-expression domain for Vglut3 within central noradrenergic neurons. Interestingly, and in contrast to previous studies, the authors demonstrated that glutamatergic signaling in central noradrenergic neurons does not exert any influence on breathing and metabolic control either under normoxic/normocapnic conditions or after chemoreflex stimulation. Also, they showed for the first-time the Vglut3-expressing NA population in C2/A2 nuclei. In addition, they were also able to demonstrate Vglut2 expression in anterior NA populations, such as LC neurons, by using more refined techniques, unlike previous studies.

A major strength of the study is the use of a set of techniques to investigate the participation of NA-based glutamatergic signaling in breathing and metabolic control. The authors provided a full characterization of the recombinase-based cumulative fate maps for Vglut transporters. They performed real-time mRNA expression of Vglut transporters in central NA neurons of adult mice. Further, they evaluated the effect of knocking down Vglut2 expression in NA neurons using a DBH-Cre; Vglut2cKO mice on breathing and control in unanesthetized mice. Finally, they injected the AAV virus containing Cre-dependent Td tomato into LC of v-Glut2 Cre mice to verify the VGlut2 expression in LC-NA neurons. A very positive aspect of the article is that the authors combined ventilation with metabolic measurements. This integration holds particular significance, especially when delving into the exploration of respiratory chemosensitivity. Furthermore, the sample size of the experiments is excellent.

Despite the clear strengths of the paper, some weaknesses exist. It is not clear in the manuscript if the experiments were performed in males and females and if the data were combined. I believe that the study would have benefited from a more comprehensive analysis exploring the sex specific differences. The reason I think this is particularly relevant is the developmental disorders mentioned by the authors, such as SIDS and Rett syndrome, which could potentially arise from disruptions in central noradrenergic (NA) function, exhibit varying degrees of sex predominance. Moreover, some of the noradrenergic cell groups are sexually dimorphic. For instance, female Wistar rats exhibit a larger LC size and more LC-NA neurons than male subjects (Pinos et al., 2001; Garcia-Falgueras et al., 2005). More recently, a detailed transcriptional profiling investigation has unveiled the identities of over 3,000 genes in the LC. This revelation has highlighted significant sexual dimorphisms, with more than 100 genes exhibiting differential expression within LC-NA neurons at the transcript level. Furthermore, this investigation has convincingly showcased that these distinct gene expression patterns have the capacity to elicit disparate behavioral responses between sexes (Mulvey et al., 2018). Therefore, the authors should compare the fate maps, Vglut transporters in males and females, at least considering LC-NA neurons. Even in the absence of identified sex differences, this information retains significant importance.

An important point well raised by the authors is that although suggestive, these experiments do not definitively rule out that NA-Vglut2 based glutamatergic signaling has a role in breathing control. Subsequent experiments will be necessary to validate this hypothesis.

An improvement could be made in terms of measuring body temperature. Opting for implanted sensors over rectal probes would circumvent the need to open the chamber, thereby preventing alterations in gas composition during respiratory measurements. Further, what happens to body temperature phenotype in these animals under different gas exposures? These data should be included in the Tables.

Is it plausible that another neurotransmitter within NA neurons might be released in higher amounts in DBH-Cre; Vglut2 cKO mice to compensate for the deficiency in glutamate and prevent changes in ventilation?

Continuing along the same line of inquiry is there a possibility that Vglut2 cKO from NA neurons not only eliminates glutamate release but also reduces NA release? A similar mechanism was previously found in VGLUT2 cKO from DA neurons in previous studies (Alsio et al., 2011; Fortin et al., 2012; Hnasko et al., 2010). Additionally, does glutamate play a role in the vesicular loading of NA? Therefore, could the lack of effect on breathing be explained by the lack of noradrenaline and not glutamate?

Reviewer #1 (Public Review):

Qin et al., demonstrate, convincingly, that plasticity of ocular dominance of binocular neurons in the visual thalamus persists in adulthood. The adult plasticity is similar to that described in critical period juveniles in that it is absent in transgenic mice with the deletion of the GABA a1 receptor in thalamus, which also blocks ocular dominance plasticity in primary visual cortex. However, the adult plasticity is not dependent on feedback from primary visual cortex, an important difference from juveniles. These findings are an important contribution to a growing body of work identifying plasticity in the adult visual system, and identifies the visual thalamus as a potential target for therapies to reverse adult amblyopia.

Reviewer #2 (Public Review):

In this work, the authors found in the mouse line of GABA a1 subunit KO in thalamic neurons, which was previously reported lacking ocular dominance (OD) plasticity in juvenile V1 and dLGN (Sommeijer et al., 2017), the adult V1 and dLGN OD plasticity was also missing. Through muscimol inhibiting the V1 feedback, thalamic OD plasticity was unaffected in both WT and KO adult mice. However, during the critical period, the thalamic OD plasticity was dependent on V1 feedback in WT mice.

Strengths:

1. The experiments were well designed. The authors used both MD and No MD controls with both WT and KO mice. The authors used in vivo SU recording, which is broadly accepted as the major method for evaluating OD plasticity.

2. The data analysis was solid. The authors used proper statistical tests for non-parametric data set.

Weaknesses:

1. In my previous review I pointed out that an alternative interpretation of the results is that the lack of OD plasticity in adult V1 and dLGN was caused by an early blockade of the development of the inhibitory circuit in dLGN, which causes life-long deficits in the functional connection of dLGN. The best way to rule out this possibility is by using conditional KO mice that dLGN synaptic inhibition was only interfered in adulthood. In response to my concern, the authors replied with a long text of reasoning why the current results are solid enough and the proposed experiment was unnecessary. I agree with most of the explanation that the current conclusion is solid, but I still think that the cKO experiment will be a good supplement to the current study, and if we do see a similar result in the cKO mice, the conclusion that the adult perturbation of thalamic inhibitory circuit interfere with the OD plasticity will be more convincing. However, I do understand that repeating the experiments again in another mouse line will be difficult and time-consuming, so the authors could choose if they want to perform the experiment or not.

2. Now the discussion part is very long and complex. Rearranging the discussion with sub-sections will make it easy to read.

Reviewer #1 (Public Review):

This manuscript by Xu and colleagues addresses the important question of how multi-modal associations are encoded in the rodent brain. They use behavioral protocols to link stimuli to whisker movement and discover that the barrel cortex can be a hub for associations. Based on anatomical correlations, they suggest that structural plasticity between different areas can be linked to training. Moreover, they provide electrophysiological correlates that link to behavior and structure. Knock-down of nlg3 abolishes plasticity and learning.

This study provides an important contribution as to how multi-modal associations can be formed across cortical regions.

Reviewer #2 (Public Review):

This manuscript by Xu et al. explores the potential joint storage/retrieval of associated signals in learning/memory and how that is encoded by some associative memory neurons using a mouse model. The authors examined mouse associative learning by pairing multimodal mouse learning including olfactory, tactile, gustatory, and pain/tail heating signals. The key finding is that after associative learning, barrel neurons respond to other multi-model stimulations. They found these barrel cortical neurons interconnect with other structures including piriform cortex, S1-Tr and gustatory cortical neurons. Further studies showed that Neuroligin 3 mediated the recruitment of associative memory neurons during paired stimulation group. The authors found that knockdown Neuroligin 3 in the barrel cortex suppressed the associative memory cell recruitment in the paired stimulation learning. Overall, while the findings of this study are interesting, the concept of associative learning involving multiple functionally connective cortical regions is not that novel. While some data presented are convincing, the other seems to lack rigor. In addition, more details and clarification of the experimental methods are needed.

Reviewer #1 (Public Review):

Meta-cognition, and difficulty judgments specifically, is an important part of daily decision-making. When facing two competing tasks, individuals often need to make quick judgments on which task they should approach (whether their goal is to complete an easy or a difficult task).

In the study, subjects face two perceptual tasks on the same screen. Each task is a cloud of dots with a dominating color (yellow or blue), with a varying degree of domination - so each cloud (as a representation of a task where the subject has to judge which color is dominant) can be seen an easy or a difficult task. Observing both, the subject has to decide which one is easier.

It is well-known that choices and response times in each separate task can be described by a drift-diffusion model, where the decision maker accumulates evidence toward one of the decisions ("blue" or "yellow") over time, making a choice when the accumulated evidence reaches a predetermined bound. However, we do not know what happens when an individual has to make two such judgments at the same time, without actually making a choice, but simply deciding which task would have stronger evidence toward one of the options (so would be easier to solve).

It is clear that the degree of color dominance ("color strength" in the study's terms) of both clouds should affect the decision on which task is easier, as well as the total decision time. Experiment 1 clearly shows that color strength has a simple cumulative effect on choice: cloud 1 is more likely to be chosen if it is easier and cloud 2 is harder. Response times, however, show a more complex interactive pattern: when cloud 2 is hard, easier cloud 1 produces faster decisions. When cloud 2 is easy, easier cloud 1 produces slower decisions.

The study explores several models that explain this effect. The best-fitting model (the Difference model is the paper's terminology) assumes that the decision-maker accumulates evidence in both clouds simultaneously and makes a difficulty judgment as soon as the difference between the values of these decision variables reaches a certain threshold. Another potential model that provides a slightly worse fit to the data is a two-step model. First, the decision maker evaluates the dominant color of each cloud, then judges the difficulty based on this information.

Importantly, the study explores an optimal model based on the Markov decision processes approach. This model shows a very similar qualitative pattern in RT predictions but is too complex to fit to the real data. Possibly, the fact that simple approaches such as the Difference model fit the data best could suggest the existence of some cognitive constraints that play a role in difficulty judgments and could be explored in future research.

The Difference model produces a well-defined qualitative prediction: if the dominant color of both clouds is known to the decision maker, the overall RT effect (hard-hard trials are slower than easy-easy trials) should disappear. Essentially, that turns the model into the second stage of the two-stage model, where the decision maker learns the dominant colors first. The data from Experiment 2 impressively confirms that prediction and provides a good demonstration of how the model can explain the data out-of-sample with a predicted change in context.

Overall, the study provides a very coherent and clean set of predictions and analyses that advance our understanding of meta-cognition. The field would benefit from further exploration of differences between the models presented and new competing predictions (for instance, exploring how the sequential presentation of stimuli or attentional behavior can impact such judgments). Finally, the study provides a solid foundation for future neuroimaging investigations.

Reviewer #2 (Public Review):

Starting from the observation that difficulty estimation lies at the core of human cognition, the authors acknowledge that despite extensive work focusing on the computational mechanisms of decision-making, little is known about how subjective judgments of task difficulty are made. Instantiating the question with a perceptual decision-making task, the authors found that how humans pick the easiest of two stimuli, and how quickly these difficulty judgments are made, are best described by a simple evidence accumulation model. In this model, perceptual evidence of concurrent stimuli is accumulated and difficulty is determined by the difference between the absolute values of decision variables corresponding to each stimulus, combined with a threshold crossing mechanism. Altogether, these results strengthen the success of evidence accumulation models in describing human decision-making, now extending it to judgments of difficulty.

The manuscript addresses a timely question and is very well written, with its goals, methods and findings clearly explained and directly relating to each other. The authors are specialists of evidence accumulation tasks and models. Their modelling of human behaviour within this framework is state-of-the-art. In particular, their model comparison is guided by qualitative signatures which are diagnostic to tease apart different models (e.g., the RT criss-cross pattern). Human behaviour is then inspected for these signatures, instead of relying exclusively on quantitative comparison of goodness-of-fit metrics.

The study has potential limitations well flagged by the authors after the revision process. The main limitation pertains to the (dis)similarity between the behavioural task used in the study and difficulty judgments people actually do in real world (and which are well illustrated in the introduction). First, difficulty judgments made in the task never impact the participant (a new trial simply follows) while difficulty judgments in the wild often determine whether to pursue or quit the corresponding task, which can have consequences years after the difficulty estimation (e.g., deciding to engage in a particular academic path as a function of the estimated difficulty). Second, while trial-by-trial feedback is delivered in the task, difficulty estimation in the wild has to be made with partial information and feedback is either absent or delayed. How much these differences are key in providing an accurate computational description of human difficulty judgments will likely require further research.

Another limitation is the absence of models based on computational principles other than evidence accumulation. Although there are good reasons to favour evidence accumulation models in these settings (as mentioned by the authors in their manuscript), showing that evidence accumulation models would have won against competitors would have further strengthened the authors' claim that difficulty judgment about perceptual information are firmly anchored in the principles of evidence accumulation.

These limitations should not distract the reader from the impact of the present work, which will likely be wide, spanning the whole field of decision-making, and this across species. It will echo in particular with the many other seminal studies that have relied on a similar theoretical account of behaviour and brain activity (evidence accumulation). In addition, this study will hopefully inspire novel task designs aiming at addressing difficulty judgment estimations in controlled lab experiments, possibly with features closer to real world difficulty estimation (e.g., long-term consequences of difficulty estimation and absence of feedback).

Reviewer #3 (Public Review):

The manuscript presents novel findings regarding the judgment of difficulty of perceptual decisions. In the main task (Experiment 1), participants accumulated evidence over time about two tasks, patches of random dot motion, and were asked to report for which patch it would be easier to make a decision about its dominant color, while not explicitly making such decision(s). By fitting several alternative models, authors demonstrated that while accuracy changes as a function of the difference between stimulus strengths, reaction times of such decisions are not solely governed by the difference in stimulus strength, but (also) by the difference in absolute accumulated evidence for color judgment of the two stimuli ('Difference model'). Predictions from the best fitted model were then tested with a new set of conditions and participants (Experiment 2). Here, authors eliminated part of the uncertainty by informing participants about the dominant color of the two stimuli ('known color' condition) and showing that reaction times were faster compared to the 'unknown color' task, and only depended on the difference between stimulus strengths.

The paper deals with a valuable question about a metacognitive aspect of perceptual decision making, which was only sparsely addressed before. The paper is very well written, figures and illustrations clearly accompanied the text, and methods and modeling are rigor. The authors also address the concern that a difficulty judgment might be a confidence estimation, another metacognitive judgment of perceptual decisions, by fitting a Confidence model to the 'known color' condition in Experiment 2 and showing that this model performs worse compared to the Difference model. This is an important control analysis, given the possibility that humans might make an implicit decision about the dominant color of each patch, and then report their level of confidence.

This work is likely to be of great interest in the field of behavioral modeling of perceptual decision making, and might encourage further investigations of how judging the difficulty of a task affects subsequent decisions about the same task.

Reviewer #1 (Public Review):

The authors focused on genetic variability in relation to insulin resistance. They used genetically different lines of mice and exposed them to the same diet. They found that genetic predisposition impacts the overall outcome of metabolic disturbances. This work provides a fundamental novel view on the role of genetics and insulin resistance.

Reviewer #2 (Public Review):

Summary:<br /> In the present study, van Gerwen et al. perform deep phosphoproteomics on muscle from saline or insulin-injected mice from 5 distinct strains fed a chow or HF/HS diet. The authors follow these data by defining a variety of intriguing genetic, dietary, or gene-by-diet phosphor-sites that respond to insulin accomplished through the application of correlation analyses, linear mixed models, and a module-based approach (WGCNA). These findings are supported by validation experiments by intersecting results with a previous profile of insulin-responsive sites (Humphrey et al, 2013) and importantly, mechanistic validation of Pfkfb3 where overexpression in L6 myotubes was sufficient to alter fatty acid-induced impairments in insulin-stimulated glucose uptake. To my knowledge, this resource provides the most comprehensive quantification of muscle phospho-proteins which occur as a result of diet in strains of mice where genetic and dietary effects can be quantifiably attributed in an accurate manner. Utilization of this resource is strongly supported by the analyses provided highlighting the complexity of insulin signaling in muscle, exemplified by contrasts to the "classically-used" C57BL6/J strain. As it stands, I view this exceptional resource as comprehensive with compelling strength of evidence behind the mechanism explored. Therefore, most of my comments stem from curiosity about pathways within this resource, many of which are likely well beyond the scope of incorporation in the current manuscript. These include the integration of previous studies investigating these strains for changes in transcriptional or proteomic profiles and intersections with available human phospho-protein data, many of which have been generated by this group.

Strengths:<br /> Generation of a novel resource to explore genetic and dietary interactions influencing the phospho-proteome in muscle. This is accompanied by the elegant application of in silico tools to highlight the utility.

Weaknesses:<br /> Some specific aspects of integration with other data among the same fixed strains could be strengthened and/or discussed.

Reviewer #3 (Public Review):

Summary:<br /> The authors aimed to investigate how genetic and environmental factors influence the muscle insulin signaling network and its impact on metabolism. They utilized mass spectrometry-based phosphoproteomics to quantify phosphosites in the skeletal muscle of genetically distinct mouse strains in different dietary environments, with and without insulin stimulation. The results showed that genetic background and diet both affected insulin signaling, with almost half of the insulin-regulated phosphoproteome being modified by genetic background on an ordinary diet, and high-fat high-sugar feeding affecting insulin signaling in a strain-dependent manner.

Strengths:<br /> The study uses state-of-the-art phosphoproteomics workflow allowing quantification of a large number of phosphosites in skeletal muscle, providing a comprehensive view of the muscle insulin signaling network. The study examined five genetically distinct mouse strains in two dietary environments, allowing for the investigation of the impact of genetic and environmental factors on insulin signaling. The identification of coregulated subnetworks within the insulin signaling pathway expanded our understanding of its organization and provided insights into potential regulatory mechanisms. The study associated diverse signaling responses with insulin-stimulated glucose uptake, uncovering regulators of muscle insulin responsiveness.

Weaknesses:<br /> Different mouse strains have huge differences in body weight on normal and high-fat high-sugar diets, which makes comparison between the models challenging. The proteome of muscle across different strains is bound to be different but the changes in protein abundance on phosphosite changes were not assessed. Authors do get around this by calculating 'insulin response' because short insulin treatment should not affect protein abundance. The limitations acknowledged by the authors, such as the need for larger cohorts and the inclusion of female mice, suggest that further research is needed to validate and expand upon the findings.

Reviewer #1 (Public Review):

Summary:<br /> The authors measured the oxygen stable isotope ratios in six orangutan teeth using a state-of-the-art micro-sampling technique (SHRIMP SI) to gather substantial multi-year isotopic data for six modern and five fossil orangutan individuals from Borneo and Sumatra. This fine-scale sampling technique allowed them to address the fundamental question of whether breastfeeding affects the oxygen isotope ratios in teeth forming in the first one to two years of life, during which orangutans are assumed to largely depend on breastmilk. The authors provide compelling evidence that the consumption of milk does not appear to affect the overall isotopic profile in early-forming teeth. They conclude that this allows us to use these teeth as terrestrial/arboreal isotopic proxies in paleoenvironmental research, which would provide an invaluable addition to otherwise largely marine climate records in these regions.

Strengths:<br /> The overall large sample size of orangutan dental isotope records as well as the rigorous dating of the fossil specimens provide a strong dataset for addressing the outlined questions. The direct comparison of modern and fossil orangutan specimens provides a valuable evaluation of the use of these modern and past environmental proxies, with some discussion of the implications for the environmental conditions during the expansion of early modern humans into this region of the world.

Weakness:<br /> Although the overall conclusions of this paper are well supported and discussed, one important aspect could have more detailed consideration: the ecology and behavior of orangutans. As one example, orangutans are almost exclusively (~96%) arboreal creatures foraging for plant foods in the forest canopy, and as such they mostly meet their water requirements from the plants they eat, only very rarely drinking surface water (Ashbury et al. 2015). As a result, all orangutan water and foods are strongly affected by the so-called canopy effect, which could have found stronger consideration in this study. The canopy effect in primate plant foods has been demonstrated to easily exceed 5‰ within the same forest canopy and even within the same tree, mainly depending on stratigraphy/height (Lowry et al. 2021). This variation may explain the noise in the isotopic data within a given orangutan tooth, which lies well within this 5% range, and could easily obscure any possible breastfeeding effect in dental isotope ratios. If the canopy effect may indeed introduce so much noise in the oxygen isotope data, this should be also considered in the use of the data as a climate proxy. The question arises if a terrestrial long-lived mammal species may be a more suitable proxy than an arboreal one.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript provides microprobe serial oxygen isotope data from thin-sectioned modern and fossil orangutan teeth in an effort to reconstruct the seasonality of rainfall in Borneo and Sumatra. The authors also explore the hypothesis that nursing could affect early tooth (first molar) isotope values. They find that all molars yield similar oxygen isotope values and therefore conclude that future research need not exclude the use of first molars. With regard to seasonality, the modern orangutans yield similar results from both islands. The authors suggest differences between modern and fossil orangutan teeth, but the comparisons could be more fully explored.

Strengths:<br /> The study employs a sampling method that captures serial isotope values within thin sections of teeth using a microprobe that provides a much higher resolution than traditional hand-held drilling.

Weaknesses:<br /> The study only examines six modern and six fossil orangutan individuals. Of those, only four modern individuals were samples across multiple molars. The comparisons between modern and fossil teeth are difficult to follow, making unclear the conclusion that climate has changed.

Reviewer #1 (Public Review):

Summary:<br /> Radial spokes (RS) are made of >20 proteins and are believed to be a transducer to coordinate axonemal dyneins to enable the beating motion of motile cilia. While the atomic structure of RS from green algae Chlamydomonas and H. Sapience has been solved by single particle cryo-EM recently, this work by Bicka et al. provided the atomic structure of RS from ciliate Tetrahymena. They identified component proteins of Tetrahymena RS, which correspond to those in the atomic structure of Chlamydomonas and human RS. These proteins were likely already guessed as RS components, based on sequence similarity, but in this work experimentally identified for the first time. Furthermore, they discovered novel isoforms of RS proteins and characterized them structurally and functionally. RSP3 has three isoforms (A, B, and C). They are distributed specifically in the three radial spokes within the repeating unit as proved by mutant analysis, cryo-EM, and proteomics. By high-speed video microscopy, they proved the essential roles of RSP3B for ciliary beating. These isoforms have never been reported in past works and this demonstrates the novelty of this work.

Strength:<br /> Their discovery of RSP3 isoforms is unexpected and, although it is still not clear why Tetrahymena needs to have these isoforms, will evoke future research. The authors characterized the multi-facet aspects of these proteins precisely, structurally by cryo-EM, functionally by waveform and velocity analysis, and in terms of protein networking by co-IP and bioID studies.

Weakness:<br /> While the first half of this manuscript about RSP3 isoforms is very well organized and described (this reviewer still has some advice to make this story convincing and attractive), the later part has room for improvement. Some results are presented in the current manuscript without mentioning figures or tables, for example in "250: The components of the Tetrahymena radial spoke stalks" no figure/table is cited. There is also inconsistency - in 327 RSP9 is mentioned as a MORN protein, but in Fig.6 Sup.3 Table.1, it is mentioned as "unknown".

Reviewer #2 (Public Review):

Summary:<br /> Radial spokes are evolutionarily conserved protein complexes that are important for cilia motility. So far, the composition of certain radial spokes was investigated in the algae Chlamydomonas, mice, and humans. This work by Bicka et al. investigated the composition of radial spokes in the ciliate Tetrahymena by analyzing knockouts and strains that express tagged radial spoke proteins, using mass spectrometry and cryo-electron tomography. While three specific types of radial spokes have been reported thus far, this study suggests that in Tetrahymena, there is another layer to the variability in radial spokes. Additionally, many proteins with predicted enzymatic folds have now been assigned to radial spokes. The comparison of ciliary complexes between species is important to define the basic principles that govern cilia motility, as well as to reveal the differences that enable cilia of various organisms to beat in diverse environments.

Strengths:<br /> The manuscript includes a thorough bioinformatic analysis of radial spoke proteins in Tetrahymena and reveals the presence of multiple orthologs to certain algae and mammalian radial spoke proteins. The mass spectrometry analysis and cryo-electron tomography experiments are solid and informative. This work provides a lot of important data and thus, opens the door to resolve the exact composition and structures of radial spokes in Tetrahymena and perhaps other species.

Weaknesses:<br /> The assignment of the three RSP3 orthologs to RS1, RS2, and RS3 is based only on missing structures in the knockouts. Although this method is informative, it is not sufficient to draw conclusions regarding the positions of the missing proteins. There are numerous examples where a structure was missing, but the absent protein was localized elsewhere (i.e., absence of central pair protrusions in patients with mutations in radial spoke proteins). To directly demonstrate the position of an RSP3 ortholog in a certain radial spoke, the protein can be labeled with a tag that is visualized in subtomogram averages (as was done in Oda et al., 2014 and other studies). Relying on the data from knockouts alone, the model for radial spoke composition in Tetrahymena (Fig. 6) may be incomplete.

The control for the bio-ID experiment was WT cells. Since there are many hits in the experiment, a better control would have been a strain with free BirA, or BirA fused to a protein that is distant from the radial spokes, such as one of the outer-dynein arm proteins, or a ciliary membrane protein.

Reviewer #3 (Public Review):

Summary:<br /> The authors aim to study the role of axoneme radial spoke proteins in forming the three radial spokes that connect the central pair microtubules with the doublet microtubules of the ciliary axoneme. They combined existing and novel mutants to first study ciliary dynamics, followed by cryoET structure and proteomics to identify known and new radial spoke protein components, and assign those with radial spoke(s) to which they belong.

Strengths: / Weaknesses:<br /> The strengths of this study are in the genetic mutants combined with the cryoET to study the unique structural impacts of each mutant on the three radial spokes. The proteomics to study protein loss and interactions also enabled a comprehensive comparison of proteins at the radial spoke under normal and mutant conditions. This allowed the authors to predict that there are several classes of each type of radial spoke. While there are some limitations with overlapping phenotypes between the mutants, this tactic allows the authors to predict known and new proteins that are predicted to localize to each of the three radial spokes. However, in some places, the conclusions are overstated and the list of molecules without functional insight simply identifies new components that will need to be the target of future studies. Two examples of this are that the authors claim to have "solved the composition of individual radial spokes" and that "adenylate kinases [that] dock to specific RSs". Neither of these statements should be made based on the results in this manuscript. Moreover, the authors state that Rsp3Bp does not change in rsp3C knockouts and conclude that Rsp3B from the A-C heterodimer is still attached to the axoneme without maintaining the RS2 structure. To me, this makes a series of strongly stated conclusions without the results to justify the statement. The authors also report on unique features of ciliary dynamics resulting from the loss of each of the three Tetrahymena RSP3 genes. This showed a strong phenotype for rsp3b knockout. However, a quantitative measure of ciliary dynamics to understand how much the presented data represent the ciliary dynamics was not clear. Furthermore, the authors argue that metachrony or coordination between cilia was affected but the presented data are not interpretable or quantified. Furthermore, the authors state that all three Rsp3 paralogs localize along the entire length of the cilium. However, Rsp3A and B do not localize to ciliary tips, while Rsp3C does. This may inform the differences found in the ciliary waveform for rsp3C mutants compared to rsp3A and rsp3B. The authors state that they have defined a "large part of the protein composition of individual RSs...". It is not clear to me that they know how much of the total RS proteome they have identified.

This manuscript identifies new candidate proteins that may function with radial spokes, future work will be required to 1) confirm their localization to the radial spoke and 2) to study their function within radial spokes.

Reviewer #1 (Public Review):

The authors aim to theoretically explain the wide range of time scales observed in cortical circuits in the brain -- a fundamental problem in theoretical neuroscience. They propose that the variety of time scales arises in recurrent neural networks with heterogeneous units that represent neuronal assemblies of different sizes that transition through sequences of high- and low-activity metastable states. When transitions are driven by intrinsically generated noise, the heterogeneity leads to a wide range of escape times (and hence time scales) across units. As a mathematically tractable model, they consider a recurrent network of heterogeneous bistable rate units in the chaotic regime. The model is an extension of the previous model by Stern et al (Phys. Rev. E, 2014) to the case of heterogeneous self-coupling parameters. Biologically, this heterogeneous parameter is interpreted as different assembly sizes. The chaoticity acts as intrinsically generated noise-driving transitions between bistable states with escape times that are indeed widely distributed because of the heterogeneity. The distribution is successfully fitted to experimental data. Using previous dynamic mean-field theory, the self-consistent auto-correlation function of the driving noise in the mean-field model is computed (I guess numerically). This leaves the theoretical problem of calculating escape times in the presence of colored noise, which is solved using the unified colored-noise approximation (UCNA). They find that the log of the correlation time of a given unit increases quadratically with the self-coupling strength of that unit, which nicely explains the distribution of time scales over several orders of magnitude. As a biologically plausible implementation of the theory, they consider a spiking neural network with clustered connectivity and heterogeneous cluster sizes (extension of the previous model by Mazzucato et al. J Neurosci 2015). Simulations of this model also exhibit a quadratic increase in the log dwell time with cluster size. Finally, the authors demonstrate that heterogeneous assemblies might be useful to differentially transmit different frequency components of a broadband stimulus through different assemblies because the assembly size modulates the gain.

I found the paper conceptually interesting and original, especially the analytical part on estimating the mean escape times in the rate network using the idea of probe units and the UCNA. It is a nice demonstration of how chaotic activity serves as noise-driving metastable activity. Calculating the typical time scales of such metastable activity is a hard theoretical problem, for which the authors made considerable advancement. The conclusions of this paper are mostly well supported by simulations and mathematical analysis, but some aspects need to be clarified and extended, especially concerning the biological plausibility of the rate network model and its relation to the spiking neural network model as well as the analytical calculation of the mean dwell time.

1) The theory is based on a somewhat unbiological network of bistable rate units. It seems to only loosely apply to the implementation with a spiking neural network with clustered architecture, which is used as a biological justification of the rate model. In the spiking model, a wide distribution of time scales also emerges as a consequence of noise-induced escapes in combination with heterogeneity. Apart from this analogy, however, the mechanisms for metastability seem to be quite different: firstly, the functional units in the spiking neural network are presumably not bistable themselves but multistability only emerges as a network effect, i.e. from the interaction with other assemblies and inhibitory neurons. (This difference yields anti-correlations between assemblies in the spiking model, in marked contrast to the independence of bistable rate units (if N is large).) Secondly, transitions between metastable states are presumably not driven by chaotic dynamics but by finite-size fluctuations (e.g. Litwin-Kumar & Doiron 2012). The latter is also strongly dependent on assembly size. More precisely, the mechanism of how assembly size shapes escape times T seems to be different: in the rate model the self-coupling ("assembly size") predominantly affects the effective potential, whereas in the spiking network, the assembly size predominantly affects the noise.

Furthermore, the prediction of the rate model is a quadratic increase of log(T), however, the data shown in Fig.5b do not seem to strongly support this prediction. More details and evidence that the data "was best fit with a quadratic polynomial" would be necessary to test the theoretical prediction. Therefore, the correspondence between the rate model and the spiking model should probably be regarded in a looser sense than presented in the paper.

2) The time scale of a bistable probe unit driven by network-generated "noise" is taken to be the mean dwell time T (mean escape time) in a metastable state. It seems that the expressions Eq.4 and Eq.21 for this time are incorrect. The mean dwell time is given by the mean first-passage time (MFPT) from one potential minumum to the opposite one including the full passage across the barrier. At least, the final point for the MFPT should be significantly beyond the barrier to complete the escape. However, the authors only compute the MFPT to a location -x_c slightly before the barrier is reached, at which point the probe unit has not managed to escape yet (e.g. it could go back to -x_2 after reaching -x_c instead of further going to +x_2). It is not clear whether the UCNA can be applied to such escape problems because it is valid only in regions, where the potential is convex, and thus the UCNA may break down near the potential barrier. Indeed, the effective potential is not defined near the barrier (see forbidden zone in Fig.4b), and hence it is not clear how to calculate the mean escape time. Nonetheless, the incomplete MFPT computed by the authors seems to qualitatively predict the dependence on the self-coupling parameter s, at least in the example of Fig.4c. However, if the incomplete MFPT is taken as a basis, then the incomplete MFPT should also be used for the white-noise case for a fair comparison. It seems that the corresponding white-noise case is given by Eq.4 with tau_1=0, which still has the same dependence on the self-coupling s_2, contrary to what is claimed in the paper (it is unclear how the curve for the white-noise case in Fig.4 was obtained). Note that the UCNA has been designed such that it is valid for both small and large tau_1 (thus, it is also unclear why the assumption of large tau_1 is needed).

3) The given argument that the time-scale separation arises as network effect is not very clear. Apart from the issue of a fair comparison of colored and white noise raised in point 1 above, an external colored noise with matched statistics that drives a single bistable unit would yield the same MFPT and thus would be an alternative explanation independent of the network dynamics.

4) The UCNA has assumptions and regimes of validity that are not stated in the paper. In particular, it assumes an Ornstein-Uhlenbeck noise, which has an exponential auto-correlation function, and local stability (region where potential is convex). Because the self-consistent auto-correlation function is generally not exponential and the probe unit also visits regions where the potential is concave, the validity of the UCNA is not clear. On the other hand, the assumption of large correlation time might be dropped as the UCNA's main feature is that it works for both large and small correlation times.

Reviewer #2 (Public Review):

It is well known that introducing clusters in balanced random networks leads to metastable dynamics that potentially span long time scales. The authors build on their previous work (Stern et al. 2014) and here show that the lifetime of metastable states depends on the size of the individual activated clusters. Showing qualitative similarities between clustered spiking networks and networks of bistable rate units, the authors further derive dynamic mean-field predictions for the separation of time scales of the dynamics in relation to differences in the strength of self-couplings in rate networks. Further, they confirm these results in simulations of spiking networks and compare them to time scales observed in the orbitofrontal cortex. Finally, the authors show that assemblies of a particular size (and thus time scale) get entrained by specific external input frequencies, allowing the network to demix temporal signals in a spatial manner.

The manuscript is in general well written and addresses a timely and important topic in neuroscience. However, there are concerns related to the discussion of alternative mechanisms for a large repertoire of time scales as well as the relation between the spiking and rate network model.

Reviewer #1 (Public Review):

In this work, the authors were aiming to probe why enhancers tend to have multiple binding sites for the same transcription factor (TF). As a test bed, they use the snail distal enhancer, which drives a band of expression in the early Drosophila embryo and is composed of multiple, generally weak binding sites for several activating TFs. Using the MS2-MCP reporter system, the authors characterize the live mRNA dynamics driven by the wild-type and mutant enhancers, in which individual or pairs of binding sites have been deleted. They complement these experimental measurements with two computational models - a simple thermodynamic model to explore the cooperativity of TF binding to enhancers and a Hidden Markov Model to analyze the kinetic parameters of their dynamic measurements. The key finding from the experiments is that ablating any of several TF binding sites individually or in pairs dramatically reduces the expression levels, though not the spatial extent, of the snail distal enhancer. This effect holds true in a ~600 bp minimal enhancer and a ~1800 bp extended enhancer. The bulk of this effect is due to a marked decrease in transcriptional amplitude. A simple thermodynamic model confirms the intuition that synergy between the TF binding sites can explain the experimental results and further analysis shows that the modest decline in transcriptional burst duration in mutant enhancers is likely due to more frequent dissociation of the enhancer-promoter complex.

The paper's strengths include the use of well-established measurement and analysis techniques to uncover the surprisingly dramatic effect of single TF binding site mutations, even in the extended enhancer which contains ~20 TF binding sites. This work starts to chip away at the question of why multiple TF binding sites are so frequently observed in enhancers and complement studies of other similar enhancers. It is likely to be of interest to the enhancer biology community. It also sets the stage to explore whether this observation will generalize to other enhancers with different properties, e.g. those with stronger TF binding sites or whose activity is more strongly shaped by repressive TFs.

Reviewer #2 (Public Review):

The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.

How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input transcription traces exhibit a 3-fold amplitude difference. Maybe the authors can clarify these apparent discrepancies.

The authors observe cooperativity between TF binding sites and transcription output, which their model suggests is driven by TF binding cooperativity ("We propose that the cooperativity allows TF binding sites with moderate or weak affinities to recruit more TFs to the enhancer"). This is plausible and likely, but not rigorously demonstrated; another possibility could be cooperativity at the step of transcription activation. One could verify that the binding step is the cooperative one via ChIP-qPCR in the different variants, but given the cautious wording of the paper, this is not absolutely necessary.

Reviewer #1 (Public Review):

In this manuscript, the authors investigated plausible circuit mechanisms for their recently reported effect of NMDAR antagonists on the synchrony of prefrontal neurons in a cognitive task. On the basis of previously proposed computational network models of spiking excitatory and inhibitory neurons and their mean-field and linear stability analysis descriptions, they show that a specific network configuration set close to the onset of instability of the asynchronous state can replicate qualitatively key empirical observations. For such a network, a small increase in external drive causes a large increase in neuronal synchrony, and this is not happening if NMDAR-dependent transmission is reduced. This shows parallelism with the empirical data thus representing its first neural network explanation.

The paper provides valuable insights into possible mechanisms related to cortical dysfunction under NMDAR hypofunction, a topic of importance for several neuropsychiatric disorders. However, the fact that the manuscript remains at a rather abstract level and does not attempt a closer match to the experimental data is a limitation of the study.

1) The manuscript is strongly based on state diagrams and parametric descriptions of neural dynamics in a computational model that has been extensively studied before (Brunel, Wang 2003). Many of the parametric dependencies of this model shown here were already reported before, although not specifically altering concurrently external inputs and NMDAR-dependent transmission as done now. The main novelty of the study is the application of this framework to a specific empirical dataset of great scientific relevance. However, the manuscript emphasizes the model exploration in relation to a limited set of effects in the data (changes in synchrony immediately before motor response) and not so much the comparison to the neural recordings more generally (for instance, firing rates, other time periods in the task, etc.)

2) As discussed in the introduction, empirical data available suggests that 0-lag synchrony in prefrontal networks is affected by manipulations that reduce NMDAR function (Zick et al. 2018) and by manipulations that enhance NMDAR function (Zick et al. 2021). The computational model presented in this manuscript does not show this U-shaped behavior and the discussion does not mention this. It should be discussed whether the model can accommodate this or not.

Reviewer #2 (Public Review):

In this paper, the authors carry out neural circuit modeling to theoretically elucidate the mechanism underlying the empirically observed (in a previous study by some of the current authors) reduction in neural synchrony in the monkey prefrontal cortex (PFC), as a result of NMDAR blockade. Empirically it was previously found that in monkeys performing a cognitive control task, PFC neurons exhibit precisely timed synchronous firing, especially in the short period before the monkey's response, leading to "0-lag" (zero in the 1-2 millisecond timescale) spiking correlations. This signature of synchrony was then found to be extinguished or diminished with the systemic administration of an NMDAR antagonist.

In the current study, the authors simulate and analyze a network of excitatory and inhibitory spiking neurons as a model of a local PFC circuit, to elucidate the mechanism underlying this effect. The model network is composed of leaky integrate-and-fire neurons with conductance-based synaptic inputs and is sparsely and randomly connected as in the classic studies of balanced networks in which neurons fire irregularly as observed in the cortex. Using mean-field theory, the authors start by mapping out the phase boundary between the asynchronous irregular and synchronous irregular states in the network as a function of network parameters controlling synaptic connectivity and external background inputs (which they parametrize as ratios of recurrent or external currents mediated by AMPAR, NMDAR or GABAA). The transition between the two phases corresponds to a Hopf-like bifurcation above which synchronous oscillations with frequency in the gamma-band (or above) emerge. It is found that with an increase in external inputs, a network in the asynchronous state (but close to criticality) can switch to the synchronous state. Based on this, the authors hypothesize that an increase in the external drive is the mechanism underlying the empirically observed increase in synchrony before the behavioral response. It is then shown that a reduction in NMDAR conductance (keeping AMPAR or GABAR conductances fixed) has the opposite effect, and pushes the network towards the asynchronous state, and can counteract or weaken the effect of increased external input. In both cases increase or decrease in synchrony is quantified by an increase or decrease in 0-lag pairwise correlations; transition to synchrony is shown to also lead to the development of nonzero-lag peaks in the average spiking correlation reflecting gamma-band oscillations. The authors then show that (with the appropriate choice of primary network parameters) their proposed mechanisms for the (natural) increase in synchrony via an increase in external inputs and the weakening of this effect with the weakening of NMDA conductances do semi-quantitatively match the observed changes in 0-lag synchrony and nonzero lag peaks in spiking correlations. Finally, they discuss the effect of the balance between average NMDA and GABA currents in the primary (baseline) network on the above effects.

Strengths:<br /> - The modeling and analysis are solid and overall this work succeeds in providing a convincing mechanistic explanation for the specific empirically observed effects in monkey PFC: the natural task-dependent modulation of 0-lag synchrony and its extinction with NMDA blockage.

- The manuscript is very readable and the figures and plots are clearly described.

- The mathematical mean-field analysis in the Methods section is also sound and well written and does/can (see below) provide a sufficient mathematical explanation of the simulation results.

Weaknesses:<br /> 1) I found the intuitive explanation of the effects of external input or NMDAR conductance on synchrony incomplete. While simulations and mean-field analysis both predict this effect, the mean-field theory and the linearization analysis and stability analysis can be used to further shed light on the precise mechanism by which external input and NMDAR conductance promote synchrony (or destabilization of the asynchronous state).

2) An important natural question (which is relevant to the connection with schizophrenia) is what are the distinct roles of AMPAR-based and NMDAR-based excitation on the transition to synchrony, and this is not addressed in this study. It would be important to clarify what is special/distinct about NMDAR in the current findings.

3) In the Introduction and Discussion, the authors speculate on the possible connection between their empirical and theoretical findings (on the effect of NMDAR hypofunction on synchronous spiking) and the pathogenesis of schizophrenia. While this is not central to the findings of the paper, because it is relevant to the broader significance and impact of this work I will note the following. Their proposed specific link to pathogenesis is as follows: the reduction in precisely timed synchrony resulting from NMDAR hypofunction can disrupt spike-timing dependent plasticity (STDP) and lead to "disconnection" of cortical circuits as observed in schizophrenia. Letting aside the fact that observations in schizophrenia relate to functional connectivity and not synaptic connectivity, previous theoretical studies of STDP in spiking networks do not support the claim that lack of synchronous activity would lead to disconnection of the circuit.

Reviewer #3 (Public Review):

The starting point of the paper is the observation by the group of Matthew Chafee that zero-lag correlations in pairs of prefrontal cortex neurons transiently increase close to the motor response in a dot-pattern expectancy task', and that this increase in synchrony is abolished by NMDA blockers. The goal of this paper is to understand the mechanisms of this NMDA-dependent increase in synchrony using computational modeling. They simulate and analyze a network of sparsely connected spiking neurons in which synaptic interactions are mediated by AMPA, NMDA, and GABA conductances with realistic time constants. In this network, it had been shown previously that when parameters are such that the network is close to a bifurcation separating asynchronous from synchronous oscillatory states, an<br /> increase in external inputs can push the network towards synchrony. They show that when the NMDA component of synaptic inputs is removed, the network moves away from the bifurcation, and thus the same increase in external inputs no longer leads to a significant increase in synchronization.

Thus, this study provides a potential explanation for the NMDA-dependent increase of synchrony observed in their data. The authors further argue that this effect might be responsible for symptoms observed in schizophrenia, through spike-timing-dependent mechanisms. Overall, this is an interesting study, but there are<br /> several weaknesses that dampened my initial enthusiasm: In particular, the model predicts a tight link between synchrony and mean firing rate that should hold during the whole task, not only at the time of the motor response but this is not explored by the authors.

Also, the relationship between changes in synchrony due to NMDAR dysfunction and schizophrenia is not very convincing. Many forms of synaptic plasticity, including STDP are dependent on NMDA receptors, and thus synaptic plasticity in schizophrenic patients is likely to be impacted independently of any synchrony. Thus, the link between the results of this paper and schizophrenia seems tenuous.

Reviewer #1 (Public Review):

Esmaily and colleagues report two experimental studies in which participants make simple perceptual decisions, either in isolation or in the context of a joint decision-making procedure. In this "social" condition, participants are paired with a partner (in fact, a computer), they learn the decision and confidence of the partner after making their own decision, and the joint decision is made on the basis of the most confident decision between the participant and the partner. The authors found that participants' confidence, response times, pupil dilation, and CPP (i.e. the increase of centro-parietal EEG over time during the decision process) are all affected by the overall confidence of the partner, which was manipulated across blocks in the experiments. They describe a computational model in which decisions result from a competition between two accumulators, and in which the confidence of the partner would be an input to the activity of both accumulators. This model qualitatively produced the variation in confidence and RTs across blocks.

The major strength of this work is that it puts together many ingredients (behavioral data, pupil and EEG signals, computational analysis) to build a picture of how the confidence of a partner, in the context of joint decision-making, would influence our own decision process and confidence evaluations. Many of these effects are well described already in the literature, but putting them all together remains a challenge. However, the construction is fragile in many places: the causal links between the different variables are not firmly established, and it is not clear how pupil and EEG signals mediate the effect of the partner's confidence on the participant's behavior.

Finally, one limitation of this setting is that the situation being studied is very specific, with a joint decision that is not the result of an agreement between partners, but the automatic selection of the most confident decisions. Thus, whether the phenomena of confidence matching also occurs outside of this very specific setting is unclear.

Reviewer #2 (Public Review):

This study is impressive in several ways and will be of interest to behavioral and brain scientists working on diverse topics.

First, from a theoretical point of view, it very convincingly integrates several lines of research (confidence, interpersonal alignment, psychophysical, and neural evidence accumulation) into a mechanistic computational framework that explains the existing data and makes novel predictions that can inspire further research. It is impressive to read that the corresponding model can account for rather non-intuitive findings, such as that information about high confidence by your collaborators means people are faster but not more accurate in their judgements.

Second, from a methodical point of view, it combines several sophisticated approaches (psychophysical measurements, psychophysical and neural modelling, electrophysiological and pupil measurements) in a manner that draws on their complementary strengths and that is most compelling (but see further below for some open questions). The appeal of the study in that respect is that it combines these methods in creative ways that allow it to answer its specific questions in a much more convincing manner than if it had used just either of these approaches alone.

Third, from a computational point of view, it proposes several interesting ways by which biologically realistic models of perceptual decision-making can incorporate socially communicated information about other's confidence, to explain and predict the effects of such interpersonal alignment on behavior, confidence, and neural measurements of the processes related to both. It is nice to see that explicit model comparison favor one of these ways (top-down driving inputs to the competing accumulators) over others that may a priori have seemed more plausible but mechanistically less interesting and impactful (e.g., effects on response boundaries, no-decision times, or evidence accumulation).

Fourth, the manuscript is very well written and provides just the right amount of theoretical introduction and balanced discussion for the reader to understand the approach, the conclusions, and the strengths and limitations.

Finally, the manuscript takes open science practices seriously and employed preregistration, a replication sample, and data sharing in line with good scientific practice.

Having said all these positive things, there are some points where the manuscript is unclear or leaves some open questions. While the conclusions of the manuscript are not overstated, there are unclarities in the conceptual interpretation, the descriptions of the methods, some procedures of the methods themselves, and the interpretation of the results that make the reader wonder just how reliable and trustworthy some of the many findings are that together provide this integrated perspective.

First, the study employs rather small sample sizes of N=12 and N=15 and some of the effects are rather weak (e.g., the non-significant CPP effects in study 1). This is somewhat ameliorated by the fact that a replication sample was used, but the robustness of the findings and their replicability in larger samples can be questioned.

Second, the manuscript interprets the effects of low-confidence partners as an impact of the partner's communicated "beliefs about uncertainty". However, it appears that the experimental setup also leads to greater outcome uncertainty (because the trial outcome is determined by the joint performance of both partners, which is normally reduced for low-confidence partners) and response uncertainty (because subjects need to consider not only their own confidence but also how that will impact on the low-confidence partner). While none of these other possible effects is conceptually unrelated to communicated confidence and the basic conclusions of the manuscript are therefore valid, the reader would like to understand to what degree the reported effects relate to slightly different types of uncertainty that can be elicited by communicated low confidence in this setup.

Third, the methods used for measurement, signal processing, and statistical inference in the pupil analysis are questionable. For a start, the methods do not give enough details as to how the stimuli were calibrated in terms of luminance etc so that the pupil signals are interpretable. Moreover, while the authors state that the traces were normalized to a value of 0 at the start of the ITI period, the data displayed in Figure 2 do not show this normalization but different non-zero values. Are these data not normalized, or was a different procedure used? Finally, the authors analyze the pupil signal averaged across a wide temporal ITI interval that may contain stimulus-locked responses (there is not enough information in the manuscript to clearly determine which temporal interval was chosen and averaged across, and how it was made sure that this signal was not contaminated by stimulus effects).

Fourth, while the EEG analysis in general provides interesting data, the link to the well-established CPP signal is not entirely convincing. CPP signals are usually identified and analyzed in a response-locked fashion, to distinguish them from other types of stimulus-locked potentials. One crucial feature here is that the CPPs in the different conditions reach a similar level just prior to the response. This is either not the case here, or the data are not shown in a format that allows the reader to identify these crucial features of the CPP. It is therefore questionable whether the reported signals indeed fully correspond to this decision-linked signal.

Fifth, the authors present some effective connectivity analysis to identify the neural mechanisms underlying the possible top-down drive due to communicated confidence. It is completely unclear how they select the "prefrontal cortex" signals here that are used for the transfer entropy estimations, and it is in fact even unclear whether the signals they employ originate in this brain structure. In the absence of clear methodical details about how these signals were identified and why the authors think they originate in the prefrontal cortex, these conclusions cannot be maintained based on the data that are presented.

Sixth, the description of the model fitting procedures and the parameter settings are missing, leaving it unclear for the reader how the models were "calibrated" to the data. Moreover, for many parameters of the biophysical model, the authors seem to employ fixed parameter values that may have been picked based on any criteria. This leaves the impression that the authors may even have manually changed parameter values until they found a set of values that produced the desired effects. The model would be even more convincing if the authors could for every parameter give the procedures that were used for fitting it to the data, or the exact criteria that were used to fix the parameter to a specific value.

Seventh, on a related note, the reader wonders about some of the decisions the authors took in the specification of their model. For example, why was it assumed that the parameters of interest in the three competing models could only be modulated by the partner's confidence in a linear fashion? A non-linear modulation appears highly plausible, so extreme values of confidence may have much more pronounced effects. Moreover, why were the confidence computations assumed to be finished at the end of the stimulus presentation, given that for trials with RTs longer than the stimulus presentation, the sensory information almost certainly reverberated in the brain network and continued to be accumulated (in line with the known timing lags in cortical areas relative to objective stimulus onset)? It would help if these model specification choices were better justified and possibly even backed up with robustness checks.

Eight, the fake interaction partners showed several properties that were highly unnatural (they did not react to the participant's confidence communications, and their response times were random and thus unrelated to confidence and accuracy). This questions how much the findings from this specific experimental setting would transfer to other real-life settings, and whether participants showed any behavioral reactions to the random response time variations as well (since several studies have shown that for binary choices like here, response times also systematically communicate uncertainty to others). Moreover, it is also unclear how the confidence convergence simulated in Figure 3d can conceptually apply to the data, given that the fake subjects did not react to the subject's communicated confidence as in the simulation.

Joint Public Review

This manuscript utilizes Drosophila melanogaster as a model system to functionally characterize the role of genes previously associated with obstructive pulmonary disease (COPD) in epithelial barrier function. Using genetic and imaging approaches, the authors characterised a previously unrecognised role of intestinal Acetylcholine receptor (AchR) signalling, in the regulation of epithelial barrier function. The working model proposes that Acetylcholine (Ach) produced by enteroendocrine cells (EEs) and enteric neurons signals to AchR in enterocytes (ECs). This signalling activates the secretion of the Peritrophic membrane (PM) through the regulation of the exocytic protein Syt4. In this way, Ach/AchR signalling works to protect epithelial barrier function and organismal tolerance to ingested damaging agents, such as those causing oxidative stress.

Overall, the data presented support the main model of the paper: EC AchR activation is necessary to maintain epithelial barrier function. The evidence, however, on the mechanisms downstream of AchR, namely, the involvement of this signalling pathway in the regulation of Syt4 is weak.

The work in this manuscript represents an important proof of concept for the use of the Drosophila midgut as a model to functionally interrogate genes from human genetic association studies in pathologies affecting epithelial homeostasis.

Reviewer #1 (Public Review):

Mano et. al. use a combination of behavioral, genetic silencing, and functional imaging experiments to explore the temporal properties of the optomotor response in Drosophila. They find a previously unreported inversion of the behavior under high contrast and luminance conditions and identify potential pathways mediating the effect.

Strengths:<br /> Quantifications of optomotor behavior have been performed for many decades. Despite a large number of previous studies, the authors still find something fundamentally novel: under high contrast conditions and extended stimulation periods, the behavior becomes dynamic over time. The turning response shows an initial transient positive following response. The amplitude of the behavior then decreases and even inverts such that animals show an anti-directional rotation response. The authors systematically explore the stimulation feature space, including large ranges of spatial and temporal frequencies and conditions with high and low contrast. They also test two wild-type fly species and even compare experiments across two different labs and setups. From these data, it seems clear that the behavior is robust and largely depends on the brightness of the stimulation, rearing conditions, and genetic background. The authors discuss that these effects have not clearly been reported elsewhere beforehand, and convincingly argue why this may be the case.

In general, the presented behavioral quantifications illustrate the importance of further experimental studies of the temporal dynamics of behavior in response to dynamically varying stimulus features, across different stimulus types, genetic backgrounds, and model animal systems. It also illustrates the importance of relating the conditions that animals experience in the laboratory to the ones they would experience in the wild. As the authors mention, the brightness during a sunny day can reach values as high as 4000 cd/m2, while experimental stimulation in the lab has so far often been orders of magnitude below that.

The study then systematically explores potential neural elements involved in the behavior. Through a set of silencing experiments, they find that T4 and T5 neurons, as expected, are required for motion behaviors. On the other hand, silencing HS cells largely abolishes the 'classical' syn-directional response but leaves anti-directional turning intact. On the other hand, silencing CH cells abolishes the anti-directional response but leaves the syn-directional behavior intact. Through functional imaging in T4, T5, HS, and CH neurons, the authors could show that none of these neurons shows a response inversion depending on contrast level. Together, these experiments nicely illustrate that the dynamics do not seem to be computed within the early parts of visual processing, but they must happen on the level of the lobula plate or further downstream.

Weaknesses:<br /> While the authors have already explored various parameters of the experiment, it would have been nice to see additional experiments regarding the initial adaptation phase. The experiments in Figure 2e, where the authors show front-to-back or back-to-front gratings before the rotation phase, are a good start. What would the behavioral dynamics look like if they had exposed animals to long periods of static high or low contrast gratings, whole field brightness, or darkness? Such experiments would surely help to better understand the stimulus features on which the adaptation elements operate. It would be interesting to explore to what degree such static stimuli impact the subsequent behavioral dynamics.

Given the dynamics of the behavior, it would probably also be worth looking at the turning dynamics after the stimulus has stopped. If direction-selective adaptation mechanisms are regulating the turning response, one may find long-lasting biases even in the absence of stimulation. If the authors have more data after the stimulus end, it would be good to further expand the time range by a few seconds to show if this is the case or not (for example, in Figure 1b).

Another important experiment could be to initially perform experiments in a closed-loop configuration, and then quickly switch to open-loop. The closed-loop configuration should allow the motion computing circuitry to adapt to the chosen environmental conditions. Explorations of the changes in turning response dynamics after such treatments should then enable further dissections of the mechanisms of adaptation. Closed-loop experiments under different contrast conditions have already been performed (for example, Leonhardt et al. 2016), which also showed complex response dynamics after stimulus on- and offset. It would be great to discuss the current open-loop experiments, and maybe some new closed-loop results, in relation to the previous work.

The authors mention the different rearing conditions, and there is one experiment in Figure S2 which mentions running experiments at 25 deg C. But it is not clear from the Methods at which temperature all other experiments have been performed. It is also not clear at which temperature the shibire block experiments were performed. As such experiments require elevated temperatures, I assume that all behavioral experiments have been performed at such levels? How high were those?

What does the fly see before and after the stimulus (i.e. the gray boxes in all figures)? Are these periods of homogenous gray levels or are these non-moving gratings with the luminance and contrast of the subsequent stimulus? It would be important to add this information to the methods and to the figure illustrations or legends.

It would be nice to discuss the potential location where the motion adaptation may be implemented in the brain. A small model scheme as an additional figure could further help to discuss how such computations may be mechanistically implemented, helping readers to think about future experimental dissections of the behavior.

For setting up similar experiments in other labs, the authors need to better describe how they measured the luminance of the arena. Do they simply report the brightness delivered by the Lightcrafter system, or did they measure this with a lux-meter? If so, at which distance was the measurement performed and with which device? Given that the behavior is sensitive to the specific properties of the stimulus, it will be important to report these numbers carefully to enable other groups to reproduce effects.

Reviewer #2 (Public Review):

This study looks at how optomotor turning in fruit flies varies with stimulus conditions. Although the response has usually been observed in the same direction of rotation as the stimulus, they find that in many situations the flies turn strongly in the opposite direction to the stimulus. This 'anti-directional' turning increases with stimulus brightness, contrast, and duration of the stimulus, and also varies with many factors such as rearing temperature, lab, strain, and developmental stage. They show that the anti-directional response depends on neurons in the visual system that are also important for the more standard response, but they don't find clear changes in the activity of these neurons that could explain the directional switch. The main conclusion is that supposedly simple behaviors may be more complicated than they first appear, and careful consideration needs to be given to the precise stimulus conditions and the response dynamics when measuring such behaviors, and especially when comparing data across labs.

Reviewer #1 (Public Review):

In this work, Cheikh et al. develop a novel method to probe tissue mechanics in vivo, with particular application to the early Drosophila embryo. The method is based on filling a pulled micropipette with a mixture of fluorescent dye and PDMS, which is cured and allowed to harden. Etching away the tip of the glass micropipette leaves exposed the PDMS core, which, like the bristles held in a brush handle, is easily deformed. Calibration of the stiffness of the PDMS tip allows for direct measurement of forces through the tip displacement. Apart from the particular application here, this method should prove to be widely useful in biological physics.

The authors then inserted this force probe into Drosophila embryos at the stage when cellularization has occurred, and demonstrate the ability to deform the tissue (visualized by fluorescently labelled cell walls). Crucially, the time course of the deformation can be controlled by the rate at which the pipette is translated, allowing for the study of potential viscous or viscoelastic effects.

The authors find from their experiments and extensive computational analysis of mechanical models of the embryo that there must be a significant difference between the mechanical properties of the apical and basal sides of the tissue.

This is a very well executed paper that provides compelling evidence for the utility of the experimental method and the particular issues in Drosophila mechanics. A strength of the paper is the clear and simple focus on a particular deformation and its experimental and theoretical analysis. The computational section is a bit less clearly connected to the observations, in the sense that some kind of very simplified model incorporating the apicobasal differences is lacking.

Reviewer #2 (Public Review):

This is a very interesting study with a potential impact on understanding the 3D mechanics of cells in epithelia. The assay that the authors developed is novel and quite useful for future studies. However, I was hoping to see more experimental results in the manuscript. For example, there is a zoo of mutants that the community speculates about possible mechanical changes in cells. I was hoping to see if the authors can settle some of these arguments by using their novel technique and analysis.

Reviewer #1 (Public Review):

In this study, the authors investigate the interactions between Plasmodium falciparum RH5, an essential ligand mediating erythrocyte invasion by the malaria parasite, and its cognate receptor basigin. Based on published observations that basigin forms complexes with the plasma membrane Ca2+-ATPase PMCA1/4 or monocarboxylate transporter MCT1, the authors asked whether RH5 can interact with basigin complexed with PMCA or MCT1, whether this modulates the function of PMCA and whether these interactions may explain the mechanism of action of neutralising antibodies targeting RH5. The objectives and rationale of the study are very clear.

Using size exclusion chromatography, 2D blue native PAGE, antibody shift, and depletion assays, the authors demonstrate that native basigin in human erythrocytes is essentially found in heteromeric complexes with either PMCA4 or MCT1. They measured the binding of PfRH5 to purified basigin-PMCA and basigin-MCT1 complexes by surface plasmon resonance and found that RH5 interacts with complexed basigin with higher affinity than with isolated basigin. RH5 did not alter the ATPase activity of PMCA, either in purified PMCA-basigin complexes or in CHO cells expressing human basigin and PMCA4, leading the authors to rule out RH5-mediated alteration of PMCA-mediated calcium export as a mechanism underlying the changes in calcium flux at the interface between the erythrocyte and the invading parasite. Finally, the authors used structural modelling to show that growth-inhibitory antibodies sterically block the binding of RH5 to basigin-PMCA and basigin-MCT1 complexes, providing a molecular explanation for why most potent anti-RH5 neutralising antibodies do not prevent RH5 binding to isolated basigin.

The paper is well-written and the claims are well-supported by the data. The study provides new insight into an essential interaction during blood-stage malaria and reveals the mode of action of growth-inhibitory antibodies, with potential implications for the design of RH5-based malaria vaccines. The study does not address whether PMCA and MCT1 are required during erythrocyte invasion by P. falciparum merozoites, and does not provide direct evidence to completely rule out a role of RH5-PMCA interaction in calcium flux modulation in the context of erythrocyte invasion by the parasite.

Reviewer #2 (Public Review):

Plasmodium falciparum RH5 (PfRH5) is an integral membrane protein of P. falciparum merozoites that acts as an essential ligand involved in host erythrocyte invasion, functioning by binding to the erythrocyte surface protein basigin. Previous work by the authors of this study and other groups has demonstrated that antibodies to PfRH5 can block invasion and can be protective in in vivo challenge studies, so PfRH5 is a promising malaria vaccine candidate. This study by Jamwal et al addresses the paradoxical observation, made in earlier work by these authors, that certain antibodies to PfRH5 efficiently inhibit parasite invasion of erythrocytes yet does not block the binding of PfRH5 to recombinant basigin ectodomain. The authors first demonstrate through a range of approaches that most native erythrocyte basigin is expressed in the form of detergent-stable complexes with one of two distinct erythrocyte membrane proteins, plasma membrane calcium ATPase (PMCA) or monocarboxylate transporter (MCT). Using in vitro biophysical techniques, they then show that recombinant PfRH5 binds more tightly (and with slower off-rates) to the native basigin-PMCA or basigin-MCT1 complexes than to the isolated recombinant basigin ectodomain. Finally and crucially, the authors then show that 2 of these known invasion-inhibitory anti-PfRH5 antibodies (called R5.016 and 9AD4) that do not block the interaction between recombinant basigin and PfRH5 do in contrast block the interaction between PfRH5 and basigin-PMCA and basigin-MCT1 complexes. By docking known atomic structures of the R5.016 and 9AD4 Fab-basigin structures onto the known or modelled basigin complex structures, the authors present a convincing argument that the invasion-inhibitory antibodies function through steric hindrance, preventing PfRH5 binding to the basigin-PMCA or basigin-MCT1 complexes. The work provides a rational explanation for the invasion-inhibitory activity of this class of PfRH5-specific antibodies and demonstrates the potential complexity underlying the mode of action of invasion-inhibitory anti-malarial antibodies.

Reviewer #3 (Public Review):

Higgins et al. examine the interaction between erythrocyte basigin and malaria parasite RH5. They use sophisticated biochemical and biophysical studies to establish that basigin on erythrocyte membranes exists primarily in association with either MCT1 or PMCA4b, that these complexes facilitate tighter binding of RH5 to basigin, and that RH5-basigin interaction does not appear to change the activity of the PMCA4b Ca++ pump. They determine that some antibodies that interfere with RH5-basigin interaction to interfere with the pathogen's entry into erythrocytes are effective only when tested in the presence of MCT1 or PMCA4b association. The studies are rigorously performed and have the potential to guide the development of better vaccines that block this invasion process.

Reviewer #1 (Public Review):

Summary:<br /> The study assesses the impact of testing contacts of cases in school classes when identified, rather than at the end of quarantine, on various outcomes such as secondary infections, tracing delay, and identification of the possible source of infection. The authors find that the intervention likely reduced tracing delay and increased the number of possible infection sources. However, due to unmeasured confounding, it remains unclear if secondary transmission actually decreased. The analysis requires clarification and further explanation in parts.

Major strengths and weaknesses:<br /> The study benefits from the assessment of various outcomes in contact tracing in addition to changes in transmission, such as tracing delay, and the identification of putative infectors; however the assumption that other cases found in households are infectors of the index case rather than putative infectees, may introduce significant bias, but this is not mentioned in the Discussion despite being significant. It is difficult to understand the intervention in Figure 1 due to unclear labelling and incomplete descriptions in the caption. The authors mention that the same school class could be included multiple times for multiple outbreaks - was there a time cutoff for inclusion? I had a lot of trouble interpreting or reproducing the values given in Table 1. Firstly, the methods used to produce the RRs given are not described in the methods section of the paper. What are the outcomes - "classes" and "indexes" are poroly defined. Is this output from univariate or multivariate regression model, and what is the link function? I was also unable to reproduce the RRs listed in the table despite attempting several methods. The closest numbers I achieved were by crudely dividing the risks (e.g. for the RR for known infection source I took the ratio of indexes for which a school contact was suspected pre and post-intervention (644/1175)/(146/429) = 1.61), but if this is the case then the unknown class is by definition not the reference category. This is the same for the other RRs stated in the table. The methods used should be clarified and results updated if erroneous. The mediation analysis components and their relevance to the study could be better explained in the methods and results.

Achievement of aims and support for conclusions:<br /> The authors partially achieved their aims by demonstrating a likely decrease in tracing delay and an increase in possible infection sources. However, the study's inability to determine if secondary transmission decreased due to unmeasured confounding limits the conclusiveness of the findings. The authors should reiterate the main numerical results in the first few paragraphs of the discussion.

Impact on the field and utility of methods and data:<br /> This study has the potential to impact the field by highlighting the benefits of testing contacts earlier in school classes. The findings on reduced tracing delay and increased identification of infection sources can inform future strategies and interventions. However, clarity on the analysis methods, as well as the results, are necessary to ensure the utility and reliability of the findings.

Reviewer #2 (Public Review):

This is a review of "Effect of an enhanced public health contact tracing intervention on the secondary transmission of SARS-CoV-2 in educational settings: the four-way decomposition analysis", by Djuric et al.

In late 2020, a province in northern Italy implemented a new testing regimen for all contacts of people known to have COVID-19, offering them SARS-CoV-2 testing immediately after the detection of the index case instead of at the end of a quarantine period. The authors of this study investigated whether this policy change reduced secondary transmission of SARS-CoV-2 in schools. In addition to studying this primary outcome, they examined two "process" outcomes; whether this policy of testing earlier enabled public health officials to more successfully identify the source of infection of the index case, and if the time interval from detection of the index case to testing of contacts in the educational setting reduced.

They concluded that the time between detection of the index case and testing of contacts did reduce before and after the policy change. Similarly, the proportion of cases for which the source of infection was identified also increased after the policy change. Both of these "process" indicators correlated with reduced secondary transmission, though only identifying the source of infection was associated with a statistically significant (at the 5% level) reduction in secondary transmission.

Strengths of this paper

Educational settings experienced significant disruption during the COVID-19 pandemic, and efforts to better understand the spread of SARS-CoV-2 in schools - and how to mitigate this spread - are of significant public health importance. This paper, therefore, addresses an important topic.

Additionally, the authors describe a detailed dataset comprising case and contact tracing data from over 1,600 index cases with in-school contacts. The richness of the data described in Table 1 provides a good opportunity to conduct a natural experiment on the potential impact of testing contacts immediately after exposure on secondary transmission. The authors also appropriately acknowledge that this interrupted time series study would be insufficient to provide causal information, given the potential for confounders.

Finally, the primary statistical method (a four-way decomposition analysis) was new to me, but - from the references cited - seems appropriate. Given the relative novelty of this method, more space could be dedicated to explaining it in the methods.

Weakness of this paper

Although the paper tackles an important topic with an appropriate dataset, the analyses feel insufficient to fully support the authors' conclusions.

First and most critically, it is difficult to understand exactly what the primary outcome of the study is. Both the median number of secondary cases per class and the proportion of classes that experienced any secondary transmission are presented in Table 1, but - at least in the unadjusted analyses - point in different directions regarding the impact of the effect of the intervention (albeit neither strongly). For example, before the policy change, the median number of secondary cases per index case is 2, while after the policy change, it has reduced to 1. In contrast, before the policy change 37% of classes experienced any secondary transmission, but after the policy change, this had increased to 39% of classes. In some of the adjusted analyses, "number of secondary cases" is stated as the outcome variable, but that is not fully defined. The "attack rate", which is well defined in the methods, could be one option for use as a consistent primary outcome, however, it is only provided for the total study population and the attack rates pre- or post-policy change are not presented or compared.

Additionally, although using a "process measure" as a secondary outcome could be valuable - especially in a natural experiment like this, where identifying a causal relationship with a complex outcome like secondary transmission will be difficult - it was somewhat unclear how the process measures described in this study were measured, or their validity. For example, the reduced time between detection of the index case and testing of contacts seems unsurprising, since the intervention itself is to test contacts immediately after the index case is identified. Additionally, the results describe reductions in median testing delay and median tracing delay, but only testing delay is defined in the methods.

Finally, there is existing published literature that provides additional context on the impact of testing on secondary transmission within schools that arguably provides a higher level of evidence than the current study, but is not cited by the authors. A key limitation of this study - which the authors acknowledge - is the interrupted time series nature of their study, which is open to confounding by other important factors that happened at the same time, including but not limited to: changes in overall incidence of COVID-19; viral evolution (e.g. the emergence of the Alpha variant (B.1.1.7) which occurred during this study and which significantly altered the risk of secondary transmission); the efficiency of the contact tracing system (including skill and size of the contact tracing workforce); and the availability of non-molecular diagnostic tests (e.g. lateral flow devices) that might allow individuals to change their behaviors even without enrolling in this study. Examples of alternative studies which might reduce some of this potential confounding include around 400 schools in Los Angeles County, California, USA, that implemented "test to stay" in 2021 and were compared to 1,600 schools that did not implement "test to stay" [https://www.cdc.gov/mmwr/volumes/70/wr/mm705152e1.htm] and a cluster-randomized trial of daily testing of exposed contacts to study in-school transmission in England, UK, also in 2021 [https://www.sciencedirect.com/science/article/pii/S0140673621019085]. Although these examples describe slightly different interventions involving enhanced testing of exposed contacts, they both compared educational settings with and without the intervention across the same time periods; and the UK study in particular has methodological advantages over this current paper, including randomization. While the findings in the current paper did not contradict these earlier, stronger papers, the example from this province should be placed in context with the totality of evidence around testing in schools.

Reviewer #1 (Public Review):

Briggs et al use a combination of mathematical modelling and experimental validation to tease apart the contributions of metabolic and electronic coupling to the pancreatic beta cell functional network. A number of recent studies have shown the existence of functional beta cell subpopulations, some of which are difficult to fully reconcile with established electrophysiological theory. More generally, the contribution of beta cell heterogeneity (metabolism, differentiation, proliferation, activity) to islet function cannot be explained by existing combined metabolic/electrical oscillator models. The present studies are thus timely in modelling the islet electrical (structural) and functional networks. Importantly, the authors show that metabolic coupling primarily drives the islet functional network, giving rise to beta cell subpopulations. The studies, however, do not diminish the critical role of electrical coupling in dictating glucose responsiveness, network extent as well as longer-range synchronization. As such, the studies show that islet structural and functional networks both act to drive islet activity, and that conclusions on the islet structural network should not be made using measures of the functional network (and vice versa).

Strengths:

- State-of-the-art multi-parameter modelling encompassing electrical and metabolic components.

- Experimental validation using advanced FRAP imaging techniques, as well as Ca2+ data from relevant gap junction KO animals.

- Well-balanced arguments that frame metabolic and electrical coupling as essential contributors to islet function.

- Likely to change how the field models functional connectivity and beta cell heterogeneity.

Weaknesses:

- Limitations of FRAP and electrophysiological gap junction measures not considered.

- Limitations of Cx36 (gap junction) KO animals not considered.

- Accuracy of citations should be improved in a few cases.

Reviewer #2 (Public Review):

In their present work, Briggs et al. combine biophysical simulations and experimental recordings of beta cell activity with analyses of functional network parameters to determine the role played by gap-junctional coupling, metabolism, and KATP conductance in defining the functional roles that the cells play in the functional networks, assess the structure-function relationship, and to resolve an important current open question in the field on the role of so-called hub cells in islets of Langerhans.

Combining differential equation-based simulations on 1000 coupled cells with demanding calcium, NAPDH, and FRAP imaging, as well as with advanced network analyses, and then comparing the network metrics with simulated and experimentally determined properties is an achievement in its own right and a major methodological strength. The findings have the potential to help resolve the issue of the importance of hub cells in beta cell networks, and the methodological pipeline and data may prove invaluable for other researchers in the community.<br /> However, methodologically functional networks may be based on different types of calcium oscillations present in beta cells, i.e., fast oscillations produced by bursts of electrical activity, slow oscillations produced by metabolic/glycolytic oscillations, or a mixture of both. At present, the authors base the network analyses on fast oscillations only in the case of simulated traces and on a mixture of fast and slow oscillations in the case of experimental traces. Since different networks may depend on the studied beta cell properties to a different extent (e.g., fast oscillation-based networks may, more importantly, depend on electrical properties and slow oscillation-based networks may more strongly depend on metabolic properties), it is important that in drawing the conclusions the authors separately address the influence of a cell's electrical and metabolic properties on its functional role in the network based on fast oscillations, slow oscillations, or a mixture of both.

Reviewer #3 (Public Review):

Over the past decade, novel approaches to understanding beta cell connectivity and how that contributes to the overall function of the pancreatic islet have emerged. The application of network theory to beta cell connectivity has been an extremely useful tool to understand functional hierarchies amongst beta cells within an islet. This helps to provide functional relevance to observations from structural and gene expression data that beta cells are not all identical.

There are a number of "controversies" in this field that have arisen from the mathematical and subsequent experimental identification of beta "hub" cells. These are small populations of beta cells that are very highly connected to other beta cells, as assessed by applying correlation statistics to individual beta cell calcium traces across the islet.

In this paper Briggs et al set out to answer the following areas of debate:<br /> 1. They use computational datasets, based on established models of beta cells acting in concert (electrically coupled) within an islet-like structure, to show that it is similarities in metabolic parameters rather than "structural" connections (ie proximity which subserves gap junction coupling) that drives functional network behaviour. Whilst the computational models are quite relevant, the fact that the parameters (eg connectivity coefficients) are quite different to what is measured experimentally, confirm the limitations of this model. Therefore it was important for the authors to back up this finding by performing both calcium and metabolic imaging of islet beta cells. These experimental data are reported to confirm that metabolic coupling was more strongly related to functional connectivity than gap junction coupling. However, a limitation here is that the metabolic imaging data confirmed a strong link between disconnected beta cells and low metabolic coupling but did not robustly show the opposite. Similarly, I was not convinced that the FRAP studies, which indirectly measured GJ ("structural") connections were powered well enough to be related to measures of beta cell connectivity.<br /> 2. The group goes on to provide further analytical and experimental data with a model of increasing loss of GJ connectivity (by calcium imaging islets from WT, heterozygous (50% GJ loss), and homozygous (100% loss). Given the former conclusion that it was metabolic not GJ connectivity that drives small world network behaviour, it was surprising to see such a great effect on the loss of hubs in the homs. That said, the analytical approaches in this model did help the authors confirm that the loss of gap junctions does not alter the preferential existence of beta cell connectivity and confirms the important contribution of metabolic "coupling". One perhaps can therefore conclude that there are two types of network behaviour in an islet (maybe more) and the field should move towards an understanding of overlapping network communities as has been done in brain networks.

Overall this is an extremely well-written paper which was a pleasure to read. This group has neatly and expertly provided both computational and experimental data to support the notion that it is metabolic but not "structural" ie GJ coupling that drives our observations of hubs and functional connectivity. However, there is still much work to do to understand whether this metabolic coupling is just a random epiphenomenon or somehow fated, the extent to which other elements of "structural" coupling - ie the presence of other endocrine cell types, the spatial distribution of paracrine hormone receptors, blood vessels and nerve terminals are also important.

Reviewer #4 (Public Review):

This manuscript describes a complex, highly ambitious set of modeling and experimental studies that appear designed to compare the structural and functional properties of beta cell subpopulations within the islet network in terms of their influence on network synchronization. The authors conclude that the most functionally coupled cell subpopulations in the islet network are not those that are most structurally coupled via gap junctions but those that are most metabolically active.

Strengths of the paper include (1) its use of an interdisciplinary collection of methods including computer simulations, FRAP to monitor functional coupling by gap junctions, the monitoring of Ca2+ oscillations in single beta cells embedded in the network, and the use of sophisticated approaches from probability theory. Most of these methods have been used and validated previously. Unfortunately, however, it was not clear what the underlying premise of the paper actually is, despite many stated intentions, nor what about it is new compared to previous studies, an additional weakness.

Although the authors state that they are trying to answer 3 critical questions, it was not clear how important these questions are in terms of significance for the field. For example, they state that a major controversy in the field is whether network structure or network function mediates functional synchronization of beta cells within the islet. However, this question is not much debated. As an example, while it is known that there can be long-range functional coupling in islets, no workers in the field believe there is a physical structure within islets that mediates this, unlike the case for CNS neurons that are known to have long projections onto other neurons. Beta cells within the islets are locally coupled via gap junctions, as stated repeatedly by the authors but these mediate short-range coupling. Thus, there are clearly functional correlations over long ranges but no structures, only correlated activity. This weakness raises questions about the overall significance of the work, especially as it seems to reiterate ideas presented previously.

Specific Comments

1. The authors state it is well accepted that the disruption of gap junctional coupling is a pathophysiological characteristic of diabetes, but this is not an opinion widely accepted by the field, although it has been proposed. The authors should scale back on such generalizations, or provide more compelling evidence to support such a claim.<br /> 2. The paper relies heavily on simulations performed using a version of the model of Cha et al (2011). While this is a reasonable model of fast bursting (e.g. oscillations having periods <1 min.), the Ca2+ oscillations that were recorded by the authors and shown in Fig. 2b of the manuscript are slow oscillations with periods of 5 min and not <1 min, which is a weakness of the model in the current context. Furthermore, the model outputs that are shown lack the well-known characteristics seen in real islets, such as fast-spiking occurring on prolonged plateaus, again as can be seen by comparing the simulated oscillations shown in Fig. 1d with those in Fig. 2b. It is recommended that the simulations be repeated using a more appropriate model of slow oscillations or at least using the model of Cha et al but employed to simulate in slower bursting.<br /> 3. Much of the data analyzed whether obtained via simulation or through experiment seems to produce very small differences in the actual numbers obtained, as can be seen in the bar graphs shown in Figs. 1e,g for example (obtained from simulations), or Fig. 2j (obtained from experimental measurements). The authors should comment as to why such small differences are often seen as a result of their analyses throughout the manuscript and why also in many cases the observed variance is high. Related to the data shown, very few dots are shown in Figs. 1e-g or Fig 4e and 4h even though these points were derived from simulations where 100s of runs could be carried out and many more points obtained for plotting. These are weaknesses unless specific and convincing explanations are provided.<br /> 4. The data shown in Fig. 4i,j are intended to compare long-range synchronization at different distances along a string of coupled cells but the difference between the synchronized and unsynchronized cells for gcoup and gKglyc was subtle, very much so.<br /> 5. The data shown in Fig. 5 for Cx36 knockout islets are used to assess the influence of gap junctional coupling, which is reasonable, but it would be reassuring to know that loss of this gene has no effects on the expression of other genes in the beta cell, especially genes involved with glucose metabolism.<br /> 6. In many places throughout the paper, it is difficult to ascertain whether what is being shown is new vs. what has been shown previously in other studies. The paper would thus benefit strongly from added text highlighting the novelty here and not just restating what is known, for instance, that islets can exhibit small-world network properties. This detracts from the strengths of the paper and further makes it difficult to wade through. Even the finding here that metabolic characteristics of the beta cells can infer profound and influential functional coupling is not new, as the authors proposed as much many years ago. Again, this makes it difficult to distill what is new compared to what is mainly just being confirmed here, albeit using different methods.

Reviewer #1 (Public Review):

Notwithstanding that the molecular underpinnings of the mechanistic target of rapamycin complex 1 (mTORC1) signaling are relatively well understood, quantitative data pertinent to mTORC1-dependent integration of a variety of stimuli is lacking. To address this question, Sparta et al., developed a series of fluorescent reporters that in combination with live cell microscopy allowed them to determine responses of mTORC1 to several stimuli including glucose, amino acids, and insulin at the single cell resolution. Considering the central role of mTORC1 in homeostasis and its dysregulation across a variety of pathological states, it was thought that this study should be of broad interest to a wide spectrum of biomedical disciplines ranging from biochemistry, molecular and cellular biology to neurobiology and cancer research.

Strengths: This study employs powerful approach based on use of live cell imaging of multiple fluorescent reports that are indicative of alterations in mTORC1 activity. In contrast to traditional approaches based on querying phosphorylation status of mTORC1 substrates by Western blotting this approach allows time-resolved measurement of mTORC1 activity at the single cell resolution. Using this approach, the authors provide solid evidence to corroborate a model of graded activation of mTORC1 by amino acids, insulin, and combination thereof.

Weaknesses: The major weaknesses were thought to be related to the interpretation of the current model of mTORC1 regulation as AND gate and reliance on a single cell line. Some minor technical issues were also observed pertinent to the lack of controls demonstrating the effectiveness of manipulations of nutrients and/or insulin as well as the effects of such manipulation on the expression of reporters used to monitor mTORC1 activity.

Reviewer #2 (Public Review):

Using fluorescent-TFEB fusion proteins and mutants thereof for live-cell imaging single cells, the authors investigated how mTORC1 responds to amino acids and growth factors. First, they demonstrated that the stably expressed fusion protein behaves as endogenous TFEB with regards to mTORC1 activation. Next, using the phosphodeficient TFEB mutant, they showed that GSK3 phosphorylation amplifies the C/N ratio, supporting the role of GSK3 and mTORC1 in co-regulating TFEB. When amino acids or insulin were added to starved cells, they found a graded response depending on amounts of AA or insulin, respectively, thus suggesting an incremental response. When multiple inputs were assessed, they found that TFEB C/N ratio also increased in increments when nutrients were added first followed by insulin. But when insulin was added first before nutrients, a minimal response occurred although this could be subsequently increased upon addition of the nutrients. Lastly, by tracking down TFEB C/N in response to different amounts of nutrients over longer periods (12 hr), they observed that a new steady state is achieved, indicating adaptation of mTORC1 activity and that this correlates with signal inputs from Akt and AMPK. Based on these findings, the authors conclude that the mTORC1-TFEB signaling continuously adjust to nutrient availability rather than just behave in "AND" gate logic fashion.

Overall, the results are robust and supportive of their conclusion. The use of fluorescent fusion proteins/mutants is nicely done. The authors have created useful tools to further analyze mTOR signaling at the single-cell level. However, the findings that mTORC1 signaling behaves like a rheostat is not really new and rather more confirmatory of previous studies. The current studies further support this model with their use of TFEB as mTORC1 target in single cells.

Reviewer #3 (Public Review):

This is an interesting manuscript from Sparta and colleagues that investigates dynamics of MTOR and TFEB signalling. The main strength is that the study is based on a systems biology approach using live cell imaging of a range of MTOR downstream readouts, capturing data on a single-cell level with capabilities to multiplex tracking over time. To monitor downstream signalling, the authors primarily rely on measuring nuclear translocation of a fluorescent reporter of TFEB, truncated to remove C-terminal DNA-binding domain and the AKT phosphorylation site. The authors further show that a TFEB reporter with 3x S>A mutations at 3 GSK3beta phosphorylation sites (134, 138 and 142) was dramatically less sensitive to stimulation by amino acids, or by insulin. The authors use these single cell tools to determine whether MTOR-TFEB signalling better fits a gated / digital pattern of response vs a gradual/ analogue mode. Data based on concentration-dependent titrations provide further support of the ability of MTOR-TFEB to respond to amino acid or insulin stimulations with gradual/incremental sensitivity. To understand how MTOR, AMPK and AKT pathways respond and integrate to multiple signals, the authors were also able to use single cell imaging approaches, comparing: TFEB, AMPK-FRET, and FOXO reporters. As follows, the authors were able to track downstream signalling following various patterns of sequential stimulation by glucose, amino acids and insulin. This work is thus able to provide further insight and illustrate how single cells within a population function during nutrient sensing signalling. The results highlight the power of single cell multi-channel imaging to interrogate signalling in real time.

Reviewer #1 (Public Review):

This paper presents extensive numerical simulations using a model that incorporates up to second-order epistasis to study the joint effects of microscopic epistasis and clonal interference on the evolutionary dynamics of a microbial population. Previous works that explicitly modeled microscopic epistasis typically assumed strong selection & weak mutation (SSWM), a condition that is generally not met in real-life evolutionary processes. Alternatively, another class of models coarse-grained the effects of microscopic epistasis into a generic distribution of fitness effects. The framework introduced in this paper represents an important advance with respect to these previous approaches, allowing for the explicit modeling of microscopic epistasis in non-SSWM scenarios. The modeling framework presented promises to be a valuable tool to study microbial evolution in silico.

Reviewer #2 (Public Review):

This paper presents an extensive numerical study of microbial evolution using a model of fitness inspired by spin glass physics. It places special emphasis on elucidating the combined effects of microscopic epistasis, which dictates how the fitness effect of a mutation depends on the genetic background on which it occurs, and clonal interference, which describes the proliferation of and competition between multiple strains. Both microscopic epistasis and clonal interference have been observed in microbial evolution experiments, and are chief contributors to the complexity of evolutionary dynamics. Correlations between random mutations and nonlinearities associated with interactions between sub-populations consisting of competing strains make it extremely challenging to make quantitative theoretical predictions for evolutionary dynamics and associated observables such as the mean fitness. While the body of theoretical and computational research on modeling evolutionary dynamics is extensive, most theoretical efforts rely on making simplifications such as the strong selection weak mutation (SSWM) limit, which neglects clonal interference, or assumptions about the distribution of fitness effects that are not experimentally verifiable.

The authors have addressed this challenge by running a numerical microbial evolution experiment over realistic population sizes (~ 100 million cells) and timescales (~ 10,000 generations) using a spin glass model of fitness that considers pairwise interactions between mutations on distinct genetic loci. By independently tuning mutation rate as well as the strength of epistasis, the authors have shown that epistasis generically slows down the growth of fitness trajectories regardless of the amount of clonal interference. On the other hand, in the absence of epistasis, clonal interference speeds up the growth of fitness trajectories, but leaves the growth unchanged in the presence of epistasis. The authors quantitatively characterize these observations using asymptotic power law fits to the mean fitness trajectories. Further, the authors employ more simplified macroscopic models that are informed by their empirical findings, to reveal the mechanistic origins of the epistasis mediated slowing down of fitness growth. Specifically, they show that epistasis leads to a broadening of the distribution of fitness increments, leading to the fixation of a large number of mutations that confer small benefits. Effectively, this leads to an increase in the number of fixed mutations required to climb the fitness peak. This increased number of required beneficial mutations together with the decreasing availability of beneficial mutations at high fitness lead to the slowdown of fitness growth. The authors' data analysis is quite solid and their conclusions are well supported by quantitative macroscopic models. The paper also includes an interesting analysis of dynamical correlations between mutations, using tools developed in the spin glass literature.

One of the highlights of this paper is the author's astute choice of model, which strikes an impressive balance between complexity, flexibility, and numerical accessibility. In particular, the authors were able to achieve results over realistic population sizes and timescales largely because of the amenability of the model to the implementation of an efficient simulation algorithm. At the same time, the strength of epistasis and clonal interference can be tuned in a facile manner, enabling the authors to map out a phase diagram spanning these two axes. One could argue that the numerical scheme employed here would only work for a specific class of models, and is therefore not generalizable to all models of evolutionary dynamics. While this is likely true, the model is capable of recapitulating several complex aspects of microbial evolution, and is therefore not unduly restrictive.

Spin glass physics has already provided significant insights into a wide range of topics in the life sciences including protein folding, neuroscience, ecology and evolution. The present work carries this approach forward, with immediate implications for microbial evolution, and potential implications in related areas of research such as microbial ecology. In addition to the theoretical value of spin glass physics, the high performance algorithm developed in this work lays the foundation for formulating data driven approaches aimed at understanding evolutionary dynamics. In the future, there is considerable scope for utilizing data generated by such models to train machine learning algorithms for quantifying parameters associated with epistasis, clonal interference, and the distribution of fitness effects in laboratory experiments.

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 (rather than. 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 held 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 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:

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 were 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.

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 #2 (Public Review):

The manuscript by Seah and Saranathan investigates the cell-based growth mechanism of so called honeycomb-structures in the upper lamina of papilionid wing scales by investigating a number of different species. The authors chose Parides eurimedes as a focus species with the developmental pathway of five other papilionid as a comparative backup. Through state-of-the-art microscopy images of different developmental steps, the authors find that the intricate f-actin filaments reorganise, support cuticular discs that template the air holes that form the honeycomb lattice.

The revised manuscript is well written and easy to follow, yet based on a somewhat limited sample size for their focus species, limiting attempts to suppress expression and alter structure shape. I have no further comments.

Reviewer #1 (Public Review):

Funabiki et al, performed a co-evolutionary analysis of Lsh/HELLS and CDCA7, two factors with links to DNA methylation pathways in mammals, amphibia and fish. The authors suggest that conserved roles for the two factors in DNA methylation maintenance pathways can be traced back to the last eukaryotic common ancestor. Overall, the findings are important and the results could be useful for researchers studying DNA methylation pathways in many different organisms.

Comments on current version:

In the revised version of this manuscript the authors addressed all previously raised issues. I would like to thank them for that. The data is now clearly presented and interpreted and more experimental detail has been added. Thus, the manuscript is much improved and provides an interesting basis for experimental follow-up and further functional investigations.

Reviewer #2 (Public Review):

In this manuscript, Funabiki and colleagues investigated the co-evolution of DNA methylation and nucleosome remolding in eukaryotes. This study is motivated by several observations: (1) despite being ancestrally derived, many eukaryotes lost DNA methylation and/or DNA methyltransferases; (2) over many genomic loci, the establishment and maintenance of DNA methylation relies on a conserved nucleosome remodeling complex composed of CDCA7 and HELLS; (3) it remains unknown if/how this functional link influenced the evolution of DNA methylation. The authors hypothesize that if CDCA7-HELLS function was required for DNA methylation in the last eukaryote common ancestor, this should be accompanied by signatures of co-evolution during eukaryote radiation.

To test this hypothesis, they first set out to investigate the presence/absence of putative functional orthologs of CDCA7, HELLS and DNMTs across major eukaryotic clades. They succeed in identifying homologs of these genes in all clades spanning 180 species. To annotate putative functional orthologs, they use similarity over key functional domains and residues - such as ICF related mutations for CDCA7 and SNF2 domains for HELLS - as well as maximum likelihood phylogenetic analyses. Using established eukaryote phylogenies, the authors conclude that the CDCA7-HELLS-DNMT axis arose in the last common ancestor to all eukaryotes. Importantly, they found recurrent loss events of CDCA7-HELLS-DNMT in at least 40 eukaryotic species, most of them lacking DNA methylation.

Having identified these factors, they successfully identify signatures of co-evolution between DNMTs, CDCA7 and HELLS using CoPAP analysis - a probabilistic model inferring the likelihood of interactions between genes given a set of presence/absence patterns. As a control, such interactions are not detected with other remodelers or chromatin modifying pathways also found across eukaryotes. Expanding on this analysis, the authors found that CDCA7 was more likely to be lost in species without DNA methylation.

In conclusion, the authors suggest that the CDCA7-HELLS-DNMT axis is ancestral in eukaryotes and raise the hypothesis that CDCA7 becomes quickly dispensable upon the loss of DNA methylation and/or that CDCA7 might be the first step toward the switch from DNA methylation-based genome regulation to other modes.

The data and analyses reported are significant and solid. Overall, this work is a conceptual advance in our understanding of the evolutionary coupling between nucleosome remolding and DNA methylation. It also provides a useful resource to study the early origins of DNA methylation related molecular process. Finally, it brings forward the interesting hypothesis that since eukaryotes are faced with the challenge of performing DNA methylation in the context of nucleosome packed DNA, loosing factors such as CDCA7-HELLS likely led to recurrent innovations in chromatin-based genome regulation.

Strengths:<br /> - The hypothesis linking nucleosome remodeling and the evolution of DNA methylation.<br /> - Deep mapping of DNA methylation related process in eukaryotes.<br /> - Identification and evolutionary trajectories of novel homologs/orthologs of CDCA7.<br /> - Identification of CDCA7-HELLS-DNMT co-evolution across eukaryotes.

Reviewer #1 (Public Review):

In chicken embryos, the counter-rotating migration of epiblast cells on both sides of the forming primitive streak (PS), a process referred to as polonaise movements, has attracted longstanding interest as a paradigm of morphogenetic cell movements. However, the association between these cell movements and PS development is still controversial. This study investigated PS development and polonaise movements separately at their initial stage, showing that both could be uncoupled (at least at the initial phase), being activated via Vg1 signaling.

Strengths of this study

Polonaise movements, i.e., the circular cell migration of epiblast cells on both sides of the forming PS in avian embryos, have been the subject of research through live imaging and promoted the development of new tools to analyze quantitatively such movements. However, conclusions from previous studies remain controversial, at least partly due to the nature of perturbations to PS development and polonaise movements.

This study performed the challenging technique of electroporation to successfully mark and manipulate Wnt/PCP pathways in unincubated chicken embryo cells at the initiation phase of these two processes. In addition, the authors separately altered PS development and polonaise movements: PS development was perturbed by inhibiting either the Wnt/PCP pathway or DNA synthesis using aphidicolin, while polonaise movements were modified by the development of a second PS after engrafting Vg1-expressing COS cells located at the opposite end of the blastoderm. The study concluded that Vg1 elicits both PS development and polonaise movements, which occur in a parallel and are not inter-dependent.

To support these conclusions, particle image velocimetry (PIV) of cell trajectories captured by live imaging was performed. These tools delineated visually appealing cell movements and gave rise to vorticity profiles, adding more value to this study.

Weaknesses of this study

Engrafted Vg1-expressing COS cells located at the anterior end of the blastoderm elicited both the development of a second PS and marked bilateral polonaise movements while perturbing these movements along the original PS. How do polonaise movements along the second PS dominate over those along the normal PS? The authors suggested a model in which Vg1 acts in a graded or dose-dependent manner since engrafted COS cells over-expressed Vg1. This model can be tested by reducing the mass of engrafted COS cells. Although the authors propose performing this analysis in further investigations, it would be preferable to incorporate into this study for better consistency.

The authors claim that chicken embryo development is representative of "amniotes," but it does not hold for all groups. Avian and mammal species are exceptional among amniotes in the sense they develop a PS (e.g., Coolen et al. 2008). Moreover, in certain mammalian embryos like mouse embryos, cells laterally to the PS do not move much (Williams et al. 2012). The authors should avoid the generalization that chicken embryos unequivocally represent amniotes as opposed to the observed in non-amniote embryos. The observations in chicken embryos as they stand are significant enough.

References:<br /> Coolen M, et al. (2008). Molecular characterization of the gastrula in the turtle Emys orbicularis: an evolutionary perspective on gastrulation. PLoS One. 3(7):e2676. doi: 10.1371/journal.pone.0002676

Williams M, et al. (2012). Mouse primitive streak forms in situ by initiation of epithelial to mesenchymal transition without migration of a cell population. Dev Dyn. 241(2):270-283. doi: 10.1002/dvdy.23711

Reviewer #2 (Public Review):

Summary:<br /> The authors are interested in large-scale cell flow during gastrulation and in particular in the polonaise movement. This movement corresponds to a bilateral vortex-like counter-rotating cell flow and transport the mesendodermal cells allowing ingression of cells through the primitive streak and ultimately the formation of the mesoderm and endoderm. The authors specifically wanted to investigate the coupling of the polonaise movement and primitive streak to understand whether the polonaise movement is a consequence of the formation of the primitive streak or the other way around. They propose a model where the primitive streak elongation is not required for the cell flow but rather for its maintenance and that robust cell flow is not required for primitive streak extension.

Strengths:<br /> Overall, the manuscript is well written with clear experimental designs. The authors have used live imaging and cell flow analysis in different conditions, where either the formation of the primitive streak or the cell flow was perturbed.<br /> Their live imaging and PIV-based analyses convincingly support their conclusions that primitive streak deformation or mitotic arrest do not impact the initiation of the polonaise movement but rather the location or maintenance of these rotations. They additionally showed that disruption of the polonaise movement in the authentic primitive streak by elegant addition of an ectopic primitive streak does not impact the original primitive streak elongation.

Weaknesses:<br /> - When using the delta-DEP-GFP construct, the authors showed that they can manipulate the shape of the primitive streak without affecting the identity and number of primitive streak cells. It is not clear however how this can affect the shape, volume or adhesion of the cells. Some mechanistic insights would strengthen the paper.<br /> - Overall, frequencies of observation are missing for a better view of the phenomenon. For example, do Vg1/Cos cells always disrupt the flow at the authentic primitive streak? Can replicate vector fields be integrated to reflect quantification?<br /> - Since myosin cables have been shown to be instrumental for the polonaise movement, it would be interesting to better investigate how the manipulations by the delta-DEP-GFP construct, or Vg1/Cos affect the myosin cables (as shown in preliminary form for the aphidicolin-treated embryos).

Reviewer #1 (Public Review):

Summary:<br /> The authors explored correlations between taste features of botanical drugs used in ancient times and therapeutic uses, finding some potentially interesting associations between intensity and complexity of flavors and therapeutic potential, plus some more specific associations described in the discussion sections. I believe the results could be of potential benefit to the drug discovery community, especially for those scientists working in the field of natural products.

Strengths:<br /> Owing to its eclectic and somehow heterodox nature, I believe the article might be of interest to a general audience. In fact, I have enjoyed reading it and my curiosity was raised by the extensive discussion.

The idea of revisiting a classical vademecum with new scientific perspectives is quite stimulating.

The authors have undertaken a significant amount of work, collecting 700 botanical drugs and exploring their taste and association with known uses via eleven trained panelists.

Weaknesses:<br /> I have some methodological concerns. Was subjective bias within the panel of participants explored or minimized in any manner? Were the panelists exposed to the drugs blindly and on several occasions to assess the robustness of their perceptions? Judging from the total number of taste assessments recorded and from Supplementary Material, it seems that not every panelist tasted every drug. Why? It may be a good idea to explore the similarity in the assessments of the same botanical drug by different volunteers. If a given descriptor was reported by a single volunteer, was it used anyway for the statistical analysis or filtered out?

The idea of "versatility" is repeatedly used in the manuscript, but the authors do not clearly define what they call "versatile".

The introduction should be expanded. There are plenty of studies and articles out there exploring the evolution of bitter taste receptors, and associating it with a hypothetical evolutionary advantage since bitter plants are more likely to be poisonous. Since plant secondary metabolites are one of the most important sources of therapeutic drugs and one of their main functions is to protect plants from environmental dangers (e.g., animals), this evolutionary interplay should be at least briefly discussed in the introductory section. Since the authors visit some classical authors, Parecelsus' famous quote "All things are poison and nothing is without poison. Solely the dose determines that a thing is not a poison" may be relevant here. Also note that some authors have explored the relationship between taste receptors and pharmacological targets (e.g., Bioorg Med Chem Lett. 2012 Jun 15;22(12):4072-4).

Reviewer #2 (Public Review):

Summary:<br /> This is an unusual, but interesting approach to link the "taste" of plants and plant extracts to their therapeutic use in ancient Graeco-Roman culture. The authors used a panel of 11 trained tasters to test ~700 different medicinal plants and describe them in terms of 22 "taste" descriptors. They correlated these descriptors with the plant's medical use as reported in the De Materia Medica (DMM 1st Century, CE). Correcting for some of the plants' evolutionary phylogenetic relationships, the authors found that taste descriptors along with intensity measures were correlated with the "versatility" and/or specific therapeutic use of the medicine. For example, simple but intense tastes were correlated with the versatility of a medicine. Specific intense tastes were linked to versatility while others were not; intense bitter, starchy, musky, sweet, cooling, and soapy were associated with versatility, but sour and woody were negatively associated. Also, some specific tastes could be associated with specific uses - both positive and negative associations. Some of these findings make sense immediately, but others are somewhat surprising, and the authors propose some links between taste and medicinal use (both historical and modern use) in the discussion. The authors state that this study allows for a re-evaluation of pre-scientific knowledge, pointing toward a central role of taste in medicine.

Strengths:<br /> The real strength of this study is the novelty of this approach - using modern-day tasters to evaluate ancient medicinal plants to understand the potential relationships between taste and therapeutic use, lending some support to the idea that the "taste" of a medicine is linked to its effectiveness as a treatment.

Weaknesses:<br /> While I find this study very interesting and potentially insightful into the development and classification of certain botanical drugs for specific medicinal use, I would encourage the authors to revise the manuscript and the accompanying figures significantly to improve the reader's understanding of the methods, analyses, and findings. A more thorough discussion of the limitations of this particular study and this general type of approach would also be very important to include.

The metric of versatility seems somewhat arbitrary. It is not well explained why versatility is important and/or its relationship with taste complexity or intensity. Similarly, the rationale for examining the relationships between individual therapeutic uses and taste intensity/complexity is not well explained, and given that a similar high intensity/low complexity relationship is common for most of the therapeutic uses, it restates the same concepts that were covered by the initial versatility comparison. There are multiple issues with the figures - the use of icons is in many cases counterproductive and other representations are not clear or cause confusion (especially Figure 3). The phylogenetic information about the botanicals is missing. Also missing is any reference/discussion about how that analysis was able to disambiguate the confounding effects of shared uses and tastes of drugs from closely related species.

Reviewer #1 (Public Review):

Summary:<br /> The overall analysis and discovery of the common motif are important and exciting. Very few human/primate ribozymes have been published and this manuscript presents a relatively detailed analysis of two of them. The minimized domains appear to be some of the smallest known self-cleaving ribozymes.

Strengths:<br /> The manuscript is rooted in deep mutational analysis of the OR4K15 and LINE1 and subsequently in modeling of a huge active site based on the closely-related core of the TS ribozyme. The experiments support the HTS findings and provide convincing evidence that the ribozymes are structurally related to the core of the TS ribozyme, which has not been found in primates prior to this work.

Weaknesses:<br /> 1. Given that these two ribozymes have not been described outside of a single figure in a Science Supplement, it is important to show their locations in the human genome, present their sequence and structure conservation among various species, particularly primates, and test and discuss the activity of variants found in non-human organisms. Furthermore, OR4K15 exists in three copies on three separate chromosomes in the human genome, with slight variations in the ribozyme sequence. All three of these variants should be tested experimentally and their activity should be presented. A similar analysis should be presented for the naturally-occurring variants of the LINE1 ribozyme. These data are a rich source for comparison with the deep mutagenesis presented here. Inserting a figure (1) that would show the genomic locations, directions, and conservation of these ribozymes and discussing them in light of this new presentation would greatly improve the manuscript. As for the biological roles of known self-cleaving ribozymes in humans, there is a bioRxiv manuscript on the role of the CPEB3 ribozyme in mammalian memory formation (doi.org/10.1101/2023.06.07.543953), and an analysis of the CPEB3 functional conservation throughout mammals (Bendixsen et al. MBE 2021). Furthermore, the authors missed two papers that presented the discovery of human hammerhead ribozymes that reside in introns (by de la PeÃ{plus minus}a and Breaker), which should also be cited. On the other hand, the Clec ribozyme was only found in rodents and not primates and is thus not a human ribozyme and should be noted as such.

2. The authors present the story as a discovery of a new RNA catalytic motif . This is unfounded. As the authors point out, the catalytic domain is very similar to the Twister Sister (or "TS") ribozyme. In fact, there is no appreciable difference between these and TS ribozymes, except for the missing peripheral domains. For example, the env33 sequence in the Weinberg et al. 2015 NCB paper shows the same sequences in the catalytic core as the LINE1 ribozyme, making the LINE1 ribozyme a TS-like ribozyme in every way, except for the missing peripheral domains. Thus these are not new ribozymes and should not have a new name. A more appropriate name should be TS-like or TS-min ribozymes. Renaming the ribozymes to lanterns is misleading.

3. In light of 2) the story should be refocused on the fact the authors discovered that the OR4K15 and LINE1 are both TS-like ribozymes. That is very exciting and is the real contribution of this work to the field.

4. Given the slow self-scission of the OR4K15 and LINE1 ribozymes, the discussion of the minimal domains should be focused on the role of peripheral domains in full-length TS ribozymes. Peripheral domains have been shown to greatly speed up hammerhead, HDV, and hairpin ribozymes. This is an opportunity to show that the TS ribozymes can do the same and the authors should discuss the contribution of peripheral domains to the ribozyme structure and activity. There is extensive literature on the contribution of a tertiary contact on the speed of self-scission in hammerhead ribozymes, in hairpin ribozyme it's centered on the 4-way junction vs 2-way junction structure, and in HDVs the contribution is through the stability of the J1/2 region, where the stability of the peripheral domain can be directly translated to the catalytic enhancement of the ribozymes.

5. The argument that these are the smallest self-cleaving ribozymes is debatable. LÃ1/4nse et al (NAR 2017) found some very small hammerhead ribozymes that are smaller than those presented here, but the authors suggest only working as dimers. The human ribozymes described here should be analyzed for dimerization as well (e.g., by native gel analysis) particularly because the authors suggest that there are no peripheral domains that stabilize the fold. Furthermore, Riccitelli et al. (Biochemistry) minimized the HDV-like ribozymes and found some in metagenomic sequences that are about the same size as the ones presented here. Both of these papers should be cited and discussed.

6. The authors present homology modeling of the OR4K15 and LINE1 ribozymes based on the crystal structures of the TS ribozymes. This is another point that supports the fact that these are not new ribozyme motifs. Furthermore, the homology model should be carefully discussed as a model and not a structure. In many places in the text and the supplement, the models are presented as real structures. The wording should be changed to carefully state that these are models based on sequence similarity to TS ribozymes. Fig 3 would benefit from showing the corresponding structures of the TS ribozymes.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript applies a mutational scanning analysis to identify the secondary structure of two previously suggested self-cleaving ribozyme candidates in the human genome. Through this analysis, minimal structured and conserved regions with imminent importance for the ribozyme's activity are suggested and further biochemical evidence for cleavage activity are presented. Additionally, the study reveals a close resemblance of these human ribozyme candidates to the known self-cleaving ribozyme class of twister sister RNAs. Despite the high conservation of the catalytic core between these RNAs, it is suggested that the human ribozyme examples constitute a new ribozyme class. Evidence for this however is not conclusive.

Strengths:<br /> The deep mutational scanning performed in this study allowed the elucidation of important regions within the proposed LINE-1 and OR4K15 ribozyme sequences. Part of the ribozyme sequences could be assigned a secondary structure supported by covariation and highly conserved nucleotides were uncovered. This enabled the identification of LINE-1 and OR4K15 core regions that are in essence identical to previously described twister sister self-cleaving RNAs.

Weaknesses:<br /> I am skeptical of the claim that the described catalytic RNAs are indeed a new ribozyme class. The studied LINE-1 and OR4K15 ribozymes share striking features with the known twister sister ribozyme class (e.g. Figure 3A) and where there are differences they could be explained by having tested only a partial sequence of the full RNA motif. It appears plausible, that not the entire "functional region" was captured and experimentally assessed by the authors.

They identify three twister sister ribozymes by pattern-based similarity searches using RNA-Bob. Also comparing the consensus sequence of the relevant region in twister sister and the two ribozymes in this paper underlines the striking similarity between these RNAs. Given that the authors only assessed partial sequences of LINE-1 and OR4K15, I find it highly plausible that further accessory sequences have been missed that would clearly reveal that "lantern ribozymes" actually belong to the twister sister ribozyme class. This is also the reason I do not find the modeled structural data and biochemical data results convincing, as the differences observed could always be due to some accessory sequences and parts of the ribozyme structure that are missing.

Highly conserved nucleotides in the catalytic core, the need for direct contacts to divalent metal ions for catalysis, the preference of Mn2+ oder Mg2+ for cleavage, the plateau in observed rate constants at ~100mM Mg2+, are all characteristics that are identical between the proposed lantern ribozymes and the known twister sister class.

The difference in cleavage speed between twister sister (~5 min-1) and proposed lantern ribozymes could be due to experimental set-up (true single-turnover kinetics?) or could be explained by testing LINE-1 or OR4K15 ribozymes without needed accessory sequences. In the case of the minimal hammerhead ribozyme, it has been previously observed that missing important tertiary contacts can lead to drastically reduced cleavage speeds.

Reviewer #1 (Public Review):

The authors have performed extensive work generating reporter mice and performing single-cell analysis combined with in situ hybridization to arrive at 14 clusters of enterochromaffin (EC) cells. Then, they focus on Piezo channel expression in distal EC cells and find that these channels might play a role in regulating colonic motility. Overall, this is an informative study that comprehensively classifies EC cells in different regions of the small and large intestine. From a functional point of view, however, the authors seem to ignore the fact that the expression of Piezo-2-IRES-Cre is broad, which would raise concerns regarding their physiological conclusions.

The authors may wish to consider the following specific points:

It is surprising that the number of ileal EC cells is less than that of the distal colon, and it would be interesting to know whether the authors can comment about ileal EC cells. It is unclear why ileal ECs were not included in the study, even though they are mentioned in the diagram (Fig. 2c).

Based on their analysis, there are 10 EC cell clusters in SI while there are only 4 clusters in the colon. The authors should comment on whether this is reflective of lesser diversity among colonic ECs or due to the smaller number of colonic ECs collected.

The authors previously described that distal colonic EC cells exhibit various morphologies (Kuramoto et al., 2021). Do Ascl1(+) EC cells particularly co-localize with EC cells with long basal processes? Also, to validate the RNA seq data, the authors might show co-localization between Piezo2/Ascl1/Tph1 in distal EC cells. It would be interesting to see whether Ascl1-CreER (which is available in Jax) specifically labels distal colonic EC cells as this could provide a good genetic tool to specifically manipulate distal colonic EC cells.

The authors used Piezo2-IRES-Cre mice, whose expression is rather broad. They might examine the distribution of Chrm3-mCitrine in the intestine (IF/IHC would be straightforward). And if the expression is in other cell types (which is most likely the case), they should justify that the observed phenotype derives from Piezo2-expressing EC cells. Alternatively, they could use Piezo2-Cre;ePetFlp (or Vil-Flp);Chrm3 to specifically express DREADD receptors in distal colonic EC cells. Also, what does 5HT release look like in jejunal EC cells in Piezo-CHRM3 mice?

For the same reasons as above, DTR experiments may also be non-specific. For example, based on the IF staining (Fig. 6b,d), there seems to be a loss of Tph1+ cells in the proximal colon of Piezo2-DTR mice, so the effects of the Piezo2-DTR likely extend beyond the distal colon.

It is unclear why the localized loss of Piezo2 in Piezo2-DTR mice alters small intestinal transit (Fig. 6g,h). The authors should discuss the functional differences observed between Piezo2-DTR (intraluminal app) and Vil1-Piezo2 KO mice i.e., small intestinal transit, 5HT release, etc. Are these differences due to the residual Piezo2 expression in Piezo2 KO mice? In this context, the authors may want to discuss their findings in the context of recent papers, such as those from the Patapoutian and Ginty groups.

Reviewer #2 (Public Review):

Summary:<br /> The authors investigated the expression profile of enterochromaffin (EC) cells after creating a new tryptophan hydroxylase 1 (Tph1) GFP-reporter mouse using scRNAseq and confirmative RNAscope analysis. They distinguish 14 clusters of Tph1+ cells found along the gut axis. The manuscript focuses on two of these, (i) a multihormonal cell type shown to express markers of pathogen/toxin and nutrient detection in the proximal small intestine, and (ii) on a EC-cluster in the distal colon, which expresses Piezo2, rendering these cells mechanosensitive. In- and ex- vivo data explore the role of the mechanosensitive EC population for intestinal/colonic transit, using chemogenetic activation, diptheria-toxin receptor dependent cell ablation and conditional gut epithelial specific Piezo2 knock-out. Whilst some of these data are confirmative of previous reports - Piezo2 has been implicated in mechanosensitive serotonin release previously, as referred to by the authors - the data are solid and emphasize the importance of mechanosensitive serotonin release for colonic propulsion. The transcriptomic data will guide future research.

Strengths:<br /> The transcriptomic data, whilst confirmative, is more granular than previous data sets. Employing new tools to establish a role of mechanosensitive EC cells for colonic and thus total intestinal transit.

Weaknesses:<br /> 1) The proposed villus/crypt distribution of the 14 cell types is not verified adequately. The RNAscope and immunohistochemistry samples presented do not allow assessment of whether this interpretation is correct - spatial transcriptomics, now approaching single-cell resolution, would be likely to help verify this claim.

2) The physiological function and/or functionality of most of the transcriptomically enriched gene products has not been assessed. Whilst a role for Piezo2 expressing cells for colonic transit is convincingly demonstrated, the nature of the mechanical stimulus or the stimulus-secretion coupling downstream of Piezo2 activation is not clear.

Reviewer #1 (Public Review):

Summary:<br /> This study aims to further resolve the history of speciation and introgression in Heliconius butterflies. The authors break the data into various partitions and test evolutionary hypotheses using the Bayesian software BPP, which is based on the multispecies coalescent model with introgression. By synthesizing these various analyses, the study pieces together an updated history of Heliconius, including a multitude of introgression events and the sharing of chromosomal inversions.

Strengths:<br /> Full-likelihood methods for estimating introgression can be very computationally expensive, making them challenging to apply to datasets containing many species. This study provides a great example of how to apply these approaches by breaking the data down into a series of smaller inference problems and then piecing the results together. On the empirical side, it further resolves the history of a genus with a famously complex history of speciation and introgression, continuing its role as a great model system for studying the evolutionary consequences of introgression. This is highlighted by a nice Discussion section on the implications of the paper's findings for the evolution of pollen feeding.

Weaknesses:<br /> The analyses in this study make use of a single method, BPP. The analyses are quite thorough so this is okay in my view from a methodological standpoint, but given this singularity, more attention should be paid to the weaknesses of this particular approach. Additionally, little attention is paid to comparable methods such as PhyloNet and their strengths and weaknesses in the Introduction or Discussion. BPP reduces computational burden by fixing certain aspects of the parameter space, such as the species tree topology or set of proposed introgression events. While this approach is statistically powerful, it requires users to make informed choices about which models to test, and these choices can have downstream consequences for subsequent analyses. It also might not be as applicable to systems outside of Heliconius where less previous information is available about the history of speciation and introgression. In general, it is likely that most modelling decisions made in the study are justified, but more attention should be paid to how these decisions are made and what the consequences of them could be, including alternative models.

• Co-estimating histories of speciation and introgression remains computationally challenging. To circumvent this in the study, the authors first estimate the history of speciation assuming no gene flow in BPP. While this approach should be robust to incomplete lineage sorting and gene tree estimation, it is still vulnerable to gene flow. This could result in a circular problem where gene flow causes the wrong species tree to be estimated, causing the true species tree to be estimated as a gene flow event. This is a flaw that this approach shares with summary-statistic approaches like the D-statistic, which also require an a-priori species tree. Enrichment of particular topologies on the Z chromosome helps resolve the true history in this particular case, but not all datasets will have sex chromosomes or chromosome-level assemblies to test against.

• The a-priori specification of network models necessarily means that potentially better-fitting models to the data don't get explored. Models containing introgression events are proposed here based on parsimony to explain patterns in gene tree frequencies. This is a reasonable and common assumption, but parsimony is not always the best explanation for a dataset, as we often see with phylogenetic inference. In general, there are no rigorous approaches to estimating the best-fitting number of introgression events in a dataset. Likewise, the study estimates both pulse and continuous introgression models for certain partitions, though there is no rigorous way to assess which of these describes the data better.

• Some aspects of the analyses involving inversions warrant additional consideration. Fewer loci were able to be identified in inverted regions, and such regions also often have reduced rates of recombination. I wonder if this might make inferences of the history of inverted regions vulnerable to the effects of incomplete lineage sorting, even when fitting the MSC model, due to a small # of truly genealogically independent loci. Additionally, there are several models where introgression events are proposed to explain the loss of segregating inversions in certain species. It is not clear why these scenarios should be proposed over those in which the inversion is lost simply due to drift or selection.

Reviewer #2 (Public Review):

Thawornwattana et al. reconstruct a species tree of the genus Heliconius using the full-likelihood multispecies coalescent, an exciting approach for genera with a history of extensive gene flow and introgression. With this, they obtain a species tree with H. aoede as the earliest diverging lineage, in sync with ecological and morphological characters. They also add resolution to the species relationships of the melpomene-silvaniform clade and quantify introgression events. Finally, they trace the origins of an inversion on chromosome 15 that exists as a polymorphism in H. numata, but is fixed in other species. Overall, obtaining better species tree resolutions and estimates of gene flow in groups with extensive histories of hybridization and introgression is an exciting avenue. Being able to control for ILS and get estimates between sister species are excellent perks. One overall quibble is that the paper seems to be best suited to a Heliconius audience, where past trees are easily recalled, or members of the different clades are well known.

Overall, applying approaches such as these to gain greater insight into species relationships with extensive gene flow could be of interest to many researchers. However, the conclusions could be strengthened with a bit more clarity on a few points.

1) The biggest point of concern was the choice of species to use for each analysis. In particular the omission of H. ismenius in the resolution of the BNM clade species tree. The analysis of the chromosome 15 inversion seems to rely on the knowledge that H. ismenius is sister to H. numata, so without that demonstrated in the BNM section the resulting conclusions of the origin of that inversion are less interruptible.

2) An argument they make in support of the branching scenario where H. aoede is the earliest diverging branch is based on which chromosomes support that scenario and the key observation that less introgression is detected in regions of low recombination. Yet, they go no further to understand the relationship between recombination rate and species trees produced.

3) How the loci were defined could use more clarity. From the methods, it seems like each loci could vary quite a bit in total bp length and number of informative sites. Understanding the data processing would make this paper a better resource for others looking to apply similar approaches.

Reviewer #3 (Public Review):

The authors use a full-likelihood multispecies coalescent (MSC) approach to identify major introgression events throughout the radiation of Heliconius butterflies, thereby improving estimates of the phylogeny. First, the authors conclude that H. aoede is the likely outgroup relative to other Heliconius species; miocene introgression into the ancestor of H. aoede makes it appear to branch later. Topologies at most loci were not concordant with this scenario, though 'aoede-early' topologies were enriched in regions of the genome where interspecific introgression is expected to be reduced: the Z chromosome and larger autosomes. The revised phylogeny is interesting because it would mean that no extant Heliconius species has reverted to a non-pollen-feeding ancestral state. Second, the authors focus on a particularly challenging clade in which ancient and ongoing gene flow is extensive, concluding that silvaniform species are not monophyletic. Building on these results, a third set of analyses investigates the origin of the P1 inversion, which harbours multiple wing patterning loci, and which is maintained as a balanced polymorphism in H. numata. The authors present data supporting a new scenario in which P1 arises in H. numata or its ancestor and is introduced to the ancestor of H. pardilinus and H. elevatus - introgression in the opposite direction to what has previously been proposed using a smaller set of taxa and different methods.

The analyses were extensive and methodologically sound. Care was taken to control for potential sources of error arising from incorrect genotype calls and the choice of a reference genome. The argument for H. aoede as the earliest-diverging Heliconius lineage was compelling, and analyses of the melpomene-silvaniform clade were thorough.

The discussion is quite short in its current form. In my view, this is a missed opportunity to summarise the level of support and biological significance of key results. This applies to the revised Melpomene-silvaniform phylogeny and, in particular, the proposed H. numata origin of P1. It would be useful to have a brief overview of the relationships that remain unclear, and which data (if any) might improve estimates.

It was good to see the authors reflect on the utility of full-likelihood approaches more generally, though the discussion of their feasibility and superiority was at times somewhat overstated and reductive. Alternative MSC-based methods that use gene tree frequencies or coalescence times can be used to infer the direction and extent of introgression with accuracy that is satisfactory for a wide variety of research questions. In practice, a combination of both approaches has often been successful. Although full-likelihood approaches can certainly provide richer information if specific parameter estimates are of interest, they quickly become intractable in large species complexes where there is extensive gene flow or significant shifts in population size. In such cases, there may be hundreds of potentially important parameters to estimate, and alternate introgression scenarios may be impossible to disentangle. This is particularly challenging in systems, unlike Heliconius where there is little a priori knowledge of reproductive isolation, genome evolution, and the unique life history traits of each species. It would be useful for the authors to expand on their discussion of strategies that can simplify inference problems in such systems, acknowledging the difficulties therein.

Reviewer #1 (Public Review):

Summary:

This is a very well written and performed study describing a TOPBP1 separation of function mutation, resulting in defective MSCI maintenance but normal sex body formation. The phenotype differs from that of a previous TOPBP1 null allele, in which both MSCI and sex body formation were defective. Additional defects in CHK phosphorylation and SETX localization are also described.

Strengths:

The study is very rigorous, with a remarkably large number of MSCI marks assayed, phosphoproteomics (leading to the interesting SETX discovery) and 10X RNAseq, allowing the MSCI phenotype to be further deconvolved. The approaches in most cases are robust.

Weaknesses:

There aren't many; please find list below:

1. The authors are committed to the idea that maintenance of MSCI is the major defect here. However, based on the data, an alternative would be that some cells achieve sex body formation and MSCI normally, while others do not. It would only take a small percentage of cells exhibiting MSCI failure to kill all the cells in the same germinal epithelium, so this could still explain the complete pachytene block. This isn't a major point...this phenotype is clearly different to the TOPBP1 KO, but a broader discussion of possibilities in the discussion would help. I raise this in the context of both the cytology and 10X analysis:

a) The assessment that sex body formation is normal is based on cytology in Supp 8 and 9, but a more rigorous approach would be to assess condensation of the XY pair in stage-matched spread cells (maybe they have that data already) by measuring distances between the X and Y centromere, or looking at stage IV of the seminiferous cycle, where all cells should have oval sex bodies but sex body mutants have persistent elongated XY pairs (see work of Namekawa and Turner). The authors do actually mention that gH2AX spreading is defective in many cells....and if this is true, condensation to form a sex body would almost certainly not have taken place in those cells.

b) Regarding the 10X data, the finding that expression of some XY genes is elevated and others are not is also consistent with a "partial" phenotype (some cells have normal XY bodies and MSCI, others fail in both). In Fig 6E, X expression looks to be elevated in B5 vs wt at all stages...if this were a maintenance issue, shouldn't it be equal to that in wt and then elevate later?

2. How is the quantitation showing impaired localization of select markers (e.g. SETX) normalized? How do we know that the antibody staining simply didn't work as well on the mutant slides?

3. Is testis TOPBP1 protein expression reduced in the B5 mutant?

4. 10X analysis: how were the genes on the y-axis in Supp 24 arranged? Is this by location on the X chromosome?

5. The final analyses in Fig 7: X-genes are subdivided based on their behavior (up, down, unchanged). What isn't clear to me is whether the authors have considered the fact that there are global changes in gene expression during meiosis (very low in lep , zyg and early pach, then ramps up hugely from mid pach). In other words, is this normalized to autosomal gene expression?

6. Again regarding the 10X analysis, my prediction would be that not ALL X and Y gene would increase in pach if MSCI were ablated...we should remember that XY genes have been subject to MSCI for some 160 million years of evolution, and this will mean that many enhancers that originally drove their expression prior to the evolution of MSCI will now be lost. This has been our experience: many XY genes aren't elevated at pach even in mutants in which MSCI is totally defective. I'd urge the authors to consider this possibility when they use XY gene expression patterns to diagnose the severity or timing of the MSCI phenotype. This could be a discussion point.

Reviewer #2 (Public Review):

Summary:<br /> This paper described the role of BRCT repeat 5 in TOPBP1, a DNA damage response protein, in the maintenance of meiotic sex chromosome inactivation (MSCI). By analyzing a Topbp1 mutant mouse with amino acid substitutions in BRCT repeat 5, the authors found reduced phosphorylation of a DNA/RNA helicase, Sentaxin, and decreased localization of the protein to the X-Y sex body in pachynema. Moreover, the authors also found decreased repression of several genes on the sex chromosomes in the male mice.

Strengths:<br /> The works including phospho-proteomics and single-cell RNA sequencing with lots of data have been done with great care and most of the results are convincing.

Weaknesses:<br /> One concern is that, although the Topbp1 mutant spermatocytes show very severe defects after the stage of late pachynema, the defect in the gene silencing in the sex body is relatively weak. It is a bit difficult to explain how such a weak misregulation of the gene silencing in mice causes the complete loss of cells in the late stage of spermatogenesis.

Reviewer #3 (Public Review):

The work presented by Ascencao and coworkers aims to deepen into the process of sex chromosome inactivation during meiosis (MSCI) as a critical factor in the regulation of meiosis progression in male mammals. For this purpose, they have generated a transgenic mouse model in which a specific domain of TOPBP1 protein has been mutated, hampering the binding of a number of protein partners and interfering with the regulatory cascade initiated by ATR. Through the use of immunolocalization of an impressive number of markers of MSCI, phosphoproteomics and single cell RNA sequencing (scRNAseq), the authors are able to show that despite a proper morphological formation of the sex body and the incorporation of most canonical MSCI makers, sex chromosome-liked genes are reactivated at some point during pachytene and this triggers meiosis progression breakdown, likely due to a defective phosphorylation of the helicase SETX.

The manuscript presents a clear advance in the understanding of MSCI and meiosis progression with two main strengths. First, the generation of a mouse model with a very uncommon phenotype. Second, the use of a vast methodological approach. The results are well presented and illustrated. Nevertheless, the discussion could be still a bit tuned by the inclusion of some ideas, and perhaps speculations, that have not been considered.

Reviewer #1 (Public Review):

The study by Kahraman et al describes the application of a reaction-based probe "diacetylated Zinpyr1" (DA-ZP1) that was developed for the enrichment of human islet beta cells (Lee et al. 2020 to purify human cadaveric alpha cells. The probe binds zinc with high enough affinity to allow the authors to separate beta cells from alpha cells based on the fluorescence intensity; beta cells had high intensity and alpha cells had medium intensity. FACs sorting of cells with intermediate fluorescent intensity were enriched for glucagon expression indicating they were alpha cells. They went on to reaggregate the purified alpha cells into pseudo-islets to test for viability, proliferation, ability to secrete glucagon and transcriptome analysis. These studies demonstrated that the pseudo-alpha cell islets were able to be maintained in culture for up to 10 days without losing their function and with only minor changes in gene expression.

The strengths of the manuscript include:<br /> 1. The description and characterization of a novel tool with which to purify human islet alpha cells<br /> 2. The ability to use the same DA-ZP1 probe to purify both human alpha and beta cells<br /> 3. The functional analysis to show that purified alpha cells retain their identity and maintain function even after in vitro culturing.<br /> 4. Providing a comparison of the transcriptome between whole islets, unsorted islets and sorted alpha cell pseudo-islets. The data is strengthened by the use of four donor islets and several timepoints for the transcriptomic analysis.<br /> 5. The quality of the data and data presentation

Weaknesses include:<br /> 1. Lack of a comparison with other published methods to purify human alpha cells<br /> 2. Unbiased transcriptome analysis of the sorted "high" vs. "medium" fluorescent populations to assess the degree of cross contamination between the 2 populations<br /> 3. Use of only one donor islet for functional analyses

Overall, this study represents a solid characterization of a new tool for purifying cadaveric human alpha cells that will be useful to researchers in the islet biology and diabetes fields.

Reviewer #2 (Public Review):

In the manuscript by Kahraman et al. the authors tested a recently developed Zn2+ indicator fluorogenic sensor as a tool to sort and purify human alpha cells from cadaveric donor islets, for downstream transcriptional and functional analysis. They demonstrate that their previously published sensor DA-ZP1, which was used to sort adult human islet beta cells in their previous work (Lee et al. 2020) they have now adapted for sorting alpha cells based on the 'intermediate' fluorescence intensity of these cells during staining. FACS purification of DA-ZP1-intermediate cells reveals they are strongly enriched for GCG+ cells (alpha cells). The sorted alpha cells can be reaggregated into alpha-pseudoislets for further studies. They carry out a variety of assays to characterize the viability, proliferation, apoptosis, glucagon secretion and transcriptomic changes in their sort purified alpha cells as compared with unsorted islet cells and intact islets. They conclude that sorting alpha cells with DA-ZP1 staining does not alter their function or transcriptome and allows stable maintenance of alpha-pseudoislets in culture for up to 10 days with no deleterious effects.

Strengths:<br /> 1. The study is a nice resource for the field, particularly with the ongoing interest in studying alpha cell biology and function relevant to health and diabetes. The probe that they have previously published can now be used to simultaneously sort alpha and beta cells, which would be a great approach for the field. The results are generally supportive of the conclusions.

2. The study used several human cadaveric donor islet preparations (four in total) representing different ancestries, limiting bias and inter-donor variation. A variety of cellular/molecular assays are employed to provide detailed phenotypic information.

3. The transcriptomic profiling are very strong and provide solid evidence that the reaggregated alpha-pseudoislets are not dedifferentiating or losing function during prolonged (10 day) culture times.

4. Visual presentation is clear and easy to follow for non-specialists.

Weaknesses:

1. The authors are presenting a previously developed probe/tool and also mention that other probes have been developed that can perform a very similar function, so the overall novelty is limited. They did not provide experimental evidence of how their probe is comparable or superior to other probes (e.g. ZIGIR, Newport Green).

2. The authors performed glucagon secretion assays to monitor the function of the sort purified and reaggregated alpha-pseudoislets, but this was only done on 1 of the 4 human islet donors, limiting the generalizability of the conclusions. Also very few experiments were performed to examine alpha cell function in the sort purified cells.

Reviewer #3 (Public Review):

This study presents a new method to highly purify live human pancreatic α cells using the zinc-based reaction probe DA-ZP1. After demonstrating this probe is capable of separating β and α cells from other islet and non-islet cells based on florescence intensity, the authors employ a variety of experimental approaches to demonstrate that these isolated α cells are functional and capable of maintaining their viability and identity in culture over time. The authors also investigate the impact of islet dissociation and cell reaggregation on the islet cell transcriptome, where they primarily identified downregulation of pathways associated with extracellular matrix organization, cell surface interactions, and focal adhesion. Overall, this study adds an additional tool to isolate human α cells to the islet biology community, which may aid in further understanding of human α cell biology under both normal and diabetic conditions. However, some caveats of this study include:

1) While the authors claim that this method improves human α cell yield over antibody-based approaches, they provide no direct comparison between the two methods.<br /> 2) The strength of studies determining cell fraction purity and α cell characteristics (function, viability, proliferation, and apoptosis rates) would be strengthened by performing these studies across multiple donors rather than multiple replicates from the same donor.<br /> 3) Given the heterogeneous nature of the human islet, the use of bulk RNA-sequencing makes the interpretation of genes obtained via the comparison of α-pseudoislets and unsorted pseudoislets difficult. Some cell-specific signals will be missed or masked by differences in cell mixture between groups. It is unclear whether these expression changes are due to α-intrinsic changes or simply the loss of other cell types.<br /> 4) Supplementary files concerning bulk sequencing data is not transparent, with only the direction of the gene expression noted.

Reviewer #1 (Public Review):

The authors primary objective in this study was to identify differences between patients with preeclampsia and normal patients with respect to the placental syncytiotrophoblast extracellular vesicle proteome.

One of the strengths of this study is that it is one of only a few studies that investigated the difference in proteome between patients with preeclampsia and those with normal pregnancies using placental extracellular vesicles obtained by an ex-vivo dual lobe placenta perfusion technique.

The main weaknesses of this study are:

1. The small sample size in that there were only 12 cases.<br /> 2. The study patients and control population of normal pregnancies were not matched for gestational age at delivery.

The authors were able to achieve their study aims and the results support their conclusions.

These findings could be used in future studies of the disease mechanisms and as biomarkers for prediction of preeclampsia. As such, they may be very useful for the identification of women at risk for preeclampsia well before the onset of disease.

Reviewer #2 (Public Review):

Summary:

Preeclampsia is a disorder of pregnancy that affects 4-5% of pregnancies worldwide. Identifying this condition early is clinically relevant as it will help clinicians to make management decisions to prevent adverse outcomes. The placenta holds a key to many pregnancy-related pathologies including preeclampsia and studies have shown many differences in the placenta of women with preeclampsia as compared to controls. However as the placenta cannot be collected directly during pregnancy, the exosomes secreted by it are considered a good alternative to tissue biopsy. In this study, the authors have compared the proteins in different sizes of exosomes from the placenta of women with and without preeclampsia. The idea is to eventually use these as biomarkers for early detection of preeclampsia.

Strengths:

The novelty factor of this study is the use of two different-sized exosomes which has not been achieved earlier.

Weaknesses:

There is already enough information about the differences in exosome contents from the placentas of women with and without preeclampsia. There are some issues with the methods which may influence the outcomes of the data.

The patient population described in the methods section is of HELLP syndrome while the title and the manuscript describe preeclampsia. While it is an important life-threatening condition to address, it is extremely rare and needs careful assessment by clinicians in terms of patient characteristics and outcomes measured.

The study measured the proteins at only a single time point after the disease has already occurred. However, the placenta is an ever-changing tissue throughout pregnancy and different proteins can come up at different times in pregnancy. Thus serial measurements are necessary and a single time point measurement like that done here does little value addition. Unfortunately, this site has not validated the identified biomarkers in plasma or circulating placental exosomes from women with and without preeclampsia. Thus the validity of these findings in real-life situations can not be judged.

Reviewer #1 (Public Review):

Summary:

How plants perceive their environment and signal during growth and development is of fundamental importance for plant biology. Over the last few decades, nano domain organisation of proteins localised within the plasma-membrane has emerged as a way of organising proteins involved in signal pathways. Here, the authors addressed how a non-surface localised signal (viral infection) was resisted by PM localised signalling proteins and the effect of nano domain organisation during this process. This is valuable work as it describes how an intracellular process affects signalling at the PM where most previous work has focused on the other way round, PM signalling effecting downstream responses in the plant. They identify CPK3 as a specific calcium dependent protein kinase which is important for inhibiting viral spread. The authors then go on to show that CPK3 diffusion in the membrane is reduced after viral infection and study the interaction between CPK3 and the remorins, which are a group of scaffold proteins important in nano domain organisation. The authors conclude that there is an interdependence between CPK3 and remorins to control their dynamics during viral infection in plants.

Strengths:

The dissection of which CPK was involved in the viral propagation was masterful and very conclusive. Identifying CPK3 through knockout time course monitoring of viral movement was very convincing. The inclusion of overexpression, constitutively active and point mutation non functioning lines further added to that.

Weaknesses:

My main concerns with the work are twofold.<br /> 1) Firstly, the imaging described and shown is not sufficient to support the claims made. The PM localisation and its non-PM localised form look similar and with no PM stain or marker construct used to support this. The sptPALM data conclusions are nice and fit the narrative. However, no raw data or movie is shown, only representative tracks. Therefore the data quality cannot be verified and in addition, the reporting of number of single particle events visualised per experiment is absent, only number of cells imaged is reported. Therefore it is impossible for the reader to appreciate the number of single molecule behaviours obtained and hence the quality of the data.

2) Secondly, remorins are involved in a lot of nano domain controlled processes at the PM. The authors have not conclusively demonstrated that during viral infection the remorin effects seen are solely due to its interaction with CPK3. The sptPALM imaging of REM1.2 in a cpk3 knockout line goes part way to solve this but more evidence would strengthen it in my opinion. How do we not know that during viral infection the entire PM protein dynamics and organisation are altered? Or that CPK3 and REM are at very distant ends of a signalling cascade. Negative control experiments are required here utilising other PM localised proteins which have no role during viral infection. In addition, if the interaction is specific, the transiently expressed CPK3-CA construct (shown to from nano domains) should be expressed with REM1.2-mEOS to show the alterations in single particle behaviour occur due to specific activations of CPK3 and REM1.2 in the absence of PIAMV viral infection and it is not an artefact of whole PM changes in dynamics during viral infection.

In addition, displaying more information throughout the manuscript (such as raw particle tracking movies and numbers of tracks measured) on the already generated data would strengthen the manuscript further.

Overall, I think this work has the potential to be a very strong manuscript but additional reporting of methods and data are required and additional lines of evidence supporting interaction claims would significantly strengthen the work and make it exceptional.

Reviewer #2 (Public Review):

Summary:

The paper provides evidence that CPK3 plays a role in plant virus infection, and reports that viral infection is accompanied by changes in the dynamics of CPK3 and REM1.2, the phosphorylation substrate of CPK3, in the plasma membrane. In addition, the dynamics of the two proteins in the PM are shown to be interdependent.

Strengths:

The paper contains novel, important information.

Weaknesses:

The interpretation of some experimental data is not justified, and the proposed model is not fully based on the available data.

Reviewer #3 (Public Review):

Summary:

This study examined the role that the activation and plasma membrane localisation of a calcium dependent protein kinase (CPK3) plays in plant defence against viruses.

The authors clearly demonstrate that the ability to hamper the cell-to-cell spread of the virus P1AMV is not common to other CPKs which have roles in defence against different types of pathogens, but appears to be specific to CPK3 in Arabidopsis. Further they show that lateral diffusion of CPK3 in the plasma membrane is reduced upon P1AMV infection, with CPK3 likely present in nano-domains. This stabilisation however, depends on one of its phosphorylation substrates a Remorin scaffold protein REM1-2. However, when REM1-2 lateral diffusion was tracked, it showed an increase in movement in response to P1AMV infection. These contrary responses to P1AMV infection were further demonstrated to be interdependent, which led the authors to propose a model in which activated CPK3 is stabilised in nano-domains in part by its interaction with REM1.2, which it binds and phosphorylates, allowing REM1-2 to diffuse more dynamically within the membrane.

The likely impact of this work is that it will lead to closer examination of the formation of nano-domains in the plasma membrane and dissection of their role in immunity to viruses, as well as further investigation into the specific mechanisms by which CPK3 and REM1-2 inhibit the cell-to-cell spread of viruses.

Strengths:

The paper provided compelling evidence about the roles of CPK3 and REM1-2 through a combination of logical reverse genetics experiments and advanced microscopy techniques, particularly in single particle tracking.

Weaknesses:

There is a lack of evidence for the downstream pathways, specifically whether the role that CPK3 has in cytoskeletal organisation may play a role in the plant's defence against viral propagation. Also, there is limited discussion about the localisation of the nano-domains and whether there is any overlap with plasmodesmata, which as plant viruses utilise PD to move from cell to cell seems an obvious avenue to investigate.

Reviewer #2 (Public Review):

Summary: Shotgun data have been analysed to obtain fungal and bacterial organisms' abundance. Through their metabolic functions and through co-occurrence networks, a functional relationship between the two types of organisms can be inferred. By means of metabolomics, function-related metabolites are studied in order to deepen the fungus-bacteria synergy.

Strengths:<br /> Data obtained from bacteria correlate with data from other authors.<br /> The study of metabolic "interactions" between fungi and bacteria is quite new.<br /> The inclusion of metabolomics data to support the results is a great contribution.

Weaknesses: Methodological descriptions are minimal.

Some example:<br /> *The CON group (line 147) has not been defined. I supposed it is the control group.<br /> * There are no statistics related to shotgun sequencing. How many reads have been sequenced? How many have been removed from the host? How many are left to study bacteria and fungi? Are these reads proportional among the 48 samples? If not, what method has been used to normalise the data?<br /> * ggClusterNet has numerous algorithms to better display the modules of the microbiome network. Which one has been used?

Reviewer #1 (Public Review):

Summary:<br /> Chen et al. describe the bacterial and fungal composition of cervical samples from women with/without Cesarean-section scar diverticulum (CSD) using whole metagenomic sequencing. Also, they report the metabolomic profile associated with CSD and built correlation networks at the taxonomical and taxonomic-metabolic levels to establish potential bacteria-fungi interactions. These interactions could be used, long-term, as therapeutic options to treat or prevent CSD.

Strengths:<br /> - The authors have used advanced techniques in shotgun sequencing which is a powerful tool able to characterize the microbiome at the species (or lower) level and metabolomics.<br /> - These are novel results showing the interaction of bacteria and fungi and present a wider view of the role of the microbiome in female infertility.

Weaknesses:<br /> - This is a pilot study with only 24 cases and 24 controls. Because the human microbiota entails individual variability, this work should be confirmed with a higher sample size to achieve enough statistical power.<br /> - The authors do not report here the use of blank controls. The use of this type of control is important to "subtract" the potential background from plasticware, buffer or reagents from the real signal. Lack of controls may lead to microbiome artefacts in the results. This can be seen in the results presented where the authors report some bacterial contaminants (Agrobacterium tumefaciensis, Aequorivita lutea, Chitinophagaceae, Marinobacter vinifirmus, etc) as part of the most common bacteria found in cervical samples.<br /> - Samples used for this study were collected from the cervix. Why not collect samples from the uterine cavity and isthmocele fluid (for cases)? In their previous paper using samples from the same research protocol ((IRB no. 2019ZSLYEC-005S) they used endometrial tissue from the patients, so access to the uterine cavity was guaranteed.<br /> - Through the use of shotgun genomics, results from all the genomes of the organisms present in the sample are obtained. However, the authors have only used the metagenomic data to infer the taxonomical annotation of fungi and bacteria.

Reviewer #3 (Public Review):

In the present study, Chen et al. revealed the fungal composition and explored its interaction with bacteria in Caesarean section scar diverticulum (CSD) patients. Performing metagenomic and mass spectrometry analysis, they found specific fungi could alter bacterial abundance through regulating the production of several metabolites such as Goyaglycoside A and Janthitrem E, which results in disruption of bacterial composition stability. Their study drew a conclusion that abnormal fungal composition and activity are essential drivers for bacterial dysbiosis in CSD patients. However, the results are not substantial enough and there are many format errors throughout the manuscript. In addition, I have some concerns or suggestions that may help to improve this work.

Major<br /> 1. Smoke or drink conditions, as well as diseases like hypertension and diabetes are important factors that could influence the metabolism of the host, thus the authors should add them in the exclusion criteria in the Methods.<br /> 2. The sample size of this study is not large enough to draw a convincing conclusion.