Reviewer #2 (Public Review):

A large number of ovarian experiments have been conducted - especially in morphological and molecular biology studies - specifically removing the ovarian membrane. This experiment is a good supplement to existing knowledge and plays an important role in early ovarian development and the regulation of ovarian homeostasis during the estrous cycle. There are also innovations in research ideas and methods, which will meet the requirements of experimental design and provide inspiration for other researchers.

This reviewer did not identify any major issues with the article. However, the following points could be further clarified:

(1) Is there any comparative data on the proteomics of RO and rete testis in early development? With some molecular markers also derived from rete testis, it would be better to provide the data or references.

(2) Although the size of RO and its components is quite small and difficult to operate, the researchers in this article had already been able to perform intracavitary injection of EOR and extract EOR or CR for mass spectrometry analysis. Therefore, can EOR, CR, or IOR be damaged or removed, providing further strong evidence of ovarian development function?

(3) Although IOR is shown on the schematic diagram, it cannot be observed in the immunohistochemistry pictures in Figure 1 and Figure 3. The authors should provide a detailed explanation.

Reviewer #3 (Public Review):

Summary:

The rete ovarii (RO) has long been disregarded as a non-functional structure within the ovary. In their study, Anbarci and colleagues have delineated the markers and developmental dynamics of three distinct regions of the RO - the intraovarian rete (IOR), the extraovarian rete (EOR), and the connecting rete (CR). Notably focusing on the EOR, the authors presented evidence illustrating that the EOR forms a convoluted tubular structure culminating in a dilated tip. Intriguingly, microinjections into this tip revealed luminal flow towards the ovary containing potentially secreted functional proteins. Additionally, the EOR cells exhibit associations with vasculature, macrophages, and neuronal projections, proposing the notion that the RO may play a functional role in ovarian development during critical ovariogenesis stages. By identifying marker genes within the RO, the authors have also suggested that the RO could serve as a potential structure linking the ovary with the neuronal system.

Strengths:

Overall, the reviewer commends the authors for their systematic research on the RO, shedding light on this overlooked structure in developing ovaries. Furthermore, the authors have proposed a series of hypotheses that are both captivating and scientifically significant, with the potential to reshape our understanding of ovarian development through future investigations.

Weaknesses:

There is a lack of conclusive data supporting many conclusions in the manuscript. Therefore, the paper's overall conclusions should be moderated until functional validations are conducted.

Joint Public Review:

Summary:

Idiopathic scoliosis (IS) is a common spinal deformity. Various studies have linked genes to IS, but underlying mechanisms are unclear such that we still lack understanding of the causes of IS. The current manuscript analyzes IS patient populations and identifies EPHA4 as a novel associated gene, finding three rare variants in EPHA4 from three patients (one disrupting splicing and two missense variants) as well as a large deletion (encompassing EPHA4) in a Waardenburg syndrome patient with scoliosis. EPHA4 is a member of the Eph receptor family. Drawing on data from zebrafish experiments, the authors argue that EPHA4 loss of function disrupts the central pattern generator (CPG) function necessary for motor coordination.

Strengths:

The main strength of this manuscript is the human genetic data, which provides convincing evidence linking EPHA4 variants to IS. The loss of function experiments in zebrafish strongly support the conclusion that EPHA4 variants that reduce function lead to IS.

Weaknesses:

The conclusion that disruption of CPG function causes spinal curves in the zebrafish model is not well supported. The authors' final model is that a disrupted CPG leads to asymmetric mechanical loading on the spine and, over time, the development of curves. This is a reasonable idea, but currently not strongly backed up by data in the manuscript. Potentially, the impaired larval movements simply coincide with, but do not cause, juvenile-onset scoliosis. Support for the authors' conclusion would require independent methods of disrupting CPG function and determining if this is accompanied by spine curvature. At a minimum, the language of the manuscript could be toned down, with the CPG defects put forward as a potential explanation for scoliosis in the discussion rather than as something this manuscript has "shown". An additional weakness of the manuscript is that the zebrafish genetic tools are not sufficiently validated to provide full confidence in the data and conclusions.

Reviewer #2 (Public Review):

Summary:

This manuscript described the second earliest known winged ovule without a capule in the Famennian of Late Devonian. Using Mathematical analysis, the authors suggest that the integuments of the earliest ovules without a cupule, as in the new taxon and Guazia, evolved functions in wind dispersal.

Strengths:

The new ovule taxon's morphological part is convincing. It provides additional evidence for the earliest winged ovules, and the mathematical analysis helps to understand their function.

Weaknesses:

The discussion should be enhanced to clarify the significance of this finding. What is the new advance compared with the Guazia finding? The authors can illustrate the character transformations using a simplified cladogram. The present version of the main text looks flat.

Reviewer #1 (Public Review):

Summary:

It is evident that studying leukocyte extravasation in vitro is a challenge. One needs to include physiological flow, culture cells and isolate primary immune cells. Timing is of utmost importance and a reproducible setup essential. Extra challenges are met when extravasation kinetics in different vascular beds is required, e.g., across the blood-brain barrier. In this study, the authors describe a reliable and reproducible method to analyze leukocyte TEM under physiological flow conditions, including this analysis. That the software can also detect reverse TEM is a plus.

Strengths:

It is quite a challenge to get this assay reproducible and stable, in particular as there is flow included. Also for the analysis, there is currently no clear software analysis program, and many labs have their own methods. This paper gives the opportunity to unify the data and results obtained with this assay under label-free conditions. This should eventually lead to more solid and reproducible results.

Also, the comparison between manual and software analysis is appreciated.

Weaknesses:

The authors stress that it can be done in BBB models, but I would argue that it is much more broadly applicable. This is not necessarily a weakness of the study but more an opportunity to strengthen the method. So I would encourage the authors to rewrite some parts and make it more broadly applicable.

Reviewer #2 (Public Review):

Summary:

This paper develops an under-flow migration tracker to evaluate all the steps of the extravasation cascade of immune cells across the BBB. The algorithm is useful and has important applications.

Strengths:

Algorithm is almost as accurate as manual tracking and importantly saves time for researchers.

Weaknesses:

Applicability can be questioned because the device used is 2D and physiological biology is in 3D. Comparisons to other automated tools was not performed by the authors.

Reviewer #3 (Public Review):

Summary:

The authors aimed to establish a faster and more efficient method of tracking steps of T-cell extravasation across the blood brain barrier. The authors developed a framework to visualize, recognize and track the movement of different immune cells across primary human and mouse brain microvascular endothelial cells without the need for fluorescence-based imaging. The authors succinctly describe the basic requirements for tracking in the introduction followed by an in-depth account of the execution.

Weaknesses and Strengths:

Materials & methods and results:

(1) The methods section also lacks details of the microfluidic device that the authors talk about in the paper. Under physiological sheer stress, the T-cells detach from the pMBMEC monolayer, and are hence unable to be detected; however, this observation requires an explanation pertaining to the reason of occurrence and potential solutions to circumvent it to ensure physiologically relevant experimental parameters.

(2) The author describes a method for debris exclusion using UFMTrack that eliminates objects of <30 pixels in size from analysis based on a mean pixel size of 400 for T lymphocytes. However, this mean pixel size appears to stem from in-vitro activated CD8 T cells, which rapidly grow and proliferate upon stimulation. In line with this, activated lymphocytes exhibit increased cytoplasmic area, making them appear less dense or "brighter" by phase microscopy compared to naïve lymphocytes, which are relatively compact and subsequently appear dimmer. Given this, it is not clear whether UFMTrack is sufficiently trained to identify naïve human lymphocytes in circulating blood, nor smaller, murine lymphocytes. Analysis of each lymphocyte subtype in terms of pixel size and intensity would be beneficial to strengthen the claim that UFMTrack can identify each of these populations. Additionally, demonstrating that UFMTrack can correctly characterize the behavior of naïve versus activated lymphocytes isolated from murine and human sources would strengthen the claim that UFMTrack can be broadly applied to study lymphocyte dynamics in diverse models without additional training

(3) Average precision was compared to the analysis of UFMTrack but it is unclear how average precision was calculated. This information should have been included in the methods section

(4) CD4 and CD8 T cells exhibit distinct biology and interaction kinetics driven in part by their MHC molecule affinity and distinct receptor expression profiles. Thus, it is unclear why two distinct mechanisms of endothelial cell activation are needed to see differences between the populations.

(5) The BMECs are barrier tissues but were cultured on µdishes in this study. To study the transmigration of T-cells across the endothelium, the model would have been more relevant on a semi-permeable membrane instead of a closed surface.

(6) Methods are provided for the isolation and expansion of human effector and memory CD4+ T cells. However, there is no mention of specific CD4+ T cell populations used for analysis with UFMTrack, nor a clear breakdown of tracking efficiency for each subpopulation. Further, there is no similar method for the isolation of CD8+ T cell compartments. A clear breakdown of the performance efficiency of UFMTrack with each cell population investigated in this study would provide greater insight into the software's performance with regard to tracking the behavior and movement of distinct immune populations.

(7) The results section is quite extensive and discusses details of establishment of the framework while highlighting both the pros and cons of the different aspects of the process, for example the limitation of the two models, 2D and 2D+T were highlighted well. However, the results section includes details which may be more fitting in the methods section.

(8) A few statements in the results section lacked literary support, which was not provided in the discussion either, such as support for increased variance of T-cell instantaneous speed on stimulated vs non-stimulated pMBMECs. Another example is the enhancement of cytokine stimulation directed T-cell movement on the pMBMECs that the authors observed but failed to relay the physiological relevance of it. The authors don't provide enough references for developments in the field prior to their work which form the basis and need for this technology.

(9) The rationale for use of OT-1 and 2D2-derived murine lymphocytes is unclear here. The OT-1 model has been generated to study antigen-specific CD8+ T cell responses, while the 2D2 model has been generated to recapitulate CD4 T cell-specific myelin oligodendrocyte glycoprotein (MOG) responses.

Figures and text:

(1) There are certain discrepancies and misarrangement of figures and text. For example, discussion of the effect of sheer flow on T cell attachment as part of the introduction in figure 1 and then mentioning it in the text again in the results section as part of figure 4 is repetitive.

(2) Section IV, subsection 1 of the results section, refers to 'data acquisition section above' in line 279, however the said section is part of materials and methods which is provided towards the end of the manuscript.

(3) There are figures in the manuscript that have not been referenced in the results section, for example, figure 3A and B. Figure 1 hasn't been addressed until subsection 7 of materials and methods

(4) A lack of significance but an observed trend of increased variance of T cell instantaneous speed is reported in line 296-298; however, the graph (figure 4G) shows a significant change in instantaneous speed between non-stimulated and TNFα-stimulated systems. This is misleading to the readers.

(5) The authors talk about three beginner experimentors testing the manual T cell tracking process but figure 5 only showcases data from two experimentors without stating the reason for excluding experimentor 1.

Discussion:

(1) While the discussion captures the major takeaways from the paper, it lacks relevant supporting references to relate the observation to physiological conditions and applicability.

(2) The discussion lacks connection to the results since the figures were not referenced while discussing an observed trend

(3) The authors briefly looked into mouse and human BMECs and their individual interaction with T-cells, but don't discuss the differences between the two, if any, that challenged their framework.

(4) Even though though the imaging tool relies on difference in appearance for detection, the authors talk about lack of feasibility in detecting transmigration of BMDMs due to their significantly different appearance. The statement lacks a problem solving approach to discuss how and why this was the case.

Relevance to the field:

Utilizing the framework provided by the authors, the application can be adapted and/or utilized for visualizing a range of different cell types, provided they are different in appearance. However, this would require extensive changes to the script and won't be adaptable in its current form.

Reviewer #1 (Public Review):

Summary:

The study seeks to establish accurate computational models to explore the role of hydrodynamic interactions on energy savings and spatial patterns in fish schools. Specifically, the authors consider a system of (one degree-of-freedom) flapping airfoils that passively position themselves with respect to the streamwise direction, while oscillating at the same frequency and amplitude, with a given phase lag and at a constant cross-stream distance. By parametrically varying the phase lag and the cross-stream distance, they systematically explore the stability and energy costs of emergent configurations. Computational findings are leveraged to distill insights into universal relationships and clarify the role of the wake of the leading foil.

Strengths:

(1) The use of multiple computational models (computational fluid dynamics, CFD, for full Navier-Stokes equations and computationally efficient inviscid vortex sheet, VS, model) offers an extra degree of reliability of the observed findings and backing to the use of simplified models for future research in more complex settings.

(2) The systematic assessment of the stability and energy savings in multiple configurations of pairs and larger ensembles of flapping foils is an important addition to the literature.

(3) The discovery of a linear phase-distance relationship in the formation attained by pairs of flapping foils is a significant contribution, which helps compare different experimental observations in the literature.

(4) The observation of a critical size effect for in-line formations of larger, above which cohesion and energetic benefits are lost at once, is a new discovery in the field.

Weaknesses:

(1) The extent to which observations on one-degree-of-freedom flapping foils could translate to real fish schools is presently unclear so some of the conclusions on live fish schools are likely to be overstated and would benefit from some more biological framing.

(2) The analysis of non-reciprocal coupling is not as novel as the rest of the study and potentially not as convincing due to the chosen linear metric of interaction (that is, the flow agreement).

Overall, this is a rigorous effort on a critical topic: findings of the research can offer important insight into the hydrodynamics of fish schooling, stimulating interdisciplinary research at the interface of computational fluid mechanics and biology.

Reviewer #2 (Public Review):

The document "Mapping spatial patterns to energetic benefits in groups of flow-coupled swimmers" by Heydari et al. uses several types of simulations and models to address aspects of stability of position and power consumption in few-body groups of pitching foils. I think the work has the potential to be a valuable and timely contribution to an important subject area. The supporting evidence is largely quite convincing, though some details could raise questions, and there is room for improvement in the presentation. My recommendations are focused on clarifying the presentation and perhaps spurring the authors to assess additional aspects:

(1) Why do the authors choose to set the swimmers free only in the propulsion direction? I can understand constraining all the positions/orientations for investigating the resulting forces and power, and I can also understand the value of allowing the bodies to be fully free in x, y, and their orientation angle to see if possible configurations spontaneously emerge from the flow interactions. But why constrain some degrees of freedom and not others? What's the motivation, and what's the relevance to animals, which are fully free?

(2) The model description in Eq. (1) and the surrounding text is confusing. Aren't the authors computing forces via CFD or the VS method and then simply driving the propulsive dynamics according to the net horizontal force? It seems then irrelevant to decompose things into thrust and drag, and it seems irrelevant to claim that the thrust comes from pressure and the drag from viscous effects. The latter claim may in fact be incorrect since the body has a shape and the normal and tangential components of the surface stress along the body may be complex.

(3) The parameter taudiss in the VS simulations takes on unusual values such as 2.45T, making it seem like this value is somehow very special, and perhaps 2.44 or 2.46 would lead to significantly different results. If the value is special, the authors should discuss and assess it. Otherwise, I recommend picking a round value, like 2 or 3, which would avoid distraction.

(4) Some of the COT plots/information were difficult to interpret because the correspondence of beneficial with the mathematical sign was changing. For example, DeltaCOT as introduced on p. 5 is such that negative indicates bad energetics as compared to a solo swimmer. But elsewhere, lower or more negative COT is good in terms of savings. Given the many plots, large amounts of data, and many quantities being assessed, the paper needs a highly uniform presentation to aid the reader.

(5) I didn't understand the value of the "flow agreement parameter," and I didn't understand the authors' interpretation of its significance. Firstly, it would help if this and all other quantities were given explicit definitions as complete equations (including normalization). As I understand it, the quantity indicates the match of the flow velocity at some location with the flapping velocity of a "ghost swimmer" at that location. This does not seem to be exactly relevant to the equilibrium locations. In particular, if the match were perfect, then the swimmer would generate no relative flow and thus no thrust, meaning such a location could not be an equilibrium. So, some degree of mismatch seems necessary. I believe such a mismatch is indeed present, but the plots such as those in Figure 4 may disguise the effect. The color bar is saturated to the point of essentially being three tones (blue, white, red), so we cannot see that the observed equilibria are likely between the max and min values of this parameter.

(6) More generally, and related to the above, I am favorable towards the authors' attempts to find approximate flow metrics that could be used to predict the equilibrium positions and their stability, but I think the reasoning needs to be more solid. It seems the authors are seeking a parameter that can indicate equilibrium and another that can indicate stability. Can they clearly lay out the motivation behind any proposed metrics, and clearly present complete equations for their definitions? Further, is there a related power metric that can be appropriately defined and which proves to be useful?

(7) Why do the authors not carry out CFD simulations on the larger groups? Some explanations should be given, or some corresponding CFD simulations should be carried out. It would be interesting if CFD simulations were done and included, especially for the in-line case of many swimmers. This is because the results seem to be quite nuanced and dependent on many-body effects beyond nearest-neighbor interactions. It would certainly be comforting to see something similar happen in CFD.

(8) Related to the above, the authors should discuss seemingly significant differences in their results for long in-line formations as compared to the CFD work of Peng et al. [48]. That work showed apparently stable groups for numbers of swimmers quite larger than that studied here. Why such a qualitatively different result, and how should we interpret these differences regarding the more general issue of the stability of tandem groups?

(9) The authors seem to have all the tools needed to address the general question about how dynamically stable configurations relate to those that are energetically optimal. Are stable solutions optimal, or not? This would seem to have very important implications for animal groups, and the work addresses closely related topics but seems to miss the opportunity to give a definitive answer to this big question.

(10) Time-delay particle model: This model seems to construct a simplified wake flow. But does the constructed flow satisfy basic properties that we demand of any flow, such as being divergence-free? If not, then the formulation may be troublesome.

Reviewer #1 (Public Review):

Summary:

This is an interesting study by Xu et al showing the effects of infection with the Treponema pallidum virus (which causes syphilis disease) on neuronal development using iPSC-derived human brain organoids as a model and single-cell RNA sequencing. This work provides an important insight into the impact of the virus on human development, bridging the gap between the phenomena observed in studies using animal models as well as non-invasive human studies showing developmental abnormalities in fetuses infected with the virus in utero through maternal vertical transmission.

Using single-cell RNAseq in combination with qPCR and immunofluorescence techniques, the authors show that T. pallidum infected organoids are smaller in size, in particular during later growth stages, contain a larger number of undifferentiated neuronal lineage cells, and exhibit decreased numbers of specific neuronal subcluster, which the authors have identified as undifferentiated hindbrain neurons.

The study is an important first step in understanding how T. pallidum affects human neuronal development and provides important insight into the potential mechanisms that underlie the neurodevelopmental abnormalities observed in infected human fetuses.

Strengths:

(1) The study is well written, and the data quality is good for the most part.

(2) The study provides an important first step in utilizing human brain organoids to study the impact of T. pallidum infection on neuronal development.

(3) The study's conclusions may provide important insight to other researchers focused on studying how viral infections impact neuronal development.

Reviewer #3 (Public Review):

This article is the first report to study the effects of T. pallidum on the neural development of an iSPC-derived brain organoid model. The study indicates that T. pallidum inhibits the differentiation of subNPC1B neurons into hindbrain neurons, hence affecting brain organoid neurodevelopment. Additionally, the TCF3 and notch signaling pathways may be involved in the inhibition of the subNPC1B-hindbrain neuron differentiation axis. While the majority of the data in this study support the conclusions, there are still some questions that need to be addressed and data quality needs to be improved. The study provides valuable insights for future investigations into the mechanisms underlying congenital neurodevelopment disability.

Reviewer #1 (Public Review):

The revised manuscript "Diffusive lensing as a mechanism of intracellular transport and compartmentalization" is very similar to the original manuscript. The main difference between the revised and the original manuscript is that the authors have removed the reference to viscosity gradient and instead talk of diffusivity gradient. With this change the manuscript the analysis and claims in the manuscript are much more aligned. The manuscript, as the original version, explores the role of spatially varying diffusion constant in three scenarios:

(i) Spatial localization of non-particles<br /> (ii) Clustering in presence of inter-particle interactions<br /> (iii) Moment analysis for non-interacting particles in space with discrete patches of inhomogeneous diffusivity.

Since the manuscript has not changed much the strengths and weaknesses, in my opinion, remain similar to that of the original manuscript.

Strengths: The implications of a heterogeneous environment on phase separation and reaction kinetics in cells are under-explored. This makes the general theme of this manuscript relevant and interesting.

Weaknesses: The central part of the paper "diffusive lensing", i.e., particles localizing in the region of low diffusion constant is not new. Some of the papers authors cite already show that. The parts on phase separation and frap analysis that could provide new results are not rigorous enough for a theory paper.

I reiterate some of my comments from the original version that are valid for the revised version as well.

My main criticism was not to say that some convention should be used or some not. But instead, the main point was to say that just because there is spatial diffusion constant that does not mean there will be a spatial gradient of particles. From the authors response to my comments, it is clear that they understand the subtilties around it and are aware of the relevant papers. However, a reader not familiar with this discussion may work under the impression that if there if there is a spatialy varying diffusion constant in cell there will be an accumulation of particles in the region of low diffusivity but that may not always be the case. Moreover, localisation of particles in the region of low diffusivity has been reported in many different context. Some of the papers that the author cite already show that. For example, in Rupprecht et al. 2018 non-isothermal interpretation is applied to the dynamics of objects inside cells.

Given that the central result is not new. The paper could still be of general interest to the biophysics community if the follow up sections (ii) Clustering in presence of inter-particle interactions and (iii) Moment analysis for non-interacting particles in space with discrete patches of inhomogeneous diffusivity were analysed rigorously.

Reviewer #2 (Public Review):

Summary:

The authors study through theory and simulations the diffusion of microscopic particles, and aim to account for the effects of inhomogeneous viscosity and diffusion - in particular regarding the intracellular environment. They propose a mechanism, termed "Diffusive lensing", by which particles are attracted towards low-diffusivity regions where they remain trapped. To obtain these results, the authors rely on agent-based simulations using custom rules performed within the Ito stochastic calculus convention, without drift. They acknowledge the fact that this convention does not describe equilibrium systems, and that their results would not hold at equilibrium - and discard these facts by invoking the facts that cells are out-of-equilibrium. Finally, they show some applications of their findings, in particular enhanced clustering in the low-diffusivity regions. The authors conclude that as inhomogeneous diffusion is ubiquitous in life, so must their mechanism be, and hence it must be important.

Strengths:

The article is well-written, clearly intelligible, its hypotheses are stated relatively clearly and the models and mathematical derivations are compatible with these hypotheses. In the appendices, the authors connect their findings to known results for classic stochastic differential equation formalisms.

Weaknesses:

This study is, in my opinion, deeply flawed. The main problem lies in the hypotheses, in particular the choice of considering drift-less dynamics in the Ito convention. It is regrettable that the authors choose to use agent-based custom simulations with little physical motivation, rather than a well-established stochastic differential equations framework.

Indeed, stochastic conventions are a notoriously tricky business, but they are both mathematically and physically well-understood and do not result in any "dilemma" [some citations in the article, such as (Lau and Lubensky) and (Volpe and Wehr), make an unambiguous resolution of these]. In the continuous-time limit, conventions are not an intrinsic, fixed property of a system, but a choice of writing; however, whenever going from one to another, one must include a corresponding "spurious drift" that compensates the effect of this change - a mathematical subtlety that is omitted in the article (except in a quick note in the appendix): in the presence of diffusive gradients, if the drift is zero in one convention, it will thus be non-zero in another. It is well established that for equilibrium systems obeying fluctuation-dissipation, the spurious drift vanishes in the anti-Ito stochastic convention; more precisely one can write in the anti-Ito convention

dx/dt = - D(x)/kT grad U(x) + sqrt(2D(x)) dW

with D(x) the diffusion, kT the thermal energy (which is space-independent at equilibrium), and dW a d-dimensional Wiener process. Equivalently one can write in the Ito convention:

dx/dt = - D(x)/kT grad U(x) + sqrt(2D(x)) dW + div D(x) (*)

where the latter term is the spurious drift arising from convention change. This ensures that the diffusion gradients do not induce currents and probability gradients, and thus that the steady-state PDF is the Gibbs measure (this form has been confirmed experimentally, for instance, for colloidal particles near walls, that have strong diffusivity gradients despite not having significant forces). It generalizes to near-equilibrium systems with non-conservative forces and/or temperature gradient in the form:

dx/dt = F(x) + sqrt(2D(x)) dW + div D(x) (**)

where the drift field F(x) encodes these forces. In some cases, it has been shown through careful microscopic analysis that one can have effectively a different form for the last term, namely

dx/dt = F(x) + sqrt(2D(x)) dW + alpha div D(x)

where alpha is a "convention parameter" that would be =1 at equilibrium. For instance, in the Volpe and Wehr review this can occur through memory effects in robotic dynamics, or through strong fluctuation-dissipation breakdown. In a near-equilibrium system, this should be strongly justified, as the continuous-time dynamics with alpha \neq 1 and drift F would be indistinguishable from one with alpha = 1 and drift F + (1-alpha) div D: the authors would have the burden of proving that the observed (absence of) drift is indeed due to alpha\neq 1, rather than to much more common force fields F(x).

Here, without further motivation than the statement that cells are out-of-equilibrium, drifts are arbitrarily set to zero in the Ito convention, which is in (**) the equivalent to adding a force with drift $-div D$ exactly compensating the spurious drift. It is the effects of this arbitrary force that are studied in the article. The fact that it results in probability gradients is trivial once formulated this way (and in no way is this new - many of the references, for instance Volpe and Wehr, mention this). Enhanced clustering is also a trivial effect of this probability gradient (the local concentration is increased by this force field, so phase separation can occur). As a side note the "neighbor sensing" scheme to describe interactions is itself very peculiar and not physically motivated - it violates stochastic thermodynamics laws too, as detailed balance is apparently not respected. There again, the authors have chosen to disregard a century of stochastic thermodynamics in favor of a non-justified unphysical custom rule.

The authors make no further justification of their choice of driftless Ito simulations than the fact that cells are out-of-equilibrium, leaving the feeling that this is a detail. They make mentions of systems (eg glycogen, prebiotic environment) for which (near-)equilibrium physics should mostly prevail, and of fluctuation dissipation ("Diffusivity varies inversely with viscosity", in the introduction). Yet the "phenomenon" they discuss is entirely reliant on an undiscussed mechanism by which these assumptions would be completely violated (the citations they make for this - Gnesotto '18 and Phillips '12 - are simply discussions of the fact that cells are out-of-equilibrium, not on any consequences on the convention).

Finally, while inhomogeneous diffusion is ubiquitous, the strength of this effect in realistic conditions is not discussed. Even in the most "optimistic" case where alpha=0 would make sense (knowing that in the cellular context we are discussing thermal systems immersed in water and if energy consumption and metabolism were stopped alpha would relax back to 1), the equation (*) above shows that having zero ito drift is equivalent to having a potential countering the spurious drift, with value

U(x) = kT log(D(x) / D0 )

[I have assumed isotropic diffusion for simplicity here, so the div is replaced by a grad]. This means that the diffusion contrasts logarithmically compare to the chemical potential ones -- for instance a major diffusion difference of 100x is equivalent to 4.6kT in potential energy, a relatively modest effect. To prove that the authors' effect of "diffusive lensing" is involved in such a system, one would thus have to<br /> 1) observe strong spatial variations of the diffusion coefficient (this is doable, and was done before), AND<br /> 2) show that there is an enrichment of the diffusing species in the low-diffusion region inversely proportional to the diffusion, AND<br /> 3) show that this enrichment cannot be attributed to mild differences in potential energy, for instance by showing that if nonequilibrium energy consumption stops, the concentration fully homogenizes while the diffusion gradients remain.

If the authors were to successfully show all that in an experimental system, or design a theoretical framework where these effects convincingly emerge from physically realistic microscopic dynamical rules, they would have indeed discovered a new phenomenon. In contrast, the current article only demonstrates the well-known fact that when using arbitrary dynamical rules in heterogeneous diffusion simulations, one can get concentration gradients.

Joint Public Review:

This manuscript by Yue et al. aims to understand the molecular mechanisms underlying the better reproductive outcomes of Tibetans at high altitude by characterizing the transcriptome and histology of full-term placenta of Tibetans and compare them to those Han Chinese at high elevations.

The approach is innovative, and the data collected are valuable for testing hypotheses regarding the contribution of the placenta to better reproductive success of populations that adapted to hypoxia. The authors identified hundreds of differentially expressed genes (DEGs) between Tibetans and Han, including the EPAS1 gene that harbors the strongest signals of genetic adaptation. The authors also found that such differential expression is more prevalent and pronounced in the placentas of male fetuses than those of female fetuses, which is particularly interesting, as it echoes with the more severe reduction in birth weight of male neonates at high elevation observed by the same group of researchers (He et al., 2022).

Comments on latest version:

The revised manuscript has incorporated the suggested changes and weakened conclusions regarding natural selection. Limitations of the study are also clearly stated in the Discussion section.

Reviewer #1 (Public Review):

This study is one in a series of excellent papers by the Forstmann group focusing on the ability of fMRI to reliably detect activity in small subcortical nuclei - in this case, specifically those purportedly involved in the hyper- and indirect inhibitory basal ganglia pathways. I have been very fond of this work for a long time, beginning with the demonstration of De Hollander, Forstmann et al. (HBM 2017) of the fact that 3T fMRI imaging (as well as many 7T imaging sequences) do not afford sufficient signal to noise ratio to reliably image these small subcortical nuclei. This work has done a lot to reshape my view of seminal past studies of subcortical activity during inhibitory control, including some that have several thousand citations.

Comments on revised version:

This is my second review of this article, now entitled "Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm" by Isherwood and colleagues.

The authors have been very responsive to the initial round of reviews.

I still think it would be helpful to see a combined investigation of the available 7T data, just to really drive the point home that even with the best parameters and a multi-study sample size, fMRI cannot detect any increases in BOLD activity on successful stop compared to go trials. However, I agree with the authors that these "sub samples still lack the temporal resolution seemingly required for looking at the processes in the SST."

As such, I don't have any more feedback.

Reviewer #2 (Public Review):

This work aggregates data across 5 openly available stopping studies (3 at 7 tesla and 2 at 3 tesla) to evaluate activity patterns across the common contrasts of Failed Stop (FS) > Go, FS > stop success (SS), and SS > Go. Previous work has implicated a set of regions that tend to be positively active in one or more of these contrasts, including the bilateral inferior frontal gyrus, preSMA, and multiple basal ganglia structures. However, the authors argue that upon closer examination, many previous papers have not found subcortical structures to be more active on SS than FS trials, bringing into question whether they play an essential role in (successful) inhibition. In order to evaluate this with more data and power, the authors aggregate across five datasets and find many areas that are *more* active for FS than SS, including bilateral preSMA, GPE, thalamus, and VTA. They argue that this brings into question the role of these areas in inhibition, based upon the assumption that areas involved in inhibition should be more active on successful stop than failed stop trials, not the opposite as they observed.

Since the initial submission, the authors have improved their theoretical synthesis and changed their SSRT calculation method to the more appropriate integration method with replacement for go omissions. They have also done a better job of explaining how these fMRI results situate within the broader response inhibition literature including work using other neuroscience methods.

They have also included a new Bayes Factor analysis. In the process of evaluating this new analysis, I recognized the following comments that I believe justify additional analyses and discussion:

First, if I understand the author's pipeline, for the ROI analyses it is not appropriate to run FSL's FILM method on the data that were generated by repeating the same time series across all voxels of an ROI. FSL's FILM uses neighboring voxels in parts of the estimation to stabilize temporal correlation and variance estimates and was intended and evaluated for use on voxelwise data. Instead, I believe it would be more appropriate to average the level 1 contrast estimates over the voxels of each ROI to serve as the dependent variables in the ROI analysis.

Second, for the group-level ROI analyses there seems to be inconsistencies when comparing the z-statistics (Figure 3) to the Bayes Factors (Figure 4) in that very similar z-statistics have very different Bayes Factors within the same contrast across different brain areas, which seemed surprising (e.g., a z of 6.64 has a BF of .858 while another with a z of 6.76 has a BF of 3.18). The authors do briefly discuss some instances in the frequentist and Bayesian results differ, but they do not ever explain by similar z-stats yield very different bayes factors for a given contrast across different brain areas. I believe a discussion of this would be useful.

Third, since the Bayes Factor analysis appears to be based on repeated measures ANOVA and the z-statistics are from Flame1+2, the BayesFactor analysis model does not pair with the frequentist analysis model very cleanly. To facilitate comparison, I would recommend that the same repeated measures ANOVA model should be used in both cases. My reading of the literature is that there is no need to be concerned about any benefits of using Flame being lost, since heteroscedasticity does not impact type I errors and will only potentially impact power (Mumford & Nichols, 2009 NeuroImage).

Fourth, though frequentist statistics suggest that many basal ganglia structures are significantly more active in the FS > SS contrast (see 2nd row of Figure 3), the Bayesian analyses are much more equivocal, with no basal ganglia areas showing Log10BF > 1 (which would be indicative of strong evidence). The authors suggest that "the frequentist and Bayesian analyses are monst in line with one another", but in my view, this frequentist vs. Bayesian analysis for the FS > SS contrast seems to suggest substantially different conclusions. More specifically, the frequentist analyses suggest greater activity in FS than SS in most basal ganglia ROIs (all but 2), but the Bayesian analysis did not find *any* basal ganglia ROIs with strong evidence for the alternative hypothesis (or a difference), and several with more evidence for the null than the alternative hypothesis. This difference between the frequentist and Bayesian analyses seems to warrant discussion, but unless I overlooked it, the Bayesian analyses are not mentioned in the Discussion at all. In my view, the frequentist analyses are treated as the results, and the Bayesian analyses were largely ignored.

Overall, I think this paper makes a useful and mostly solid contribution to the literature. I have made some suggestions for adjustments and clarification of the neuroimaging pipeline and Bayesian analyses that I believe would strengthen the work further.

Reviewer #1 (Public Review):

In this work, the authors investigate an important question - under what circumstances should a recurrent neural network optimised to produce motor control signals receive preparatory input before the initiation of a movement, even though it is possible to use inputs to drive activity just-in-time for movement?

This question is important because many studies across animal models have show that preparatory activity is widespread in neural populations close to motor output (e.g. motor cortex / M1), but it isn't clear under what circumstances this preparation is advantageous for performance, especially since preparation could cause unwanted motor output during a delay.

They show that networks optimised under reasonable constraints (speed, accuracy, lack of pre-movement) will use input to seed the state of the network before movement, and that these inputs reduce the need for ongoing input during the movement. By examining many different parameters in simplified models they identify a strong connection between the structure of the network and the amount of preparation that is optimal for control - namely, that preparation has the most value when nullspaces are highly observable relative to the readout dimension and when the controllability of readout dimensions is low. They conclude by showing that their model predictions are consistent with the observation in monkey motor cortex that even when a sequence of two movements is known in advance, preparatory activity only arises shortly before movement initiation.

Overall, this study provides valuable theoretical insight into the role of preparation in neural populations that generate motor output, and by treating input to motor cortex as a signal that is optimised directly this work is able to sidestep many of the problematic questions relating to estimating the potential inputs to motor cortex.

Reviewer #2 (Public Review):

This work clarifies neural mechanisms that can lead to a phenomenology consistent with motor preparation in its broader sense. In this context, motor preparation refers to activity that occurs before the corresponding movement. Another property often associated with preparatory activity is a correlation with global movement characteristics such as reach speed (Churchland et al., Neuron 2006), reach angle (Sun et al., Nature 2022), or grasp type (Meirhaeghe et al., Cell Reports 2023). Such activity has notably been observed in premotor and primary motor cortices, and it has been hypothesized to serve as an input to a motor execution circuit. The timing and mechanisms by which such 'preparatory' inputs are made available to motor execution circuits remain however unclear in general, especially in light of the presence of a 'trigger-like' signal that appears to relate to the transition from preparatory dynamics to execution activity (Kaufman et al. eNeuron 2016, Iganaki et al., Cell 2022, Zimnik and Churchland, Nature Neuroscience 2021).

The preparatory inputs have been hypothesized to fulfill one or several (non-mutually-exclusive) possible objectives. Two notable hypotheses are that these inputs could be shaped to maximize output accuracy under regularization of the input magnitude; or that they may help the flexible re-use of the neural machinery involved in the control of movements in different contexts.

Here, the authors investigate in detail how the former hypothesis may be compatible with the presence of early inputs in recurrent network models driving arm movements, and compare models to data.

Strengths:

The authors are able to deploy an in-depth evaluation of inputs that are optimized for producing an accurate output at a pre-defined time while using a regularization term on the input magnitude, in the case of movements that are thought to be controlled in a quasi-open loop fashion such as reaches.

First, the authors have identified that optimal control theory is a great framework to study this question as it provides methods to find and analyze exact solutions to this cost function in the case of models with linear dynamics. The authors not only use this framework to get an exact assessment of how much pre-movement input arises in large recurrent networks, but also give insight into the mechanisms by which it happens by dissecting in detail low-dimensional networks. The authors find that two key network properties - observability of the readout's nullspace and limited controllability - give rise to optimal inputs that are large before the start of the movement (while the corresponding network activity lies in the nullspace of the readout). Further, the authors numerically investigate the timing of optimized inputs in models with nonlinear dynamics, and find that pre-movement inputs can also arise in these more general networks. The authors also explore how some variations on their model's constraints - such as penalizing the input roughness or changing task contingencies about the go cue timing - affect their results. Finally, the authors point out some coarse-grained similarities between the pre-movement activity driven by the optimized inputs in some of the models they studied, and the phenomenology of preparation observed in the brain during single reaches and reach sequences. Overall, the authors deploy an impressive arsenal of tools and a very in-depth analysis of their models.

Limitations:

(1) Though the optimal control theory framework is ideal to determine inputs that minimize output error while regularizing the input norm or other simple input features, it cannot easily account for some other varied types of objectives - especially those that may lead to a complex optimization landscape. For instance, the reusability of parts of the circuit, sparse use of additional neurons when learning many movements, and ease of planning (especially under uncertainty about when to start the movement), may be alternative or additional reasons that could help explain the preparatory activity observed in the brain. It is interesting to note that inputs that optimize the objective chosen by the authors arguably lead to a trade-off in terms of other desirable objectives. Specifically, the inputs the authors derive are time-dependent, so a recurrent network would be needed to produce them and it may not be easy to interpolate between them to drive new movement variants. In addition, these inputs depend on the desired time of output and therefore make it difficult to plan, e.g. in circumstances when timing should be decided depending on sensory signals. Finally, these inputs are specific to the full movement chain that will unfold, so they do not permit reuse of the inputs e.g. in movement sequences of different orders. Of note, the authors have pointed out in the discussion how their framework may be extended in future work to account for some additional objectives, such as inputs' temporal smoothness or some strategies for dealing with go cue timing uncertainty.

(2) Relatedly, if the motor circuits were to balance different types of objectives, the activity and inputs occurring before each movement may be broken down into different categories that may each specialize into their own objective. For instance, previous work (Kaufman et al. eNeuron 2016, Iganaki et al., Cell 2022, Zimnik and Churchland, Nature Neuroscience 2021) has suggested that inputs occurring before the movement could be broken down into preparatory inputs 'stricto sensu' - relating to the planned characteristics of the movement - and a trigger signal, relating to the transition from planning to execution - irrespective of whether the movement is internally timed or triggered by an external event. The current work does not address which type(s) of early input may be labeled as 'preparatory' or may be thought of as a part of 'planning' computations, or whether these inputs may come from several different source circuits.

(3) While the authors rightly point out some similarities between the inputs that they derive and observed preparatory activity in the brain, notably during motor sequences, there are also some differences. For instance, while both the derived inputs and the data show two peaks during sequences, the data reproduced from Zimnik and Churchland show preparatory inputs that have a very asymmetric shape that really plummets before the start of the next movement, whereas the derived inputs have larger amplitude during the movement period - especially for the second movement of the sequence. In addition, the data show trigger-like signals before each of the two reaches. Finally, while the data show a very high correlation between the pattern of preparatory activity of the second reach in the double reach and compound reach conditions, the derived inputs appear to be more different between the two conditions. Note that the data would be consistent with separate planning of the two reaches even in the compound reach condition, as well as the re-use of the preparatory input between the compound and double reach conditions. Therefore, different motor sequence datasets - notably, those that would show even more coarticulation between submovements - may be more promising to find a tight match between the data and the author's inputs. Further analyses in these datasets could help determine whether the coarticulation could be due to simple filtering by the circuits and muscles downstream of M1, planning of movements with adjusted curvature to mitigate the work performed by the muscles while permitting some amount of re-use across different sequences, or - as suggested by the authors - inputs fully tailored to one specific movement sequence that maximize accuracy and minimize the M1 input magnitude.

(4) Though iLQR is a powerful optimization method to find inputs optimizing the author's cost function, it also has some limitations. First, given that it relies on a linearization of the dynamics at each timestep, it has a limited ability to leverage potential advantages of nonlinearities in the dynamics. Second, the iLQR algorithm is not a biologically plausible learning rule and therefore it might be difficult for the brain to learn to produce the inputs that it finds. Therefore, when observing differences between model and data, this can confound the question of whether it comes from a difference of assumed objective or a difference of optimization procedure. It remains unclear whether using alternative algorithms with different limitations - for instance, using variants of BPTT to train a separate RNN to produce the inputs in question - could impact some of the results.

(5) Under the objective considered by the authors, the amount of input occurring before the movement might be impacted by the presence of online sensory signals for closed-loop control. Even if considering that the inputs could include some sensory activity and/or that the RNN activity could represent general variables whose states can be decoded from M1, the model would not include mechanisms that process imperfect (delayed, noisy) sensory feedback to adapt the output in a trial-specific manner. It is therefore an open question whether the objective and network characteristics suggested by the authors could also explain the presence of preparatory activity before e.g. grasping movements that are thought to be more sensory-driven (Meirhaeghe et al., Cell Reports 2023).

Reviewer #3 (Public Review):

I remain enthusiastic about this study. The manuscript is well-written, logical, and conceptually clear. To my knowledge, no prior modeling study has tackled the question of 'why prepare before executing, why not just execute?' Prior studies have simply assumed, to emulate empirical findings, that preparatory inputs precede execution. They never asked why. The authors show that, when there are constraints on inputs, preparation becomes a natural strategy. In contrast, with no constraint on inputs, there is no need for preparation as one could get anything one liked just via the inputs during movement. For the sake of tractability, the authors use a simple magnitude constraint: the cost function punishes the integral of the squared inputs. Thus, if small inputs before movement can reduce the size of the inputs needed during movement, preparation is a good strategy. This occurs if (and only if) the network has strong dynamics (otherwise feeding it preparatory activity would not produce anything interesting). All of this is sensible and clarifying.

As discussed in the prior round of reviews, the central constraint that the authors use is a mathematically tractable stand-in for a range of plausible (but often trickier to define and evaluate) constraints, such as simplicity of inputs (or inputs being things that other areas could provide). The manuscript now embraces this fact more explicitly, and also gives some results showing that other constraints (such as on the derivative of activity, which is one component of complexity) can have the same effect. The manuscript also now discusses and addresses a modest weakness of the previous manuscript: the preparatory activity in their simulations is often overly complex temporally, lacking the (rough) plateau typically seen for data. Depending on your point of view, this is simply 'window dressing', but from my perspective it was important to know that their approach could yield more realistic-looking preparatory activity. Both these additions (the new constraint, and the more realistic temporal profile of preparatory activity) are added simply as supplementary figures rather than in the main text, and are brought up only in the Discussion. At first this struck me as slightly odd, but in the end I think this is appropriate. These are really Discussion-type issues, and dealing with them there makes sense. The 'different constraints' issue in particular is deep, tricky to explore for technical reasons, and could thus support a small research program. I think it is fair to talk about it thoughtfully (as the Discussion now does) and then just mention some simple results.

My remaining comments largely pertain to some subtle (but to me important) nuances at a few locations in the text. These should be easy for the authors to address, in whatever way they see fit.

Specific comments:

(1) The authors state the following on line 56: "For preparatory processes to avoid triggering premature movement, any pre-movement activity in the motor and dorsal pre-motor (PMd) cortices must carefully exclude those pyramidal tract neurons."<br /> This constraint is overly restrictive. PT neurons absolutely can change their activity during preparation in principle (and appear to do so in practice). The key constraint is looser: those changes should have no net effect on the muscles. E.g., if d is the vector of changes in PT neuron firing rates, and b is the vector of weights, then the constraint is that b'd = 0. d = 0 is one good way of doing this, but only one. Half the d's could go up and half could go down. Or they all go up, but half the b's are negative. Put differently, there is no reason the null space has to be upstream of the PT neurons. It could be partly, or entirely, downstream.<br /> In the end, this doesn't change the point the authors are making. It is still the case that d has to be structured to avoid causing muscle activity, which raises exactly the point the authors care about: why risk this unless preparation brings benefits? However, this point can be made with a more accurate motivation. This matters, because people often think that a null-space is a tricky thing to engineer, when really it is quite natural. With enough neurons, preparing in the null space is quite simple.

(2) Line 167: 'near-autonomous internal dynamics in M1'.<br /> It would be good if such statements, early in the paper, could be modified to reflect the fact that the dynamics observed in M1 may depend on recurrence that is NOT purely internal to M1. A better phrase might be 'near-autonomous dynamics that can be observed in M1'. A similar point applies on line 13. This issue is handled very thoughtfully in the Discussion, starting on line 713. Obviously it is not sensible to also add multiple sentences making the same point early on. However, it is still worth phrasing things carefully, otherwise the reader may have the wrong impression up until the Discussion (i.e. they may think that both the authors, and prior studies, believe that all the relevant dynamics are internal to M1). If possible, it might also be worth adding one sentence, somewhere early, to keep readers from falling into this hole (and then being stuck there till the Discussion digs them out).

(3) The authors make the point, starting on line 815, that transient (but strong) preparatory activity empirically occurs without a delay. They note that their model will do this but only if 'no delay' means 'no external delay'. For their model to prepare, there still needs to be an internal delay between when the first inputs arrive and when movement generating inputs arrive.

This is not only a reasonable assumption, but is something that does indeed occur empirically. This can be seen in Figure 8c of Lara et al. Similarly, Kaufman et al. 2016 noted that "the sudden change in the CIS [the movement triggering event] occurred well after (~150 ms) the visual go cue... (~60 ms latency)" Behavioral experiments have also argued that internal movement-triggering events tend to be quite sluggish relative to the earliest they could be, causing RTs to be longer than they should be (Haith et al. Independence of Movement Preparation and Movement Initiation). Given this empirical support, the authors might wish to add a sentence indicating that the data tend to justify their assumption that the internal delay (separating the earliest response to sensory events from the events that actually cause movement to begin) never shrinks to zero.

While on this topic, the Haith and Krakauer paper mentioned above good to cite because it does ponder the question of whether preparation is really necessary. By showing that they could get RTs to shrink considerably before behavior became inaccurate, they showed that people normally (when not pressured) use more preparation time than they really need. Given Lara et al, we know that preparation does always occur, but Haith and Krakauer were quite right that it can be very brief. This helped -- along with neural results -- change our view of preparation from something more cognitive that had to occur, so something more mechanical that was simply a good network strategy, which is indeed the authors current point. Working a discussion of this into the current paper may or may not make sense, but if there is a place where it is easy to cite, it would be appropriate.

Reviewer #1 (Public Review):

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.

Reviewer #2 (Public Review):

In this work, Dasgupta et al. investigate 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.

Reviewer #3 (Public Review):

The data reported here demonstrate that Sema7a defines the local behavior of growing axons in the developing zebrafish lateral line. The analysis is sophisticated and convincingly demonstrates effects on axon growth and synapse architecture. Collectively, the findings point to the idea that the diffusible form of sema7a may influence how axons grow within the neuromast and that the GPI-linked form of sema7a may subsequently impact how synapses form, though additional work is needed to strongly link each form to its' proposed effect on circuit assembly.

Comments on latest version:

The authors comprehensively and appropriately addressed most of the reviewers' concerns. In particular, they added evidence that hair cells express both Sema7A isoforms, showed that membrane bound Sema7A does not have long range effects on guidance, demonstrated how axons behave close to ectopic Sema7A, and analyzed other features of the hair cells that revealed no strong phenotypes. The authors also softened the language in many, but not all places. Overall, I am satisfied with the study as a whole.

Reviewer #4 (Public Review):<br /> <br /> This study provides direct evidence showing that Sema7a plays a role in the axon growth during the formation of peripheral sensory circuits in the lateral-line system of zebrafish. This is a valuable finding because the molecules for axon growth in hair-cell sensory systems are not well understood. The majority of the experimental evidence is convincing, and the analysis is rigorous. The evidence supporting Sema7a's juxtracrine vs. secreted role and involvement in synapse formation in hair cells is less conclusive. The study will be of interest to cell, molecular and developmental biologists, and sensory neuroscientists.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Of relevance to PD pathophysiology, the authors evaluated the physiological and morphological changes of DRN serotoninergic and dopaminergic neurons after a partial loss of nigrostriatal dopamine neurons, which serves as a mouse model of early parkinsonian pathology. Moreover, the authors identified a series of physiological and morphological changes of subtypes of DRN neurons that depend on nigral dopaminergic neurodegeneration, LC noradrenergic neurodegeneration, or both. Indeed this work highlights the importance of LC noradrenergic degeneration in PD pathophysiology.

Overall, this is a well-designed study with high significance to the Parkinson's research field.

Reviewer #2 (Public Review):

In this paper, Boi et al. thoroughly classified the electrophysiological and morphological characteristics of serotonergic and dopaminergic neurons in the DRN and examined the alterations of these neurons in the 6-OHDA-induced mouse PD model. Using whole-cell patch clamp recording, they found that 5-HT and dopamine (DA) neurons in the DRN are electrophysiologically distinct from each other. Additionally, they characterized distinct morphological features of 5-HT and DA neurons in the DRN. Notably, these specific features of 5-HT and DA neurons in the DRN exhibited different changes in the 6-OHDA-induced PD model. Then the authors utilized desipramine (DMI) to separate the effects of nigrostriatal DA depletion and noradrenaline (NA) depletion induced by 6-OHDA. Interestingly, protection from NA depletion by DMI pretreatment reversed the changes in 5-HT neurons, while having a minor impact on the changes in DA neurons in the DRN. These data indicate that the role of NA lesion in the altered properties of DRN 5-HT neurons by 6-OHDA is more critical than that of DA lesions.

Overall, this study provides foundational data on the 5-HT and DA neurons in the DRN and their potential involvement in PD symptoms. Given the deficits of the DRN in PD, this paper may offer insights into the cellular mechanisms underlying non-motor symptoms associated with PD.

Reviewer #2 (Public Review):

Summary:

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:

Overall, the manuscript is presented in a 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:

The manuscript has improved in clarity and conceptual and methodological considerations in response to the last review. However, the reported results still provide incomplete support for the claims the authors make in the paper.

In relation to other reviewers' earlier comments, the model notation used is still not consistent and model results are reported incompletely, which make it difficult to gain a full picture of the data and how they support the authors' secondary claims. For instance, across the models in the supplementary materials, ß coefficients are only reported selectively which makes it difficult to assess the model as a whole. Furthermore, different terms (task 1, task 2 vs. BM-Local, BM-global) are used to refer to the same levels of a variable, and it is unclear which levels of a dummy variable correspond to which task, making it overall very difficult to comprehend the modelling procedure.

Reviewer #3 (Public Review):

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 valuable and solid findings are informative for understanding this complex condition, as well as biological motion processing mechanisms in general. However, the correlations present a pattern that needs further examination in future studies because many of the differences between correlations are not significant.

Strengths:

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

Weaknesses:

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

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

Theoretical assumptions. The authors make some statements about local vs global biological motion processing that may have been made in previous studies, but would appear controversial and not definitive. E.g., that local BM processing does not improve with age and is uninfluenced by attention.

Reviewer #3 (Public Review):

In this work, Jarc et al. describe a method to decouple the mechanisms supporting progenitor self-renewal and expansion from feed-forward mechanisms promoting their differentiation.

The authors aimed at expanding pancreatic progenitor (PP) cells, strictly characterized as PDX1+/SOX9+/NKX6.1+ cells, for several rounds. This required finding the best cell culture conditions that allow sustaining PP cell proliferation along cell passages while avoiding their further differentiation. They achieve this by comparing the transcriptome of PP cells that can be expanded for several passages against the transcriptome of unexpanded (just differentiated) PP cells.

The optimized culture conditions enabled the selection of PDX1+/SOX9+/NKX6.1+ PP cells and their consistent, 2000-fold, expansion over ten passages and 40-45 days. Transcriptome analyses confirmed the stabilization of PP identity and the effective suppression of differentiation. These optimized culture conditions consisted in substituting the Vitamin A containing B27 supplement with a B27 formulation devoid of vitamin A (to avoid retinoic acid (RA) signaling from an autocrine feed-forward loop), substituting A38-01 with the ALK5 II inhibitor (ALK5i II) that targets primarily ALK5, supplementation of medium with FGF18 (in addition to FGF2) and the canonical Wnt inhibitor IWR-1, and cell culture on vitronectin-N (VTN-N) as a substrate instead of Matrigel.

The strength of this work relies on a clever approach to identify cell culture modifications that allow expansion of PP cells (once differentiated) while maintaining, if not reinforcing, PP cell identity. Along the work, it is emphasized that PP cell identity is associated to the co-expression of PDX1, SOX9 and NKX6.1. The optimized protocol is unique (among the other datasets used in the comparison shown here) at inducing a strong upregulation of GP2, a unique marker of human fetal pancreas progenitors. Importantly GP2+ enriched hPS cell-derived PP cells are more efficiently differentiating into pancreatic endocrine cells (Aghazadeh et al., 2022; Ameri et al., 2017).

The unlimited expansion of PP cells reported here would allow scaling-up the generation of beta cells, for the cell therapy of diabetes, by eliminating a source of variability derived from the number of differentiation procedures to be carried out when starting at the hPS cell stage each time. The approach presented here would allow selection of the most optimally differentiated PP cell population for subsequent expansion and storage. Among other conditions optimized, the authors report a role for Vitamin A in activating retinoic acid signaling in an autocrine feed-forward loop, and the supplementation with FGF18 to reinforce FGF2 signaling.

This is a relevant topic in the field of research, and some of the cell culture conditions reported here for PP expansion might have important implications in cell therapy approaches. Thus, the approach and results presented in this study could be of interest for researchers working in the field of in vitro pancreatic beta cell differentiation from hPSCs. Table S1 and Table S4 are clearly detailed and extremely instrumental to this aim.

Reviewer #2 (Public Review):

The paper presents a novel approach to expand iPSC-derived pdx1+/nkx6.1+ pancreas progenitors, making them potentially suitable for GMP-compatible protocols. This advancement represents a significant breakthrough for diabetes cell replacement therapies, as one of the current bottlenecks is the inability of expanding PP without compromising their differentiation potential. The study employs a robust dataset and state-of-the-art methodology, unveiling crucial signaling pathways (eg TGF, Notch...) responsible for sustaining pancreas progenitors while preserving their differentiation potential in vitro.

The current version of the paper has improved, increasing the clarity and providing clear explanations to the comments raised regarding quantifications, functionality of the cells in vivo etc...

The discussion on challenges adds depth to the study and encourages future research to build upon these important findings

Reviewer #1 (Public Review):

Summary:

The authors use innovative CRISPRi method to uncover regulators of cell density and volume in neutrophils. The results show that cells require NHE activity during chemoattractant-driven cell migration. Before migration occurs, cells also undergo a rapid cell volume increase. These results indicate that water flux, driven by ion channels, appears to play a central role in neutrophil migration. The paper is very well written and clear. The revised version has addressed all of my questions.

Reviewer #2 (Public Review):

Nagy et al investigated the role of volume increase and swelling in neutrophils in response to the chemoattractant. Authors show that following chemoattractant response cells lose their volume slightly owing to the cell spreading phase and then have a relatively rapid increase in the cell volume that is concomitant with cell migration. Authors performed an impressive genome-wide CRISPR screen and buoyant density assay to identify the regulators of neutrophil swelling. This assay showed that stimulating cells with chemoattractant fMLP lead to an increase in the cell volume that was abrogated with the FPR1 receptor knockout. The screen revealed a cascade that could potentially be involved cell swelling including NHE1 (sodium-proton antiporter) and PI3K. NHE1 and PI3K is required for chemoattractant-induced swelling in human primary neutrophils. Authors also suggest slightly different functions of NHE1 and PI3K activity where PI3K is also required for maintain chemoattractant-induced cell shape changes. Authors convincingly show that chemoattractant induced cell swelling is linked to cell migration and NHE1 is required for swelling at the later stages of swelling since the cells at the early point work on low-volume and low-velocity regime. Interesting authors also show that lack of swelling in NHE1 inhibited cells could be rescued by mild hypo-osmotic swelling strengthening the argument that water influx followed chemoattractant stimulation is important for potentiation for migration.

The conclusions of this paper are mostly well supported by data and is pretty convincing

Reviewer #1 (Public Review):

This study presents a novel application of the inverted encoding (i.e., decoding) approach to detect the correlates of crossmodal integration in the human EEG (electrophysiological) signal. The method is successfully applied to data from a group of 41 participants, performing a spatial localization task on auditory, visual, and audio-visual events. The analyses clearly show a behavioural superiority for audio-visual localization. Like previous studies, the results when using traditional univariate ERP analyses were inconclusive, showing once more the need for alternative, more sophisticated approaches. Instead, the principal approach of this study, harnessing the multivariate nature of the signal, captured clear signs of super-additive responses, considered by many as the hallmark of multisensory integration. Unfortunately, the manuscript lacks many important details in the descriptions of the methodology and analytical pipeline. Although some of these details can eventually be retrieved from the scripts that accompany this paper, the main text should be self-contained and sufficient to gain a clear understanding of what was done. (A list of some of these is included in the comments to the authors). Nevertheless, I believe the main weakness of this work is that the positive results obtained and reported in the results section are conditioned upon eye movements. When artifacts due to eye movements are removed, then the outcomes are no longer significant.

Therefore, whether the authors finally achieved the aims and showed that this method of analysis is truly a reliable way to assess crossmodal integration, does not stand on firm ground. The worst-case scenario is that the results are entirely accounted for by patterns of eye movements in the different conditions. In the best-case scenario, the method might truly work, but further experiments (and/or analyses) would be required to confirm the claims in a conclusive fashion.

If finally successful, this approach could bring important advances in the many fields where multisensory integration has been shown to play a role, by providing a way to bring much-needed coherence across levels of analysis, from behaviour to single-cell electrophysiology. To achieve this, one would have to make sure that the pattern of super-additive effects, the standard self-imposed by the authors as a proxy for multisensory integration, shows up reliably regardless of eye movement or artifact corrections. One first step toward this goal would be, perhaps, to facilitate the understanding of results in context by reporting both the uncorrected and corrected analyses in the main results section. Second, one could try to support the argument given in the discussion, pointing out the origin of the super-additive effects in posterior electrode sites, by also modelling frontal electrode clusters and showing they aren't informative as to the effect of interest.

Reviewer #2 (Public Review):

Summary:

This manuscript seeks to reconcile observations in multisensory perception - from behavior and neural responses. It is intuitively obvious that perceiving a stimulus via two senses results in better performance than one alone. In fact, it is not uncommon to observe that for a perceptual task, the percentage of correct responses seen with two senses is higher than the sum of the percentage correct obtained with each modality individually. i.e. the gains are "superadditive". The gains of adding a second sense are typically larger when the performance with the first sense is relatively poor - this effect is often called the principle of inverse effectiveness. More generally, what this tells us is that performance in a multisensory perceptual task is a non-linear sum of performance for each sensory modality alone.

Despite this abundant evidence of behavioral non-linearity in multisensory integration, evoked responses (EEG) to such sensory stimuli often show little evidence of it - and this is the problem this manuscript tackles. The key assertion made is that univariate analysis of the EEG signal is likely to average out the non-linear effects of integration. This is a reasonable assertion, and their analysis does indeed provide evidence that a multivariate approach can reveal non-linear interactions in the evoked responses.

Strengths:

It is of great value to understand how the process of multisensory integration occurs, and despite a wealth of observations of the benefits of perceiving the world with multiple senses, we still lack a reasonable understanding of how the brain integrates information. For example - what underlies the large individual differences in the benefits of two senses over one? One way to tackle this is via brain imaging, but this is problematic if important features of the processing - such as non-linear interactions are obscured by the lack of specificity of the measurements. The approach they take to the analysis of the EEG data allows the authors to look in more detail at the variation in activity across EEG electrodes, which averaging across electrodes cannot.

This version of the manuscript is well-written and for the most part clear. It shows a good understanding of the non-linear effects described above (where many studies show a poor understanding of "superadditivity" of perceptual performance) and the report of non-linear summation of neural responses is convincing.

A particular strength of the paper is their use of a statistical model of multisensory integration as their "null" model of neural responses, and the "inverted-encoder" which infers an internal representation of the stimulus which can explain the EEG responses. This encoder generates a prediction of decoding performance, which can be used to generate predictions of multisensory decoding from unisensory decoding, or from a sum of the unisensory internal representations.

In behavioural performance, it is frequently observed that the performance increase from two senses is close to what is expected from the optimal integration of information across the senses, in a statistical sense. It can be plausibly explained by assuming that people are able to weigh sensory inputs according to their reliability - and somewhat optimally. Critically the apparent "superadditive" effect on performance described above does not require any non-linearity in the sum of information across the senses but can arise from correctly weighting the information according to reliability.

The authors apply a similar model to predict the neural responses expected to audiovisual stimuli from the neural responses to audio and visual stimuli alone, assuming optimal statistical integration of information. The neural responses to audiovisual stimuli exceed the predictions of this model and this is the main evidence supporting their conclusion, and it is convincing.

Weaknesses:

The main weakness of the manuscript is that their behavioural data show no evidence of performance that exceeds the predictions of these statistical models. In fact, the models predict multisensory performance from unisensory performance pretty well. So this manuscript presents the opposite problem to that which motivated the study - neural interactions across the senses which appear to be more non-linear than perception. This makes it hard to interpret their results, as surely if these nonlinear neural interactions underlie the behaviour, then we should be able to see evidence of it in the behaviour? I cannot offer an easy explanation for this.

Overall, therefore, I applaud the motivation and the sophistication of the analysis method and think it shows great promise for tackling these problems, but the manuscript unfortunately brushes over an important problem specific to the results. It appeals to the higher-level reasoning - that non-linearity is a behavioural hallmark of integration and therefore we should see it in neural responses. Yet it ignores the fact that the behaviour observed here does not exceed the predictions of the "null" model applied to the neural response.

Part of the problem, I think, is that the authors never explain the difference between superadditivity of perceptual performance (proportion correct) and superadditivity of the underlying processing, which is implied by the EEG results but not their behavior. This is of course a difficult matter to describe succinctly or clearly (I somehow doubt I have). It is however worth addressing. The literature is full of confusing claims of superadditivity. I believe these authors understand this distinction and have an opportunity to represent it clearly for the benefit of all.

Joint Public Review:

Mahapatra and Takahashi report on the physiological consequences of pharmacologically blocking either clathrin and dynamin function during compensatory endocytosis or of the cortical actin scaffold both in the calyx of Held synapse and hippocampal boutons in acute slice preparations.

Although many aspects of these pharmacological interventions have been studied in detail during the past decades, this is a comprehensive and comparative study, which reveals some interesting differences between a fast synapse (Calyx of Held) tuned to reliably transmit at several 100 Hz and a more slow hippocampal CA1 synapse. In particular the authors find that acute disturbance of the synaptic actin network leads to a marked frequency-dependent enhancement of synaptic depression in the Calyx, but not in the hippocampal synapse. This striking difference between both preparations is the most interesting finding.

Comments on latest version:

The authors have done a great job revising the paper and only minor revisions are suggested to the Discussion of the paper.

Two quite relevant and recent papers should be cited and briefly discussed because they relate directly to Pitstop2 effects and actin-myosin-scaffold proteins in the calyx of Held synapse.

One is: Paksoy A et al, (2022) "Effects of the clathrin inhibitor Pitstop-2 on synaptic vesicle recycling at a central synapse in vivo." Front. Synaptic Neurosci. 14:1056308. doi: 10.3389/fnsyn.2022.1056308. This paper shows with EM that changes caused by PitStop2 perturbation of "clathrin function suggest that clathrin plays a role in SV recycling from both, the plasma membrane and large endosomes, under physiological activity patterns, in vivo."

Second: A role for actin-myosin and MLCK in short-term plasticity has been shown by Srinivasan G., et al. (2008) "The Pool of Fast Releasing Vesicles Is Augmented by Myosin Light Chain Kinase Inhibition at the Calyx of Held Synapse." J Neurophysiol 99: 1810-1824, 2008. The data here suggests that MLCK plays a crucial role in determining the size of the pool of synaptic vesicles that undergo fast release but not the Pr of the synapse. In other words, MLCK inhibition augments super-priming of vesicles at the calyx of Held synapse.

Reviewer #1 (Public Review):

Summary:

The authors aim to test the sensory recruitment theory of visual memory, which assumes that visual sensory areas are recruited for working memory and that these sensory areas represent visual memories in a similar fashion to how perceptual inputs are represented. To test the overlap between working memory (WM) and perception, the authors use coarse stimulus (aperture) biases that are known to account for (some) orientation decoding in visual cortex (i.e., stimulus energy is higher for parts of an image where a grating orientation is perpendicular to an aperture edge, and stimulus energy drives decoding). Specifically, the authors show gratings (with a given "carrier" orientation) behind two different apertures: One is a radial modulator (with maximal energy aligned with the carrier orientation) and the other an angular modulator (with maximal energy orthogonal to the carrier orientation). When subject detect contrast changes in these stimuli (the perceptual task), orientation decoding only works when training and testing within each modulator, but not across modulators, showing the impact of stimulus energy on decoding performance. Instead, when subjects remember the orientation over a 12s delay, orientation decoding works irrespective of the modulator used. The authors conclude that representations during WM are therefore not "sensory-like", given that they are immune to aperture biases. This invalidates the sensory recruitment hypothesis, or at least the part assuming that when sensory areas that are recruited during WM, they are recruited in a manner that resembles how these areas are used during perception.

Strengths:

Duan and Curtis very convincingly show that aperture effects that are present during perception, do not appear to be present during the working memory delay. Especially when the debate about "why can we decode orientations from human visual cortex" was in full swing, many may have quietly assumed this to be true (e.g., "the memory delay has no stimuli, and ergo no stimulus aperture effects"), but it is definitely not self-evident and nobody ever thought to test it directly until now. In addition to the clear absence of aperture effects during the delay, Duan and Curtis also show that when stimulus energy aligns with the carrier orientation, cross-generalization between perception and memory does work (which could explain why perception-to-memory cross decoding also works). All in all, this is a clever manipulation, and I'm glad someone did it, and did it well.

Weaknesses:

There seems to be a major possible confound that prohibits strong conclusions about "abstractions" into "line-like" representation, which is spatial attention. What if subjects simply attend the end points of the carrier grating, or attend to the edge of the screen where the carrier orientation "intersects" in order to do the task? This may also result in reconstructions that have higher bold at areas close to the stimulus/screen edges along the carrier orientation. The question then would be if this is truly an "abstracted representation", or if subjects are merely using spatial attention to do the task.

Alternatively (and this reaches back to the "fine vs coarse" debate), another argument could be that during memory, what we are decoding is indeed fine-scale inhomogenous sampling of orientation preferences across many voxels. This is clearly not the most convincing argument, as the spatial reconstructions (e.g., Figure 3A and C) show higher BOLD for voxels with receptive fields that are aligned to the remembered orientation (which is in itself a form of coarse scale bias), but could still play a role.

To conclude that the spatial reconstruction from the data indeed comes from a line-like representation, you'd need to generate modeled reconstructions of all possible stimuli and representations. Yes, Figure 4 shows that a line results in a modeled spatial map that resembles the WM data, but many other stimuli might too, and some may better match the data. For example, the alternative hypothesis (attention to grating endpoints) may very well lead to a very comparable model output to the one from a line. But testing this would not suffice, as there may be an inherent inverse problem (with multiple stimuli that can lead to the same visual field model).

The main conclusion, and title of the paper, that visual working memories are abstractions of percepts, is therefore not supported. Subjects could be using spatial attention, for example. Furthermore, even if it is true that gratings are abstracted into lines, this form of abstraction would not generalize to any non-spatial feature (e.g., color cannot become a line, contrast cannot become a line, etc.), which means it has limited explanatory power.

Additional context:

The working memory and perception tasks are rather different. In this case, the perception task does not require the subject to process the carrier orientation (which is largely occluded, and possibly not that obvious without paying attention to it), but attention is paid to contrast. In this scenario, stimulus energy may dominate the signal. In the WM task, subjects have to work out what orientation is shown to do the task. Given that the sensory stimulus in both tasks is brief (1.5s during memory encoding, and 2.5s total in the perceptual task), it would be interesting to look at decoding (and reconstructions) for the WM stimulus epoch. If abstraction (into a line) happens in working memory, then this perceptual part of the task should still be susceptible to aperture biases. It allows the authors to show that it is indeed during memory (and not merely the task or attentional state of the subject) that abstraction occurs.

What's also interesting is what happens in the passive perceptual condition, and the fact that spatial reconstructions for areas beyond V1 and V2 (i.e., V3, V3AB, and IPS0-1) align with (implied) grating endpoints, even when an angular modulator is used (Figure 3C). Are these areas also "abstracting" the stimulus (in a line-like format)?

Review after revision:

(1) It's nice of the authors to simulate how a dot stimulus affects the image computable model, but this does not entirely address my concern about attention to endpoints. The assumption that attention can be used in the same manner as a physical stimulus to calculate stimulus energy is questionable. (also, why would a dot at 15º lead to high stimulus energy tangential to that orientation?). This simulation also does not at all address my concern about model mimicry (many possible inputs can lead to a line-like output).

(2) It's also nice that the authors agree that much more work needs to be done, and these results may not generalize to all forms of memory. Given this agreement, and until that "more work" is done, I strongly believe we should refrain from making hyperbolic claims that might preemptively imply all visual working memories are abstractions of percepts. Time (and much more work) will likely show things to be much more subtle and complex.

The work presented in this paper is cool, but it uses a specific case: spatial stimuli (gratings) with the task to remember orientation. This limits possible conclusions for several reasons (1) These results are specific to EVC, as visual maps are a prerequisite meaning that these results will not hold up in other, non-retinotopic areas. (2) The fact that subjects are "focusing" along the main stimulus axis (attention or not) can simply be a strategy employed by the majority of (but not all) subjects - a strategy that may not be necessary to do the task, and therefore not a canonical method of Abstraction. It may be a "shared preferred strategy" or something. (3) If subjects had to (for example) remember contrast, and not orientation, results may have been entirely different (I would hypothesize there is no line-like abstraction in this case). Vice versa, if the perceptual task would have been on orientation (instead of contrast), the authors admit that "participants would reformat the grating into a line-like representation to make the judgments" (quote from author's response under "Additional context"). Thus, the results may be entirely about the task/ cognitive state, and not about how perceptual information is abstracted into memory.

Instead of unveiling *the* working memory Abstraction, this work (very nicely) shows a specific instance of possible abstraction. A more correct (but admittedly, less "sexy") conclusion may be "Visual working memories of orientation can be abstracted into a line in early visual cortex". As it stands, the authors still do not acknowledge any of the alternatives that myself (see above) and the other reviewers have put forth, nor do they acknowledge recent work by Chunharas et al. (2023, BioRxiv), that directly applies principles of efficient coding to address the exact same question of working memory abstraction. The link between a "line-like" representation and efficient coding implied by the authors (in their response) is merely tentative to me, but it would be great if the authors could explain this further.

These were, and remain, the major weaknesses in the original submission, that in my view have not been adequately addressed by the authors, as many overly broad conclusions about abstractions are currently still present in the manuscript (in for example the title).

Reviewer #2 (Public Review):

Summary:

In this work, Duan and Curtis addressed an important issue related to the nature of working memory representations. This work is motivated by findings illustrating that orientation decoding performance for perceptual representations can be biased by the stimulus aperture (modulator). Here, the authors examined whether the decoding performance for working memory representations is similarly influenced by these aperture biases. The results provide convincing evidence that working memory representations have a different representational structure, as the decoding performance was not influenced by the type of stimulus aperture.

Strengths:

The strength of this work lies in the direct comparison of decoding performance for perceptual representations with working memory representations. The authors take well-motivated approach and illustrate that perceptual and working memory representations do not share a similar representational structure. The authors test a clear question, with a rigorous approach and provide compelling evidence. First, the presented oriented stimuli are carefully manipulated to create orthogonal biases introduced by the stimulus aperture (radial or angular modulator), regardless of the stimulus carrier orientation. Second, the authors implement advanced methods to decode the orientation information, in visual and parietal cortical regions, when directly perceiving or holding an oriented stimulus in memory. The data illustrates that working memory decoding is not influenced by the type of aperture, while this is the case in perception. In sum, the main claims are important and shed light on the nature of working memory representations.

Weaknesses:

After the authors revised the original manuscript, a few of my initial concerns remain.

(1) Theoretical framing in the introduction. The introduction proposes that decoding of orientation information during perception does not reflect orientation selectivity, and it is instead driven by coarse scale biases. This is an overstatement. Recent work shows that orientation decoding is indeed influenced by coarse biases, but also reflects orientation selectivity (Roth, Kay & Merriam, 2022).

(2) The description of the image computable V1 model remains incomplete. The steerable pyramid is a model that simulates the responses of V1 neurons. To do so, it incorporates a set of linear receptive fields with varying orientation and spatial frequency tuning. However, the information that is lacking in the Methods is whether the implemented pyramid also included two quadrature phase pairs (odd and even phase Gabor filters making the output phase invariant). The sum of the squares of the responses to these offset phase filters computes the stimulus energy within each orientation and spatial frequency channel. Without this description, it is unclear what the model output represents.

Reviewer #1 (Public Review):

In this study, Gonzalez Alam et al. report a series of functional MRI results about the neural processing from the visual cortex to high-order regions in the default-mode network (DMN), compiling evidence from task-based functional MRI, resting-state connectivity, and diffusion-weighted imaging. Their participants were first trained to learn the association between objects and rooms/buildings in a virtual reality experiment; after the training was completed, in the task-based MRI experiment, participants viewed the objects from the earlier training session and judged if the objects were in the semantic category (semantic task) or if they were previously shown in the same spatial context (spatial context task). Based on the task data, the authors utilised resting-state data from their previous studies, visual localiser data also from previous studies, as well as structural connectivity data from the Human Connectome Project, to perform various seed-based connectivity analysis. They found that the semantic task causes more activation of various regions involved in object perception while the spatial context task causes more activation in various regions for place perception, respectively. They further showed that those object perception regions are more connected with the frontotemporal subnetwork of the DMN while those place perception regions are more connected with the medial-temporal subnetwork of the DMN. Based on these results, the authors argue that there are two main pathways connecting the visual system to high-level regions in the DMN, one linking object perception regions (e.g., LOC) leading to semantic regions (e.g., IFG, pMTG), the other linking place perception regions (e.g., parahippocampal gyri) to the entorhinal cortex and hippocampus.

Below I provide my takes on (1) the significance of the findings and the strength of evidence, (2) my guidance for readers regarding how to interpret the data, as well as several caveats that apply to their results, and finally (3) my suggestions for the authors.

(1) Significance of the results and strength of the evidence

I would like to praise the authors for, first of all, trying to associate visual processing with high-order regions in the DMN. While many vision scientists focus specifically on the macroscale organisation of the visual cortex, relatively few efforts are made to unravel how neural processing in the visual system goes on to engage representations in regions higher up in the hierarchy (a nice precedent study that looks at this issue is by Konkle and Caramazza, 2017). We all know that visual processing goes beyond the visual cortex, potentially further into the DMN, but there's no direct evidence. So, in this regard, the authors made a nice try to look at this issue.

Having said this, the authors' characterisation of the organisation of the visual cortex (object perception/semantics vs. place perception/spatial contexts) does not go beyond what has been known for many decades by vision neuroscience. Specifically, over the past two decades, numerous proposals have been put forward to explain the macroscale organisation of the visual system, particularly the ventrolateral occipitotemporal cortex. A lateral-medial division has been reliably found in numerous studies. For example, some researchers found that the visual cortex is organised along the separation of foveal vision (lateral) vs. peripheral vision (medial), while others found that it is structured according to faces (lateral) vs. places (medial). Such a bipartite division is also found in animate (lateral) vs. inanimate (medial), small objects (lateral) vs. big objects (medial), as well as various cytoarchitectonic and connectomic differences between the medial side and the lateral side of the visual cortex. Some more recent studies even demonstrate a tripartite division (small objects, animals, big objects; see Konkle and Caramazza, 2013). So, in terms of their characterisation of the visual cortex, I think Gonzalez Alam et al. do not add any novel evidence to what the community of neuroscience has already known.

However, the authors' effort to link visual processing with various regions of the DMN is certainly novel, and their attempt to gather converging evidence with different methodologies is commendable. The authors are able to show that, in an independent sample of resting-state data, object-related regions are more connected with semantic regions in the DMN while place-related regions are more connected with navigation-related regions in the DMN, respectively. Such patterns reveal a consistent spatial overlap with their Kanwisher-type face/house localiser data and also concur with the HCP white-matter tractography data. Overall, I think the two pathways explanation that the authors seek to argue is backed by converging evidence. The lack of travelling wave type of analysis to show the spatiotemporal dynamics across the cortex from the visual cortex to high-level regions is disappointing though because I was expecting this type of analysis would provide the most convincing evidence of a 'pathway' going from one point to another. Dynamic caudal modelling or Granger causality may also buttress the authors' claim of pathway because many readers, like me, would feel that there is not enough evidence to convincingly prove the existence of a 'pathway'.

(2) Guidance to the readers about interpretation of the data

The organisation of the visual cortex and the organisation of the DMN historically have been studied in parallel with little crosstalk between different communities of researchers. Thus, the work by Gonzalez Alam et al. has made a nice attempt to look at how visual processing goes beyond the realm of the visual cortex and continues into different subregions of the DMN.

While the authors of this study have utilised multiple methods to obtain converging evidence, there are several important caveats in the interpretation of their results:

(1) While the authors choose to use the term 'pathway' to call the inter-dependence between a set of visual regions and default-mode regions, their results have not convincingly demonstrated a definitive route of neural processing or travelling. Instead, the findings reveal a set of DMN regions are functionally more connected with object-related regions compared to place-related regions. The results are very much dependent on masking and thresholding, and the patterns can change drastically if different masks or thresholds are used.

(2) Ideally, if the authors could demonstrate the dynamics between the visual cortex and DMN in the primary task data, it would be very convincing evidence for characterising the journey from the visual cortex to DMN. Instead, the current connectivity results are derived from a separate set of resting state data. While the advantage of the authors' approach is that they are able to verify certain visual regions are more connected with certain DMN regions even under a task-free situation, it falls short of explaining how these regions dynamically interact to convert vision into semantic/spatial decision.

(3) There are several results that are difficult to interpret, such as their psychophysiological interactions (PPI), representational similarity analysis, and gradient analysis. For example, typically for PPI analysis, researchers interrogate the whole brain to look for PPI connectivity. Their use of targeted ROI is unusual, and their use of spatially extensive clusters that encompass fairly large cortical zones in both occipital and temporal lobes as the PPI seeds is also an unusual approach. As for the gradient analysis, the argument that the semantic task is higher on Gradient 1 than the spatial task based on the statistics of p-value = 0.027 is not a very convincing claim (unhelpfully, the figure on the top just shows quite a few blue 'spatial dots' on the hetero-modal end which can make readers wonder if the spatial context task is really closer to the unimodal end or it is simply the authors' statistical luck that they get a p-value under 0.05). While it is statistically significant, it is weak evidence (and it is not pertinent to the main points the authors try to make).

(3) My suggestion for the authors

There are several conceptual-level suggestions that I would like to offer to the authors:

(1) If the pathway explanation is the key argument that you wish to convey to the readers, an effective connectivity type of analysis, such as Granger causality or dynamic caudal modelling, would be helpful in revealing there is a starting point and end point in the pathway as well as revealing the directionality of neural processing. While both of these methods have their issues (e.g., Granger causality is not suitable for haemodynamic data, DCM's selection of seeds is susceptible to bias, etc), they can help you get started to test if the path during task performance does exist. Alternatively, travelling wave type of analysis (such as the results by Raut et al. 2021 published in Science Advances) can also be useful to support your claims of the pathway.

(2) I think the thresholding for resting state data needs to be explained - by the look of Figure 2E and 3E, it looks like whole-brain un-thresholded results, and then you went on to compute the conjunction between these un-thresholded maps with network templates of the visual system and DMN. This does not seem statistically acceptable, and I wonder if the conjunction that you found would disappear and reappear if you used different thresholds. Thus, for example, if the left IFG cluster (which you have shown to be connected with the visual object regions) would disappear when you apply a conventional threshold, this means that you need to seriously consider the robustness of the pathway that you seek to claim... it may be just a wild goose that you are chasing.

(3) There are several analyses that are hard to interpret and you can consider only reporting them in the supplementary materials, such as the PPI results and representational similarity analysis, as none of these are convincing. These analyses do not seem to add much value to make your argument more convincing and may elicit more methodological critiques, such as statistical issues, the set-up of your representational theory matrix, and so on.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Alam et al. sought to understand how memory interacts with incoming visual information to effectively guide human behavior by using a task that combines spatial contexts (houses) with objects of one or multiple semantic categories. Three additional datasets (all from separate participants) were also employed: one that functionally localized regions of interest (ROIs) based on subtractions of different visually presented category types (in this case, scenes, objects, and scrambled objects); another consisting of resting-state functional connectivity scans, and a section of the Human Connectome Project that employed DTI data for structural connectivity analysis. Across multiple analyses, the authors identify dissociations between regions preferentially activated during scene or object judgments, between the functional connectivity of regions demonstrating such preferences, and in the anatomical connectivity of these same regions. The authors conclude that the processing streams that take in visual information and support semantic or spatial processing are largely parallel and distinct.

Strengths:

(1) Recent work has reconceptualized the classic default mode network as two parallel and interdigitated systems (e.g., Braga & Buckner, 2017; DiNicola et al., 2021). The current manuscript is timely in that it attempts to describe how information is differentially processed by two streams that appear to begin in visual cortex and connect to different default subnetworks. Even at a group level where neuroanatomy is necessarily blurred across individuals, these results provide clear evidence of stimulus-based dissociation.

(2) The manuscript contains a large number of analyses across multiple independent datasets. It is therefore unlikely that a single experimenter choice in any given analysis would spuriously produce the overall pattern of results reported in this work.

Weaknesses:

(1) Throughout the manuscript, a strong distinction is drawn between semantic and spatial processing. However, given that only objects and spatial contexts were employed in the primary experiment, it is not clear that a broader conceptual distinction is warranted between "semantic" and "spatial" cognition. There are multiple grounds for concern regarding this basic premise of the manuscript.<br /> a. One can have conceptual knowledge of different types of scenes or spatial contexts. A city street will consistently differ from a beach in predictable ways, and a kitchen context provides different expectations than a living room. Such distinctions reflect semantic knowledge of scene-related concepts, but in the present work spatial and "all other" semantic information are considered and discussed as distinct and separate.<br /> b. As a related question, are scenes uniquely different from all other types of semantic/category information? If faces were used instead of scenes, could one expect to see different regions of the visual cortex coupling with task-defined face > object ROIs? The current data do not speak to this possibility, but as written the manuscript suggests that all (non-spatial) semantic knowledge should be processed by the FT-DMN.<br /> c. Recent precision fMRI studies characterizing networks corresponding to the FT-DMN and MTL-DMN have associated the former with social cognition and the latter with scene construction/spatial processing (DiNicola et al., 2020; 2021; 2023). This is only briefly mentioned by the authors in the current manuscript (p. 28), and when discussed, the authors draw a distinction between semantic and social or emotional "codes" when noting that future work is necessary to support the generality of the current claims. However, if generality is a concern, then emphasizing the distinction between object-centric and spatial cognition, rather than semantic and spatial cognition, would represent a more conservative and better-supported theoretical point in the current manuscript.

(2) Both the retrosplenial/parieto-occipital sulcus and parahippocampal regions are adjacent to the visual network as defined using the Yeo et al. atlas, and spatial smoothness of the data could be impacting connectivity metrics here in a way that qualitatively differs from the (non-adjacent) FT-DMN ROIs. Although this proximity is a basic property of network locations on the cortical surface, the authors have several tools at their disposal that could be employed to help rule out this possibility. They might, for instance, reduce the smoothing in their multi-echo data, as the current 5 mm kernel is larger than the kernel used in Experiment 2's single-echo resting-state data. Spatial smoothing is less necessary in multi-echo data, as thermal noise can be attenuated by averaging over time (echoes) instead of space (see Gonzalez-Castillo et al., 2016 for discussion). Some multi-echo users have eschewed explicit spatial smoothing entirely (e.g., Ramot et al., 2021), just as the authors of the current paper did for their RSA analysis. Less smoothing of E1 data, combined with a local erosion of either the MTL-DMN and VIS masks (or both) near their points of overlap in the RSFC data, would improve confidence that the current results are not driven, at least in part, by spatial mixing of otherwise distinct network signals.

(3) The authors identify a region of the right angular gyrus as demonstrating a "potential role in integrating the visual-to-DMN pathways." This would seem to imply that lesion damage to right AG should produce difficulties in integrating "semantic" and "spatial" knowledge. Are the authors aware of such a literature? If so, this would be an important point to make in the manuscript as it would tie in yet another independent source of information relevant to the framework being presented. The closest of which I am aware involves deficits in cued recall performance when associates consisted of auditory-visual pairings (Ben-Zvi et al., 2015), but that form of multi-modal pairing is distinct from the "spatial-semantic" integration forwarded in the current manuscript.

Reviewer #1 (Public Review):

The study by Chikermane and colleagues investigates the functional, structural, and dopaminergic network substrates of cortical beta oscillations (13-30 Hz). The major strength of the work lies in the methodology taken by the authors, namely a multimodal lesion network mapping. First, using invasive electrophysiological recordings from healthy cortical territories of epileptic patients they identify regions with the highest beta power. Next, they leverage open-access MRI data and PET atlases and use the identified high-beta regions as seeds to find (1) the whole-brain functional and structural maps of regions that form the putative underlying network of high-beta regions and (2) the spatial distribution of dopaminergic receptors that show correlation with nodal connectivity of the identified networks. These steps are achieved by generating aggregate functional, structural, and dopaminergic network maps using lead-DBS toolbox, and by contrasting the results with those obtained from high-alpha regions.

The main findings are:<br /> (1) Beta power is strongest across frontal, cingulate, and insular regions in invasive electrophysiological data, and these regions map onto a shared functional and structural network.<br /> (2) The shared functional and structural networks show significant positive correlations with dopamine receptors across the cortex and basal ganglia (which is not the case for alpha, where correlations are found with GABA).

Nevertheless, a few clarifications regarding the choice of high-power electrodes and distributions of functional connectivity maps (i.e., strength and sign across cortex and sub-cortex) can help with understanding the results.

Reviewer #2 (Public Review):

Summary:

This is a very interesting paper that leveraged several publicly available datasets: invasive cortical recording in epilepsy patients, functional and structural connectomic data, and PET data related to dopaminergic and gaba-ergic synapses. These were combined to create a unified hypothesis of beta band oscillatory activity in the human brain. They show that beta frequency activity is ubiquitous, not just in sensorimotor areas, and cortical regions where beta predominated had high connectivity to regions high in dopamine re-update.

Strengths:

The authors leverage and integrate three publicly available human brain datasets in a creative way. While these public datasets are powerful tools for human neuroscience, it is innovative to combine these three types of data into a common brain space to generate novel findings and hypotheses. Findings are nicely controlled by separately examining cortical regions where alpha predominates (which have a different connectivity pattern). GABA uptake from PET studies is used as a control for the specificity of the relationship between beta activity and dopamine uptake. There is much interest in synchronized oscillatory activity as a mechanism of brain function and dysfunction, but the field is short on unifying hypotheses of why particular rhythms predominate in particular regions. This paper contributes nicely to that gap. It is ambitious in generating hypotheses, particularly that modulation of beta activity may be used as a "proxy" for modulating phasic dopamine release.

Weaknesses:

As the authors point out, the use of normative data is excellent for exploring hypotheses but does not address or explore individual variations which could lead to other insights. It is also biased to resting state activity; maps of task-related activity (if they were available) might show different findings.

The figures, results, introduction, and methods are admirably clear and succinct but the discussion could be both shorter and more convincing.

Reviewer #3 (Public Review):

Summary:

In this paper, Chikermane et al. leverages a large open dataset of intracranial recordings (sEEG or ECoG) to analyze resting state (eyes closed) oscillatory activity from a variety of human brain areas. The authors identify a dominant proportion of channels in which beta band activity (12-30Hz) is most prominent and subsequently seek to relate this to anatomical connectivity data by using the sEEG/ECoG electrodes as seeds in a large set of MRI data from the human connectome project. This reveals separate regions and white matter tracts for alpha (primarily occipital) and beta (prefrontal cortex and basal ganglia) oscillations. Finally, using a third available dataset of PET imaging, the authors relate the parcellated signals to dopamine signaling as estimated by spatial uptake patterns of dopamine, and reveal a significant correlation between the functional connectivity maps and the dopamine reuptake maps, suggesting a functional relationship between the two.

Strengths:

Overall, I found the paper well justified, focused on an important topic, and interesting. The authors' use of 3 different open datasets was creative and informative, and it significantly adds to our understanding of different oscillatory networks in the human brain, and their more elusive relation with neuromodulator signaling networks by adding to our knowledge of the association between beta oscillations and dopamine signaling. Even my main comments about the lack of a theta network analysis and discussion points are relatively minor, and I believe this paper is valuable and informative.

Weaknesses:

The analyses were adequate, and the authors cleverly leveraged these different datasets to build an interesting story. The main aspect I found missing (in addition to some discussion items, see below) was an examination of the theta network. Theta oscillations have been involved in a number of cognitive processes including spatial navigation and memory, and have been proposed to have different potential originating brain regions, and it would be informative to see how their anatomical networks (e.g. as in Figure 2) look like under the author's analyses.

The authors devote a significant portion of the discussion to relating their findings to a popular hypothesis for the function of beta oscillations, the maintenance of the "status quo", mostly in the context of motor control. As the authors acknowledge, given the static nature of the data and lack of behavior, this interpretation remains largely speculative and I found it a bit too far-reaching given the data shown in the paper. In contrast, I missed a more detailed discussion on the growing literature indicating a role for beta in mood (e.g. in Kirkby et al. 2018), especially given the apparent lack of hippocampal and amygdala involvement in the paper, which was surprising.

Major comment:

• Although the proportion of electrodes with theta-dominant oscillations was lower (~15%) than alpha (~22%) or beta (~57%), it would be very valuable to also see the same analyses the authors carried out in these frequency bands extended to theta oscillations.

Reviewer #1 (Public Review):

Vision is a highly active process. Humans move their eyes 3-4 times per second to sample information with high visual acuity from our environment, and where eye movements are directed is critical to our understanding of active vision. Here, the authors propose that the cost of making a saccade contributes critically to saccade selection (i.e., whether and where to move the eyes). The authors build on their own recent work that the effort (as measured by pupil size) that comes with planning and generating an eye movement varies with saccade direction. To do this, the authors first measured pupil size for different saccade directions for each participant. They then correlated the variations in pupil size obtained in the mapping task with the saccade decision in a free-choice task. The authors observed a striking correlation: pupil size in the mapping task predicted the decision of where to move the eyes in the free choice task. In this study, the authors provide a number of additional insightful analyses (e.g., based on saccade curvature, and saccade latency) and experiments that further support their claim that the decision to move the eyes is influenced by the effort to move the eyes in a particular direction. One experiment showed that the same influence of assumed saccade costs on saccade selection is observed during visual search in natural scenes. Moreover, increasing the cognitive load by adding an auditory counting task reduced the number of saccades, and in particular reduced the costly saccades. In sum, these experiments form a nice package that convincingly establishes the association between pupil size and saccade selection.

In my opinion, the causal structure underlying the observed results is not so clear. While the relationship between pupil size and saccade selection is compelling, it is not clear that saccade-related effort (i.e., the cost of a saccade) really drives saccade selection. Given the correlational nature of this relationship, there are other alternatives that could explain the finding. For example, saccade latency and the variance in landing positions also vary across saccade directions. This can be interpreted for instance that there are variations in oculomotor noise across saccade directions, and maybe the oculomotor system seeks to minimize that noise in a free-choice task. In fact, given such a correlational result, many other alternative mechanisms are possible. While I think the authors' approach of systematically exploring what we can learn about saccade selection using pupil size is interesting, it would be important to know what exactly pupil size can add that was not previously known by simply analyzing saccade latency. For example, saccade latency anisotropies across saccade directions are well known, and the authors also show here that saccade costs are related to saccade latency. An important question would be to compare how pupil size and saccade latency uniquely contribute to saccade selection. That is, the authors could apply the exact same logic to their analysis by first determining how saccade latencies (or variations in saccade landing positions; see Greenwood et al., 2017 PNAS) vary across saccade directions and how this saccade latency map explains saccade selection in subsequent tasks. Is it more advantageous to use one or the other saccade metric, and how well does a saccade latency map correlate with a pupil size map?

In addition to eye-movement-related anisotropies across the visual field, there are of course many studies reporting visual field anisotropies (see Himmelberg, Winawer & Carrasco, 2023, Trends in Neuroscience for a review). It would be interesting to understand how the authors think about visual field anisotropies in the context of their own study. Do they think that their results are (in)dependent on such visual field variations (see Greenwood et al., 2017, PNAS; Ohl, Kroell, & Rolfs, 2024, JEP:Gen for a similar discussion)?

Finally, the authors conclude that their results "suggests that the eye-movement system and other cognitive operations consume similar resources that are flexibly allocated among each other as cognitive demand changes. The authors should speculate what these similar resources could mean? What are the specific operations of the auditory task that overlap in terms of resources with the eye movement system?

Reviewer #2 (Public Review):

The authors attempt to establish presaccadic pupil size as an index of 'saccade effort' and propose this index as one new predictor of saccade target selection. They only partially achieved their aim: When choosing between two saccade directions, the less costly direction, according to preceding pupil size, is preferred. However, the claim that with increased cognitive demand participants would especially cut costly directions is not supported by the data. I would have expected to see a negative correlation between saccade effort and saccade direction 'change' under increased load. Yet participants mostly cut upwards saccades, but not other directions that, according to pupil size, are equally or even more costly (e.g. oblique saccades).

Strengths:

The paper is well-written, easy to understand, and nicely illustrated.

The sample size seems appropriate, and the data were collected and analyzed using solid and validated methodology.

Overall, I find the topic of investigating factors that drive saccade choices highly interesting and relevant.

Weaknesses:

The authors obtain pupil size and saccade preference measures in two separate tasks. Relating these two measures is problematic because the computations that underly saccade preparation differ. In Experiment 1, the saccade is cued centrally, and has to be delayed until a "go-signal" is presented; In Experiment 2, an immediate saccade is executed to an exogenously cued peripheral target. The 'costs' in Experiment 1 (computing the saccade target location from a central cue; withholding the saccade) do not relate to Experiment 2. It is unfortunate, that measuring presaccadic pupil size directly in the comparatively more 'natural' Experiment 2 (where saccades did not have to be artificially withheld) does not seem to be possible. This questions the practical application of pupil size as an index of saccade effort

The authors claim that the observed direction-specific 'saccade costs' obtained in Experiment 1 "were not mediated by differences in saccade properties, such as duration, amplitude, peak velocity, and landing precision (Figure 1e,f)". Saccade latency, however, was not taken into account here but is discussed for Experiment 2.

The apparent similarity of saccade latencies and pupil size, however, is striking. Previous work shows shorter latencies for cardinal than oblique saccades, and shorter latencies for horizontal and upward saccades than downward saccades - directly reflecting the pupil sizes obtained in Experiment 1 as well as in the authors' previous study (Koevoet et al., 2023, PsychScience).

-

The authors state that "from a costs-perspective, it should be efficient to not only adjust the number of saccades (non-specific), but also by cutting especially expensive directions the most (specific)". However, saccade targets should be selected based on the maximum expected information gain. If cognitive load increases (due to an additional task) an effective strategy seems to be to perform less - but still meaningful - saccades. How would it help natural orienting to selectively cut saccades in certain (effortful) directions? Choosing saccade targets based on comfort, over information gain, would result in overall more saccades to be made - which is non-optimal, also from a cost perspective.

Overall, I am not sure what practical relevance the relation between pupil size (measured in a separate experiment) and saccade decisions has for eye movement research/vision science. Pupil size does not seem to be a straightforward measure of saccade effort. Saccade latency, instead, can be easily extracted in any eye movement experiment (no need to conduct a separate, delayed saccade task to measure pupil dilation), and seems to be an equally good index.

Reviewer #3 (Public Review):

This manuscript extends previous research by this group by relating variation in pupil size to the endpoints of saccades produced by human participants under various conditions including trial-based choices between pairs of spots and search for small items in natural scenes. Based on the premise that pupil size is a reliable proxy of "effort", the authors conclude that less costly saccade targets are preferred. Finding that this preference was influenced by the performance of a non-visual, attention-demanding task, the authors conclude that a common source of effort animates gaze behavior and other cognitive tasks.

Strengths:

Strengths of the manuscript include the novelty of the approach, the clarity of the findings, and the community interest in the problem.

Weaknesses:

Enthusiasm for this manuscript is reduced by the following weaknesses:

(1) A relationship between pupil size and saccade production seems clear based on the authors' previous and current work. What is at issue is the interpretation. The authors test one, preferred hypothesis, and the narrative of the manuscript treats the hypothesis that pupil size is a proxy of effort as beyond dispute or question. The stated elements of their argument seem to go like this:<br /> PROPOSITION 1: Pupil size varies systematically across task conditions, being larger when tasks are more demanding.<br /> PROPOSITION 2: Pupil size is related to the locus coeruleus.<br /> PROPOSITION 3: The locus coeruleus NE system modulates neural activity and interactions.<br /> CONCLUSION: Therefore, pupil size indexes the resource demand or "effort" associated with task conditions.<br /> How the conclusion follows from the propositions is not self-evident. Proposition 3, in particular, fails to establish the link that is supposed to lead to the conclusion.

(2) The authors test one, preferred hypothesis and do not consider plausible alternatives. Is "cost" the only conceivable hypothesis? The hypothesis is framed in very narrow terms. For example, the cholinergic and dopamine systems that have been featured in other researchers' consideration of pupil size modulation are missing here. Thus, because the authors do not rule out plausible alternative hypotheses, the logical structure of this manuscript can be criticized as committing the fallacy of affirming the consequent.

(3) The authors cite particular publications in support of the claim that saccade selection is influenced by an assessment of effort. Given the extensive work by others on this general topic, the skeptic could regard the theoretical perspective of this manuscript as too impoverished. Their work may be enhanced by consideration of other work on this general topic, e.g, (i) Shenhav A, Botvinick MM, Cohen JD. (2013) The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron. 2013 Jul 24;79(2):217-40. (ii) Müller T, Husain M, Apps MAJ. (2022) Preferences for seeking effort or reward information bias the willingness to work. Sci Rep. 2022 Nov 14;12(1):19486. (iii) Bustamante LA, Oshinowo T, Lee JR, Tong E, Burton AR, Shenhav A, Cohen JD, Daw ND. (2023) Effort Foraging Task reveals a positive correlation between individual differences in the cost of cognitive and physical effort in humans. Proc Natl Acad Sci U S A. 2023 Dec 12;120(50):e2221510120.

(4) What is the source of cost in saccade production? What is the currency of that cost? The authors state (page 13), "... oblique saccades require more complex oculomotor programs than horizontal eye movements because more neuronal populations in the superior colliculus (SC) and frontal eye fields (FEF) [76-79], and more muscles are necessary to plan and execute the saccade [76, 80, 81]." This statement raises questions and concerns. First, the basis of the claim that more neurons in FEF and SC are needed for oblique versus cardinal saccades is not established in any of the publications cited. Second, the authors may be referring to the fact that oblique saccades require coordination between pontine and midbrain circuits. This must be clarified. Second, the cost is unlikely to originate in extraocular muscle fatigue because the muscle fibers are so different from skeletal muscles, being fundamentally less fatigable. Third, if net muscle contraction is the cost, then why are upward saccades, which require the eyelid, not more expensive than downward? Thus, just how some saccades are more effortful than others is not clear.

(5) The authors do not consider observations about variation in pupil size that seem to be incompatible with the preferred hypothesis. For example, at least two studies have described systematically larger pupil dilation associated with faster relative to accurate performance in manual and saccade tasks (e.g., Naber M, Murphy P. Pupillometric investigation into the speed-accuracy trade-off in a visuo-motor aiming task. Psychophysiology. 2020 Mar;57(3):e13499; Reppert TR, Heitz RP, Schall JD. Neural mechanisms for executive control of speed-accuracy trade-off. Cell Rep. 2023 Nov 28;42(11):113422). Is the fast relative to the accurate option necessarily more costly?

(6) The authors draw conclusions based on trends across participants, but they should be more transparent about variation that contradicts these trends. In Figures 3 and 4 we see many participants producing behavior unlike most others. Who are they? Why do they look so different? Is it just noise, or do different participants adopt different policies?

Reviewer #1 (Public Review):

In the manuscript "A microglia clonal inflammatory disorder in Alzheimer's Disease", Vicario et al. provide a compelling study elucidating a potential contribution of somatic mutations within the microglia population of the CNS that accelerates microglia activation and disease-associated gene signatures in Alzheimer's disease. Here they especially identified an "enrichment" of pathological SNVs in microglia, but not the peripheral blood, that are associated with clonal proliferative disorders and neurological diseases in a subset of patients with AD. Convincingly, they identified P-SNVs in microglia of AD patients located within the ring domain of CBL, a negative regulator of MAPK signaling. They further provide mechanistic insights into how these variants result in MAPK over-activation and subsequently in a pro-inflammatory phenotype in human microglia-like cells in vitro.

Overall, this study provides clear and detailed evidence from an AD patient cohort pointing to a potential contribution of microglia-specific somatic mutations to disease onset and/or progression in a subset of patients with Alzheimer's disease.

Strengths:<br /> As outlined above, the study identified P-SNVs in microglia of AD patients associated with clonal proliferative disorders, but also gave an in-depth analysis of re-occurring P-SNVs located within the ring domain of CBL, a negative regulator of MAPK signaling. They further provide mechanistic insights into how these variants result in MAPK over-activation and subsequently in a pro-inflammatory phenotype in HEK cells, BV2 cells, MAC cells, and human microglia-like cells in vitro.

Great care was taken here to validate their hypotheses at each step, as well as to identify the limitations of the possible conclusions. For example, they highlight that the pathway proposed to be affected may be an explanation for a subset of AD patients, and emphasize that it is yet unclear whether this accumulation of pathological SNVs is a cause or consequence of disease progression

The study clearly supports an enrichment of P-SNVs in several genes associated with clonal proliferative disorders in microglia and nicely separates this from SNVs associated with clonal hematopoiesis in the peripheral blood found in AD patients and controls.

The authors further acknowledged that several age-matched control patients were diagnosed with cancer or tumor-associated diseases and carefully dissected the occurring SNVs in these patients are not associated with the P-SNVs identified in the microglial compartment of the AD cohort.

Weaknesses:

Even though the study is overall very convincing, several points could help to connect the seen somatic variants in microglia more with a potential role in disease progression. The connection of P-SNVs in the genes chosen from neurological disorders was not further highlighted by the authors.

The authors show in snRNA-seq data that a disease-associated microglia state seems to be enriched in patients with somatic variants in the CBL ring domain, however, this analysis could be deepened. For example, how this knowledge may translate to patient benefits when the relevant cell populations appear concentrated in a single patient sample (Figure 5; AD52) is unclear; increasing the analyzed patient pool for Figure 5 and showcasing the presence of this microglia state of interest in a few more patients with driving mutations for CBL or other MAPK pathway associated mutations would lend their hypotheses further credibility.

A potential connection between P-SNVs in microglia and disease pathology and symptoms was not further explored by the authors.

A recent preprint (Huang et al., 2024) connected the occurrence of somatic variants in genes associated with clonal hematopoiesis in microglia in a large cohort of AD patients, this study is not further discussed or compared to the data in this manuscript.

Reviewer #2 (Public Review):

Summary:

In this study, Vicaro et al. aimed to quantify and characterize mosaic mutations in human sporadic Alzheimer's disease (AD) brain samples. They focused on three broad classes of brain cells, neurons that express the marker NeuN, microglia that express the marker PU.1, and double-negative cells that presumably comprise all other brain cell types, including astrocytes, oligodendrocytes, oligodendrocyte progenitor cells, and endothelial cells. The authors find an enrichment of potentially pathogenic somatic mutations in AD microglia compared to controls, with MAPK pathway genes being particularly enriched for somatic mutations in those cells. The authors report a striking enrichment for mutations in the gene CBL and use in vitro functional assays to show that these mutations indeed induce MAPK pathway activation.

The current state of the AD and somatic mutation fields puts this work into context. First, AD is a devastating disease whose prevalence is only increasing as the population of the U.S. is aging, necessitating the investigation of novel features of AD to identify new therapeutic opportunities. Second, microglia have recently come into focus as important players in AD pathogenesis. Many AD risk genes are selectively expressed in microglia, and microglia from AD brain samples show a distinct transcriptional profile indicating an inflammatory phenotype. The authors' previous work shows that a genetic mouse model of mosaic BRAF activation in macrophages (including microglia) displays a neurodegenerative phenotype similar to AD (Mass et al., 2017, doi:10.1038/nature23672). Third, new technological developments have allowed for identifying mosaic mutations present in only a small fraction of or even single cells. Together, these data form a rationale for studying mosaic mutations in microglia in AD. In light of the authors' findings regarding MAPK pathway gene somatic mutations, it is also important to note that MAPK has previously been implicated in AD neuroinflammation in the literature.

Strengths:

The study demonstrated several strengths.

Firstly, the authors used two methods to identify mosaic mutations:<br /> (1) deep (~1,100x) DNA sequencing of a targeted panel of 716 genes they hypothesized might, if mutated somatically, play a role in AD, and<br /> (2) deep (400x) whole-exome sequencing (WES) to identify clonal mosaics outside of those 716 genes.

A second strength is the agreement between these experiments, where WES found many variants identified in the panel experiment, and both experiments revealed somatic mutations in MAPK pathway genes.

Third, the authors demonstrated in several in vitro systems that many mutations they identified in MAPK genes activate MAPK signaling. Finally, the authors showed that in some human brain samples, single-cell gene expression analysis revealed that cells bearing a mosaic MAPK pathway mutation displayed dysregulated inflammatory signaling and dysregulation in other pathways. This single-cell analysis was in agreement with their in vitro analyses.

Weaknesses:

The study also showed some weaknesses. The sample size (45 AD donors and 44 controls) is small, reflected in the relatively modest effect sizes and p-values observed. This weakness is partially ameliorated by the authors' extensive molecular and functional validation of mutation candidates. Another weakness is the lack of discussion of whether the genes found to be mutated somatically in AD show any AD-risk alleles in the population. If they did, it would further support the authors' conclusions that they are playing a role in AD. Finally, as the authors point out, this study cannot conclude whether microglial mosaic mutations cause AD or are an effect of AD. Future studies may shed more light on this important question.

Conclusions and Impact:

Considering the study's aims, strengths, and weaknesses, I conclude that the authors achieved their goal of characterizing the role of mosaic mutations in human AD. Their data strongly suggest that mosaic MAPK mutations in microglia are associated with AD. The impacts of this study remain to be seen, but they could include attempts to target CBL or other mutated genes in the treatment of AD. This work also suggests a similar approach to identifying potentially causative somatic mutations in other neurodegenerative diseases.

Reviewer #1 (Public Review):

Summary:

The study of human intelligence has been the focus of cognitive neuroscience research, and finding some objective behavioral or neural indicators of intelligence has been an ongoing problem for scientists for many years. Melnick et al, 2013 found for the first time that the phenomenon of spatial suppression in motion perception predicts an individual's IQ score. This is because IQ is likely associated with the ability to suppress irrelevant information. In this study, a high-resolution MRS approach was used to test this theory. In this paper, the phenomenon of spatial suppression in motion perception was found to be correlated with the visuo-spatial subtest of gF, while both variables were also correlated with the GABA concentration of MT+ in the human brain. In addition, there was no significant relationship with the excitatory transmitter Glu. At the same time, SI was also associated with MT+ and several frontal cortex FCs.

Strengths:

(1) 7T high-resolution MRS is used.

(2) This study combines the behavioral tests, MRS, and fMRI.

Weaknesses:

(1) In the intro, it seems to me that the multiple-demand (MD) regions are the key in this study. However, I didn't see any results associated with the MD regions. Did I miss something??

(2) How was the sample size determined? Is it sufficient??

(3) In Schallmo elife 2018, there was no correlation between GABA concentration and SI. How can we justify the different results different here?

(4) Basically this study contains the data of SI, BDT, GABA in MT+ and V1, Glu in MT+ and V1-all 6 measurements. There should be 6x5/2 = 15 pairwise correlations. However, not all of these results are included in Figure 1 and supplementary 1-3. I understand that it is not necessary to include all figures. But I suggest reporting all values in one Table.

(5) In Melnick (2013), the IQ scores were measured by the full set of WAIS-III, including all subtests. However, this study only used the visual spatial domain of gF. I wonder why only the visuo-spatial subtest was used not the full WAIS-III?

(6) In the functional connectivity part, there is no explanation as to why only the left MT+ was set to the seed region. What is the problem with the right MT+?

(7) In Melnick (2013), the authors also reported the correlation between IQ and absolute duration thresholds of small and large stimuli. Please include these analyses as well.

Reviewer #2 (Public Review):

Summary:

Recent studies have identified specific regions within the occipito-temporal cortex as part of a broader fronto-parietal, domain-general, or "multiple-demand" (MD) network that mediates fluid intelligence (gF). According to the abstract, the authors aim to explore the mechanistic roles of these occipito-temporal regions by examining GABA/glutamate concentrations. However, the introduction presents a different rationale: investigating whether area MT+ specifically, could be a core component of the MD network.

Strengths:

The authors provide evidence that GABA concentrations in MT+ and its functional connectivity with frontal areas significantly correlate with visuo-spatial intelligence performance. Additionally, serial mediation analysis suggests that inhibitory mechanisms in MT+ contribute to individual differences in a specific subtest of the Wechsler Adult Intelligence Scale, which assesses visuo-spatial aspects of gF.

Weaknesses:

While the findings are compelling and the analyses robust, the study's rationale and interpretations need strengthening. For instance, Assem et al. (2020) have previously defined the core and extended MD networks, identifying the occipito-temporal regions as TE1m and TE1p, which are located more rostrally than MT+. Area MT+ might overlap with brain regions identified previously in Fedorenko et al., 2013, however the authors attribute these activations to attentional enhancement of visual representations in the more difficult conditions of their tasks. For the aforementioned reasons, It is unclear why the authors chose MT+ as their focus. A stronger rationale for this selection is necessary and how it fits with the core/extended MD networks.

Moreover, although the study links MT+ inhibitory mechanisms to a visuo-spatial component of gF, this evidence alone may not suffice to position MT+ as a new core of the MD network. The MD network's definition typically encompasses a range of cognitive domains, including working memory, mathematics, language, and relational reasoning. Therefore, the claim that MT+ represents a new core of MD needs to be supported by more comprehensive evidence.

Reviewer #3 (Public Review):

Summary:

This manuscript aims to understand the role of GABA-ergic inhibition in the human MT+ region in predicting visuo-spatial intelligence through a combination of behavioral measures, fMRI (for functional connectivity measurement), and MRS (for GABA/glutamate concentration measurement). While this is a commendable goal, it becomes apparent that the authors lack fundamental understanding of vision, intelligence, or the relevant literature. As a result, the execution of the research is less coherent, dampening the enthusiasm of the review.

Strengths:

(1) Comprehensive Approach: The study adopts a multi-level approach, i.e., neurochemical analysis of GABA levels, functional connectivity, and behavioral measures to provide a holistic understanding of the relationship between GABA-ergic inhibition and visuo-spatial intelligence.

(2) Sophisticated Techniques: The use of ultra-high field magnetic resonance spectroscopy (MRS) technology for measuring GABA and glutamate concentrations in the MT+ region is a recent development.

Weaknesses:

Study Design and Hypothesis<br /> (1) The central hypothesis of the manuscript posits that "3D visuo-spatial intelligence (the performance of BDT) might be predicted by the inhibitory and/or excitation mechanisms in MT+ and the integrative functions connecting MT+ with the frontal cortex." However, several issues arise:<br /> 1.1 The Suppression Index depicted in Figure 1a, labeled as the "behavior circle," appears irrelevant to the central hypothesis.<br /> 1.2 The construct of 3D visuo-spatial intelligence, operationalized as the performance in the Block Design task, is inconsistently treated as another behavioral task throughout the manuscript, leading to confusion.<br /> 1.3 The schematics in Figure 1a and Figure 6 appear too high-level to be falsifiable. It is suggested that the authors formulate specific and testable hypotheses and preregister them before data collection.

(2) Central to the hypothesis and design of the manuscript is a misinterpretation of a prior study by Melnick et al. (2013). While the original study identified a strong correlation between WAIS (IQ) and the Suppression Index (SI), the current manuscript erroneously asserts a specific relationship between the block design test (from WAIS) and SI. It should be noted that in the original paper, WAIS comprises Similarities, Vocabulary, Block design, and Matrix reasoning tests in Study 1, while the complete WAIS is used in Study 2. Did the authors conduct other WAIS subtests other than the block design task?

(3) Additionally, there are numerous misleading references and unsubstantiated claims throughout the manuscript. As an example of misleading reference, "the human MT ... a key region in the multiple representations of sensory flows (including optic, tactile, and auditory flows) (Bedny et al., 2010; Ricciardi et al., 2007); this ideally suits it to be a new MD core." The two references in this sentence are claims about plasticity in the congenitally blind with sensory deprivation from birth, which is not really relevant to the proposal that hMT+ is a new MD core in healthy volunteers.<br /> Another example of unsubstantiated claim: the rationale for selecting V1 as the control region is based on the assertion that "it mediates the 2D rather than 3D visual domain (Born & Bradley, 2005)". That's not the point made in the Born & Bradley (2005) paper on MT. It's crucial to note that V1 is where the initial binocular convergence occurs in cortex, i.e., inputs from both the right and left eyes to generate a perception of depth.

Results & Discussion<br /> (1) The missing correlation between SI and BDT is crucial to the rest of the analysis. The authors should discuss whether they replicated the pattern of results from Melnick et al. (2013) despite using only one WAIS subtest.

(2) ROIs: can the authors clarify if the results are based on bilateral MT+/V1 or just those in the left hemisphere? Can the authors plot the MRS scan area in V1? I would be surprised if it's precise to V1 and doesn't spread to V2/3 (which is fine to report as early visual cortex).

(3) Did the authors examine V1 FC with either the frontal regions and/or whole brain, as a control analysis? If not, can the author justify why V1 serves as the control region only in the MRS but not in FC (Figure 4) or the mediation analysis (Figure 5)? That seems a little odd given that control analyses are needed to establish the specificity of the claim to MT+.

(4) It is not clear how to interpret the similarity or difference between panels a and b in Figure 4.

(5) SI is not relevant to the authors' priori hypothesis, but is included in several mediation analyses. Can the authors do model comparisons between the ones in Figure 5c, d, and Figure S6? In other words, is SI necessary in the mediation model? There seem discrepancies between the necessity of SI in Figures 5c/S6 vs. Figure 5d.

(6) The sudden appearance of "efficient information" in Figure 6, referring to the neural efficiency hypothesis, raises concerns. Efficient visual information processing occurs throughout the visual cortex, starting from V1. Thus, it appears somewhat selective to apply the neural efficiency hypothesis to MT+ in this context.

Transparency Issues:<br /> (1) Don't think it's acceptable to make the claim that "All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary information". It is the results or visualizations of data analysis, rather than the raw data themselves, that are presented in the paper/supp info.

(2) No GitHub link has been provided in the manuscript to access the source data, which limits the reproducibility and transparency of the study.

Minor:<br /> "Locates" should be replaced with "located" throughout the paper. For example: "To investigate this issue, this study selects the human MT complex (hMT+), a region located at the occipito-temporal border, which represents multiple sensory flows, as the target brain area."

Use "hMT+" instead of "MT+" to be consistent with the term in the literature.

"Green circle" in Figure 1 should be corrected to match its actual color.

The abbreviation for the Wechsler Adult Intelligence Scale should be "WAIS," not "WASI."

Reviewer #1 (Public Review):

Summary:

This is a fine paper that serves the purpose to show that the use of light sheet imaging may be used to provide whole brain imaging of axonal projections. The data provided suggest that at this point the technique provides lower resolution than with other techniques. Nonetheless, the technique does provide useful, if not novel, information about particular brain systems.

Strengths:

The manuscript is well written. In the introduction a clear description of the functional organization of the barrel cortex is provided provides the context for applying the use of specific Cre-driver lines to map the projections of the main cortical projection types using whole brain neuroanatomical tracing techniques. The results provided are also well written, with sufficient detail describing the specifics of how techniques were used to obtain relevant data. Appropriate controls were done, including the identification of whisker fields for viral injections and determination of the laminar pattern of Cre expression. The mapping of the data provides a good way to visualize low resolution patterns of projections.

Weaknesses:

(1) The results provided are, as stated in the discussion, "largely in agreement with previously reported studies of the major projection targets". However it must be stated that the study does not "extend current knowledge through the high sensitivity for detecting sparse axons, the high specificity of labeling of genetically defined classes of neurons and the brain wide analysis for assigning axons to detailed brain regions" which have all been published in numerous other studies. ( the allen connectivity project and related papers, along with others). If anything the labeling of axons obtained with light sheet imaging in this study does not provide as detailed mapping obtained with other techniques. Some detail is provided of how the raw images are processed to resolve labeled axons, but the images shown in the figures do not demonstrate how well individual axons may be resolved, of particular interest would be to see labeling in terminal areas such as other cortical areas, striatum and thalamus. As presented the light sheet imaging appears to be rather low resolution compared to the many studies that have used viral tracing to look at cortical projections from genetically identified cortical neurons.<br /> (2) Amongst the limitations of this study is the inability to resolve axons of passage and terminal fields. This has been done in other studies with viral constructs labeling synaptophysin. This should be mentioned.<br /> (3) There is no quantitative analysis of differences between the genetically defined neurons projecting to the striatum, what is the relative area innervated by, density of terminals, other measures.<br /> (4) Figure 5 is an example of the type of large sets of data that can be generated with whole brain mapping and registration to the Allen CCF that provides information of questionable value. Ordering the 50 plus structures by the density of labeling does not provide much in terms of relative input to different types of areas. There are multiple subregions for different functional types ( ie, different visual areas and different motor subregions are scattered not grouped together. Makes it difficult to understand any organizing principles.<br /> (5) The GENSAT Cre driver lines used must have the specific line name used, not just the gene name as the GENSAT BAC-Cre lines had multiple lines for each gene and often with very different expression patterns. Rbp4_KL100, Tlx3_PL56, Sim1_KJ18, Ntsr1_ GN220.

Reviewer #2 (Public Review):

Summary:

This study takes advantage of multiple methodological advances to perform layer-specific staining of cortical neurons and tracking of their axons to identify the pattern of their projections. This publication offers a mesoscale view of the projection patterns of neurons in the whisker primary and secondary somatosensory cortex. The authors report that, consistent with the literature, the pattern of projection is highly different across cortical layers and subtype, with targets being located around the whole brain. This was tested across 6 different mouse types that expressed a marker in layer 2/3, layer 4, layer 5 (3 sub-types) and layer 6.<br /> Looking more closely at the projections from primary somatosensory cortex into the primary motor cortex, they found that there was a significant spatial clustering of projections from topographically separated neurons across the primary somatosensory cortex. This was true for neurons with cell bodies located across all tested layers/types.

Strengths:

This study successfully looks at the relevant scale to study projection patterns, which is the whole brain. This is achieved thanks to an ambitious combination of mouse lines, immuno-histochemistry, imaging and image processing, which results in a standardized histological pipeline that processes the whole-brain projection patterns of layer-selected neurons of the primary and secondary somatosensory cortex.<br /> This standardization means that comparisons between cell-types projection patterns are possible and that both the large-scale structure of the pattern and the minute details of the intra-areas pattern are available.<br /> This reference dataset and the corresponding analysis code are made available to the research community.

Weaknesses:

One major question raised by this dataset is the risk of missing axons during the post-processing step. Indeed, it appears that the control and training efforts have focused on the risk of false positives (see Figure 1 supplementary panels). And indeed, the risk of overlooking existing axons in the raw fluorescence data id discussed in the article.

Based on the data reported in the article, this is more than a risk. In particular, Figure 2 shows an example Rbp4-L5 mouse where axonal spread seems massive in Hippocampus, while there is no mention of this area in the processed projection data for this mouse line.

Similarily, the Ntsr1-L6CT example shows a striking level of fluorescence in Striatum, that does not reflect in the amount of axons that are detected by the algorithms in the next figures.<br /> These apparent discrepancies may be due to non axonal-specific fluorescence in the samples. In any case, further analysis of such anatomical areas would be useful to consolidate the valuable dataset provided by the article.

Reviewer #3 (Public Review):

Summary:

-The paper offers a systematic and rigorous description of the layer-and sublayer specific outputs of the somatosensory cortex using a modern toolbox for the analysis of brain connectivity which combines: 1) Layer-specific genetic drivers for conditional viral tracing; 2) whole brain analyses of axon tracts using tissue clearing and imaging; 3) Segmentation and quantification of axons with normalization to the number of transduced neurons; 4) registration of connectivity to a widely used anatomical reference atlas; 5) functional validation of the connectivity using optogenetic approaches in vivo.

Strengths:

- Although the connectivity of the somatosensory cortex is already known, precise data are dispersed in different accounts (papers, online resources,) using different methods. So the present account has the merit of condensing this information in one very precisely documented report. It also brings new insights on the connectivity, such as the precise comparison of layer specific outputs, and of the primary and secondary somatosensory areas. It also shows a topographic organization of the circuits linking the somatosensory and motor cortices. The paper also offers a clear description of the methodology and of a rigorous approach to quantitative anatomy.

Weaknesses:

The weakness relates to the intrinsic limitations of the in toto approaches, that currently lack the precision and resolution allowing to identify single axons, axon branching or synaptic connectivity. These limitations are identified and discussed by the authors.

Reviewer #1 (Public Review):

Abbasi et al. assess in this MEG study the directed connectivity of both cortical and subcortical regions during continuous speech production and perception. The authors observed bidirectional connectivity patterns between speech-related cortical areas as well as subcortical areas in production and perception. Interestingly, they found in speaking low-frequency connectivity from subcortical (the right cerebellum) to cortical (left superior temporal) areas, while connectivity from the cortical to subcortical areas was in the high frequencies. In listening a similar cortico-subcortical connectivity pattern was observed for the low frequencies, but the reversed connectivity in the higher frequencies was absent.

The work by Abbasi and colleagues addresses a relevant, novel topic, namely understanding the brain dynamics between speaking and listening. This is important because traditionally production and perception of speech and language are investigated in a modality-specific manner. To have a more complete understanding of the neurobiology underlying these different speech behaviors, it is key to also understand their similarities and differences. Furthermore, to do so, the authors utilize state-of-the-art directed connectivity analyses on MEG measurements, providing a quite detailed profile of cortical and subcortical interactions for the production and perception of speech. Importantly, and perhaps most interesting in my opinion, is that the authors find evidence for frequency-specific directed connectivity, which is (partially) different between speaking and listening. This could suggest that both speech behaviors rely (to some extent) on similar cortico-cortical and cortico-subcortical networks, but different frequency-specific dynamics.

These elements mentioned above (investigation of both production and perception, both cortico-cortical and cortico-subcortical connectivity is considered, and observing frequency-specific connectivity profiles within and between speech behaviors), make for important novel contributions to the field. Notwithstanding these strengths, I find that they are especially centered on methodology and functional anatomical description, but that precise theoretical contributions for neurobiological and cognitive models of speech are less transparent. This is in part because the study compares speech production and perception in general, but no psychophysical or psycholinguistic manipulations are considered. I also have some critical questions about the design which may pose some confounds in interpreting the data, especially with regard to comparing production and perception.

(1) While the cortico-cortical and cortico-subcortical connectivity profiles highlighted in this study and the depth of the analyses are impressive, what these data mean for models of speech processing remains on the surface. This is in part due, I believe, to the fact that the authors have decided to explore speaking and listening in general, without targeting specific manipulations that help elucidate which aspects of speech processing are relevant for the particular connectivity profiles they have uncovered. For example, the frequency-specific directed connectivity is it driven by low-level psychophysical attributes of the speech or by more cognitive linguistic properties? Does it relate to the monitoring of speech, timing information, and updating of sensory predictions? Without manipulations trying to target one or several of these components, as some of the referenced work has done (e.g., Floegel et al., 2020; Stockert et al., 2021; Todorović et al., 2023), it is difficult to draw concrete conclusions as to which representations and/or processes of speech are reflected by the connectivity profiles. An additional disadvantage of not having manipulations within each speech behavior is that it makes the comparison between listening and speaking harder. That is, speaking and listening have marked input-output differences which likely will dominate any comparison between them. These physically driven differences (or similarities for that matter; see below) can be strongly reduced by instead exploring the same manipulations/variables between speaking and listening. If possible (if not to consider for future work), it may be interesting to score psychophysical (e.g., acoustic properties) or psycholinguistic (e.g., lexical frequency) information of the speech and see whether and how the frequency-specific connectivity profiles are affected by it.

(2) Recent studies comparing the production and perception of language may be relevant to the current study and add some theoretical weight since their data and interpretations for the comparisons between production and perception fit quite well with the observations in the current work. These studies highlight that language processes between production and perception, specifically lexical and phonetic processing (Fairs et al., 2021), and syntactic processing (Giglio et al., 2024), may rely on the same neural representations, but are differentiated in their (temporal) dynamics upon those shared representations. This is relevant because it dispenses with the classical notion in neurobiological models of language where production and perception rely on (partially) dissociable networks (e.g., Price, 2010). Rather those data suggest shared networks where different language behaviors are dissociated in their dynamics. The speech results in this study nicely fit and extend those studies and their theoretical implications.

(3) The authors align the frequency-selective connectivity between the right cerebellum and left temporal speech areas with recent studies demonstrating a role for the right cerebellum for the internal modelling in speech production and monitoring (e.g., Stockert et al., 2021; Todorović et al., 2023). This link is indeed interesting, but it does seem relevant to point out that at a more specific scale, it does not concern the exact same regions between those studies and the current study. That is, in the current study the frequency-specific connectivity with temporal regions concerns lobule VI in the right cerebellum, while in the referenced work it concerns Crus I/II. The distinction seems relevant since Crus I/II has been linked to the internal modelling of more cognitive behavior, while lobule VI seems more motor-related and/or contextual-related (e.g., D'Mello et al., 2020; Runnqvist et al., 2021; Runnqvist, 2023).

(4) On the methodological side, my main concern is that for the listening condition, the authors have chosen to play back the speech produced by the participants in the production condition. Both the fixed order as well as hearing one's own speech as listening condition may produce confounds in data interpretation, especially with regard to the comparison between speech production and perception. Could order effects impact the observed connectivity profiles, and how would this impact the comparison between speaking and listening? In particular, I am thinking of repetition effects present in the listening condition as well as prediction, which will be much more elevated for the listening condition than the speaking condition. The fact that it also concerns their own voice furthermore adds to the possible predictability confound (e.g., Heinks-Maldonado et al., 2005). In addition, listening to one's speech which just before has been articulated may, potentially strategically even, enhance inner speech and "mouthing" in the participants, hereby thus engaging the production mechanism. Similarly, during production, the participants already hear their own voice (which serves as input in the subsequent listening condition). Taken together, both similarities or differences between speaking and listening connectivity may have been due to or influenced by these order effects, and the fact that the different speech behaviors are to some extent present in both conditions.

(5) The ability of the authors to analyze the spatiotemporal dynamics during continuous speech is a potentially important feat of this study, given that one of the reasons that speech production is much less investigated compared to perception concerns motor and movement artifacts due to articulation (e.g., Strijkers et al., 2010). Two questions did spring to mind when reading the authors' articulation artifact correction procedure: If I understood correctly, the approach comes from Abbasi et al. (2021) and is based on signal space projection (SSP) as used for eye movement corrections, which the authors successfully applied to speech production. However, in that study, it concerned the repeated production of three syllables, while here it concerns continuous speech of full words embedded in discourse. The articulation and muscular variance will be much higher in the current study compared to three syllables (or compared to eye movements which produce much more stable movement potentials compared to an entire discourse). Given this, I can imagine that corrections of the signal in the speaking condition were likely substantial and one may wonder (1) how much signal relevant to speech production behavior is lost?; (2) similar corrections are not necessary for perception, so how would this marked difference in signal processing affect the comparability between the modalities?

References:<br /> - Abbasi, O., Steingräber, N., & Gross, J. (2021). Correcting MEG artifacts caused by overt speech. Frontiers in Neuroscience, 15, 682419.<br /> - D'Mello, A. M., Gabrieli, J. D., & Nee, D. E. (2020). Evidence for hierarchical cognitive control in the human cerebellum. Current Biology, 30(10), 1881-1892.<br /> - Fairs, A., Michelas, A., Dufour, S., & Strijkers, K. (2021). The same ultra-rapid parallel brain dynamics underpin the production and perception of speech. Cerebral Cortex Communications, 2(3), tgab040.<br /> - Floegel, M., Fuchs, S., & Kell, C. A. (2020). Differential contributions of the two cerebral hemispheres to temporal and spectral speech feedback control. Nature Communications, 11(1), 2839.<br /> - Giglio, L., Ostarek, M., Sharoh, D., & Hagoort, P. (2024). Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening. Proceedings of the National Academy of Sciences, 121(11), e2310766121.<br /> - Heinks‐Maldonado, T. H., Mathalon, D. H., Gray, M., & Ford, J. M. (2005). Fine‐tuning of auditory cortex during speech production. Psychophysiology, 42(2), 180-190.<br /> - Price, C. J. (2010). The anatomy of language: a review of 100 fMRI studies published in 2009. Annals of the new York Academy of Sciences, 1191(1), 62-88.<br /> - Runnqvist, E., Chanoine, V., Strijkers, K., Pattamadilok, C., Bonnard, M., Nazarian, B., ... & Alario, F. X. (2021). Cerebellar and cortical correlates of internal and external speech error monitoring. Cerebral Cortex Communications, 2(2), tgab038.<br /> - Runnqvist, E. (2023). Self-monitoring: The neurocognitive basis of error monitoring in language production. In Language production (pp. 168-190). Routledge.<br /> - Stockert, A., Schwartze, M., Poeppel, D., Anwander, A., & Kotz, S. A. (2021). Temporo-cerebellar connectivity underlies timing constraints in audition. Elife, 10, e67303.<br /> - Strijkers, K., Costa, A., & Thierry, G. (2010). Tracking lexical access in speech production: electrophysiological correlates of word frequency and cognate effects. Cerebral cortex, 20(4), 912-928.<br /> - Todorović, S., Anton, J. L., Sein, J., Nazarian, B., Chanoine, V., Rauchbauer, B., ... & Runnqvist, E. (2023). Cortico-cerebellar monitoring of speech sequence production. Neurobiology of Language, 1-21.

Reviewer #2 (Public Review):

Summary:

The authors re-analyse MEG data from a speech production and perception study and extend their previous Granger causality analysis to a larger number of cortical-cortical and in particular cortical-subcortical connections. Regions of interest were defined by means of a meta-analysis using Neurosynth.org and connectivity patterns were determined by calculating directed influence asymmetry indices from the Granger causality analysis results for each pair of brain regions. Abbasi et al. report feedforward signals communicated via fast rhythms and feedback signals via slow rhythms below 40 Hz, particularly during speaking. The authors highlight one of these connections between the right cerebellum lobule VI and auditory association area A5, where in addition the connection strength correlates negatively with the strength of speech tracking in the theta band during speaking (significant before multiple comparison correction). Results are interpreted within a framework of active inference by minimising prediction errors.

While I find investigating the role of cortical-subcortical connections in speech production and perception interesting and relevant to the field, I am not yet convinced that the methods employed are fully suitable to this endeavour or that the results provide sufficient evidence to make the strong claim of dissociation of bottom-up and top-down information flow during speaking in distinct frequency bands.

Strengths:

The investigation of electrophysiological cortical-subcortical connections in speech production and perception is interesting and relevant to the field. The authors analyse a valuable dataset, where they spent a considerable amount of effort to correct for speech production-related artefacts. Overall, the manuscript is well-written and clearly structured.

Weaknesses:

The description of the multivariate Granger causality analysis did not allow me to fully grasp how the analysis was performed and I hence struggled to evaluate its appropriateness.<br /> Knowing that (1) filtered Granger causality is prone to false positives and (2) recent work demonstrates that significant Granger causality can simply arise from frequency-specific activity being present in the source but not the target area without functional relevance for communication (Schneider et al. 2021) raises doubts about the validity of the results, in particular with respect to their frequency specificity. These doubts are reinforced by what I perceive as an overemphasis on results that support the assumption of specific frequencies for feedforward and top-down connections, while findings not aligning with this hypothesis appear to be underreported. Furthermore, the authors report some main findings that I found difficult to reconcile with the data presented in the figures. Overall, I feel the conclusions with respect to frequency-specific bottom-up and top-down information flow need to be moderated and that some of the reported findings need to be checked and if necessary corrected.

Major points

(1) I think more details on the multivariate GC approach are needed. I found the reference to Schaum et al., 2021 not sufficient to understand what has been done in this paper. Some questions that remained for me are:

(i) Does multivariate here refer to the use of the authors' three components per parcel or to the conditioning on the remaining twelve sources? I think the latter is implied when citing Schaum et al., but I'm not sure this is what was done here?

If it was not: how can we account for spurious results based on indirect effects?

(ii) Did the authors check whether the GC of the course-target pairs was reliably above the bias level (as Schaum et. al. did for each condition separately)? If not, can they argue why they think that their results would still be valid? Does it make sense to compute DAIs on connections that were below the bias level? Should the data be re-analysed to take this concern into account?

(iii) You may consider citing the paper that introduced the non-parametric GC analysis (which Schaum et al. then went on to apply): Dhamala M, Rangarajan G, Ding M. Analyzing Information Flow in Brain Networks with Nonparametric Granger Causality. Neuroimage. 2008; 41(2):354-362. https://doi.org/10.1016/j.neuroimage.2008.02. 020

(2) GC has been discouraged for filtered data as it gives rise to false positives due to phase distortions and the ineffectiveness of filtering in the information-theoretic setting as reducing the power of a signal does not reduce the information contained in it (Florin et al., 2010; Barnett and Seth, 2011; Weber et al. 2017; Pinzuti et al., 2020 - who also suggest an approach that would circumvent those filter-related issues). With this in mind, I am wondering whether the strong frequency-specific claims in this work still hold.

(3) I found it difficult to reconcile some statements in the manuscript with the data presented in the figures:

(i) Most notably, the considerable number of feedforward connections from A5 and STS that project to areas further up the hierarchy at slower rhythms (e.g. L-A5 to R-PEF, R-Crus2, L CB6 L-Tha, L-FOP and L-STS to R-PEF, L-FOP, L-TOPJ or R-A5 as well as R-STS both to R-Crus2, L-CB6, L-Th) contradict the authors' main message that 'feedback signals were communicated via slow rhythms below 40 Hz, whereas feedforward signals were communicated via faster rhythms'. I struggled to recognise a principled approach that determined which connections were highlighted and reported and which ones were not.

(ii) "Our analysis also revealed robust connectivity between the right cerebellum and the left parietal cortex, evident in both speaking and listening conditions, with stronger connectivity observed during speaking. Notably, Figure 4 depicts a prominent frequency peak in the alpha band, illustrating the specific frequency range through which information flows from the cerebellum to the parietal areas." There are two peaks discernible in Figure 4, one notably lower than the alpha band (rather theta or even delta), the other at around 30 Hz. Nevertheless, the authors report and discuss a peak in the alpha band.

(iii) In the abstract: "Notably, high-frequency connectivity was absent during the listening condition." and p.9 "In contrast with what we reported for the speaking condition, during listening, there is only a significant connectivity in low frequency to the left temporal area but not a reverse connection in the high frequencies."<br /> While Fig. 4 shows significant connectivity from R-CB6 to A5 in the gamma frequency range for the speaking, but not for the listening condition, interpreting comparisons between two effects without directly comparing them is a common statistical mistake (Makin and Orban de Xivry). The spectrally-resolved connectivity in the two conditions actually look remarkably similar and I would thus refrain from highlighting this statement and indicate clearly that there were no significant differences between the two conditions.

(iv) "This result indicates that in low frequencies, the sensory-motor area and cerebellum predominantly transmit information, while in higher frequencies, they are more involved in receiving it."<br /> I don't think that this statement holds in its generality: L-CB6 and R-3b both show strong output at high frequencies, particularly in the speaking condition. While they seem to transmit information mainly to areas outside A5 and STS these effects are strong and should be discussed.

(4) "However, definitive conclusions should be drawn with caution given recent studies raising concerns about the notion that top-down and bottom-up signals can only be transmitted via separate frequency channels (Ferro et al., 2021; Schneider et al., 2021; Vinck et al., 2023)."

I appreciate this note of caution and think it would be useful if it were spelled out to the reader why this is the case so that they would be better able to grasp the main concerns here. For example, Schneider et al. make a strong point that we expect to find Granger-causality with a peak in a specific frequency band for areas that are anatomically connected when the sending area shows stronger activity in that band than the receiving one, simply because of the coherence of a signal with its own linear projection onto the other area. The direction of a Granger causal connection would in that case only indicate that one area shows stronger activity than the other in the given frequency band. I am wondering to what degree the reported connectivity pattern can be traced back to regional differences in frequency-specific source strength or to differences in source strength across the two conditions.

Reviewer #3 (Public Review):

In the current paper, Abbasi et al. aimed to characterize and compare the patterns of functional connectivity across frequency bands (1 Hz - 90 Hz) between regions of a speech network derived from an online meta-analysis tool (Neurosynth.org) during speech production and perception. The authors present evidence for complex neural dynamics from which they highlight directional connectivity from the right cerebellum to left superior temporal areas in lower frequency bands (up to beta) and between the same regions in the opposite direction in the (lower) high gamma range (60-90 Hz). Abbasi et al. interpret their findings within the predictive coding framework, with the cerebellum and other "higher-order" (motor) regions transmitting top-down sensory predictions to "lower-order" (sensory) regions in the lower frequencies and prediction errors flowing in the opposite direction (i.e., bottom-up) from those sensory regions in the gamma band. They also report a negative correlation between the strength of this top-down functional connectivity and the alignment of superior temporal regions to the syllable rate of one's speech.

Strengths:

(1) The comprehensive characterization of functional connectivity during speaking and listening to speech may be valuable as a first step toward understanding the neural dynamics involved.

(2) The inclusion of subcortical regions and connectivity profiles up to 90Hz using MEG is interesting and relatively novel.

(3) The analysis pipeline is generally adequate for the exploratory nature of the work.

Weaknesses:

(1) The work is framed as a test of the predictive coding theory as it applies to speech production and perception, but the methodological approach is not suited to this endeavor.

(2) Because of their theoretical framework, the authors readily attribute roles or hierarchy to brain regions (e.g., higher- vs lower-order) and cognitive functions to observed connectivity patterns (e.g., feedforward vs feedback, predictions vs prediction errors) that cannot be determined from the data. Thus, many of the authors' claims are unsupported.

(3) The authors' theoretical stance seems to influence the presentation of the results, which may inadvertently misrepresent the (otherwise perfectly valid; cf. Abbasi et al., 2023) exploratory nature of the study. Thus, results about specific regions are often highlighted in figures (e.g., Figure 2 top row) and text without clear reasons.

(4) Some of the key findings (e.g., connectivity in opposite directions in distinct frequency bands) feature in a previous publication and are, therefore, interesting but not novel.

(5) The quantitative comparison between speech production and perception is interesting but insufficiently motivated.

(6) Details about the Neurosynth meta-analysis and subsequent selection of brain regions for the functional connectivity analyses are incomplete. Moreover, the use of the term 'Speech' in Neurosynth seems inappropriate (i.e., includes irrelevant works, yielding questionable results). The approach of using separate meta-analyses for 'Speech production' and 'Speech perception' taken by Abbasi et al. (2023) seems more principled. This approach would result, for example, in the inclusion of brain areas such as M1 and the BG that are relevant for speech production.

(7) The results involving subcortical regions are central to the paper, but no steps are taken to address the challenges involved in the analysis of subcortical activity using MEG. Additional methodological detail and analyses would be required to make these results more compelling. For example, it would be important to know what the coverage of the MEG system is, what head model was used for the source localization of cerebellar activity, and if specific preprocessing or additional analyses were performed to ensure that the localized subcortical activity (in particular) is valid.

(8) The results and methods are often detailed with important omissions (a speech-brain coupling analysis section is missing) and imprecisions (e.g., re: Figure 5; the Connectivity Analysis section is copy-pasted from their previous work), which makes it difficult to understand what is being examined and how. (It is also not good practice to refer the reader to previous publications for basic methodological details, for example, about the experimental paradigm and key analyses.) Conversely, some methodological details are given, e.g., the acquisition of EMG data, without further explanation of how those data were used in the current paper.

(9) The examination of gamma functional connectivity in the 60 - 90 Hz range could be better motivated. Although some citations involving short-range connectivity in these frequencies are given (e.g., within the visual system), a more compelling argument for looking at this frequency range for longer-range connectivity may be required.

(10) The choice of source localization method (linearly constrained minimum variance) could be explained, particularly given that other methods (e.g. dynamic imaging of coherent sources) were specifically designed and might potentially be a better alternative for the types of analyses performed in the study.

(11) The mGC analysis needs to be more comprehensively detailed for the reader to be able to assess what is being reported and the strength of the evidence. Relatedly, first-level statistics (e.g., via estimation of the noise level) would make the mGC and DAI results more compelling.

(12) Considering the exploratory nature of the study, it is essential for other researchers to continue investigating and validating the results presented in the current manuscript. Thus, it is concerning that data and scripts are not fully and openly available. Data need not be in its raw state to be shared and useful, which circumvents the stated data privacy concerns.

Reviewer #1 (Public Review):

Summary:

This paper reports the finding that less fat accumulates in C. elegans that are feeding on Comamonas aquatica DA1877 (DA) vs the standard lab diet of Escherichia coli OP50 (OP50). While these bacteria are likely to be different in many ways, the authors found that fat accumulation phenotype depends on the vitamin B12 content of the bacterial diet and the involvement of B12 in the methionine cycle, affecting SAMS-1 and phosphatidylcholine (PC) synthesis. They report that low PC levels activate SREBP-1 (SBP-1 in C. elegans) and that an important target of SBP-1 is the delta 9 desaturase FAT-7. Finally, they describe a role for ASM-3, an acid sphingomyelinase, in influencing PC synthesis and fat accumulation in the worm.

Strengths:

This is a comprehensive story about how a dietary change affects fat accumulation in C. elegans. Their experimental evidence is convincing. The most novel aspect of this paper is that the coelomecyte expression of asm-3 contributes to PC/TAG homeostasis in C. elegans, which most likely occurs through the production of phosphocholine by the enzymatic breakdown of sphingomyelin by ASM-3. The phosphocholine will provide precursors for phosphatidylcholine (PC) synthesis, contributing to the PC synthesis pathway.

Weaknesses:

In the way the story is presented, the authors tend to imply that they discovered the pathways of B12, PC, SBP-1, and FAT-7, ignoring some important studies describing the relationship between PC synthesis and TAG accumulation in both the mammalian lipid metabolism field (liver) as well as in C. elegans. Many previous studies with similar results are not cited appropriately. Thus, the pathways reported in the paper are not new, and in this sense, the work is mostly confirmatory.

Reviewer #2 (Public Review):

Summary:

Han et al. present a manuscript focusing on difference metabolism and the regulatory circuits controlling it in C. elegans fed two bacterial diets. In the first three figures and a half figures, using a combination of methods, they investigate lipid levels, changes in gene expression and genetic assays to come to the conclusion that vitamin B12 acts through the S-adenosylmethioine synthase sams-1 to perturb phosphatidylcholine levels, which in turn stimulate the C. elegans ortholog of the SREBP transcription factors to activate fatty acid synthesis genes such as fat-7/SCD1. Thus, while connections between diet, metabolic pathways and gene regulation is of general interest, this study largely confirms the work of others without direct credit in many instances, then fails to develop a more novel cell non-autonomous link between the pathways in the last two figures. Thus, this study would be expected to have a useful impact on the field, if it can be placed in context of previously published work.

Strengths:

(1) Connections between diet, metabolic pathways and gene regulation is of general interest<br /> (2) Figures 1-4 confirm data/observations from previously published work from MacNeil, et al. Cell 2015; Walker, et al. Cell 2011; Svensk, et al. PLoS Genetics 2013; Smulan, et al. Cell Reports, 2016; Giese, et al. eLife 2020 and Qin, et al. Cell Reports 2022..<br /> (3) The data in figures 5 and 6 showing importance of non-cell autonomous effects on metabolism.

Weaknesses:

(1) In order to differentiate their study from previous work, it seems that the authors try to make the argument that PC is higher in Comomonas than E. coli, therefore they are looking at repression of SBP-1-dependent function, however, the pairing of the diets is arbitrary, and the comparisons could easily be reversed. They are simply comparing a higher to a lower level of PC, rather than a basal to a lower, thus the concepts are the same. In addition, they fail to cite the larger body of literature linking phospholipid balance to SREBP function. For example, multiple studies in mammalian models link phospholipid balance, not just lowered PC, to SREBP function: Lim, Genes and Dev 2011; Wang, et al. Cell Stem Cell, 2018; Rong, et al. J Clin Invest 2017; Smulan et al, Cell Reports, 2016; Dobrosotskaya, Science. 2002 and recently, Rong, et al. Cell Met 2024.

(2) Figure 1: For example, the data in figure 1, shows measures of lipid content, RNA seq showing changes in metabolic enzymes such as fat-7/SCD-1 and lipid levels have already been shown in MacNeil, et al. Cell 2013 (lipid levels and gene expression changes) and the lipid levels in Comomonas vs E. coli were published in Ditot, et al. Nature Communications 2022 by Dr. Marian Walhout's lab.

(3) Figure 2/3: In Figure 2 and 3, they use a genetic screen to find regulators of fat-7/scd1 expression, and unsurprisingly, pull out genes with known to regulate this pathway. The authors go on to show that changes in SAM lead to changes in PC, and affect SBP-1/SREBP-1-dependent lipogenesis. This is a well described pathway from publications by the Walhout lab, Dr. Amy Walker's lab and Dr. Marc Pilon's lab (Walker, et al. Cell 2011; Svensk, et al. PLoS Genetics 2013; Smulan, et al. Cell Reports, 2016; Giese, et al. eLife 2020) in addition to a recent publication, Qin, et al. Cell Reports 2022. While some of these studies are cited in other places in the manuscript, the authors describe their results as "discovery", then fail to cite the relevant studies at those points (selected examples below

(4) Selected examples of citation issues:

a) Selected example: pg 6: "To understand the mechanism underlying the regulation of host lipid content triggered by DA, we examined the gene expression changes elicited by the two different bacterial diets in young adult animals by RNA-seq...In particular, genes related to the biosynthesis of unsaturated fatty acids showed a significant decrease in expression in DA-fed worms. For example, the delta-(9) fatty acid desaturases, fat-5 and fat-7, (which convert fatty acids 16:0 to 16:1n7 and 18:0 to 18:1n9, respectively32) decreased"

MacNeil et al Cell 2013 published a transcriptomics comparing young adult DA and Op50, which demonstrated decreases in fat-5 and fat-7. While MacNeil is cited in other parts of the paper, since the authors have performed a highly similar experiment and obtained similar results, this should be described as confirming the MacNeil study rather than as new data.

b) Selected Example: pg 10: "To determine whether PC levels have a causal effect on organismal lipid content, we supplemented worm diets with choline, the PC precursor, and uncovered a dose-dependent decrease in lipid content as measured by O.R.O staining (Figure 3B)."

Addition of choline to supplement defects in PC synthesis was first shown by Brendza, et al. Biochem J 2007. It was confirmed in Walker, et al. 2011, and further confirmation of PC rescue show in Ding, et al. 2015. The Brendza study is not cited at all and while studies from the Walker lab are cited in other places, the authors omit that changes in the DA diet are the same as changes seen when choline rescues PC loss from other perturbations.

c) Selected Example: pg 9: "Notably, DA has been reported as a B12-rich bacterium compared to OP16, hinting at the possibility that the DA diet might boost dietary B12 levels."

Reference 16 is Watson, et al. Cell 2015 where the Walhout lab demonstrates that DA does in fact act through the diet to alter the Met/SAM cycle and other B12 dependent processes in C. elegans. This paper, along with MacNeil above broke ground in linking B12 and the Met/SAM cycle to specific phenotypes in C. elegans, which was followed up by extensive work from the Walhout lab on this cycle, thus, it seems odd that the authors describe their own data as "hinting" at this connection.

d) Selected example: pg 17: "Indeed, this is further supported by our observation that mutants of histone methyltransferases SET-2 and SET-30 (which install H3K4me1 and H3K4me2, respectively) exhibited elevated lipid content on DA diet (data not shown). Notably, while both set-2 and set-30 mutants had this effect, only set-2 appears to control fat-7 expression (data not shown)". Extensive work from Dr. Anne Brunet's lab (Greer, et al. Nature 2010; Greer, et al. Nature 2011; Han, et al. Nature 2017) link set-2 and H3K4 methylation to lipid accumulation and fat-7. The authors fail to cite these studies.

Reviewer #3 (Public Review):

Summary:

The authors presented data that linked vitamin B12, S-adenosyl methionine (SAM), and phosphatidylcholine (PC) synthesis to lipid homeostasis in C. elegans. They confirmed mechanisms previously shown by other labs, including the regulation of FAT-7 expression by SBP-1, and the targeting of SEIP-1 by PC levels. The authors also attempted to link the synthesis of phospho-choline by the ASM-3 sphingomyelinase to PC synthesis and lipid homeostasis. However, the relative contribution of phospho-choline by ASM-3 versus the canonical Kennedy pathway was not elucidated. Therefore, the significance of the ASM-3-dependent mechanism to PC synthesis requires further investigation.

Strengths:

The authors used a wide range of biochemical and cell biological methods to measure fatty acid composition, neutral lipid levels, and lipid droplet dynamics in C. elegans. The quality of the data is generally high.

Weaknesses:

Data interpretation and the construction of the working model did not seem to take into account the two well-established pathways for PC synthesis. The Kennedy pathway generates PC from phospho-choline and DAG via a cytidine-based intermediate. The second PC synthesis pathway entails the methylation of PE by PEMT, with the donor methyl groups provided by the vitamin B12-dependent 1-carbon cycle. The authors' model seemed to overlook part of the Kennedy pathway that involves choline kinase (and not ASM-3) as the canonical enzyme that generates phospho-choline. The authors also did not explicitly consider DAG as a precursor of triacylglycerol (TAG), which was directly or indirectly measured as a readout of organismal fat content in the paper. Therefore, alternative models should be entertained. For example, the proposed genetic and dietary effects on lipid homeostasis could stem from the competition for a limiting pool of precursors that were shared by PC and TAG synthesis. PC itself may not have a deterministic role, as depicted by the authors' model. Finally, the claim that "coelomocytes regulate diets-induced lipid homeostasis through asm-3" was not well supported. In the absence of quantitative analysis of phospho-choline in mutants, it was unclear how much ASM-3 contributed to the overall phospho-choline, and ultimately PC level. The proposed inter-tissue regulation of PC synthesis also requires coelomocytes-specific knock-down/depletion of asm-3 for verification.

Reviewer #1 (Public Review):

Li et al. report here on the expression of a G-protein subunit Gng13 in ectopic tuft cells that develop after severe pulmonary injury in mice. By deleting this gene in ectopic tuft cells as they arise, the authors observed worsened lung injury and greater inflammation after influenza infection, as well as a decrease in the overall number of ectopic tuft cells. This was in stark contrast to deletion of Trpm5, a cation channel generally thought to be required for all functional gustatory signaling in tuft cells, where no phenotype is observed. Strengths here include a thorough assessment of lung injury via a number of different techniques. Weaknesses are notable: Confusingly, these findings are at odds with reports from other groups demonstrating no obvious phenotype upon influenza infection in mice lacking the transcription factor Pou2f3, which is essential for all tuft cell specification and development. The authors speculate that heterogeneity within nascent tuft cell populations, specifically the presence of pro- and anti-inflammatory tuft cells, may explain this difference, but they do not provide any data to support this idea.

Notes on revision: The authors provided responses to some of my critiques. I think the central discrepancy between the lack of a phenotype in Pou2f3 and Trpm5 KO mice compared to the stronger phenotype in the Chat-Cre / Gng13 KO mice remains unresolved and will require future work to provide a clear model. This may or may not ultimately involve tuft cell heterogeneity.

Reviewer #2 (Public Review):

Summary:

The study by Li et al. aimed to demonstrate the role of the G𝛾13-mediated signal transduction pathway in tuft cell-driven inflammation resolution and repairing injured lung tissue. The authors showed the reduced number of tuft cells in the parenchyma of G𝛾13 null lungs following viral infection. Mice with a G𝛾13 null mutation showed increased lung damage and heightened macrophage infiltration when exposed to the H1N1 virus. Their further findings suggested that lung inflammation resolution, epithelial barrier and fibrosis were worsen in G𝛾13 null mutants.

Strengths:

The revised study carefully analyzed phenotypes in mice lacking G𝛾13 in response to viral infection, providing further support that G𝛾13+ tuft cells play a role in the resolution of inflammation and injury repair.

Reviewer #3 (Public Review):

Summary:

Prior research on SCC3, a cohesin subunit protein, in yeast and Arabidopsis has underscored its vital role in cell division. This study investigated into the specific functions of SCC3 in rice mitosis and meiosis. In a weakened SCC3 mutant, sister chromatids separating was observed in anaphase I, resulting in 24 univalents and subsequent sterility. The authors meticulously documented SCC3's loading and degradation dynamics on chromosomes, noting its impact on DNA replication. Despite the loss of homologous chromosome pairing and synapsis in the mutant, chromosomes retained double-strand breaks without fragmenting. Consequently, the authors inferred that in the scc3 mutant, DNA repair more frequently relies on sister chromatids as templates compared to the wild type.

Strengths:

The study presents exceptionally well-executed research in the field of rice cytogenetics.

Weaknesses:

While the paper's conclusions are generally well-supported, further substantiation is needed for the claim that SCC3 inhibits template choice for sister chromatids. To bolster this conclusion, I recommend that the authors perform whole-genome sequencing on parental and F1 individuals from two rice variants, subsequently calculating the allele frequencies at heterozygous sites in the F1 individuals. If SCC3 indeed inhibits inter-sister chromatid repair in the wild type, we would anticipate a higher frequency of inter-homologous chromosome repair (i.e., gene conversion). This should be manifested as a bias away from the Mendelian inheritance ratio (50:50) in the offspring of the wild type compared to the offspring of the scc3+/- mutant.

Reviewer #1 (Public Review):

Summary:

The revised manuscript is much improved. As stated previously, it is on an interesting and important topic and provides many new potentially important findings. The manuscript contains a large amount of high-quality data. In the revised manuscript, the authors have done a nice job addressing the concerns raised in the previous review. They have refined their conclusions and the evidence provided supports conclusions drawn. Likewise, the writing and low of the manuscript is much improved.

Strengths:

The manuscript contains a large amount of high-quality data that is used to draw interesting and important conclusions.

Weaknesses:

There are still some issues with grammar and word usage, but these should be easily corrected with some additional minor editing. Other than some minor editing, my only real question/concern is whether the data presented shows that SCC3 is directly involved in gene regulation. It may well be that changes in chromatin structure caused by mutations in SCC3 and the axial element protein containing genes examined indirectly affect transcript levels for the genes examined.

Reviewer #2 (Public Review):

Summary:

This manuscript shows detailed evidence about the role of cohesin regulator in rice meiosis and mitosis

Strengths:

There is a very clear mechanism for its role during replication

Weaknesses:

The authors did not consider to create heterozygous mutants for the replication fork.

April 15. Revisions read.

Reviewer #1 (Public Review):

Interactions known to be important for melanosome transport include exon F and the globular tail domain (GTD) of MyoVa with Mlph. Motivated by a discrepancy between in vitro and cell culture results regarding necessary interactions for MyoVa to be recruited to the melanosome, the authors used a series of pull-down and pelleting assays experiments to identify an additional interaction that occurs between exon G of MyoVa and Mlph. This interaction is independent of and synergistic with the interaction of Mlph with exon F. However, the interaction of the actin-binding domain of Mlph can occur either with exon G or with the actin filament, but not both simultaneously. These data lead to a modified recruitment model where both exon F and exon G enhance binding of Mlph to auto-inhibited MyoVa, and then via an unidentified switch (PKA?) the actin-binding domain of Mlph dissociates from MyoVa and interacts with the actin filament to enhance MyoVa processivity.

The only weakness noted is that the authors could have had a more complete story if they pursued whether PKA phosphorylation/dephosphorylation of Mlph is indeed the switch for the actin-binding domain of Mlph to interact with exon G versus the actin filament.

Reviewer #2 (Public Review):

The authors identify a third component in the interaction between myosin Va and melanophilin- an interaction between a 32-residue sequence encoded by exon-g in myosin Va and melanophilin's actin binding domain. This interaction has implications for how melanosome motility may be regulated.

The authors have now included some necessary controls that were requested. In terms of adding new information to increase the significance and impact of the paper, they added a single affinity measurement. Unfortunately, it did not involve Exon G specifically. Moreover, they did not add any new mechanistic or functional data to provide a more conceptual advance. For example, is the Exon G interaction regulated by phosphorylation? Is this what dictates the choice between Mlph's actin binding domain (ABD) binding to actin or to exon-G. How does local actin concentration influence this decision. What changes regarding melanosome dynamics in cells between these two alternatives? Do in vitro reconstitution assays show that binding to Exon-G instead of actin affects the processivity of a Rab27a/Myosin 5a/Mlph transport complex? Finally, while the authors make clear in the abstract and text that they are just identifying a third component that mediates the Melanophilin-dependent association of myosin-5a with melanosomes, the title gives the impression that they identified all three in this manuscript. I really think the title should be changed to something like Identification of a third component that mediates the Melanophilin-dependent association of myosin-5a with melanosomes, as this accurately reflects what is new in this work.

Reviewer #1 (Public Review):

Summary:

The authors perform a multidisciplinary approach to describe the conformational plasticity of P-Rex1 in various states (autoinhibited, IP4 bound and PIP3 bound). Hydrogen-deuterium exchange (HDX) is used to reveal how IP4 and PIP3 binding affect intramolecular interactions. While IP4 is found to stabilize autoinhibitory interactions, PIP3 does the opposite, leading to deprotection of autoinhibitory sites. Cryo-EM of IP4 bound P-Rex1 reveals a structure in the autoinhibited conformation, very similar to the unliganded structure reported previously (Chang et al. 2022). Mutations at observed autoinhibitory interfaces result in a more open structure (as shown by SAXS), reduced thermal stability and increased GEF activity in biochemical and cellular assays. Together their work portrays a dynamic enzyme that undergoes long-range conformational changes upon activation on PIP3 membranes. The results are technically sound and the conclusions are justified. The main drawback is the limited novelty due to the recently published structure of unliganded P-Rex1, which is virtually identical to the IP4 bound structure presented here. Novel aspects suggest a regulatory role for IP4, but the exact significance and mechanism of this regulation has not been explored.

Strengths:

The authors use a multitude of techniques to describe the dynamic nature and conformational changes of P-Rex1 upon binding to IP4 and PIP3 membranes. The different approaches together fit well with the overall conclusion that IP4 binding negatively regulates P-Rex1, while binding to PIP3 membranes leads to conformational opening and catalytic activation. The experiments are performed very thoroughly and are technically sound. The results are clear and support the conclusions.

Weaknesses:

(1) The novelty of the study is compromised due to the recently published structure of unliganded P-Rex1 (Chang et al. 2022). The unliganded and IP4 bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta-gamma is presented.

(2) The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

Reviewer #2 (Public Review):

Summary:

In this new paper, the authors used biochemical, structural, and biophysical methods to elucidate the mechanisms by which IP4, the PIP3 headgroup, can induce an autoinhibit form of P-Rex1 and propose a model of how PIP3 can trigger long-range conformational changes of P-Rex1 to relieve this autoinhibition. The main findings of this study are that a new P-Rex1 autoinhibition is driven by an IP4-induced binding of the PH domain to the DH domain active site and that this autoinhibit form stabilized by two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle (4HB) subdomain. Moreover, they found that the binding of phospholipid PIP3 to the PH domain can disrupt these interactions to relieve P-Rex1 autoinhibition.

Strengths:

The study provides good evidence that binding of IP4 to the P-Rex1 PH domain can make the two long-range interactions between the catalytic DH domain and the first DEP domain, and between the PH domain and the C-terminal IP4P 4HB subdomain that generate a novel P-Rex1 autoinhibition mechanism. This valuable finding adds an extra layer of P-Rex1 regulation (perhaps in the cytoplasm) to the synergistic activation by phospholipid PIP3 and the heterotrimeric Gβγ subunits at the plasma membrane. Overall, this manuscript's goal sounds interesting, the experimental data were carried out carefully and reliably.

Weakness:

The set of experiments with the disulfide bond S235C/M244C caused a bit of confusion for interpretation, it should be moved into the supplement, and the text and Figure 4 were altered accordingly.

Reviewer #3 (Public Review):

Summary:

In this report, Ravala et al demonstrate that IP4, the soluble head-group of phosphatiylinositol 3,4,5 - trisphosphate (PIP3), is an inhibitor of pREX-1, a guanine nucleotide exchange factor (GEF) for Rac1 and related small G proteins that regulate cell cell migration. This finding is perhaps unexpected since pREX-1 activity is PIP3-dependent. By way of Cryo-EM (revealing the structure of the p-REX-1/IP4 complex at 4.2Å resolution), hydrogen-deuterium mass spectrometry and small angle X-ray scattering, they deduce a mechanism for IP4 activation, and conduct mutagenic and cell-based signaling assays that support it. The major finding is that IP4 stabilizes two interdomain interfaces that block access of the DH domain, which conveys GEF activity towards small G protein substrates. One of these is the interface between the PH domain that binds to IP4 and a 4-helix bundle extension of the IP4 Phosphatase domain and the DEP1 domain. The two interfaces are connected by a long helix that extends from PH to DEP1. Although the structure of fully activated pREX-1 has not been determined, the authors propose a "jackknife" mechanism, similar to that described earlier by Chang et al (2022) (referenced in the author's manuscript) in which binding of IP3 relieves a kink in a helix that links the PH/DH modules and allows the DH-PH-DEP triad to assume an extended conformation in which the DH domain is accessible. While the structure of the activated pREX-1 has not been determined, cysteine mutagenesis that enforces the proposed kink is consistent with this hypothesis. SAXS and HDX-MS experiments suggest that IP4 acts by stiffening the inhibitory interfaces, rather than by reorganizing them. Indeed, the cryo-EM structure of ligand-free pREX-1 shows that interdomain contacts are largely retained in the absence of IP4.

Strengths:

The manuscript thus describes a novel regulatory role for IP4 and is thus of considerable significance to our understanding of regulatory mechanisms that control cell migration, particularly in immune cell populations. Specifically, they show how the inositol polyphosphate IP4 controls the activity of pREX-1, a guanine nucleotide exchange factor that controls the activity of small G proteins Rac and CDC42. In their clearly-written discussion, the authors explain how PIP3, the cell membrane and the Gbeta-gamma subunits of heterotrimeric membranes together localize pREX-1 at the membrane and induce activation. The quality of experimental data is high and both in vitro and cell-based assays of site-directed mutants designed to test the author's hypotheses are confirmatory. The results strongly support the conclusions. The combination of cryo-EM data, that describe the static (if heterogeneous) structures with experiments (small angle x-ray scattering and hydrogen-deuterium exchange-mass spectrometry) that report on dynamics are well employed by the authors

Manuscript revision:

The reviewers noted a number of weaknesses, including error analysis of the HDX data, interpretation of the mutagenesis data, the small fraction of the total number of particles used to generate the EM reconstruction, the novelty of the findings in light of the previous report by Cheng et al, 2022, various details regarding presentation of structural results and questions regarding the interpretation of the inhibition data (Figure 1D). The authors have responded adequately to these critiques. It appears that pREX-1 is a highly dynamic molecule, and considerable heterogeneity among particles might be expected.

While, indeed, the conformation of pREX presented in this report is not novel, the finding that this inactive conformational state is stabilized by IP4 is significant and important. The evidence for this is both structural and biochemical, as indicated by micromolar competition of IP4 with PI3-enriched vesicles resulting in the inhibition of pREX-1 GEF activity.

Reviewer #1 (Public Review):

The comments below are from my review of the first submission of this article. I would now like to thank the authors for their hard work in responding to my comments. I am happy with the changes they have made, in particular the inclusion of further experimental evidence in Figures 2 and 4. I have no further comments to make.

In 'Systems analysis of miR-199a/b-5p and multiple miR-199a/b-5p targets during chondrogenesis', Patel et al. present a variety of analyses using different methodologies to investigate the importance of two miRNAs in regulating gene expression in a cellular model of cartilage development. They first re-analysed existing data to identify these miRNAs as one of the most dynamic across a chondrogenesis development timecourse. Next, they manipulated the expression of these miRNAs and showed that this affected the expression of various marker genes as expected. An RNA-seq experiment on these manipulations identified putative mRNA targets of the miRNAs which were also supported by bioinformatics predictions. These top hits were validated experimentally and, finally, a kinetic model was developed to demonstrate the relationship between the miRNAs and mRNAs studied throughout the paper.

I am convinced that the novel relationships reported here between miR-199a/b-5p and target genes FZD6, ITGA3 and CAV1 are likely to be genuine. It is important for researchers working on this system and related diseases to know all the miRNA/mRNA relationships but, as the authors have already published work studying the most dynamic miRNA (miR-140-5p) in this biological system I was not convinced that this study of the second miRNA in their list provided a conceptual advance on their previous work.

I was also concerned with the lack of reporting of details of the manipulation experiments. The authors state that they have over-expressed miR-199a-5p (Figure 2A) and knocked down miR-199b-5p (Figure 2B) but they should have reported their proof that these experiments had worked as predicted, e.g. showing the qRT-PCR change in miRNA expression. Similarly, I was concerned that one miRNA was over-expressed while the other was knocked down - why did the authors not attempt to manipulate both miRNAs in both directions? Were they unable to achieve a significant change in miRNA expression or did these experiments not confirm the results reported in the manuscript?

I had a number of issues with the way in which some of the data is presented. Table 1 only reported whether a specific pathway was significant or not for a given differential expression analysis but this concealed the extent of this enrichment or the level of statistical significance reported. Could it be redrawn to more similarly match the format of Figure 3A? The various shades of grey in Figure 2 and Figure 4 made it impossible to discriminate between treatments and therefore identify whether these data supported the conclusions made in the text. It also appeared that the same results were reported in Figure 3B and 3C and, indeed, Figure 3B was not referred to in the main text. Perhaps this figure could be made more concise by removing one of these two sets of panels?

Overall, while I think that this is an interesting and valuable paper, I think its findings are relatively limited to those interested in the role of miRNAs in this specific biomedical context.

Reviewer #2 (Public Review):

Summary:

This study represents an ambitious endeavor to comprehensively analyze the role of miR-199a/b-5p and its networks in cartilage formation. By conducting experiments that go beyond in vitro MSC differentiation models, more robust conclusions can be achieved.

Strengths:

This research investigates the role of miR-199a/b-5p during chondrogenesis using bioinformatics and in vitro experimental systems. The significance of miRNAs in chondrogenesis and OA is crucial, warranting further research, and this study contributes novel insights.

Weaknesses:

While miR-140 and miR-455 are used as controls, these miRNAs have been demonstrated to be more relevant to Cartilage Homeostasis than chondrogenesis itself. Their deficiency has been genetically proven to induce Osteoarthritis in mice. Therefore, the results of this study should be considered in comparison with these existing findings.

Reviewer #2 (Public Review):

Summary:

This manuscript mainly studied the biological effect of tenascin XB (TNXB) on hemophilic arthropathy (HA) progression. Using bioinformatic and histopathological approaches, the authors identified the novel candidate gene TNXB for HA. Next, authors showed that TNXB knockdown lead to chondrocyte apoptosis, matrix degeneration and subchondral bone loss in vivo/vitro. Furthermore, AKT agonist promoted extracellular matrix synthesis and prevented apoptosis in TNXB knockdown chondrocytes.

Strengths:

In general, this study significantly advances our understanding of HA pathogenesis. The authors utilize comprehensive experimental strategies to demonstrate the role of TNXB in cartilage degeneration associated with HA. The results are clearly presented, and the conclusions appear appropriate.

Weaknesses:

Additional clarification is required regarding the gender of the F8-/- mouse in the study. Is the mouse male or female?

Reviewer #1 (Public Review):

Summary:

Chen and colleagues first compared the cartilage tissues collected from OA and HA patients using histology and immunostaining. Then, a genome-wide DNA methylation analysis was performed, which informed the changes of a novel gene, TNXB. IHC confirmed that TNXB has a lower expression level in HA cartilage than OA. Next, the authors demonstrated that TNXB levels were reduced in HA animal model, and intraarticular injection of AAV carrying TNXB siRNA induced cartilage degradation and promoted chondrocyte apoptosis. Based on KEGG enrichment, histopathological analysis, and western blot, the authors also showed the relationship between TNXB and AKT phosphorylation. Lastly, AKT agonist, specifically SC79 in this study, was shown to partially rescue the changes of in vitro-cultured chondrocytes induced by Tnxb knock-down. Overall, this is an interesting study and provided sufficient data to support their conclusion.

Strengths:

(1) Both human and mouse samples were examined.<br /> (2) The HA model was used.<br /> (3) genome-wide DNA methylation analysis was performed.

Weaknesses:

(1) In some experiments, the selection of the control groups was not ideal.<br /> (2) More details on analyzing methods and information on replicates need to be included.<br /> (3) Discussion can be improved by comparing findings to other relevant studies.<br /> (4) The use of transgenic mice with conditional Tnxb depletion can further define the physiological roles of Tnxb.

Reviewer #1 (Public Review):

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

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

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

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

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

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

The authors have revised their manuscript and adequately addressed the major concerns. Although more in depth analyses of these rich datasets are definitely possible, the current results nevertheless stand on their own. Indeed, the work serves as a beacon to move away from the idea that cortico-collicular projections function primarily to impart behavioral relevance upon auditory midbrain neurons. This knowledge inspires a search for alternative explanations as to the role of auditory cortico-collicular synapses in behavior.

Reviewer #2 (Public Review):

Summary:

This study takes a new approach to studying the role of corticofugal projections from auditory cortex to inferior colliculus. The authors performed two-photon imaging of cortico-recipient IC neurons during a click detection task in mice with and without lesions of auditory cortex. In both groups of animals, they observed similar task performance and relatively small differences in the encoding of task-response variables in the IC population. They conclude that non-cortical inputs to the IC provide can substantial task-related modulation, at least when AC is absent.

Strengths:

This study provides valuable new insight into big and challenging questions around top-down modulation of activity in the IC. The approach here is novel and appears to have been executed thoughtfully. Thus, it should be of interest to the community.

Weaknesses:

There are however, substantial concerns about the interpretation of the findings and limitations to the current analysis. In particular, Analysis of single unit activity is absent, making interpretation of population clusters and decoding less interpretable. These concerns should be addressed to make sure that the results can be interpreted clearly in an active field that already contains a number of confusing and possibly contradictory findings.

Reviewer #3 (Public Review):

Summary:

This study aims to demonstrate that cortical feedback is not necessary to signal behavioral outcome to shell neurons of the inferior colliculus during a sound detection task. The demonstration is achieved in a very clear manner by the observation of the activity of cortico-recepient neurons in animals which have received lesions of the auditory cortex. The experiment shows that neither behavior performance nor neuronal responses are significantly impacted by cortical lesions except for the case of partial lesions which seem to have a disruptive effect on behavioral outcome signaling.

Strengths:

The demonstration of the main conclusions is based on state-of-the-art, carefully controlled methods and is highly convincing. There is an in depth discussion of the different effects of auditory cortical lesions on sound detection behavior.

Weaknesses:

The description of feedback signals could be more detailed although it is difficult to achieve good temporal resolution with the calcium imaging technique necessary for targeting cortico-recipient neurons.

Reviewer #1 (Public Review):

Summary:<br /> This is an excellent study by a superb investigator who discovered and is championing the field of migrasomes. This study contains a hidden "gem" - the induction of migrasomes by hypotonicity and how that happens. In summary, an outstanding fundamental phenomenon (migrasomes) en route to becoming transitionally highly significant.

Strengths:

Innovative approach at several levels. Migrasomes - discovered by Dr Yu's group - are an outstanding biological phenomenon of fundamental interest and now of potentially practical value.

Weaknesses:

I feel that the overemphasis on practical aspects (vaccine), however important, eclipses some of the fundamental aspects that may be just as important and actually more interesting. If this can be expanded, the study would be outstanding.

Reviewer #2 (Public Review):

Summary:

The authors' report describes a novel vaccine platform derived from a newly discovered organelle called a migrasome. First, the authors address a technical hurdle in using migrasomes as a vaccine platform. Natural migrasome formation occurs at low levels and is labor intensive, however, by understanding the molecular underpinning of migrasome formation, the authors have designed a method to make engineered migrasomes from cultured, cells at higher yields utilizing a robust process. These engineered migrasomes behave like natural migrasomes. Next, the authors immunized mice with migrasomes that either expressed a model peptide or the SARS-CoV-2 spike protein. Antibodies against the spike protein were raised that could be boosted by a 2nd vaccination and these antibodies were functional as assessed by an in vitro pseudoviral assay. This new vaccine platform has the potential to overcome obstacles such as cold chain issues for vaccines like messenger RNA that require very stringent storage conditions.

Strengths:

The authors present very robust studies detailing the biology behind migrasome formation and this fundamental understanding was used to form engineered migrasomes, which makes it possible to utilize migrasomes as a vaccine platform. The characterization of engineered migrasomes is thorough and establishes comparability with naturally occurring migrasomes. The biophysical characterization of the migrasomes is well done including thermal stability and characterization of the particle size (important characterizations for a good vaccine).

Weaknesses:

With a new vaccine platform technology, it would be nice to compare them head-to-head against a proven technology. The authors would improve the manuscript if they made some comparisons to other vaccine platforms such as a SARS-CoV-2 mRNA vaccine or even an adjuvanted recombinant spike protein. This would demonstrate a migrasome-based vaccine could elicit responses comparable to a proven vaccine technology. Additionally, understanding the integrity of the antigens expressed in their migrasomes could be useful. This could be done by looking at functional monoclonal antibodies binding to their migrasomes in a confocal microscopy experiment.

Reviewer #1 (Public Review):

Summary:

In this paper, Wang et al show that differentiated peridermal cells of the zebrafish epidermis extend cytoneme-like protrusions toward the less differentiated, intermediate layer below. They present evidence that expression of a dominant-negative cdc42, inhibits cytoneme formation and leads to elevated expression of a marker of undifferentiated keratinocytes, krtt1c19e, in the periderm layer. Data is presented suggesting the involvement of Delta-Notch signaling in keratinocyte differentiation. Finally, changes in expression of the inflammatory cytokine IL-17 and its receptors is shown to affect cytoneme number and periderm structure in a manner similar to Notch and cdc42 perturbations.

Strengths:

Overall, the idea that differentiated cells signal to underlying undifferentiated cells via membrane protrusions in skin keratinocytes is interesting and novel, and it is clear that periderm cells send out thin membrane protrusions that contain a Notch ligand. Further, perturbations that affect cytoneme number, Notch signaling, and IL-17 expression clearly lead to changes in periderm structure and gene expression.

Weaknesses:

More work is needed to determine whether the effects on keratinocyte differentiation are due to a loss of cytonemes themselves, or to broader effects of inhibiting cdc42. Moreover, more evidence is needed to support the claim that periderm cytonemes deliver Delta ligands to induce Notch signaling below. Without these aspects of the study being solidified, understanding how IL-17 affects these processes seems premature.

Reviewer #2 (Public Review):

Summary:

The aim of the study was to understand how cells of the skin communicate across dermal layers. The research group has previously demonstrated that cellular connections called airinemes contribute to this communication. The current work builds upon this knowledge by showing that differentiated keratinocytes also use cytonemes, specialized signaling filopodia, to communicate with undifferentiated keratinocytes. They show that cytonemes are the more abundant type of cellular extension used for communication between the differentiated keratinocyte layer and the undifferentiated keratinocytes. Disruption of cytoneme formation led to the expansion of the undifferentiated keratinocytes into the periderm, mimicking skin diseases like psoriasis. The authors go on to show that disruption of cytonemes results in perturbations in Notch signaling between the differentiated keratinocytes of the periderm and the underlying proliferating undifferentiated keratinocytes. Further, the authors show that Interleukin-17, also known to drive psoriasis, can restrict the formation of periderm cytonemes, possibly through the inhibition of Cdc42 expression. This work suggests that cytoneme-mediated Notch signaling plays a central role in normal epidermal regulation. The authors propose that disruption of cytoneme function may be an underlying cause of various human skin diseases.

Strengths:

The authors provide strong evidence that periderm keratinocytes cytonemes contain the notch ligand DeltaC to promote Notch activation in the underlying intermediate layer to regulate accurate epidermal maintenance.

Weaknesses:

The impact of the study would be increased if the mechanism by which Interlukin-17 and Cdc42 collaborate to regulate cytonemes was defined. Experiments measuring Cdc42 activity, rather than just measuring expression, would strengthen the conclusions.

Reviewer #3 (Public Review):

Summary:

Leveraging zebra fish as a research model, Wang et al identified "cytoneme-like structures" as a mechanism for mediating cell-cell communications among skin epidermal cells. The authors further demonstrated that the "cytoneme-like structures" can mediate Notch signaling, and the "cytoneme-like structures" are influenced by IL17 signaling.

Strengths:

Elegant zebrafish genetics, reporters, and live imaging.

Weaknesses: (minor)<br /> This paper focused on characterizing the "cytoneme-like structures" between different layers and the NOTCH signaling. However, these "cytoneme-like structures" observed in undifferentiated KC (Figure 2B), although at a slightly lower frequency, were not interpreted. In addition, it is unclear if these "cytoneme-like structures" can mediate other signaling pathways than NOTCH.

Overall, this is a solid paper with convincing data reporting the "cytoneme-like structures" in vivo, and with compelling data demonstrating the roles in NOTCH signaling and the regulation by IL17.

These findings provide a foundation for future work exploring the "cytoneme-like structures" in the mammalian system and other epithelial tissue types. This paper also suggests a potential connection between the "cytoneme-like structures" and psoriasis, which needs to be further explored in clinical samples.

Reviewer #1 (Public Review):

Summary:

Juvenile Hormone (JH) plays a key role in insect development and physiology. Although the intracellular receptor for JH was identified long ago, a number of studies have shown that part of JH functions should be fulfilled through binding to an unknown membrane receptor, which was proposed to belong to the RTK family. In this study, the authors screened all RTKs from the H. armigera genome for their ability to mediate responses to JH III treatment both in cultured cells and in developing animals. They also present convincing evidence that CAD96CA and FGFR1 directly bind JH III, and that their role might be conserved in other insect species.

Strengths:

Altogether, the experimental approach is very complete and elegant, providing evidence for the role of CAD96CA and FGFR1 in JH signalling using different techniques and in different contexts. I believe that this work will open new perspectives to study the role of JH and better understand what is the contribution of signalling through membrane receptors for JH-dependent developmental processes.

Weaknesses:

I don't see major weaknesses in this study. However, I think that the manuscript would benefit from further information or discussion regarding the relationship between the two newly identified receptors. Experiments (especially in HEK-293T cells) suggest that CAD96CA and FGFR1 are sufficient on their own to transduce JH signalling. However, they are also necessary since loss-of-function conditions for each of them are sufficient to trigger strong effects (while the other is supposed to be still present).

In addition, despite showing different expression patterns, the two receptors seem to display similar developmental functions according to loss-of-function phenotypes. It is therefore unclear how to draw a model for membrane receptor-mediated JH signalling that includes both CAD96CA and FGFR1.

Reviewer #2 (Public Review):

Summary:

Juvenile hormone (JH) is a pleiotropic terpenoid hormone in insects that mainly regulates their development and reproduction. In particular, its developmental functions are described as the "status quo" action, as its presence in the hemolymph (the insect blood) prevents metamorphosis-initiating effects of ecdysone, another important hormone in insect development, and maintains the juvenile status of insects.

While such canonical functions of JH are known to be mediated by its intracellular receptor complex composed of Met and Tai, there have been multiple reports suggesting the presence of cell membrane receptor(s) for JH, which mediate non-genomic effects of this terpenoid hormone. In particular, the presence of receptor tyrosine kinase(s) that phosphorylate Met/Tai in response to JH and thus indirectly affect the canonical JH signaling pathway has been strongly suggested. Given the importance of JH in insect physiology and the fact that the JH signaling pathway is a major target of insect growth regulators, elucidating the identification and functions of putative JH membrane receptors is of great significance from both basic and applied perspectives.

In the present study, the authors identified candidate receptors for such cell membrane JH receptors, CAD96CA and FGFR1, in the cotton bollworm Helicoverpa armigera.

Strengths:

Their in vitro analyses are conducted thoroughly using multiple methods, which overall supports their claim that these receptors can bind to JH and mediate their non-genomic effects.

Weaknesses:

Results of their in vivo experiments, particularly those of their loss-of-function analyses using CRISPR mutants are still preliminary, and the results rather indicate that these membrane receptors do not have any physiologically significant roles in vivo. More specifically, previous studies in lepidopteran species have clearly and repeatedly shown that precocious metamorphosis is the hallmark phenotype for all JH signaling-deficient larvae. In contrast, the present study showed that Cad96ca and Fgfr1 G0 mutants only showed a slight acceleration in their pupation timing, which is not a typical phenotype one would expect from JH signaling deficiency. This is inconsistent with their working model provided in Figure 6, which indicates that these cell membrane JH receptors promote the canonical JH signaling by phosphorylating Met/Tai.

If the authors argue that this slight acceleration of pupation is indeed a major JH signaling-deficient phenotype in Helicoverpa, they need to provide more data to support their claim by analyzing CRISPR mutants of other genes involved in JH signaling, such as Jhamt and Met. An alternative explanation is that there is functional redundancy between CAD96CA and FGFR1 in mediating phosphorylation of Met/Tai. This possibility can be tested by analyzing double knockouts of these two receptors.

Currently, the validity of their calcium imaging analysis in Figure 5 is also questionable. When performing calcium imaging in cultured cells, it is critically important to treat all the cells at the end of each experiment with a hormone or other chemical reagents that universally induce calcium increase in each particular cell line. Without such positive control, the validity of calcium imaging data remains unknown, and readers cannot properly evaluate their results.

Reviewer #3 (Public Review):

Summary:

In this study, Li et al. identified CAD96CA and FGF1 among 20 receptor tyrosine kinase receptors as mediators of JH signaling. By performing a screen in HaEpi cells with overactivated JH signaling, the authors pinpointed two main RTKs that contribute to the transduction of JH. Using the CRISPR/Cas9 system to generate mutants, the authors confirmed that these RTKs are required for normal JH activation, as precocious pupariation was observed in their absence. Additionally, the authors demonstrated that both CAD96CA and FGF1 exhibit a high affinity for JH, and their activation is necessary for the proper phosphorylation of Tai and Met, transcription factors that promote the transcriptional response. Finally, the authors provided evidence suggesting that the function of CAD96CA and FGF1 as JH receptors is conserved across insects.

Strengths:

The data provided by the authors are convincing and support the main conclusions of the study, providing ample evidence to demonstrate that phosphorylation of the transducers Met and Tai mainly depends on the activity of two RTKs. Additionally, the binding assays conducted by the authors support the function of CAD96CA and FGF1 as membrane receptors of JH. The study's results validate, at least in H. amigera, the predicted existence of membrane receptors for JH.

Weaknesses:

The study has several weaknesses that need to be addressed. Firstly, it is not clear what criteria were used by the authors to discard several other RTKs that were identified as repressors of JH signaling. For example, while NRK and Wsck may not fulfill all the requirements to become JH receptors, other evidence, such as depletion analysis and target gene expression, suggests they are involved in proper JH signaling activation.

Secondly, the expression of the six RTKs, which, when knocked down, were able to revert JH signaling activation, was mainly detected in the last larval stage of H. amigera. However, since JH signaling is active throughout larval development, it is unclear whether these RTKs are completely required for pathway activation or only needed for high activation levels at the last larval stage.<br /> Additionally, the mechanism by which different RTKs exert their functions in a specific manner is not clear. According to the expression profile of the different RTKs, one might expect some redundant role of those receptors. In fact the no reversion of phosphorilation of tai and met upon depletion of Wsck in cells with overactivated JH signalling seems to support this idea.

Nevertheless, and despite the overlapping expression of the different receptors, all RTKs seem to be required for proper pathway activation, even in the case of FGF1 which seems to be only expressed in the midgut. This is an intriguing point unresolved in the study.

Finally, the study does not explain how RTKs with known ligands could also bind JH and contribute to JH signaling activation. in Drosophila, FGF1 is activated by pyramus and thisbe for mesoderm development, while CAD96CA is activated by collagen during wound healing. Now the authors claim that in addition to these ligands, the receptors also bind to JH. However, it is unclear whether these RTKs are activated by JH independently of their known ligands, suggesting a specific binding site for JH, or if they are only induced by JH activation when those ligands are present in a synergistic manner. Alternatively, another explanation could be that the RTK pathways by their known ligands activation may induce certain levels of JH transducer phosphorylation, which, in the presence of JH, contributes to the full pathway activation without JH-RTK binding being necessary.

Reviewer #1 (Public Review):

Summary:

In this study the authors use an elegant set of single-molecule experiments to assess the transcriptional and post-transcriptional regulation of RecB. The question stems from a previous observation from the same lab, that RecB protein levels are low and not induced under DNA damage. The authors first show that recB transcript levels are low and have a short half-life. They further show that RecB levels are likely regulated via translational control. They provide evidence for low noise in RecB protein levels across cells and show that the translation of the mRNA increases under double-strand break conditions. Authors identify Hfq binding sites in the recBCD operon and show that Hfq regulates the levels of RecB protein without changing the mRNA levels. They suggest that RecB translation is directly controlled by Hfq binding to mRNA, as mutating one of the binding sites has a direct effect on RecB protein levels.

Strengths:

The implication of Hfq in regulation of RecB translation is important and suggests mechanisms of cellular response to DNA damage that are beyond the canonically studied mechanisms (such as transcriptional regulation by LexA). Data are clearly presented and the writing is direct and easy to follow. Overall, the study is well-designed and provides novel insights into the regulation of RecB, that is part of the complex required to process break ends.

Weaknesses:

Some key findings need additional support/ clarifications to strengthen the conclusions. These are suggested to the authors.

Reviewer #2 (Public Review):

Summary:

The authors carry out a careful and rigorous quantitative analysis of RecB transcript and protein levels at baseline and in response to DNA damage. Using single-molecule FISH and Halo-tagging in order to achieve sensitive measurements, they provide evidence that enhanced RecB protein levels in response to DNA damage are achieved through a post-transcriptional mechanism mediated by the Sm-like RNA binding protein, Hfq. In terms of biological relevance, the authors suggest that this mechanism provides a way to control the optimum level of RecB expression as both deletion and over-expression are deleterious. In addition, the proposed mechanism provides a new framework for understanding how transcriptional noise can be suppressed at the protein level.

Strengths:

Strengths of the manuscript include the rigorous approaches and orthogonal evidence to support the core conclusions, for example, the evidence that altering either Hhq or its recognition sequence on the RNA similarly enhance the protein to RNA ratio of RecB. The writing is clear and the experiments are well-controlled. The modeling approaches provide essential context to interpret the data, particularly given the small numbers of molecules per cell. The interpretations are careful and well supported.

Weaknesses:

The authors make a compelling case for the biological need to exquisitely control RecB levels, which they suggest is achieved by the pathway they have uncovered and described in this work. However, this conclusion is largely inferred as the authors only investigate the effect on cell survival in response to (high levels of) DNA damage and in response to two perturbations - genetic knock-out or over-expression, both of which are likely more dramatic than the range of expression levels observed in unstimulated and DNA damage conditions.

Reviewer #3 (Public Review):

Summary:

The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.

Strengths:

(1) The manuscript is well-written and easy to understand.<br /> (2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.<br /> (3) The imaging and analysis are carefully performed with necessary controls.

Weaknesses:

The major weaknesses include a lack of mechanistic depth, and part of the conclusions are not fully supported by the data.

(1) Mechanistically, it is still unclear why upon DNA damage, translation level of recB mRNA increases, which makes the story less complete. The authors mention in the Discussion that a moderate (30%) decrease in Hfq protein was observed in previous study, which may explain the loss of translation repression on recB. However, given that this mRNA exists in very low copy number (a few per cell) and that Hfq copy number is on the order of a few hundred to a few thousand, it's unclear how 30% decrease in the protein level should resides a significant change in its regulation of recB mRNA.<br /> (2) Based on the experiment and the model, Hfq regulates translation of recB gene through binding to the RBS of the upstream ptrA gene through translation coupling. In this case, one would expect that the behavior of ptrA gene expression and its response to Hfq regulation would be quite similar to recB. Performing the same measurement on ptrA gene expression in the presence and absence of Hfq would strengthen the conclusion and model.<br /> (3) The authors agree that they cannot exclude the possibility of sRNA being involved in the translation regulation. However, this can be tested by performing the imaging experiments in the presence of Hfq proximal face mutations, which largely disrupt binding of sRNAs.<br /> (4) The data on construct with a long region of Hfq binding site on recB mRNA deleted is less convincing. There is no control to show that removing this sequence region itself has no effect on translation, and the effect is solely due to the lack of Hfq binding. A better experiment would be using a Hfq distal face mutant that is deficient in binding to the ARN motifs.<br /> (5) Ln 249-251: The authors claim that the stability of recB mRNA is not changed in ∆hfq simply based on the steady-state mRNA level. To claim so, the lifetime needs to be measured in the absence of Hfq.<br /> (6) What's the labeling efficiency of Halo-tag? If not 100% labeled, is it considered in the protein number quantification? Is the protein copy number quantification through imaging calibrated by an independent method? Does Halo tag affect the protein translation or degradation?<br /> (7) Upper panel of Fig S8a is redundant as in Fig 5B. Seems that Fig S8d is not described in the text.

Reviewer #1 (Public Review):

I thank the authors for addressing almost all my comments on the previous version of this manuscript, which studies the representation by gender and name origin of authors from Nature and Springer Nature articles in Nature News.

The representation of author identities is an important step towards equality in science, and the authors found that women are underrepresented in news quotes and mentions with respect to the proportion of women authors.

The research is rigorously conducted. It presents relevant questions and compelling answers. The documentation of the data and methods is thoroughly done, and the authors provide the code and data for reproduction.

Reviewer #2 (Public Review):

The authors have done well to address the points raised in my previous review.

The updated version of this manuscript retains the technical competence of the first, but with important changes that make the analysis more legible and results better contextualized. Specifically, the discussion is richer, the interpretation of the results is more nuanced, the terminology is more precise, and issues of clarity related to the methodology and results have been resolved.

Broad caveats remain about the nature of authorship, and who we should expect to be quoted in science journalism. Namely, who is the lead author? Ideally, the corresponding author would be included as well, or else some bibliometric definition of the most senior author on the byline. However, the authors' approach here is certainly adequate, and they did well to incorporate discussion of authorship and the scholarly division of labour in their discussion.

In sum, I find the article greatly improved and a competent analysis into the unequal use of quotations in scientific journalism.

Reviewer #1 (Public Review):

The study offers intriguing insights, yet interpretations warrant caution, as the authors themselves acknowledged in their discussion of limitations.

The observed grid-like neural activity might not signify navigating a social landscape but rather a sensory feature space. The study's design had participants associate each face with a pair of bar lengths, with the purported 'navigation' being merely a response to the morphing of bar graph images. Crucially, the task did not necessitate any social cognitive processing to estimate grid-like activity. When making social decisions in a separate task, it is unclear whether participants were actually traversing a social space mentally or simply recalling the bar graphs linked to each face to calculate decision values. Notably, during the trust game, competence and trustworthiness did not equally influence decision-making (as illustrated by Equation 1), implying the possibility that the space represented may be more perceptual than social in nature.

The existence of a universal brain representation for faces within a social context is still debatable. Participants were not required to form a cognitive map of the six faces based on social traits; they could simply remember each face's trait values. While the study suggests that reaction times correlated with the perceived social distances between faces hint at the creation of internal representations, this phenomenon could occur without a true cognitive map of the face relationships. To convincingly argue for such internal representations in the brain, additional multivariate pattern analysis would be necessary to demonstrate that these are not merely the result of perceptual differences in the bar graphs associated with each face.

Reviewer #3 (Public Review):

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

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

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

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

After revision, the authors now discuss some of this and the limitations and notes that future work is required to address the problem.

Reviewer #1 (Public Review):

Summary:

The study by He et al. investigates the relationship of an increased susceptibility of diabetes patients towards COVID-19. The paper raises the possibility that hyperglycemia-induced cathepsin L maturation could be one of the driving forces in this pathology, suggesting that an increased activity of CTSL leads to accelerated virus infection rates due to an elevated processing of the SARS-CoV-2 spike protein.

In a clinical case-control study, the team found that severity of corona infections was higher in diabetic patients, and their CTSL levels correlated well with the progression of the disease. They further showed an increase in CTSL activity in long term as well as acute hyperglycemia. SARS-CoV-2 increasingly infected cells that were cultured in serum from diabetic patients, the same was observed using high glucose medium. No effect was observed in the medium with increased concentrations of insulin. CTSL knockout abolished the glucose-dependent increase in infection.

Increased glucose levels did not correlate with an increase in CTSL transcription. Rather He et al. could show that high glucose levels led to CTSL translocation from the ER into the lysosome. It was the glucose-dependent processing of the protease to its active form which promoted infection.

Overall, it is a very complete study starting from a clinical observation and ending on the molecular mechanism. A strength is certainly the wide selection of experiments. The clinical study to investigate the effect of glucose on CTSL concentrations in healthy individuals sets the stage for experiments in cell culture, animal models and human tissue. The effect of CTSL knockout cell lines on glucose-induced SARS-CoV2 infection rates are convincing. Finally, the team used a combination of Western blots and confocal microscopy to identify the underlying molecular mechanisms.

The authors keep the diabetic condition at the center of their study and extend on previous knowledge of glucose-induced CTSL activation and their consequences for Covid19 infections. By doing so, they create a novel connection between CTSL involvement in SARS-CoV2 infections and diabetes. This enables novel, public awareness of the susceptibility of diabetes patients to the disease.

Reviewer #2 (Public Review):

Summary:

In this study, the authors hypothesized that individuals with diabetes have elevated blood CTSL levels, which facilitates SARS-CoV-2 infection. The authors conducted in vitro experiments, revealing that elevated glucose levels promote SARS-CoV-2 infection in wild-type cells. In contrast, CTSL knockout cells show reduced susceptibility to high glucose-promoted effects. Additionally, the authors utilized lung tissue samples obtained from both diabetic and non-diabetic patients, along with db/db diabetic and control mice. Their findings indicate that diabetic conditions lead to an elevation in CTSL activity in both human and mice.

Strengths:

The authors have effectively met their research objectives, and their conclusions are supported by the data presented. Their findings suggest that high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum to the lysosome, potentially contributing to diabetic comorbidities and complications.

Weaknesses:

(1) In Figure 1e, the authors measured plasma levels of COVID-19 related proteins, including ACE2, CTSL, and CTSB, in both diabetic and non-diabetic COVID-19 patients. Notably, only CTSL levels exhibited a significant increase in diabetic patients compared to non-diabetic patients, and these levels varied throughout the course of COVID-19. Given that the diabetes groups encompass both male and female patients, it is essential to ascertain whether the authors considered the potential impact of gender on CTSL levels. The diabetes groups comprised a higher percentage of male patients (61.3%) compared to the non-diabetes group, where males constituted only 38.7%.

(2) lines145-149: "The results showed that WT Huh7 cell cultured in high glucose medium exhibited a much higher infective rate than those in low glucose medium. However, CTSL KO Huh7 cells maintained a low infective rate of SARS-CoV-2 regardless of glucose or insulin levels (Fig. 3f-h). Therefore, hyperglycemia enhanced SARS-CoV-2 infection dependent on CTSL." However, this evidence may be insufficient to support the claim that hyperglycemia enhances SARS-CoV-2 infection dependent on CTSL. The human hepatoma cell line Huh7 might not be an ideal model to validate the authors' hypothesis regarding high blood glucose promoting SARS-CoV-2 infection through CTSL.

(3) The Abstract and Introduction sections lack effective organization.

In this revised version of the study, the authors have addressed my concerns by providing additional experiments, references and discussing further the points of controversy. I think that the authors have made improvements to the manuscript.

Reviewer #1 (Public Review):

Summary:

In this study, Liu et al. investigate the signaling pathway that triggers sliding motility in the bacterium B. subtilis in response to subinhibitory concentrations of the antibiotic chloramphenicol. The authors used a genetic approach to identify the master regulator CodY playing a regulatory role in this behavior. They used transcriptional and metabolomic profiling to delineate the spatiotemporal separation of the regulatory networks that define distinct metabolic states related to purine metabolism and pyruvate utilization, which are ultimately responsible for the induction of sliding in response to chloramphenicol. Many readers would be interested to read this work showing how extracellular signals modulate microbial physiology and metabolism.

Strengths:

This work presents numerous technical and conceptual strengths. In the opinion of this referee, the most significant conceptual strength of this work is to (once again) provide evidence that antibiotics are not merely produced by bacteria to eliminate competitors. Bacteria have evolved to respond to their presence and activate a range of physiological responses, which are poorly understood. Understanding these responses is critical to fully understand the evolutionary consequences associated with the use of antibiotics. From a technical standpoint, perhaps the most relevant aspect is the robust phenotypic assay developed by the authors to study sliding motility in the presence of chloramphenicol. This robustness enables genetic work using mutants and performing omics assays to characterize the response to chloramphenicol in detail. Additionally, two sets of results stood out and provided important value to this work. One is the comparison established between the sliding induced by chloramphenicol and the sliding generated in the ΔcodY mutant, to determine the genes and the metabolites (using transcriptomics and metabolomics) specifically associated with the response to chloramphenicol without being part of the general Cody-mediated induction of sliding. The second set of results led the authors to identify precise genes of bacterial metabolism (pdhA) responsible for the sliding phenotype in response to chloramphenicol, and conducted genetic experiments to demonstrate that the pdhA mutant does not respond to the presence of chloramphenicol.

Weaknesses:

This work has three main weaknesses, all related to transcriptomic and metabolomic analyses. Firstly, there is the challenge of understanding the essence of the omics results. This section presents an overwhelming array of genes involved in different metabolic pathways, without an obvious thread to tie these hits together. It is easy to get lost in this section. For instance, one cannot be certain if the hits from one particular metabolic pathway are significant enough to figure out to which degree is this pathway responsible for the sliding phenotype. This section contains a huge diversity of genes and pathways and needs to be streamlined. Related to this, the message of the omics experiments highlights a very close relationship between purine and pyruvate metabolism in sliding motility. However, it is unclear how these metabolic pathways may influence sliding or any other specific bacterial behavior. I do not mean to say that it is not possible, just that the connection/mechanism is missing. The third weakness concerns the omics results that sometimes are in conflict. The authors proposed that this may stem from a division of labor and the coexistence of different subpopulations with different metabolisms within the microbial community. While plausible, other possibilities are equally plausible and should be tested in a revised version of the work.

Reviewer #2 (Public Review):

Summary:

Liu and colleagues describe the transcriptional changes observed during chloramphenicol-induced surface mobility of Bacillus subtilis. Practically, they describe that numerous transcriptional regulatory pathways are influenced by the subinhibitory concentration of a translational inhibitor and some of these regulatory changes might contribute to the induction of sliding. Nevertheless, how such translational stress is translated to induction of sliding remains undetermined. The authors clearly describe their aim (line 457): "Our goal for this study was to gain insight into how B. subtilis mobilizes a colony in response to subinhibitory exposure to translation inhibitors.", this is unfortunately not solved here, only the authors characterize the transcriptional landscape differences.

Strengths:

The very thorough analysis of transcriptional changes in the wild type and codY mutant strains is appreciated, and there are definitely a plethora of changes observed related to several global transcriptional regulators in B. subtilis. I compliment the authors for this very detailed and thorough description of transcriptional changes.

Weaknesses:

While the transcriptional changes are well and carefully described, the discussion practically interprets the correlations as causations. I am not disputing that the authors are not on the correct path with their assumptions, but their conclusions are not supported by direct experimental data, especially on (1) translational stress directly inducing mobility and (2) division of labor.

Major 1:

The authors conclude that their results point towards a putative mechanism, e.g. line 460 "which suggests translation stress is a trigger for colony mobilization"; however, no experiment demonstrates this aspect. The authors do not test ppGpp-related stress (mutants in ppGpp-related genes, or mutating the functional domain of CodY), nor do they directly connect ppGpp levels dynamics with induction of subsequent pathways. Again, I understand that the authors are on the right path to connect these pathways and identify what is causing mobility induction, but no direct data is represented, solely the transcriptional changes, therefore remains slightly descriptive.

The statement in the chapter title (line 474) is not demonstrated directly and should be revised. Similarly, in line 476, the authors claim that their "data supports a model", but "support" would require direct experimental data on this aspect.

The authors even clearly indicate in lines 504-506 that they do not reveal the direct mechanism, but the rest of the discussion delivers statements that do not consider the lack of direct data.

Major 2:

Line 427: "The results are consistent with a division of metabolic labor among cells in the expanding population" - the data shows heterogeneity, but the direct division of labor is not demonstrated.

Line 442: So in this case, the proposed division of labor is disrupted in the codY mutant (no inner localisation), and hence expansion appears, suggesting a lack of a putative division of labor is not necessary for induced mobility. On the contrary, there could be heterogeneous gene expression, division of labor requires demonstration of fitness benefit from such interaction.

Division of labor assumes that a mixture of mutants would complement full sliding dynamics, and this could be easily demonstrated by fluorescent labeled cells that should be organized in a similar fashion to those observed with luciferase reporters (pucA mutant on the outer ring, while pdhA mutant interior colony part). Without such experimental demonstration, the authors can only conclude spatially heterogeneous gene expresstion without clear functional contribution to subinhibitory chrolamphenociol-induced surface mobility.

Again, the authors' statement in line 472 "reveal a regulated, spatiotemporal division of metabolism" is not demonstrated by experiment, but spatial heterogeneity is revealed here.<br /> The statement in the Discussion chapter (line 499) is also not demonstrated by experimental data: "Metabolic coordination enables surface expansion of mobilitzed B. subtilis"

Line 550: while I agree with the authors' statement that these functions work cooperatively as demonstrated by van Gestel and colleagues (2015 PloS Biol), the exploitation of these shared goods is not quantitatively equivalent, see Jautzus et al 2022 ISME J (DOI: 10.1038/s41396-022-01279-8).

In summary: the two major conclusions of the manuscript are unfortunately not demonstrated, the presented transcriptional data delivers suggestions, supported with specific mutants displaying certain phenotypes (lack of mobility induction or constitutive mobility without inducer), but it remains unclear how translational stress induces mobility and whether the transcriptional heterogeneity detected directly contributes to metabolic division of labor.

The authors should present direct evidence on the major concerns: how translational stress induces surface mobility (using ppGpp synthesis and turnover mutants and specific CdoY mutant lacking ppGpp sensing) and whether the metabolic division of labor contributes to induced surface mobility (mixing mutants and following their distribution).

Reviewer #1 (Public Review):

By identifying a loss of function mutant of IQCH in infertile patient, Ruan et al. shows that IQCH is essential for spermiogenesis by generating a knockout mouse model of IQCH. Similar to infertile patient with mutant of IQCH, Iqch knockout mice are characterized by a cracked flagellar axoneme and abnormal mitochondrial structure. Mechanistically, IQCH regulates the expression of RNA-binding proteins (especially HNRPAB), which are indispensable for spermatogenesis.

Although this manuscript contains a potentially interesting piece of work that delineates a mechanism of IQCH that associates with spermatogenesis, this reviewer feels that a number of issues require clarification and re-evaluation for a better understanding of the role of IQCH in spermatogenesis.

Line 251 - 253, "To elucidate the molecular mechanism by which IQCH regulates male fertility, we performed liquid chromatography tandem mass spectrometry (LC‒MS/MS) analysis using mouse sperm lysates and detected 288 interactors of IQCH (Figure 5-source data 1)."

The reviewer had already raised significant concerns regarding the text above, noting that "LC‒MS/MS analysis using mouse sperm lysates" would not identify interactors of IQCH. However, this issue was not addressed in the revised manuscript. In the Methods section detailing LC-MS/MS, the authors stated that it was conducted on "eluates obtained from IP". However, there was no explanation provided on how IP for LC-MS/MS was performed. Additionally, it was unclear whether LC-MS or LC-MS/MS was utilized. The primary concern is that if LC‒MS/MS was conducted for the IP of IQCH, IQCH itself should have been detected in the results; however, as indicated by Figure 5-source data 1, IQCH was not listed.

Reviewer #3 (Public Review):

In this study, Ruan et al. investigate the role of the IQCH gene in spermatogenesis, focusing on its interaction with calmodulin and its regulation of RNA-binding proteins. The authors examined sperm from a male infertility patient with an inherited IQCH mutation as well as Iqch CRISPR knockout mice. The authors found that both human and mouse sperm exhibited structural and morphogenetic defects in multiple structures, leading to reduced fertility in Ichq-knockout male mice. Molecular analyses such as mass spectrometry and immunoprecipitation indicated that RNA-binding proteins are likely targets of IQCH, with the authors focusing on the RNA-binding protein HNRPAB as a critical regulator of testicular mRNAs. The authors used in vitro cell culture models to demonstrate an interaction between IQCH and calmodulin, in addition to showing that this interaction via the IQ motif of IQCH is required for IQCH's function in promoting HNRPAB expression. In sum, the authors concluded that IQCH promotes male fertility by binding to calmodulin and controlling HNRPAB expression to regulate the expression of essential mRNAs for spermatogenesis. These findings provide new insight into molecular mechanisms underlying spermatogenesis and how important factors for sperm morphogenesis and function are regulated.

The strengths of the study include the use of mouse and human samples, which demonstrate a likely relevance of the mouse model to humans; the use of multiple biochemical techniques to address the molecular mechanisms involved; the development of a new CRISPR mouse model; ample controls; and clearly displayed results. Assays are done rigorously and in a quantitative manner. Overall, the claims made by the authors in this manuscript are well-supported by the data provided.

Reviewer #2 (Public Review):

The authors analysed functional MRI recordings of brain activity at rest, using state-of-the-art methods that reveal the diverse ways in which information can be integrated in the brain. In this way, they found brain areas that act as (synergistic) gateways for the 'global workspace', where conscious access to information or cognition would occur, and brain areas that serve as (redundant) broadcasters from the global workspace to the rest of the brain. The results are compelling and are consistent with the already assumed role of several networks and areas within the Global Neuronal Workspace framework. Thus, in a way, this work comes to stress the role of synergy and redundancy as complementary information processing modes, which fulfill different roles in the bigger context of information integration.

In addition, to prove that the identified high-order interactions are relevant to the phenomenon of consciousness, the same analysis was performed in subjects under anesthesia or with disorders of consciousness (DOC), showing that indeed the loss of consciousness is associated with a deficient integration of information within the gateway regions.

Reviewer #3 (Public Review):

The work proposes a model of neural information processing based on a 'synergistic global workspace,' which processes information in three principal steps: a gatekeeping step (information gathering), an information integration step, and finally, a broadcasting step. They provided an interpretation of the reduced human consciousness states in terms of the proposed model of brain information processing, which could be helpful to be implemented in other states of consciousness. The manuscript is well-organized, and the results are important and could be interesting for a broad range of literature, suggesting interesting new ideas for the field to explore.

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, 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 the sites of Pol V redistribution in h1 mutants would significantly enhance the impact of this manuscript. Below I have listed several strengths and a weakness of the manuscript.

Strengths:

- 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 /> - 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 /> - 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.

Weakness:

- The manuscript does not include detection or quantification of Pol V transcripts generated at ectopic sites in the h1 mutant background. Pol V encroachment into heterochromatin in the h1 mutant is indirectly shown by NRPE1-dependent methylation at such ectopic sites.

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:

The main conclusion of the manuscript is that the presence of linker Histone H1 protects Arabidopsis pericentromeric heterochromatic regions and longer transposable elements 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:

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. The manuscript also contains recruitment data for SUVH1 in wild-type and h1 mutant backgrounds.<br /> 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 data clearly show that there is a hierarchy in which DNA-methylation is impacted by presence of H1 while H1 distribution is independent of DNA-methylation.

Weaknesses:

The manuscript is driven by a strong and reasonable hypothesis that absence of H1 results increased access of chromatin binding factors and that this explains how the RdDM machinery is restricted from encroaching heterochromatic regions, which are particularly enriched in H1. Indeed, increased binding of NPRE1 at pericentromeric sites is observed; however, the major DNA-methylation changes at these sites are symmetric and not related to the RdDM pathway. Thus, the authors propose that many factors redistribute, which is again reasonable. The authors show redistribution of SUVH1 and relate their data to a previous report showing redistribution of the PcG machinery in H1 depletion mutants (Teano et al. in Cell reports (Volume 42, Issue 8, 29 August 2023), but the manuscript provides limited mechanistic insight as to why there is a strong increase in heterochromatin symmetric DNA-methylation.

Reviewer #1 (Public Review):

The authors design an automated 24-well Barnes maze with 2 orienting cues inside the maze, then model what strategies the mice use to reach the goal location across multiple days of learning. They consider a set of models and conclude that the animals begin with a large proportion of random choices (choices irrespective of the goal location), which over days of experience becomes a combination of spatial choices (choices targeted around the goal location) and serial choices (successive stepwise choices in a given direction). Moreover, the authors show that after the animal has many days of experience in the maze, they still often began each trial with a random choice, followed by spatial or serial choices.

This study is written concisely and the results are presented concisely. The best fit model provides valuable insight into how the animals solve this task, and therefore offers a quantitative foundation upon which tests of neural mechanisms of the components of the behavioral strategy can be performed. These tests will also benefit from the automated nature of the task.

Reviewer #2 (Public Review):

This paper uses a novel maze design to explore mouse navigation behaviour in an automated analogue of the Barnes maze. A major strength is the novel and clever experimental design which rotates the floor and intramaze cues before the start of each new trial, allowing the previous goal location to become the next starting position. The modelling sampling a Markov chain of navigation strategies is elegant, appropriate and solid, appearing to capture the behavioural data well. This work provides a valuable contribution and I'm excited to see further developments, such as neural correlates of the different strategies and switches between them.

Reviewer #3 (Public Review):

Strength:

The development of an automated Barnes maze allows for more naturalistic and uninterrupted behavior, facilitating the study of spatial learning and memory, as well as the analysis of the brain's neural networks during behavior when combined with neurophysiological techniques. The system's design has been thoughtfully considered, encompassing numerous intricate details. These details include the incorporation of flexible options for selecting start, goal, and proximal landmark positions, the inclusion of a rotating platform to prevent the accumulation of olfactory cues, and careful attention given to atomization, taking into account specific considerations such as the rotation of the maze without causing wire shortage or breakage. When combined with neurophysiological manipulations or recordings, the system provides a powerful tool for studying spatial navigation system.<br /> The behavioral experiment protocols, along with the analysis of animal behavior, are conducted with care, and the development of behavioral modeling to capture the animal's search strategy is thoughtfully executed. It is intriguing to observe how the integration of these innovative stochastic models can elucidate the evolution of mice's search strategy within a variant of the Barnes maze.

Comments on revised version:

The authors have addressed all the points I outlined in the previous round of review, resulting in significant improvements to the manuscript. However, I have one remaining comment. Given the updated inter-animal analysis (Supplementary Figure 8), it appears that male and female mice develop strategies differently across days. Male mice seem to progressively increase their employment of spatial strategy across days, at the expense of the random strategy. Conversely, female mice exhibit both spatial and serial strategies at their highest levels on day 2, with minimal changes observed on the subsequent days.<br /> These findings could alter the interpretation of Figure 5 and the corresponding text in the section "Evolution of search strategy across days".<br /> For instance, this statement on page 6 doesn't hold for female mice: "The spatial strategy was increased across days, ... largely at the expense of the random strategy."

Reviewer #1 (Public Review):

Jiang et al. demonstrated that ablating Neurexins results in alterations to glycinergic transmission and its calcium sensitivity, utilizing a robust experimental system. Specifically, the authors employed rAAV-Cre-EGFP injection around the MNTB in Nrxn1/2/3 triple conditional mice at P0, measuring Glycine receptor-dependent IPSCs from postsynaptic LSO neurons at P13-14. Notably, the authors presented a clear reduction of 60% and 30% in the amplitudes of opto- and electric stimulation-evoked IPSCs, respectively. Additionally, they observed changes in kinetics, alterations in PPR, and sensitivity to lower calcium and the calcium chelator, EGTA, indicating solid evidence for changes in presynaptic properties of glycinergic transmission.

Furthermore, the authors uncovered an unexpected increase in sIPSC frequency without altering amplitude. Although the precise mechanism remains unknown, the authors discussed this complex phenotype by considering various possibilities, including the potential scenario where the augmentation in synapses may result from Nrxn deletion rather than being a causal effect.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Jiang et al., explore the role of neurexins at glycinergic MNTB-LSO synapses. The authors utilize elegant and compelling ex vivo slice electrophysiology to assess how the genetic conditional deletion of Nrxns1-3 impacts inhibitory glycinergic synaptic transmission and found that TKO of neurexins reduced electrically and optically evoked IPSC amplitudes, slowed optically evoked IPSC kinetics and reduced presynaptic release probability. The authors use classic approaches including reduced [Ca2+] in ACSF and EGTA chelation to propose that changes in these evoked properties are likely driven by the loss of calcium channel coupling. Intriguingly, while evoked transmission was impaired, the authors reported that spontaneous IPSC frequency was increased, due to an increase in the number of synapses in LSO. Overall, this manuscript provides important insight into the role of neurexins at the glycinergic MNTB-LSO synapse and further emphasizes the need for continued study of both the non-redundant and redundant roles of neurexins.

The authors have addressed all of my previous concerns.

Reviewer #3 (Public Review):

Summary:

The authors investigate the hypothesis that neurexins serve a crucial role as regulators of the synaptic strength and timing at the glycinergic synapse between neurons of the medial nucleus of the trapezoid body (MNTB) and the lateral superior olivary complex (LSO). It is worth mentioning that LSO neurons are an integration station of the auditory brainstem circuit displaying high reliability and temporal precision. These features are necessary for computing interaural cues to derive sound source location from comparing the intensities of sounds arriving at the two ears. In this context, the authors' findings build up according to the hypothesis first by displaying that neurexins were expressed in the MNTB at varying levels. They followed this up with deletion of all neurexins in the MNTB through the employment of a triple knock-out (TKO). Using electrophysiological recordings in acute brainstem slices of these TKO mice, they gathered solid evidence for the role of neurexins in synaptic transmission at this glycinergic synapse primarily by ensuring tight coupling of Ca2+ channels and vesicular release sites. Additionally, the authors uncovered a connection between the deletion of neurexins and a higher number of glycinergic synapses of TKO mice, for which they provided evidence in the form of immunostainings and related it to electrophysiological data on spontaneous release. Consequently, this investigation expands our knowledge on the molecular regulation of synaptic transmission at glycinergic synapses, as well as on the auditory processing at the level of the brainstem.

Strengths:

The authors demonstrate substantial results in support of the hypothesis of a critical role of neurexins for regulating glycinergic transmission in the LSO using various techniques. They provide evidence for the expression of neurexins in the MNTB and consecutively successfully generate and characterize the neurexin TKO. For their study on LSO IPSCs the authors transduced MNTB neurons by co-injection of virus carrying Cre and ChR2 and subsequently optogenetically evoke release of glycine. As a result, they observed a significant reduction in amplitude and significantly slower rise and decay times of the IPSCs of the TKO in comparison with control mice in which MNTB neurons were only transduced with ChR2. Furthermore, they observed an increased paired pulse ratio (PPR) of LSO IPSCs in the TKO mice, indicating lower release probability. Elaborating on the hypothesis that neurexins are essential for the coupling of synaptic vesicles to Ca2+ channels, the authors show lowered Ca2+ sensitivity in the TKO mice. Additionally, they reveal convincing evidence for the connection between the increased frequency of spontaneous IPSC and the higher number of glycinergic synapses of the LSO in the TKO mice, revealed by immunolabeling against the glycinergic presynaptic markers GlyT2 or VGAT.

Weaknesses:

A concern is on novelty as this work on the effects of pan-neurexin deletion in a glycinergic synapse is quite consistent with the authors prior work on glutamatergic synapses (Luo et al., 2020).

Reviewer #3 (Public Review):

This study demonstrated the application of OPM-MEG in neurodevelopment studies of somatosensory beta oscillations and connections with children as young as 2 years old. It provides a new functional neuroimaging method which has high spatial-temporal resolution as well wearable which makes it a new useful tool for studies in young children. They have constructed a 192-channel wearable OPM-MEG system includes field compensation coils which allows free head movement scanning with relatively high ratio of usable trials. Beta band oscillations during somatosensory tasks are well localized and the modulation with age are found in the amplitude, connectivity, and pan-spectral burst probability. It is demonstrated that the wearable OPM-MEG could be used in children as a quite practical and easy to deploy neuroimaging method with performance as good as conventional MEG. With both good spatial (several millimeter) and temporal (milliseconds) resolution, it provides a novel and powerful technology to neurodevelopment research and clinical application not limited to somatosensory areas.

The conclusions of this paper are mostly well supported by data acquired under proper method.

Reviewer #1 (Public Review):

Summary:

Chartampila et al. describe the effect of early-life choline supplementation on cognitive functions and epileptic activity in a mouse model of Alzheimer's disease. The cognitive abilities were assessed by the novel object recognition test and the novel object location test, performed in the same cohort of mice at 3 months and 6 months of age. Neuronal loss was tested using NeuN immunoreactivity, and neuronal hyperexcitability was examined using FosB and video-EEG recordings, providing multi-level correlations between these different parameters.

Strengths:

The study was designed as a 6-month follow-up, with repeated behavioral and EEG measurements through disease development and multilevel correlations providing valuable and interesting findings on AD progression and the effect of early-life choline supplementation. Moreover, the behavioral data that suggest an adverse effect of low choline in WT mice are interesting and important also beyond the context of AD, highlighting the dramatic effect of diet on the phenotypes of animal models.

Weaknesses:

The readability could be improved.

Reviewer #2 (Public Review):

Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.

(1) The conclusions of the paper are mostly supported by the data and in the revised manuscript clarification is provided concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3 and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. The revised manuscript more clearly indicates for each individual experiment which form is used. However, a discussion on the potential effects of the modifications on CCL5 in the results and discussion sections is still missing.<br /> (2) In general, authors used high concentrations of CCL5 in their experiments. In their reply to the comments they indicate that at lower CCL5 concentrations no LLPS is detected. This is important information since it may indicate the need for chemokine oligomerization for LLPS. This info should be added to the manuscript and comparison with for instance the obligate monomer CCL7 and another chemokine such as CXCL4 that easily forms oligomers may clarify whether LLPS is controlled by oligomerization.<br /> (3) Statistical analyses have been improved in the revised manuscript.

Reviewer #1 (Public Review):

The authors perform RNA-seq on FACS isolated neurons from adult worms at days 1 and 8 of adulthood to profile the gene expression changes that occur with cognitive decline. Supporting data are included indicating that by day 7 of adulthood, learning and memory are reduced, indicating that this timepoint or after represents cognitively aged worms. Neuronal identity genes are reduced in expression within the cognitively aged worms, whereas genes involved in proteostasis, transcription/chromatin, and the stress response are elevated. A number of specific examples are provided, representing markers of specific neuronal subtypes, and correlating expression changes to the erosion of particular functions (e.g. motor neurons, chemosensory neurons, aversive learning neurons, etc).

To investigate whether upregulation of genes in neurons with age is compensatory or deleterious, the authors reduced expression of a set of three significantly upregulated genes and performed behavioral assays in young adults. In each case, reduction of expression improved memory, consistent with a model in which age-associated increases impair neuronal function.

The authors then characterize learning and memory in wild type, daf-2, and daf-2/daf-16 worms with age and find that daf-2 worms have an extended ability to learn for approximately 10 days longer that wild types. This was daf-16 dependent. Memory was extended in daf-2 as well, and strikingly, daf-2;daf-16 had no short term memory even at day 1. Transcriptomic analysis of FACS-sorted neurons was performed on the three groups at day 8. The authors focus their analysis on daf-2 vs. daf-2;daf-16 and present evidence that daf-2 neurons express a stress-resistance gene program. They also find small differences between the N2 and daf-2;daf-16 neurons, which correlate with the observed behavioral differences, though these differences are modest.

The authors tested eight candidate genes that were more highly expressed in daf-2 neurons vs. daf-2;daf-16 and showed that reduction of 2 and 5 of these genes impaired learning and memory, respectively, in daf-2 worms. This finding implicates specific neuronal transcriptional targets of IIS in maintaining cognitive ability in daf-2 with age, which, importantly, are distinct from those in young wild type worms.

Overall, this is a strong study with rigorously performed experiments. The authors achieved their aim of identifying transcriptional changes in neurons that underlie loss of learning and memory in C. elegans, and how cognition is maintained in insulin/IGF-1-like signaling mutants.

Reviewer #2 (Public Review):

Weng et al. perform a comprehensive study of gene expression changes in young and old animals, in wild-type and daf-2 insulin receptor mutants, in the whole animal and specifically in the nervous system. Using this data, they identify gene families that are correlated with neuronal ageing, as well as a distinct set of genes that are upregulated in neurons of aged daf-2 mutants. This is particularly interesting as daf-2 mutants show both extended lifespan and healthier neurons in aged animals, reflected by better learning/memory in older animals compared with wild-type controls. Indeed, knockdown of several of these upregulated genes resulted in poorer learning and memory. In addition, the authors showed that several genes upregulated during ageing in wild-type neurons also contribute to learning and memory; specifically, knockdown of these genes in young animals resulted in improved memory. This indicates that (at least in this small number of cases), genes that show increased transcript levels with age in the nervous system somehow suppress memory, potentially by having damaging effects on neuronal health.

Finally, from a resource perspective, the neuronal transcriptome provided here will be very useful for C. elegans researchers as it adds to other existing datasets by providing the transcriptome of older animals (animals at day 8 of adulthood) and demonstrating the benefits of performing tissue-specific RNAseq instead of whole-animal sequencing.

The work presented here is of high quality and the authors present convincing evidence supporting their conclusions. I only have a few comments/suggestions:

(1) Do the genes identified to decrease learning/memory capacity in daf-2 animals (Figure 4d/e) also impact neuronal health? daf-2 mutant worms show delayed onset of age-related changes to neuron structure (Tank et al., 2011, J Neurosci). Does knockdown of the genes shown to affect learning also affect neuron structure during ageing, potentially one mechanism through which they modulate learning/memory?

(2) The learning and memory assay data presented in this study uses the butanone olfactory learning paradigm, which is well established by the same group. Have the authors tried other learning assays when testing for learning/memory changes after knockdown of candidate genes? Depending on the expression pattern of these genes, they may have more or less of an effect on olfactory learning versus for e.g. gustatory or mechanosensory-based learning.

(3) A comment on the 'compensatory vs dysregulatory' model as stated by the authors on page 7 - I understand that this model presents the two main options, but perhaps this is slightly too simplistic: gene expression that rises during ageing may be detrimental for memory (= dysregulatory), but at the same time may also be beneficial other physiological roles in other tissues (=compensatory).

Comments on revised version:

I am satisfied with how the authors have addressed all my comments/suggestions.

Reviewer #3 (Public Review):

Summary

In this manuscript, Weng et al. identify the neuron specific transcriptome that impacts age dependent cognitive decline. The authors design a pipeline to profile neurons from wild type and long-lived insulin receptor/IGF-1 mutants using timepoints when memory functions are declining. They discover signatures unique to neurons which validates their approach. The authors identify that genes related to neuronal identity are lost with age in wild type worms. For example, old neurons reduce the expression of genes linked to synaptic function and neuropeptide signaling and increase the expression of chromatin regulators, insulin peptides and glycoproteins. Depletion of selected genes which are upregulated in old neurons (utx-1, ins-19 and nmgp-1) leads to improved short memory function. This indicates that some genes that increase with age have detrimental effects on learning and memory. The pipeline is then used to test neuronal profiles of long-lived insulin/IGF-1 daf-2 mutants. Genes related to stress response pathways are upregulated in long lived daf-2 mutants (e.g. dod-24, F08H9.4) and those genes are required for improved neuron function.

Strengths

The manuscript is well written, and the experiments are well described. The authors take great care to explain their reasoning for performing experiments in a specific way and guide the reader through the interpretation of the results, which makes this manuscript an enjoyable and interesting read. The authors discover novel regulators of learning and memory using neuron-specific transcriptomic analysis in aged animals, which underlines the importance of cell specific deep sequencing. The timepoints of the transcriptomic profiling are elegantly chosen, as they coincide with the loss of memory and can be used to specifically reveal gene expression profiles related to neuron function. The authors discuss on the dod-24 example how powerful this approach is. In daf-2 mutants whole-body dod-24 expression differs from neuron specific profiles, which underlines the importance of precise cell specific approaches. This dataset will provide a very useful resource for the C. elegans and aging community as it complements existing datasets with additional time points and neuron specific deep profiling.

Weakness

This study nicely describes the neuron specific profiles of aged long-lived daf-2 mutants. Selected neuronal genes that were upregulated in daf-2 mutants (e.g. F08H9.4, mtl-1, dod-24, alh-2, C44B7.5) decreased learning/memory when knocked down. However, the knock down of these genes was not specific to neurons. The authors use a neuron-sensitive RNAi strain to address this concern and acknowledge this caveat in the text. While it is likely that selected candidates act only in neurons it is possible that other tissues participate as well.

Reviewer #1 (Public Review):

Summary:

The authors utiilze the model organism C. elegans to interrogate cell non-autonomous signaling between GABAergic neurons and somatic tissues. They demonstrate that RNAi of isp-1 or spg-7 in GABAergic neurons leads to lifespan extension and improved healthspan (by resistance to paraquat or heat stress), which are dependent on the transcription factor daf-16/FOXO3a.

Strengths:

The authors are clear and straightforward in their study. They examine the healthspan of C. elegans at days 3, 6, and 9 to give a wide perspective on how the phenotypes changes with aging. They use two methods to specifically knockdown isp-1 or spg-7 in GABAergic neurons: (1) a previously published rde-1 mutant that has rde-1 and sid-1 restored only in GABAergic neurons and (2) a novel model uses a sid-1 mutant that makes dsRNA of isp-1 or spg-7 in GABAergic neurons. They use multiple methods to examine healthspan. They identified daf-16/FOXO3a as the mechanism of their phenotype and ruled out other transcription factors. The authors do not use FUdR in their studies, which is known to confound experiments.

Weaknesses:

(1) Incomplete validation of GABAergic knockdown. The study relies on the specific knockdown of isp-1 or spg-7 in GABAergic neurons, but in the opinion of this reviewer, the authors do not adequately validate their models to demonstrate GABAergic specificity. For the previously published rde-1 mutant model, a simple validation of specific knockdown of GFP in GFP-labeled GABAergic neurons should be included. They should also show that GFP RNAi would not be effective in knocking down intestinal GFP, for example.

Their second model is poorly explained and not validated and this reviewer could not find similar previously published models of its kind. This model claims that dsRNA of isp-1 was made in the GABAergic neurons of a sid-1 mutant, but no evidence is shown to support this claim. The authors point to changes in phenotypes such as lifespan extension and reduced lipofuscin in the intestines as proof that knockdown is occurring in the GABAergic neurons, but this is indirect evidence. Rigorous validation of this model is needed, especially if it is the first model of its kind.

(2) Lifespan. The control lifespans using the rde-1 mutants are very short-lived and no explanation for this is provided (eg. Figure 1D, E). The authors use two RNAis in their lifespan with daf-16 and isp-1. For their controls, they should use empty vector mixed with isp-1, not only isp-1 RNAi.

(3) Cell non-autonomous effects. The claims that GABAergic mitochondrial dysfunction have effects on somatic tissues is weak. More specific tests on somatic stress resistance are warranted for their claims. Better quality images of intestinal mitochondria are needed. Examining additional tissues, such as muscle, would also strengthen their claims. For example, they could examine muscle mitochondria and determine if muscle strength is improved in their models.

(4) Dependence on daf-16/FOXO3a. The authors show that loss of daf-16 reverses the lifespan and healthspan effects in their model. Next, they show that loss of daf-16 reverses the effects of isp-1 in the intestines and in the germline. However, they only show the daf-16 mutant data and not the positive control (EV and isp-1 alone), which should be included. Furthermore, the phenotypes they examine are only a subset of somatic phenotypes, and this reviewer would be more convinced with the additional controls and with more parameters examined.

Reviewer #2 (Public Review):

Summary:

In this work, the authors show that GABAergic neurons play a role in sensing mitochondrial stress and regulating organismal aging. Thus, disrupting the mitochondrial mitochondria function in GABAergic neurons induces resistance to thermal and paraquat stresses, promotes longevity, and affects reproduction. This mechanism is regulated by the iron-sulfur subunit of complex III of the mitochondrial electron transport chain, ISP-1, and a mitochondrial quality control m-AAA protease, SPG-7, which in turn requires DAF-16/FoxO activity in GABAergic neurons.

Strengths:

A strength of this work is that the authors identify the specific site where mitochondrial stress promotes health and longevity, i.e., GABAergic neurons. In addition, the paper corroborates the findings with the appropriate experiments. How neuronal regulation of mitochondrial function impacts systemic health and aging is of interest to cell biology and neuroscience fields.

Weaknesses:

The entire paper is based on tissue-specific RNAi in GABAergic neurons, which was achieved using two different conditions of RNAi (although not for all experiments). However, multiple studies have shown deficiencies in the tissue-specific RNAi in C. elegans, especially for the rde-1(ne219) mutant used in this study. Therefore, it is necessary to repeat critical experiments by rescuing the isp-1 or spg-7 mutants in GABAergic neurons. Additionally, it is clear in the paper that perturbing mitochondrial function requires DAF-16/FoxO activity in GABAergic neurons to promote longevity, yet the downstream cellular pathways are not described.

Reviewer #3 (Public Review):

Summary:

This manuscript describes RNAi depletion of isp-1 or spg-7 in the GABAergic neurons of C. elegans leads to: lifespan extension; increased resistance to paraquat oxidative stress and heat stress; decreased brood size and mitotic germ cell numbers in the gonad and increased DNA aggregates in the oocytes; increased mitochondrial membrane potential, ATP levels, mitochondrial mass, mitochondrial DNA copies, mitochondrial DNA polymerase gamma polg-1 levels, and decreased ROS levels. The authors further show that daf-16 is necessary for GABAergic depletion of isp-1 mediated lifespan extension, stress resistance, increased mitochondrial membrane potential, mitochondrial mass and DNA copies, and decreased brood size. Unc-25 for GABA synthesis, unc-31 for neuropeptide secretion, and flp-13 neuropeptide are all in the same pathway of isp-1 RNAi in GABAergic neurons for lifespan extension and stress resistance.

Strengths:

The topic is interesting and relatively novel in terms of GABAergic mitochondrial dysfunction. The data provided support the conclusions well.

Weaknesses:

The mechanistic evidence needs to be improved substantially.

Reviewer #1 (Public Review)

Summary:

In this study, Xie and colleagues aimed to explore the function and potential mechanisms of the gut microbiota in a hamster model of severe leptospirosis. The results demonstrated that Leptospira infection was able to cause intestine damage and inflammation. Leptospira infection promoted an expansion of Proteobacteria, increased gut barrier permeability, and elevated LPS levels in the serum. Thus, they proposed an LPS-neutralization therapy which improved the survival rate of moribund hamsters combined with antibody therapy or antibiotic therapy.

Strengths:

The work is well-designed and the story are interesting to me. The gut microbiota is essential for immunity and systemic health. Many life-threatening pathogens, such as SARS-CoV-2 and other gut-damaged infection, have the potential to disrupt the gut microbiota in the later stages of infection, causing some harmful gut microbiota-derived substances to enter the bloodstream. It is emphasized that in addition to exogenous pathogenic pathogens, harmful substances of intestinal origin should also be considered in critically ill patients.

Reviewer #2 (Public Review):

Severe leptospirosis in humans and some mammals often meet death in the endpoint. In this article, authors explored the role of the gut microbiota in severe leptospirosis. They found that Leptospira infection promoted a dysbiotic gut microbiota with an expansion of Proteobacteria and LPS neutralization therapy synergized with antileptospiral therapy significantly improved the survival rates in severe leptospirosis. This study is well-organized and has potentially important clinical implications not only for severe leptospirosis but also for other gut-damaged infections.

Reviewer #3 (Public Review):

Summary:

This is a well prepared manuscript which presented interesting research result.

Strengths:

The omics method produced unbiased results.

Weaknesses:

LPS neutralization is not new method for treating leptospiral infection.

Reviewer #1 (Public Review):

Spikol et al. investigate the roles of two distinct populations of neurons in the nucleus incertus (NI). The authors established two new transgenic lines that label gsc2- and rln3a-expressing neurons. They show that the gsc2+ and rln3a+ NI neurons show divergent projection patterns and project to different parts of the interpeduncular nucleus (IPN), which receive inputs from the habenula (Hb). Furthermore, calcium imaging shows that gsc2 neurons are activated by the optogenetic activation of the dorsal Hb-IPN and respond to aversive electric shock stimuli, while rln3a neurons are highly spontaneously active. The ablation of rln3a neurons, but not gsc2 neurons, alters locomotor activity of zebrafish larvae.

The strength of the paper is their genetic approach that enabled the authors to characterize many different features of the two genetically targeted populations in the NI. These two neuronal populations are anatomically closely apposed and would have been indistinguishable without their genetic tools. Their analyses provide valuable information on the diverse anatomical, physiological and behavioral functions of the different NI subtypes. On the other hand, these pieces of evidence are loosely linked with each other to reach a mechanistic understanding of how the NI works in a circuit. For example, the anatomical study revealed the connections from the NI to the IPN, while the optogenetic mapping experiments investigate the other way around, i.e. the connection from the IPN to the NI.

Reviewer #3 (Public Review):

This study uses a range of methods to characterize heterogeneous neural populations within the nucleus incertus (NI). The authors focus on two major populations, expressing gsc2 and rln3a, and present convincing evidence that these cells have different patterns of connectivity, calcium activity and effects on behavior. Although the study does not go as far as clarifying the role of NI in any specific neural computation or aspect of behavioral control, the findings will be valuable in support of future endeavors to do so. In particular, the authors have made two beautiful knock-in lines that recapitulate endogenous expression pattern of gsc2 and rln3a which will be a powerful tool to study the roles of the relevant NI cells. Experiments are well done, data are high quality and most claims are well supported. In this revised version, the authors have added additional analysis that has clarified their results and strengthened some of the claims.

Two points of note:

• The data very clearly show different patterns of neurites for gsc2 and rln3a neurons in the IPN and the authors interpret these are being axonal arbors. However, they do not rule out the possibility that some of the processes might be dendritic in nature. Of relevance to this point, they cite a recent study (Petrucco et al. 2023) that confirmed that, as in other species, tegmental neurons in zebrafish extend spatially segregated dendritic as well as axonal arbors into IPN, and the authors speculate that these GABAergic tegmental cells might in fact be part of NI.

• Although the gsc2 and rln3a populations show differences in calcium activity, there is not as clear a dichotomy as stated in the abstract. For example, both populations clearly respond to electric shocks, albeit with different response time courses.

Reviewer #4 (Public Review):

Summary:

In the present study, Spikol et al. explore the projection patterns and functional characteristics of two distinct and genetically defined populations in the larval zebrafish Nucleus Incertus (NI), expressing the transcription factor gsc2 or the neuropeptide rln3a. To label in vivo these neurons two transgenic lines were generated by CRISPR/Cas9 mediated Knock-in. These genetic tools allowed the analysis of the projection patterns of these neuronal populations showing that the NI neurons expressing gsc2 and rln3a exhibit markedly different projection patterns, targeting separate subregions within the midbrain interpeduncular nucleus (IPN).<br /> Functional imaging and behavioral analysis revealed that while gsc2 neurons respond to electric shock stimuli, rln3a neurons show high spontaneous activity and play a role in regulating locomotor activity.

Strengths:

The paper relies on a series of rigorous experimental approaches including molecular genetic, neuroanatomical, functional and behavioral analysis. The resources generated including the two knock-in transgenic reporter lines will be of great value for the zebrafish neurobiology community as well as inspire further studies of the NI in other model systems.

Weaknesses:

Technical weaknesses present in the first version of the manuscript have largely been addressed in the present revision.

Reviewer #1 (Public Review):

Summary:

The authors define a new metric for visual displays, derived from psychophysical response times, called visual homogeneity (VH). They attempt to show that VH is explanatory of response times across multiple visual tasks. They use fMRI to find visual cortex regions with VH-correlated activity. On this basis, they declare a new visual region in human brain, area VH, whose purpose is to represent VH for the purpose of visual search and symmetry tasks.

Strengths:

The authors present carefully designed experiments, combining multiple types of visual judgments and multiple types of visual stimuli with concurrent fMRI measurements. This is a rich dataset with many possibilities for analysis and interpretation.

Weaknesses:

The datasets presented here should provide a rich basis for analysis. However, in this version of the manuscript, I believe that there are major problems with the logic underlying the authors' new theory of visual homogeneity (VH), with the specific methods they used to calculate VH, and with their interpretation of psychophysical results using these methods. These problems with the coherency of VH as a theoretical construct and metric value make it hard to interpret the fMRI results based on searchlight analysis of neural activity correlated with VH. In addition, the large regions of VH correlations identified in Experiments 1 and 2 vs. Experiments 3 and 4 are barely overlapping. This undermines the claim that VH is a universal quantity, represented in a newly discovered area of visual cortex, that underlies a wide variety of visual tasks and functions.

Maybe I have missed something, or there is some flaw in my logic. But, absent that, I think the authors should radically reconsider their theory, analyses, and interpretations, in light of detailed comments below, in order to make the best use of their extensive and valuable datasets combining behavior and fMRI. I think doing so could lead to a much more coherent and convincing paper, albeit possibly supporting less novel conclusions.

THEORY AND ANALYSIS OF VH

(1) VH is an unnecessary, complex proxy for response time and target-distractor similarity.

VH is defined as a novel visual quality, calculable for both arrays of objects (as studied in Experiments 1-3) and individual objects (as studied in Experiment 4). It is derived from a center-to-distance calculation in a perceptual space. That space in turn is derived from multi-dimensional scaling of response times for target-distractor pairs in an oddball detection task (Experiments 1 and 2) or in a same different task (Experiments 3 and 4). Proximity of objects in the space is inversely proportional to response times for arrays in which they were paired. These response times are higher for more similar objects. Hence, proximity is proportional to similarity. This is visible in Fig. 2B as the close clustering of complex, confusable animal shapes.

VH, i.e. distance-to-center, for target-present arrays is calculated as shown in Fig. 1C, based on a point on the line connecting target and distractors. The authors justify this idea with previous findings that responses to multiple stimuli are an average of responses to the constituent individual stimuli. The distance of the connecting line to the center is inversely proportional to the distance between the two stimuli in the pair, as shown in Fig. 2D. As a result, VH is inversely proportional to distance between the stimuli and thus to stimulus similarity and response times. But this just makes VH a highly derived, unnecessarily complex proxy for target-distractor similarity and response time. The original response times on which the perceptual space is based are far more simple and direct measures of similarity for predicting response times.

(2) The use of VH derived from Experiment 1 to predict response times in Experiment 2 is circular and does not validate the VH theory.

The use of VH, a response time proxy, to predict response times in other, similar tasks, using the same stimuli, is circular. In effect, response times are being used to predict response times across two similar experiments using the same stimuli. Experiment 1 and the target present condition of Experiment 2 involve the same essential task of oddball detection. The results of Experiment 1 are converted into VH values as described above, and these are used to predict response times in experiment 2 (Fig. 2F). Since VH is a derived proxy for response values in Experiment 1, this prediction is circular, and the observed correlation shows only consistency between two oddball detection tasks in two experiments using the same stimuli.

(3) The negative correlation of target-absent response times with VH as it is defined for target-absent arrays, based on distance of a single stimulus from center, is uninterpretable without understanding the effects of center-fitting. Most likely, center-fitting and the different VH metric for target-absent trials produce an inverse correlation of VH with target-distractor similarity.

The construction of the VH perceptual space also involves fitting a "center" point such that distances to center predict response times as closely as possible. The effect of this fitting process on distance-to-center values for individual objects or clusters of objects is unknowable from what is presented here. These effects would depend on the residual errors after fitting response times with the connecting line distances. The center point location and its effects on distance-to-center of single objects and object clusters are not discussed or reported here.

Yet, this uninterpretable distance-to-center of single objects is chosen as the metric for VH of target-absent displays (VHabsent). This is justified by the idea that arrays of a single stimulus will produce an average response equal to one stimulus of the same kind. But it is not logically clear why response strength to a stimulus should be a metric for homogeneity of arrays constructed from that stimulus, or even what homogeneity could mean for a single stimulus from this set. And it is not clear how this VHabsent metric based on single stimuli can be equated to the connecting line VH metric for stimulus pairs, i.e. VHpresent, or how both could be plotted on a single continuum.

It is clear, however, what *should* be correlated with difficulty and response time in the target-absent trials, and that is the complexity of the stimuli and the numerosity of similar distractors in the overall stimulus set. Complexity of the target, similarity with potential distractors, and number of such similar distractors all make ruling out distractor presence more difficult. The correlation seen in Fig. 2G must reflect these kinds of effects, with higher response times for complex animal shapes with lots of similar distractors and lower response times for simpler round shapes with fewer similar distractors.

The example points in Fig. 2G seem to bear this out, with higher response times for the deer stimulus (complex, many close distractors in the Fig. 2B perceptual space) and lower response times for the coffee cup (simple, few close distractors in the perceptual space). While the meaning of the VH scale in Fig. 2G, and its relationship to the scale in Fig. 2F, are unknown, it seems like the Fig. 2G scale has an inverse relationship to stimulus complexity, in contrast to the expected positive relationship for Fig. 2F. This is presumably what creates the observed negative correlation in Fig. 2G.

Taken together, points 1-3 suggest that VHpresent and VHabsent are complex, unnecessary, and disconnected metrics for understanding target detection response times. The standard, simple explanation should stand. Task difficulty and response time in target detection tasks, in both present and absent trials, are positively correlated with target-distractor similarity.

I think my interpretations apply to Experiments 3 and 4 as well, although I find the analysis in Fig. 4 especially hard to understand. The VH space in this case is based on Experiment 3 oddball detection in a stimulus set that included both symmetric and asymmetric objects. But the response times for a very different task in Experiment 4, a symmetric/asymmetric judgment, are plotted against the axes derived from Experiment 3 (Fig. 4F and 4G). It is not clear to me why a measure based on oddball detection that requires no use of symmetry information should be predictive of within-stimulus symmetry detection response times. If it is, that requires a theoretical explanation not provided here.

(4) Contrary to the VH theory, same/different tasks are unlikely to depend on a decision boundary in the middle of a similarity or homogeneity continuum.

The authors interpret the inverse relationship of response times with VHpresent and VHabsent, described above, as evidence for their theory. They hypothesize, in Fig. 1G, that VHpresent and VHabsent occupy a single scale, with maximum VHpresent falling at the same point as minimum VHabsent. This is not borne out by their analysis, since the VHpresent and VHabsent value scales are mainly overlapping, not only in Experiments 1 and 2 but also in Experiments 3 and 4. The authors dismiss this problem by saying that their analyses are a first pass that will require future refinement. Instead, the failure to conform to this basic part of the theory should be a red flag calling for revision of the theory.

The reason for this single scale is that the authors think of target detection as a boundary decision task, along a single scale, with a decision boundary somewhere in the middle, separating present and absent. This model makes sense for decision dimensions or spaces where there are two categories (right/left motion; cats vs. dogs), separated by an inherent boundary (equal left/right motion; training-defined cat/dog boundary). In these cases, there is less information near the boundary, leading to reduced speed/accuracy and producing a pattern like that shown in Fig. 1G.

This logic does not hold for target detection tasks. There is no inherent middle point boundary between target present and target absent. Instead, in both types of trial, maximum information is present when target and distractors are most dissimilar, and minimum information is present when target and distractors are most similar. The point of greatest similarity occurs at then limit of any metric for similarity. Correspondingly, there is no middle point dip in information that would produce greater difficulty and higher response times. Instead, task difficulty and response times increase monotonically with similarity between targets and distractors, for both target present and target absent decisions. Thus, in Figs. 2F and 2G, response times appear to be highest for animals, which share the largest numbers of closely similar distractors.

DEFINITION OF AREA VH USING fMRI

(1) The area VH boundaries from different experiments are nearly completely non-overlapping.

In line with their theory that VH is a single continuum with a decision boundary somewhere in the middle, the authors use fMRI searchlight to find an area whose responses positively correlate with homogeneity, as calculated across all of their target present and target absent arrays. They report VH-correlated activity in regions anterior to LO. However, the VH defined by symmetry Experiments 3 and 4 (VHsymmetry) is substantially anterior to LO, while the VH defined by target detection Experiments 1 and 2 (VHdetection) is almost immediately adjacent to LO. Fig. S13 shows that VHsymmetry and VHdetection are nearly non-overlapping. This is a fundamental problem with the claim of discovering a new area that represents a new quantity that explains response times across multiple visual tasks. In addition, it is hard to understand why VHsymmetry does not show up in a straightforward subtraction between symmetric and asymmetric objects, which should show a clear difference in homogeneity.

(2) It is hard to understand how neural responses can be correlated with both VHpresent and VHabsent.

The main paper results for VHdetection are based on both target-present and target-absent trials, considered together. It is hard to interpret the observed correlations, since the VHpresent and VHabsent metrics are calculated in such different ways and have opposite correlations with target similarity, task difficulty, and response times (see above). It may be that one or the other dominates the observed correlations. It would be clarifying to analyze correlations for target-present and target-absent trials separately, to see if they are both positive and correlated with each other.

(3) Definition of the boundaries and purpose of a new visual area in the brain requires circumspection, abundant and convergent evidence, and careful controls.

Even if the VH metric, as defined and calculated by the authors here, is a meaningful quantity, it is a bold claim that a large cortical area just anterior to LO is devoted to calculating this metric as its major task. Vision involves much more than target detection and symmetry detection. Cortex anterior to LO is bound to perform a much wider range of visual functionalities. If the reported correlations can be clarified and supported, it would be more circumspect to treat them as one byproduct of unknown visual processing in cortex anterior to LO, rather than treating them as the defining purpose for a large area of visual cortex.

Reviewer #3 (Public Review):

Summary:

This study proposes visual homogeneity as a novel visual property that enables observers perform to several seemingly disparate visual tasks, such as finding an odd item, deciding if two items are same, or judging if an object is symmetric. In Exp 1, the reaction times on several objects were measured in human subjects. In Exp 2, visual homogeneity of each object was calculated based on the reaction time data. The visual homogeneity scores predicted reaction times. This value was also correlated with the BOLD signals in a specific region anterior to LO. Similar methods were used to analyze reaction time and fMRI data in a symmetry detection task. It is concluded that visual homogeneity is an important feature that enables observers to solve these two tasks.

Strengths:

(1) The writing is very clear. The presentation of the study is informative.<br /> (2) This study includes several behavioral and fMRI experiments. I appreciate the scientific rigor of the authors.

Weaknesses:

(1) My main concern with this paper is the way visual homogeneity is computed. On page 10, lines 188-192, it says: "we then asked if there is any point in this multidimensional representation such that distances from this point to the target-present and target-absent response vectors can accurately predict the target-present and target-absent response times with a positive and negative correlation respectively (see Methods)". This is also true for the symmetry detection task. If I understand correctly, the reference point in this perceptual space was found by deliberating satisfying the negative and positive correlations in response times. And then on page 10, lines 200-205, it shows that the positive and negative correlations actually exist. This logic is confusing. The positive and negative correlations emerge only because this method is optimized to do so. It seems more reasonable to identify the reference point of this perceptual space independently, without using the reaction time data. Otherwise, the inference process sounds circular. A simple way is to just use the mean point of all objects in Exp 1, without any optimization towards reaction time data.

(2) Visual homogeneity (at least given the current from) is an unnecessary term. It is similar to distractor heterogeneity/distractor variability/distractor statics in literature. However, the authors attempt to claim it as a novel concept. The title is "visual homogeneity computations in the brain enable solving generic visual tasks". The last sentence of the abstract is "a NOVEL IMAGE PROPERTY, visual homogeneity, is encoded in a localized brain region, to solve generic visual tasks". In the significance, it is mentioned that "we show that these tasks can be solved using a simple property WE DEFINE as visual homogeneity". If the authors agree that visual homogeneity is not new, I suggest a complete rewrite of the title, abstract, significance, and introduction.

(3) Also, "solving generic tasks" is another overstatement. The oddball search tasks, same-different tasks, and symmetric tasks are only a small subset of many visual tasks. Can this "quantitative model" solve motion direction judgment tasks, visual working memory tasks? Perhaps so, but at least this manuscript provides no such evidence. On line 291, it says "we have proposed that visual homogeneity can be used to solve any task that requires discriminating between homogeneous and heterogeneous displays". I think this is a good statement. A title that says "XXXX enable solving discrimination tasks with multi-component displays" is more acceptable. The phrase "generic tasks" is certainly an exaggeration.

(4) If I understand it correctly, one of the key findings of this paper is "the response times for target-present searches were positively correlated with visual homogeneity. By contrast, the response times for target-absent searches were negatively correlated with visual homogeneity" (lines 204-207). I think the authors have already acknowledged that the positive correlation is not surprising at all because it reflects the classic target-distractor similarity effect. But the authors claim that the negative correlations in target-absent searches is the true novel finding.

(5) I would like to make it clear that this negative correlation is not new either. The seminal paper by Duncan and Humphreys (1989) has clearly stated that "difficulty increases with increased similarity of targets to nontargets and decreased similarity between nontargets" (the sentence in their abstract). Here, "similarity between nontargets" is the same as the visual homogeneity defined here. Similar effects have been shown in Duncan (1989) and Nagy, Neriani, and Young (2005). See also the inconsistent results in Nagy& Thomas, 2003, Vicent, Baddeley, Troscianko&Gilchrist, 2009.<br /> More recently, Wei Ji Ma has systematically investigated the effects of heterogeneous distractors in visual search. I think the introduction part of Wei Ji Ma's paper (2020) provides a nice summary of this line of research.

I am surprised that these references are not mentioned at all in this manuscript (except Duncan and Humphreys, 1989).

(6) If the key contribution is the quantitative model, the study should be organized in a different way. Although the findings of positive and negative correlations are not novel, it is still good to propose new models to explain classic phenomena. I would like to mention the three studies by Wei Ji Ma (see below). In these studies, Bayesian observer models were established to account for trial-by-trial behavioral responses. These computational models can also account for the set-size effect, behavior in both localization and detection tasks. I see much more scientific rigor in their studies. Going back to the quantitative model in this paper, I am wondering whether the model can provide any qualitative prediction beyond the positive and negative correlations? Can the model make qualitative predictions that differ from those of Wei Ji's model? If not, can the authors show that the model can quantitatively better account for the data than existing Bayesian models? We should evaluate a model either qualitatively or quantitatively.

(7) In my opinion, one of the advantages of this study is the fMRI dataset, which is valuable because previous studies did not collect fMRI data. The key contribution may be the novel brain region associated with display heterogeneity. If this is the case, I would suggest using a more parametric way to measure this region. For example, one can use Gabor stimuli and systematically manipulate the variations of multiple Gabor stimuli, the same logic also applies to motion direction. If this study uses static Gabor, random dot motion, object images that span from low-level to high-level visual stimuli, and consistently shows that the stimulus heterogeneity is encoded in one brain region, I would say this finding is valuable. But this sounds like another experiment. In other words, it is insufficient to claim a new brain region given the current form of the manuscript.

REFERENCES<br /> - Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96(3), 433-458. doi: 10.1037/0033-295x.96.3.433<br /> - Duncan, J. (1989). Boundary conditions on parallel processing in human vision. Perception, 18(4), 457-469. doi: 10.1068/p180457<br /> - Nagy, A. L., Neriani, K. E., & Young, T. L. (2005). Effects of target and distractor heterogeneity on search for a color target. Vision Research, 45(14), 1885-1899. doi: 10.1016/j.visres.2005.01.007<br /> - Nagy, A. L., & Thomas, G. (2003). Distractor heterogeneity, attention, and color in visual search. Vision Research, 43(14), 1541-1552. doi: 10.1016/s0042-6989(03)00234-7<br /> - Vincent, B., Baddeley, R., Troscianko, T., & Gilchrist, I. (2009). Optimal feature integration in visual search. Journal of Vision, 9(5), 15-15. doi: 10.1167/9.5.15<br /> - Singh, A., Mihali, A., Chou, W. C., & Ma, W. J. (2023). A Computational Approach to Search in Visual Working Memory.<br /> - Mihali, A., & Ma, W. J. (2020). The psychophysics of visual search with heterogeneous distractors. BioRxiv, 2020-08.<br /> - Calder-Travis, J., & Ma, W. J. (2020). Explaining the effects of distractor statistics in visual search. Journal of Vision, 20(13), 11-11.

Reviewer #1 (Public Review):

This is an interesting report examining activity patterns in mouse ACC and in the OFC neurons projecting to ACC. In addition, the effects of inactivation are examined. In aggregate, the results provide new and interesting information about these two brain areas and they translate motivation into action - a function that it seems intuitively plausible that ACC might perform but, despite this intuition, there have been comparatively few direct tests of the idea and little is known of the specific mechanisms. The study is performed carefully and is written up clearly.

The combination of recording and inactivation/inhibition experiments and the combination of investigation of ACC neurons and of OFC regions projecting to ACC are very impressive.

Reviewer #2 (Public Review):

Summary:

Regalado et al. studied how an extended motivational state, necessary for maintaining behavioural drive despite unrewarding experiences, could be encoded in the ACC and its potential causal implications for learning discriminatory behaviour and avoiding unrewarding stimuli. They designed a self-initiated learning task and identified bulk neural responses tuned specifically to reward delivery as well as trial initiation. Interestingly, in both cases, neural activity precedes behavioural onset, indicating the encoding of a motivational signal. To investigate the neural encoding of motivational signals during unrewarded, distracting stimuli presentation, they created a discrimination task by introducing 'no reward' cues, during which animals need to learn not to reduce running speed and not engage in licking. Interestingly, with mice learning to increase running speed and reduce licking rates after 'no reward' cues, the preceding ACC activity also gradually increased. Importantly, only the increase in running speed after 'no reward' cues was impaired upon optogenetic inhibition of ACC activity during early training, linking the extended motivational signal in ACC and learning to maximise rewards by actively avoiding distracting and unrewarded stimuli. Such motivational signals could also be observed in OFC-ACC projecting neurons. Especially the continuous ramping of activity upon repeated 'non-reward' cues, which could be exclusively observed in the 'fast learner' subgroup, provides an interesting concept of how an extended motivational signal necessary for learning avoidance of unrewarded stimuli could be implemented in ACC. The shift in the temporal activity of initially reward-responsive neurons towards the preceding 'no reward' cue, provides a potential mechanism linking extended motivation to reward maximisation. This mechanism seems to be particularly important in periods of persistent 'non-reward' cues, as demonstrated in the impairment of running speed increase after two consecutive 'non-reward' cues.

Appraisal:

The authors provide convincing experimental evidence to support their claims of an extended motivational signal encoded in the ACC that is implemented by OFC-ACC signalling and critically involved in learning avoidance of unrewarded stimuli. The newly designed task seems appropriate to identify correlates of relevant cognitive and behavioural variables (e.g. sustained motivation). The combination of recording Ca2+ transients (bulk as well as longitudinal single neuron recordings) to identify potential neural responses and subsequent evaluation of their causal role in establishing and maintaining this persistent motivational state using opto- and pharmacogenetic manipulations is generally accepted.

Impact:

The findings will be valuable for further research on the impact of motivational states on behaviour and cognition. The authors provided a promising concept of how persistent motivational states could be maintained, as well as established a novel, reproducible task assay. While experimental methods used are currently state-of-the-art, theoretical analysis seems to be incomplete/not extensive.

Reviewer #1 (Public Review):

Summary:

In this paper, the authors introduce a new deep learning-based algorithm for tracking animal poses, especially in minimizing drift effects. The algorithm's performance was validated by comparing it with two other popular algorithms, DeepLabCut and LEAP.

Strengths:

The authors showcased the effectiveness of their new algorithm in a systematic manner, covering individual levels of mice, drosophilas, macaques, and multi-animal poses.

Weaknesses:

(1) The accessibility of this tool for biological research is not clearly addressed, despite its potential usefulness. Researchers in biology often have limited expertise in deep learning training, deployment, and prediction. A detailed, step-by-step user guide is crucial, especially for applications in biological studies.

(2) The proposed algorithm focuses on tracking and is compared with DLC and LEAP, which are more adept at detection rather than tracking.

Reviewer #2 (Public Review):

Summary:

The authors present a new model for animal pose estimation. The core feature they highlight is the model's stability compared to existing models in terms of keypoint drift. The authors test this model across a range of new and existing datasets. The authors also test the model with two mice in the same arena. For the single animal datasets the authors show a decrease in sudden jumps in keypoint detection and the number of undetected keypoints compared with DeepLabCut and SLEAP. Overall average accuracy, as measured by root mean squared error, generally shows similar but sometimes superior performance to DeepLabCut and better performance compared to SLEAP. The authors confusingly don't quantify the performance of pose estimation in the multi (two) animal case instead focusing on detecting individual identity. This multi-animal model is not compared with the model performance of the multi-animal mode of DeepLabCut or SLEAP.

Strengths:

The major strength of the paper is successfully demonstrating a model that is less likely to have incorrect large keypoint jumps compared to existing methods. As noted in the paper, this should lead to easier-to-interpret descriptions of pose and behavior to use in the context of a range of biological experimental workflows.

Weaknesses:

There are two main types of weaknesses in this paper. The first is a tendency to make unsubstantiated claims that suggest either model performance that is untested or misrepresents the presented data, or suggest excessively large gaps in current SOTA capabilities. One obvious example is in the abstract when the authors state ADPT "significantly outperforms the existing deep-learning methods, such as DeepLabCut, SLEAP, and DeepPoseKit." All tests in the rest of the paper, however, only discuss performance with DeepLabCut and SLEAP, not DeepPoseKit. At this point, there are many animal pose estimation models so it's fine they didn't compare against DeepPoseKit, but they shouldn't act like they did. Similar odd presentation of results are statements like "Our method exhibited an impressive prediction speed of 90{plus minus}4 frames per second (fps), faster than DeepLabCut (44{plus minus}2 fps) and equivalent to SLEAP (106{plus minus}4 fps)." Why is 90{plus minus}4 fps considered "equivalent to SLEAP (106{plus minus}4 fps)" and not slower? I agree they are similar but they are not the same. The paper's point of view of what is "equivalent" changes when describing how "On the single-fly dataset, ADPT excelled with an average mAP of 92.83%, surpassing both DeepLabCut and SLEAP (Figure 5B)" When one looks at Figure 5B, however, ADPT and DeepLabCut look identical. Beyond this, oddly only ADPT has uncertainty bars (no mention of what uncertainty is being quantified) and in fact, the bars overlap with the values corresponding to SLEAP and DeepPoseKit. In terms of making claims that seem to stretch the gaps in the current state of the field, the paper makes some seemingly odd and uncited statements like "Concerns about the safety of deep learning have largely limited the application of deep learning-based tools in behavioral analysis and slowed down the development of ethology" and "So far, deep learning pose estimation has not achieved the reliability of classical kinematic gait analysis" without specifying which classical gait analysis is being referred to. Certainly, existing tools like DeepLabCut and SLEAP are already widely cited and used for research.

The other main weakness in the paper is the validation of the multi-animal pose estimation. The core point of the paper is pose estimation and anti-drift performance and yet there is no validation of either of these things relating to multi-animal video. All that is quantified is the ability to track individual identity with a relatively limited dataset of 10 mice IDs with only two in the same arena (and see note about train and validation splits below). While individual tracking is an important task, that literature is not engaged with (i.e. papers like Walter and Couzin, eLife, 2021: https://doi.org/10.7554/eLife.64000) and the results in this paper aren't novel compared to that field's state of the art. On the other hand, while multi-animal pose estimation is also an important problem the paper doesn't engage with those results either. The two methods already used for comparison in the paper, SLEAP and DeepPoseKit, already have multi-animal modes and multi-animal annotated datasets but none of that is tested or engaged with in the paper. The paper notes many existing approaches are two-step methods, but, for practitioners, the difference is not enough to warrant a lack of comparison. The authors state that "The evaluation of our social tracking capability was performed by visualizing the predicted video data (see supplement Videos 3 and 4)." While the authors report success maintaining mouse ID, when one actually watches the key points in the video of the two mice (only a single minute was used for validation) the pose estimation is relatively poor with tails rarely being detected and many pose issues when the mice get close to each other.

Finally, particularly in the methods section, there were a number of places where what was actually done wasn't clear. For example in describing the network architecture, the authors say "Subsequently, network separately process these features in three branches, compute features at scale of one-fourth, one-eight and one-sixteenth, and generate one-eight scale features using convolution layer or deconvolution layer." Does only the one-eight branch have deconvolution or do the other branches also? Similarly, for the speed test, the authors say "Here we evaluate the inference speed of ADPT. We compared it with DeepLabCut and SLEAP on mouse videos at 1288 x 964 resolution", but in the methods section they say "The image inputs of ADPT were resized to a size that can be trained on the computer. For mouse images, it was reduced to half of the original size." Were different image sizes used for training and validation? Or Did ADPT not use 1288 x 964 resolution images as input which would obviously have major implications for the speed comparison? Similarly, for the individual ID experiments, the authors say "In this experiment, we used videos featuring different identified mice, allocating 80% of the data for model training and the remaining 20% for accuracy validation." Were frames from each video randomly assigned to the training or validation sets? Frames from the same video are very correlated (two frames could be just 1/30th of a second different from each other), and so if training and validation frames are interspersed with each other validation performance doesn't indicate much about performance on more realistic use cases (i.e. using models trained during the first part of an experiment to maintain ids throughout the rest of it.)

Reviewer #1 (Public Review):

Summary:

The mechanisms of how axonal projections find their correct target requires the interplay of signalling pathways, and cell adhesion that act over short and long distances. The current study aims to use the small ventral lateral clock neurons (s-LNvs) of the Drosophila clock circuit as a model to study axon projections. These neurons are born during embryonic stages and are part of the core of the clock circuit in the larval brain. Moreover, these neurons are maintained through metamorphosis and become part of the adult clock circuit. The authors use the axon length by means of anti-Pdf antibody or Pdf>GFP as a read-out for the axonal length. Using ablation of the MB- the overall target region of the s-LNvs, the authors find defects in the projections. Next, by using Dscam mutants or knock-down they observe defects in the projections. Manipulations by the DNs - another group of clock neurons- can induce defects in the s-LNvs axonal form, suggesting an active role of these neurons in the morphology of the s-LNvs.

Strengths:

The use of Drosophila genetics and a specific neural type allows targeted manipulations with high precision.

Proposing a new model for a small group of neurons for axonal projections allows us to explore the mechanism with high precision.

Weaknesses:

It is unclear how far the proposed model can be seen as developmental.

The study of changes in fully differentiated and functioning neurons may affect the interpretation of the findings.

Reviewer #2 (Public Review):

Summary:

The paper from Li et al shows a mechanism by which axons can change direction during development. They use the sLNv neurons as a model. They find that the appearance of a new group of neurons (DNs) during post-embryonic proliferation secretes netrins and repels horizontally towards the midline, the axonal tip of the LNvs.

Strengths:

The experiments are well done and the results are conclusive.

Weaknesses:

The novelty of the study is overstated, and the background is understated. Both things need to be revised.

Reviewer #1 (Public Review):

Summary:

The study investigated the neural circuits underlying social novelty preference in mice. Using viral circuit tracing, chemogenetics, and optogenetics in the vHPC, LS, and VTA, the authors found that vHPC to LS projections may contribute to the salience of social novelty investigations. In addition, the authors identify LS projections to the VTA involved in social novelty and familiar food responses. Finally, via viral tracing, they demonstrate that vHPC-LS neurons may establish direct monosynaptic connections with VTA dopaminergic neurons. The experiments are well-designed, and the conclusions are mostly very clear. The manuscript is well-written and logically organized, and the content will be of interest to specialists in the field and to the broad readership of the journal.

Strengths:

(1) The vHPC has been involved in social memory for novel and familiar conspecifics. Yet, how the vHPC conveys this information to drive motivation for novel social investigations remains unclear. The authors identified a pathway from the vHPC to the LS and eventually the VTA, that may be involved in this process.

(2) Mice became familiar with a novel conspecific by co-housing for 72h. This represents a familiarization session with a longer duration as compared to previous literature. Using this new protocol, the authors found robust social novelty preference when animals were given a choice between a novel and familiar conspecific.

(3) The effects of vHPC-LS inhibition are specific to novel social stimuli. The authors included novel food and novel object control experiments and those were not affected by neuronal manipulations.

(4) For optogenetic studies, the authors applied closed-loop photoinhibition only when the animals investigated either the novel conspecific or the familiar. This optogenetic approach allowed for the investigation of functional manipulations to selective novel or familiar stimuli approaches.

Weaknesses:

(1) The abstract and the overall manuscript pose that the authors identified a novel vHPC-LS-VTA pathway that is necessary for mice to preferentially investigate novel conspecifics. However, the authors assessed the functional manipulations of vHPC-LS and LS-VTA circuits independently and the sentence could be misleading. Therefore, a viral strategy specifically designed to target the vHPC-LS-VTA circuit combined with optogenetic/chemogenetic tools and behavior may be necessary for the statement of this conclusion.

(2) The authors combined males and females in their analysis, as neural circuit manipulation affected novelty discrimination ratios in both sexes. However, supplementary Figure 1 demonstrates the chemogentic inhibition of vHPC-LS circuit may cause stronger effects in male mice as compared to females.

(3) In most experiments, the same animals were used for social novelty preference, for food or object novelty responses but washout periods between experiments are not mentioned in the methods section. In this line, the authors did not mention the time frame between the closed-loop optogenetic experiments that silenced the vHPC-LS only during familiar and then only novel social investigations. When using the same animals tested for social experiments in the same context there may be an effect of context-dependent social behaviors that could affect future outcomes.

(4) All the experiments were performed in a non-cell-type-specific manner. The viral strategies used targeted multiple neuronal subpopulations that could have divergent effects on social novelty preference. This constraint could be added in the discussion section.

(5) The authors' assumptions were all based on experiments of necessity. The authors could use an experiment of sufficiency by targeting for instance the LS-VTA circuit and assess if animals reduce novel social investigations with LS-VTA photostimulation.

Reviewer #2 (Public Review):

Summary:

Rashid and colleagues demonstrate a novel hippocampal lateral septal circuit that is important for social recognition and drives the exploration of novel conspecifics. Their study spans from neural tracing to close-loop optogenetic experiments with clever controls and conditions to provide compelling evidence for their conclusion. They demonstrate that downstream of the hippocampal septal circuit, septal projections to the ventral tegmental area are necessary for general novelty discrimination. The study opens an avenue to study these circuits further to uncover the plasticity and synaptic mechanisms regulating social novelty preference.

Strengths:

Chemogenetic and optogenetic experiments have excellent behavioral controls. The synaptic tracing provides important information that informs the narrative of experiments presented and invites future studies to investigate the effects of septal input on dopaminergic activity.

Weaknesses:

There are unclear methodological important details for circuit manipulation experiments and analyses where multiple measures are needed but missing. Based on the legends, the chemogenetic experiment is done in a within-animal design. That is the same mouse receives SAL and CNO. However, the data is not presented in a within-animal manner such that we can distinguish if the behavior of the same animal changes with drug treatment. Similarly, the methods specify that the optogenetic manipulations were done in three different conditions, but the analyses do not report within-animal changes across conditions nor account for multiple measures within subjects. Finally, it is unclear if the order of drug treatment and conditions were counterbalanced across subjects.

Reviewer #1 (Public Review):

Summary:

In this manuscript by Mou and Ji, the authors describe the correlation between firing rates in the ACC with that of CA1 ensembles during observational learning. Their main findings include trajectory selective (observational) responses in ACC, correlations between ACC and CA1 place cells for specific trajectories during observational learning, and correlations between ACC and CA1 place cells that are reactivated during SWRs, specifically during CA1 replays.

Strengths:

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

Weaknesses:

Lack of physiological characterization of the neurons that could have been included, such as regular firing rates of neurons in different regions (not only constrained to behavioral landmarks) or PSTH during sharp-wave ripples. The first experiment, NMDA blockage, is a bit disconnected from the rest of the results. Perhaps clarifying in the text a bit further that this proves that ACC is necessary for social learning would help.

Reviewer #2 (Public Review):

Summary:

In the manuscript, Xiang Mou and Daoyun JI investigate how ACC neurons activated by observational learning communicate with the hippocampus. They assess this line of communication through a complex behavioral technique, in vivo electrophysiology, pharmacological approaches, and data analytical techniques. Firstly, the authors find that observational performance is dependent on the ACC, and that the ACC possesses neurons that show side selectivity (trajectory-related) in both the observation box when shuttling to reward, and during subsequent maze running, shuttling to the corresponding same side for reward. The side-selective activation appears stronger for correct trials compared to error trials specifically during observation of Demo rats. They compare how the CA1 of the hippocampus encodes these two environments and find that ACC side-selective neurons show a correlation with side-selective CA1 ensembles during maze behavior, water consumption, and sharp-wave ripples.

Strengths:

Overall, the paper provides strong evidence that ACC neurons are activated by observational learning and that this activation seems to be correlated with CA1 activity.

Weaknesses:

Concerns, however, surround the strength of evidence that links ACC and CA1 activity during observational learning. Only weak correlations between the two regions are shown, and it is unclear if the ACC may lead to CA1 activity or vice versa. It is possible that these processes reflect two parallel pathways. Without manipulation of ACC, it is difficult to assess whether ACC activity influences hippocampal replay.

Reviewer #3 (Public Review):

Summary:

Mou and Ji investigated neuro-computational mechanisms behind observational spatial learning in rats and reported several signs of functional coupling between the ACC and CA1 at the single neuron level. Using multi-site tetrode recording, they found that ACC cells encoding a path on a maze were activated while a rat observed another rat took that path. This activation was also correlated with the activation of CA1 cells encoding the same path and facilitated their replay during sharp-wave ripples (SWRs) before the recording rat ran on the maze by itself. These activity patterns were associated with correct path choice during self-running and were absent in control conditions where the recording rat did not learn the correct choice through observations. Based on these findings, the authors argue that ACC cells capture the critical information during observation to organize hippocampal cell activity for subsequent spatial decisions.

Strengths:

The authors used multiple outcome measures to build a strong case for path-specific spike coordination between ACC and CA1 cells. The analyses were conducted carefully, and proper control measures were used to establish the statistical significance of the detected effects. The authors also demonstrated tight correlations between the spike coordination patterns and the successful use of observed information for future decisions.

Weaknesses:

(1) As evidence for the activation of path information in the ACC during observation, the authors showed positive correlations between firing rates during observation and those during self-running. This argument will be solidified if the authors use a decoding approach to demonstrate the activation of path-selective ACC ensemble activity patterns during observation. This approach will also open the door to uncovering how the activation of ACC path representation is related to the moment-to-moment position of the demonstrator rat and whether it is coupled with the timing of SWRs.

(2) The authors argued that the ACC biases the content of awake replay in CA1 during SWRs in the observation period. The reviewer wonders if a similar bias also occurs during SWRs in the self-run period (i.e., water consumption after the correct choice). This analysis will be helpful in testing if the biased replay occurs due to the need to convert observed information into future choices.

(3) Although the authors demonstrated the necessity of the ACC for the task, it still remains to be determined firing coordination between the ACC and CA1 during observation is necessary for the correct path choice during self-runs. Some discussion on this point, along with future direction, would be beneficial for readers.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Zhang et al. report a genetic screen to identify novel transcriptional regulators that could coordinate mitochondrial biogenesis. They performed an RNAi-based modifier screen wherein they systematically knocked down all known transcription factors in the developing Drosophila eye, which was already sensitised and had decreased mitochondrial DNA content. Through this screen, they identify CG1603 as a potential regulator of mitochondrial content. They show that protein levels of mitochondrial proteins like TFAM, SDHA, and other mitochondrial proteins and mtDNA content are downregulated in CG1603 mutants. RNA-Seq and ChIP-Seq further show that CG1603 binds to the promoter regions of several known nuclear-encoded mitochondrial genes and regulates their expression. Finally, they also identified YL-1 as an upstream regulator of CG1603. Overall, it is a very important study as our understanding of the regulation of mitochondrial biogenesis remains limited across metazoans. Most studies have focused on PGC-1α as a master regulator of mitochondrial biogeneis, which seems a context-dependent regulator. Also, PGC-1α mediated regulation could not explain the regulation of 1100 genes that are required for mitochondrial biogenesis. Therefore, identifying a new regulator is crucial for understanding the overall regulation of mitochondrial biogenesis.

Reviewer #2 (Public Review):

Summary:

In this study, the authors aim to identify the nuclear genome-encoded transcription factors that regulate mtDNA maintenance and mitochondrial biogenesis. They started with an RNAi screening in developing Drosophila eyes with reduced mtDNA content and identified a number of putative candidate genes. Subsequently, using ChIP-seq data, they built a potential regulatory network that could govern mitochondrial biogenesis. Next, they focused on a candidate gene, CG1603, for further characterization. Based on the expression of different markers, such as TFAM and SDHA, in the RNAi and OE clones in the midgut cells, they argue that CG1603 promotes mitochondrial biogenesis and the expression of ETC complex genes. Then, they used a mutant of CG1603 and showed that both mtDNA levels and mitochondrial protein levels were reduced. Using clonal analyses, they further show a reduction in mitochondrial biogenesis and membrane potential upon loss of CG1603. They made a reporter line of CG1603, showed that the protein is localized to the mitochondria, and binds to polytene chromosomes in the salivary gland. Based on the RNA-seq results from the mutants and the ChIP data, the authors argue that the nucleus-encoded mitochondrial genes that are downregulated >2 folds in the CG1603 mutants and that are bound by CG1603 are related to ETC biogenesis. Finally, they show that YL-1, another candidate in the network, is an upstream regulator of CG1603.

Strengths:

This is a valuable study, which identifies a potential regulator and a network of nucleus-encoded transcription factors that regulate mitochondrial biogenesis. Through in-vivo and in-vitro experimental evidence, the authors identify the role of CG1603 in this process. The screening strategy was smart, and the follow-up experiments were nicely executed.

Weaknesses:

Some additional experiments showing the effects of CG1603 loss on ETC integrity and functionality would strengthen the work.

Reviewer #1 (Public Review):

Summary:

The authors investigate ligand and protein-binding processes in GPCRs (including dimerization) by the multiple walker supervised molecular dynamics method. The paper is interesting and it is very well written.

Strengths:

The authors' method is a powerful tool to gain insight into the structural basis for the pharmacology of G protein-coupled receptors.

Weaknesses:

Cholesterol may play a fundamental role in GPCR dimerization (as cited by the authors, Prasanna et al, "Cholesterol-Dependent Conformational Plasticity in GPCR Dimers"). Yet they do not use cholesterol in their simulations of the dimerization.

Reviewer #2 (Public Review):

The study by Deganutti and co-workers is a methodological report on an adaptive sampling approach, multiple walker supervised molecular dynamics (mwSuMD), which represents an improved version of the previous SuMD.

Case-studies concern complex conformational transitions in a number of G protein Coupled Receptors (GPCRs) involving long time-scale motions such as binding-unbinding and collective motions of domains or portions. GPCRs are specialized GEFs (guanine nucleotide exchange factors) of heterotrimeric Gα proteins of the Ras GTPase superfamily. They constitute the largest superfamily of membrane proteins and are of central biomedical relevance as privileged targets of currently marketed drugs.

MwSuMD was exploited to address:<br /> (1) Binding and unbinding of the arginine-vasopressin (AVP) cyclic peptide agonist to the V2 vasopressin receptor (V2R);<br /> (2) Molecular recognition of the β2-adrenergic receptor (β2-AR) and heterotrimeric GDP-bound Gs protein;<br /> (3) Molecular recognition of the A1-adenosine receptor (A1R) and palmitoylated and geranylgeranylated membrane-anchored heterotrimeric GDP-bound Gi protein;<br /> (4) The whole process of GDP release from membrane-anchored heterotrimeric Gs following interaction with the glucagon-like peptide 1 receptor (GLP1R), converted to the active state following interaction with the orthosteric non-peptide agonist danuglipron;<br /> (5) The heterodimerization of D2 dopamine and A2A adenosine receptors (D2R and A2AR, respectively) and binding to a bi-valent ligand.

The mwSuMD method is solid and valuable, has wide applicability, and is compatible with the most world-widely used MD engines. It may be of interest to the computational structural biology community.

The huge amount of high-resolution data on GPCRs makes those systems suitable, although challenging, for method validation and development.

While the approach is less energy-biased than other enhanced sampling methods, knowledge, at the atomic detail, of binding sites/interfaces and conformational states is needed to define the supervised metrics, the higher the resolution of such metrics is the more accurate the outcome is expected to be. The definition of the metrics is a user- and system-dependent process.

The too many and ambitious case-studies undermine the accuracy of the output and reduce the important details needed for a methodological report. In some cases, the available CryoEM structures could have been exploited better.

The most consistent example concerns AVP binding/unbinding to V2R. The consistency with CryoEM data decreases with an increase in the complexity of the simulated process and involved molecular systems (e.g. receptor recognition by membrane-anchored G protein and the process of nucleotide exchange starting from agonist recognition by an inactive-state receptor). The last example, GPCR hetero-dimerization, and binding to a bi-valent ligand, is the most speculative one as it does not rely on high-resolution structural data for metrics supervision.

Reviewer #3 (Public Review):

Summary:

In the present work, Deganutti et al. report a structural study on GPCR functional dynamics using a computational approach called supervised molecular dynamics.

Strengths:

The study has the potential to provide novel insight into GPCR functionality. An example is the interaction between loops of GPCR and G proteins, which are not resolved experimentally, or the interaction between D344 and R385 identified during the Gs coupling by GLP-1R. However, validation of the findings, even computationally through for instance in silico mutagenesis study, is advisable.

Weaknesses:

In its current form, the manuscript seems immature and in particular, the described results grasp only the surface of the complex molecular mechanisms underlying GPCR activation. No significant advance of the existing structural data on GPCR and GPCR/G protein coupling is provided. Most of the results are a reproduction of the previously reported structures.

Reviewer #1 (Public Review):

Summary:

This manuscript presents evidence of 'vocal style' in sperm whale vocal clans. Vocal style was defined as specific patterns in the way that rhythmic codas were produced, providing a fine-scale means of comparing coda variations. Vocal style effectively distinguished clans similar to the way in which vocal repertoires are typically employed. For non-identity codas, vocal style was found to be more similar among clans with more geographic overlap. This suggests the presence of social transmission across sympatric clans while maintaining clan vocal identity.

Strengths:

This is a well-executed study that contributes exciting new insights into cultural vocal learning in sperm whales. The methodology is sound and appropriate for the research question, building on previous work and ground-truthing much of their theories. The use of the Dominica dataset to validate their method lends strength to the concept of vocal style and its application more broadly to the Pacific dataset. The results are framed well in the context of previous works and clearly explain what novel insights the results provide to the current understanding of sperm whale vocal clans. The discussion does an overall great job of outlining why horizontal social learning is the best explanation for the results found.

Weaknesses:

The primary issues with the manuscript are in the technical nature of the writing and a lack of clarity at times with certain terminology. For example, several tree figures are presented and 'distance' between trees is key to the results, yet 'distance' is not clearly defined in a way for someone unfamiliar with Markov chains to understand. However, these are issues that can easily be dealt with through minor revisions with a view towards making the manuscript more accessible to a general audience.

I also feel that the discussion could focus a bit more on the broader implications - specifically what the developed methods and results might imply about cultural transmission in other species. This is specifically mentioned in the abstract but not really delved into in detail during the discussion.

Reviewer #2 (Public Review):

Summary:

The current article presents a new type of analytical approach to the sequential organisation of whale coda units.

Strengths:

The detailed description of the internal temporal structure of whale codas is something that has been thus far lacking.

Weaknesses:

It is unclear how the insight gained from these analyses differs or adds to the voluminous available literature on how codas varies between whale groups and populations. It provides new details, but what new aspects have been learned, or what features of variation seem to be only revealed by this new approach?<br /> The theoretical basis and concepts of the paper are problematical and indeed, hamper potentially the insights into whale communication that the methods could offer. Some aspects of the results are also overstated.

Reviewer #3 (Public Review):

Summary:

The study presented by Leitao et al., represents an important advancement in comprehending the social learning processes of sperm whales across various communicative and socio-cultural contexts. The authors introduce the concept of "vocal style" as an addition to the previously established notion of "vocal repertoire," thereby enhancing our understanding of sperm whale vocal identity.

Strengths:

A key finding of this research is the correlation between the similarity of clan vocal styles for non-ID codas and spatial overlap (while no change occurs for ID codas), suggesting that social learning plays a crucial role in shaping symbolic cultural boundaries among sperm whale populations. This work holds great appeal for researchers interested in animal cultures and communication. It is poised to attract a broad audience, including scholars studying animal communication and social learning processes across diverse species, particularly cetaceans.

Weaknesses:

In terms of terminology, while the authors use the term "saying" to describe whale vocalizations, it may be more conservative to employ terms like "vocalize" or "whale speech" throughout the manuscript. This approach aligns with the distinction between human speech and other forms of animal communication, as outlined in prior research (Hockett, 1960; Cheney & Seyfarth, 1998; Hauser et al., 2002; Pinker & Jackendoff, 2005; Tomasello, 2010).

Reviewer #2 (Public Review):

Summary:

The manuscript by Djebar et al investigated the role and the underlying mechanism of the ciliary transition zone protein Rpgrip1l in zebrafish spinal alignment. They showed that rpgrip1l mutant zebrafish develop a nearly full penetrance of body curvature at juvenile stages. The mutant fish have cilia defects associated with ventricular dilations and loss of the Reissner fibers. Scoliosis onset and progression are also strongly associated with astrogliosis and neuroinflammation, and anti-inflammatory drug treatment prevents scoliosis in mutant zebrafish, suggesting a novel pathogenic mechanism for human idiopathic scoliosis. This study is quite comprehensive with high-quality data, and the manuscript is well written, providing important information on how the ciliary transition zone protein functions in maintaining the zebrafish body axis straightness.

Strengths:

Very clear and comprehensive analysis of the mutant zebrafish.

Weaknesses:

(1) In Figures 1D-G, magnified high-resolution pictures are required to show there are indeed no vertebral malformations.

(2) Are the transcriptome data and proteomic data consistent? Consistent targets in both analyses should be highlighted.

(3) What is the role of Anxa2 in neuroinflammation? Is increased Anxa2 expression in rpgrip1l mutant zebrafish reduced after anti-inflammatory drug treatment? What is the expression level of anxa2 in cep290 mutant zebrafish?

(4) More background about Rpgrip1l should be provided in the introduction, particularly the past studies of the mammalian homolog of Rpgrip11, if there are any.

(5) Is there any human disease associated with Rpgrip1l? Do these patients have scoliosis phenotype?

(6) A summary diagram at the end would be helpful for understanding the main findings.

Reviewer #1 (Public Review):

Summary:

In this study, Djebar et al. perform a comprehensive analysis of mutant phenotypes associated with the onset and progression of scoliosis in zebrafish ciliary transition zone mutants rpgrip1l and cep290. They determine that rpgrip1l is required in foxj1a-expressing cells for normal spine development, and that scoliosis is associated with brain ventricle dilations, loss of Reissner fiber polymerization, and the loss of 'tufts' of multi-cilia surrounding the subcommissural organ (the source of Reissner substance). Informed by transcriptomic and proteomic analyses, they identify a neuroinflammatory response in rpgrip1l and cep290 mutants that is associated with astrogliosis and CNS macrophage/microglia recruitment. Furthermore, anti-inflammatory drug treatment reduced scoliosis penetrance and severity in rpgrip1l mutants. Based on their data, the authors propose a feed-forward loop between astrogliosis, induced by perturbed ventricular homeostasis, and immune cell recruitment as a novel pathogenic mechanism of scoliosis in zebrafish ciliary transition zone mutants.

Strengths:

(1) Comprehensive characterization of the causes of scoliosis in ciliary transition zone mutants rpgrip1l and cep290.

(2) Comparison of rpgrip1l mutants pre- and post-scoliosis onset allowed authors to identify specific phenotypes as being correlated with spine curvature, including brain ventricle dilations, loss of Reissner fiber, and loss of cilia in proximity to the sub-commissural organ.

(3) Elegant genetic demonstration that increased urotensin peptide levels do not account for spinal curvature in rpgrip1l mutants.

(4) The identification of astrogliosis and Annexin over-expression in glial cells surrounding diencephalic and rhombencephalic ventricles as being correlated with scoliosis onset and severe curve progression is a very interesting finding, which may ultimately inform pathogenic mechanisms driving spine curvature

Weaknesses:

(1) The fact that cilia loss/dysfunction and Reissner fiber defects cause scoliosis in zebrafish is already well established in the literature, as is the requirement for cilia in foxj1a-expressing cells.

(2) Neuroinflammation has already been identified as the underlying pathogenic mechanism in at least 2 previously published scoliosis models (zebrafish ptk7a and sspo mutants).

(3) Anti-inflammatory drugs like aspirin, NAC, and NACET have also previously been demonstrated to suppress scoliosis onset and severe curve progression in these models.

Therefore, although similar observations in rpgrip1l and cep290 mutants (as reported here) add to a growing body of literature that supports a common biological mechanism underlying spine curvature in zebrafish, the novelty of reported findings is diminished.

(4) Although authors demonstrate that astrogliosis and/or macrophage or microglia cell recruitment are correlated with scoliosis, they do not formally demonstrate that these events are sufficient to drive spine curvature. Thus, the functional consequences of astrogliosis and microglia infiltration remain uncertain.

(5) The authors do not investigate the effect of anti-inflammatory treatments on other phenotypes they have correlated with spinal curve onset (like ventricle dilation, Reissner fiber loss, and multi-cilia loss around the subcommissural organ). This would help to identify causal events in scoliosis.

Reviewer #3 (Public Review):

Summary:

This paper describes a new mechanism of clearance of protein aggregates occurring during mitosis.

The authors have observed that animal cells can clear misfolded aggregated proteins at the end of mitosis. The images and data gathered are solid, convincing, and statistically significant. However, there is a lack of insight into the underlying mechanism. They show the involvement of the ER, ATPase-dependent, BiP chaperone, and the requirement of Cdk1 inactivation (a hallmark of mitotic exit) in the process. They also show that the mechanism seems to be independent of the APC/C complex (anaphase-promoting complex). Several points need to be clarified regarding the mechanism that clears the aggregates during mitosis:

• What happens in the cell substructure during mitosis to explain the recruitment of BiP towards the aggregates, which seem to be relocated to the cytoplasm surrounded by the ER membrane.

• How the changes in the cell substructure during mitosis explain the relocation of protein aggregates during mitosis.

• Why BiP seems to be the main player of this mechanism and not the cyto Hsp70 first described to be involved in protein disaggregation.

Strengths:

Experimental data showing clearance of protein aggregates during mitosis is solid, statistically significant, and very interesting.

Weaknesses:

Weak mechanistic insight to explain the process of protein disaggregation, particularly the interconnection between what happens in the cell substructure during mitosis to trigger and drive clearance of protein aggregates.

Reviewer #1 (Public Review):

Strengths:

The manuscript utilizes a previously reported misfolding-prone reporter to assess its behaviour in ER in different cell line models. They make two interesting observations:

(1) Upon prolonged incubation, the reporter accumulates in nuclear aggregates.

(2) The aggregates are cleared during mitosis. They further provide some insight into the role of chaperones and ER stressors in aggregate clearance. These observations provide a starting point for addressing the role of mitosis in aggregate clearance. Needless to say, going ahead understanding the impact of aggregate clearance on cell division will be equally important.

Weaknesses:

The study almost entirely relies on an imaging approach to address the issue of aggregate clearance. A complementary biochemical approach would be more insightful. The intriguing observations pertaining to aggregates in the nucleus and their clearance during mitosis lack mechanistic understanding. The issue pertaining to the functional relevance of aggregation clearance or its lack thereof has not been addressed. Experiments addressing these issues would be a terrific addition to this manuscript.

Reviewer #2 (Public Review):

Summary:

The authors provide an interesting observation that ER-targeted excess misfolded proteins localize to the nucleus within membrane-entrapped vesicles for further quality control during cell division. This is useful information indicating transient nuclear compartmentalization as a quality control strategy for misfolded ER proteins in mitotic cells, although endogenous substrates of this pathway are yet to be identified.

Strengths:

This microscopy-based study reports unique membrane-based compartments of ER-targeted misfolded proteins within the nucleus. Quarantining aggregating proteins in membrane-less compartments is a widely accepted protein quality control mechanism. This work highlights the importance of membrane-bound quarantining strategies for aggregating proteins. These observations open up multiple questions on proteostasis biology. How do these membrane-bound bodies enter the nucleus? How are the single-layer membranes formed? How exactly are these membrane-bound aggregates degraded? Are similar membrane-bound nuclear deposits present in post-mitotic cells that are relevant in age-related proteostasis diseases? Etc. Thus, the observations reported here are potentially interesting.

Weaknesses:

This study, like many other studies, used a set of model misfolding-prone proteins to uncover the interesting nuclear-compartment-based quality control of ER proteins. The endogenous ER-proteins that reach a similar stage of overdose of misfolding during ER stress remain unknown.

The mechanism of disaggregation of membrane-trapped misfolded proteins is unclear. Do these come out of the membrane traps? The authors report a few vesicles in living cells. This may suggest that membrane-untrapped proteins are disaggregated while trapped proteins remain aggregates within membranes.

The authors figure out the involvement of proteasome and Hsp70 during the disaggregation process. However, the detailed mechanisms including the ubiquitin ligases are not identified. Also, is the protein ubiquitinated at this stage?

This paper suffers from a lack of cellular biochemistry. Western blots confirming the solubility and insolubility of the misfolded proteins are required. This will also help to calculate the specific activity of luciferase more accurately than estimating the fluorescence intensities of soluble and aggregated/compartmentalized proteins. Microscopy suggested the dissolution of the membrane-based compartments and probably disaggregation of the protein. This data should be substantiated using Western blots. Degradation can only be confirmed by Western blots. The authors should try time course experiments to correlate with microscopy data. Cycloheximide chase experiments will be useful.

The cell models express the ER-targeted misfolded proteins constitutively that may already reprogram the proteostasis. The authors may try one experiment with inducible overexpression.

It is clear that a saturating dose of ER-targeted misfolded proteins activates the pathway. The authors performed a few RT-PCR experiments to indicate the proteostasis-sensitivity. Proteome-based experiments will be better to substantiate proteostasis saturation.

The authors should immunostain the nuclear compartments for other ER-membrane resident proteins that span either the bilayer or a single layer. The data may be discussed.

All microscopy figures should include control cells with similarly aggregating proteins or without aggregates as appropriate. For example, is the nuclear-targeted FlucDM-EGFP similarly entrapped? A control experiment will be interesting. Expression of control proteins should be estimated by western blots.

There are few more points that may be out of the scope of the manuscript. For example, how do these compartments enter the nucleus? Whether similar entry mechanisms/events are ever reported? What do the authors speculate? Also, the bilayer membrane becomes a single layer. This is potentially interesting and should be discussed with probable mechanisms. Also, do these nuclear compartments interfere with transcription and thereby deregulate cell division? What about post-mitotic cells? Similar deposits may be potentially toxic in the absence of cell division. All these may be discussed.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Boudjerna and Balagé et al. aim to elucidate the spatial origin of centriole amplification and the mechanisms behind the formation of an apical-basal body patch in multiciliated cells (MCCs). To this end, they focused on the role of microtubules and developed new tools for spatiotemporal and high-resolution analysis of different stages of centriole amplification, including the centrosome stages, A-stage, G-stage, and MCC-stage. Among these tools, the MEF-MCC cells grown on micropatterns stands out for its versatility as it is not tissue-specific and does not require epithelial cell-to-cell contact for differentiation. Additionally, the Cen2-GFP; mRuby-Deup1 knock-in mouse model was used to study different stages of centriole amplification in physiological brain MCCs. This model offers an advantage over the previously described Cen2-GFP model by enabling the resolution of early events in centriole amplification through the visualization of Deup1-positive structures and their dynamics. Finally, the authors leveraged powerful imaging techniques, including super-resolution microscopy, the U-ExM, and high-resolution live cell imaging in order to detect and track centriole amplification, elongation, disengagement, and migration.

By combining the MEF-MCC and knock-in mouse model with spatiotemporal imaging in control and nocodazole-treated cells(treated acutely or chronically), the authors define the sequence of events during centriole amplification, revealing the critical roles of microtubules for the first time. Initially, the centrosome-mediated microtubule network forms, organizing a pericentrosomal nest from which procentrioles and deuterosomes emerge. Their findings indicate the importance of microtubules in recruiting and maintaining pericentriolar material clouds that contain DEUP1, PCNT, SAS6, PLK1, PLK4, and tubulins. Following the amplification stage, the procentrioles mature, leading to cells displaying numerous MTOCs, as demonstrated by regrowth experiments. Mature centrioles then disengage from deuterosomes, attach to the nuclear envelope, and migrate to the apical surface facilitated by microtubules.

Strengths:

The manuscript provides new insights into the regulatory function of microtubules in centriole amplification. Addressing the role of microtubules during different stages of centriole amplification required the development of new tools to study brain MCCs, which will be useful in future studies of MCCs. A notable strength of this manuscript is the authors' thorough and quantitative analysis of highly dynamic processes in MCCs. The precision and detail in describing these dynamic events are impressive. This comprehensive analysis advances our understanding of MCC biology.

Weaknesses:

The role of microtubules and other molecular players during different stages of centriole amplification in brain MCCs can be further studied and strengthened using the tools developed in the manuscript. A more quantitative description of some of the analysis performed in the manuscript is required to strengthen the conclusions.

Reviewer #1 (Public Review):

The manuscript by Boudjema et al. describes the cellular events underlying centriole amplification and apical migration to allow the assembly of hundreds of motile cilia in multi-ciliated cells. For this, they use cell culture models in combination with fixed and live cell imaging using antibody staining and fluorescence from endogenously tagged centriole and deuterostome markers, respectively. The work is largely descriptive and functional analyses are restricted to treatment with the microtubule depolymerizing drug nocodazole. The imaging is state-of-the-art including confocal microscopy, live imaging with optical sectioning and high optical and temporal resolution, as well as super-resolution imaging by ultra-expansion microscopy.

The study does a good job of providing a very detailed description of the dynamics of centrioles and deuterostomes that lead to centriole amplification and apical migration in multiciliated cells. This detailed view was missing in previous work. It also reveals the involvement of microtubules at multiple steps: the formation of a cloud of deuterostome precursors, the nuclear envelope tethering of newly formed centrioles, their separation, and their migration to the apical surface.

It would have been useful to expand the analysis of the role of microtubules by including analyses of the requirement for specific microtubule motors, for a better understanding and additional evidence that microtubule-based transport is involved. A weak point is that there is no visualization of microtubules together with deuterosomes and centrioles at the different steps of centriole amplification and migration, to directly address how these structures may interact with and move along microtubules.

Overall, apart from experimental aspects and since this is largely a descriptive study, the manuscript would benefit from more precise language and a better description of the complex events underlying centriole amplification and movements.

Reviewer #2 (Public Review):

This important work will be of interest to centriole and cilia cell biologists. It describes in detail how microtubules control multiple aspects of centriole amplification in brain multiciliated cells. This study provides a greater time-resolved and molecular proteomic mapping of the different steps involved, with or without microtubule disruption. Boudjema et al. show that microtubules are important throughout the centriole amplification process, from the early stages, where the procentrioles emerge from a pericentriolar "nest", through the growth stage where microtubules maintain the perinuclear localisation, to the detachment stage, where microtubules assist in perinuclear disengagement and apical migration. The results are generally well supported by the evidence, but the manuscript would benefit significantly from some heavy editing to introduce more niche terms, standardize abbreviations in text, and labels on figures to help bring the readers, especially non-specialists, along with them - increasing the accessibility of their work.

Reviewer #3 (Public Review):

Summary:

The authors want to prove that there is a redox potential between germline stem cells (GSCs) and somatic cyst stem cells (CySCs) in the Drosophila testis, with ROS being higher in the former compared to the latter. They also want to prove that ROS travels from CySCs to GSCs. Finally, they begin to characterize the phenotypes caused by loss of SOD (which normally lowers ROS levels) in the tj- lineage and how this impacts the germline.

Strengths:

The role of SOD in somatic support cells is an under-explored area.

Weaknesses:

The authors fall short of accomplishing their goals. There are issues with the concept of the paper (ROS gradient between cells that causes a transfer of ROS across membranes for homeostasis), the data, the figures, and the scholarship of the testis. I have discussed each of the points in detail below. These weaknesses negatively impact the conclusions put forward by the authors. In short, their data is not compelling: there is no evidence provided by the authors that ROS diffuses from CySCs to GSCs as most of the claims about stem cells are founded on data about differentiating germ and somatic cells. The somatic SOD depletion phenotype is incompletely characterized and several pathways appear to change in these cells, including reduced Egfr signaling, increased Tor signaling, and increased Hh signaling. None of these results are sufficiently followed up on. And none of them are considered relative to their known roles in the testis. For example, high Hh signaling in CySCs increases their competitiveness with GSCs. Increased Tor signaling in all CySCs does not affect the CySC lineage. Reduced Egfr signaling in CySCs reduces the number of CySCs and reduces/inhibits abscission between GSCs-gonialblasts.

Major issues:

(1) Data<br /> a. Problems proving which mitochondria are associated with which lineage.<br /> b. There is no evidence that ROS diffuses from CySCs into GSCs.<br /> c. The changes in gst-GFP (redox readout) are possibly seen in differentiating germ cells (i.e., spermatogonia) but not in GSCs. This weakens their model that ROS in CySC is transferred to GSCs.<br /> d. Most of the paper examines the effect of SOD depletion (which should increase ROS) on the CySC lineage and GSC lineage. One big caveat is that tj-Gal4 is expressed in hub cells (Fairchild, 2016) so the loss of SOD from hub cells may also contribute to the phenotype. In fact, the niche in Figure 2D looks larger than the niche in the control in Figure 2C, arguing that the expression of Tj in niche cells may be contributing to the phenotype. The authors need to better characterize the niche in tj>SOD-RNAi testes.<br /> e. The tj>SOD-RNAi phenotype is an expansion of the Zfh1+ CySC pool, expansion of the Tj+ Zfh1- cyst cells (both due to increased somatic proliferation) and a non-autonomous disruption of the germline.<br /> f. I am not convinced that MAPK signaling is decreased in tj>SOD-i testes. Not only is this antibody finicky, but the authors don't have any follow-up experiments to see if they can restore SOD-depleted CySCs by expressing an Egfr gain of function. Additionally, reduced Egfr activity causes fewer somatic cells (not more) (Amoyel, 2016) and also inhibits abscission between GSCs and gonialblasts (Lenhart 2015), which causes interconnected cysts of 8- to 16 germ cells with one GSC emanating from the hub.<br /> g. The increase in Hh signaling in SOD-depleted CySCs would increase their competitiveness against GSCs and GSCs would be lost (Amoyel 2014). The authors need to validate that Hh protein expression is indeed increased in SOD-depleted CySCs/cyst cells and which cells are producing this Hh. Normally, only hub cells produce Hh (Michel, 2012; Amoyel 2013) to promote self-renewal in CySCs.<br /> h. The increase in p4E-BP is an indication that Tor signaling is increased, but an increase in Tor in the CySC lineage does not significantly affect the number of CySCs or cyst cells (Chen, 2021). So again I am not sure how increased Tor factors into their phenotype.<br /> i. The over-expression of SOD in CySCs part is incomplete. The authors would need to monitor ROS in these testes. They would also need to examine with tj>SOD affects the size of the hub.

(2) Concept<br /> Why would it be important to have a redox gradient across adjacent cells? The authors mention that ROS can be passed between cells, but it would be helpful for them to provide more details about where this has been documented to occur and what biological functions ROS transfer regulates.

(3) Issues with scholarship of the testis<br /> a. Line 82 - There is no mention of BMPs, which are the only GSC-self-renewal signal. Upd/Jak/STAT is required for adhesion of GSCs to the niche but not self-renewal (Leatherman and Dinardo, 2008, 2010). The author should read a review about the testis. I suggest Greenspan et al 2015. The scholarship of the testis should be improved.<br /> b. Line 82-84 - BMPs are produced by both hub cells and CySCs. BMP signaling in GSCs represses bam. So it is not technically correct to say the CySCs repress bam expression in GSCs.<br /> c. Throughout the figures the authors score Vasa+ cells for GSCs. This is technically not correct. What they are counting is single, Vasa+ cells in contact with the niche. All graphs should be updated with the label "GSCs" on the Y-axis.

(4) Issues with the text<br /> a. Line 1: multi-lineage is not correct. Multi-lineage refers to stem cells that produce multiple types of daughter cells. GSCs produce only one type of offspring and CySCs produce only one type of offspring. So both are uni-lineage. Please change accordingly.<br /> b. Lines 62-75 - Intestinal stem cells have constitutively high ROS (Jaspar lab paper) so low ROS in stem cell cells is not an absolute.<br /> c. Line 79: The term cystic is not used in the Drosophila testis. There are cyst stem cells (CySCs) that produce cyst cells. Please revise.<br /> d. Line 90 - perfectly balanced is an overstatement and should be toned down.<br /> e. Line 98 - division of labour is not supported by the data and should be rephrased.<br /> f. Line 200 - the authors provide no data on BMPs - the GSC self-renewal cue - so they should avoid discussing an absence of self-renewal cues.

(5) Issues with the figures<br /> a. The images are too small to appreciate the location of mitochrondria in GSCs and CySCs.<br /> b. Figure 1<br /> i. cell membranes are not marked, reducing the precision of assigning mitochondria to GSC or CySCs. It would be very helpful if the authors depleted ATP5A from GSCs and showed that the puncta are reduced in these cells and did a similar set of experiments for the tj-Gal4 lineage. It would also be very helpful if the authors expressed membrane markers (like myr-GFP) in the GSC and then in the CySC lineage and then stained with ATP5A. This would pinpoint in which cells ATP5A immunoreactivity is occurring.<br /> ii. The presumed changes in gst-GFP (redox readout) are possibly seen in differentiating germ cells (i.e., spermatogonia) but not in GSC.<br /> iii. Panels F, Q, and S are not explained and currently are irrelevant.<br /> c. Figure 3K - The evidence to support less Ecad in GSCs in tj>SOD-i testes is not compelling as the figure is too small and the insets show changes in Ecad in somatic cells, not GSC.<br /> d. Figure 4:<br /> i. Panel A, B The apparent decline (not quantified) may not contribute to the phenotype.<br /> ii. dpERK is a finicky antibody and the authors are showing a single example of each genotype. This is an important experiment because the authors are going to use it to conclude that MAPK is decreased in the tj>SOD-i samples. However, the authors don't have any positive (dominant-active Egfr) or negative (tj>mapk-i). As is standing the data are not compelling. The graph in F does not convey any useful information.<br /> e. Figure S1D - cannot discern green on black. It is critical for the authors to show monochromes (gray scale) for the readouts that they want to emphasize. I cannot see the green on black in Figure S1D.<br /> f. Figure S4 - there is no quantification of the number of Tj cells in K-N.

(6) Issues with Methods<br /> a. Materials and Methods are not described in sufficient depth - please revise.<br /> b. Note that tj-Gal4 has real-time expression in hub cells and this is not considered by the authors. The ideal genotype for targeting CySCs is tjGal4, Gal80TS, hh-Gal80. Additionally, the authors do not mention whether they are depleting throughout development into adulthood or only in adults. If the latter, then they must have used a temperature shift like growing the flies at 18C and then upshifting to 25C or 29C during adult stages.<br /> c. The authors need to show data points in all of the graphs. Some graphs do this but others do not.<br /> d. The authors state that all data points are from three biological replicates. This is not sufficient for GSC and CySC counts. Most labs count GSCs and CySCs from at least 10 testes of the correct genotype.

Reviewer #1 (Public Review):

The manuscript by Majhi and colleagues describes the effects of manipulating ROS levels in somatic stem cells of the testis on overall testis architecture, signaling, and function. The conclusions made by the authors are somewhat difficult to judge as the changes to the testis cell types are mostly not apparent in the representative images shown. This is true in examining gstD1-GFP expression and in the analysis of cell types and behaviours (e.g. cell cycle) and cell signaling pathway activity. Thus, the reader is left to try and interpret the quantification of the data to justify the authors' conclusions, but it is often not clear how the quantification was accomplished. For example, it is not clear how CySC vs. GSC quantification is done when the molecular markers used do not define the surface of these cells (plasma membrane) and mark different cellular compartments (Tj is nuclear while Vasa is perinuclear or cytoplasmic). Why the changes reported in quantification are not apparent in the specific example images chosen for the figures is worrisome. I'm much more used to being able to clearly see what the authors are reporting in the images, and then using the quantification to illustrate the range of data observed and demonstrate statistical significance. For this reason, I'm very concerned about the strength and validity of the conclusions. In addition, while many different characteristics of the testis somatic and germline cells are analyzed, a general and consistent view of how ROS affects these cells is not presented. In particular, one of the principle conclusions, that ROS signaling in the CySCs affects ROS signaling in the GSCs, is not well-supported by the data presented.

Specific Comments:

In Figure 1, it is very difficult to identify where CySCs end and GSCs begin without using a cell surface marker for these different cell types. In addition, the methods for quantifying the mitochondrial distribution in GSCs vs. CySCs are very much unclear, and appear to rely on colocalization with molecular markers that are not in the same cellular compartment (Tj-nuclear vs Vasa-perinuclear and cytoplasmic), the reader has no way to determine the validity of the mitochondrial distribution. Similarly, the labeling with gstD1-GFP is also very much unclear - I see little to no GFP signal in either GSCs or CySCs in panels 1G-K. Lastly, while the expression of SOD in CySCs does increase the gstD1-GFP signal in CySCs, the effects on GSCs claimed by the authors are not apparent.

In Figure 2, while the cell composition of the niche region does appear to be different from controls when SOD1 is knocked down in the CySCs, at least in the example images shown in Figures 2A and B, how cell type is quantified in Figures 2E-G is very much unclear in the figure and methods. Are these counts of cells contacting the niche? If so, how was that defined? Or were additional regions away from the niche also counted and, if so, how were these regions defined?

In Figure 3, it is quite interesting that there is an increase in Eya+, differentiating cyst cells in SOD1 knockdown animals, and that these Eya+ cells appear closer to the niche than in controls. However, this seems at odds with the proliferation data presented in Figure 2, since Eya+ somatic cells do not normally divide at all. Are they suggesting that now differentiating cyst cells are proliferative? In addition, it is important for them to show example images of the changes in Socs36E and ptp61F expression.

Overall, the various changes in signaling are quite puzzling-while Jak/Stat signaling from the niche is reduced, hh signaling appears to be increased. Similarly, while the authors conclude that premature differentiation occurs close to the niche, EGF signaling, which occurs from germ cells to cyst cells during differentiation, is decreased. Many times these changes are contradictory, and the authors do not provide a suitable explanation to resolve these contradictions.

Reviewer #2 (Public Review):

Summary:

In this work, the authors investigate the role of the Superoxide disumutase 1 (Sod1) enzyme, which acts to reduce the reactive oxygen species load, in the Drosophila testis. They show that the knockdown of Sod1 in somatic cells impacts stem cell numbers both autonomously in the soma and non-autonomously in the germline. Somatic stem cell numbers are increased, while germline stem cells are decreased and differentiate prematurely. The authors then show that in somatic Sod1 knockdowns, several signalling pathways are disrupted and that these may be responsible at least in part for the phenotypes observed. Finally, over-expression of Sod1 in the soma results in opposite phenotypes, suggesting that ROS levels do play a role in maintaining the balance between both stem cell populations in the testis.

Strengths:

The main strength of this work is to show a previously unappreciated role for Sod1 (and presumably by extension of ROS) in the Drosophila testis and in the regulation of stem cell self-renewal and differentiation. The authors use multiple readouts to show that the knockdown of Sod1 in the soma increases the number of somatic cells and also drives a non-autonomous, premature differentiation of germ cells. They also quantify the early differentiation of the germline using two different methods. Importantly, overexpression of Sod1 produces opposite phenotypes to knockdown, strengthening the conclusions.

Weaknesses:

Although the data presented are interesting, an important weakness of the manuscript as it currently stands is that many statements are not fully supported by the data. In particular, the authors do not provide any evidence of "cell redox-pairs" as indicated in the manuscript title, nor of intercellular redox gradients, as stated in several places throughout. While the data are consistent with non-autonomous regulation of ROS levels, this would not constitute a gradient. However, and crucially, there is no evidence provided to show that Sod1 manipulation in the soma is affecting ROS levels in the germline and that any of the phenotypes observed are a consequence of elevated ROS in the germline, rather than indirect effects caused by dysregulation of somatic self-renewal and differentiation, which is known to impact the germline. Indeed, there are many published reports of autonomous manipulations in the soma that influence either germline stem cell number (eg PMID: 19797664 among others) or differentiation (eg PMID: 17629483). The latter example is particularly relevant as the authors show altered somatic ERK levels, and the role of somatic ERK in promoting germ cell development is well established (PMID: 11048722, 11048723,...). Thus, whether Sod1 plays any non-autonomous role in controlling germ cell fate through ROS in the germline directly, or whether the phenotypes observed can all be explained by autonomous effects on somatic cell behaviour is debatable, but the experiments presented here do not distinguish between these two hypotheses. The only evidence presented by the authors for a non-autonomous role of Sod1 is the expression of a GFP reporter for gstD1. The quantifications and images are not clear and do not show unambiguously that this reporter is expressed in germ cells. Indeed, the quantifications show overlap between somatic and germline markers, suggesting that either the images themselves or the way they are quantified does not allow the authors to distinguish between the two cell types. Similarly, the claim that somatic mitochondria are enriched at the CySC-GSC interface and that this distribution maintains the redox balance in the niche is not supported by any experimental data. CySCs are extremely thin cells and much of the space is occupied by the nucleus (PMID: 114676), therefore it is likely that mitochondria would be enriched at the periphery. A careful analysis would be necessary to show that this enrichment is specific to the interface with GSCs. Moreover, no experiments are conducted to test whether mitochondrial distribution in CySCs has any impact on GSCs. Finally, no experiments are conducted to show definitively that the phenotypes observed upon Sod1 knockdown are indeed due to increased ROS, while this claim is made several times in the text. At present, the data presented here can support a role for Sod1 in somatic CySCs, but much more caution is required in attributing this to either ROS or intercellular ROS signaling. Therefore, several claims made in the title and throughout the text are not supported by evidence.

Besides this central point, there are other areas that should be improved. In particular, the data using the Fucci reporter to show accelerated proliferation do not appear convincing. It would seem that the proportions of cells in each phase are roughly similar, just that there are more cycling cells. A careful analysis of these results would distinguish between these two and determine whether Sod1 knockdown simply impairs differentiation (and therefore results in more somatic cells proliferating) or whether it speeds up the cell cycle (resulting in an increased mitotic index as suggested, but this requires a ratio to be shown). Similarly, several quantifications are not clearly explained, making it hard to understand what is being measured. As an example, while the decrease in pERK in CySCs is clear from the image and matched in the quantification, the increase in cyst cells is not apparent from the fire LUT used. The change in fluorescence intensity therefore may be that more cells have active ERK, rather than an increase per cell (similar arguments apply to the quantifications for p4E-BP or Ptc). Therefore, it is hard to know whether Sod1 knockdown results in increased or decreased signaling in individual cells.

Impact of study:

Demonstrating intercellular communication through ROS and its importance in maintaining the balance between two stem cell populations would be a finding of interest to a broad field. However, it remains to be demonstrated that this is the case, and given this, this study will have a limited impact.

Reviewer #1 (Public Review):

The microtubule cytoskeleton is essential for basic cell functions, enabling intracellular transport, and establishment of cell polarity and motility. Microtubule-associated proteins (MAPs) contribute to the regulation of microtubule dynamics and stability - mechanisms that are specifically important for the development and physiological function of neurons. Here, the authors aimed to elucidate the neuronal function of the MAP Hmmr, which they had previously identified in a (yet unpublished) quantitative study of the proteome associated with neuronal microtubules. The authors conduct well-controlled experiments to demonstrate the localization of endogenous as well as exogenous Hmmr on microtubules within the soma as well as all neurites of hippocampal neurons. Functional analysis using gain- and loss-of-function approaches demonstrates that Hmmr levels are crucial for neuronal morphogenesis, as the length of both dendrites and axons decreases upon loss of Hmmr and increases upon Hmmr overexpression. In addition to length alterations, the branching pattern of neurites changes with Hmmr levels. To uncover the mechanism of how Hmmr influences neuronal morphology, the authors follow the lead that Hmmr overexpression induces looped microtubules in the soma, indicative of an increase in microtubule stability. Microtubule acetylation indeed decreases and increases with Hmmr LOF and GOF, respectively. Together with a rescue of nocodazole-induced microtubule destabilization by Hmmr GOF, these results argue that Hmmr regulates microtubule stability. Highlighted by the altered movement of a plus-end-associated protein, Hmmr also has an effect on the dynamic nature of microtubules. The authors present evidence suggesting that the nucleation frequency of neuronal microtubules depends on Hmmr's ability to recruit the microtubule nucleator Tpx2. The authors discuss how branching may be regulated by Hmmr-mediated microtubule dynamics and speculate about the physiological significance of altered neuronal morphogenesis. Together, their work adds novel insight into MAP-mediated regulation of microtubules as a prerequisite for neuronal morphogenesis.

Reviewer #2 (Public Review):

The mechanism of microtubule formation, stabilization, and organization in neurites is important for neuronal function. In this manuscript, the authors examine the phenotype of neurons following alteration in the level of the protein HMMR, a microtubule-associated protein with established roles in mitosis. Neurite morphology is measured as well as microtubule stability and dynamic parameters using standard assays. A binding partner of HMMR, TPX2, is localized. The results support a role for HMMR in microtubule stabilization in neurons.

The results show that HMMR is distributed as puncta on neurons using standard immunofluorescence and PLA. Depletion of HMMR reduced neurite length and extent of branching; reduced post-translational acetylation of neurite microtubules. Conversely, overexpression of HMMR increased resistance to nocodazole. The parameters of microtubule dynamics were also impacted by reduction or overexpression of HMMR. The authors discuss the possibility HMMR regulates neurite morphological changes via regulation of microtubule nucleation and dynamics.

Reviewer #3 (Public Review):

The authors tested a dietary intervention focused on improving meal regularity in this interesting paper. The study, a two-group, single-center, randomized, controlled, single-blind trial, utilized a smartphone application to track participants' meal frequencies and instructed the experimental group to confine their eating to these times for six weeks. The authors concluded that improving meal regularity reduced excess body weight despite food intake not being altered and contributed to overall improvements in well-being.

The concept is interesting, but the need for more rigor is of concern.

A notable limitation is the reliance on self-reported food intake, with the primary outcome being self-reported body weight/BMI, indicating an average weight loss of 2.62 kg. Despite no observed change in caloric intake, the authors assert weight loss among participants.

The trial's reliance on self-reported caloric intake is problematic, as participants tend to underreport intake; for example, in the NEJM paper (DOI: 10.1056/NEJM199212313272701), some participants underreported caloric intake by approximately 50%, rendering such data unreliable and hence misleading. More rigorous methods for assessing food intake are available and should have been utilized. Merely acknowledging the unreliability of self-reported caloric intake is insufficient as it would still leave the reader with the impression that there is no change in food intake when we actually have no idea if food intake was altered. A more robust approach to assessing food intake is imperative. Even if a decrease in caloric intake is observed through rigorous measurement, as I am convinced a more rigorous study would unveil testing this paradigm, this intervention may merely represent another short-term diet among countless others that show that one may lose weight by going on a diet, principally due to heightened dietary awareness.

Furthermore, the assessment of circadian rhythm using the MCTQ, a self-reported measure of chronotype, may not be as reliable as more objective methods like actigraphy.

Given the potential limitations associated with self-reported data in both dietary intake and circadian rhythm assessment, the overall impact of this manuscript is low. Increasing rigor by incorporating more objective and reliable measurement techniques in future studies could strengthen the validity and impact of the findings.

Reviewer #1 (Public Review):

The authors Wilming and colleagues set out to determine the impact of regularity of feeding per se on the efficiency of weight loss. The idea was to determine if individuals who consume 2-3 meals within individualized time frames, as opposed to those who exhibit stochastic feeding patterns throughout the circadian period, will cause weight loss.

The methods are rigorous, and the research is conducted using a two-group, single-center, randomized-controlled, single-blinded study design. The participants were aged between 18 and 65 years old, and a smartphone application was used to determine preferred feeding times, which were then used as defined feeding times for the experimental group. This adds strength to the study since restricting feeding within preferred/personalized feeding windows will improve compliance and study completion. Following a 14-day exploration phase and a 6-week intervention period in a cohort of 100 participants (inclusive of both the controls and the experimental group that completed the study), the authors conclude that when meals are restricted to 45min or less durations (MTVS of 3 or less), this leads to efficient weight loss. Surprisingly, the study excludes the impact of self-reported meal composition on the efficiency of weight loss in the experimental group. In light of this, it is important to follow up on this observation and develop rigorous study designs that will comprehensively assess the impact of changes (sustained) in dietary composition on weight loss. The study also reports interesting effects of regularity of feeding on eating behavior, which appears to be independent of weight loss. Perhaps the most important observation is that personalized interventions that cater to individual circadian needs will likely result in more significant weight loss than when interventions are mismatched with personal circadian structures. One are of concern for the study is its two-group design; however, single-group cross-over designs are tedious to develop, and an adequate 'wash-out' period may be difficult to predict. A second weakness is not considering the different biological variables and racial and ethnic diversity and how that might impact outcomes. In sum, the authors have achieved the aims of the study, which will likely help move the field forward.

Reviewer #2 (Public Review):

Summary:

The authors investigated the effects of the timing of dietary occasions on weight loss and well-being with the aim of explaining if a consistent, timely alignment of dietary occasions throughout the days of the week could improve weight management and overall well-being. The authors attributed these outcomes to a timely alignment of dietary occasions with the body's own circadian rhythms. However, the only evidence the authors provided for this hypothesis is the assumption that the individual timing of dietary occasions of the study participants identified before the intervention reflects the body's own circadian rhythms. This concept is rooted in understanding of dietary cues as a zeitgeber for the circadian system, potentially leading to more efficient energy use and weight management. Furthermore, the primary outcome, body weight loss, was self-reported by the study participants.

Strengths:

The innovative focus of the study on the timing of dietary occasions rather than daily energy intake or diet composition presents a fresh perspective in dietary intervention research. The feasibility of the diet plan, developed based on individual profiles of the timing of dietary occasions identified before the intervention, marks a significant step towards personalised nutrition.

Weaknesses:

Several methodological issues detract from the study's credibility, including unclear definitions not widely recognized in nutrition or dietetics (e.g., "caloric event"), lack of comprehensive data on body composition, and potential confounders not accounted for (e.g., age range, menstrual cycle, shift work, unmatched cohorts, inclusion of individuals with normal weight, overweight, and obesity). The primary outcome's reliance on self-reported body weight and subsequent measurement biases further undermines the reliability of the findings. Additionally, the absence of registration in clinical trial registries, such as the EU Clinical Trials Register or clinicaltrials.gov, and the multiple testing of hypotheses which were not listed a priori in the research protocol published on the German Register of Clinical Trials impede the study's transparency and reproducibility.

Achievement of Objectives and Support for Conclusions:

The study's objectives were partially met; however, the interpretation of the effects of meal timing on weight loss is compromised by the weaknesses mentioned above. The evidence only partially supports some of the claims due to methodological flaws and unstructured data analysis.

Impact and Utility:

Despite its innovative approach, significant methodological and analytical shortcomings limit the study's utility. If these issues were addressed, the research could have meaningful implications for dietary interventions and metabolic research. The concept of timing of dietary occasions in sync with circadian rhythms holds promise but requires further rigorous investigation.

Reviewer #1 (Public Review):

In this work, the authors provide a valuable transcriptomic resource for the intermediate free-living transmission stage (miracidium larva) of the blood fluke. The single-cell transcriptome inventory is beautifully supplemented with in situ hybridization, providing spatial information and absolute cell numbers for many of the recovered transcriptomic states. The identification of sex-specific transcriptomic states within the populations of stem cells was particularly unexpected. The work comprises a rich resource to complement the biology of this complex system, however falls short in some technical aspects of the bioinformatic analyses of the generated sequence data.

(1) Four sequencing libraries were generated and then merged for analysis, however, the authors fail to document any parameters that would indicate that the clustering does not suffer from any batch effects.

(2) Additionally, the authors switch between analysis platforms without a clear motivation or explanation of what the fundamental differences between these platforms are. While in theory, any biologically robust observation should be recoverable from any permutation of analysis parameters, it has been recently documented that the two popular analysis platforms (Seurat - R and scanPy - python) indeed do things slightly differently and can give different results (https://www.biorxiv.org/content/10.1101/2024.04.04.588111v1). For this reason, I don't think that one can claim that Seurat fails to find clusters resolved by SAM without running a similar pipeline on the cluster alone as was done with SAM/scanPy here. The manuscript itself needs to be checked carefully for misleading statements in this regard.

(3) Similarly, the manuscript contains many statements regarding clusters being 'connected to', or forming a 'bridge' on the UMAP projection. One must be very careful about these types of statements, as the relative position of cells on a reduced-dimension cell map can be misleading (see Chari and Pachter 2023). To support these types of interpretations, the authors should provide evidence of gene expression transitions that support connectivity as well as stability estimates of such connections under different parameter conditions. Otherwise, these descriptors hold little value and should be dropped and the transcriptomic states simply defined as clusters with no reference to their positions on the UMAP.

(4) The underlying support for the clusters as transcriptomically unique identities is not well supported by the dot plots provided. The authors used very permissive parameters to generate marker lists, which hampers the identification of highly specific marker genes. This permissive approach can allow for extensive lists of upregulated genes for input into STRING/GO analyses, this is less useful for evaluating the robustness of the cluster states. Running the Seurat::FindAllMarkers with more stringent parameters would give a more selective set of genes to display and thereby increase the confidence in the reader as to the validity of profiles selected as being transcriptomically unique.

(5) Figure 5B shows a UMAP representation of cell positions with a statement that the clustering disappears. As a visual representation of this phenomenon, the UMAP is a very good tool, however, to make this statement you need to re-cluster your data after the removal of this gene set and demonstrate that the data no longer clusters into A/B and C/D. Also, as a reader, these data beg the question: which genes are removed here? Is there an over-representation of any specific 'types' of genes that could lead to any hypotheses of the function? Perhaps the STRING/GO analyses of this gene set could be informative.

(6) How do the proportions of cell types characterized via in situ here compare to the relative proportions of clusters obtained? It does not correspond to the percentages of the clusters captured (although this should be quantified in a similar manner in order to make this comparison direct: 10,686/20,478 = ~50% vs. 7%), how do you interpret this discrepancy? While this is mentioned in the discussion, there is no sufficient postulation as to why you have an overabundance of the stem cells compared to their presence in the tissue. While it is true that you could have a negative selection of some cell types, for example as stated the size of the penetration glands exceeds both that of the 10x capabilities (40uM), and the 30uM filters used in the protocol, this does not really address why over half of the captured cells represent 'stem cells'. A more realistic interpretation would be biological rather than merely technical. For example, while the composition of the muscle cells and the number of muscle transcriptomes captured are quite congruent at ~20%, the organism is composed of more than 50% of neurons, but only 15% of the transcriptomic states are assigned to neuronal. Could it be that a large fraction of the stem cells are actually neural progenitors? Are there other large inconsistencies between the cluster sizes and the fraction of expected cells? Could you look specifically at early transcription factors that are found in the neurons (or other cell types) within the various stem cell populations to help further refine the precursor/cell type relationships?

Reviewer #2 (Public Review):

Summary:

In this manuscript the authors have generated a single-cell atlas of the miracidium, the first free-living stage of an important human parasite, Schistosoma mansoni. Miracidia develop from eggs produced in the mammalian (human) host and are released into freshwater, where they can infect the parasite's intermediate snail host to continue the life cycle. This study adds to the growing single-cell resources that have already been generated for other life-cycle stages and, thus, provides a useful resource for the field.

Strengths:

Beyond generating lists of genes that are differentially expressed in different cell types, the authors validated many of the cluster-defining genes using in situ hybridization chain reaction. In addition to providing the field with markers for many of the cell types in the parasite at this stage, the authors use these markers to count the total number of various cell types in the organism. Because the authors realized that their cell isolation protocols were biasing the cell types they were sequencing, they applied a second method to help them recover additional cell types.

Schistosomes have ZW sex chromosomes and the authors make the interesting observation that the stem cells at this stage are already expressing sex (i.e. W)-specific genes.

Weaknesses:

The sample sizes upon which the in situ hybridization results and cell counts are based are either not stated (in most cases) or are very small (n=3). This lack of clarity about biological replicates and sample sizes makes it difficult for the reader to assess the robustness of the results and the extremely small sample sizes (when provided) are a missed opportunity to explore the variability of the system, or lack thereof.

Although assigning transcripts to a given cell type is usually straightforward via in situ experiments, the authors fail to consider the potential difficulty of assigning the appropriate nuclei to cells with long cytoplasmic extensions, like neurons. In the absence of multiple markers and a better understanding of the nervous system, it seems likely that the authors have overestimated the number of neurons and misassigned other cell types based on their proximity to neural projections.

The conclusion that germline genes are expressed in the miracidia stem cells seems greatly overstated in the absence of any follow-up validation. The expression scales for genes like eled and boule are more than 3 orders of magnitude smaller than those used for any of the robustly expressed genes presented throughout the paper. These scales are undefined, so it isn't entirely clear what they represent, but neither of these genes is detected at levels remotely high (or statistically significant) enough to survive filters for cluster-defining genes. Given that germ cells often develop early in embryogenesis and arrest the cell cycle until later in development, and that these transcripts reveal no unspliced forms, it seems plausible that the authors are detecting some maternally supplied transcripts that have yet to be completely degraded.

Reviewer #1 (Public Review):

Summary:

The article explores the connection between immunogenic cell death (ICD)-related genes and bladder cancer prognosis, immune infiltration, and response to therapy. The study identifies a risk-scoring model involving four ICD-related genes (CALR, IL1R1, IFNB1, IFNG), showing a correlation between higher risk scores and weaker anti-tumor immune function.

Strengths:

The significance lies in the potential for personalized treatment guidance in bladder cancer. The establishment of a risk-scoring model to predict patient survival is noteworthy.

Weaknesses:

However, the identification of ICD-related genes is somewhat conventional, focusing on known genes regulating cancer immune response. To enhance the significance of the risk-scoring model, it would be better if the authors could validate the model across various cancer types. The strength of evidence appears moderate, but broader applicability would strengthen the findings.

Reviewer #2 (Public Review):

Immunogenic cell death (ICD) can lead to the release of factors such as DAMPs which promote an adaptive immune response. In the context of cancer, there is clear evidence of anti-tumour benefits as a result of ICD, perhaps induced by chemotherapy.

Lilong et al used TCGA data to explore whether a previously published 34 gene 'ICD-related' signature could stratify bladder cancer patients by prognosis and ultimately predict patient survival. The gene signature contains many genes involved in inflammation and immunity (IFNg, IL6, TNF, IL17A, TLR4, CD8B, etc) and those related to ICD (such as CALR, HMGB1, HSP, NLRP3, etc). The authors divide patients into 'ICD-high' and '-low' based on the expression of this gene set and find that 'ICD-high' is associated with longer survival in TCGA bladder cancer data. The authors further argue that ICD-high group responds better to PD1 therapies. From this 34-gene signature, it appears that LASSO regularisation and Cox analysis identifies a four-gene 'risk' signature (CALR, IL1R1, IFNB1, IFNG) which is associated with shorter patient survival and lower immunotherapy response rates. This is the primary finding. Their methodology is very similar to a publication in 2021 in Frontiers in Immunology instead in the context of head and neck squamous cell carcinoma. This paper is not referenced.

In terms of the strengths of the work, it is certainly plausible that the author's four gene signature has an association with survival in bladder cancer, at least based on the two datasets studied. However, the relatedness of their findings to ICD is unconvincing, and glaring omissions from the manuscript in terms of methods limit confidence in the work. The authors show a potential association with bladder cancer patient survival and their four gene signatures, but substantial revisions are required for this to be appropriately evidenced.

Reviewer #2 (Public Review):

Summary:

The authors provide compelling evidence that stimulation of epidermal cells in Drosophila larvae results in the stimulation of sensory neurons that evoke a variety of behavioral responses. Further, the authors demonstrate that epidermal cells are inherently mechanoresponsive and implicate a role for store-operated calcium entry (mediated by Stim and Orai) in the communication to sensory neurons.

Strengths:

The study represents a significant advance in our understanding of mechanosensation. Multiple strengths are noted. First, the genetic analyses presented in the paper are thorough with appropriate consideration to potential confounds. Second, behavioral studies are complemented by sophisticated optogenetics and imaging studies. Third, identification of roles for store-operated calcium entry is intriguing. Lastly, conservation of these pathways in vertebrates raise the possibility that the described axis is also functional in vertebrates.

Weaknesses:

The study has a few conceptual weaknesses that are arguably minor. The involvement of store-operated calcium entry implicates ER calcium store release. Whether mechanical stimulation evokes ER calcium release in epidermal cells and how this might come about (e.g., which ER calcium channels, roles for calcium-induced calcium release etc.) remains unaddressed. On a related note, the kinetics of store-operated calcium entry is very distinct from that required for SV release. The link between SOC and epidermal cells-neuron transmission is not reconciled. Finally, it is not clear how optogenetic stimulation of epidermal cells results in the activation of SOC.

Reviewer #1 (Public Review):

Summary:

In this meticulously conducted study, the authors show that Drosophila epidermal cells can modulate escape responses to noxious mechanical stimuli. First, they show that activation of epidermal cells evokes many types of behaviors including escape responses. Subsequently, they demonstrate that most somatosensory neurons are activated by activation of epidermal cells, and that this activation has a prolonged effect on escape behavior. In vivo analyses indicate that epidermal cells are mechanosensitive and require stored-operated calcium channel Orai. Altogether, the authors conclude that epidermal cells are essential for nociceptive sensitivity and sensitization, serving as primary sensory noxious stimuli.

Strengths:

The manuscript is clearly written. The experiments are logical and complementary. They support the authors' main claim that epidermal cells are mechanosensitive and that epidermal mechanically evoked calcium responses require the stored-operated calcium channel Orai. Epidermal cells activate nociceptive sensory neurons as well as other somatosensory neurons in Drosophila larvae, and thereby prolong escape rolling evoked by mechanical noxious stimulation.

Weaknesses:

Core details are missing in the protocols, including the level of LED intensity used, which are necessary for other researchers to reproduce the experiments. For most experiments, the epidermal cells are activated for 60 s, which is long when considering that nocifensive rolling occurs on a timescale of milliseconds. It would be informative to know the shortest duration of epidermal cell activation that is sufficient for observing the behavioral phenotype (prolongation of escape behavior) and activation of sensory neurons.

Reviewer #1 (Public Review):

This is a very interesting study by Kyle Spinler et al., demonstrating the novel role of MSI2-HOXA9 translocation in the development and pathogenesis of blast crisis CML. The authors employed appropriate in vitro and in vivo assays, including a sophisticated transplantation-based model of CML, which is well-established in the field of studying the pathogenesis of CML. Additionally, the authors successfully concluded that the MSI2 RNA binding domain RRM1 has a preferential impact on the growth of blast crisis CML.

The quality of this research article could be significantly enhanced by addressing the following points:

Major:

(1) Do mice with BCR-ABL/MSI2-HOXA9 leukemia have an increased pool of leukemic stem cells (LSC), or do they have an increased propensity to develop blast cells? Is it the number of LSCs that has increased, or is it the function of LSC to give rise to the disease that has increased? It is not clear if the detected differences in Lineage-negative cells (Figure S1D) were detected in vitro in retrovirally transduced cells or were detected in vivo in transplanted mice. If the differences were detected in vitro, could the author confirm the same findings in vivo? This will greatly enhance the understanding of in vivo disease pathogenesis and could directly link the aggressivity of the disease (shortened survival) with an increased stem cell-like population.

(2) The authors suggest that BCR-ABL/MSI2-HOXA9 leads to the development of blast crisis-CML. One of the main characteristics of blast crisis-CML is drug resistance. Is BCR-ABL/MSI2-HOXA9 leukemia resistant to classical CML treatment drugs?

(3) The authors have emphasized the heightened expression of Polrmt in delineating the mitochondrial phenotype of BCR-ABL/MSI2-HOXA9 leukemia cells. However, the regulatory mechanism governing the expression of Polrmt by MSI2-HOXA9 has not been clearly demonstrated by the authors. Unveiling this mechanism would constitute a novel finding and significantly elevate the quality of the research.

(4) Did the authors observe any survival differences between BCR-ABL/NUP98-HOXA9 and BCR-ABL/MSI2-HOXA9?

Reviewer #2 (Public Review):

The manuscript titled, "Identification of a Musashi2 translocation as a novel oncogene in myeloid leukemia" by Spinler et al. studies the functional role of the translocation t(7;17)(p15;q23), resulting in MSI2/HOXA9 fusion gene, as a secondary driver in bcCML. MSI2-HOXA9 forced expression along with BCR-ABL enhances colony formation and leads to a more aggressive disease in vivo. Depletion of the RNA binding domain RRM1 or RRM2 of MSI2 led to a significant reduction in colony formation, with RRM1 depletion specifically impacting differentiation and blast cell counts. Mechanistically, the authors find that MSI2-HOXA9 aberrantly localizes to the nucleus, elevating the expression of mitochondrial polymerase Polrmt, thereby leading to upregulation of mitochondrial components and enhancing mitochondrial function and basal respiration. Overall, this study examines how the rare MSI2-HOXA9 fusion gene can act as a novel cooperating oncogene and could serve as a secondary hit in the progression of CML to blast crisis.

Strengths:

(1) Demonstration that MSI2-HOXA9 contributes to oncogenesis in the BCR-ABL context.

(2) Development of a novel cooperativity model for BCR-ABL and provides additional supporting data for the role of MSI2 in leukemogenesis.

(3) Evidence that MSI2-HOXA9 acts uniquely compared to MSI2 alone through nuclear vs. cytoplasmic localization and activation of mitochondrial polymerase Polrmt.

Weaknesses:

(1) MSI2-HOXA9 fusion is extremely rare as it has been only found in a handful of patients and it is not clear whether other MSI2 fusions function in a similar manner.

(2) The mechanism needs to be strengthened since MSI2 alone or the HOXA9 mutant may not be linked to the mitochondrial mechanism.

(3) It is not clear that the mitochondrial pathway is sufficient for the MSI2-HOXA9 oncogenic mechanism.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigate the contributions of the long noncoding RNA snhg3 in liver metabolism and MAFLD. The authors conclude that liver-specific loss or overexpression of Snhg3 impacts hepatic lipid content and obesity through epigenetic mechanisms. More specifically, the authors invoke that the nuclear activity of Snhg3 aggravates hepatic steatosis by altering the balance of activating and repressive chromatin marks at the Pparg gene locus. This regulatory circuit is dependent on a transcriptional regulator SNG1.

Strengths:

The authors developed a tissue-specific lncRNA knockout and KI models. This effort is certainly appreciated as few lncRNA knockouts have been generated in the context of metabolism. Furthermore, lncRNA effects can be compensated in a whole organism or show subtle effects in acute versus chronic perturbation, rendering the focus on in vivo function important and highly relevant. In addition, Snhg3 was identified through a screening strategy and as a general rule the authors the authors attempt to follow unbiased approaches to decipher the mechanisms of Snhg3.

Weaknesses:

Despite efforts at generating a liver-specific knockout, the phenotypic characterization is not focused on the key readouts. Notably missing are rigorous lipid flux studies and targeted gene expression/protein measurement that would underpin why the loss of Snhg3 protects from lipid accumulation. Along those lines, claims linking the Snhg3 to MAFLD would be better supported with careful interrogation of markers of fibrosis and advanced liver disease. In other areas, significance is limited since the presented data is either not clear or rigorous enough. Finally, there is an important conceptual limitation to the work since PPARG is not established to play a major role in the liver.

Reviewer #2 (Public Review):