Reviewer #1 (Public Review):

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

Reviewer #2 (Public Review):

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

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

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

Reviewer #3 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #2 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #3 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

Reviewer #2 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

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

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

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

Reviewer #3 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Joint Public Review

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #2 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #2 (Public Review):

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

Reviewer #3 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

Strengths of this paper

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

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

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

Weakness of this paper

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

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

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

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

Reviewer #1 (Public Review):

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

Strengths:

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

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

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

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

Weaknesses:

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

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

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

Reviewer #2 (Public Review):

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

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

Reviewer #3 (Public Review):

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

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

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

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

Reviewer #4 (Public Review):

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

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

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

Specific Comments

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #2 (Public Review):

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

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

Reviewer #3 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

There are two other points of interest, that deserve future investigation:

1) The authors performed immunolocalizations of Arp2 and pharmacological inhibitions of Arp2/3, and found some possible effect on honeycomb lattice development. The inter-ridge region of the butterfly Papilio polytes, which lacks these structures, did not seem to be affected by drug treatments. Effects were time-dependent, which makes sense. These data provide circumstantial evidence that Arp2/3 is involved in the late role of F-actin formation or re-organisation.

2) The authors perform a comparative study in additional papilionids (Fig. 6 in particular). I find these data to be quite limited without a dense sampling, but they are nonetheless interesting and support a second-phase role of F-actin re-organisation.

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

Reviewer #2 (Public Review):

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

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

Reviewer #1 (Public Review):

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

Comments on current version:

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

Reviewer #2 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

Strengths of this study

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

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

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

Weaknesses of this study

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

The authors may wish to consider the following specific points:

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

Reviewer #3 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

There aren't many; please find list below:

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

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

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

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

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

Reviewer #3 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

Weaknesses:

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

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

Reviewer #3 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

The main weaknesses of this study are:

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

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

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

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

Reviewer #2 (Public Review):

Summary:

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

Strengths:

The paper contains novel, important information.

Weaknesses:

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

Reviewer #3 (Public Review):

Summary:

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

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

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public Review):

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

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

Weaknesses: Methodological descriptions are minimal.

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #3 (Public Review):

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

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

Reviewer #3 (Public Review):

The major strength of this manuscript is the "anvi-estimate-metabolism' tool, which is already accessible online, extensively documented, and potentially broadly useful to microbial ecologists. However, the context for this tool and its validation is lacking in the current version of the manuscript. It is unclear whether similar tools exist; if so, it would help to benchmark this new tool against prior methods. Simulated datasets could be used to validate the approach and test its robustness to different levels of bacterial richness, genome sizes, and annotation level.

The concept of metabolic independence was intriguing, although it also raises some concerns about the overinterpretation of metagenomic data. As mentioned by the authors, IBD is associated with taxonomic shifts that could confound the copy number estimates that are the primary focus of this analysis. It is unclear if the current results can be explained by IBD-associated shifts in taxonomic composition and/or average genome size. The level of prior knowledge varies a lot between taxa; especially for the IBD-associated gamma-Proteobacteria. It can be difficult to distinguish genes for biosynthesis and catabolism just from the KEGG module names and the new normalization tool proposed herein markedly affects the results relative to more traditional analyses. As such, it seems safer to view the current analysis as hypothesis-generating, requiring additional data to assess the degree to which metabolic dependencies are linked to IBD.

Reviewer #1 (Public Review):

In this work, Veseli et al. present a computational framework to infer the functional diversity of microbiomes in relation to microbial diversity directly from metagenomic data. The framework reconstructs metabolic modules from metagenomes and calculates the per-population copy number of each module, resulting in the proportion of microbes in the sample carrying certain genes. They applied this framework to a dataset of gut microbiomes from 109 inflammatory bowel disease (IBD) patients, 78 patients with other gastrointestinal conditions, and 229 healthy controls. They found that the microbiomes of IBD patients were enriched in a high fraction of metabolic pathways, including biosynthesis pathways such as those for amino acids, vitamins, nucleotides, and lipids. Hence, they had higher metabolic independence compared with healthy controls. To an extent, the authors also found a pathway enrichment suggesting higher metabolic independence in patients with gastrointestinal conditions other than IBD indicating this could be a signal for a general loss in host health. Finally, a machine learning classifier using high metabolic independence in microbiomes could predict IBD with good accuracy. Overall, this is an interesting and well-written article and presents a novel workflow that enables a comprehensive characterization of microbiome cohorts.

Reviewer #2 (Public Review):

This study builds upon the team's recent discovery that antibiotic treatment and other disturbances favour the persistence of bacteria with genomes that encode complete modules for the synthesis of essential metabolites (Watson et al. 2023). Veseli and collaborators now provide an in-depth analysis of metabolic pathway completeness within microbiomes, finding strong evidence for an enrichment of bacteria with high metabolic independence in the microbiomes associated with IBD and other gastrointestinal disorders. Importantly, this study provides new open-source software to facilitate the reconstruction of metabolic pathways, estimate their completeness and normalize their results according to species diversity. Finally, this study also shows that the metabolic independence of microbial communities can be used as a marker of dysbiosis. The function-based health index proposed here is more robust to individuals' lifestyles and geographic origin than previously proposed methods based on bacterial taxonomy.

The implications of this study have the potential to spur a paradigm shift in the field. It shows that certain bacterial taxa that have been consistently associated with disease might not be harmful to their host as previously thought. These bacteria seem to be the only species that are able to survive in a stressed gut environment. They might even be important to rebuild a healthy microbiome (although the authors are careful not to make this speculation).

This paper provides an in-depth discussion of the results, and limitations are clearly addressed throughout the manuscript. Some of the potential limitations relate to the use of large publicly available datasets, where sample processing and the definition of healthy status varies between studies. The authors have recognised these issues and their results were robust to analyses performed on a per-cohort basis. These potential limitations, therefore, are unlikely to have affected the conclusions of this study.

Overall, this manuscript is a magnificent contribution to the field, likely to inspire many other studies to come.

Reviewer #1 (Public Review):

Summary of the major findings -

1. The authors used saturation mutagenesis and directed evolution to mutate the highly conserved fusion loop (98 DRGWGNGCGLFGK 110) of the Envelope (E) glycoprotein of Dengue virus (DENV). They created 2 libraries with parallel mutations at amino acids 101, 103, 105-107, and 101-105 respectively. The in vitro transcribed RNA from the two plasmid libraries was electroporated separately into Vero and C6/36 cells and passaged thrice in each of these cells. They successfully recovered a variant N103S/G106L from Library 1 in C6/36 cells, which represented 95% of the sequence population and contained another mutation in E outside the fusion loop (T171A). Library 2 was unsuccessful in either cell type.

2. The fusion loop mutant virus called D2-FL (N103S/G106L) was created through reverse genetics. Another variant called D2-FLM was also created, which in addition to the fusion loop mutations, also contains a previously published, evolved, and optimized prM-furin cleavage sequence that results in a mature version of the virus (with lower prM content). Both D2-FL and D2-FLM viruses grew comparably to wild type virus in mosquito (C6/36) cells but their infectious titers were 2-2.5 log lower than wildtype virus when grown in mammalian (Vero) cells. These viruses were not compromised in thermostability, and the mechanism for attenuation in Vero cells remains unknown.

4. Next, the authors probed the neutralization of these viruses using a panel of monoclonal antibodies (mAbs) against fusion loop and domain I, II and III of E protein, and against prM protein. As intended, neutralization by fusion loop mAbs was reduced or impaired for both D2-FL and D2-FLM, compared to wild type DENV2. D2-FLM virus was equivalent to wild type with respect to neutralization by domain I, II, and III antibodies tested (except domain II-C10 mAb) suggesting an intact global antigenic landscape of the mutant virion. As expected, D2-FLM was also resistant to neutralization by prM mAbs (D2-FL was not tested in this batch of experiments).

5. Finally, the authors evaluated neutralization in the context of polyclonal serum from convalescent humans (n=6) and experimentally infected non-human primates (n=9) at different time points (27 total samples). Homotypic sera (DENV2) neutralized D2-FL, D2-FLM, and wild type DENV similarly, suggesting that the contribution of fusion loop and prM epitopes is insignificant in a serotype-specific neutralization response. However, heterotypic sera (DENV4) neutralized D2-FL and D2-FLM less potently than wild type DENV2, especially at later time points, demonstrating the contribution of fusion loop- and prM-specific antibodies to heterotypic neutralization.

Impact of the study-

1. The engineered D2-FL and D2-FLM viruses are valuable reagents to probe antibodies targeting the fusion loop and prM in the overall polyclonal response to DENV.

2. Though more work is needed, these viruses can facilitate the design of a new generation of DENV vaccine that does not elicit fusion loop- and prM-specific antibodies, which are often poorly neutralizing and lead to antibody-dependent enhancement effect (ADE).

3. This work can be extended to other members of the flavivirus family.

4. A broader impact of their work is a reminder that conserved amino acids may not always be critical for function and therefore should not be immediately dismissed in substitution/mutagenesis/protein design efforts.

Appraisal of the results -

The data largely support the conclusions, but some improvements and extensions can benefit the work.

1. In Figure 3A, the authors concluded that the engineered dengue virus fusion loop mutant viruses are insensitive to monoclonal antibodies (mAbs) targeting the fusion loop. However, the reduction in neutralization sensitivity varied depending on the mAb tested. The contribution of the optimized prM cleavage site (D2-FLM) to sensitivity to fusion loop mAbs also varied.

a) Are the epitopes known for these mAbs? It would be useful to discuss how the epitope of 1M7 differs from the other mAbs. What are the critical residues?<br /> d) Maybe the D2-FL mutant can be further evolved with selection pressure with fusion loop mAbs 1M7 +/-1N5 and/or other fusion loop mAbs.

2. It would have been useful to include D2-M for comparison (with evolved furin cleavage sequence but no fusion loop mutations).

3. Data for polyclonal serum can be better discussed. Table 1 is not discussed much in the text.

Suggestions for further experiments-

1. It would be interesting to see the phenotype of single mutants N103S and G106L, relative to double mutant N103S/G106L (D2-FL).<br /> 2. The fusion capability of these viruses can be gauged using liposome fusion assay under different pH conditions and different lipids.<br /> 3. Correlative antibody binding vs neutralization data would be useful.

Reviewer #2 (Public Review):

Antibody-dependent enhancement (ADE) of Dengue is largely driven by cross-reactive antibodies that target the DENV fusion loop or pre-membrane protein. Screening polyclonal sera for antibodies that bind to these cross-reactive epitopes could increase the successful implementation of a safe DENV vaccine that does not lead to ADE. However, there are few reliable tools to rapidly assess the polyclonal sera for epitope targets and ADE potential. Here the authors develop a live viral tool to rapidly screen polyclonal sera for binding to fusion loop and pre-membrane epitopes. The authors performed a deep mutational scan for viable viruses with mutations in the fusion loop (FL). The authors identified two mutations functionally tolerable in insect C6/36 cells, but lead to defective replication in mammalian Vero cells. These mutant viruses, D2-FL and D2-FLM, were tested for epitope presentation with a panel of monoclonal antibodies and polyclonal sera. The D2-FL and D2-FLM viruses were not neutralized by FL-specific monoclonal antibodies demonstrating that the FL epitope has been ablated.

Overall the central conclusion that the engineered viruses can predict epitopes targeted by antibodies is supported by the data and the D2-FL and D2-FLM viruses represent a valuable tool to the DENV research community.

Reviewer #1 (Public Review):

This study investigated an important question in human reproduction: why most fully aneuploid embryos is incompatible with normal fetal development. Specifically, the authors investigated the cellular responses to aneuploidy through analysis of gene expression in a set of donated human blastocysts. The samples included uniform aneuploid embryos of meiotic origin and mosaic aneuploid embryos from the SAC inhibitor reversine treatment. The authors relied mainly on low-input RNA sequencing and immunofluorescence staining. Pathway analysis with RNA-seq data of trophectoderm cells suggested activation of p53 and possibly apoptosis, and this cellular signature appeared to be stronger in TE cells with a higher degree of aneuploidy. Immunostaining also found some evidence of apoptosis, increased expression of HSP70 and autophagy in some aneuploid cells. With combinational OCT4 and GATA4 as lineage markers, it appeared that aneuploidy could alter the second lineage segregation and primitive endoderm formation in particular.

Although this study is largely descriptive, it generated valuable RNA-seq data from a set of aneuploid TE cells with known karyotypes. Immunostaining results in general were consistent with findings in mouse embryos and human gastruloids.

While there is a scarcity of human embryo materials for research, the lack of single cell level data limits further extension of the presented data on the consequences of mosaic embryos. A major concern is that the gene list used for pathway analysis is not FDR controlled. It is also unclear how the many plots generated with the "supervised approach" were actually performed. The authors also appear to have ignored the possibility that high-dosage group could have a higher mitotic defects. Assuming a fully aneuploid embryo, why do only some cells display p53 and autophagy marker? The conclusion about proteotoxic stress was largely based on staining of HSP70. It appears from Figure 3 d,h that the same cells exhibited increased HSP70 and CASP8 staining. Since HSP70 is known to have anti-apoptotic effect, could the increased expression of Hsp70 be an anti-apoptotic response?

Reviewer #2 (Public Review):

A high fraction of cells in early embryos carry aneuploid karyotypes, yet even chromosomally mosaic human blastocysts can implant and lead to healthy newborns with diploid karyotypes. Previous studies in other models have shown that genotoxic and proteotoxic stresses arising from aneuploidy lead to the activation of the p53 pathway and autophagy, which helps eliminate cells with aberrant karyotypes. These observations have been here evaluated and confirmed in human blastocysts. The study also demonstrates that the second lineage and formation of primitive endoderm are particularly impaired by aneuploidy.

This is a timely and potentially important study. Aneuploidy is common in early embryos and has a negative impact on their development, but the reasons behind this are poorly understood. Furthermore, how mosaic aneuploid embryos with a fraction of euploidy greater than 50 % can undergo healthy development remains a mystery. Most of our current information comes from studies on murine embryos, making a substantial study on human embryos of great importance. However, there are only very few new findings or insights provided by this study. Some of the previous findings were reproduced, but it is difficult to say whether this is a real finding, or whether it is a consequence of a low sample number. The authors could get much more insight with their data.

Reviewer #1 (Public Review):

Understanding the ecology including the dietary ecology of enantiornithines is challenging by all means. This work explores the possible trophic diversity of the "opposite-bird" enantiornithines by referring to the body mass, jaw mechanical advantage, finite element analysis of the jaw bones, and morphometrics of the claws and skull of both fossil and extant avian species. By incorporation of the dietary information of longipterygids and pengornithinds, the authors predicted a wide variety of foods for enantiornithine ancestors. This indicates the evolutionary successes of enantiornitine during Cretaceous is very likely to have been driven by the wide range of recipes. I believe this work represented the most comprehensive analysis of enantiornithines' diet and trophic diversity by far and the first systematic dietary analysis of bohaiornithids, though the analysis themselves are largely based on the indirect evidence including jaw bone morphologies and claw and skull morphometrics. Anyway, I believe the authors did most the paleontologists could do, and I do not know whether the conclusions could be further supported by incorporating some geochemical data, as most of the specimens the authors analyzed were recovered from a small geographic area. The results also indicate that the developmental trajectories of enantiornithines, at least for jaw bones, might also have been diverse to some extent in response to the diverse ecological niches they adapted. My only concern regarding the analysis is to what extent the conclusions are convincing by comparing specimens representing various ontogenetic stages.

Reviewer #2 (Public Review):

Miller et al. take a variety of measurements and analytical techniques to assess the ecology of various species of the enantiornithine clade Bohaiornithidae. From this they suggest that the ancestral enantiornithine was a generalist and that the descendant clades occupied a breadth of niches similar to that of the radiation of derived birds after the K-Pg extinction.

I am not a statistician so I found much of the paper to be outside my ability to review. I also am not an expert on enantiornithines or cranial morphology of birds, so these areas I also am not the best reviewer.

However, I have published on bird foot functional morphology, notably that of birds of prey. This area thus is where I concentrated my efforts in the review.

Overall, I find the idea that enantiornithines had occupied a similar niche breadth to post-K-Pg derived birds to be a curious, thought provoking proposal. On methodology, I have a few questions about bird feet comparisons. Whether my comments require minor or major edits is not really possible to say since I am not commenting on e.g. the skull-based analyses.

STRENGTHS<br /> The paper uses a multi-proxy approach to assess ecological categories. This is broader than in previous works and is to be commended. I am not well placed to comment on the specifics of the statistical methods however.

LANGUAGE<br /> The manuscript is very well written. I don't recall seeing many or possibly any grammatical issues. That's rare these days and I commend the authors on checking their manuscript and making it readable. This said, I found the extensive use of acronyms and abbreviations to be difficult to follow. This is not much of a criticism but in a general-readership journal, perhaps not having everything abbreviated might be preferential.

The manuscript uses phrases like "superficially resembles" and "is similar to" a lot. I'm trying not to be picky, but very often these phrasings don't say how the features are similar (or not). Is it the curvature etc? Could these be expanded upon a bit more in the text please? It isn't very easy to assess similarity r dissimilarity without some point of reference.

FIGURES<br /> The figures are generally very good, and the captions are generously descriptive. However, all figures are graphs, tables, etc. It would be nice, somewhere, to have an image or group of images showing us what a bohaiornithine is.. especially since this is a general-readership journal. I wasn't aware of the details of enantiornithine clades before reading this manuscript, and I suspect other readers would be in the same place. Can we get some images of fossils, a skeletal diagram, or something?

RAPTOR CLAWS<br /> This is my main criticism.

The foot morphometrics suggest that there is a morphological difference between claws of raptors that feed on large prey, and those of raptors that feed on small prey. I am curious what these morphological differences are.

In our paper(s) (Fowler et al., 2009; 2011), we looked at the feet (especially the claws) of various birds of prey, and studied foot functional morphology compared with prey choice, capture and immobilization strategy. We devised a behavioural categorization that separated the behavior (mainly in subduing the prey) between "small" and "large" prey, that being whether they can be fully contained within the foot of the raptor. Most if not all raptors take small prey, and these are typically killed using constriction. Some raptors have specialized in small prey/constriction (e.g. most owls). Some raptors might also take large prey, but since (by definition) large prey cannot be fully contained within the foot then the prey item cannot be constricted and a different immobilization (kill) mechanism must be employed (which differs among clades).

We never made a morphological distinction between small and large prey specialists largely because all raptors take small prey. I am thus interested in what taxa are designated small vs large prey specialists in this study. Perhaps these authors have found characters that distinguish primarily small-prey-specialist raptors, but I do not know what they are and maybe this should be included in the text somewhere.

Owls are mainly small prey specialists. Compared with other raptors, they have a unusual foot that has (I am generalising here) short non-ungual phalanges contrasting with long ungual phalanges which are relatively low curvature. We (Fowler et al 2009) suggest that this gives owls a more tightly closable foot (short non-ungual phalanges), but maintains reach of each toe (long claw). This could be seen as indicative of small -prey specialization, but again, other raptor clades take small prey without this very specialized foot. If the "small prey specialist" category here is really just owls then it might be slightly misleading.

This is my main criticism. I would at least like some explanation of what is in this category.

Otherwise I must leave assessment of cranial functional morphology, and general statistical analysis to other reviewers.

IMPACT<br /> As I have already stated, the idea that Enantiornithines occupied a similar breadth of niches to post K-Pg birds is thought provoking, moreso than upon initial reading. The authors note that this raises questions about the adaptations or survivorship of derived birds, and this is what I find most intriguing, and is what I think will appeal to most readers.

Reviewer #3 (Public Review):

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

The approaches used by the authors are generally appropriate for the questions being asked, their comparisons are thorough, and the interpretations are generally reasonable. However, there are a number of major flaws to the comparisons used that should at least be addressed by the authors, if not overcome by modifying the methodology. Smaller concerns/comments are provided in "Recommendations for the authors."

My first major concern is about how the presence of teeth might influence both qualitative and quantitative comparisons to extant birds. The authors should discuss how the presence of teeth might facilitate or prevent feeding strategies that might be inconsistent with (for example) patterns reconstructed using finite element analysis for a comparative sample of toothless birds.

Next, the authors should discuss the potential impact that cranial kinesis might have on the functionality of the jaws - especially with regards to the mitigation of stresses experienced by the skull. Do the quantitative approaches used here to characterize the mechanics of the jaws account for kinesis in extant birds? If so, how? If not, how do the authors' account for that mechanical difference in their interpretations?

My next concern regards potential biases introduced by the approach taken to reconstruct the bohaiornithid skulls sampled here. Using elements from closely related taxa to fill out an incomplete skull during reconstruction is reasonable, but it may influence the results of subsequent shape comparisons - especially when the "donor" skull is compared to the recipient. The authors should explain how they accounted for this possibility in their methods or their interpretations.

Next, it is unclear how or where much of the data used or generated by this study are made available. I appreciate that the authors thoroughly cite the literature from which some data (e.g., extant FEA data), but all data used should be provided in the supplement. Likewise for the FEA models generated for the newly sampled taxa. The authors indicate that some R scripts are available online (Lines 787-788), but that link is currently non-functional, so I could not verify what was made available. And unless I missed it, the authors don't indicate that other data (e.g., FEA models) are also available there. Any data used in, or generated by, this paper should be made available online - including FEA models, tree files and analysis output files.

Also pertaining to the methods, in some places, the methods the authors used to analyze their data were not specified. For example, the authors mention that "all analyses of the [MA/FEA] data were performed in R" and "scripts [are] available" online (Lines 786-787), but the authors don't specify what those analyses actually are - unless that was specified elsewhere and I missed it? I know very little about FEA or MA analyses, so maybe these approaches are well understood in those circles, but I am unable to assess the approaches here without downloading and digging into the scripts.

A broader recommendation here: in several places, I found this paper difficult to follow. That's partly understandable, the authors are discussing and comparing trends across a wide variety of data types and analyses - which is certainly both challenging and commendable. But that variety of analyses has resulted in a staggering variety of acronyms that I found nearly impossible to keep track of. Minimally, I recommend that the authors redefine the most important acronyms at the start of each major subheading.

Related to that last point, in the discussion, I often found myself missing the forest for the trees, so to speak - the authors paid much attention to interpreting the results of each analytical approach for each taxon (which I appreciate), but I found it difficult to keep track of the take-home message the authors were trying to convey. I would recommend a reorganization of the discussion that follows a backbone based on the authors' key messages - for example, a section on species-level interpretations (maybe with sub-headings for each approach discussed), followed by larger-picture discussions of Bohaiornithidae and Enantiornithes more generally. The authors included a section at the end of their discussion that already provides that larger picture for Enantiornithes, but the section on "Bohaiornithid Ecology and Evolution" includes a lot of species-level comparison that I think would be better suited for species-focused sub-sections, and I think the paper would be better served by reserving this section for a bohaiornithid-level survey.

Reviewer #2 (Public Review):

This manuscript reports on the role of Rho-associated coiled-coil kinase (ROCK) in biomineralization of sea urchin larval skeletons. A number of experiments examine the initiation, growth, and patterning of the skeleton in an effort to determine if, and how, ROCK participates in skeletal formation. The authors conclude that ROCK controls the formation, growth, and morphology (patterning) of the skeleton based on a number of inhibition studies. The main target of the experiments is the actomyosin cytoskeleton which has been the focus of many ROCK studies in vertebrates. Based on similar experimental outcomes when comparing the results here with published data from vertebrates, they suggest that ROCK and the actomyosin network operate in a similar way in biomineralization despite independent evolutionary origins of the sea urchin larval skeletons and the skeletons of vertebrates.

My concerns are the interpretation of the experiments. The main overriding concern is a possible over-interpretation of the role of ROCK. In the literature that ROCK participates in many biological processes with a major contribution to the actin cytoskeleton. And when a function is attributed to ROCK, it is usually based on the determination of a protein that is phosphorylated by this kinase. Here that is not the case. The observation here is in most cases stunted growth of the spicule skeleton and some mis-patterning occurs or there is an absence of skeleton if the inhibitor is added prior to initiation of skeletal growth. They state in the abstract that ROCK impairs the organization of F-actin around the spicules. The evidence for that as a direct role is absent. They use morpholino data and ROCK inhibitor data to draw their conclusion. My main concern is the concentration of the inhibitor used since at the high concentrations used, the inhibitor chosen is known to inhibit other kinases as well as ROCK (PKA and PKC). They indicate that this inhibition is specifically in the skeletogenic cells based on the isolation of skeletogenic cells in culture and spicule production either under control or ROCK inhibition and they observe the same - stunting and branching or absence of skeletons if treated before skeletogenesis commences. Again, however, the high concentrations are known to inhibit the other kinases. They use blebbistatin and latrunculin and show that these known inhibitors of actin cytoskeleton lead to abnormal spiculogenesis, This coincidence is suggestive but is not proof that it is ROCK acts on the actomyosin cytoskeleton given the specificity concerns.

Reviewer #1 (Public Review):

Using a pharmacological and knock-down approach, the authors could demonstrate that ROCK activity is required for the normal development of the larval skeleton. The presence of ROCK in the pluteus stage depends on the activity of VEGF that is responsible for the formation of the tubular syncytial sheath of the calcifying primary mesenchyme cells in which the skeleton forms. The importance of ROCK in skeleton formation was confirmed in cell culture experiments, demonstrating that ROCK inhibition leads to decreased elongation and abnormal branching of spicules. µCT analyses underline this finding demonstrating that the inhibition of ROCK mainly affects the elongation of spicules while growth in girth is little affected. F-actin labeling experiments could demonstrate that ROCK inhibition interferes with the organization of the actomyosin network in the early phase of skeleton formation, while f-actin organization in the tips of the elongating spicule is unaffected by the pharmacological inhibition of ROCK. Finally, ROCK inhibition strongly affects the expression of major regulatory and calcification-related genes in the calcifying cells. Based on these findings the authors propose a model for the regulatory interaction between the skeletogenic GRN, ROCK, and the f-actin system relevant for skeletogenesis.

I reviewed this paper previously for submission to another Journal. I emphasize again, that this is an interesting and important work that aims to uncover the interaction between the Rho-associated Kinase, ROCK, the actomyosin network, and its relevance for the formation of the calcitic skeleton of the sea urchin larva. I carefully went through the revised manuscript. In their new version, the authors rearranged the figures to provide a more direct comparison between the in vivo and cell culture experiments which mitigates the criticism of collateral effects by the inhibitors on the whole organism. The authors also performed an additional experiment localizing the F-Actin signal in spicules of PMC cell cultures under ROCK inhibition. This experiment strengthens the concept that ROCK activity is important for tip dominance rather than CaCO3 deposition rates. The results section was substantially reorganized and only very minor changes were made to the introduction and discussion.

I think that this work has great potential to provide seminal insights into an understudied aspect of the biomineralization process - the role and regulation of the cytoskeleton in calcifying cells. As I mentioned in my previous review there are some gaps in this work that need to be answered to provide a conclusive dataset on the role of ROCK and the actomyosin system in the mineralization process. The manuscript in its current form provides evidence for the interaction of ROCK with the actomyosin system in the sea urchin larva and that perturbation of this system affects skeletogenesis. However, it is missing an explanation regarding the mechanism by which ROCK affects skeleton formation. No difference in f-actin localization was found at the spicule tips in control and ROCK-inhibited larvae. A slight hint was found in the difference in vesicle size and f-actin organization within calcifying cells, but it remains unresolved if ROCK activity impacts the trafficking of calcification vesicles. The authors provide an interesting discussion on the involvement of f-actin and ROCK on vesicular trafficking, and exocytosis based on existing knowledge from animal and plant models. But for the sea urchin larva, this important link between ROCK, f-actin, and the biomineralization process remains unanswered. In their previous work by Winter et al. 2021, the authors demonstrated excellent technologies to monitor vesicular dynamics in the calcifying cells. This tool would be ideal to investigate the role of ROCK and the actomyosin network on the trafficking dynamics of Ca2+-rich vesicles. These experiments (among others suggested in the following review) may help to uncover the critical mechanism to resolve the missing gap in this manuscript.

Major comments<br /> One MASO led to reduced skeleton formation while the other one additionally induced ectopic branching. How was the optimum concentration for the MASOs determined? Did the authors perform a dose-response curve? What is the reason for this difference? Which of the two MASOs can be validated by reduced ROCK protein abundance? Since the ROCK antibody works, I would like to see a control experiment on Rock protein abundance in control and ROCK MO injected larvae which is the gold-standard for validating the knock-down.

L212 "Together, these measurements show that ROCK is not required for the uptake of calcium into cells." But what about trafficking and exocytosis? As mentioned earlier, I think this is a really important point that needs to be confirmed to understand the function of ROCK in controlling calcification. In their previous study (reference 45) the authors demonstrated that they have superior techniques in measuring vesicle dynamics in vivo. Here an acute treatment with the ROCK inhibitor would be sufficient to test if calcein-positive vesicle motion, including the observed reduction in velocity close to the tissue skeleton interface, is affected by the inhibitor.

Is there a colocalization of ROCK and f-actin in the tips of the spicules? This would support the mechano-sensing-hypothesis by ROCK.

L 283. "F-actin is enriched at the tips of the spicules independently of ROCK activity" The results of this paragraph clearly demonstrate that ROCK inhibition has no effect on the localization of f-actin at the tips of the growing spicules. In addition, the new cell culture experiments underline this observation. Still, the central question that remains is, what is the interaction between ROCK, f-actin, and the mineralization process, that leads to the observed deformations? What does the f-actin signal look like in a branched phenotype or in larvae that failed to develop a skeleton (inhibition from Y20)?

Immunohistochemical analyses on f-actin localization and abundance should be additionally performed with ROCK knock-down phenotypes to confirm the pharmacological inhibition.

L 365 "...supporting its role in mineral deposition..." "...Overall, our studies indicate that ROCK activity....is essential for the formation of the spicule cavity......which could be essential for mineral deposition..." I think the authors need to do a better job in clearly separating between the potential processes impacted by ROCK perturbation. Is it stabilization and mechano-sensing in the spicule tip or the intracellular trafficking and deposition of the ACC? If the dataset does not allow for a definite conclusion, I suggest clearly separating the different possibilities combined with thorough discussion-based findings from other mineralizing systems where the interaction between ROCK and F-actin has been described.

Reviewer #2 (Public Review):

In this manuscript, Birkbak and colleagues use a novel approach to transform multi-omics datasets in images and apply Deep Learning methods for image analysis. Interestingly they find that the spatial representation of genes on chromosomes and the order of chromosomes based on 3D contacts leads to best performance. This supports that both 1D proximity and 3D proximity could be important for predicting different phenotypes. I appreciate that the code is made available as a github repository. The authors use their method to investigate different cancers and identify novel genes potentially involved in these cancers. Overall, I found this study important for the field.

In the original submission there were several major points with this manuscript could be grouped in three parts:

1. While the authors have provided validation for their model, it is not always clear that best approaches have been used. This has now been addressed in the revised version of the manuscript.

2. Potential improvement to the method

a. It is very encouraging the use of HiC data, but the authors used a very coarse approach to integrate it (by computing the chromosome order based on interaction score). We know that genes that are located far away on the same chromosome can interact more in 3D space than genes that are relatively close in 1D space. Did the authors consider this aspect? Why not group genes based on them being located in the same TAD? In the revised version of the manuscript, the authors discussed this possibility but did not do any new additional analysis.

b. Authors claim that "given that methylation negatively correlates with gene expression, these were considered together". This is clearly not always the case. See for example https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02728-5. In the revised version of the manuscript, the authors addressed fully this comment.

3. Interesting results that were not explained.

a. In Figure 3A methylation seems to be most important omics data, but in 3B, mutations and expression are dominating. The authors need to explain why this is the case. In the revised version of the manuscript, the authors have clarified this.

Reviewer #1 (Public Review):

This study by Sokač et al. entitled "GENIUS: GEnome traNsformatIon and spatial representation of mUltiomicS data" presents an integrative multi-omics approach which maps several genomic data sources onto an image structure on which established deep-learning methods are trained with the purpose of classifying samples by their metastatic disease progression signatures. Using published samples from the Cancer Genome Atlas the authors characterize the classification performance of their method which only seems to yield results when mapped onto one out of four tested image-layouts.

A few remaining issues are unclear to me:

1) While the authors have now extended the documentation of the analysis script they refer to as GENIUS, I assume that the following files are not part of the script anymore, since they still contain hard-coded file paths or hard-coded gene counts:

• https://github.com/mxs3203/GENIUS/blob/master/GenomeImage/make_images_by_chr.py
• https://github.com/mxs3203/GENIUS/blob/master/GenomeImage/randomize_normal_imgs.py
• https://github.com/mxs3203/GENIUS/blob/master/GenomeImage/utils.py

If these files are indeed not part of the script anymore, then I would recommend removing them from the GitHub repo to avoid confusion. If, however, they are still part of the script, the authors failed to remove all hard-coded file paths and the software will fail when users attempt to use their own datasets.

2) The authors leave most of the data formatting to the user when attempting to use datasets other than their own presented for this study:

Script arguments:

• a. clinical_data: Path to CSV file that must contain ID and label column we will use for prediction
• b. ascat_data: Path to output matrix of ASCAT tool. Check the example input for required columns
• c. all_genes_included: Path to the CSV file that contains the order of the genes which will be used to create Genome Image
• d. mutation_data: Path CSV file representing mutation data. This file should contain Polyphen2 score and HugoSymbol
• e. gene_exp_data: Path to the csv file representing gene expression data where columns=sample_ids and there should be a column named "gene" representing the HugoSymbol of the gene
• f. gene_methyl_data: Path to the csv file representing gene methylation data wherecolumns=sample_ids and there should be a column named "gene1" representing the HugoSymbol of the gene

While this suggests that users will have a difficult time adjusting this analysis script to their own data, this issue is exacerbated by the fact that their analysis script has almost no internal checks whether data format standards were met. Thus, the user will be left with cryptic error messages and will likely give up soon after. I therefore strongly recommend adding internal data format checks and helpful error or warning messages to their script to guide users in the input data adoption process.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors analyzed data from 99 individuals with implanted electrodes who were performing a word-list recall task. Because the task involves successively encoding and then recalling 25 lists in a row, they were able to measure the similarity in neural responses for items within the same list as well as items across different lists, allowing them to test hypotheses about the impact of between-list boundaries on neural responses. They find that, in addition to slow drift in responses across items, there is boundary-related structure in the medial parietal lobe such that early items in each list show similarity (for recalled items) and late items in each list show similarity (for not recalled items).

Strengths:<br /> The dataset used in this paper is substantially larger than most iEEG datasets, allowing for the detection of nuanced differences between item positions and for analyses of individual differences in boundary-related responses. There are excellent visualizations of the similarity structure between items for each region, and this work connects to a growing literature on the role of event boundaries in structuring neural responses.

Weaknesses:<br /> 1) My primary confusion in the current version of this paper is that the analyses don't seem to directly compare the two proposed models illustrated in Fig 1B, i.e. the temporal context model (with smooth drifts between items, including across lists) versus the boundary model (with similarities across all lists for items near boundaries). After examining smooth drift in the within-list analysis (Fig 2), the across-list analyses (Figs 3-5) use a model with two predictors (boundary proximity and list distance), neither of which is a smoothly-drifting context. Therefore there does not appear to be a quantitative analysis supporting the conclusion that in lateral temporal cortex "drift exhibits a relationship with elapsed time regardless of the presences of intervening boundaries" (lines 272-3).

2) The feature representation used for the neural response to each item is a gamma power time-frequency matrix. This makes it unclear what characteristics of the neural response are driving the observed similarity effects. It appears that a simple overall scaling of the response after boundaries (stronger responses to initial items during the beginning portion of the 1.6s time window) would lead to the increased cosine similarity between initial items, but wouldn't necessarily reflect meaningful differences in the neural representation or context of these items.

3) The specific form of the boundary proximity models is not well justified. For initial items, a model of e^(1-d) is used (with d being serial position), but it is not stated how the falloff scale of this model was selected (as opposed to e.g. e^((1-d)/2)). For final items, a different model of d/#items is used, which seems to have a somewhat different interpretation (about drift between boundaries, rather than an effect specific to items near a final boundary). The schematic in Fig 1B appears to show a hypothesis which is not tested, with symmetric effects at initial and final boundaries.

4) The main text description of Fig 2 only describes drift effects in lateral temporal cortex, but Fig 2 - supplement 1 shows that there is also drift and a significant subsequent memory effect in the other two ROIs as well. There is not a significant memory x drift slope interaction in these regions; are the authors arguing that the lack of this interaction (different drift rates for remembered versus forgotten items) is critical for interpreting the roles of lateral temporal cortex versus medial parietal and hippocampal regions?

5) The parameter fits for the "list distance" regressor are not shown or analyzed, though they do appear to be important for the observed similarity structure (e.g. Fig 3E). I would interpret this regressor as also being "boundary-related" in the sense that it assumes discrete changes in similarity at boundaries.

6) It is unclear to me whether the authors believe that the observed similarity after boundaries is due to an active process in which "the medial parietal lobe uses drift-resets" (line 16) to reinstate a boundary-related context, or that this similarity is simply because "the context for the first item may be the boundary itself" (lines 246-7), and therefore this effect would emerge naturally from a temporal context model that incorporates the full task structure as the "items."

Reviewer #1 (Public Review):

Summary:<br /> This study applied pattern similarity analyses to intracranial EEG recordings to determine how neural drift is related to memory performance in a free recall task. The authors compared neural similarity within and across lists, in order to contrast signals related to contextual drift vs. the onset of event boundaries. They find that within-list neural differentiation in the lateral temporal cortex correlates with the probability of word recall; in contrast, across-list pattern similarity in the medial parietal lobe correlates with recall for items near event boundaries (early-list serial positions). This primacy effect persists for the first three items of a list. Medial parietal similarity is also enhanced across lists for end-of-list items, however, this effect then predicts forgetting. The authors do not find that within- or across-list pattern similarity in the hippocampus is related to recall probability.

Strengths:<br /> The authors use a large dataset of human intracranial electrophysiological recordings, which gives them high statistical power to compare neural activity and memory across three important memory encoding regions. In so doing, the authors also address a timely and important question about the neural mechanisms that underlie the formation of memories for events.

The use of both within and across event pattern similarity analyses, combined with linear mixed effects modeling, is a marriage of techniques that is novel and translatable in principle to other types of data.

Weaknesses:<br /> In several instances the paper does not address apparent inconsistencies between the prior literature and the findings. For example, the first main finding is that recalled items have more differentiated lateral temporal cortex representations within lists than not recalled items. This seems to be the opposite of the prediction from temporal context models that are used to motivate the paper-context models would predict that greater contextual similarity within a list should lead to greater memory through enhanced temporal clustering in recall. This is what El-Kalliny et al (2019) found, using a highly similar design (free recall, intracranial recordings from the lateral temporal lobe). The authors never address this contradiction in any depth in order to reconcile it with the previous literature and with the motivating theoretical model.

The way that the authors conduct the analysis of medial parietal neural similarity at boundaries leads to results that cannot be conclusively interpreted. The authors report enhanced similarity across lists for the first item in each list, which they interpret as reflecting a qualitatively distinct boundary signal. However, this finding can readily be explained by contextual drift if one assumes that whatever happens at the start of each list is similar or identical across lists (for example, a get ready prompt or reminder of instructions). The authors do not include analyses to rule this out, which undermines one of the main findings.

Although several previous studies have linked hippocampal fMRI and electrophysiological activity at event boundaries with memory performance, the authors do not find similar relationships between hippocampal activity, event boundaries, and memory. There are potential explanations for why this might be the case, including the distinction between item vs. associative memory, which has been a prominent feature of previous work examining this question. However, the authors do not address these potential explanations (or others) to explain their findings' divergence from prior work -this makes it difficult to interpret and to draw conclusions from the data about the hippocampus' mechanistic role in forming event memories.

There is a similar absence of interpretation with respect to the previous literature for the data showing enhanced boundary-related similarity in the medial parietal cortex. The authors' interpretation seems to be that they have identified a boundary-specific signal that reflects a large and abrupt change in context, however, another plausible interpretation is that enhanced similarity in the medial parietal cortex is related to a representation of a schema for the task structure that has been acquired across repeated instances.

The authors do not directly compare their model to other models that could explain how variability in neural activity predicts memory. One example is the neural fatigue hypothesis, which the authors mention, however there are no analyses or data to suggest that their data is better fit by a boundary/contextual drift mechanism as opposed to neural fatigue.

Reviewer #2 (Public Review):

Summary: The goal of this study is to clarify how the brain simultaneously represents item-specific temporal information and item-independent boundary information. The authors report spectral EEG data from intracranial patients performing a delayed free recall task. They perform cosine similarity analyses on principal components derived from gamma band power across stimulus duration. The authors find that similarity between items in serial position 1 (SP1) and all other within-list items decreases as a function of serial position, consistent with temporal context models. The authors find that across-list item similarity to SP1 is greatest for SP1 items relative to items from other serial positions, an effect that is greater in medial parietal lobe compared to lateral temporal cortex and hippocampus. The authors conclude that their findings suggest that perceptual boundary information is represented in medial parietal lobe. Despite a robust dataset, the methodological limitations of the study design prevent strong interpretations from being made from these data. The same-serial position across-list similarity may be driven by attentional mechanisms that are distinct from boundary information.

Strengths:<br /> 1. The motivation of the study is strong as how both temporal contextual drift and event boundaries contribute to memory mechanisms is an important open question.

2. The dataset of spectral EEG data from 99 intracranial patients provides the opportunity for precise spatiotemporal investigation of neural memory mechanisms.

Weaknesses:<br /> 1. Because this is not a traditional event boundary study, the data are not ideally positioned to demonstrate boundary specific effects. In a typical study investigating event boundary effects, a series of stimuli are presented and within that series occurs an event boundary -- for instance, a change in background color. The power of this design is that all aspects between stimuli are strictly controlled -- in particular, the timing -- meaning that the only difference between boundary-bridging items is the boundary itself. The current study was not designed in this manner, thus it is not possible to fully control for effects of time or that multiple boundaries occur between study lists (study to distractor, distractor to recall, recall to study). Each list in a free recall study can be considered its own "mini" experiment such that the same mechanisms should theoretically be recruited across any/all lists. There are multiple possible processes engaged at the start of a free recall study list which may not be specific to event boundaries per se. For example, and as cited by the authors, neural fatigue/attentional decline (and concurrent gamma power decline) may account for serial position effects. Thus, SP1 on all lists will be similar by virtue of the fact that attention/gamma decrease across serial position, which may or may not be a boundary-specific effect. In an extreme example, the analyses currently reported could be performed on an independent dataset with the same design (e.g. 12 word delayed free recall) and such analyses could potentially reveal high similarity between SP1-list1 in the current study and SP1-list1 in the second dataset, effects which could not be specifically attributed to boundaries.

2. Comparisons of recalled "pairs" does not account for the lag between those items during study or recall, which based on retrieved context theory and prior findings (e.g. Manning et al., 2011), should modulate similarity between item representations. Although the GLM will capture a linear trend, it will not reveal serial position specific effects. It appears that the betas reported for the SP12 analyses are driven by the fact that similarity with SP12 generally increases across serial position, rather a specific effect of "high similarity to SP12 in adjacent lists" (Page 5, excluding perhaps the comparison with list x+1). It is also unclear how the SP12 similarity analyses support the statement that "end-list items are represented more distinctly, or less similarly, to all succeeding items" (Page 5). It is not clear how the authors account for the fact that the same participants do not contribute equally to all ROIs or if the effects are consistent if only participants who have electrodes in all ROIs are included.

3. The authors use the term "perceptual" boundary which is confusing. First, "perceptual boundary" seems to be a specific subset of the broader term "event boundary," and it is unclear why/how the current study is investigating "perceptual" boundaries specifically. Second and relatedly, the current study does not have a sole "perceptual" boundary (as discussed in point 1 above), it is really a combination of perceptual and conceptual since the task is changing (from recalling the words in the previous list to studying the words in the current list OR studying the words in the current list to solving math problems in the current list) in addition to changes in stimulus presentation.

4. Although the results show that item-item similarity in the gamma band decreases across serial position, it is unclear how the present findings further describe "how gamma activity facilitates contextual associations" (Page 5). As mentioned in point 1 above, such effects could be driven by attentional declines across serial position -- and a concurrent decline in gamma power -- which may be unrelated to, and actually potentially impair, the formation of contextual associations, given evidence from the literature that increased gamma power facilitates binding processes.

5. Some of the logic and interpretations are inconsistent with the literature. For example, the authors state that "The temporal context model (TCM) suggests that gradual drift in item similarity provides context information to support recovery of individual items" however, this does not seem like an accurate characterization of TCM. According to TCM, context is a recency-weighted average of previous experience. Context "drifts" insofar as information is added to/removed from context. Context drift thus influences item similarity -- it is not that item similarity itself drifts, but that any change in item-item similarity is due to context drift. The current findings do not appear at odds with the conceptualization of drift and context in current version of the context maintenance and retrieval model. Furthermore, the context representation is posited to include information beyond basic item representations. Two items, regardless of their temporal distance, can be associated with similar contexts if related information is included in both context representations, as predicted and shown for multiple forms of relatedness including semantic relatedness (Manning & Kahana, 2012) and task relatedness (Polyn et al., 2012).

Reviewer #1 (Public Review):

Summary

This paper summarises responses from a survey completed by around 5,000 academics on their manuscript submission behaviours. The authors find several interesting stylised facts, including (but not limited to):

- Women are less likely to submit their papers to highly influential journals (*e.g.*, Nature, Science and PNAS).<br /> - Women are more likely to cite the demands of co-authors as a reason why they didn't submit to highly influential journals.<br /> - Women are also more likely to say that they were advised not to submit to highly influential journals.

Recommendation

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

Major comments

## What do you mean by bias?

In the second paragraph of the introduction, it is claimed that "if no biases were present in the case of peer review, then 'we should expect the rate with which members of less powerful social groups enjoy successful peer review outcomes to be proportionate to their representation in submission rates." There are a couple of issues with this statement.<br /> - First, the authors are implicitly making a normative assumption that manuscript submission and acceptance rates *should* be equalised across groups. This may very well be the case, but there can also be important reasons why not -- e.g., if men are more likely to submit their less ground-breaking work, then one might reasonably expect that they experience higher rejection rates compared to women, conditional on submission.<br /> - Second, I assume by "bias", the authors are taking a broad definition, i.e., they are not only including factors that specifically relate to gender but also factors that are themselves independent of gender but nevertheless disproportionately are associated with one gender or another (e.g., perhaps women are more likely to write on certain topics and those topics are rated more poorly by (more prevalent) male referees; alternatively, referees may be more likely to accept articles by authors they've met before, most referees are men and men are more likely to have met a given author if he's male instead of female). If that is the case, I would define more clearly what you mean by bias. (And if that isn't the case, then I would encourage the authors to consider a broader definition of "bias"!)

## Identifying policy interventions is not a major contribution of this paper

In my opinion, the survey evidence reported here isn't really strong enough to support definitive policy interventions to address the issue and, indeed, providing policy advice is not a major -- or even minor -- contribution of your paper, so I would not mention policy interventions in the abstract. (Basically, I would hope that someone interested in policy interventions would consult another paper that much more thoughtfully and comprehensively discusses the costs and benefits of various interventions!)

Minor comments

- What is the rationale for conditioning on academic rank and does this have explanatory power on its own---i.e., does it at least superficially potentially explain part of the gender gap in intention to submit?

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Basson et al. study the representation of women in "high-impact" journals through the lens of gendered submission behavior. This work is clear and thorough, and it provides new insights into gender disparities in submissions, such as that women were more likely to avoid submitting to one of these journals based on advice from a colleague/mentor. The results have broad implications for all academic communities and may help toward reducing gender disparities in "high-impact" journal submissions. I enjoyed reading this article, and I have several recommendations regarding the methodology/reporting details that could help to enhance this work.

Strengths:<br /> This is an important area of investigation that is often overlooked in the study of gender bias in publishing. Several strengths of the paper include:<br /> 1) A comprehensive survey of thousands of academics. It is admirable that the authors retroactively reached out to other researchers and collected an extensive amount of data.<br /> 2) Overall, the modeling procedures appear thorough, and many different questions are modeled.<br /> 3) There are interesting new results, as well as a thoughtful discussion. This work will likely spark further investigation into gender bias in submission behavior, particularly regarding the possible gendered effect of mentorship on article submission.

Weaknesses:<br /> 1) The GitHub page should be further clarified. A detailed description of how to run the analysis and the location of the data would be helpful. For example, although the paper says that "Aggregated and de-identified data by gender, discipline, and rank for analyses are available on GitHub," I was unable to find such data.<br /> 2) Why is desk rejection rate defined as "the number of manuscripts that did not go out for peer review divided by the number of manuscripts rejected for each survey respondent"? For example, in your Grossman 2020 reference, it appears that manuscripts are categorized as "reviewed" or "desk-rejected" (Grossman Figure 2). If there are gender differences in the denominator, then this could affect the results.<br /> 3) Have you considered correcting for multiple comparisons? Alternatively, you could consider reporting P-values and effect sizes in the main text. Otherwise, sometimes the conclusions can be misleading. For example, in Figure 3 (and Table S28), the effect is described as significant in Social Sciences (p=0.04) but not in Medical Sciences (p=0.07).<br /> 4) More detail about the models could be included. It may be helpful to include this in each table caption so that it is clear what all the terms of the model were. For instance, I was wondering if journal or discipline are included in the models.

Reviewer #3 (Public Review):

Summary:<br /> This is a strong manuscript by Basson and colleagues which contributes to our understanding of gender disparities in scientific publishing. The authors examine attitudes and behaviors related to manuscript submission in influential journals (specifically, Science, Nature and PNAS). The authors rightly note that much attention has been paid to gender disparities in work that is already published, but this fails to capture the unseen hurdles that occur prior to publication (which include decisions about where to publish, desk rejections, revisions and resubmissions, etc.). They conducted a survey study to address some of these components and their results are interesting:

They find that women are less likely to submit their manuscript to Science, Nature or PNAS. While both men and women feel their work would be better suited for more specialized journals, women were more likely to think their work was 'less novel or groundbreaking.'

A smaller proportion of respondents indicated that they were actively discouraged from submitting their manuscripts to these journals. In this instance, women were more likely to receive this advice than men.

Lastly, the authors also looked at self-reported acceptance and rejection rates and found that there were no gender differences in acceptance or rejection rates.

These data are helpful in developing strategies to mitigate gender disparities in influential journals.

Comments:<br /> The methods the authors used are appropriate for this study. The low response rate is common for this type of recruitment strategy. The authors provide a thoughtful interpretation of their data in the Discussion.

Reviewer #4 (Public Review):

This manuscript covers an important topic of gender biases in the authorship of scientific publications. Specifically, it investigates potential mechanisms behind these biases, using a solid approach, based on a survey of researchers.

Main strengths

The topic of the MS is very relevant given that across sciences/academia representation of genders is uneven, and identified as concerning. To change this, we need to have evidence on what mechanisms cause this pattern. Given that promotion and merit in academia are still largely based on the number of publications and impact factor, one part of the gap likely originates from differences in publication rates of women compared to men.

Women are underrepresented compared to men in journals with high impact factor. While previous work has detected this gap, as well as some potential mechanisms, the current MS provides strong evidence, based on a survey of close to 5000 authors, that this gap might be due to lower submission rates of women compared to men, rather than the rejection rates. The data analysis is appropriate to address the main research aims. The results interestingly show that there is no gender bias in rejection rates (desk rejection or overall) in three high-impact journals (Science, Nature, PNAS). However, submission rates are lower for women compared to men, indicating that gender biases might act through this pathway. The survey also showed that women are more likely to rate their work as not groundbreaking, and be advised not to submit to prestigious journals

With these results, the MS has the potential to inform actions to reduce gender bias in publishing, and actions to include other forms of measuring scientific impact and merit.

Main weakness and suggestions for improvement

1) The main message/further actions: I feel that the MS fails to sufficiently emphasise the need for a different evaluation system for researchers (and their research). While we might act to support women to submit more to high-impact journals, we could also (and several initiatives do this) consider a broader spectrum of merits (e.g. see https://coara.eu/ ). Thus, I suggest more space to discuss this route in the Discussion. Also, I would suggest changing the terms that imply that prestigious journals have a better quality of research or the highest scientific impact (line 40: journals of the highest scientific impact) with terms that actually state what we definitely know (i.e. that they have the highest impact factor). And think this could broaden the impact of the MS

2) Methods: while methods are all sound, in places it is difficult to understand what has been done or measured. For example, only quite late (as far as I can find, it's in the supplement) we learn the type of authorship considered in the MS is the corresponding authorship. This information should be clear from the very start (including the Abstract).

Second, I am unclear about the question on the perceived quality of research work. Was this quality defined for researchers, as quality can mean different things (e.g. how robust their set-up was, how important their research question was)? If researchers have different definitions of what quality means, this can cause additional heterogeneity in responses. Given that the survey cannot be repeated now, maybe this can be discussed as a limitation.

I was surprised to see that discipline was considered as a moderator for some of the analyses but not for the main analysis on the acceptance and rejection rates.

I was also suppressed not to see publication charges as one of the reasons asked for not submitting to selected journals. Low and middle-income countries often have more women in science but are also less likely to support high publication charges.

Finally, academic rank was asked of respondents but was not taken as a moderator.

Reviewer #1 (Public Review):

Summary:<br /> This paper addresses the mechanisms positioning microtubule asters in Drosophila explants. Taking advantage of a genetic mutant, blocking the cell cycle in early embryos, the authors generate embryos with centrosomes detached from nuclei and then study the positioning mechanisms of such asters in explants. They conclude that asters interact via pushing forces. While this is an artificial system, understanding the mechanics of asters positioning, in particular, whether forces are pushing or pulling is an important one.

Strengths:<br /> The major strength of this paper is the series of laser cutting experiments supporting that asters position via pushing forces acting both on the boundary (see below for a relevant comment) and between asters. The combination of imaging, data analysis and mathematical modeling is also powerful.

Weaknesses:<br /> This paper has weaknesses, mainly in the presentation but also in the quality of the data which do not always support the conclusions satisfactorily (this might in part be a presentation issue).

In Figure 2, it is difficult for me to understand what is being tracked. I believe that the authors track the yolk granules (visible as large green blobs) and not lipid droplets. There is some confusion between the text, legends and methods so I could not tell. If the authors are tracking yolk granules as a proxy for hydrodynamics flows it seems appropriate to cite previous papers that have used and verified these methods. More notably, this figure is somewhat disconnected with the rest of the paper. I find the analysis interesting in principle but would urge the authors to propose some interpretation of the experiments in the context of their big-picture message. At this point, I cannot understand what the Figure adds.

In Figure 3, it is not surprising that the aster-aster interactions are different from interactions with the boundary which is likely more rigid. It is also hard to understand why the force and thus velocity should scale as microtubule length. This Figure should be better conceptualized. I think that it becomes clear at the end of the paper that the authors are trying to derive an effective potential to use in a mathematical model in Figure 5 to test their hypotheses. I think that should be told from the start, so a reader understands why these experiments are being shown.

The experiments in Figure 4 are very nice in supporting a pushing model. However, it would help if the authors could speculate what the single aster is pushing against in this experiment. The experiments reported in Figure 1 seemed to suggest that the aster mainly pushed against the boundary. In the experiments in Figure 4 do the individual asters touch the boundary on both sides? I think that readers need more information on what the extract looks like for those experiments.

Figure 4F could use some statistics. I doubt that the acceleration in the pink curves would be significant. I believe that the deceleration is and that is probably the most crucial result. Since the authors present only 3 asters pairs it is important to be sure that these conclusions are solid.

Reviewer #2 (Public Review):

Summary:<br /> The aster, consisting of microtubules, plays important roles in spindle positioning and the determination of the cleavage site in animals. The mechanics of aster movement and positioning have been extensively studied in several cell types. However, there is no unified biophysical model, as different mechanisms appear to predominate in different model systems. In the present manuscript, the authors studied aster positioning mechanics in the Drosophila syncytial embryo, in which short-ranged aster repulsion generates a separation force. Taking advantage of the ex vivo system developed by the group and the fly gnu mutant, in which the nuclear number can be minimized, the authors performed time-lapse observations of single asters and multiple asters in the explant. The observed aster dynamics were interpreted by building a mathematical model dealing with forces. They found that aster dissociation from the boundary depends on the microtubule pushing force. Additionally, laser ablation targeting two separating asters showed that aster-aster separation is also mediated by the microtubule pushing force. Furthermore, they built a simulation model based on the experimental results, which reproduced aster movement in the explant under various conditions. Notably, the actual aster dynamics were best reproduced in the model by including a short-ranged inhibitory term when asters are close to the boundary or each other.

Strengths:<br /> This study reveals a unique aster positioning mechanics in the syncytial embryo explant, which leads to an understanding of the mechanism underlying the positioning of multiple asters associated with nuclei in the embryo. The use of explants enabled accurate measurement of aster motility and, therefore, the construction of a quantitative model. This is a notable achievement.

Weaknesses:<br /> The main conclusion that aster repulsion predominates in this system has already been drawn by the same authors in their recent study (de-Carvalho et al., Development, 2022). As the present work provides additional support to the previous study using different experimental system, the authors should emphasize that the present manuscripts adds to it (but the conceptual novelty is limited). The molecular mechanisms underlying aster repulsion remain unexplored since the authors were unable to identify specific factor(s) responsible for aster repulsion in the explant.

Specific suggestions:<br /> Microtubules should be visualized more clearly (either in live or fixed samples). This is particularly important in Figure 4E and Video 4 (laser ablation experiment to create asymmetric asters).

Reviewer #1 (Public Review):

The authors use a previously established reporter comprising a slow- and a fast-folding fluorescent protein fused to a randomly-generated library of penta-peptides at its amino-terminus and a signal sequence for import into the endoplasmic reticulum (ER). They then determine the stability of these constructs in a high throughput FACS-sorting procedure and identify a set of peptides that route the construct to proteasomal degradation. Increasing the copy number of one of these peptides further decreases the stability of the construct. This polypeptide resembles a "degron" for ER proteins, because it also targets other ER proteins with different topological and folding properties for degradation. It only works when placed at the amino-terminus of a protein and utilizes components of the Hrd1 ubiquitin ligase complex, a well-established quality control ubiquitin ligase in the ER membrane. Importantly, the degron also targets ER-proteins in mammalian cells.

The authors convincingly show that fusion of their newly identified degron to the amino terminus of ER-resident proteins with different topology suffices to target them for proteasomal degradation. The data for this are well-founded and contain appropriate controls. While technically sound, the study does only give superficial information on general properties of the degron and its recognition by cellular factors. Further simple experiments would have addressed a number of important points. The authors only provide data about the composition of the identified amino acid sections from the high-throughput approach and the statistical preference for certain amino acids at individual positions. They do not study degron composition experimentally by substituting individual amino acids with other residues and analyzing protein stability. Increasing the numbers of the initially identified degron pentamer increases substrate turnover, but the basis for this remains unclear. Each copy may be actively involved in better recognition, elongation of the degron may facilitate accessibility by recognition factors or multiplying the short amino acid stretch may generate new signatures at the amino-terminus that are more readily recognized by a quality control machinery. Consequently, this study does not allow conclusions to be drawn about general properties of degron composition and/or structure. The degron also functions with cytoplasmic proteins, suggesting that similar characteristics of a polypeptide attract the attention of quality control systems also in other cellular compartments. However, the authors did not pursue this finding further, e.g. by identifying factors for degron recognition in the cytoplasm. It would have been particularly interesting to test whether the degron would initiate degradation when placed at cytoplasmically-exposed amino termini of membrane-bound ER proteins. Information on degron properties is required to better understand principles of substrate recognition by protein quality control pathways and to design constructs for targeting endogenous proteins via proteolysis targeting chimeras (PROTACs).

Reviewer #2 (Public Review):

Summary:<br /> Sharninghausen et al use a generic screening platform to search for short (5 amino acid) degrons that function in the lumen of the endoplasmic reticulum (ER) of budding yeast. The screen did indeed identify a number of sequences which increased the rate of degradation of their test proteins. Although the effect of the single degron was rather modest the authors could show that by mutimerising the sequence (4x) they obtained degrons that functioned fairly efficiently. Further characterisation indicated that the degrons only functioned when placed at the N-terminus of the target protein and, were dependent on both the proteasome and the segregase Cdc48 (p97) for degradation. The authors also demonstrated that degradation was via the ERAD pathway.

Strengths:<br /> In general, the data presented is supportive of the conclusions drawn and the authors have thus identified a sequence that can be appended onto other ER targeted proteins to mediate their degradation within the lumen of the ER. How useful this will be to the community remains to be seen.

Weaknesses:<br /> While the observation that such mutimerised sequences can act as degrons is an interesting curiosity, it is not clear that such sequences function in vivo. In fact the DegV1 sequence used throughout the paper is not present in any yeast or fungal proteins and the fact that it has to be located at the N-terminus of the protein to induce degradation is at odds with the idea that proteins to be degraded need to be unfolded. Thus, the role of such sequences in vivo is questionable.

Reviewer #1 (Public Review):

This study by Park et al. describes an interesting approach to disentangle gene-environment pathways to cognitive development and psychotic-like experiences (PLEs) in children. They have used data from the ABCD (Adolescent Brain Cognitive Development) study and have included phenotypes polygenic scores (PGS) of educational attainment (EA) and cognition, environmental exposure data, cognitive performance data and self-reported PLEs. The study has several strengths, including its large sample size, interesting approach and comprehensive statistical model,

One remaining concern is the authors' conflation of PLEs and schizophrenia. They stated, for example, that it is necessary to adjust for schizophrenia PGS. Even though studies have found a statistical relationship between schizophrenia PGS and PLEs, this relationship is not very strong (although statistically significant) and other studies have found no relationship. Similarly, having PLEs increases the risk of developing psychosis, but that does not necessarily mean that this risk is substantial or specific. I think this needs more nuance in the manuscript and the term 'schizophrenia' should be used sparsely and very carefully as the paper has focused on PLEs.

Reviewer #2 (Public Review):

This paper tried to assess the link between genetic and environmental factors on psychotic-like experiences, and the potential mediation through cognitive ability. This study was based on data from the ABCD cohort, including 6,602 children aged 9-10y. The authors report a mediating effect, suggesting that cognitive ability is a key mediating pathway in the link between several genetic and environmental (risk and protective) factors on PLEs.

Strengths of the methods<br /> The authors use a wide range of validated (genetic, self- and parent-reported, as well as cognitive) measures in a large dataset with a 2-year follow-up period. The statistical methods have potential to address key limitations of previous research.

Weaknesses of the methods<br /> The methodological advantage of the method (Integrated generalized structured component analysis, IGSCA) over the standard method (Structural equation modeling, SEM) is not fully clear.<br /> Not all methods are fully explained (how genetic components were derived; how cognition was assessed in Lee et al., 2018).<br /> Not the largest or most recent GWAS (Genome-wide association studies) were used to generate PGS.

Strengths of the results<br /> The authors included a comprehensive array of analyses.

Weaknesses of the results<br /> Some factor loadings presented in Figure 3 seem counterintuitive/inconsistent.<br /> Supplementary tables are difficult to assess. Unclear significance statement / p-values in Table 2.

Appraisal<br /> The authors suggest that their findings provide evidence for policy reforms (e.g., targeting residential environment, family SES (social economic status), parenting, and schooling).

Impact<br /> Immediate impact is limited given the short follow-up period (2y), possibly concerns for selection bias and attrition in the data, and some methodological concerns. The authors are transparent about most of these limitations.

Reviewer #1 (Public Review):

Summary:<br /> This Research Advance is an extension of this group's prior paper published in 2022 on the conserved roles of the Hippo pathway effector Yorkie in C. owczarzaki (PMID: 35659869). This species is an amoeba that holds an important phylogenetic position as a close relative of multicellular animals. The prior study used genome editing to delete the C. owczarzaki Yki (termed coYki) and found that Yki is not required for proliferation but instead regulates cell contractility and cell aggregation. In the current study, the authors wanted to address whether Hippo pathway kinases - coHippo (coHpo) and coWarts (coWts) - regulate coYki and whether they are dispensable for proliferation but instead regulate cell contractility and cell aggregation. They used genome editing to delete coHpo and coWts singly in C. owczarzaki. Both mutant strains had increased nuclear location of transfected coYki (tagged with Scarlet), suggesting that Hippo kinase pathway regulation of Yki is conserved in this organism. Neither kinase is required for proliferation. Either kinase mutant strain had a significantly increased percentage of cells that were elongated, which was relatively rare in a control population. The incident of elongation could be enhanced in both kinase-mutant and in control cells when myosin inhibitors were added to the media. coHpo and coWts-mutant aggregates were more tightly packed than control cell aggregates, which they hypothesize is due to the increased contractility seen in kinase-mutant cells. They could reduce the density of packing in kinase-mutant aggregates when they treated the cells with myosin or F-actin inhibitors. To test whether the effects observed in kinase-mutant strains were due to increased Yki activation, they generated a coYki with four S to A substitutions (termed coYki4SA), which should produce a dominant-active Yki impervious to phosphorylation and hence inactivation by Hippo kinases. Control C. owczarzaki cells transfected with coYki4SA had increased cell density in aggregates and elongation in adherent cells. These results support their conclusions that coHpo and coWts regulate cell contractility and cell packing through coYki.

Strengths:<br /> The major strengths of the paper include high quality data, robust analyses of the data, and a well-written manuscript. The combination of genome editing in C. owczarzaki, transfection of C. owczarzaki, and time-lapse movies of adherent cells generally support the conclusions (1) that control of cell density is an ancient function of the Hippo pathway; (2) that Hippo pathway control of cytoskeletal properties and contractile behavior underlie its regulation of cell density, and (3) that Hippo kinase control of Yki localization is likely an ancient function of the pathway.

Weaknesses:<br /> There are only minor weaknesses. (1) Fig. 3C needs the "still" for the movie of control C. owczarzaki (in Movie S1). (2) The elongated cell shape is seen infrequently in control cells, and I wonder whether these events are transient inactivation of coHpo or coWts in these cells. Perhaps the authors could comment on this in the discussion. (3) Does C. owczarzaki normally aggregate or this is a lab-specific phenotype? For example, the slime mold Dictyostelium discoideum forms aggregates during its life cycle. Could some additional information about C. owczarzaki be added to the introduction?

Reviewer #2 (Public Review):

Summary:<br /> The study builds on the work of the Pan group and others which has described the existence of core Hippo pathway proteins in Capsaspora and, more recently, described a role for a Yorkie/YAP homologue in regulation of cell shape and actin, as opposed to proliferation. For this recent study, they developed genetic techniques to mutate genes in Capsaspora, and this technology has been leveraged again in this study. Using loss of genetic approaches, the authors find that loss of either of the two major kinases in the Hippo pathway core kinase cassette (Warts and Hippo) impact Capsaspora morphology and the actin cytoskeleton. This is phenocopied by overexpression of Capsaspora Yorkie/YAP. In addition, Capsaspora Yorkie/YAP accumulates in the nucleus of organisms lacking Warts or Hippo, as it does in metazoans. While these experiments are not overly surprising, they still provide important verification that core Hippo signaling events are conserved in Capsaspora.

Subsequently, they show that Capsaspora lacking Warts or Hippo do not overproliferate, which contrasts with many studies in animals, particularly in epithelial tissues where loss of Warts or Hippo often causes overproliferation. Rather, the authors show that Capsaspora Warts and Hippo regulate cell morphology and actomyosin-dependent contractile behaviour. They speculate from these findings that Hippo signalling could regulate the density of Capsaspora when they grow in aggregates and draw parallels to the known role of the Hippo pathway in contact inhibition of mammalian cells grown in culture.

Strengths:<br /> Together with their 2022 paper, this study paints an emerging picture that the ancestral function of the Hippo pathway is to regulate the actin cytoskeleton, not proliferation, which is a significant finding. This also suggests that the ability to control proliferation was something that the Hippo pathway was re-purposed to do at some stage during the evolution of metazoans. These findings are important for the Hippo field, and our understanding of cellular signalling and evolution more broadly.

Weaknesses:<br /> Further biochemical and genetic experiments would allow the authors to more convincingly prove that core features of Hippo signalling are conserved in Capsaspora - e.g., that Capsaspora Hippo/MST activates Warts/LATS by phosphorylation and Warts/LATS represses Yorkie/YAP by phosphorylation hey serine residues. Additional genetic studies would also allow one to determine whether Capsaspora Yki/YAP controls actomyosin contractility by transcription (with the Scalloped/TEAD homologue) and/or by non-transcriptional mechanisms, as have been reported for Yki in Drosophila. Higher resolution imaging approaches such as electron microscopy would likely give further mechanistic insights into how Hpo, Wts and Yki modulate actomyosin contractility in Capsaspora.

Reviewer #3 (Public Review):

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

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

The work carried out in this study is technically precise at all levels, molecular, cellular and microscopy. The reviewer here acknowledges how difficult is to work and develop tools and mutant lines in a non-model organism and therefore congratulates the authors in their efforts. The authors have done excellent work in this sense and all data presented seems to be solid.

Nevertheless, some of the observations, in my opinion, should be further investigated before taking the conclusion that the Hippo pathway controls cell density and a contractile behavior in the C. owczarzaki. On the hand the authors claim as main conclusions what they have partially already claimed in the previous work (Phillips et al. eLife 2022;0:e77598).

Reviewer #1 (Public Review):

In this manuscript, the authors aimed to provide information about the likely function of uncharacterised genes in fission yeast. The authors highlight the bias in the literature to well-studied genes/proteins and the fact that the functions of many proteins that are conserved from yeast to humans remain unknown. Initial functional characterisation could provide the impetus for researchers to dedicate time and resources to detailed investigations of protein function. The authors subject the fission yeast deletion set to a battery of perturbations (drug treatments etc) and measured the resultant colony size. In total, 131 conditions were analysed for nearly 3,500 mutants, representing a rich dataset. Clustering analysis was then used to identify common phenotype patterns and thereby infer protein functions using a "guilt by association approach. To assign potential GO terms to uncharacterised proteins, the authors developed a new computational approach (NET-FF) which combined two previous approaches, which they validated against curated annotations on the S. pombe database Pombase. Finally, the authors chose a group of genes which their analysis predicted to be involved in cellular ageing for experimental validation, cross-validating a priority unstudied novel gene (SPAC23C4.09c) to be involved in this process. Overall, the functional analysis performed in this manuscript is rigorous, thorough and incorporates some novel approaches leading to new insights and predicted protein functions. It will be an important resource for the fission yeast community.

Reviewer #2 (Public Review):

This manuscript describes colony-growth phenotypes to measure the fitness of deletion mutants for 3509 non-essential S. pombe genes in 131 conditions. 3492 mutants, including 124 mutants of 'priority unstudied' proteins conserved in humans, providing varied functional clues.

Phenotype-correlation networks provide evidence for the roles of poorly characterized proteins through guilt by association with known proteins. Gene Ontology (GO) terms were predicted using machine learning methods that take advantage of protein-network and protein-homology data.

Integrated analyses produced 1,675 novel GO predictions for 783 genes, including 47 predictions for 23 priority unstudied proteins. Experimental validation for genes involved in cellular ageing were obtained.

A method called NET-FF, which combines network embeddings and protein homology data to predict GO annotations, was developed. The authors demonstrate NET-FF predicts GO terms better than random and compare the information content of the predicted terms with the PomBase GO annotations. The phenotypic data was used to filter the GO annotation predictions made by NET-FF and then explore specific biological examples supported by both datasets

This is a very impressive and rich resource of phenotypic data and it will be particularly useful for the S. pombe research community and generally useful for the functional characterization of highly conserved eukaryotic genes. Overall, the analysis is powerful and sound.

Reviewer #3 (Public Review):

Fission yeast is an important model organism and studies on fission yeast have provided many key insights into the understanding of genes and biological pathways. However, even in such a well-studied model organism, there are still many genes without known functions.

In this work, the authors took advantage of the availability of genome-wide fission yeast deletion mutants to systematically analyze the mutant phenotypes under 131 different conditions. This effort generated a genotype-phenotype dataset larger than the currently curated genotype-phenotype dataset, which is derived from studies over many decades by hundreds of fission yeast laboratories. The authors used the dataset to construct gene clusters that provide functional clues for many genes without previously known functions, including ones conserved in humans. This rich resource will surely be highly useful to the fission yeast community and beyond.

In addition, the authors also used machine learning to generate functional predictions of fission yeast genes and yield novel understandings, which are validated by experimental analysis of new ageing-related genes.

Overall, this study provides unprecedented and highly valuable resources for understanding fission yeast gene functions.

Reviewer #1 (Public Review):

Summary:

In this paper, Jeong et al. investigate the prevalence and cause of TADs that are preserved in eukaryotic cells after cohesin depletion. The authors perform an extensive analysis of previously published Hi-C data, and find that roughly 15% of TADs are preserved in both mouse liver cells and in HCT-116 cells. They confirm previous findings that epigenetic mismatches across the boundaries of TADs can cause TAD preservation. However, the authors also find that not all preserved TADs can be explained this way. Jeong et al. provide an argument based on polymer simulations that "physical boundaries" in 3D structures provide an additional mechanism that can lead to TAD preservation. However, in its current form, we do not find the argumentation and evidence that leads to this claim to be fully compelling.

Strengths:

We appreciate the extensive statistical analysis performed by the authors on the extent to which TAD's are preserved; this does seem like a novel and valuable contribution to the field.

Weaknesses:

1. As the authors briefly note, the fact that compartmentalization due to epigenetic mismatches can cause TAD-like structures upon cohesin depletion has already been discussed in the literature; see for example Extended Data Figure 8 in (Schwarzer et al., 2017) or the simulation study (Nuebler et al., 2018). We are hence left with the impression that the novelty of this finding is somewhat overstated in this manuscript.<br /> 2. It is not quite clear what the authors conceptually mean by "physical boundaries" and how this could offer additional insight into preserved TADs. First, the authors use the CCM model to show that TAD boundaries correlate with peaks in the single cell boundary probability distribution of the model. This finding is consistent with previous reports that TAD-like structures are present in single cells, and that specific TAD boundaries only arise as a population average. The finding based on the CCM simulations hence seems to be that preserved TADs also arise as a population average in cohesin-depleted cells, but we do not follow what the term "physical boundaries" refers to in this context. The authors then use the Hi-C data to infer a maximum-entropy-based HIPPS model. They find that preserved TADs often have boundaries that correspond to peaks in the single cell boundary probabilities of the inferred model. The authors seem to imply that these peaks in the boundary probability correspond to "physical boundaries" that cause the preservation of TADs. This argument seems circular; the model is based on inferring interaction strengths between monomers, such that the model recreates the input Hi-C map. This means that the ensemble average of the model should have a TAD boundary where one is present in the input Hi-C data. A TAD boundary in the Hi-C data would then seem to imply a peak in the model's single-cell boundary probability. (The authors do display two examples where this is not the case in Fig.3h, but looking at these cases by eye, they do not seem to correspond to strong TAD boundaries.) "Physical boundaries" in the model are hence a consequence of the preserved TADs, rather than the other way around, as the authors seem to suggest. At the very least the boundary probability in the HIPPS model is not an independent statistic from the Hi-C map (on which their model is constrained), so we have concerns about using the physical boundaries idea to understand where some of the preserved TADs come from.

References:<br /> Nuebler, J., Fudenberg, G., Imakaev, M., Abdennur, N., & Mirny, L. A. (2018). Chromatin organization by an interplay of loop extrusion and compartmental segregation. Proceedings of the National Academy of Sciences of the United States of America, 115(29), E6697-E6706. https://doi.org/10.1073/PNAS.1717730115/SUPPL_FILE/PNAS.1717730115.SAPP.PDF

Schwarzer, W., Abdennur, N., Goloborodko, A., Pekowska, A., Fudenberg, G., Loe-Mie, Y., Fonseca, N. A., Huber, W., Haering, C. H., Mirny, L., & Spitz, F. (2017). Two independent modes of chromatin organization revealed by cohesin removal. Nature 2017 551:7678, 551(7678), 51-56. https://doi.org/10.1038/nature24281

Reviewer #2 (Public Review):

Summary:

Here Jeong et al., use a combination of theoretical and experimental approaches to define molecular contexts that support specific chromatin conformations. They seek to define features that are associated with TADs that are retained after cohesin depletion (the authors refer to these TADs as P-TADs). They were motivated by differences between single cell data, which suggest that some TADs can be maintained in the absence of cohesin, whereas ensemble HiC data suggest complete loss of TADs. By reananalyzing a number of HiC datasets from different cell types, the authors observe that in ensemble methods, a significant subset of TADs are retained. They observe that P-TADs are associated with mismatches in epigenetic state across TAD boundaries. They further observe that "physical boundaries" are associated with P-TAD maintenance. Their structure/simulation based approach appears to be a powerful means to generate 3D structures from ensemble HiC data, and provide chromosome conformations that mimic the data from single-cell based experiments. Their results also challenge current dogma in the field about epigenetic state being more related to compartment formation rather than TAD boundaries. Their analysis is particularly important because limited amounts of imaging data are presently available for defining chromosome structure at the single-molecule level, however, vast amounts of HiC and ChIP-seq data are available. By using HiC data to generate high quality simulated structural data, they overcome this limitation. Overall, this manuscript is important for understanding chromosome organization, particularly for contacts that do not require cohesin for their maintenance, and for understanding how different levels of chromosome organization may be interconnected. I cannot comment on the validity of the provided simulation methods and hope that another reviewer is qualified to do this.

Reviewer #3 (Public Review):

This manuscript presents a comprehensive investigation into the mechanisms that explain the presence of TADs (P-TADs) in cells where cohesin has been removed. In particular, to study TADs in wildtype and cohesin depleted cells, the authors use a combination of polymer simulations to predict whole chromosome structures de novo and from Hi-C data. Interestingly, they find that those TADs that survive cohesin removal contain a switch in epigenetic marks (from compartment A to B or B to A) at the boundary. Additionally, they find that the P-TADs are needed to retain enhancer-promoter and promoter-promoter interactions.

Overall, the study is well-executed, and the evidence found provides interesting insights into genome folding and interpretations of conflicting results on the role of cohesin on TAD formation.

To strengthen their claims, the authors should compare their de-novo prediction approach to their data-driven predictions at the single cell level.

Joint Public Review:

This paper by Castello-Serrano et al. addresses the role of lipid rafts in trafficking in the secretory pathway. By performing carefully controlled experiments with synthetic membrane proteins derived from the transmembrane region of LAT, the authors describe, model and quantify the importance of transmembrane domains in the kinetics of trafficking of a protein through the cell. Their data suggest affinity for ordered domains influences the kinetics of exit from the Golgi. Additional microscopy data suggest that lipid-driven partitioning might segregate Golgi membranes into domains. However, the relationship between the partitioning of the synthetic membrane proteins into ordered domains visualised ex vivo in GPMVs, and the domains in the TGN, remain at best correlative. Additional experiments that relate to the existence and nature of domains at the TGN are necessary to provide a direct connection between the phase partitioning capability of the transmembrane regions of membrane proteins and the sorting potential of this phenomenon.

The authors have used the RUSH system to study the traffic of model secretory proteins containing single-pass transmembrane domains that confer defined affinities for liquid ordered (lo) phases in Giant Plasma Membrane derived Vesicles (GPMVs), out of the ER and Golgi. A native protein termed LAT partitioned into these lo-domains, unlike a synthetic model protein termed LAT-allL, which had a substituted transmembrane domain. The authors experiments provide support for the idea that ER exit relies on motifs in the cytosolic tails, but that accelerated Golgi exit is correlated with lo domain partitioning.

Additional experiments provided evidence for segregation of Golgi membranes into coexisting lipid-driven domains that potentially concentrate different proteins. Their inference is that lipid rafts play an important role in Golgi exit. While this is an attractive idea, the experiments described in this manuscript do not provide a convincing argument one way or the other. It does however revive the discussion about the relationship between the potential for phase partitioning and its influence on membrane traffic.

Our detailed comments are listed below:

ER exit:<br /> The experiments conducted to identify an ER exit motif in the C-terminal domain of LAT are straightforward and convincing. This is also consistent with available literature. The authors should comment on whether the conservation of the putative COPII association motif (detailed in Fig. 2A) is significantly higher than that of other parts of the C-terminal domain. One cause of concern is that addition of a short cytoplasmic domain from LAT is sufficient to drive ER exit, and in its absence the synthetic constructs are all very slow. However, the argument presented that specific lo phase partitioning behaviour of the TMDs do not have a significant effect on exit from the ER is a little confusing. This is related to the choice of the allL-TMD as the 'non-lo domain' partitioning comparator. Previous data has shown that longer TMDs (23+) promote ER export (eg. Munro 91, Munro 95, Sharpe 2005). The mechanism for this is not, to my knowledge, known. One could postulate that it has something to do with the very subject of this manuscript- lipid phase partitioning. If this is the case, then a TMD length of 22 might be a poor choice of comparison. A TMD 17 Ls' long would be a more appropriate 'non-raft' cargo. It would be interesting to see a couple of experiments with a cargo like this.

Golgi exit:<br /> For the LAT constructs, the kinetics of Golgi exit as shown in Fig. 3B are surprisingly slow. About half of the protein remains in the Golgi at 1 h after biotin addition. Most secretory cargo proteins would have almost completely exited the Golgi by that time, as illustrated by VSVG in Fig. S3. There is a concern that LAT may have some tendency to linger in the Golgi, presumably due to a factor independent of the transmembrane domain, and therefore cannot be viewed as a good model protein. For kinetic modeling in particular, the existence of such an additional factor would be far from ideal. A valuable control would be to examine the Golgi exit kinetics of at least one additional secretory cargo.

Comments about the trafficking model<br /> 1. In Figure 1E, the export of LAT-TMD from the ER is fitted to a single-exponential fit that the authors say is "well described". This is unclear and there is perhaps something more complex going on. It appears that there is an initial lag phase and then similar kinetics after that - perhaps the authors can comment on this?

2. The model for Golgi sorting is also complicated and controversial, and while the authors' intention to not over-interpreting their data in this regard must be respected, this data is in support of the two-phase Golgi export model (Patterson et al PMID:18555781). Furthermore contrary to the statement in lines 200-202, the kinetics of VSVG exit from the Golgi (Fig. S3) are roughly linear and so are NOT consistent with the previous report by Hirschberg et al. Moreover, the kinetics of LAT export from the Golgi (Fig. 3B) appear quite different, more closely approximating exponential decay of the signal. These points should be described accurately and discussed.

Relationship between membrane traffic and domain partitioning:<br /> 1. Phase segregation in the GPMV is dictated by thermodynamics given its composition and the measurement temperature (at low temperatures 4degC). However at physiological temperatures (32-37degC) at which membrane trafficking is taking place these GPMVs are not phase separated. Hence it is difficult to argue that a sorting mechanism based solely on the partitioning of the synthetic LAT-TMD constructs into lo domains detected at low temperatures in GPMVs provide a basis (or its lack) for the differential kinetics of traffic of out of the Golgi (or ER). The mechanism in a living cell to form any lipid based sorting platforms naturally requires further elaboration, and by definition cannot resemble the lo domains generated in GPMVs at low temperatures.

2. The lipid compositions of each of these membranes - PM, ER and Golgi are drastically different. Each is likely to phase separate at different phase transition temperatures (if at all). The transition temperature is probably even lower for Golgi and the ER membranes compared to the PM. Hence, if the reported compositions of these compartments are to be taken at face value, the propensity to form phase separated domains at a physiological temperature will be very low. Are ordered domains even formed at the Golgi at physiological temperatures?

3. The hypothesis of 'lipid rafts' is a very specific idea, related to functional segregation, and the underlying basis for domain formation has been also hotly debated. In this article the authors conflate thermodynamic phase separation mechanisms with the potential formation of functional sorting domains, further adding to the confusion in the literature. To conclude that this segregation is indeed based on lipid environments of varying degrees of lipid order, it would probably be best to look at the heterogeneity of the various membranes directly using probes designed to measure lipid packing, and then look for colocalization of domains of different cargo with these domains.

4. In the super-resolution experiments (by SIM- where the enhancement of resolution is around two fold or less compared to optical), the authors are able to discern a segregation of the two types of Golgi-resident cargo that have different preferences for the lo-domains in GPMVs. It should be noted that TMD-allL and the LATallL end up in the late endosome after exit of the Golgi. Previous work from the Bonafacino laboratory (PMID: 28978644) has shown that proteins (such as M6PR) destined to go to the late endosome bud from a different part of the Golgi in vesicular carriers, while those that are destined for the cell surface first (including TfR) bud with tubular vesicular carriers. Thus at the resolution depicted in Fig 5, the segregation seen by the authors could be due to an alternative explanation, that these molecules are present in different areas of the Golgi for reasons different from phase partitioning. The relatively high colocalization of TfR with the GPI probe in Fig 5E is consistent with this explanation. TfR and GPI prefer different domains in the GPMV assays yet they show a high degree of colocalization and also traffic to the cell surface.

Reviewer #1 (Public Review):

Summary:<br /> This important study from Godneeva et al. establishes a Drosophila model system for understanding how the activity of Tif1 proteins is modified by SUMO. The authors nicely show that Bonus, like homologous mammalian Tif1 proteins, is a repressor, and that it interacts with other co-repressors Mi-2/NuRD and setdb1 in Drosophila ovaries and S2 cells. They also show that Bonus is SUMOylated by Su(var)2-10 on at least one lysine at its N-terminus to promote its interaction with setdb1. By combining nice biochemistry with an elegant reporter gene approach, they show that SUMOylation is important for Bonus interaction with setdb1, and that this SUMO-dependent interaction triggers high levels of H3K9me3 deposition and gene silencing. While there are still major questions of how SUMO molecularly promotes this process, this study is a valuable first step that opens the door for interesting future experimentation.

Major Point:<br /> The RNAseq and ChIPseq data is not available. This is critical for the review of the paper and would help the readers and reviewers interpret the Bonus mutant phenotype and its mechanism of repressing genes.

1) The author's conclusion that Bonus SUMOylation is "essential for its chromatin localization" is not supported by the data. Figure 5F shows less 3KR mutant in the chromatin fraction but there is still significant signal.<br /> 2) The author's conclusion that Bonus is SUMOylated at a single site close to its N-terminus is not necessarily true. In several SUMO and Bonus blots throughout the paper (5B, 6C, S4A), there are >2 differentially migrating species that could represent more than one SUMO added to Bonus. While the single K20R mutation eliminates all of these species in Fig 5C, it is possible that K20R SUMOylation is required for additional SUMOylation events on other residues. One way to determine if Bonus is SUMOylated on multiple sites is to add recombinant SUMO protease to the extract and see if multiple higher molecular weight bands collapse into a single migrating species (implying multiple SUMOs) or multiple migrating species (implying something else is altering gel migration).<br /> 3) The authors state that most upregulated genes in BonusGLKD are not highly enriched in H3K9me3. The heatmap in figure 3D is not an ideal presentation of this argument. The authors should show an example of what the signal on a highly enriched gene looks like for comparison. The authors also argue that because most upregulated genes in BonusGLKD are not highly enriched in H3K9me3, they must be indirectly repressed. Another possibility is that bonus-mediated H3K9me3 is only important (and present) during early nurse cell differentiation and is later lost and dispensable during the rapid endocycles. After bonus establishes repression though H3K9me3, it might be maintained through bonus-Mi2/Nurd, something else, or nothing at all. The authors could discuss this possibility or perform H3K9me3 ChIP during cyst formation and early nurse cell differentiation rather than in whole ovaries, which are enriched for later stages.<br /> 4) The BonusGLKD RNAseq analysis is underwhelming. The conclusion that "Bonus represses tissue-specific genes" has limited value. Every gene that is not expressed in ovaries is "tissue-specific." What subset of tissue-specific genes does Bonus repress? What common features do these genes have and how do they compare to other sets of tissue-specific genes, such as those reportedly repressed by setdb1, Polycomb proteins, small ovary, l(3)mbt, and stonewall (among others in female germ cells). Comparing these available data sets could help the authors understand the mechanism of Bonus repression and how BonusGLKD leads to sterility. The authors could also further analyze the differences between nos-Gal4 and MT-Gal4 to better understand why nos- but not MT-driven knockdown is sterile.

Main Study Limitations:<br /> 1) It is unclear which genes are directly vs indirectly regulated by bonus, which makes it difficult to understand Bonus's repressive mechanism. Several lines of experiments could help resolve this issue. 1) Bonus ChIPseq, which the authors mentioned was difficult. 2) RNAseq of BonusGLKD rescued with KR3 mutation. This would help separate SUMO/setdb1-dependent regulation from Mi-2 dependent regulation. Similarly, comparing differentially expressed genes in Su(var)2-10GLKD, setdb1GLKD, 3KR rescue, and MI-2 GLKD could identify overlapping targets and help refine how bonus represses subsets of genes through these different corepressors.

2) The paper falls short in discussing how SUMO might promote repression. This is important when considering the conservation (of lack thereof) of SUMOylation sites in Tif1 proteins in distantly related animals. One piece of data that was not discussed is the apparent localization of SUMOylated bonus in the cytoplasmic fraction of the blot in Figure 5F. Su(var)2-10 is mostly a nuclear protein, so is bonus SUMOylated in the nucleus and then exported to the cytoplasm? Also, setdb1 is a nuclear protein, so it is unlikely that the SUMOylated bonus directly interacts with setdb1 on target genes. Together with Fig 5E (unSUMOylatable Bonus aggregates in the nucleus), one could make a model where SUMO solubilizes bonus (perhaps by disassembling aggregates) and indirectly allows it to associate with setdb1 and chromatin. It is also important to note that in Figure 5I, the K3R mutation appears to lessen but not eliminate Bonus interaction with setdb1. This data again disfavors a model where SUMO establishes an interaction interface between setdb1 and Bonus. To determine which form of Bonus interacts with setdb1, the authors could perform a setdb1 pulldown and monitor the SUMOylation state of coIPed Bonus through mobility shift. If mostly unSUMOylated bonus interacts with setdb1, and SUMO indirectly promotes Bonus interaction with setdb1 (perhaps by disassembling Bonus aggregates), then the precise locations of Bonus SUMOylation sites could more easily shift during evolution, disfavoring the author's convergent evolution hypothesis.

Reviewer #2 (Public Review):

Summary:<br /> The authors analyze the functions and regulation of Bon, the sole Drosophila ortholog of the TIF1 family of mammalian transcriptional regulators. Bon has been implicated in several developmental programs, however the molecular details of its regulation have not been well understood. Here, the authors reveal the requirement of Bon in oogenesis, thus establishing a previously unknown biological function for this protein. Furthermore, careful molecular analysis convincingly established the role of Bon in transcriptional repression. This repressor function requires interactions with the NuRD complex and histone methyltransferase SetDB1, as well as sumoylation of Bon by the E3 SUMO ligase Su(var)2-10. Overall, this work represents a significant advance in our understanding of the functions and regulation of Bon and, more generally, the TIF1 family. Since Bon is the only TIF1 family member in Drosophila, the regulatory mechanisms delineated in this study may represent the prototypical and important modes of regulation of this protein family. The presented data are rigorous and convincing. As discussed below, this study can be strengthened by a demonstration of a direct association of Bon with its target genes, and by analysis of the biological consequences of the K20R mutation.

Strengths:<br /> 1. This study identified the requirement for Bon in oogenesis, a previously unknown function for this protein.<br /> 2. Identified Bon target genes that are normally repressed in the ovary, and showed that the repression mechanism involves the repressive histone modification mark H3K9me3 deposition on at least some targets.<br /> 3. Showed that Bon physically interacts with the components of the NuRD complex and SetDB1. These protein complexes are likely mediating Bon-dependent repression.<br /> 4. Identified Bon sumoylation site (K20) that is conserved in insects. This site is required for repression in a tethering transcriptional reporter assay, and SUMO itself is required for repression and interaction with SetDB1. Interestingly, the K20-mutant Bon is mislocalized in the nucleus in distinct puncta.<br /> 5. Showed that Su(var)2-10 is a SUMO E3 ligase for Bon and that Su(var)2-10 is required for Bon-mediated repression.

Weaknesses:<br /> The study would be strengthened by demonstrating a direct recruitment of Bon to the target genes identified by RNA-seq. Given that the global ChIP-seq was not successful, a few possibilities could be explored. First, Bon ChIP-qPCR could be performed on the individual targets that were functionally confirmed (e.g. rbp6, pst). Second, a global Bon ChIP-seq has been reported in PMID: 21430782 - these data could be used to see if Bon is associated with specific targets identified in this study. In addition, it would be interesting to see if there is any overlap with the repressed target genes identified in Bon overexpression conditions in PMID: 36868234.

The second area where the manuscript can be improved is to analyze the biological function of the K20R mutant Bonus protein. The molecular data suggest that this residue is important for function, and it would be important to confirm this in vivo.

Reviewer #1 (Public Review):

In the study by Venkat et al. the authors expand the current knowledge of allosteric diversity in the human kinome by c-terminal splicing variants using as a paradigm DCLK1. In this work, the authors provide evolutionary and some mechanistic evidence about how c-terminal isoform specific variants generated by alternative splicing can regulate catalytic activity by means of coupling specific phosphorylation sites to dynamical and conformational changes controlling active site and substrate pocket occupancy, as well as interfering with protein-protein interacting interfaces that altogether provides evidence of c-terminal isoform specific regulation of the catalytic activity in protein kinases.

The paper is overall well written, the rationale and the fundamental questions are clear and well explained, the evolutionary and MD analyses are very detailed and well explained. Overall I think this is a study that brings some new aspects and concepts that are important for the protein kinase field, in particular the allosteric regulation of the catalytic core by c-terminal segments, and how evolutionary cues generate more sophisticated mechanisms of allosteric control in protein kinases.

Current submission: I have read and gone through the revised manuscript and the rebuttal letter and I confirm that the authors did an excellent job answering all the comments satisfactorily.

Reviewer #2 (Public Review):

In this study, the authors explore the structure/function of the DCLK kinases, most specifically DCLK1 as it is the most studied to date. Recently, the C-terminal domain has garnered attention as it was found to regulate the kinase domain, however, the different isoforms retain additional amino acid sequences with as-yet-undefined functions. The authors provide an evolutionary and biochemical characterization of these regions and provide evidence for some functionality for these additional C-terminal sequences. While these experiments are informative they do require that the protein is soluble and not membrane-bound as has been suggested to be important for functionality in other studies. Still, this is a major contribution to understanding the structure/function of these proteins that will be important in future experimental designs.

Reviewer #1 (Public Review):

This carefully done research paper presents a fundamental model of techniques that are useful for the elucidation of kinase substrates. The paper utilizes state-of-the-art approaches to define a kinetic phosphoproteome and how to integrate that data with complementary approaches using a chemical probe (in this case KTPyS, a triphosphate) to find these substrates. Using these approaches TgCDPK1 was demonstrated to affect microneme secretion via a direct interaction with a HOOK complex (defined as a HOOK protein TGG1_289100, an FTS TGGT1_264050 and 2 other proteins TGGT1_316650 and 306920).

This work is carefully controlled and the analysis pathways are logical and provide paradigms for how to approach the question of identifying substrates of kinases using proteomic approaches employing genetic and chemical strategies.

The authors succeeded in the identification of candidate substrates for TgCDPK1. Validation of the results was provided by previous studies in the literature that characterized some of these substrates as well as the experiments in this manuscript on the characterization of the HOOK complex that is phosphorylated by CDPK1.

The HOOK complex (defined as a HOOK protein TGG1_289100, an FTS TGGT1_264050, and 2 other proteins TGGT1_316650 and 306920) was clearly demonstrated to be involved in invasion via its role in microneme trafficking.

Reviewer #2 (Public Review):

In this study, the authors take a multipronged approach to identify the substrate repertoire of calcium-dependent protein kinase, CDPK1 in Toxoplasma that includes quantitative phosphoproteomics, myristoylation, thiophosphorylation, immunoprecipitation as well as proximity-based labeling. Their finding also reveals that CDPK1 functions in parasite invasion and egress by phosphorylating different protein candidates. More importantly, the authors successfully determine one branch of the CDPK1 signaling pathway that regulates invasion through the phosphorylation of the HOOK protein involved in the translocation and secretion of micronemal proteins.

Reviewer #3 (Public Review):

In this manuscript, Chan and collaborators investigate the role of CDPK1 in regulating microneme trafficking and exocytosis in Toxoplasma gondii. Micronemes are apicomplexan-specific organelles localized at the apical end of the parasite and depending on cortical microtubules. Micronemes contain proteins that are exocytosed in a Ca²+-dependent manner and are required for T. gondii egress, motility, and host-cell invasion. In Apicomplexa, Ca²+ signaling is dependent on Ca²+-dependent protein kinases (CDPKs). CDPK1 has been demonstrated to be essential for Ca²+-stimulated micronemes exocytosis allowing parasite egress, gliding motility, and invasion. It is also known that intracellular calcium storages are mobilized following a cyclic nucleotide-mediated activation of protein kinase G. This step, occurs upstream of CDPK1 functions. However, the exact signaling pathway regulated by CDPK1 remains unknown. In this paper, the authors used phosphoproteomic analysis to identify new proteins phosphorylated by CDPK1. They demonstrated that CDPK1 activity is required for calcium-stimulated trafficking of micronemes to the apical end, depending on a complex of proteins that include HOOK and FTS, which are known to link cargo to the dynein machinery for trafficking along microtubules. Overall, the authors identified evidence for a new protein complex involved in microneme trafficking through the exocytosis process for which circumstantial evidence of its functionality is demonstrated here.

Reviewer #1 (Public Review):

In this nice study, the authors set out to investigate the role of the canonical circadian gene Clock in the rhythmic biology of the basal metazoan Nematostella vectensis, a sea anemone, which might illuminate the evolution of the Clock gene functionality. To achieve their aims the team generated a Clock knockout mutant line (Clock-/- ) by CRISPR/Cas9 gene deletion and subsequent crossing. They then compared wild-type (WT) with Clock-/- animals for locomotor activity and transcriptomic changes over time in constant darkness (DD) and under light/dark cycles to establish these phenotypes under circadian control and those driven by light cycles. In addition, they used Hybridization Chain Reaction-In situ Hybridization (HCR-ISH) to demonstrate the spatial expression of Clock and a putative circadian clocl-controlled gene Myh7 in whole-mounted juvenile anemones.

The authors demonstrate that under LD both WT and Clock-/- animals were behaviourally rhythmic but under DD the mutants lost this rhythmicity, indicating that Clock is necessary for endogenous rhythms in activity. With altered LD regimes (LD6:6) they show also that Clock is light-dependent. RNAseq comparisons of rhythmic gene expression in WT and Clock-/- animals suggest that clock KO has a profound effect on the rhythmic genome, with very little overlap in rhythmic transcripts between the two phenotypes; of the rhythmic genes in both LD and DD in WT animals (220- termed clock-controlled genes, CCGS) 85% were not rhythmic in Clock-/- animals in either light condition. In silico gene ontology (GO) analysis of CCGS reflected process associated with circadian control. Correspondingly, those genes rhythmic in KO animals under DD (here termed neoCCGs) were not rhythmic in WT, lacked upstream E-box motifs associated with circadian regulation, and did not display any GO enrichment terms. 'Core' circadian genes (as identified in previous literature) in WT and Clock-/- animals were only rhythmic under entrainment (LD) conditions whilst Clock-/- displayed altered expression profiles under LD compared to WT. Comparing CCGs with previous studies of cycling genes in Nematostellar, the authors selected a gene from 16 rhythmic transcripts. One of these, Myh7 was detectable by both RNAseq and HCR-ISH and considered a marker of the circadian clock by the authors.

The authors claim that the study reveals insights into the evolutionary origin of circadian timing; Clock is conserved across distant groups of organisms, having a function as a positive regulator of the transcriptional translational feedback loop at the heart of daily timing, but is not a central element of the core feedback loop circadian system in this basal species. Their behavioural and transcriptomic data largely support the claims that Clock is necessary for endogenous daily activity but that the putative molecular circadian system is not self-sustained under constant darkness (this was known already for WT animals)- rather it is responsive to light cycles with altered dynamics in Clock-/- specimens in some core genes under LD. In the main, I think the authors achieved their aims and the manuscript is a solid piece of important work. The Clock-/- animal is a useful resource for examining time-keeping in a basal metazoan.

The work described builds on other transcriptomic-based works on cnidaria, including Nematostellar, and does probe into the molecular underpinnings with a loss-of-function in a gene known to be core in other circadian systems. The field of chronobiology will benefit from the evolutionary aspect of this work and the fact that it highlights the necessity to study a range of non-model species to get a fuller picture of timing systems to better appreciate the development and diversity of clocks.

Strengths:<br /> The generation of a line of Clock mutant Nematostellar is a very useful tool for the chronobiological community and coupled with a growing suite of tools in this species will be an asset. The experiments seem mostly well conceived and executed (NB see 'weaknesses'). The problem tackled is an interesting one and should be an important contribution to the field.

Weaknesses:<br /> I think the claims about shedding light on the evolutionary origin of circadian time maintenance are a little bold. I agree that the data do point to an alternative role for Clock in this animal in light responsiveness, but this doesn't illuminate the evolution of time-keeping more broadly in my view. In addition, these are transcriptomic data and so should be caveated- they only demonstrate the expression of genes and not physiology beyond that. The time-course analysis is weakened by its low resolution, particularly for the RAIN algorithm when 4-hour intervals constrain the analysis. I accept that only 24h rhythms were selected in the analysis from this but, it might be that detail was lost - I think a preferred option would be 2 or 3-hour resolution or 2 full 24h cycles of analysis.

The authors discount the possibility of the observed 12h rhythmicity in Clock-/- animals by exposing them to LD6:6 cycles before free-running them in DD. I suggest that LD cycles are not a particularly robust way to entrain tidal animals as far as we know. Recent papers show inundation/mechanical agitation are more reliable cues (Kwiatkowski ER, et al. Curr Biol. 2023, 2;33(10):1867-1882.e5. doi: 10.1016/j.cub.2023.03.015; Zhang L., et al Curr Biol. 2013, 23;19, 1863-1873 doi.org/10.1016/j.cub.2013.08.038.) and might be more effective in revealing endogenous 12h rhythms in the absence of 24h cues.

Reviewer #2 (Public Review):

This manuscript addresses an important question: what is the role of the gene Clock in the control of circadian rhythms in a very primitive group of animals: Cnidaria. Clock has been found to be essential for circadian rhythms in several animals, but its function outside of Bilaterian animals is unknown. The authors successfully generated a severe loss-of-function mutant in Nematostella. This is an important achievement that should help in understanding the early evolution of circadian clocks. Unfortunately, this study currently suffers from several important weaknesses. In particular, the authors do not present their work in a clear fashion, neither for a general audience nor for more expert readers, and there is a lack of attention to detail. There are also important methodological issues that weaken the study, and I have questions about the robustness of the data and their analysis. I am hoping that the authors will be able to address my concerns, as this work should prove important for the chronobiology field and beyond. I have highlighted below the most important issues, but the manuscript needs editing throughout to be accessible to a broad audience, and referencing could be improved.

Major issues:<br /> 1) Why do the authors make the claim in the abstract that CLOCK function is conserved with other animals when their data suggest that it is not essential for circadian rhythms? dCLK is strictly required in Drosophila for circadian rhythms. In mammals, there are two paralogs, CLOCK and NPAS2, but without them, there are no circadian rhythms either. Note also that the recent claim of BMAL1-independent rhythms in mammals by Ray et al., quoted in the discussion to support the idea that rhythms can be observed in the absence of the positive elements of the circadian core clock, had to be corrected substantially, and its main conclusions have been disputed by both Abruzzi et al. and Ness-Cohn et al. This should be mentioned.

2) The discussion of CIPC on line 222 is hard to follow as well. How does mRNA rhythm inform the function of CIPC, and why would it function as a "dampening factor"? Given that it is "the only core clock member included in the Clock-dependent CCGs," (220) more discussion seems warranted. Discussing work done on this protein in mammals and flies might provide more insight.

3) The behavioral arrhythmicity seen with their Clock mutation is really interesting. However, what is shown is only an averaged behavior trace and a single periodogram for the entire population. This leaves open the possibility that individual animals are poorly synchronized with each other, rather than arrhythmic. I also note that in DD there seem to be some residual rhythms, though they do not reach significance. Thus, it is also possible that at least some individual animals retain weak rhythms. The authors should analyze behavioral rhythms in individual animals to determine whether behavioral rhythmicity is really lost. This is important for the solidity of their main conclusions.

4) There is no mention in the results section of the behavior of heterozygotes. Based on supplement figure 2A, there is a clear reduction in amplitude in the heterozygous animals. Perhaps this might be because there is only half a dose of Clock, but perhaps this could be because of a dominant-negative activity of the truncated protein. There is no direct functional evidence to support the claim that the mutant allele is nonfunctional, so it is important to discuss carefully studies in other species that would support this claim, and the heterozygous behavior since it raises the possibility that the mutant allele acts as a dominant negative.

5) I do not understand what the bar graphs in Figure 2E and 3B represent - what does the y-axis label refer to?

6a. I note that RAIN was used, with a p<0.05 cut-off. I believe RAIN is quite generous in calling genes rhythmic, and the p-value cut-off is also quite high. What happens if the stringency is increased, for example with a p<0.01.<br /> b. It would be worth choosing a few genes called rhythmic in different conditions (mutant or wild-type. LD or DD), and using qPCR to validate the RNAseq results. For example, in Figure 3D, Myh7 RNAseq data are shown, and they do not look convincing. I am surprised this would be called a circadian rhythm. In wild-type, the curve seems arrhythmic to me, with three peaks, and a rather large difference between the first and second ZT0 time point. In the Clock mutants, rhythms seem to have a 12hr period, so they should not be called rhythmic according to the material and methods, which says that only ca 24hr period mRNA rhythms were considered rhythmic. Also, the result section does not say anything about Myh7 rhythms. What do they tell us? Why were they presented at all?

7) The authors should explain better why only the genes that are both rhythmic in LD and DD are considered to be clock-controlled genes (CCGs). In theory, any gene rhythmic in DD could be a CCG. However, Leach and Reitzel actually found that most genes in DD1 do not cycle the next day (DD2)? This suggests that most "rhythmic" genes might show a transient change in expression due to prolonged obscurity and/or the stress induced by the absence of a light-dark cycle, rather than being clock controlled. Is this why the authors saw genes rhythmic under both LD and DD as actual CCGs? I would suggest verifying that in DD the phase of the oscillation for each CCG is similar to that in LD. If a gene is just responding to obscurity, it might show an elevated expression at the end of the dark period of LD, and then a high level in the first hours of DD. Such an expression pattern would be very unlikely to be controlled by the circadian clock.

8) Since there are still rhythms in LD in Clock mutants, I wonder whether there is a paralog that could be taking Clock's place, similar to NPAS2 in mammals.

9) I do not follow the point the authors try to make in lines 268-272. The absence of anticipatory behavior in Drosophila Clk mutants results from disruption of the circadian molecular clock, due to the loss of Clk's circadian function. Which light-dependent function of Clock are the authors referring to, then? Also, following this, it should be kept in mind that clock mutant mice have a weakened oscillator. The effect on entrainment is secondary to the weakening of the oscillator, rather than a direct effect on the light input pathway (weaker oscillators have increased response to environmental inputs). The authors thus need to more clearly explain why they think there is a conservation of circadian and photic clock function.

Reviewer #1 (Public Review):

In their manuscript, Laporte et al. analyze the process of formation of the quiescent-cell nuclear microtubule (Q-nMT) bundle, a set of parallel MTs that emanate from the nuclear side of the spindle pole bodies (SPBs) upon the entry of Saccharomyces cerevisiae cells in quiescence. Based on their results, the authors propose that Q-nMT bundle formation is a multistep process that comprises three distinct sequential phases. The authors further evaluate the role of different factors during the growth of the Q-nMT bundle upon quiescence entry, as well as during the disassembly of this structure once cells resume their proliferation.

The Q-nMT is an interesting cellular structure whose physiological function is still widely unknown. Hence, providing new insights into the dynamics of Q-nMT bundle formation and identifying new factors involved in this process is an interesting topic of relevance in the field. The authors made a substantial effort in order to evaluate Q-nMT bundle formation and provide a considerable amount of data, mainly obtained from microscopy analyses. Overall, the experiments are well described and properly executed, and the data in the manuscript are clearly presented.

Despite the interest in the study, there are important issues that could affect the validity of the conclusions drawn in the manuscript. In this way, regarding the analysis of the dynamics of Q-nMT bundle formation, the experimental set up described in some of the experiments raises certain concerns, which mostly derive from the nocodazole treatments and the use of this microtubule-depolymerizing agent as the only approach to evaluate the stability of the Q-nMT bundle. On the other hand, regarding the factors involved in Q-nMT formation, the differences in microtubule length with the wild-type strain, despite being statistically significant, are really subtle for many of the mutants analyzed (e.g., bir1, slk19, etc.). Additionally, there are proteins that are proposed to participate in the process of Q-nMT formation and whose expression during quiescence needs to be demonstrated. Finally, although the cell viability defects observed for some of the mutants in these factors could be certainly associated with the lack of expression or mutation of the specific gene under evaluation, in none of the cases can they be directly attributed to a defect in aberrant Q-nMT bundle formation.

Based on the aforementioned reasons, and despite the considerable effort by the authors, it is my impression that many of the conclusions of the manuscript are not sufficiently justified by the data provided. Additional evidence, including the incorporation of key experimental controls that are currently missing, would be required in order to more strongly support the conclusions of the manuscript.

Reviewer #2 (Public Review):

Summary: The authors investigate the assembly of the Q-nMT, a stable microtubule structure that is assembled during quiescence. Notably, the authors show that the formation of the Q-nMT cannot be solely explained by changes in the physicochemical properties of quiescent cells. The authors report that Q-nMT assembly occurs in three regulated steps and identify kinesin motor proteins involved in the assembly and disassembly of the structure.

Strengths: The findings provide new insight into the assembly and possible function of the Q-nMT with respect to the response of haploid budding yeast to glucose starvation.

Weaknesses: The manuscript would benefit from more precise language and requires additional clarification regarding how claims are supported by the evidence. Clear definitions are also required, for example, "active process" is not defined. Some conclusions are not supported by the results, for example, the claim that the Q-nMT functions as a checkpoint effector that inhibits re-entry into the cell cycle.

Reviewer #3 (Public Review):

In this study, the authors analyzed a unique and very stable microtubule bundle that is formed in yeast cells entering quiescence. They show that the structure is required for yeast cells to maintain viability during quiescence and that it needs to be disassembled for cell cycle re-entry. They identify different stages during the assembly process and focus on the molecular players required for microtubule bundle formation and stabilization. They identify kinetochore as well as molecular motors such as auroraB, kinesin-14, and kinesin-5 that assemble, stabilize and crosslink the microtubules of the bundle. The paper also investigates the disassembly of the structure and shows that disassembly is required for cell cycle re-entry.

The study is very comprehensive, provides quantifications to support claims, and identifies various players involved in these processes, providing mechanistic insight. It also presents various control experiments to exclude alternative explanations and support the proposed model.

It is the first molecular-level insight into how this very stable microtubule structure can be assembled, maintained, and disassembled, and how this is coordinated with cell cycle exit and re-entry. This information may be very useful when analyzing similarly stable, microtubule-based structures in other organisms such as cilia in animals, which also display cell cycle-coordinated dynamics.

Overall, this is a nicely presented study that provides important insight into the field and beyond, but there are a few points that need to be addressed regarding methods used for quantifications and data presentation.

Reviewer #1 (Public Review):

In their study, Aman et al. utilized single cell transcriptome analysis to investigate wild-type and mutant zebrafish skin tissues during the post-embryonic growth period. They identified new epidermal cell types, such as ameloblasts, and shed light on the effects of TH on skin morphogenesis. Additionally, they revealed the important role of the hypodermis in supporting pigment cells and adult stripe formation. Overall, I find their figures to be of high quality, their analyses to be appropriate and compelling, and their major claims to be well-supported by additional experiments. Therefore, this study will be an important contribution to the field of vertebrate skin research.

Reviewer #2 (Public Review):

This work describes transcriptome profiling of dissected skin of zebrafish at post-embryonic stages, at a time when adult structures and patterns are forming. The authors have used the state-of-the-art combinatorial indexing RNA-seq approach to generate single cell (nucleus) resolution. The data appears robust and is coherent across the four different genotypes used by the authors.

The authors present the data in a logical and accessible manner, with appropriate reference to the anatomy. They include helpful images of the biology and schematics to illustrate their interpretations.

The datasets are then interrogated to define cell and signalling relationships between skin compartments in six diverse contexts. The hypotheses generated from the datasets are then tested experimentally. Overall, the experiments are appropriate and rigorously performed. They ask very interesting questions of interactions in the skin and identify novel and specific mechanisms. They validate these well.

The authors use their datasets to define lineage relationships in the dermal scales and also in the epidermis. They show that circumferential pre-scale forming cells are precursors of focal scale forming cells while there appeared a more discontinuous relationship between lineages in the epidermis.

The authors present transcriptome evidence for enamel deposition function in epidermal subdomains. This is convincingly confirmed with an ameloblastin in situ. They further demonstrate distinct expression of SCPP and collagen genes in the SFC regions.

The authors then demonstrate that Eda and TH signalling to the basal epidermal cells generates FGF and PDGF ligands to signal to surrounding mesenchyme, regulating SFC differentiation and dermal stratification respectively.

Finally, they exploit RNA-seq data performed in parallel in the bnc2 mutants to identify the hypodermal cells as critical regulators of pigment patterning and define the signalling systems used.

Whilst these six interactions in the skin are disparate, the stories are unified by use of the sci-RNA-seq data to define interactions. Overall, it's an assembly of work which identifies novel and interesting cell interactions and cross-talk mechanisms.

The paper provides robust evidence of cell interrelationships in the skin undergoing morphogenesis and will be a welcome dataset for the field.

Reviewer #2 (Public Review):

This work describes transcriptome profiling of dissected skin of zebrafish at post-embryonic stages, at a time when adult structures and patterns are forming. The authors have used the state-of-the-art combinatorial indexing RNA-seq approach to generate single cell (nucleus) resolution. The data appears robust and is coherent across the four different genotypes used by the authors.

The authors present the data in a logical and accessible manner, with appropriate reference to the anatomy. They include helpful images of the biology and schematics to illustrate their interpretations.

The datasets are then interrogated to define cell and signalling relationships between skin compartments in six diverse contexts. The hypotheses generated from the datasets are then tested experimentally. Overall, the experiments are appropriate and rigorously performed. They ask very interesting questions of interactions in the skin and identify novel and specific mechanisms. They validate these well.

The authors use their datasets to define lineage relationships in the dermal scales and also in the epidermis. They show that circumferential pre-scale forming cells are precursors of focal scale forming cells while there appeared a more discontinuous relationship between lineages in the epidermis.

The authors present transcriptome evidence for enamel deposition function in epidermal subdomains. This is convincingly confirmed with an ameloblastin in situ. They further demonstrate distinct expression of SCPP and collagen genes in the SFC regions.

The authors then demonstrate that Eda and TH signalling to the basal epidermal cells generates FGF and PDGF ligands to signal to surrounding mesenchyme, regulating SFC differentiation and dermal stratification respectively.

Finally, they exploit RNA-seq data performed in parallel in the bnc2 mutants to identify the hypodermal cells as critical regulators of pigment patterning and define the signalling systems used.

Whilst these six interactions in the skin are disparate, the stories are unified by use of the sci-RNA-seq data to define interactions. Overall, it's an assembly of work which identifies novel and interesting cell interactions and cross-talk mechanisms.

The paper provides robust evidence of cell interrelationships in the skin undergoing morphogenesis and will be a welcome dataset for the field.

Reviewer #1 (Public Review):

Polymorphisms in genes in the human leukocyte antigen (HLA) class II region comprise the most important inherited risk factors for many autoimmune diseases including type 1 diabetes (T1D) and celiac disease (CD). The paper focuses on the novel triad ((SNPs): rs3135394, rs9268645, and rs3129877) finding quite interesting results. The paper suggests further studies at the molecular and structural level to increase our fundamental knowledge of the etiology of autoimmune deceases.

Reviewer #2 (Public Review):

In this manuscript, Aydemir et al. utilized the large TEDDY study and examined the effect of previously identified tri-SNP in the HLA-DRA gene on the risk of type 1 diabetes (T1D) and celiac disease (CD). They confirmed the protective effect of the tri-SNP haplotype "101" on T1D development. Meanwhile, the same haplotype appeared to be positively associated with risk for CD and the development of CD autoimmunity. The authors further explored the molecular effect of different tri-SNP haplotypes. They proposed that C4A and C4B might be the downstream target.

Overall, the study is rigorously conducted with proper statistical methods applied. The tri-SNP could be used as an additional risk factor when estimating T1D and celiac disease susceptibility in genetic screening. However, how this locus be incorporated into the current scheme of genetic screening is not discussed and is unlikely to be straightforward.

Reviewer #2 (Public Review):

In this study, Aso and Rubin generated new split-GAL4 lines to label Drosophila mushroom body output neurons (MBONs) that previously lacked specific GAL4 drivers. The MBONs represent the output channels for the mushroom body (MB), a computational center in the fly brain. Prior research identified 21 types of typical MBONs whose dendrites exclusively innervate the MB and 14 types of atypical MBONs whose dendrites also innervate brain regions outside the MB. These MBONs transmit information from the MB to other brain areas and form recurrent connections to dopaminergic neurons whose axonal terminals innervate the MB. Investigating the functions of the MBONs is crucial to understanding how the MB processes information and regulates behavior. The authors previously established a collection of split-GAL4 lines for most of the typical MBONs and one atypical MBON. That split-GAL4 collection has been an invaluable tool for researchers studying the MB. This work extends their previous effort by generating additional driver lines labeling the MBON types not covered by the previous split-GAL4 collection. Using these new driver lines, the authors also activated the labeled MBONs using optogenetics and assessed their role in learning, locomotion, and valence coding. The expression patterns of the new split-GAL4 lines and the behavioral analysis presented in this manuscript are generally convincing. I believe that these new lines will be a valuable resource for the fly community.

Reviewer #1 (Public Review):

In this manuscript Rubin and Aso provide important new tools for the study of learning and memory in Drosophila. In flies, olfactory learning and memory occurs at the Mushroom Body (MB) and is communicated to the rest of the brain through Mushroom Body Output Neurons (MBONs). Previously, typical MBONs were thoroughly studied. Here, atypical MBONs that have dendritic input both within the MB lobes and in adjacent brain regions are studied. The authors describe new cell-type-specific GAL4 drivers for the majority of atypical MBONs (and other MBONs) and using an optogenetic activation screen they examined their ability to drive behaviors and learning.

The experiments in this manuscript were carefully performed and the results are clear. The tools provided in this manuscript are of great importance to the field.

Reviewer #1 (Public Review):

Summary:

Parkinson and colleagues address an interesting and important question, i.e., whether the bumblebee Bombus terrestris can perceive field-realistic concentrations of different pesticides in a sugar solution mimicking nectar. The study directly follows up on a previous study conducted by the same team (Kessler et al. 2015, Nature), which was partly questioned by another more recent study (Arce et al. 2018, Proc. R. Soc. B). The authors apply a combination of electrophysiological measurements and behavioral feeding tests to answer this question. Their results strongly suggest that B. terrestris workers are not able to perceive field-realistic doses of pesticides in a sugar solution. They additionally show that B. terrestris can physiologically differentiate between solutions varying in sugar composition.

Strengths:

Sophisticated methodology, a combination of approaches, clear and precise language

Weaknesses:

Topic and study implications could be discussed more broadly, the statistical approach is not fully clear to me.

Reviewer #2 (Public Review):

Summary:

This manuscript is part of the Wright lab's ongoing studies that investigate whether the bumblebee B. terrestris can detect the presence of pesticides when feeding. Previously, they showed that B. terrestris cannot detect neonicotinoids and would prefer food containing neonicotinoids (Kessler et al. 2015). However, in that paper, they showed that B. terrestris cannot taste neonicotinoids but did not provide evidence on why B. terrestris prefer food containing neonicotinoids. In the current paper, the authors continue to suggest that B. terrestris cannot taste neonicotinoids as well as another insecticide, sulfoxaflor, based on additional behavioral experiments and electrophysiological experiments focusing on specific GRNs. While the data from these experiments continue to suggest that B. terrestris cannot taste these insecticides using their mouthparts, whether B. terrestris can actually perceive these insecticides, and why this species prefers food containing these compounds is still unknown.

Strengths:

The authors provided additional evidence that B. terrestris cannot taste neonicotinoids with their mouthparts.

Weaknesses:

There are too many overgeneralizations in the manuscript and parts of it are written in a way that seems to sound combative towards studies from other groups that came to slightly different conclusions from their previous paper.

Reviewer #1 (Public Review):

This work investigates the function of the PTB domain containing adaptor protein Numb in skeletal muscle structure and function. In particular, the effects of reduced Numb expression in aging muscle is proposed as a mechanism for reduced contractile function associated with sarcopenia. Using ex-vivo analysis of conditional Numb and Numblike knockout muscle the authors demonstrate that loss of Numb but not the related Numblike expression perturbs muscle muscle force generation. In order to explore the molecular mechanisms involved, Numb interacting proteins were identified in C2C12 cell cultured myotubes by immunoprecipitation and LC-MS/MS. The authors identify Septin 7 as a Numb binding protein and demonstrate that loss of Numb/Numblike in myofibers causes changes in Septin 7 subcellular localization. Several questions remain. The authors could provide further clarity on the expression of Numb and Numb-like proteins and the specificity of antibodies used in this study since some Numb antibodies recognize both Numb and Numblike. The authors focus on septin 7 amongst the list of potential Numb interactions identified by AP-MS. Of note, septin 2, 9 and 10 were also identified in the AP-MS experiment. Whether these septins form a complex or are also disrupted by Numb/Numblike loss remains an interesting area for further investigation. Additional investigation of the specificity and mapping of the Numb-Septin 7 (or another Septin) interaction would be of interest and provide an approach for future studies to demonstrate the biological relevance and specificity of the Numb-Septin 7 interaction in skeletal muscle.

Reviewer #2 (Public Review):

Summary:<br /> This main purpose of this investigation was to 1) compare the effects of a single knockout (sKO) of Numb or a double knockout (dKO) of Numb and NumbL on ex-vivo physiological properties of the extensor digitorium longus (EDL) muscle in C57BL/6NCrl mice; and 2) analyze protein complexes isolated from C2C12 myotubes via immunoprecipitation and LC/MS/MS for potential Numb binding partners. The main findings are 1) the muscles from sKO and dKO were significantly weaker with little difference between the sKO and dKO lines, indicating the reduced force is mainly due to the inactivation of the Numb gene; and 2) there were 11 potential Numb binding proteins that were identified and cytoskeletal specific proteins including Septin 7.

Strengths:<br /> Strait-forward yet elegant design to help determine the important role the Numb has in skeletal muscle.

Weaknesses: There were a limited number of samples (3-6) that were used for the physiological experiments; however, there was a very large effect size in terms of differences in muscle tension development between the induced KO models and the controls.

Reviewer #1 (Public Review):

Summary:

Pineda et al investigate the association of the hypothesis that Dux4, an embryonic transcription factor, expression in tumor cells is associated with immune evasion and resistance to immunotherapy. They analyze existing cohorts of bulk RNAseq sequenced tumors across cancer types to identify Dux4 expression and association with survival. They find that Dux4 expression is detected in a higher proportion of metastatic tumors compared to primary tumors, is associated with decreased immune infiltrate and a variety of immune metrics and previously nominated immune signatures, and do an in depth evaluation of a cohort of metastatic urothelial cell carcinoma, finding that Dux4 expression is associated with a more immunodeficient tumor microenvironment (desert or excluded microenvironment) and worse survival in this aPDL1 treated cohort. They then find that Dux4 expression is a major independent predictor of survival in this cohort using different types of survival analyses (KM, Cox PH, and random survival forests). With prior existing biological data supporting the hypothesis (in prior work, the senior author has demonstrated Dux4 expression causally suppresses MHC-I expression in interferon-gamma treated cell lines), the current work links Dux4 expression with less immune activity in clinical tumor samples and with survival in ICI treated urothelial carcinomas, and demonstrates that Dux4 expression provides independent information towards survival including other molecular and clinical characteristics (TMB, ECOG PS as the other strongest markers), and provides interesting resolution on landmark analyses with TMB and Dux4 expression providing greater informativeness at later survival landmarks (e.g. 1 year and later), while ECOG PS has strong informativeness already at earlier time points. This work provides impetus towards more mechanistic and functional dissection of the mechanism of Dux4-associated changes with the tumor microenvironment (e.g. in vivo mouse studies) as well as potential interventional studies (e.g. Dux4 as a target in combination therapies). What the work does not provide is additional resolution on the mechanism of how Dux4 may be associated with a more immunodeficient microenvironment.

The conclusions are generally well supported, but there are issues that would benefit from clarification and extension:

- The finding that Dux4 expression is detected in a higher proportion of metastatic tumors and at higher levels compared to primaries (Fig 1BC) is striking. However, at least for one tumor type (melanoma), the "primary" samples are sourced as n=400+ tumors from TCGA, but the TCGA melanoma cohort is comprised of mostly metastatic (n=81 primary and 367 metastatic tumors in the PanCan Atlas), so it is unclear whether this is correctly interpreted. The analysis of tumors with matched FFPE and flash frozen samples with hybrid probe capture and polyA sequencing, respectively is a nice validation to show that the difference in Dux4 expression is not due to differences in preservation of starting material/sequencing in the metastatic samples vs primary samples (S1BC). However, the cited work from which this data arises (D. Robinson et al 2015) is a study of a cohort of prostate cancers with polyA bulk RNAseq sequencing and at least in that work does not seem to have matched FFPE sequencing, making the provenance of this data unclear at a minimum.

- The findings that Dux4 expression in the metastatic urothelial carcinoma setting is associated with a more immunodeficient microenvironment (Figure 2) is clear and unambiguous using multiple lines of data and analyses (bulk RNAseq, DUX4-positive vs DUX4-negative tumors, different immune cell and cytokine signatures; IHC showing an association with immune deserts and immune excluded phenotypes). However, this is an association and does not demonstrate causality.

- The survival analyses (Fig 3,4,5) show fairly convincingly that Dux4 provide independent predictive information beyond clinical variables and TMB towards survival in the aPDL1 treated metastatic urothelial carcinoma cohort, however, there are different choices of Dux4 expression categorization where the rationale is not clearly justified (e.g. Dux4 expression < 0.5 TPM and > 1 TPM in Fig 3, < 0.25 TPM and > 1 TPM in Fig 4 and 5) by either the underlying distribution (e.g. a bimodal distribution) or some type of percentile split.

- The authors demonstrate that adding Dux4 to clinical markers and TMB results in an improved predictive model for survival, but there are a few questions regarding this model as a clinical biomarker<br /> o Is Dux4 expression better than other correlated immune signatures/markers (e.g. interferon gamma, T effector signature, overall immune infiltrate) in providing additional information?<br /> o Since Dux4 expression is categorized to < 0.25 TPM and > 1 TPM, not all patients are included in the model (i.e. between 0.25 TPM and 1 TPM). How many patients this excludes is unclear, and is important to know if this is to be a clinically relevant biomarker.

- The use of random survival forests to quantify the (predictive) marginal effect of Dux4+ vs Dux4- expression on survival in a non-parametric model as well as shed light on association with survival at different landmark times using Shapley values is quite interesting and well conducted.

Reviewer #2 (Public Review):

Summary:

This article takes an expansive look at the potential role of DUX4 in cancer treatment and prognosis, including its correlation with other key biomarkers, the potential for cancer to be resistant to treatment, and risk prediction.

Strengths:

The primary strength of this work is the breadth of the analyses. The authors have linked DUX4 to not just one but multiple points in the trajectory of cancer, which increases the face validity of their conclusion that DUX4 is meaningfully related to the course of a cancer as well as the prognosis for a patient.

Statistically, the authors have taken care to properly validate their findings using appropriate bootstrapping and testing strategies.

Weaknesses:

Several weaknesses are noted. First, there is little-to-no description of the underlying sample population. It is only stated that "several large cohorts of patients with different metastatic cancers" were analyzed, and that a cohort of patients with advanced urothelial cancer was used for estimating associations with clinical outcomes. Lacking is information on the sampling mechanism, inclusion/exclusion criteria, treatment modalities, the definition of 'time = 0', the number of events observed, or even the sample size. Knowledge about the underlying study design would help explain some counterintuitive results, e.g. that the hazard of death among patients with Stage IV cancer is half that of those with Stage I cancer (Table 1); presumably this is not because Stage IV is actually protective but rather an artifact of the sampling scheme for these data. Second, the definition of negative versus positive DUX4 expression varies throughout the paper. In Figure 2A and Figure 3A, it is defined as >1 TPM vs. <= 1 TPM; in Figure 3C, it is defined as >1 TPM vs. < 0.5 TPM; in Figure 4A and Figure 5A, it is defined as >1 TPM vs. < 0.25 TPM; in Figure S1C it is partitioned into four groups, with boundaries defined at 0.25 TPM, 1 TPM, and 5 TPM. If categorization is needed, a rationale should be provided (ideally prospectively and not based upon the observed data, so as to avoid the perception of forking paths analyses), and it should be consistently applied. Third and finally, data seem to be occasionally excluded without rationale. For example, as mentioned above, the Cox model presented in Figure 4A seems to exclude all patients with DUX4 TPM between 0.25 and 1. Figure 3C excludes patients with either DUX4 TPM between 0.5 and 1 and/or with TMB in the lowest quartile (although the latter decision was ostensibly to control for TMB confounding, there are more appropriate ways to do so that don't result in loss of data, e.g. a stratified KM plot). Excluding patients based upon a particular region of the covariate space makes interpreting the resulting model awkward.

Reviewer #1 (Public Review):

In this study, the researchers aimed to investigate the cellular landscape and cell-cell interactions in cavernous tissues under diabetic conditions, specifically focusing on erectile dysfunction (ED). They employed single-cell RNA sequencing to analyze gene expression patterns in various cell types within the cavernous tissues of diabetic individuals. The researchers identified decreased expression of genes associated with collagen or extracellular matrix organization and angiogenesis in several cell types, including fibroblasts, chondrocytes, myofibroblasts, valve-related lymphatic endothelial cells, and pericytes. They also discovered a newly identified marker, LBH, that distinguishes pericytes from smooth muscle cells in mouse and human cavernous tissues. Furthermore, the study revealed that pericytes play a role in angiogenesis, adhesion, and migration by communicating with other cell types within the corpus cavernosum. However, these interactions were found to be significantly reduced under diabetic conditions. The study also investigated the role of LBH and its interactions with other proteins (CRYAB and VIM) in maintaining pericyte function and highlighted their potential involvement in regulating neurovascular regeneration. Overall, the manuscript is well-written and the study provides novel insights into the pathogenesis of ED in patients with diabetes and identifies potential therapeutic targets for further investigation.

Reviewer #2 (Public Review):

Summary: In this manuscript, the authors performed single cell RNA-sequencing of cells from the penises of healthy and diabetes mellitus model (STZ injection-based) mice, identified *Lbh* as a marker of penis pericytes, and report that penis-specific overexpression of *Lbh* is sufficient to rescue erectile function in diabetic animals. In public human single cell RNA-sea datasets, the authors report that *LBH* is similarly specific to pericytes and down regulated in diabetic patients. Additionally, the authors report discovery of CRYAB and VIM1 as protein interacting partners with LBH.

The authors contributions are of interest to the erectile dysfunction community and their *Lbh* overexpression experiments are especially interesting and well-conducted. However, claims in the manuscript regarding the specificity of *Lbh* as a pericyte marker, the mechanism by which *Lbh* overexpression rescues erectile function, cell-cell interactions impaired by diabetes, and protein-interaction partners require qualification or further evidence to justify.

Major claims and evidence:

1. Marker gene specificity and quantification: One of the authors' major contributions is the identification of *Lbh* as a marker of pericytes in their data. The authors present qualitative evidence for this marker gene relationship, but it is unclear from the data presented if *Lbh* is truly a specific marker gene for the pericyte lineage (either based on gene expression or IF presented in Fig. 2D, E). Prior results (see Tabula Muris Consortium, 2018) suggest that *Lbh* is widely expressed in non-pericyte cell types, so the claims presented in the manuscript may be overly broad. Even if *Lbh* is not a globally specific marker, the authors' subsequent intervention experiments argue that it is still an important gene worth studying.<br /> 2. Cell-cell communication and regulon activity changes in the diabetic penis: The authors present cell-cell communication analysis and TF regulon analysis in Fig 3 and report differential activities in healthy and DM mice. These results are certainly interesting, however, no statistical analyses are performed to justify claimed changes in the disease state and no validations are performed. It is therefore challenging to interpret these results, and the relevant claims do not seem well supported.<br /> 3. Rescue of ED by Lbh overexpression: This is a striking and very interesting result that warrants attention. By simple overexpression of the pericyte marker gene Lbh, the authors report rescue of erectile function in diabetic animals. While mechanistic details are lacking, the phenomenon appears to have a large effect size and the experiments appear sophisticated and well conducted. If anything, the authors appear to underplay the magnitude of this result.<br /> 4. Mechanistic claims for rescue of ED by Lbh overexpression: The authors claim that cell type-specific effects on MPCs are responsible for the rescue of erectile function induced by Lbh overexpression. This causal claim is unsupported by the data, which only show that Lbh overexpression influences MPC performance. In vivo, it's likely that Lbh is being over expressed by diverse cell types, any of which could be the causal driver of ED rescue. In fact, the authors report rescue of cell type abundance in endothelial cells and neuronal cells. Therefore, it cannot be concluded that MPC effects alone or in principal are responsible for ED rescue.<br /> 5. Protein interaction data: The authors claim that CRYAB and VIM1 are novel interacting partners of LBH. However, the evidence presented (2 blots in Fig. 6A,B) lack the relevant controls. It is possible that CRYAB and VIM1 are cross-reactive with the anti-LBH antibody or were not washed out completely. The abundance of bands on the Coomassie stain in Fig. 6A suggests that either event is plausible. Therefore, the evidence presented is insufficient to support the claim that CRYAB and VIM1 are protein interacting partners of LBH.

**Impact**: These data will trigger interest in Lbh as a target gene within the erectile dysfunction community.

Reviewer #3 (Public Review):

Bae et al. described the key roles of pericytes in cavernous tissues in diabetic erectile dysfunction using both mouse and human single-cell transcriptomic analysis. Erectile dysfunction (ED) is caused by dysfunction of the cavernous tissue and affects a significant proportion of men aged 40-70. The most common treatment for ED is phosphodiesterase 5 inhibitors; however, these are less effective in patients with diabetic ED. Therefore, there is an unmet need for a better understanding of the cavernous microenvironment, cell-cell communications in patients with diabetic ED, and the development of new therapeutic treatments to improve the quality of life.

Pericytes are mesenchymal-derived mural cells that directly interact with capillary endothelial cells (ECs). They play a vital role in the pathogenesis of erectile function as their interactions with ECs are essential for penile erection. Loss of pericytes has been associated with diabetic retinopathy, cancer, and Alzheimer's disease and has been investigated in relation to the permeability of cavernous blood vessels and neurovascular regeneration in the authors' previous studies. This manuscript explores the mechanisms underlying the effect of diabetes on pericyte dysfunction in ED. Additionally, the cellular landscape of cavernous tissues and cell type-specific transcriptional changes were carefully examined using both mouse and human single-cell RNA sequencing in diabetic ED. The novelty of this work lies in the identification of a newly identified pericyte (PC)-specific marker, LBH, in mouse and human cavernous tissues, which distinguishes pericytes from smooth muscle cells. LBH not only serves as a cavernous pericyte marker, but its expression level is also reduced in diabetic conditions. The LBH-interacting proteins (Cryab and Vim) were further identified in mouse cavernous pericytes, indicating that these signaling interactions are critical for maintaining normal pericyte function. Overall, this study demonstrates the novel marker of pericytes and highlights the critical role of pericytes in diabetic ED.

Joint Public Review:

In this manuscript, the authors proposed an approach to systematically characterise how heterogeneity in a protein signalling network affects its emergent dynamics, with particular emphasis on drug-response signalling dynamics in cancer treatments. They named this approach Meta Dynamic Network (MDN) modelling, as it aims to consider the potential dynamic responses globally, varying both initial conditions (i.e., expression levels) and biophysical parameters (i.e., protein interaction parameters). By characterising the "meta" response of the network, the authors propose that the method can provide insights not only into the possible dynamic behaviours of the system of interest but also into the likelihood and frequency of observing these dynamic behaviours in the natural system.

The authors studied the Early Cell Cycle (ECC) network as a proof of concept, specifically focusing on PI3K, EGFR, and CDK4/6, with particular interest in identifying the mechanisms that cancer could potentially exploit to display drug resistance. The biochemical reaction model consists of 50 equations (state variables) with 94 kinetic parameters, described using SBML and computed in Matlab. Based on the simulations, the authors concluded the following main points: a large number of network states can facilitate resistance, the individual biophysical parameters alone are insufficient to predict resistance, and adaptive resistance is an emergent property of the network. Finally, the authors attempt to validate the model's prediction that differential core sub-networks can drive drug resistance by comparing their observations with the knock-out information available in the literature. The authors identified subnetworks potentially responsible for drug resistance through the inhibition of individual pathways. Importantly, some concerns regarding the methodology are discussed below, putting in doubt the validity of the main claims of this work.

While the authors proposed a potentially useful computational approach to better understand the effect of heterogeneity in a system's dynamic response to a drug treatment (i.e., a perturbation), there are important weaknesses in the manuscript in its current form:

(1) It is unclear how the random parameter sets (i.e., model instances) and initial conditions are generated, and how this choice biases or limits the general conclusions for the case studied. Particularly, it is not evident how the kinetic rates are related to any biological data, nor if the parameter distributions used in this study have any biological relevance.<br /> (2) Related to this problem, it is not clear whether the considered 100,000 random parameter samples sufficiently explore parameter space due to the combinatorial explosion that arises from having 94 free parameters, nor 100,000 random initial conditions for a system with 50 species (variables).<br /> (3) Moreover, the authors filter out all the cases with stiff behaviour. This filtering step appears to select model parameters based on computational convenience, rather than biological plausibility.<br /> (4) Also, it is not clear how exactly the drug effect is incorporated into the model (e.g., molecular inhibition?), nor how it is evaluated in the dynamic simulations (e.g., at the beginning of the simulation?). Moreover, in a complex network, the results may differ depending on whether the inhibition is applied from the start or after the network has reached a stable state.<br /> (5) On the same line, the conclusions need to be discussed in the context of stability, particularly when evaluating the role of initial conditions. As stable steady states are determined by the model parameters, once again, the details of how the perturbation effect is evaluated on the simulation dynamics are critical to interpret the results.<br /> (6) The presented validation of the model results (Fig. 7) is only qualitative, and the interpretation is not carefully discussed in the manuscript, particularly considering the comparison between fold-change responses without specifying the baseline states.

Reviewer #1 (Public Review):

Wang and all present an interesting body of work focused on the effects of high altitude and hypoxia on erythropoiesis, resulting in erythrocytosis. This work is specifically focused on the spleen, targeting splenic macrophages as central cells in this effect. This is logical since these cells are involved in erythrophagocytosis and iron recycling. The results suggest that hypoxia induces splenomegaly with decreased number of splenic macrophages. There is also evidence that ferroptosis is induced in these macrophages, leading to cell destruction. However, additional data demonstrates that RBC clearance is increased, aka shortening the RBC lifespan, calling into question whether splenic function is impaired in hypoxia or whether the spleen enlargement is compensatory, leading to increased erythropoiesis; similarly, increased iron in the spleen provides potential evidence of enhanced erythrophagocytosis with iron release. Many of the reviewers' prior comments are not addressed or only superficially addressed and the additional experimental results and text to the background and discussion sections in the revised manuscript does not increase enthusiasm or clarity. Taken together, there are many issues with the presented results, with somewhat superficial data, with overstated conclusions, decreasing confidence that the hypotheses and observed results are directly causally related to hypoxia in the way that the authors propose.

Reviewer #2 (Public Review):

The authors aimed at elucidating the development of high altitude polycythemia which affects mice and men staying in a hypoxic atmosphere at high altitude (hypobaric hypoxia; HH). HH causes increased erythropoietin production which stimulates the production of red blood cells. The authors hypothesize that increased production is only partially responsible for exaggerated red blood cell production, i.e. polycythemia, but that decreased erythrophagocytosis in the spleen contributes to high red blood cells counts.

The main strength of the study is the use of a mouse model exposed to HH in a hypobaric chamber. However, not all of the reported results are convincing due to some smaller effects which one may doubt to result in the overall increase in red blood cells as claimed by the authors. Moreover, direct proof for reduced erythrophagocytosis is compromised due to a strong spontaneous loss of labelled red blood cells, although effects of labelled E. coli phagocytosis are shown.

Their discussion addresses some of the unexpected results, such as the reduced expression of HO-1 under hypoxia but due to the above mentioned limitations much of the discussion remains hypothetical.

In response to the reviewers´comments the authors extensively tried to address the points that were raised. They provided additional data, removed figures from the initial manuscript and referred to ongoing or further work. Nevertheless, not all questions could be answered leaving some hand-waiving and hypothetical explanations for some unexpected results.

Reviewer #3 (Public Review):

The manuscript by Yang et al. investigated in mice how hypobaric hypoxia can modify the RBC clearance function of the spleen, a concept that is of interest. Via interpretation of their data, the authors proposed a model that hypoxia causes an increase in cellular iron levels, possibly in RPMs, leading to ferroptosis, and downregulates their erythrophagocytic capacity. However, most of the data is generated on total splenocytes/total spleen, and the conclusions are not always supported by the presented data. The model of the authors could be questioned by the paper by Youssef et al. (which the authors cite, but in an unclear context) that the ferroptosis in RPMs could be mediated by augmented erythrophagocytosis. As such, the loss of RPMs in vivo which is indeed clear in the histological section shown (and is a strong and interesting finding) can be not directly caused by hypoxia, but by enhanced RBC clearance. Such a possibility should be taken into account.

Major points:

1) The authors present data from total splenocytes and then relate the obtained data to RPMs, which are quantitatively a minor population in the spleen. Eg, labile iron is increased in the splenocytes upon HH, but the manuscript does not show that this occurs in the red pulp or RPMs. They also measure gene/protein expression changes in the total spleen and connect them to changes in macrophages, as indicated in the model Figure (Fig. 7). HO-1 and levels of Ferritin (L and H) can be attributed to the drop in RPMs in the spleen. Are any of these changes preserved cell-intrinsically in cultured macrophages? This should be shown to support the model (relates also to lines 487-88, where the authors again speculate that hypoxia decreases HO-1 which was not demonstrated). In the current stage, for example, we do not know if the labile iron increase in cultured cells and in the spleen in vivo upon hypoxia is the same phenomenon, and why labile iron is increased. To improve the manuscript, the authors should study specifically RPMs.

2) The paper uses flow cytometry, but how this method was applied is suboptimal: there are no gating strategies, no indication if single events were determined, and how cell viability was assessed, which are the parent populations when % of cells is shown on the graphs. How RBCs in the spleen could be analyzed without dedicated cell surface markers? A drop in splenic RPMs is presented as the key finding of the manuscript but Fig. 3M shows gating (suboptimal) for monocytes, not RPMs. RPMs are typically F4/80-high, CD11-low (again no gating strategy is shown for RPMs). Also, the authors used single-cell RNAseq to detect a drop in splenic macrophages upon HH, but they do not indicate in Fig. A-C which cluster of cells relates to macrophages. Cell clusters are not identified in these panels, hence the data is not interpretable).

3) The authors draw conclusions that are not supported by the data, some examples:

a) They cannot exclude eg the compensatory involvement of the liver in the RBCs clearance (the differences between HH sham and HH splenectomy is mild in Fig. 2 E, F and G)

b) Splenomegaly is typically caused by increased extramedullary erythropoiesis, not RBC retention. Why do the authors support the second possibility? Related to this, why do the authors conclude that data in Fig. 4 G,H support the model of RBC retention? A significant drop in splenic RBCs (poorly gated) was observed at 7 days, between NN and HH groups, which could actually indicate increased RBC clearance capacity = less retention.

c) Lines 452-54: there is no data for decreased phagocytosis in vivo, especially in the context of erythrophagocytosis. This should be done with stressed RBCs transfusion assays, very good examples, like from Youssef et al. or Threul et al. are available in the literature.

d) Line 475 - ferritinophagy was not shown in response to hypoxia by the manuscript, especially that NCOA4 is decreased, at least in the total spleen.

4) In a few cases, the authors show only representative dot plots or histograms, without quantification for n>1. In Fig. 4B the authors write about a significant decrease (although with n=1 no statistics could be applied here; of note, it is not clear what kind of samples were analyzed here). Another example is Fig. 6I. In this case, it is even more important as the data are conflicting the cited article and the new one: PMCID: PMC9908853 which shows that hypoxia stimulates efferocytosis. Sometimes the manuscript claim that some changes are observed, although they are not visible in representative figures (eg for M1 and M2 macrophages in Fig. 3M)

5) There are several unclear issues in methodology:

- what is the purity of primary RPMs in the culture? RPMs are quantitatively poorly represented in splenocyte single-cell suspensions. This reviewer is quite skeptical that the processing of splenocytes from approx 1 mm3 of tissue was sufficient to establish primary RPM cultures. The authors should prove that the cultured cells were indeed RPMs, not monocyte-derived macrophages or other splenic macrophage subtypes.<br /> - (around line 183) In the description of flow cytometry, there are several missing issues. In 1) it is unclear which type of samples were analyzed. In 2) it is not clear how splenocyte cell suspension was prepared.<br /> - In line 192: what does it mean: 'This step can be omitted from cell samples'?<br /> - 'TO method' is not commonly used anymore and hence it was unclear to this Reviewer. Reticulocytes should be analyzed with proper gating, using cell surface markers.<br /> - The description of 'phagocytosis of E. coli and RBCs' in the Methods section is unclear and incomplete. The Results section suggests that for the biotinylated RBCs, phagocytosis? or retention? Of RBCs was quantified in vivo, upon transfusion. However, the Methods section suggests either in vitro/ex vivo approach. It is vague what was indeed performed and how in detail. If RBC transfusion was done, this should be properly described. Of note, biotinylation of RBCs is typically done in vivo only, being a first step in RBC lifespan assay. The such assay is missing in the manuscript. Also, it is not clear if the detection of biotinylated RBCs was performed in permeablized cells (this would be required).

The authors did not substantially improve the quality of their manuscript in the revised version, at least in the case of the limitations which I have spotted. The major points which remain unclear:<br /> 1. No gating strategies for flow cytometry are provided.<br /> 2. Figure 3M still does not show a typical F4/80 vs CD11b gating, with a population of true RPMs gated.<br /> 3. In a few cases data still lack biological replicates+statistics.<br /> 4. Results from scRNA-seq are not presented more clearly (=clusters in Fig 3E are described as macrophages, but it is not explained which among the clusters are RPMs).<br /> 5. The compensatory role of liver macrophages is omitted.<br /> 6. The authors misunderstood by suggestion to perform in vivo erythrophagocytosis assay using stained RBCs. This assay quantifies the true capacity for erythrophagocytosis in RPMs or KCs in the organ, regardless of the ferroptosis that may be a subsequent consequence (please, see initial Figures in Yousseff et al. paper). Using the percentage of biotin-positive RBCs in the spleen (although this method is not well described in the Methods), the authors rather show increased RBCs clearance at 7 days following hypoxia. Hence, the model where first hypoxia increases erythrophagocytosis in RPMs, consequently leading to their ferroptosis still cannot be excluded.<br /> 7. The Methods are poorly described and unclear - the authors claimed that they have used in vivo biotinylation assay to assess the lifespan of RBCs but it is not described. Instead, the paragraph „Phagocytosis of E. coli and RBCs" suggests that RBCs were stained with biotin for phagocytic assay in culture with macrophages. Phagocytosis of E. coli is still described in the Methods although the authors opted to remove the data from the revised manuscript.<br /> Some points are unclear in the current version of the manuscript, after the addition of new data:<br /> 8. Data in Figure 4D versus 4E,F are not consistent, showing less retention versus increased retention of RBCs in the spleen (retention of senescent RBCs in the spleen should be measured anyway quantitatively, eg, with proper flow cytometry)<br /> 9. The increase of labile iron in the red pulp might not be in RPMs - especially since they seem depleted. Flow cytometry should be used to assess which cell types show increased iron levels.

Reviewer #1 (Public Review):

It is well established that tuberculosis (TB), which is caused by Mycobacterium tuberculosis (Mtb), is a leading cause of mortality and morbidity worldwide. However, the only vaccine licensed against tuberculosis is Bacille Calmette Guerin (BCG), has been around for nearly a century, and has limited efficacy in adults. Herein, the authors sought to investigate the effectiveness of a nanoparticle-based formulation of a subunit vaccine composed of Mtb lipid and protein antigens. The authors found that they were able to load the lipid, mycolic acid, into their nanoparticles without disrupting the architecture and that the loaded particles activated T cells both in vitro and in vivo. Moreover, when they vaccinated with particles loaded with both lipid and protein antigens, they found that the lipid antigen persisted, and mycolic acid-specific T cells were able to be activated 6 weeks post-vaccination, in contrast to peptide-specific T cells. The authors investigated further and found that persistence required the nanoparticle encapsulation, rather than free lipid, and that it was independent of route (intratracheal, intravenous, or subcutaneous) of administration. To address the mechanisms underlying antigen persistence, the authors loaded the nanoparticles with a dye and demonstrated that the nanoparticle encapsulated lipid antigen was primarily stored in lung alveolar macrophages and that CD1b+ dendritic cells presented the antigen to mycolic acid specific T cells. Finally, the authors conducted mixed bone marrow chimera studies to examine the phenotype of the mycolic acid specific T cells and found that the memory T cell population phenotypically resembled T follicular helper, regulatory T cells, and exhausted T cells. Interestingly, while a large percentage of these lipid antigen specific T cells in the lymph nodes, lung and spleen were CXCR5+PD1+, the cells were still proliferating (Ki67+). Overall, this is a comprehensive study that has the potential to significantly enhance the field.

Reviewer #2 (Public Review):

The work presented here by Morgun et al is performed in the context of vaccine development, a field especially active in the context of tuberculosis (TB). The generation of a new vaccine either enhancing or replacing the 100-year-old BCG is urgently needed.

Most subunit vaccines integrate protein antigens formulated with adjuvants and there are few examples of the performance of subunit vaccines integrating lipid antigens. Considering the hydrophobic and lipid nature of the mycobacterial cell envelope studies, assessing the suitability of mycobacterial lipids in vaccine formulations may contribute to generate new vaccines to tackle the disease.

The mycobacterial lipid antigens under study are mycolic acids (MA), which are located at the cell wall covalently linked to arabinogalactan. These lipids carry extremely long chain fatty acids of up to 60-90 carbons.

The group has previously shown that formulating MA into micellar nanocarriers and vaccinating mice intranasally it could activate CD1-restricted T cells. However, this formulation did not allow for the incorporation of protein antigens.

This work is novel, and it brings new data of high relevance for the TB vaccine field pointing to alternative formulations and antigens and immune mechanisms.

Authors assay different routes of vaccination but the main results are obtained using non-conventional vaccination routes. Although, it maybe out of the scope of the paper, no protection studies are provided.

Reviewer #1 (Public Review):

Murphy, Fancy and Skene performed a reanalysis of snRNA-seq data from Alzheimer Disease (AD) patients and healthy controls published previously by Mathys et al. (2019), arriving at the conclusion that many of the transcriptional differences described in the original publication were false positives. This was achieved by revising the strategy for both quality control and differential expression analysis. I believe the authors' intention was to show the results of their reanalysis not as a criticism of the original paper (which can hardly be faulted for their strategy which was state-of-the-art at the time and indeed they took extra measures attempting to ensure the reliability of their results), but primarily to raise awareness and provide recommendations for rigorous analysis of sc/snRNA-seq data for future studies.

STRENGTHS:

The authors demonstrate that the choice of data analysis strategy can have a vast impact on the results of a study, which in itself may not be obvious to many researchers.

The authors apply a pseudobulk-based differential expression analysis strategy (essentially, adding up counts from all cells per individual and comparing those counts with standard RNA-seq differential expression tests), which is (a) in line with latest community recommendations, (b) different from the "default options" in most popular scRNA-seq analysis suites, and (c) explains the vastly different number of DEGs identified by the authors and the original publication. The recommendation of this approach together with a detailed assessment of the DEGs found by both methodologies could be a useful finding for the research community. Unfortunately, it is currently not fully substantiated and is confounded with concurrent changes in QC measures (see weaknesses).

The authors show a correlation between the number of DEGs and the number of cells assessed, which indicates a methodological shortcoming of the original paper's approach (actually, the authors of the original paper already acknowledged that the lesser number of DEGs for rare cell types was a technical artefact). To be educational for the reader it would be important to provide more information about the DEGs that were "found" and those that were "lost". Given vast inter-individual heterogeneity in humans, it is likely that the study was underpowered to find weaker differences using the pseudobulks (Fig. 1B shows that only genes with more than 4-fold change were found "significant").

All code and data used in this study are publicly available to the readers.

WEAKNESSES:

The authors interpret the fact that they found fewer DEGs with their method than the original paper as a good thing by making the assumption that all genes that were not found were false positives. However, they do not prove this, and it is likely that at least some genes were not found due to a lack of statistical power and not because they were actually "incorrect". The original paper also performed independent validations of some genes that were not found here.

I am concerned that the only DEGs found by the authors are in the rare cell types, foremost the rare microglia (see Fig. 1f). It is unclear to me how many cells the pseudo-bulk counts were based on for these cells types, but it seems that (a) there were few and (b) there were quite few reads per cells. If both are the case, the pseudobulk counts for these cell populations might be rather noisy and the DEG results are liable to outliers with extreme fold changes.

The authors claim they improved the quality control of the dataset. While I do not think they did anything wrong per se, the authors offer no objective metric to assess this putative improvement. This is another major weakness of the paper as it confounds the results of the improved (?) differential analysis strategy and dilutes the results. I detail this weakness in the two following points:

Removing low-quality cells: The authors apply a new QC procedure resulting in the removal of some 20k more cells than in the original publication. They state "we believe the authors' quality control (QC) approach did not capture all of these low quality cells" (l. 26). While all the QC metrics used are very sensible, it is unclear whether they are indeed "better". For instance, removal with a mitochondrial count of <5% seems harsh and might account for a large proportion of additional cells filtered out in comparison to the original analysis. There is no blanket "correct cutoff" for this percentage. For instance, the "classic" Seurat tutorial https://satijalab.org/seurat/articles/pbmc3k_tutorial.html uses the 5% threshold chosen by the authors, an MAD-based selection of cutoff arrived at 8% here https://www.sc-best-practices.org/preprocessing_visualization/quality_control.html, another "best practices" guide choses by default 10% https://bioconductor.org/books/3.17/OSCA.basic/quality-control.html#quality-control-discarded, etc. Generally, the % of mitochondrial reads varies a lot between datasets. As far as I can tell, the original paper did not use a fixed threshold but instead used a clustering approach to identify cells with an "abnormally high" mitochondrial read fraction. That also seems reasonable. Overall, I cannot assess whether the new QC is really more appropriate than the original analysis and the authors do not provide any evidence in favor of their strategy.

Batch correction: "Dataset integration has become a standard step in single-cell RNA-Seq protocols" (l. 29). While it is true that many authors now choose to perform an integration step as part of their analysis workflow, this is by no means uncontroversial as there is a risk of "over-integration" and loss of true biological differences. Also, there are many different methods for dataset integration out there, which will all have different results. More importantly, the authors go on "we found different cell type proportions to the authors (Fig. 1a) which could be due to accounting for batch effects" but offer no support for the claim that the batch effects are indeed related to the observed differences. An alternative explanation would be a selective loss/gain of certain cell types during quality control. The original paper stated concerns about losing certain cell types (microglia, which do not seem to be differentially abundant in the original paper / new analysis).

Relevant literature is incompletely cited. Instead of referring to reviews of best practices and benchmarks comparing methods for batch correction and or differential analysis, the authors only refer to their own previous work.

Due to a lack of comparison with other methods and due to the fact that the author's methodology was only applied to a single dataset, the paper presents merely a case study, which could be useful but falls short of providing a general recommendation for a best practice workflow.

APPRAISAL:

The manuscript could help to increase awareness of data analysis choices in the community, but only if the superiority of the methodology was clearly demonstrated. The recommended pseudobulk differential expression approach along with the indication of drastic differences that this might have on the results is the main output of the current manuscript, but it is difficult to assess unequivocally how this influenced the results because the differential analysis comes after QC and cell type annotation, which have also been changed in comparison to the original publication. In my opinion, the purpose of the paper might be better served by focusing on the DE strategy without changing QC and instead detailing where/how DEGs were gained/lost and supporting whether these were false positives.

Reviewer #2 (Public Review):

Summary: This paper takes on the important topic of preprocessing of single cell/nuclei RNA-seq prior to testing for differential gene expression. However, the manuscript has a number of critical weaknesses.

Strengths: This is an important topic and a key dataset for illustration.

Weaknesses: A major contribution is the use of the authors' own inhouse pipeline for data preparation (scFLOW), but this software is unpublished since 2021 and consequently not yet refereed. It isn't reasonable to take this pipeline as being validated in the field.

The authors claim that Mathys' analysis didn't use batch correction prior to analysis and claim that such processing is routine in the field, but the only citation they give is to the above-mentioned scFLOW. Batch correction for DEG analysis isn't the field standard, for example, Bryois et al. (2022) PMID: 35915177 doesn't perform batch correction. Whether or not to do such preprocessing is certainly arguable, but the authors need to argue it, not presuppose it.

The authors spend considerable effort in discounting the pseudoreplication analysis of Mathys. It is well understood that this analysis yields a lot of false positives, but Mathys only used this approach for removing genes, not as a valid test in and of itself. They also worry that the significant findings in Mathys' paper are influenced by the number of cells of each type. I'm sure it is since power is a function of sample size, but is this a bad thing? It seems odd that their approach is not influenced by sample size.

Reviewer #1 (Public Review):

Summary: Cullinan et al. explore the hypothesis that the cytoplasmic N- and C-termini of ASIC1a, not resolved in x-ray or cryo-EM structures, form a dynamic complex that breaks apart at low pH, exposing a C-terminal binding site for RIPK1, a regulator of necrotic cell death. They expressed channels tagged at their N- and C-termini with the fluorescent, non-canonical amino acid ANAP in CHO cells using amber stop-codon suppression. Interaction between the termini was assessed by FRET between ANAP and colored transition metal ions bound either to a cysteine reactive chelator attached to the channel (TETAC) or metal-chelating lipids (C18-NTA). A key advantage to using metal ions is that they are very poor FRET acceptors, i.e. they must be very close to the donor for FRET to occur. This is ideal for measuring small distances/changes in distance on the scales expected from the initial hypothesis. In order to apply chelated metal ions, CHO cells were mechanically unroofed, providing access to the inner leaflet of the plasma membrane. At high pH, the N- and C- termini are close enough for FRET to be measured, but apparently too far apart to be explained by a direct binding interaction. At low pH, there was an apparent increase in FRET between the termini. FRET between ANAP on the N-and C-termini and metal ions bound to the plasma membrane suggests that both termini move away from the plasma membrane at low pH. The authors propose an alternative hypothesis whereby close association with the plasma membrane precludes RIPK1 binding to the C-terminus of ASIC1a.

Strengths: The findings presented here are certainly valuable for the ion channel/signaling field and the technical approach only increases the significance of the work. The choice of techniques is appropriate for this study and the results are clear and high quality. Sufficient evidence is presented against the starting hypothesis.

Weaknesses: I have a few questions about certain controls and assumptions that I would like to see discussed more explicitly in the manuscript.

--My biggest concern is with the C-terminal citrine tag. Might this prevent the hypothesized interaction between the N- and C-termini? What about the serine to cysteine mutations? The authors might consider a control experiment in channels lacking the C-terminal FP tag.

--Figure 2 supplement 1 shows apparent read-through of the N-terminal stop codons. Given that most of the paper uses N-terminal ANAP tags, this figure should be moved out of the supplement. Do N-terminally truncated subunits form functional channels? Do the authors expect N-terminally truncated subunits to co-assemble in trimers with full-length subunits? The authors should include a more explicit discussion regarding the effect of truncated channels on their FRET signal in the case of such co-assembly.

--As the epitope used for the western blots in Figure 2 and supplements is part of the C-terminal tag, these blots do not provide an estimate of the fraction of C-terminally truncated channels (those that failed to incorporate ANAP at the stop codon). What effect would C-terminally truncated channels have on the FRET signal if incorporated into trimers with full-length subunits?

--Some general discussion of these results in the context of trimeric channels would be helpful. Is the putative interaction of the termini within or between subunits? Are the distances between subunits large enough to preclude FRET between donors on one subunit and acceptor ions bound on multiple subunits?

--The authors conclude that the relatively small amount of FRET between the cytoplasmic termini suggests that the interaction previously modeled in Rosetta is unlikely. Is it possible that the proposed structure is correct, but labile? For example, could it be that the FRET signal is the time average of a state in which the termini directly interact (as in the Rosetta model) and one in which they do not?

Reviewer #2 (Public Review):

Summary:<br /> The authors use previously characterised FRET methods to measure distances between intracellular segments of ASIC and with the membrane. The distances are measured across different conditions and at multiple positions in a very complete study. The picture that emerges is that the N- and C-termini do not associate.

Strengths:<br /> Good controls, good range of measurements, advanced, well-chosen and carefully performed FRET measurements. The paper is a technical triumph. Particularly, given the weak fluorescence of ANAP, the extent of measurements and the combination with TETAC is noteworthy.

The distance measurements are largely coherent and favour the interpretation that the N and C terminus are not close together as previously claimed.

Weaknesses:<br /> One difficulty is that we do not have a positive control for what binding of something to either N- or C-terminus would look like (either in FRET or otherwise).

One limitation that is not mentioned is the unroofing. The concept of interaction with intracellular domains is being examined. But the authors use unroofing to measure the positions, fully disrupting the cytoplasm. Thus it is not excluded that the unroofing disrupts that interaction. This should be mentioned as a possible (if unlikely) limitation.

Reviewer #3 (Public Review):

Summary: The manuscript by Cullinan et al., uses ANAP-tmFRET to test the hypothesis that the NTD and CTD form a complex at rest and to probe these domains for acid-induced conformational changes. They find convincing evidence that the NTD and CTD do not have a propensity to form a complex. They also report these domains are parallel to the membrane and that the NTD moves towards, and the CTD away, from the membrane upon acidification.

Strengths:<br /> The major strength of the paper is the use of tmFRET, which excels at measuring short distances and is insensitive to orientation effects. The donor-acceptor pairs here are also great choices as they are minimally disruptive to the structure being studied.

Furthermore, they conduct these measurements over several positions with the N and C tails, both between the tails and to the membrane. Finally, to support their main point, MST is conducted to measure the association of recombinant N and C peptides, finding no evidence of association or complex formation.

Weaknesses:<br /> While tmFRET is a strength, using ANAP as a donor requires the cells to be unroofed to eliminate background signal. This causes two problems. First, it removes any possible low affinity interacting proteins such as actinin (PMID 19028690). Second, the pH changes now occur to both 'extracellular' and 'intracellular' lipid planes. Thus, it is unclear if any conformational changes in the N and CTDs arise from desensitization of the receptor or protonation of specific amino acids in the N or CTDs or even protonation of certain phospholipid groups such as in phosphatidylserine. The authors do comment that prolonged extracellular acidification leads to intracellular acidification as well. But the concerns over disruption by unroofing/washing and relevance of the changes remain.

The distances calculated depend on the R0 between donor and acceptor. In turn, this depends on the donor's emission spectrum and quantum yield. The spectrum and yield of ANAP is very sensitive to local environment. It is a useful fluorophore for patch fluorometry for precisely this reason, and gating-induced conformational changes in the CTD have been reported just from changes in ANAP emission alone (PMID 29425514). Therefore, using a single R0 value for all positions (and both pHs at a single position) is inappropriate. The authors should either include this caveat and give some estimate of how big an impact changes spectrum and yield might have, or actually measure the emission spectra at all positions tested.

Overall, the writing and presentation of figures could be much improved with specific points mentioned in the recommendations for authors section.

The authors argue that the CTD is largely parallel to the plasma membrane, yet appear to base this conclusion on ANAP to membrane FRET of positions S464 and M505. Two positions is insufficient evidence to support such a claim. Some intermediate positions are needed.

Upon acidification, NTD position Q14 moves towards the plasma membrane (Figure 8B). Q14 also gets closer to C515 or doesn't change relative to 505 (Figures 7C and B) upon acidification. Yet position 505 moves away from the membrane (Figure 8D). How can the NTD move closer to the membrane, and to the CTD but yet the CTD move further from the membrane? Some comment or clarification is needed.

Reviewer #1 (Public Review):

In this manuscript, Nagel et al. sought to comprehensively characterize the composition of urinary compounds, some of which are putative chemosignals. They used urines from adult males and females in three different strains, including one wild-derived strain. By performing mass spectrometry of two classes of compounds: volatile organic compounds and proteins, they found that urines from inbred strains are qualitatively similar to those of a wild strain. This finding is significant because there is a high degree of genetic diversity in wild mice, with chemosensory receptor genes harboring many polymorphisms.

In the second part of this work, the authors used calcium imaging to monitor the pattern of vomeronasal neuron responses to these urines. By performing pairwise comparisons, the authors found a large degree of strain-specific response and a relatively minor response to sex-specific urinary stimuli. This is a finding generally in agreement with previous calcium imaging work by Ron Yu and colleagues in 2008. The authors extend the previous work by using urines from wild mice. They further report that the concentration diversity of urinary compounds in different urine batches is largely uncorrelated with the activity profiles of these urines. In addition, the authors found that the patterns of vomeronasal neuron response to urinary cues are not identical when measured using different recipient strains. This fascinating finding, however, requires an additional control to exclude the possibility that this is not due to sampling error.

There are several weaknesses in this manuscript, including the lack of analysis of the compositions of sulfated steroids and other steroids, which have been proposed to be the major constituents of vomeronasal ligands in urines and the indirect (correlational) nature of their mass spectrometry data and activity data.

Overall, the major contribution of this work is the identification of specific molecules in mouse urines. This work is likely to be of significant interest to researchers in chemosensory signaling in mammals and provides a systematic avenue to exhaustively identify vomeronasal ligands in the future.

Reviewer #2 (Public Review):

This manuscript by Nagel et al provides a comprehensive examination of the chemical composition of mouse urine (an important source of semiochemicals) across strain and sex, and correlates these differences with functional responses of vomeronasal sensory neurons (an important sensory population for detecting chemical social cues). The strength of the work lies in the careful and comprehensive imaging and chemical analyses, the rigor of quantification of functional responses, and the insight into the relevance of olfactory work on lab-derived vs wild-derived mice.

With regards to the chemical analysis, the reader should keep in mind that a difference in the concentration of a chemical across strain or sex does not necessarily mean that that chemical is used for chemical communication. In the most extreme case, the animals may be completely insensitive to the chemical. Thus, the fact that the repertoire of proteins and volatiles could potentially allow sex and/or strain discrimination, it is unclear to what degree both are used in different situations.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Nagel et al. describes studies of mouse vomeronasal sensory neuron (VSN) tuning to mouse urine samples across different sexes and strains, including wild mice, alongside mass spectrometry analysis of the same samples. The authors performed live Ca2+ imaging (CAL520 dye) of VSNs in acute vomeronasal organ (VNO) slices to determine how VSNs are tuned to pairs of stimuli that differ in their origin (e.g. male C57BL/6 versus male BALB/c urine, male C57BL/6 versus female C57BL/6, etc.). For each pair of tested odorants, the results measure the proportion of VSNs that respond to both stimuli ("generalists") or just one of the two ("specialists"), as well as metrics of tuning preference and response reliability. The authors find in most cases that generalists make up a larger proportion of responsive VSNs than specialists, but several pairwise comparisons showed a high degree of strain selectivity. Notably, the authors evaluated VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding strain-dependent differences in the representation of mouse urine. Alongside these measurements of VSN tuning, the authors report results of mass spectrometry analyses of volatiles and proteins in the same urine samples. These analyses indicated a number of molecules in each category that vary across sex and strain, and therefore represent candidate vomeronasal ligands. However, this study did not directly test whether any of these candidate molecules drives VSN activity, limiting the interpretability of these comparisons. Overall, this work provides useful information related to mouse vomeronasal chemosensation, but future work will be necessary to link the physiological measurements to the observed molecular diversity.

Strengths:<br /> A strength of the current study is its focus on characterizing the neural responses of the VNO to urine derived from wild mice. The majority of existing vomeronasal system research has relied on the use of inbred strains for both neural response recordings and investigations of candidate vomeronasal system ligands. Inbreeding in laboratory environments may alter the chemical composition of bodily secretions, thereby potentially changing the information they contain. Moreover, the more homogeneous nature of inbred strains could be critical when studying the AOS mediated social aspects. If there exist noticeable differences in the chemical composition of secretions from wild animals compared to inbred strains, this would suggest that future research must consider natural sources of candidate ligands outside of inbred strains. This work identifies some intriguing differences - worthy of further exploration - between the urine composition of wild mice versus inbred mice, as well as disparities in how the VNO responds to urine from these different sources. However, the molecular composition and VNO responsiveness to wild mouse urine was found to be highly overlapping with inbred mouse urine, supporting the continued investigation of candidate ligands found in inbred mouse urine.

Another positive aspect of this work is its use of the same set of stimuli as a previous study by the same authors (Bansal et al., 2021) in the downstream accessory olfactory bulb. The consistency in stimulus selection facilitates a comparison of information processing of sex and strain information from the sensory periphery to the brain. Although comparisons between the two connected regions are not a focus of this work, and methodological differences (e.g., Ca2+ imaging versus electrophysiology) may introduce caveats into comparisons, the support of "apples to apples" comparisons across connected circuits is critical to progress in the field.

Finally, this study directly measured VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding subtle but important differences in the representation of mouse urine in these two recipient strains. Given that there is a long history of research into strain-specific differences in social behavior, this research paves the way for future studies into how different mouse strains detect and process social chemosignals.

Weaknesses:<br /> One of the primary objectives in this study is to ascertain the extent to which the response profiles of VSNs are specific to sex and strain. The design of these Ca2+ imaging experiments uses a simple stimulus design, using two interleaved bouts of stimulation with pairs of urine (e.g. male versus female C57BL/6, male C57BL/6 versus male BALB/c) at a single dilution factor (1:100). This introduces two significant limitations: (1) the "generalist" versus "specialist" descriptors pertain only to the specific pairwise comparisons made and (2) there is no information about the sensitivity/concentration-dependence of the responses.

The functional measurements of VSN tuning to various pairs of urine stimuli are consistently presented alongside mass spectrometry-based comparisons. Although it is clear from the manuscript text that the mass spectrometry-based analysis was separated from the VSN tuning experiments/analysis, the juxtaposition of VSN tuning measurements with independent molecular diversity measurements gives the appearance to readers that these experiments were integrated (i.e., that the diversity of ligands was underlying the diversity of physiological responses). This is a hypothesis raised by the parallel studies, not a supported conclusion of the work. This data presentation style risks confusing readers.

The impact of mass spectrometry findings is limited by the fact that none of these molecules (in bulk, fractions, or monomolecular candidate ligands) were tested on VSNs. It is possible that only a very small number of these ligands activate the VNO. The list of variably expressed proteins - especially several proteins that are preferentially found in female urine - is compelling, but, again, there is no evidence presented that indicates whether or not these candidate ligands drive VSN activity. It is noteworthy that the largest class of known natural ligands for VSNs are small nonvolatiles that are found at high levels in mouse urine. These molecules were almost certainly involved in driving VSN activity in the physiology assays (both "generalist" and "specialist"), but they are absent from the molecular analysis.

Reviewer #2 (Public Review):

The Xerces Blue is an iconic species, now extinct, that is a symbol for invertebrate conservation. Using genomic sequencing of century-old specimens of the Xerces Blue and its closest living relatives, the authors hypothesize about possible genetic indicators of the species' demise. Although the limited range and habitat destruction are the most likely culprits, it is possible that some natural reasons have been brewing to bring this species closer to extinction.

The importance of this study is in its generality and applicability to any other invertebrate species. The authors find that low effective population size, high inbreeding (for tens of thousands of years), and higher fraction of deleterious alleles characterize the Xerces colonies prior to extinction. These signatures can be captured from comparative genomic analysis of any target species to evaluate its population health.

It should be noted that it remains unclear if these genomic signatures are indeed predictive of extinction, or populations can bounce back given certain conditions and increase their genetic diversity somehow.

Methods are detailed and explained well, and the study could be replicated. I think this is a solid piece of work. Interested researchers can apply these methods to their chosen species and eventually, we will assemble datasets to study extinction process in many species to learn some general rules.

Reviewer #1 (Public Review):

The authors report a study, where they have sequenced whole genomes of four individuals of an extinct species of butterfly from western North America (Glaucopsyche xerces), along with seven genomes of a closely related species (Glaucopsyche lygdamus), mainly from museum specimens, several to many decades old. They then compare these fragmented genomes to a high-quality, chromosome-level assembly of a genome of a European species in the same genus (Glaucopsyche alexis). They find that the extinct species shows clear signs of declining population sizes since the last glacial period and an increase in inbreeding, perhaps exacerbating the low viability of the populations and contributing to the extinction of the species.

The study really highlights how museum specimens can be used to understand the genetic variability of populations and species in the past, up to a century or more ago. This is an incredibly valuable tool, and can potentially help us to quickly identify whether current populations of rare and declining species are in danger due to inbreeding, or whether at least their genetic integrity is in good condition and other factors need to be prioritised in their conservation. In the case of extinct species, sequencing museum specimens is really our only window into the dynamics of genomic variability prior to extinction, and such information can help us understand how genetic variation is related to extinction.

I think the authors have achieved their goal admirably, they have used a careful approach to mapping their genomic reads to a related species with a high-quality genome assembly. They might miss out on some interesting genetic information in the unmapped reads, but by and large, they have captured the essential information on genetic variability within their mapped reads. Their conclusions on the lower genetic variability in the extinct species are sound, and they convincingly show that Glaucopyche xerces is a separate species to Glaucopsyche lygdamus (this has been debated in the past).

Reviewer #1 (Public Review):

In this study, the authors build upon previous research that utilized non-invasive EEG and MEG by analyzing intracranial human ECoG data with high spatial resolution. They employed a receptive field mapping task to infer the retinotopic organization of the human visual system. The results present compelling evidence that the spatial distribution of human alpha oscillations is highly specific and functionally relevant, as it provides information about the position of a stimulus within the visual field.

Using state-of-the-art modeling approaches, the authors not only strengthen the existing evidence for the spatial specificity of the human dominant rhythm but also provide new quantification of its functional utility, specifically in terms of the size of the receptive field relative to the one estimated based on broad band activity.

The present manuscript currently omits the complementary view that the retinotopic map of the visual system might be related to eye movement control. Previous research in non-human primates using microelectrode stimulation has clearly shown that neuronal circuits in the visual system possess motor properties (e.g. Schiller and Styker 1972, Schiller and Tehovnik 2001). More recent work utilizing Utah arrays, receptive field mapping, and electrical stimulation further supports this perspective, demonstrating that the retinotopic map functions as a motor map. In other words, neurons within a specific area responding to a particular stimulus location also trigger eye movements towards that location when electrically stimulated (e.g. Chen et al. 2020).

Similarly, recent studies in humans have established a link between the retinotopic variation of human alpha oscillations and eye movements (e.g., Quax et al. 2019, Popov et al. 2021, Celli et al. 2022, Liu et al. 2023, Popov et al. 2023). Therefore, it would be valuable to discuss and acknowledge this complementary perspective on the functional relevance of the presented evidence in the discussion section.

Reviewer #2 (Public Review):

Summary:<br /> In this work, Yuasa et al. aimed to study the spatial resolution of modulations in alpha frequency oscillations (~10Hz) within the human occipital lobe. Specifically, the authors examined the receptive field (RF) tuning properties of alpha oscillations, using retinotopic mapping and invasive electroencephalogram (iEEG) recordings. The authors employ established approaches for population RF mapping, together with a careful approach to isolating and dissociating overlapping, but distinct, activities in the frequency domain. Whereby, the authors dissociate genuine changes in alpha oscillation amplitude from other superimposed changes occurring over a broadband range of the power spectrum. Together, the authors used this approach to test how spatially tuned estimated RFs were when based on alpha range activity, vs. broadband activities (focused on 70-180Hz). Consistent with a large body of work, the authors report clear evidence of spatially precise RFs based on changes in alpha range activity. However, the size of these RFs were far larger than those reliably estimated using broadband range activity at the same recording site. Overall, the work reflects a rigorous approach to a previously examined question, for which improved characterization leads to improved consistency in findings and some advance of prior work.

Strengths:<br /> Overall, the authors take a careful and well-motivated approach to data analyses. The authors successfully test a clear question with a rigorous approach and provide strong supportive findings. Firstly, well-established methods are used for modeling population RFs. Secondly, the authors employ contemporary methods for dissociating unique changes in alpha power from superimposed and concomitant broadband frequency range changes. This is an important confound in estimating changes in alpha power not employed in prior studies. The authors show this approach produces more consistent and robust findings than standard band-filtering approaches. As noted below, this approach may also account for more subtle differences when compared to prior work studying similar effects.

Weaknesses:<br /> -Theoretical framing: The authors frame their study as testing between two alternative views on the organization, and putative functions, of occipital alpha oscillations: i) alpha oscillation amplitude reflects broad shifts in arousal state, with large spatial coherence and uniformity across cortex; ii) alpha oscillation amplitude reflects more specific perceptual processes and can be modulated at local spatial scales. However, in the introduction this framing seems mostly focused on comparing some of the first observations of alpha with more contemporary observations. Therefore, I read their introduction to more reflect the progress in studying alpha oscillations from Berger's initial observations to the present. I am not aware of a modern alternative in the literature that posits alpha to lack spatially specific modulations. I also note this framing isn't particularly returned to in the discussion. A second important variable here is the spatial scale of measurement. It follows that EEG based studies will capture changes in alpha activity up to the limits of spatial resolution of the method (i.e. limited in ability to map RFs). This methodological distinction isn't as clearly mentioned in the introduction, but is part of the author's motivation. Finally, as noted below, there are several studies in the literature specifically addressing the authors question, but they are not discussed in the introduction.

-Prior studies: There are important findings in the literature preceding the author's work that are not sufficiently highlighted or cited. In general terms, the spatio-temporal properties of the EEG/iEEG spectrum are well known (i.e. that changes in high frequency activity are more focal than changes in lower frequencies). Therefore, the observations of spatially larger RFs for alpha activities is highly predicted. Specifically, prior work has examined the impact of using different frequency ranges to estimate RF properties, for example ECoG studies in the macaque by Takura et al. NeuroImage (2016) [PubMed: 26363347], as well as prior ECoG work by the author's team of collaborators (Harvey et al., NeuroImage (2013) [PubMed: 23085107]), as well as more recent findings from other groups (Luo et al., (2022) BioRxiv: https://doi.org/10.1101/2022.08.28.505627). Also, a related literature exists for invasively examining RF mapping in the time-voltage domain, which provides some insight into the author's findings (as this signal will be dominated by low-frequency effects). The authors should provide a more modern framing of our current understanding of the spatial organization of the EEG/iEEG spectrum, including prior studies examining these properties within the context of visual cortex and RF mapping. Finally, I do note that the author's approach to these questions do reflect an important test of prior findings, via an improved approach to RF characterization and iEEG frequency isolation, which suggests some important differences with prior work.

-Statistical testing: The authors employ many important controls in their processing of data. However, for many results there is only a qualitative description or summary metric. It appears very little statistical testing was performed to establish reported differences. Related to this point, the iEEG data is highly nested, with multiple electrodes (observations) coming from each subject, how was this nesting addressed to avoid bias?

Reviewer #3 (Public Review):

Summary:<br /> This study tackles the important subject of sensory driven suppression of alpha oscillations using a unique intracranial dataset in human patients. Using a model-based approach to separate changes in alpha oscillations from broadband power changes, the authors try to demonstrate that alpha suppression is spatially tuned, with similar center location as high broadband power changes, but much larger receptive field. They also point to interesting differences between low-order (V1-V3) and higher-order (dorsolateral) visual cortex. While I find some of the methodology convincing, I also find significant parts of the data analysis, statistics and their presentation incomplete. Thus, I find that some of the main claims are not sufficiently supported. If these aspects could be improved upon, this study could potentially serve as an important contribution to the literature with implications for invasive and non-invasive electrophysiological studies in humans.

Strengths:<br /> The study utilizes a unique dataset (ECOG & high-density ECOG) to elucidate an important phenomenon of visually driven alpha suppression. The central question is important and the general approach is sound. The manuscript is clearly written and the methods are generally described transparently (and with reference to the corresponding code used to generate them). The model-based approach for separating alpha from broadband power changes is especially convincing and well-motivated. The link to exogenous attention behavioral findings (figure 8) is also very interesting. Overall, the main claims are potentially important, but they need to be further substantiated (see weaknesses).

Weaknesses:<br /> I have three major concerns:<br /> 1. Low N / no single subject results/statistics: The crucial results of Figure 4,5 hang on 53 electrodes from four patients (Table 2). Almost half of these electrodes (25/53) are from a single subject. Data and statistical analysis seem to just pool all electrodes, as if these were statistically independent, and without taking into account subject-specific variability. The mean effect per each patient was not described in text or presented in figures. Therefore, it is impossible to know if the results could be skewed by a single unrepresentative patient. This is crucial for readers to be able to assess the robustness of the results. N of subjects should also be explicitly specified next to each result.

2. Separation between V1-V3 and dorsolateral electrodes: Out of 53 electrodes, 27 were doubly assigned as both V1-V3 and dorsolateral (Table 2, Figures 4,5). That means that out of 35 V1-V3 electrodes, 27 might actually be dorsolateral. This problem is exasperated by the low N. for example all the 20 electrodes in patient 8 assigned as V1-V3 might as well be dorsolateral. This double assignment didn't make sense to me and I wasn't convinced by the authors' reasoning. I think it needlessly inflates the N for comparing the two groups and casts doubts on the robustness of these analyses.

3. Alpha pRFs are larger than broadband pRFs: first, as broadband pRF models were on average better fit to the data than alpha pRF models (dark bars in Supp Fig 3. Top row), I wonder if this could entirely explain the larger Alpha pRF (i.e. worse fits lead to larger pRFs). There was no anlaysis to rule out this possibility. Second, examining closely the entire 2.4 section there wasn't any formal statistical test to back up any of the claims (not a single p-value is mentioned). It is crucial in my opinion to support each of the main claims of the paper with formal statistical testing.

While I judge these issues as crucial, I can also appreciate the considerable effort and thoughtfulness that went into this study. I think that addressing these concerns will substantially raise the confidence of the readership in the study's findings, which are potentially important and interesting.

Reviewer #1 (Public Review):

This study investigates the impact of recurrent connections on grid fields generated in networks trained by adjusting the strength of feedforward spatial inputs. The main result is that if the recurrent connections in the network are given a 1D continuous attractor architecture, then aligned grid firing patterns emerge in the network following training. Detailed analyses of the low dimensional dynamics of the resulting networks are then presented. The simulations and analyses appear carefully carried out.

The feedforward model investigated by the authors (previously introduced by Kropff & Treves, 2008) is an interesting and important alternative to models that generate grid firing patterns through 2-dimensional continuous attractor network (CAN) dynamics. However, while both classes of model generate grid fields, in making comparisons the manuscript is insufficiently clear about their differences. In particular, in the CAN models grid firing is a direct result of their 2-D architecture, either a torus structure with a single activity bump (e.g. Guanella et al. 2007, Pastoll et al. 2013), or sheet with multiple local activity bumps (Fuhs & Touretzky, Burak & Fiete, 2009). In these models, spatial input can anchor the grid representations but is not necessary for grid firing. By contrast, in the feedforward models neurons transform existing spatial inputs into a grid representation. Thus, the two classes of model implement different computations; CANs path integrate, while the feedforward models transform spatial representations. A demonstration that a 1D CAN generates coordinated 2D grid fields would be surprising and important, but it's less clear why coordination between grids generated by the feedforward mechanism would be surprising. As written, it's unclear which of these claims the study is trying to make. If the former, then the conclusion doesn't appear well supported by the data as presented, if the latter then the results are perhaps not so unexpected, and the imposed attractor dynamics may still not be relevant.

Whichever claim is being made, it could be helpful to more carefully evaluate the model dynamics given predictions expected for the different classes of model. Key questions that are not answered by the manuscript include:

- At what point is the 1D attractor architecture playing a role in the models presented here? Is it important specifically for training or is it also contributing to computation in the fully trained network?

- Is an attractor architecture required at all for emergence of population alignment and gridness? Key controls missing from Figure 2 include training on networks with other architectures. For example, one might consider various architectures with randomly structured connectivity (e.g. drawing weights from exponential or Gaussian distributions).

- In the trained models do the recurrent connections substantially influence activity in the test conditions? Or after training are the 1D dynamics drowned out by feedforward inputs?

- What is the low dimensional structure of the input to the network? Can the apparent discrepancy between dimensionality of architecture and representation be resolved by considering structure of the inputs, e.g. if the input is a 2 dimensional representation of location then is it surprising that the output is too?

- What happens to representations in the trained networks presented when place cells remap? Is the 1D manifold maintained as expected for CAN models, or does it reorganise?

Reviewer #2 (Public Review):

Summary:<br /> The authors proposed that grid cells may be aligned by simpler, 1D attractors, and they showed that the structure and the representational space of an attractor network can be two different topological objects.

Strengths:<br /> It is very interesting that the toroidal topology of the population activity (the representational space) and the structure of the attractor network do not necessarily to be the same. The authors carried out extensive computational modeling to support such evidence. The results presented by the authors in this study could have an impact in the grid cell field, which will motivate future experimental studies to examine the detailed structure of the grid cell population.

Weaknesses:<br /> The authors mentioned that "the recurrent collateral structure defines the geometry of the manifold..." and pointed out that this assumption is wrong. I am afraid this claim is too strong. The Gardner Torus paper showed evidence of the 2D CAN exists in the EC as a possible substrate of the grid pattern. Do the authors mean here that even the population activity in the grid cells show the torus structure, it does not necessarily mean that the grid cells form a 2D CAN? I understand that from the computational modeling view, it is doable to find counter-examples (like the 1D attractor network) in which the representational space is a torus but the structure is different. However, from the experimental view, do you expect that the grid cell network is a low-dimensional attractor network? To prove this, is there any evidence from the experimental data?

Reviewer #3 (Public Review):

Summary:

The paper proposes an alternative to the attractor hypothesis, as an explanation for the fact that grid cell population activity patterns (within a module) span a toroidal manifold. The proposal is based on a class of models that were extensively studied in the past, in which grid cells are driven by synaptic inputs from place cells in the hippocampus. The synapses are updated according to a Hebbian plasticity rule. Combined with an adaptation mechanism, this leads to patterning of the inputs from place cells to grid cells such that the spatial activity patterns are organized as an array of localized firing fields with hexagonal order. I refer to these models below as feedforward models.

It has already been shown by Si, Kropff, and Treves in 2012 that recurrent connections between grid cells can lead to alignment of their spatial response patterns. This idea was revisited by Urdapilleta, Si, and Treves in 2017. Thus, it should already be clear that in such models, the population activity pattern spans a manifold with toroidal topology. The main new contributions in the present paper are (i) in considering some forms of recurrent connectivity that were not directly addressed before (but see comments below). (ii) in applying topological analysis to simulations of the model. (iii) in interpreting the results as a potential explanation for the observations of Gardner et al.

Strengths:

The exploration of learning in a feedforward model, when recurrent connectivity in the grid cell layer is structured in a ring topology, is interesting. The insight that this not only aligns the grid cells in a common direction but also creates a correspondence between their intrinsic coordinate (in terms of the ring-like recurrent connectivity) and their tuning on the torus is interesting as well, and the paper as a whole may influence future theoretical thinking on the mechanisms giving rise to the properties of grid cells.

Weaknesses:

1. It is not clear to me that the proposal here is fundamentally new. In Si, Kropff and Treves (2012) recurrent connectivity was dependent on the head direction tuning and thus had a ring structure. Urdapilleta, Si, and Treves considered connectivity that depends on the distance on a 2d plane.

2. The paper refers to the connectivity within the grid cell layer as an attractor. However, would this connectivity, on its own, indeed sustain persistent attractor states? This is not examined in the paper. Furthermore, is this even necessary to obtain the results in the model? Perhaps weak connections that do not produce an attractor would be sufficient to align the spatial response patterns during the learning of feedforward weights, and reproduce the results? In general, there is no exploration of how the strength of collateral interactions affects the outcome.

3. I did not understand what is learned from the local topology analysis. Given that all the grid cells are driven by an input from place cells that spans a 2d manifold, and that the activity in the grid cell network settles on a steady state that depends only on the inputs, isn't it quite obvious that the manifold of activity in the grid cell layer would have, locally, a 2d structure?

4. The modeling is all done in planar 2d environments, where the feedforward learning mechanism promotes the emergence of a hexagonal pattern in the single neuron tuning curve. This, combined with the fact that all neurons develop spatial patterns with the same spacing and orientation, implies even without any topological analysis that the emerging topology of the population activity is a torus.

However, the toroidal topology of grid cells in reality has been observed by Gardner et al also in the wagon wheel environment and in sleep, and there is substantial evidence based on pairwise correlations that it persists also in various other situations, in which the spatial response pattern is not a hexagonal firing pattern. It is not clear that the mechanism proposed in the present paper would generate toroidal topology of the population activity in more complex environments. In fact, it seems likely that it will not do so.

5. Moreover, the recent work of Gardner et al. demonstrated much more than the preservation of the topology in the different environments and in sleep: the toroidal tuning curves of individual neurons remained the same in different environments. Previous works, that analyzed pairwise correlations under hippocampal inactivation and various other manipulations, also pointed towards the same conclusion. Thus, the same population activity patterns are expressed in many different conditions. In the present model, the results of Figure 6 suggest that even across distinct rectangular environments, toroidal tuning curves will not be preserved, because there are multiple possible arrangements of the phases on the torus which emerge in different simulations.

6. In real grid cells, there is a dense and fairly uniform representation of all phases (see the toroidal tuning of grid cells measured by Gardner et al). Here the distribution of phases is not shown, but Figure 7 suggests that phases are non uniformly represented, with significant clustering around a few discrete phases. This, I believe, is also the origin for the difficulty in identifying the toroidal topology based on the transpose of the matrix M: vectors representing the spatial response patterns of individual neurons are localized near the clusters, and there are only a few of them that represent other phases. Therefore, there is no dense coverage of the toroidal manifold that would exist if all phases were represented equally. This is not just a technical issue, however: there appears to be a mismatch between the results of the model and the experimental reality, in terms of the phase coverage.

7. The manuscript makes several strong claims that incorrectly represent the relation between experimental data and attractor models, on one hand, and the present model on the other hand. For the latter, see the comments above. For the former, I provide a detailed list in the recommendations to the authors, but in short: the paper claims that attractor models induce rigidness in the neural activity which is incompatible with distortions seen in the spatial response patterns of grid cells. However, this claim seems to confuse distortions in the spatial response pattern, which are fully compatible with the attractor model, with distortions in the population activity patterns, which would be incompatible with the attractor model. The attractor model has withstood numerous tests showing that the population activity manifold is rigidly preserved across conditions - a strong prediction (which is not made, as far as I can see, by feedforward models). I am not aware of any data set where distortions of the population activity manifold have been identified, and the preservation has been demonstrated in many examples where the spatial response pattern is disrupted. This is the main point of two papers cited in the present manuscript: by Yoon et al, and Gardner et al.

8. There is also some weakness in the mathematical description of the dynamics. Mathematical equations are formulated in discrete time steps, without a clear interpretation in terms of biophysically relevant time scales. It appears that there are no terms in the dynamics associated with an intrinsic time scale of the neurons or the synapses, and this introduces a difficulty in interpreting synaptic weights as being weak or strong. As mentioned above, the nature of the recurrent dynamics within the grid cell network (whether it exhibits continuous attractor behavior) is not sufficiently clear.

In my view, the weaknesses discussed above limit the ability of the model, as it stands, to offer a compelling explanation for the toroidal topology of grid cell population activity patterns, and especially the rigidity of the manifold across environments and behavioral states. Still, the work offers an interesting way of thinking on how the toroidal topology might emerge. Perhaps with certain additional elements this may motivate new theoretical insights.

Reviewer #1 (Public Review):

Summary:<br /> Mitochondria is the power plant of the cells including neurons. Thomas et al. characterized the distribution of mitochondria in dendrites and spines of L2/3 neurons from the ferret visual cortex, for which visually driven calcium responses of individual dendritic spines were examined. The authors analyzed the relationship between the position of mitochondria and the morphology or orientation selectivity of nearby dendrite spines. They found no correlation between mitochondrion location and spine morphological parameters associated with the strength of synapses, but correlation with the spine-somatic difference of orientation preference and local heterogeneity in preferred orientation of nearby spines. Moreover, they reported that the spines that have a mitochondrion in the head or neck are larger in size and have stronger orientation selectivity. Therefore, they proposed that "mitochondria are not necessarily positioned to support the energy needs of strong spines, but rather support the structurally and functionally diverse inputs."

Strengths:<br /> This paper attempted to address a fundamental question: whether the distribution of the mitochondria along the dendrites of visual cortical neurons is associated with the functions of the spines, postsynaptic sites of excitatory synapses. Two state of the art techniques (2 photon Ca imaging of somata and spines and EM reconstructions of cortical pyramidal neurons) had been used, which provides a great opportunity to examine and correlate the function of spine ultrastructure and spatial distribution of dendritic mitochondria.

Weaknesses:<br /> Overall, the findings are interesting. However, the study lacks the data providing insights into either the mechanisms or the functional meaning of the pattern of mitochondrion distribution along the dendrites, which restricts the significance of the study. It also suffers from small correlation coefficients and small sample sizes (60-121 spines in 4 neurons) as well as missing some important analysis.

Reviewer #2 (Public Review):

Summary:<br /> Mitochondria in synapses are important to support functional needs, such as local protein translation and calcium buffering. Thus, they may be strategically localized to maximize functional efficiency. In this study, the authors examine whether a correlation exists between the positioning of mitochondria and the structure or function of dendritic spines in the visual cortex of a ferret. Unexpectedly, the authors found no correlation between structural measures of synaptic strength to mitochondria positioning, which may indicate that they are not localized only because of the local energy needs. Instead, the authors discover that mitochondria are positioned preferably in spines that display heterogeneous responses, showing that they are localized to support specific functional needs probably distinct from ATP output.

Strengths:<br /> The thorough analysis provides a yet unprecedented insight into the correlation between synaptic tuning and mitochondrial positioning in the visual cortex in vivo.

Weaknesses:<br /> The study defined 1 μm and 5 μm as short and extended ranges relative to the synapse and examined the correlation between mitochondria volume and multiple parameters within that defined range. Results showed that mitochondria display preferences towards spines that respond differently to visual stimuli or areas with low local calcium activity. However, it is not known whether this mitochondria preference is a cause or a result of spine heterogeneity. It will be interesting to see the correlation of spine volume relative to mitochondrial positioning in 1µm and 5µm ranges around mitochondria.

Analysis of this study suggested that mitochondrial volume does not correlate with the structural measure of synaptic strength (e.g. spine volume and post-synaptic density (PSD) area). However, the authors did not examine whether mitochondrial volume correlates to synaptic transmission frequency or plasticity. It may still be possible that mitochondria are localized in positions that exhibit a high frequency of transmission or a high degree of plasticity. Future studies will have to determine the underlying cause of mitochondria positioning preference.

Reviewer #3 (Public Review):

Summary: This is a careful examination of the distribution of mitochondria in the basal dendrites of ferret visual cortex in a previously published volume electron microscopy dataset. The authors report that mitochondria are sparsely, as opposed to continuously distributed in the dendritic shafts, and that they tend to cluster near dendritic spines with heterogeneous orientation selectivity.

Strengths: Volume EM is the gold standard for quantification of organelle morphology. An unusual strength of this particular dataset is that the orientation selectivity of the dendritic spines was measured by calcium imaging prior to EM reconstruction. This allowed the authors to assess how spines with varying selectivity are organized relative to mitochondria, leading to an intriguing observation that they localize to heterogeneous spine clusters. The analysis is carefully performed.

Weaknesses: Using threshold distances between mitochondria and synapses as opposed to absolute distances may overlook important relationships in the data.

Reviewer #1 (Public Review):

Summary<br /> In this manuscript, Hagihara et al. characterized the relationship between the changes in lactate and pH and the behavioral phenotypes in different animal models of neuropsychiatric disorders at a large-scale level. The authors have previously reported that increased lactate levels and decreased pH are commonly observed in the brains of five genetic mouse models of schizophrenia (SZ), bipolar disorder (BD), and autism spectrum disorder (ASD). In this study, they expanded the detection range to 109 strains or conditions of animal models, covering neuropsychiatric disorders and neurodegenerative disorders. Through statistical analysis of the first 65 strains/conditions of animal models which were set as exploratory cohort, the authors found that most strains showed decreased pH and increased lactate levels in the brains. There was a significant negative correlation between pH and lactate levels both at the strain/condition level and the individual animal level. Besides, only working memory was negatively correlated with brain lactate levels. These results were successfully duplicated by studying the confirmative cohort, including 44 strains/conditions of animal models. In all strains/conditions, the lactate levels were not correlated with age, sex, or storage duration of brain samples.

Strengths<br /> 1. The manuscript is well-written and structured. In particular, the discussion is really nice, covering many potential mechanisms for the altered lactate levels in these disease models.<br /> 2. Tremendous efforts were made to recruit a huge number of various animal models, giving the conclusions sufficient power.

Weaknesses<br /> 1. The biggest concern of this study is the limited novelty. The point of "altered pH and/or lactate levels in the brains from human and rodent animals of neuropsychiatric disorders" has been reported by the same lab and other groups in many previous papers.<br /> 2. This study is mostly descriptive, lacking functional investigations. Although a larger cohort of animal models were studied which makes the conclusion more solid, limited conceptual advance is contributed to the relevant field, as we are still not clear about what the altered levels of pH and lactate mean for the pathogenesis of neuropsychiatric disorders.<br /> 3. The experiment procedure is also a concern. The brains from animal models were acutely collected without cardiac perfusion in this study, which suggests that resident blood may contaminate the brain samples. The lactate is enriched in the blood, making it a potential confounded factor to affect the lactate levels as well as pH in the brain samples.<br /> 4. The lactate and pH levels may also be affected by other confounded factors, such as circadian period, and locomotor activity before the mice were sacrificed. This should also be discussed in the paper.<br /> 5. Another concern is the animal models. Although previous studies have demonstrated that dysfunctions of these genes could cause related phenotypes for certain disorders, many of them are not acknowledged by the field as reliable disease models. Besides, gene deficiency could also cause many known or unknown unrelated phenotypes, which may contribute to the altered levels of lactate and pH, too. In this circumstance, the conclusion "pH and lactate levels are transdiagnostic endophenotype of neuropsychiatric disorders" is somewhat overstated.<br /> 6. The negative correlationship between pH and lactate is rather convincing. However, how much the contribution of lactate to pH is not tested. In addition, regarding pH and lactate, which factor contributes most to the pathogenesis of neuropsychiatric disorders is also unclear. These questions may need to be addressed in the future study.<br /> 7. The authorship is open to question. Most authors listed in this paper may only provide mice strains or brain samples. Maybe it is better just to acknowledge them in the acknowledgments section.<br /> 8. The last concern is about the significance of this study. Although the majority of strains showed increased lactate, some still showed decreased lactate levels in the brains. These results suggested that lactate or pH is an endophenotype for neuropsychiatric disorders, but it is hard to serve as a good diagnostic index as the change is not unidirectional in different disorders. In other words, the relationship between lactate level and neuropsychiatric disorders is not exclusive.

Reviewer #2 (Public Review):

Hagihara et al. conducted a study investigating the correlation between decreased brain pH, increased brain lactate, and poor working memory. They found altered brain pH and lactate levels in animal models of neuropsychiatric and neurodegenerative disorders. Their study suggests that poor working memory performance may predict higher brain lactate levels.

However, the study has some significant limitations. One major concern is that the authors examined whole-brain pH and lactate levels, which might not fully represent the complexity of disease states. Different brain regions and cell types may have distinct protein and metabolite profiles, leading to diverse disease outcomes. For instance, certain brain regions like the hippocampus and nucleus accumbens exhibit opposite protein/signaling pathways in neuropsychiatric disease models.

Moreover, the memory tests used in the study are specific to certain brain regions, but the authors did not measure lactate levels in those regions. Without making lactate measurements in brain-regions and cell types involved in these diseases, any conclusions regarding the role of lactate in CNS diseases is premature.

Additionally, evidence suggests that exogenous treatment with lactate has positive effects, such as antidepressant effects in multiple disease models (Carrard et al., 2018, Carrard et al., 2021, Karnib et al., 2019, Shaif et al., 2018). It also promotes learning, memory formation, neurogenesis, and synaptic plasticity (Suzuki et al., 2011, Yang et al., 2014, Weitian et al., 2015, Dong et al., 2017, El Hayek et al. 2019, Wang et al., 2019, Lu et al., 2019, Lev-Vachnish et a.l, 2019, Descalzi G et al., 2019, Herrera-López et al., 2020, Ikeda et al., 2021, Zhou et al., 2021,Roumes et al., 2021, Frame et al., 2023, Akter et al., 2023).

In conclusion, the relevance of total brain pH and lactate levels as indicators of the observed correlations is controversial, and evidence points towards lactate having more positive rather than negative effects. It is important that the authors perform studies looking at brain-region-specific concentrations of lactate and that they modulate lactate levels (decrease) in animal models of disease to validate their conclusions. it is also important to consider the above-mentioned studies before concluding that "altered brain pH and lactate levels are rather involved in the underlying pathophysiology of some patients with neuropsychiatric disorders" and that "lactate can serve as a potential therapeutic target for neuropsychiatric disorders".

Reviewer #1 (Public Review):

This study by Hormigo et al. examines the relationship between activity in the zona incerta (ZI) and behavior. The authors aim to assess the hypothesis that the ZI might mediate a general behavioral function, namely the distribution of information about ongoing movement to other brain areas that regulate behavior. Given the heterogeneity of prior literature on the ZI, this topic is important and interesting. The study employs a strong diversity of technical approaches, spanning electrophysiological recordings, calcium imaging, optogenetics, virally-mediated cell-type ablation, and several behavioral assays. The output is a large dataset where each experiment is useful and interesting, and together, the results could be interpreted as consistent with the prospect of the ZI mediating a general function. However, there are notable weaknesses in the current version of this paper. First, it is unclear whether the experiments and analyses were set up to be able to rule out more specific candidate functions of the ZI. Second, many important details of the experiments and their results are hard to decipher given the current descriptions and presentations of the data.

The paper could be significantly strengthened by including more details from each experiment, stronger justifications for the limited behaviors and experimental analyses performed, and, finally, a broader analysis of how the recorded activity in the ZI relates to behavioral parameters.

(1) Anatomical specification: The ZI contains many distinct subdivisions--each with its own topographically organized inputs/outputs and putative functions. The current manuscript doesn't reference these known divisions or their behavioral distinctions, and one cannot tell exactly which portion(s) of the ZI was included in the current study.

Moreover, the elongated structure of the ZI makes it very difficult to specifically or completely infect virally. The data could be better interpreted if the paper included basic information on the locations of recordings, the extent of the AAV spread in the ZI in each viral experiment, and what fraction of infected neurons were inside versus outside ZI.

(2) Electrophysiological recording on the treadmill: The authors are commended for this technically very difficult experiment. The authors do not specify, however, how they knew when they were recording in ZI rather than surrounding structures, particularly given that recording site lesions were only performed during the last recording session. A map of the locations of the different classes of units would be valuable data to relate to the literature.

(3) The rationale of the analysis of activity with respect to "movement peak": It is unclear why the authors did not assess how ZI activity correlates with a broad set of movement parameters, but rather grouped heterogeneous behavioral epochs to analyze firing with respect to "movement peaks".

(4) The display of mean categorical data in various figures is interesting, however, the reader cannot gather a very detailed view of ZI firing responses or potential heterogeneity with so little information about their distributions.

(5) Somatosensory firing responses in ZI: It is unclear why the authors chose the specific stimuli used in the study. How often did they evoke reflexive motor responses? What was the latency of sensory-evoked responses in ZI activity and the latency of the reflexive movement?

(6) It would be valuable to see example traces in Figure 3 to get a better sense of the time course and contexts under which Ca signals in ZI tracks movement. What is the typical latency? What is the typical range of magnitudes of responses? Does the Ca signal track both fast and slow movements? How are the authors sure that there are no movement artifacts contributing to the calcium imaging? It seems there is more information in the dataset that could be valuable.

(7) Figure 4: The rationale for quantifying the F/Fo responses over a 6-second window, rather than with respect to discrete movement parameters, is not well explained. What types of movement are binned in this approach and might this broad binning hinder the ability to detect more specific relationships between activity and movement?

(8) Separation of sensory and motor responses in Figure 5: The current data do not adequately differentiate whether the responses are sensory or motor given the high correlation of the sensory inputs driving motor responses. Because isoflurane can diminish auditory responses early in the auditory pathway, this reviewer is not convinced the isoflurane experiments are interpretable.

(9) Given the broad duration of the mean avoidance response (Fig. 6 C, bottom), it would be useful to know to what extent this plot reflects a prolonged behavior or is the result of averaging different animals/trials with different latencies. Given that the shapes of the F/Fo responses in ZI appear similar across avoids and escapes (Fig. 6D), despite their apparent different speeds and movement durations (Fig 6C), it would be valuable to know how the timing of the F/Fo relates to movement on a trial-by-trial basis.

(10) Lesion quantification: One cannot tell what rostral-caudal extent of ZI was lesioned and quantified in this experiment. It would be easier to interpret if also plotted for each animal, so the reader can tell how reliable the method is. The mean ablation would be better shown as a normalized fraction of cells. Although the authors claim the lesions have little impact on behavior, it appears the incompleteness of the lesions could warrant a more conservative interpretation.

(11) Optogenetics: the location of infected neurons is poorly described, including the rostral-caudal extent and the fraction of neurons inside and outside of ZI. Moreover, it is unclear how strongly the optogenetic manipulations in this study are expected to affect neuronal activity in ZI.

Reviewer #2 (Public Review):

The manuscript presents compelling evidence for the role of the zona incerta area of the brain in regulating movement and sensory stimuli in mice. The study uses an appropriate and validated methodology in line with the current state-of-the-art, including optogenetic manipulation and recording of single-unit activity. The authors' claims and conclusions are well-supported by their data, which includes a comprehensive review of previous research on the zona incerta. Overall, the manuscript provides solid evidence for the role of the zona incerta in regulating movement and sensory processing.

Major strengths and weaknesses of the methods and results.<br /> The zona incerta has many integrative functions that link sensory stimuli with motor responses to guide behavior.<br /> The study explored the activation of zona incerta GABAergic neurons during cued avoidance tasks and found that these neurons activate during goal-directed avoidance movement. Optogenetic manipulation of these neurons affected movement speed and performance during active avoidance tasks.<br /> The findings suggest that the zona incerta area of the brain plays a significant role in regulating movement and responding to salient auditory tones in association with movement in mice. The evidence presented is fundamental and provides a comprehensive review of previous research on the zona incerta and its involvement in various behaviors and sensory processing.

The article is very well written, with a correct hypothesis and a cutting-edge methodology to achieve the expected objectives. Moreover, they use statistical rigorous approaches in the analysis of the results. Also, analyzes are performed using scripts that automate all aspects of data analysis, ensuring their objectivity. The results are very novel, and provide solid evidence for the role of the zona incerta in regulating movement and sensory processing.

Reviewer #1 (Public Review):

In this paper, the interocular/binocular combination of temporal luminance modulations is studied. Binocular combination is of broad interest because it provides a remarkable case study of how the brain combines information from different sources. In addition, the mechanisms of binocular combination are of interest to vision scientists because they provide insight into when/where/how information from two eyes is combined.

This study focuses on how luminance flicker is combined across two eyes, extending previous work that focused mainly on spatial modulations. The results appear to show that temporal modulations are combined in different ways, with additional differences between subcortical and cortical pathways.

The manuscript has been revised to address prior reviewers' comments. It now provides more justification for the empirical choices made by the authors, and a better illustration of the methods. That said, the paper would still benefit from an expanded rationale for significance beyond this specific area. There were no substantive changes made to the abstract or introduction, and only little to the discussion.

Reviewer #2 (Public Review):

Previous studies have extensively explored the rules by which patterned inputs from the two eyes are combined in visual cortex. Here the authors explore these rules for un-patterned inputs (luminance flicker) at both the level of cortex, using Steady-State Visual Evoked Potentials (SSVEPs) and at the sub-cortical level using pupillary responses. They find that the pattern of binocular combination differs between cortical and sub-cortical levels with the cortex showing less dichoptic masking and somewhat more binocular facilitation.

Importantly, the present results with flicker differ markedly from those with gratings (Hou et al., 2020, J Neurosci, Baker and Wade 2017 cerebral cortex, Norcia et al, 2000 Neuroreport, Brown et al., 1999, IOVS. When SSVEP responses are measured under dichoptic conditions where each eye is driven with a unique temporal frequency, in the case of grating stimuli, the magnitude of the response in the fixed contrast eye decreases as a function of contrast in the variable contrast eye. Here the response increases by varying (small) magnitudes. The authors favor a view that cortex and perception pool binocular flicker inputs approximately linearly using cells that are largely monocular. The lack of a decrease below the monocular level when modulation strength increase is taken to indicate that previously observed normalization mechanism in pattern vision does not play a substantial role in the processing of flicker. The authors present of computational model of binocular combination that captures features of the data when fit separately to each data set. Because the model has no frequency dependence and is based on scalar quantities, it cannot make joint predictions for the multiple experimental conditions which one of its limitations.

A strength of the current work is the use of frequency-tagging of both pupil and EEG responses to measure responses for flicker stimuli at two anatomical levels of processing. Flicker responses are interesting but have been relatively neglected. The tagging approach allows one to access responses driven by each eye, even when the other eye is stimulated which is a great strength. The tagging approach can be applied at both levels of processing at the same time when stimulus frequencies are low, which is an advantage as they can be directly compared. The authors demonstrate the versatility of frequency tagging in a novel experimental design which may inspire other uses, both within the present context and others. A disadvantage of the tagging approach for studying sub-cortical dynamics via pupil responses is that it is restricted to low temporal frequencies given the temporal bandwidth of the pupil. The inclusion of a behavioral measure and a model is also a strength, but there are some limitations in the modeling (see below).

The authors suggest in the discussion that luminance flicker may preferentially drive cortical mechanisms that are largely monocular and in the results that they are approximately linear in the dichoptic cross condition (no effect of the fixed contrast stimulus in the other eye). By contrast, prior research using dichoptic dual frequency flickering stimuli has found robust intermodulation (IM) components in the VEP response spectrum (Baitch and Levi, 1988, Vision Res; Stevens et al., 1994 J Ped Ophthal Strab; France and Ver Hoeve, 1994, J Ped Ophthal Strab; Suter et al., 1996 Vis Neurosci). The presence of IM is a direct signature of binocular interaction and suggests that at least under some measurement conditions, binocular luminance combination is "essentially" non-linear, where essential implies a point-like non-linearity such as squaring of excitatory inputs. The two views are in striking contrast.

In this revised manuscript, the addition of Figure 8, which shows more complete response spectra, partially addresses this issue. However, it also raises new questions. Critically, intermodulation (IM) has to be generated at or after a point of binocular combination, as it is a mixture of the two monocular frequencies and the monocular frequencies can only mix after a point of binocular combination.

In equations 1 and 2 and in the late summation and two-stage models of Meese et al (2006), there are divisive binocular cross-links prior to a summation block. This division is a form of binocular interaction. Do equations 1 and 2 generate IM on their own with parameters used for the overall modeling? Multiplication of two inputs clearly does, as the authors indicate in their toy model. If not, then a different binocular summation rule than the one expressed in equation 3 needs to be considered to produce IM.

The discussion considers flicker processing as manifest in the EEG to be largely monocular, given the relative lack of binocular facilitation and suppression effects. And yet there is robust IM. These are difficult to reconcile as it stands. The authors suggest that their generic modeling framework can predict IM, but can it predict IM with the parameters used to fit the data, e.g. with very low values of the weight of interocular suppression and no other binocular non-linearity?

Determining whether IM can be generated by the existing non-linear elements in the model is important because previous work on dichoptic flicker IM has considered a variety of simple models of dichoptic flicker summation and has favored models involving either a non-linear combination of linear monocular inputs (Baitch and Levi, Vis Research, 1988) or a non-linear combination of rectified (non-linear) monocular inputs (Regan and Regan, Canadian J Neurol Sci, 1989). In either case, the last stage of binocular combination is non-linear, rather than linear. The authors' model is different - it has a stage of divisive binocular interaction and this "quasi-monocular" stage feeds a linear binocular combination stage.

There is a second opportunity to test the proposed model that the authors could take advantage of. In the initial review, two of the reviewers were curious about what is predicted for counter-phase inputs to the two eyes. The authors indicate that the class of models they are using could be extended to cover this case. As it turns out, this experiment has been done for dichoptic full-field flicker (Sherrington, BrJPsychiatr, 1904); van der Tweel and Estevez, Ophthalmologica, 1974; Odom and Chao, IntJNeurosci, 1995; Cavonius, QJExpPsych, 1979; Levi et al., BJO, 1982). More importantly, the predictions of several binocular combination models for anti-phase inter-ocular flicker stimulation have been tested for both the VEP and psychophysics (Odom and Chao, Int J Neurosci). Varying the relative phase of the two eyes inputs from in phase to antiphase, Odom and Chao observed that the 2nd harmonic response went to a minimum at 90 deg of interocular phase. This will happen because a 2nd order nonlinearity in the monocular path will double the phase shift of the second harmonic, putting the two eyes' 2nd harmonic response out of phase when the interocular phase is 90 deg. Summing these inputs thus leads to cancellation at 90 deg, rather than 180 deg of interocular phase. Does the authors' model predict this behavior with typical parameters used in the modeling? In the end, to account for details of both VEP and psychophysical data, Odom and Chao favored a two-path model with one path comprising non-linear monocular inputs being combined linearly and a second path combining linear monocular inputs at a non-linear binocular stage. A similar set of results and models has been developed for inter-ocular presentation of gratings (Zemon et al., PNAS, 1995).

The Odom/Chao/Zemon VEP and psychophysical data are directly relevant to the authors' work and need to be taken into account in sufficient detail so that we can judge the consistency of the proposed framework with their data and the similarities and differences in the model predictions for dichoptic flicker combination. These models are also relevant to the generation of IM, a concern raised above.

Reviewer #1 (Public Review):

The goal of the authors is to use whole-exome sequencing to identify genomic factors contributing to asthenoteratozoospermia and male infertility. Using whole-exome sequencing, they discovered homozygous ZMYND12 variants in four unrelated patients. They examined the localization of key sperm tail components in sperm from the patients. To validate the findings, they knocked down the ortholog in Trypanosoma brucei. They further dissected the complex using co-immunoprecipitation and comparative proteomics with samples from Trypanosoma and Ttc29 KO mice. They concluded that ZMYND12 is a new asthenoteratozoospermia-associated gene, bi-allelic variants of which cause severe flagellum malformations and primary male infertility.

The major strengths are that the authors used the cutting-edge technique, whole-exome sequencing, to identify genes associated with male infertility, and used a new model organism, Trypanosoma brucei to validate the findings, together with other high-throughput tools, including comparative proteomics to dissect the protein complex essential for normal sperm formation/function. The major weakness is that limited samples could be collected from the patients for further characterization by other approaches, including western blotting and TEM.

In general, the authors achieved their goal, and the conclusion is supported by their results. The findings not only provide another genetic marker for the diagnosis of asthenoteratozoospermia but also enrich the knowledge of cilia/flagella.

Reviewer #2 (Public Review):

The manuscript by Dacheux et al. reported homozygous deleterious variants of ZMYND12 in four unrelated men with asthenoteratozoospermia. Based on the immunofluorescence assays in human sperm cells, it was shown that ZMYND12 deficiency altered the localization of DNAH1, DNALI1, WDR66 and TTC29 (four of the known key proteins involved in sperm flagellar formation). Trypanosoma brucei and mouse models were further employed for mechanistic studies, which revealed that ZMYND12 is part of the same axonemal complex as TTC29 and DNAH1. Their findings are solid, and this manuscript will be very informative for clinicians and basic researchers in the field of human infertility.

Reviewer #3 (Public Review):

In this study, the authors identified homozygous ZMYND12 variants in four unrelated patients. In sperm cells from these individuals, immunofluorescence revealed altered localization of DNAH1, DNALI1, WDR66, and TTC29. Axonemal localization of ZMYND12 ortholog TbTAX-1 was confirmed using the Trypanosoma brucei model. RNAi knock-down of TbTAX-1 dramatically affected flagellar motility, with a phenotype similar to ZMYND12-variant-bearing human sperm. Co-immunoprecipitation and ultrastructure expansion microscopy in T. brucei revealed TbTAX-1 to form a complex with TTC29. Comparative proteomics with samples from Trypanosoma and Ttc29 KO mice identified a third member of this complex: DNAH1. The data presented revealed that ZMYND12 is part of the same axonemal complex as TTC29 and DNAH1, which is critical for flagellum function and assembly in humans, and Trypanosoma. The manuscript is informative for the clinical and basic researchers in the field of spermatogenesis and male infertility.

Reviewer #1 (Public Review):

It has been shown previously that maternal aging in mice is associated with an increase in accumulation of damaged mitochondria and activation of parkin-mediated autophagy (see DOI: 10.1080/15548627.2021.1946739). It has also been shown that C-natriuretic peptide (CNP) regulates oocyte meiotic arrest and that its use during in vitro oocyte maturation can improve parameters associated with decreased oocyte quality. Here the authors tested whether use of CNP treatment in vivo could improve oocyte quality and fertility of aged mice, for which they provided convincing evidence. They also attempted to determine how CNP improves oocyte developmental competence. They showed a correlation between CNP use in vivo and the appearance (and some functional qualities) of cytoplasmic organelles more closely approximating those of oocytes from young mice. However, this correlation could not be interpreted to imply causation. Additional experiments performed using CNP during in vitro maturation were not properly controlled and so are not possible to interpret.

A strength of the manuscript is that the authors use an in vivo treatment to improve oocyte quality rather than just using CNP during oocyte maturation in vitro as has been done previously. This strategy provides more potential for improving oocyte quality - over the course of oocyte growth and maturation - rather than just the final few hours of maturation alone. This strategy also has the potential to be translated into a more generally useful clinical therapeutic method that using CNP during in vitro maturation. However, it is difficult to glean information regarding how CNP might have its effects in vivo. A range of models are used in the manuscript with a mix of in vivo studies with in vitro experiments, which results in some disconnect between systemic CNP and its reported intrafollicular action as well as in the short-term versus longer-term actions of CNP on oocyte quality. Specifically, CNP was shown to be reduced in the plasma of aged mice, but this was not shown in the granulosa cells, which are the reported source of CNP that acts on oocytes. Whether the ovarian source of CNP is reduced in aged females was not demonstrated, and CNP is not known to act on oocytes through an endocrine effect. In vivo treatments with CNP by i.p. injection were performed, but the dose (120 ug/kg) and time (14 days) of treatment were not validated by any prior experiments to give them physiological relevance.

Weaknesses:

1. The Results section is not always clear regarding what CNP treatment was done - in vivo injections or in vitro maturation. For example, what is the difference, if any, between Figures 2C-D and Figures S2A-B?

This remains unclear in the revised manuscript.

2. Immature oocytes from aged females (~1 year) were treated with a two-step culture system with a pre-IVM step with CNP. Controls included oocytes from young (6-8 weeks) females or oocytes from aged females treated by conventional IVM. The description of these methods suggests that control oocytes did not receive an equivalent pre-IVM culture, hence the relevance of comparisons of CNP-treated versus control oocyte is questionable. This concern has not been addressed in the revised manuscript. It was observed that aged oocytes pre-cultured in CNP improved polar body extrusion rates and meiotic spindle morphology compared to oocytes in conventional IVM, as has been well established. The description of statistical methods does not make clear whether the PBE rate in CNP-treated old oocytes remained significantly lower than young controls.

This concern has not been addressed in the revised manuscript.

3. The main effect of the CNP 2-week treatment appears to be increasing the number of follicles that grow into secondary and antral stages, but there is no attempt made to discover the mechanism by which this occurs and therefore to understand why there might be an increase in the number of ovulated eggs, quality of the eggs, and litter size. It is also not clear how an intraperitoneal injection can guarantee its effectiveness because the half-life of CNP is very short, only a few minutes.

This concern has not been addressed in the revised manuscript.

4. Meiotic spindle morphology, as well as a number of putative markers of cytoplasmic maturation are also suggested to be improved after pre-culture with CNP. In each case a subjective interpretation of "normal" morphology of these markers is derived from observations of the young controls and the proportions of oocytes with normal or abnormal appearance is evaluated. However, parameters that define abnormal patterns of these markers appear to be subjective judgements, and whether these morphological patterns can be mechanistically attributed to the differences in developmental potential cannot be concluded.

This concern has not been addressed in the revised manuscript.

5. In addition to the localization patterns of mitochondria, the mitochondrial membrane potential, oocyte ATP content and ROS levels were assessed through more objective quantitative methods. These are well known to be defective in oocytes of aged females and CNP treatment improved these measures. Mitochondrial dysfunction is the most obvious link between oocyte apoptosis, autophagy, cytoplasmic organelle miss-localization and aberrant spindle morphology. Among the most intriguing results is the finding that CNP mediated a cAMP-dependent protein kinase (PKA) dependent reduction in mitochondrial autophagy mediators PINK and Parkin and reduced the recruitment of Parkin to mitochondria in oocytes. However, it may not be possible to directly link this observation to the improvements in IVM oocyte quality, since PINK/Parkin assessments were performed in oocytes from cultured follicles treated with CNP for 6 days.

This weakness has not been addressed in the revised manuscript.

6. The gold standard assay for oocyte quality is embryo transfer and live birth. The authors assessed the impact of maturing oocytes in vitro in the presence of CNP on oocyte quality by less robust assays (e.g., preimplantation embryo development in vitro), so the impact on oocyte quality is less certain.

This weakness has not been addressed in the revised manuscript.

7. The numbers of embryos should have been corrected for the number of eggs fertilized as a starting point so that the percentage that developed to each stage could be expressed as a percentage of successfully fertilized eggs rather than overall percentages. As currently shown in the Figures and described in the Legend, there is no information regarding what the percentage on the y-axis means. For example, does Figure 4B show the number of 2C embryos divided by the number of eggs inseminated? Or is it divided by the number of successfully fertilized eggs, and if so, how was that assessed?

There is no additional information provided in the revised manuscript to address these concerns.

8. When fewer eggs are fertilized, the numbers of embryos per group are lower and so the impact of culturing multiple embryos together is lost. As a result, it is possible that culture conditions rather than oocyte quality drove the differences in the numbers of embryos that achieved each stage of development.

This concern has not been addressed in the revised manuscript. Similar numbers of oocytes were cultured together, but not similar numbers of fertilized oocytes, or embryos.

9. Not all claims in the Discussion are supported by the evidence provided. For example, "In addition, the findings demonstrated that CNP improved cytoplasmic maturation events by maintaining normal CG, ER and Golgi apparatus distribution and function in aged oocytes" but it was never demonstrated that the altered distribution had any functional impact.

This concern has not been addressed in the revised manuscript.

10. Incompleteness and errors in the Methods section reduce confidence in many of the results reported.

This concern has not been addressed in the revised manuscript.

11. The methods used for Statistical Analysis are never explained in either the Methods or the Figure legends. It is unclear whether appropriate analyses were done, and it is frequently unclear what was the sample size and how many times a particular experiment was repeated. These weaknesses detract from confidence in the data.

This concern has not been addressed adequately in the revised manuscript.

Reviewer #2 (Public Review):

The authors found that the age-related reduction in the serum CNP concentration was highly correlated with decreased oocyte quality. Treatment with exogenous CNP promoted follicle growth and ovulation in aged mice and enhanced meiotic competency and fertilization ability. The cytoplasmic maturation of aged oocytes was thoroughly improved by CNP treatment. CNP treatment also ameliorated DNA damage and apoptosis caused by ROS accumulation in aged oocytes. CNP reversed the defective phenotypes in aged oocytes by alleviating oxidative damage and suppressing excessive PINK1/Parkin-mediated mitophagy. CNP functioned as a cAMP/PKA pathway modulator to decrease PINK1 stability and inhibit Parkin recruitment. CNP may be used to improve the overall success rates of clinically assisted reproduction in older women.

The author has modified the text and the level of the article has been improved. Additional experiments will further enhance the credibility of the article.

1）The control also needs to be pre-cultured as that in CNP treatment.

2）The mechanism is done 6 days later after CNP treatment. It is hard to know whether it is direct or indirect.

Reviewer #1 (Public Review):

This manuscript describes a series of experiments documenting trophic egg production in a species of harvester ant, Pogonomyrmex rugosus. In brief, queens are the primary trophic egg producers, there is seasonality and periodicity to trophic egg production, trophic eggs differ in many basic dimensions and contents relative to reproductive eggs, and diets supplemented with trophic eggs had an effect on the queen/worker ratio produced (increasing worker production).

The manuscript is very well prepared and the methods are sufficient. The outcomes are interesting and help fill gaps in knowledge, both on ants as well as insects, more generally. More context could enrich the study and flow could be improved.

Reviewer #2 (Public Review):

The manuscript by Genzoni et al. provides evidence that trophic eggs laid by the queen in the ant Pogonomyrmex rugosis have an inhibitory effect on queen development. The authors also compare a number of features of trophic eggs, including protein, DNA, RNA, and miRNA content, to reproductive eggs. To support their argument that trophic eggs have an inhibitory effect on queen development, the authors show that trophic eggs have a lower content of protein, triglycerides, glycogen, and glucose than reproductive eggs, and that their miRNA distributions are different relative to reproductive eggs. Although the finding of an inhibitory influence of trophic eggs on queen development is indeed arresting, the egg cross-fostering experiment that supports this finding can be effectively boiled down to a single figure (Figure 6). The rest of the data are supplementary and correlative in nature (and can be combined), especially the miRNA differences shown between trophic and reproductive eggs. This means that the authors have not yet identified the mechanism through which the inhibitory effect on queen development is occurring. To this reviewer, this finding is more appropriate as a short report and not a research article. A full research article would be warranted if the authors had identified the mechanism underlying the inhibitory effect on queen development. Furthermore, the article is written poorly and lacks much background information necessary for the general reader to properly evaluate the robustness of the conclusions and to appreciate the significance of the findings.

Reviewer #3 (Public Review):

In "Trophic eggs affect caste determination in the ant Pogonomyrmex rugosus" Genzoni et al. probe a fundamental question in sociobiology, what are the molecular and developmental processes governing caste determination? In many social insect lineages, caste determination is a major ontogenetic milestone that establishes the discrete queen and worker life histories that make up the fundamental units of their colonies. Over the last century, mechanisms of caste determination, particularly regulators of caste during development, have remained relatively elusive. Here, Genzoni et al. discovered an unexpected role for trophic eggs in suppressing queen development - where bi-potential larvae fed trophic eggs become significantly more likely to develop into workers instead of gynes (new queens). These results are unexpected, and potentially paradigm-shifting, given that previously trophic eggs have been hypothesized to evolve to act as an additional intra-colony resource for colonies in potentially competitive environments or during specific times in colony ontogeny (colony foundation), where additional food sources independent of foraging would be beneficial. While the evidence and methods used are compelling (e.g., the sequence of reproductive vs. trophic egg deposition by single queens, which highlights that the production of trophic eggs is tightly regulated), the connective tissue linking many experiments is missing and the downstream mechanism is speculative (e.g., whether miRNA, proteins, triglycerides, glycogen levels in trophic eggs is what suppresses queen development). Overall, this research elevates the importance of trophic eggs in regulating queen and worker development but how this is achieved remains unknown.

Reviewer #1 (Public Review):

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

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

The paper was well prepared.

Comments on latest version:

The revisions the authors have made have improved the manuscript.

Reviewer #2 (Public Review):

The manuscript by Nishikawa et al. addresses time-dependent changes in the electron transfer energetics in the photosynthetic reaction center from Blastochloris viridis, whose time-dependent structural changes upon light illumination were recently demonstrated by time-resolved serial femtosecond crystallography (SFX) using X-ray free-electron laser (XFEL) (Dods et al., Nature, 2021). Based on the redox potential Em values of bacteriopheophytin in the electron transfer active branch (BL) by solving the linear Poisson-Boltzmann equation, the authors found that Em(HL) values in the charge-separated 5-ps structure obtained by XFEL are not clearly changed, suggesting that the P+HL- state is not stabilized owing to protein reorganization. Furthermore, chlorin ring deformation upon HL- formation, which was expected from their QM/MM calculation, is not recognized in the 5-ps XFEL structure. Then the authors concluded that the structural changes in the XFEL structures are not related to the actual time course of charge separation. They argued that their calculated changes in Em and chlorin ring deformations using the XEFL structures may reflect the experimental errors rather than the real structural changes; they mentioned this problem is due to the fact that the XFEL structures were obtained at not high resolutions (mostly at 2.8 Å). I consider that their systematic calculations may suggest a useful theoretical interpretation of the XFEL study.

Comments on latest version:

The authors have satisfied my concerns. I consider that their present manuscript is more attractive and informative for readers.

Reviewer #1 (Public Review):

Summary: This paper performs fine-mapping of the silkworm mutants bd and its fertile allelic version, bdf, narrowing down the causal intervals to a small interval of a handful of genes. In this region, the gene orthologous to mamo is impaired by a large indel, and its function is later confirmed using expression profiling, RNAi, and CRISPR KO. All these experiments are convincingly showing that mamo is necessary for the suppression of melanic pigmentation in the silkworm larval integument.

The authors also use in silico and in vitro assays to probe the potential effector genes that mamo may regulate.

Strengths: The genotype-to-phenotype workflow, combining forward (mapping) and reverse genetics (RNAi and CRISPR loss-of-function assays) linking mamo to pigmentation are extremely convincing.

Weaknesses:

1) The last section of the results, entitled "Downstream target gene analysis" is primarily based on in silico genome-wide binding motif predictions.<br /> While the authors identify a potential binding site using EMSA, it is unclear how much this general approach over-predicted potential targets. While I think this work is interesting, its potential caveats are not mentioned. In fact the Discussion section seems to trust the high number of target genes as a reliable result. Specifically, the authors correctly say: "even if there are some transcription factor-binding sites in a gene, the gene is not necessarily regulated by these factors in a specific tissue and period", but then propose a biological explanation that not all binding sites are relevant to expression control. This makes a radical short-cut that predicted binding sites are actual in vivo binding sites. This may not be true, as I'd expect that only a subset of binding motifs predicted by Positional Weight Matrices (PWM) are real in vivo binding sites with a ChIP-seq or Cut-and-Run signal. This is particularly problematic for PWM that feature only 5-nt signature motifs, as inferred here for mamo-S and mamo-L, simply because we can expect many predicted sites by chance.

2) The last part of the current discussion ("Notably, the industrial melanism event, in a short period of several decades ... a more advanced self-regulation program") is flawed with important logical shortcuts that assign "agency" to the evolutionary process. For instance, this section conveys the idea that phenotypically relevant mutations may not be random. I believe some of this is due to translation issues in English, as I understand that the authors want to express the idea that some parts of the genome are paths of least resistance for evolutionary change (e.g. the regulatory regions of developmental regulators are likely to articulate morphological change). But the language and tone is made worst by the mention that in another system, a mechanism involving photoreception drives adaptive plasticity, making it sound like the authors want to make a Lamarckian argument here (inheritance of acquired characteristics), or a point about orthogenesis (e.g. the idea that the environment may guide non-random mutations).<br /> Because this last part of the current discussion suffers from confused statements on modes and tempo of regulatory evolution and is rather out of topic, I would suggest removing it.

In any case, it is important to highlight here that while this manuscript is an excellent genotype-to-phenotype study, it has very few comparative insights on the evolutionary process. The finding that mamo is a pattern or pigment regulatory factor is interesting and will deserve many more studies to decipher the full evolutionary study behind this Gene Regulatory Network.

Minor Comment :

The gene models presented in Figure 1 are obsolete, as there are more recent annotations of the Bm-mamo gene that feature more complete intron-exon structures, including for the neighboring genes in the bd/bdf intervals. It remains true that the mamo locus encodes two protein isoforms.<br /> An example of the Bm-mamo locus annotation, can be found at : https://www.ncbi.nlm.nih.gov/gene/101738295<br /> RNAseq expression tracks (including from larval epidermis) can be displayed in the embedded genome browser from the link above using the "Configure Tracks" tool.

Based on these more recent annotations, I would say that most of the work on the two isoforms remains valid, but FigS2, and particularly Fig.S2C, need to be revised.

Reviewer #2 (Public Review):

Summary:<br /> The authors tried to identify new genes involved in melanin metabolism and its spatial distribution in the silkworm Bombyx mori. They identified the gene Bm-mamo as playing a role in caterpillar pigmentation. By functional genetic and in silico approaches, they identified putative target genes of the Bm-mamo protein. They showed that numerous cuticular proteins are regulated by Bm-mamo during larval development.

Strengths:<br /> -preliminary data about the role of cuticular proteins to pattern the localization of pigments<br /> - timely question<br /> - challenging question because it requires the development of future genetic and cell biology tools at the nanoscale

Weaknesses:<br /> - statistical sampling limited<br /> - the discussion would gain in being shorter and refocused on a few points, especially the link between cuticular proteins and pigmentation. The article would be better if the last evolutionary-themed section of the discussion is removed.

A recent paper has been published on the same gene in Bombyx mori (https://www.sciencedirect.com/science/article/abs/pii/S0965174823000760) in August 2023. The authors must discuss and refer to this published paper through the present manuscript.

Reviewer #1 (Public Review):

This manuscript presents an important study that contributes to our understanding of the reliability of ancient environmental DNA (aeDNA) extracted from sediment cores. The authors address the potential biases and challenges associated with using aeDNA to infer past ecosystems, specifically focusing on the case of mammoths and woolly rhinoceroses in the Yamal peninsula, West Siberia.

The introduction provides an overview of the significance of sedimentary deposits as archives of past ecosystem changes and illustrates the remarkable insights gained from previous studies using aeDNA, highlighting its potential for reconstructing paleoecology, phylogeography, and understanding extirpation and extinction events of keystone taxa. The authors then report the detection of DNA and near complete mitochondrial genomes of multiple mammoth and woolly rhinoceros individuals in the sampled sediment cores (which are dated to the last few centuries). The authors then employed additional methods to confirm the presence of ancient DNA from mammoths in these sediment cores. Conventional PCR and Sanger sequencing of a mammoth COI fragment confirmed the amplification of mammoth DNA. Mammal metabarcoding and droplet digital PCR (ddPCR) further supported the detection of mammoth DNA in both cores.

The hybridisation enrichment experiment results showed high read counts assigned to Mammuthus, ranging from 2,852 to 72,919 reads per library in core LK-001. Negative controls did not produce any reads assigned to mammals, indicating the absence of contamination. The study also revealed the presence of woolly rhinoceros sequences in the sediment cores, with 12 out of 23 libraries producing more than 100 reads assigned to woolly rhinoceros. The total number of woolly rhinoceros reads was 2,737, and the cumulative mitogenome coverage reached 44%.

The authors carefully addressed the incongruity between the temporal occurrence of these extinct species and the presence of their DNA in recent sediments. They proposed several mechanisms that could explain the recovery of Pleistocene megafaunal DNA in the sediment cores. The minor amount of ancient DNA post mortem damage observed in the mammoth sequences indicates exceptional preservation, consistent with an origin from (recent) permafrost. The dynamics of permafrost thawing and redeposition in the study area provide a plausible explanation for the presence of ancient DNA in the sediments. The authors discuss potential mechanisms for the redistribution of Late Pleistocene material in the sediments, including thermo-denudation processes, methane emissions from degrading permafrost, and the formation of taliks and methane seepage. These processes can disturb the stratigraphy of lake sediments and potentially mix ancient material within the modern sediments. I believe the conclusions are supported by the data and the manuscript is well-written and clear to follow for the reader.

Reviewer #2 (Public Review):

Summary:<br /> The authors report the successful retrieval of mitogenomes from extinct Pleistocene megafauna (woolly Mammoth and woolly rhino) from recent sediment cores from two close Siberian lakes. The cores are too recent to represent real time points of these two extinct species (known to have been extinct for several thousands of years) and therefore, the most plausible interpretation is that permafrost thawing and similar physical processes in the lakes have made surface old ancient DNA, maybe from nearby, deep-buried carcasses.

Strengths:<br /> The pattern of postmortem damage at the end of the Mammoth DNA reads as well as the length distribution (reported in Figure 1) is expected for authentic ancient DNA extracts (besides the phylogenetic evidence). These results pose a question, in my view, on the general reliability of sedimentary DNA in similar contexts, especially in the absence of direct radiocarbon dating of associated remains and in the absence of an understanding of the local geo-physical dynamics. At the same time, the evidence reported here suggests that, at least in Siberian lakes, the sediments can preserve a rich ancient DNA record that it is worth surveying.

Weaknesses:<br /> Although admittedly the work can represent two cases of environments with singular thermal conditions and geodynamics, it opens also the possibility of studying more lake sediments for trying to understand if these findings can be generalized.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the researchers used ancient environmental DNA (aeDNA) retrieved from sediment cores, from two lakes in the Arctic, on the Yamal peninsula, in Siberia. The dating of one of the cores, showed that the sediment layers were very recent (ranging between the years 2019 - 1895). From this core they sequenced 23 libraries which were enriched for mammal mitochondrial genomes. They found a high proportion of two species that have been extinct for thousands of years, the mammoth and the woolly rhinoceros. The highest proportion of mammoth reads were found in very young layer (~81 years old) and as this initial finding does not match the temporal occurrence of the species, they confirmed the identification with several other methods. Additionally, they applied a different dating method on some samples and found that the aging of the samples was not completely congruent. The authors suggest the that the presence of these two Pleistocene megafauna in such recent sediment layers is a consequence of physical processes, specific to the study site, and that the high quality of the aeDNA recovered is a result of permafrost preservation.

Strengths:<br /> The strengths of the study are in the rigorous confirmation of the identification of the taxa with four different PCR and sequencing techniques being used, the initial enrichment panel, and then subsequent metabarcoding PCRs, and taxa specific PCR for COI and cytB. Along with the ancient DNA protocol applied, this is therefore very convincing that the DNA detected in the samples is indeed from the Pleistocene mammals. Additionally, two methods were used to age the sediment cores, and although the depth of the samples tested do not overlap, they give reasonable ages (apart from the anomalous sample) and all together these are robust results.

Weaknesses:<br /> The paper could benefit from clearer aims in the introductions because as it stands the initial aim states that the authors are looking for Arctic mammal abundances through time. However, there are no results relating to general arctic mammal biodiversity presented, which leaves the reader wondering. Perhaps the focus of the study is more on identifying and dating the Pleistocene megafauna. Additionally, it is presented as an analysis on the two taxa, but it feels like the woolly rhinoceros does not receive the same treatment as the mammoth, as there are no additional molecular results, confirmation or figures relating to DNA from this taxa.

Overall the results support that there has been some movement of DNA throughout the sediment core which may impact the dating of the last occurrence of particular extinct taxa. As highlighted, though the geological processes by which this may have arisen are specific to this particular lake and may not be broadly relevant, therefore highlighting that knowledge of each system is important to understanding DNA distribution.

Reviewer #1 (Public Review):

This manuscript by Neininger-Castro and colleagues presents a novel automatic image analysis method for assessing sarcomeres, the basic units of myofibrils and validates this tool in a couple of experimental approaches that interfere with sarcomere assembly in iPSC-cardiomyocytes (iPSC-CM).

Automatic quantification of sarcomeres is definitely something that is useful to the field. I am surprised that there is no reference in the manuscript to SarcTrack, published by Toepfer and colleagues in 2019 (PMID 30700234), which has exactly the same purpose. The advantage of the image analysis software presented in the current manuscript appears to me to be that it can cover both mature sarcomeres and nascent sarcomeres in premyofibrils effectively.

Reviewer #2 (Public Review):

Neininger-Castro et al report on their original study entitled "Independent regulation of Z-lines and M-lines during sarcomere assembly in cardiac myocytes revealed by the automatic image analysis software sarcApp", In this study, the research team developed two software, yoU-Net and sarcApp, that provide new binarization and sarcomere quantification methods. The authors further utilized human induced pluripotent stem cell-derived cardiomyocytes (hiCMs) as their model to verify their software by staining multiple sarcomeric components with and without the treatment of Blebbistatin, a known myosin II activity inhibitor. With the treatment of different Blebbistatin concentrations, the morphology of sarcomeric proteins was disturbed. These disrupted sarcomeric structures were further quantified using sarcApp and the quantification data supported the phenotype. The authors further investigated the roles of muscle myosins in sarcomere assembly by knocking down MYH6, MYH7, or MYOM in hiCMs. The knockdown of these genes did not affect Z-line assembly yet the knockdown of MYOM affected M-line assembly. The authors demonstrated that different muscle myosins participate in sarcomere assembly in different manners.

Reviewer #3 (Public Review):

Neininger-Castro and colleagues developed software tools for the quantification of sarcomeres and sarcomere-precursor features in immunostained human induced pluripotent stem cell-derived cardiac myocytes (hiCMs). In the first part they used a deep-learning- based model called a U-Net to construct and train a network for binarization of immunostained cardiomyocyte images. They also wrote graphical user interface (GUI) software that will assist other labs to use this approach and made it publicly available. They did not compare their approach to existing ones, but example from one image suggests their binarization tool outperforms Otsu thresholding binarization.

In the second part they developed a software tool called sarcApp that classifies sarcomere structures in the binarized image as a Z-Line or Z-Body and assigns each to either a myofibril or to stress fibers. The tools can then automatically count and measure multiple features (33 per cell and 24 per myofibril) and report them on a per-cell, per-myofibril, and per- stress fiber basis.

To test the tools they used Blebbistatin to inhibit sarcomere assembly and showed that the sarcApp tool could capture changes in multiple features such as fewer myofibrils, fewer Z-Lines, decreased myofibril persistence, decreased Z-Line length and altered myofibril orientation in the Blebbistatin treated cells. With some changes the tool was also shown to quantify sarcomeres in titin and myomesin stained cardiomyocytes.

Finally they used sarcApp to quantify the changes in sarcomere assembly after siRNA mediated knockout of MYH7, MYH7, or MYOM. The analysis indicates that neither MYH6 nor MYH7 knockdown perturbed the assembly of Z- or M-lines, and that knockdown of MYOM perturbed the A-band/M-Line but not the Z-Line assembly according to features captured by the sarcApp tool.

Overall the authors developed and made publicly available an excellent software tool that will be very useful for labs that are interested in studying sarcomere assembly. Multiple features that are difficult to measure or count manually can be automatically measured by the software quickly and accurately.

There are however some remaining questions about these tools:<br /> 1. The binarization tool which is tailored to sarcomere image binarization appears promising but was not systematically compared with existing approaches. Example from one cell suggests it outperforms Otsu's binarization approach.<br /> 2. How robust is the tool? The tool was tested on images from one type of cardiomyocytes (hiCMs) taken from one lab using Nikon Spinning Disk confocal microscope equipped with Apo TIRF Oil 100X 1.49 NA objective or instant Structured Illumination Microscopy (iSIM), using deconvolution (Microvolution software) and in a specific magnification. It remains to be seen whether the tool would be equally effective with images taken with other microscopy systems, with other cardiomyocytes (chick or neonatal rat), with different magnifications, live imaging, etc. The authors state that this approach is also useful in other situations, but the data is not included in this manuscript.<br /> 3. The tool was developed for evaluation of sarcomere assembly. The authors show that for this application it can detect the perturbation by Blebbistatin, or knockdown of sarcomeric genes. It remains to be seen if this tool is also useful for assessment of sarcomere structure for other questions beside sarcomere assembly and in other sarcomere pathologies.