Reviewer #1 (Public Review):

The authors demonstrate that reactivation of mild vs strong aversive contextual associations produces dissociable effects on fos expression across a wide network of relevant brain regions. Mild, 2-shock memory recruits a 'small-world' network in which amygdalar regions are functionally connected to other regions that modulate their activity and behavioral output, whereas strong, 10-shock memory isolates amygdalar nuclei from the rest of the network. These different patterns of correlated neural activity correspond with functional/behavioral differences - the authors confirm that weak, 2-shock memory is more effectively extinguished and is susceptible to reconsolidation relative to strong, 10-shock memory.

One major drawback of the manuscript is the fact that the data were collected from male subjects only. One might expect similar behavioral outcomes from male and female rats receiving 2-shock and 10-shock training. However, increasing attention to sex as a biological variable has revealed an interesting truth, namely that males and females can engage distinct neural pathways to arrive at the same behavioral destination. It should not be taken for granted that retrieval of aversive contextual associations would reproduce the same networks in females, and, as such, the manuscript does not give a complete accounting of the phenomenon under study.

Reviewer #2 (Public Review):

The manuscript examined the behavioural and neural profile of weak and strong fear memories. The data provide strong evidence that weak but not strong fear memories are subject to extinction and reconsolidation disruption. Strong memories also show greater generalization. These differences were echoed in differential neural connectivity with weak fear memories showing greater connectivity between brains areas than strong fear memories.

The findings are of a great importance and offer insight into why resistance to extinction and reconsolidation may underlie fear-related psychopathology.<br /> The study uses key behavioural tests to study the durability of weak vs strong memories (extinction and reconsolidation) as well as studies the generalisation of those memories. These behavioural effects nicely dovetail with the neural connectivity analyses that were performed.<br /> The data presented in this paper will be the basis for future hypothesis driven examinations on the causal influence of specific pathways involved in contextual fear.<br /> Excellent use of the open field to control for motor effects.

This is a strong paper and the results support the conclusions. The findings are of broad interest and are important for future research.

Reviewer #1 (Public Review):

Bolumar et al. isolated and characterized EV subpopulations, apoptotic bodies (AB), Microvesicles (MV), and Exosomes (EXO), from endometrial fluid through the female menstrual cycle. By performing DNA sequencing, they found the MVs contain more specific DNA sequences than other EVs, and specifically, more mtDNA were encapsulated in MVs. They also found a reduction of mtDNA content in the human endometrium at the receptive and post-receptive period that is associated with an increase in mitophagy activity in the cells, and a higher mtDNA content in the secreted MVs was found at the same time. Last, they demonstrated that the endometrial Ishikawa cell-derived EVs could be taken by the mouse embryos and resulted in altered embryo metabolism.

This is a very interesting study and is the first one demonstrating the direct transmission of maternal mtDNA to embryos through EVs.

Reviewer #2 (Public Review):

In Bolumar, Moncayo-Arlandi et al. the authors explore whether endometrium-derived extracellular vesicles contribute DNA to embryos and therefore influence embryo metabolism and respiration. The manuscript combines techniques for isolating different populations of extracellular vesicles, DNA sequencing, embryo culture, and respiration assays performed on human endometrial samples and mouse embryos.

Vesicle isolation is technically difficult and therefore collection from human samples is commendable. Also, the influence of maternally derived DNA on the bioenergetics of embryos is unknown and therefore novel. However, several experiments presented in the manuscript fail to reach statistical significance, likely due to the small sample sizes. This manuscript is a good but incomplete start as to the potential function of maternal DNA transfer via vesicles.

In my opinion the manuscript supports the following of the authors' claims:

1. Different amounts of nDNA and mtDNA are shed in human endometrial extracellular vesicles during different phases of the menstrual cycle.<br /> 2. Endometrial microvesicles are more enriched for mitochondrial DNA sequences compared to other types of vesicles present in the human samples.<br /> 3. Fluorescently labelled DNA from extracellular vesicles derived from an endometrial adenocarcinoma cell line can be incorporated into hatched mouse embryos.<br /> 4. Culture of mouse embryos with endometrial extracellular vesicles can influence embryo respiration and the effect is greater when cultured with isolated exosomes compared to other isolated microvesicles.

My main concerns with the manuscript:

1. Several experiments presented fail to reach statistical significance or are qualitative.<br /> 2. The definitive experiments presented in the manuscript are limited to the transfer of DNA in general not mtDNA. Therefore a strong connection with metabolism is missing, diminishing the significance of the findings.

Reviewer #1 (Public Review):

Summary:<br /> Previously, researchers targeting certain brain areas in mice have relied on manual reconstruction of 3D trajectories based on published atlases of 2D sections in standardized anatomical planes. Over a decade ago, Leica's AngleTwo software provided an early proprietary software interface to rodent atlases based on 2D graphics. However, the more recent advent of open-source 3D gaming engines and CAD software (here the authors used Unity) and the adoption of a common 3D atlas framework (the Common Coordinate Framework, or CCF, from the Allen Institute) by the neuroscience community have enabled more advanced targeting based on 3D anatomy, as primate researchers and human clinicians have done previously with MRI data using bespoke and commercial software solutions. The Neuropixels Trajectory Explorer (https://github.com/petersaj/neuropixels_trajectory_explorer, by Andy Peters) pioneered a software interface to the 3D mouse atlas for electrode insertions, and here Birman et al. have built on the aforementioned previous efforts to provide the most comprehensive trajectory planning software in mice to date, which they call Pinpoint. The most critical improvement lies in the ability to model the experimental rig and instruments in the same 3D environment as the atlas, since previously researchers needed to iteratively guess and check whether instruments physically fit with each other and the other constraints imposed by the rig. Other key features include coordinate transforms to map the CCF to more accurate in vivo anatomical data, as well as an API and hardware interface to commonly used micromanipulators.

Strengths:<br /> The feature set in Pinpoint makes it the best available software for planning instrument trajectories given geometrical constraints. Additionally, the documentation and open-source nature of the software should allow many extensions and improvements in the future, and as the authors note, it can also be used as a powerful teaching tool. Especially as researchers continue to push the boundaries of concurrent electrodes and optical fibers or other instruments within a single brain, this software will be of great use for neuroscience.

Weaknesses:<br /> Although Pinpoint enables instrument insertion planning with geometrical constraints for the first time and has many other novel features, it remains to be quantified how useful it is in terms of time/efficiency gains and accuracy of planned trajectories. For instance, although using a coordinate transform to MRI anatomical data is more accurate than the CCF alone in principle, users will need to verify how much this improved planning ability translates to time saved and/or improved trajectories as reconstructed from histology of dyed electrode tracks. The utility of the hardware interface for automating experiments versus the risk of damaging instruments with such an approach also remains to be quantified. Researchers using experimental subjects other than adult mice will have to wait for future integration of their atlases of choice, although the open-source nature of the project invites others to try adding this and other desired features themselves.

Reviewer #2 (Public Review):

Pinpoint by Birman et al. serves not only as a probe trajectory planning tool but also offers a far richer suite of functionalities. It provides a simple and intuitive environment that users can learn within minutes and start planning trajectories for multiple probes based on the Allen mouse brain atlas. Pinpoint further includes two MRI-based transformations to better map the Allen atlas to live brains. It features a coefficient to adjust for different Bregma-Lambda distances and includes a mouse skull model to provide a better approximation of the craniotomy coordinates, rather than the coordinate of the point of insertion on the brain. It also offers tools to link the application to manipulator controllers to visualise the position of probes in the brain in real-time. Remarkably, most of these features are available right from the web browser, without the need to install anything or any coding knowledge.

The authors developed an open-source and well-documented software. Although I did not test it myself, it can communicate with the most common recording softwares (Open Ephys, SpikeGLX) and manipulators (New Scale, Sensapex) in the field. The current level of support by the developers on GitHub is reassuring, and I hope this continues as Pinpoint matures into a more stable and robust version.

Reviewer #3 (Public Review):

Summary:<br /> Birman and colleagues have introduced an invaluable tool designed specifically for electrophysiologists, simplifying the precise planning of trajectories for placing high-density probes within designated locations. Pinpoint offers users an interactive 3D environment within which they can explore electrophysiological trajectories within the anatomical context of the mouse brain. Within this environment, users can visualize the probe, target regions, and the constraints imposed by their experimental setup. Advanced users also have the flexibility to customize the entire Pinpoint scene to align with alternative coordinate systems and rig geometries. In cases involving multiple-probe recordings, Pinpoint shows 3D paths while issuing warnings about potential collisions. Additionally, Pinpoint can account for the individual variability in brain size among mice.

Strengths:<br /> Pinpoint provides real-time visualization of current brain region targets alongside neural data. Anatomical targeting information is accessible live during recordings. This is made possible through two sets of features: hardware that allows Pinpoint to communicate with micro-manipulators and software that broadcasts the current location of each recording channel to data acquisition software. Researchers can monitor the precise positioning of their probe during insertion and observe the anatomical locations of live electrophysiology data throughout an experiment, enabling them to make corrections if necessary.

Weaknesses:<br /> 1. Pinpoint's novelty lies in its ability to be linked to data acquisition programs and electronic micro-manipulators. However, a similar program, Neuropixels Trajectory Explorer, was released before Pinpoint with comparable features. Please refer to https://github.com/petersaj/neuropixels_trajectory_explorer. It would be beneficial to clarify the distinctions between these two applications and discuss on the necessity and advantages of creating Pinpoint.

2. Currently, in Pinpoint, users can only select one area of the mouse brain for probe placement and then use the controller to adjust the probe´s position if they wish to target multiple brain areas. This can complicate planning when inserting multiple probes. It would be advantageous to have the option to choose the specific areas the probes are to traverse, with Pinpoint automatically suggesting the most optimal trajectories while avoiding potential collisions. While this may require additional development, a comment on this possibility would be appreciated.

Reviewer #1 (Public Review):

Summary:<br /> Mice can learn to associate sensory cues (sound and light) with a reward or activation of dopamine neurons in the ventral tegmental area (VTA), and then anticipate the reward from the sensory cue only. Using this paradigm, Harada et al. showed that after learning, the cue is able to induce dopamine release in the projection targets of the VTA, namely the nucleus accumbens and lateral hypothalamus (LH). Within the LH, dopamine release from VTA neurons (either by presentation of the cue or direct optical stimulation of VTA neurons) activates orexin neurons, measured as an increase in intracellular calcium levels.

Strengths:<br /> This study utilized genetically encoded optical tools to selectively stimulate dopamine neurons and to monitor dopamine release in target brain areas and the calcium response of orexin neurons. This allowed a direct assessment of the relationship between the behavioral response of the animals, the release of a key neurotransmitter in select brain areas, and its effect on target cells, with a precision previously not possible. The results shed light on the mechanism underlying reward-related learning and expectation.

Weaknesses:<br /> • The Ca increase in orexin neurons in response to optical stimulation of VTA DA neurons is convincing. However, there is an accumulated body of literature indicating that dopamine inhibits orexin neurons through D2 receptors, particularly at high concentrations both directly and indirectly (PMID 15634779, 16611835, 26036709, 30462527; but note that synaptic effects at low conc are excitatory - PMID 30462527, 26036709). There should be a clear acknowledgment of these previous studies and a discussion directly addressing the discrepancy. Furthermore, there are in-vivo studies that investigated the role of dopamine in the LH involving orexin neurons in different behavioral contexts (e.g. PMID 24236888). The statement found in the introduction "whether and how dopamine release modulates orexin neuronal activity has not been investigated vigorously" (3rd para of Introduction) is an understatement of these previous reports.

• Along these lines, previous reports of concentration-dependent bidirectional dopaminergic modulation of orexin neurons suggest that high and low levels of DA would affect orexin neurons differently. Is there any way to estimate the local concentration of DA released by the laser stimulation protocol used in this study? Could there be a dose dependency in the intensity of laser stimulation and orexin neuron response?

• The transient dip in DA signal during omission sessions in Fig2C (approx 1% decrease from baseline) is similar in amplitude compared to the decrease seen in non-laser trails shown in Fig 1C right panel (although the time course of the latter is unknown as the data is truncated). The authors should clarify whether those dips are a direct effect of the cue itself or indeed reward prediction error.

• There seem to be orexin-negative-GCaMP6 positive cells (Fig. 4B), suggesting that not all cells were phenotypically orexin+ at the time of imaging. The proportion of GCaMP6 cells that were ORX+ or negative and whether they responded differently to the stimuli should be indicated.

• Laser stimulation of DA neurons at the level of cell bodies (in VTA) induces an increase in DA release within the LH (Fig. 3C, D), however, there is no corresponding Ca signal in orexin neurons (Fig.4C). In contrast, stimulating DA terminals within the LH induces a robust, long-lasting Ca signal (> 30s) in orexin neurons (Fig. 5). The initial peak is blocked by raclopride but the majority of Ca signal is insensitive to DA antagonists (please add a positive control or cite references indicating that the dose of antagonists used was sufficient; also the timing of antagonist administration should be indicated). Taken together, these results seem to suggest that DA does not directly increase Ca signal in orexin neurons. What could be mediating the remaining component?

• Similarly, there is an elevation of Ca signal in orexin neurons that remains significantly higher after the cue/laser stimulation (Fig. 4F). It appears that it is this sustained component that is missing in omission trials. This can be analyzed further.

• Mice of both sexes were used in this study; it would be interesting to know whether sex differences were observed or not.

Reviewer #2 (Public Review):

Summary:<br /> This is an interesting and well-written study assessing the role of dopaminergic inputs from the VTA on orexin cell responses in an opto-pavlovian conditioning task. These data are consistent with a possible role of this system in reward expectation and are surprisingly one of the first demonstrations of a role for dopamine in this phenomenon.

Strengths:

The study has used an interesting opto-Pavlovian approach combined with fibre photometry.

Weaknesses:

It is unclear what n size was used or analysed, particularly for AUC measures e.g. Figures 1 D/E and 3 G. The number of trials reflected and the animal numbers need clarification.

The study focussed on opto-stim omissions - this work would be significantly strengthened by a comparison to a real-world examination where animals are trained for a radiation reward (food pellet). Have the authors considered the role of orexin in the opposing situation i.e. a surprise addition of reward? Similarly, there remains some conjecture regarding the role of these systems in reward and aversion - have the authors considered aversive learning paradigms - fear, or fear extinction - to further explore the roles of this system? There are some (important) discussions about the possible role of orexin in negative reinforcement. Further studies to address this could be warranted.

I think some further discussion of the work by Lineman concerning the interesting bidirectional actions of d1/d2 r signalling on glutamatergic transmission onto orexin neurons is worthwhile. While this work is currently cited, the nuance and perhaps relevance to d1 and d2 signalling could be contextualised a little more (https://doi.org/10.1152/ajpregu.00150.2018).

Reviewer #3 (Public Review):

Summary:<br /> Harada and colleagues describe an interesting set of experiments characterizing the relationship between dopamine cell activity in the ventral tegmental area (VTA) and orexin neuron activity in the lateral hypothalamus (LH). All experiments are conducted in the context of an opto-Pavlovian learning task, in which a cue predicts optogenetic stimulation of VTA dopamine neurons. With training, cues that predict DA stimulation come to elicit dopamine release in LH (a similar effect is seen in accumbens). After training, omission trials (cue followed by no laser) result in a dip (inhibition) of dopamine release in LH, characteristic of reward prediction error observed in the striatum. Across cue training, the activity pattern of orexin neurons in LH mirrors that of LH DA levels. However, unlike the DA signal, orexin neurons do not exhibit a decrease in activity in omission trials. Systemic blockade of D2 but not D1 receptors blocked DA release in LH following VTA DA cell stimulation.

Strengths:<br /> Although much work has been dedicated to examining projections from orexin cells to VTA, less has been done to characterize reciprocal projections and their function. In this way, this paper is a very important addition to the literature. The experiments are technically sound (with some limitations, below) and utilize sophisticated approaches, the manuscript is nicely written, and the conclusions are mostly reasonable based on the data collected.

Weaknesses:<br /> I believe the impact of the paper could be enhanced by considering and/or addressing the following:

Major:<br /> • I encourage the authors to discuss in the Introduction previous work on DA regulation of orexin neurons. In particular, the authors cite, but do not describe in any detail, the very relevant Linehan paper (2019; Am J Physiol Regul) which shows that DA differentially alters excitatory/inhibitory input onto orexin neurons and that these actions are reversed by D1 vs D2 receptor antagonists. Another paper (Bubser, 2005, EJN) showed that dopamine agonists increase the activity of orexin neurons and that these effects are blocked by D1/D2 antagonists. The current findings should be discussed in the context of these (and any other relevant) papers in the Discussion, too.<br /> • In the Discussion, the authors provide two (plausible) explanations for why they did not observe a dip in the calcium signal of orexin neurons during omission trials. Is it not possible that these cells do not encode for this type of RPE?<br /> • Related to the above - I am curious about the authors' thoughts on why there is such redundancy in the system. i.e. why is dopamine doing the same thing in NAC and LH in the context of cue-reward learning?<br /> • The data, as they stand, are largely correlative and do not indicate that DA recruitment of orexin neurons is necessary for learning to occur. It would be compelling if blocking the orexin cell recruitment affected some behavioral outcomes of learning. Similarly - does raclopride treatment across training prevent learning?<br /> • Only single doses of SCH23390 and raclopride were used. How were these selected? It would be nice to use more of a dose range to show that 1) and effect of D1R blockade was not missed, and 2) that the reduction in orexin signal with raclopride was dose-dependent.<br /> • Fig 1C, could the effect the authors observed be due to movement? Relatedly, what was the behavior like when the cue was on? Did mice orient/approach the cue? Also, when does the learning about the cue occur? Does it take all 10 days of learning or does this learning/cue-induced increase in dopamine signaling occur in less than 10 days?<br /> • Also related to the above, could the observed dopamine signal be a result of just the laser turning on? It would seem important to include mice with a control sensor.<br /> • Fig 1E, the effect seems to be driven by one mouse which looks like it could be a statistical outlier. The inclusion of additional animals would make these data more compelling.<br /> • For Fig 1C, 3D, 3F, and 4D, could the authors please show the traces for the entire length of laser onset? It would be helpful to see both the rise and the fall of dopamine signals.<br /> • Fig 2C, could the authors comment on how they compared the AUC to baseline? Was this comparison against zero? Because of natural hills and troughs during signals prior to cue (which may not equate to a zero), comparing the omission-induced dip to a zero may not be appropriate. A better baseline might be using the signals prior to the cue.<br /> • Could the authors comment on how they came up with the 4-5.3s window to observe the AUC in Fig 3H?

Reviewer #1 (Public Review):

Summary:<br /> Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness, and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.

Strengths:<br /> The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.

Weaknesses:<br /> To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; i.e. 25% of shocks are omitted, regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, or 0%. Given previous findings on interactions between verbal instruction and experiential learning (Doll et al., 2009; Li et al., 2011; Atlas et al., 2016), it seems problematic a) to treat the instructions as veridical and b) average responses over time. Based on this prior work, it seems reasonable to assume that participants would learn to downweight the instructions over time through learning (particularly in the 100% and 0% cases); this would be the purpose of prediction errors as a teaching signal. The authors do recognize this and perform a subset analysis in the 21 participants who showed parametric increases in anticipatory SCR as a function of instructed shock probability, which strengthened findings in the VTA/SN; however given that one-third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account. Lastly, I think that findings in threat-sensitive regions such as the anterior insula and amygdala may not be adequately captured in the title or abstract which strictly refers to the "human reward system"; more nuance would also be warranted.

Reviewer #2 (Public Review):

The question of whether the neural mechanisms for reward and punishment learning are similar has been a constant debate over the last two decades. Numerous studies have shown that the midbrain dopamine neurons respond to both negative and salient stimuli, some of which can't be well accounted for by the classic RL theory (Delgado et al., 2007). Other research even proposed that aversive learning can be viewed as reward learning, by treating the omission of aversive stimuli as a negative PE (Seymour et al., 2004).

Although the current study took an axiomatic approach to search for the PE encoding brain regions, which I like, I have major concerns regarding their experimental design and hence the results they obtained. My biggest concern comes from the false description of their task to the participants. To increase the number of "valid" trials for data analysis, the instructed and actual probabilities were different. Under such a circumstance, testing axiom 2 seems completely artificial. How does the experimenter know that the participants truly believe that the 75% is more probable than, say, the 25% stimulation? The potential confusion of the subjects may explain why the SCR and relief report were rather flat across the instructed probability range, and some of the canonical PE encoding regions showed a rather mixed activity pattern across different probabilities. Also for the post-hoc selection criteria, why pick the larger SCR in the 75% compared to the 25% instructions? How would the results change if other criteria were used?

To test axiom 3, which was to compare the 100% stimulation to the 0% stimulation conditions, how did the actual shock delivery affect the fMRI contrast result? It would be more reasonable if this analysis could control for the shock delivery, which itself could contaminate the fMRI signal, with extra confound that subjects may engage certain behavioral strategies to "prepare for" the aversive outcome in the 100% stimulation condition. Therefore, I agree with the authors that this contrast may not be a good way to test axiom 3, not only because of the arguments made in the discussion but also the technical complexities involved in the contrast.

Reviewer #3 (Public Review):

Summary:<br /> The authors conducted a human fMRI study investigating the omission of expected electrical shocks with varying probabilities. Participants were informed of the probability of shock and shock intensity trial-by-trial. The time point corresponding to the absence of the expected shock (with varying probability) was framed as a prediction error producing the cognitive state of relief/pleasure for the participant. fMRI activity in the VTA/SN and ventral putamen corresponded to the surprising omission of a high probability shock. Participants' subjective relief at having not been shocked correlated with activity in brain regions typically associated with reward-prediction errors. The overall conclusion of the manuscript was that the absence of an expected aversive outcome in human fMRI looks like a reward-prediction error seen in other studies that use positive outcomes.

Strengths:<br /> Overall, I found this to be a well-written human neuroimaging study investigating an often overlooked question on the role of aversive prediction errors, and how they may differ from reward-related prediction errors. The paper is well-written and the fMRI methods seem mostly rigorous and solid.

Weaknesses:<br /> I did have some confusion over the use of the term "prediction-error" however as it is being used in this task. There is certainly an expectancy violation when participants are told there is a high probability of shock, and it doesn't occur. Yet, there is no relevant learning or updating, and participants are explicitly told that each trial is independent and the outcome (or lack thereof) does not affect the chances of getting the shock on another trial with the same instructed outcome probability. Prediction errors are primarily used in the context of a learning model (reinforcement learning, etc.), but without a need to learn, the utility of that signal is unclear.

An overarching question posed by the researchers is whether relief from not receiving a shock is a reward. They take as neural evidence activity in regions usually associated with reward prediction errors, like the VTA/SN. This seems to be a strong case of reverse inference. The evidence may have been stronger had the authors compared activity to a reward prediction error, for example using a similar task but with reward outcomes. As it stands, the neural evidence that the absence of shock is actually "pleasurable" is limited-albeit there is a subjective report asking subjects if they felt relief.

I have some other comments, and I elaborate on those above comments, below:

1. A major assumption in the paper is that the unexpected absence of danger constitutes a pleasurable event, as stated in the opening sentence of the abstract. This may sometimes be the case, but it is not universal across contexts or people. For instance, for pathological fears, any relief derived from exposure may be short-lived (the dog didn't bite me this time, but that doesn't mean it won't next time or that all dogs are safe). And even if the subjective feeling one gets is temporary relief at that moment when the expected aversive event is not delivered, I believe there is an overall conflation between the concepts of relief and pleasure throughout the manuscript. Overall, the manuscript seems to be framed on the assumption that "aversive expectations can transform neutral outcomes into pleasurable events," but this is situationally dependent and is not a common psychological construct as far as I am aware.

2. The authors allude to this limitation, but I think it is critical. Specifically, the study takes a rather simplistic approach to prediction errors. It treats the instructed probability as the subjects' expectancy level and treats the prediction error as omission related activity to this instructed probability. There is no modeling, and any dynamic parameters affected by learning are unaccounted for in this design. That is subjects are informed that each trial is independently determined and so there is no learning "the presence/absence of stimulations on previous trials could not predict the presence/absence of stimulation on future trials." Prediction errors are central to learning. It is unclear if the "relief" subjects feel on not getting a shock on a high-probability trial is in any way analogous to a prediction error, because there is no reason to update your representation on future trials if they are all truly independent. The construct validity of the design is in question.

3. Related to the above point, even if subjects veered away from learning by the instruction that each trial is independent, the fact remains that they do not get shocks outside of the 100% probability shock. So learning is occurring, at least for subjects who realize the probability cue is actually a ruse.

4. Bouton has described very well how the absence of expected threat during extinction can create a feeling of ambiguity and uncertainty regarding the signal value of the CS. This in large part explains the contextual dependence of extinction and the "return of fear" that is so prominent even in psychologically healthy participants. The relief people feel when not receiving an expected shock would seem to have little bearing on changing the long-term value of the CS. In any event, the authors do talk about conditioning (CS-US) in the paper, but this is not a typical conditioning study, as there is no learning.

5. In Figure 2 A-D, the omission responses are plotted on trials with varying levels of probability. However, it seems to be missing omission responses in 0% trials in these brain regions. As depicted, it is an incomplete view of activity across the different trial types of increasing threat probability.

6. If I understand Figure 2 panels E-H, these are plotting responses to the shock versus no-shock (when no-shock was expected). It is unclear why this would be especially informative, as it would just be showing activity associated with shocks versus no-shocks. If the goal was to use this as a way to compare positive and negative prediction errors, the shock would induce widespread activity that is not necessarily reflective of a prediction error. It is simply a response to a shock. Comparing activity to shocks delivered after varying levels of probability (e.g., a shock delivered at 25% expectancy, versus 75%, versus 100%) would seem to be a much better test of a prediction error signal than shock versus no-shock.

7. I was unclear what the results in Figure 3 E-H were showing that was unique from panels A-D, or where it was described. The images looked redundant from the images in A-D. I see that they come from different contrasts (non0% > 0%; 100% > 0%), but I was unclear why that was included.

8. As mentioned earlier, there is a tendency to imply that subjects felt relief because there was activity in "the reward pathway."

9. From the methods, it wasn't entirely clear where there is jitter in the course of a trial. This centers on the question of possible collinearity in the task design between the cue and the outcome. The authors note there is "no multicollinearity between anticipation and omission regressors in the first-level GLMs," but how was this quantified? The issue is of course that the activity coded as omission may be from the anticipation of the expected outcome.

10. I did not fully understand what the LASSO-PCR model using relief ratings added. This result was not discussed in much depth, and seems to show a host of clusters throughout the brain contributing positively or negatively to the model. Altogether, I would recommend highlighting what this analysis is uniquely contributing to the interpretation of the findings.

Reviewer #1 (Public Review):

Strengths:<br /> The authors introduced a new adapted paradigm from continuous flash suppression (CFS). The new CFS tracking paradigm (tCFS) allowed them to measure suppression depth in addition to breakthrough thresholds. This innovative approach provides a more comprehensive understanding of the mechanisms underlying continuous flash suppression. The observed uniform suppression depth across target types (e.g., faces and gratings) is novel and has new implications for how the visual system works. The experimental manipulation of the target contrast change rate, as well as the modeling, provided strong support for an early interocular suppression mechanism. The authors argue that the breakthrough threshold alone is not sufficient to infer about unconscious processing.

Weaknesses:<br /> A major finding in the current study is the null effect of the image categories on the suppression depth measured in the tCFS paradigm, from which the authors infer an early interocular mechanism underlying CFS suppression. This is not strictly logical as an inference based on the null effect. The authors may consider statistical evaluation of the null results, such as equivalence tests or Bayesian estimation.

More importantly, since limited types of image categories have been tested, there may be some exceptional cases. According to "Twofold advantages of face processing with or without visual awareness" by Zhou et al. (2021), pareidolia faces (face-like non-face objects) are likely to be an exceptional case. They measured bidirectional binocular rivalry in a blocked design, similar to the discrete condition used in the current study. They reported that the face-like non-face object could enter visual awareness in a similar fashion to genuine faces but remain in awareness in a similar fashion to common non-face objects. We could infer from their results that: when compared to genuine faces, the pareidolia faces would have a similar breakthrough threshold but a higher suppression threshold; when compared to common objects, the pareidolia faces would have a similar suppression threshold but a low breakthrough threshold. In this case, the difference between these two thresholds for pareidolia faces would be larger than either for genuine faces or common objects. Thus, it would be important for the authors to discuss the boundary between the findings and the inferences.

Reviewer #2 (Public Review):

Summary<br /> The paper introduces a valuable method, tCFS, for measuring suppression depth in continuous flash suppression (CFS) experiments. tCFS uses a continuous-trial design instead of the discrete trials standard in the literature, resulting in faster, better controlled, and lower-variance estimates. The authors measured suppression depth during CFS for the first time and found similar suppression depths for different image categories. This finding provides an interesting contrast to previous results that breakthrough thresholds differ for different image categories and refine inferences of subconscious processing based solely on breakthrough thresholds. However, the paper overreaches by claiming breakthrough thresholds are insufficient for drawing certain conclusions about subconscious processing.

Strengths<br /> 1. The tCFS method, by using a continuous-trial design, quickly estimates breakthrough and re-suppression thresholds. Continuous trials better control for slowly varying factors such as adaptation and attention. Indeed, tCFS produces estimates with lower across-subject variance than the standard discrete-trial method (Fig. 2). The tCFS method is straightforward to adopt in future research on CFS and binocular rivalry.<br /> 2. The CFS literature has lacked re-suppression threshold measurements. By measuring both breakthrough and re-suppression thresholds, this work calculated suppression depth (i.e., the difference between the two thresholds), which warrants different interpretations from the breakthrough threshold alone.<br /> 3. The work found that different image categories show similar suppression depths, suggesting some aspects of CFS are not category-specific. This result enriches previous findings that breakthrough thresholds vary with image categories. Re-suppression thresholds vary symmetrically, such that their differences are constant.

Weaknesses<br /> 1. The results and arguments in the paper do not support the claim that 'variations in breakthrough thresholds alone are insufficient for inferring unconscious or preferential processing of given image categories,' to take one example phrasing from the abstract. The same leap in reasoning recurs on lines 28, 39, 125, 566, 666, 686, 759, etc.<br /> Take, for example, the arguments on lines 81-83. Grant that images are inequivalent, and this explains different breakthrough times. This is still no argument against differential subconscious processing. Why are images non-equivalent? Whatever the answer, does it qualify as 'residual processing outside of awareness'? Even detecting salience requires some processing. The authors appear to argue otherwise on lines 694-696, for example, by invoking the concept of effective contrasts, but why is effective contrast incompatible with partial processing? Again, does detecting (effective) contrast not involve some processing? The phrases 'residual processing outside of awareness' and 'unconscious processing' are broad enough to encompass bottom-up salience and effective contrast. Salience and (effective) contrast are arguably uninteresting, but that is a different discussion. The authors contrast 'image categories' or semantics with 'low-level factors.' In my opinion, this is a clearer contrast worth emphasizing more. However, semantic processing is not equal to subconscious processing writ large. The preceding does not detract from the interest in finding uniform suppression depth. Suppression depth and absolute bCFS can conceivably be due to orthogonal mechanisms warranting their own interpretations. In fact, the authors briefly take this position in the Discussion (lines 696-704, 'A hybrid model ...'). The involvement of different mechanisms would defeat the argument on lines 668-670.

2. These two hypotheses are confusing and should be more clearly distinguished: a) varying breakthrough times may be due to low-level factors (lines 76-79); b) uniform suppression depth may also arise from early visual mechanisms (e.g., lines 25-27).

Neutral remarks<br /> The depth between bCFS and reCFS depended on measurement details such as contrast change speed and continuous vs. discrete trials. With discrete trials, the two thresholds showed inverse relations (i.e., reCFS > bCFS) in some participants. The authors discuss possible reasons at some length (adaptation, attention, etc. ). Still, a variable measure does not clearly indicate a uniform mechanism.

Reviewer #3 (Public Review):

Summary:<br /> In the 'bCFS' paradigm, a monocular target gradually increases in contrast until it breaks interocular suppression by a rich monocular suppressor in the other eye. The present authors extend the bCFS paradigm by allowing the target to reduce back down in contrast until it becomes suppressed again. The main variable of interest is the contrast difference between breaking suppression and (re) entering suppression. The authors find this difference to be constant across a range of target types, even ones that differ substantially in the contrast at which they break interocular suppression (the variable conventionally measured in bCFS). They also measure how the difference changes as a function of other manipulations. Interpretation in terms of the processing of unconscious visual content, as well as in terms of the mechanism of interocular suppression.

Strengths:<br /> Interpretation of bCFS findings is mired in controversy, and this is an ingenuous effort to move beyond the paradigm's exclusive focus on breaking suppression. The notion of using the contrast difference between breaking and entering suppression as an index of suppression depth is interesting, but I also feel like it can be misleading at times, as detailed below.

Weaknesses:<br /> Here's one doubt about the 'contrast difference' measure used by the authors. The authors seem confident that a simple subtraction is meaningful after the logarithmic transformation of contrast values, but doesn't this depend on exactly what shape the contrast-response function of the relevant neural process has? Does a logarithmic transformation linearize this function irrespective of, say, the level of processing or the aspect of processing that we're talking about? Given that stimuli differ in terms of the absolute levels at which they break (and re-enter) suppression, the linearity assumption needs to be well supported for the contrast difference measure to be comparable across stimuli.

Here's a more conceptual doubt. The authors introduce their work by discussing ambiguities in the interpretation of bCFS findings with regard to preferential processing, unconscious processing, etc. A large part of the manuscript doesn't really interpret the present 'suppression depth' findings in those terms, but at the start of the discussion section (lines 560-567) the authors do draw fairly strong conclusions along those lines: they seem to argue that the constant 'suppression depth' value observed across different stimuli argues against preferential processing of any of the stimuli, let alone under suppression. I'm not sure I understand this reasoning. Consider the scenario that the visual system does preferentially process, say, emotional face images, and that it does so under suppression as well as outside of suppression. In that scenario, one might expect the contrast at which such a face breaks suppression to be low (because the face is preferentially processed under suppression) and one might also expect the contrast at which the face enters suppression to be low (because the face is preferentially processed outside of suppression). So the difference between the two contrasts might not stand out: it might be the same as for a stimulus that is not preferentially processed at all. In sum, even though the author's label of 'suppression depth' on the contrast difference measure is reasonable from some perspectives, it also seems to be misleading when it comes to what the difference measure can actually tell us that bCFS cannot.

The authors acknowledge that non-zero reaction time inflates their 'suppression depth' measure, and acknowledge that this inflation is worse when contrast ramps more quickly. But they argue that these effects are too small to explain either the difference between breaking contrast and re-entering contrast to begin with, or the increase in this difference with the contrast ramping rate. I agree with the former: I have no doubt that stimuli break suppression (ramping up) at a higher contrast than the one at which they enter suppression (ramping down). But about the latter, I worry that the RT estimate of 200 ms may be on the low side. 200 ms may be reasonable for a prepared observer to give a speeded response to a clearly supra-threshold target, but that is not the type of task observers are performing here. One estimate of RT in a somewhat traditional perceptual bistability task is closer to 500 ms (Van Dam & Van Ee, Vis Res 45 2005), but I am uncertain what a good guess is here. Bottom line: can the effect of contrast ramping rate on 'suppression depth' be explained by RT if we use a longer but still reasonable estimated RT than 200 ms?

A second remark about the 'ramping rate' experiment: if we assume that perceptual switches occur with a certain non-zero probability per unit time (stochastically) at various contrasts along the ramp, then giving the percept more time to switch during the ramping process will lead to more switches happening at an earlier stage along the ramp. So: ramping contrast upward more slowly would lead to more switches at relatively low contrast, and ramping contrast downward more slowly would lead to more switches at relatively high contrasts. This assumption (that the probability of switching is non-zero at various contrasts along the ramp) seems entirely warranted. To what extent can that type of consideration explain the result of the 'ramping rate' experiment?

When tying the 'dampened harmonic oscillator' finding to dynamic systems, one potential concern is that the authors are seeing the dampened oscillating pattern when plotting a very specific thing: the amount of contrast change that happened between two consecutive perceptual switches, in a procedure where contrast change direction reversed after each switch. The pattern is not observed, for instance, in a plot of neural activity over time, threshold settings over time, etcetera. I find it hard to assess what the observation of this pattern when representing a rather unique aspect of the data in such a specific way, has to do with prior observations of such patterns in plots with completely different axes.

Reviewer #1 (Public Review):

This paper studies how amacrine cells influence retinal output signals. The approach taken is unusually direct. First, the amacrine light response is characterized. Second, the properties of signaling between the amacrine cell and ganglion cells is characterized by injecting current into the amacrine cell while measuring ganglion cell spiking. Third, the ganglion cell light response is analyzed in terms of components produced by signaling pathways that go through the amacrine cell and those that do not. Interpretation of the results relies on several important and largely untested assumptions. If some of the concerns that this dependence produces can be reduced the paper would be substantially stronger.

Linear vs. nonlinear and direct vs. indirect<br /> Influences of an amacrine cell on the ganglion cell response are separated into direct effects - in which the amacrine cell directly produces a component of the ganglion cell response - and indirect effects - in which the amacrine cell modulates component(s) of the ganglion cell response (e.g. lines 97-99). In various places direct and indirect are equated with linear and nonlinear. Importantly, this assumption forms the basis of the analysis in the paper. It is not clear why a direct pathway through the amacrine cell should be linear. For example, it seems entirely possible that nonlinear models would capture the amacrine cell light response better than linear models. Similarly, nonlinear models may better capture the transmission of signals from amacrine cells to ganglion cells. Clarity on this issue is essential to interpret the results in the paper. One example of this issue comes up in the sentence on line 233. The definition of modulation is precise but only in the context of the above assumptions.

Components of oSTA<br /> The set of pre-spike stimuli that are orthogonal to the "direct" STA is used to characterize the "indirect" pathways conveying signals to a ganglion cell. For the reasons noted above, it is not clear that this is accurate. In addition, the text describes the PCs of this orthogonal stimulus ensemble as features. This is introduced in the paragraph starting on line 177, and this paragraph has the disclaimer that these features do not correspond to neural pathways. That important caveat to interpretation could be reiterated in the following text - particularly in discussing the different forms of modulation.

Related to this point, the analysis of Figures 3 and 4 relies on the PCs of this orthogonal stimulus ensemble. Since the PCs themselves do not map onto pathways or mechanisms, it is not clear how to interpret some of the results. For example, when you see a polarity shift along one of the PCs, what happens along others (for example, could they also be shifting polarity such that the net effect is a change in kinetics but not a change in polarity)? This also comes up in the paragraph on line 236, as it is not clear how the separation works given the way the components used as the basis of the separation are defined.

Some of these issues are clarified in Figure 4D, and perhaps it would help to start with that description. I think this section would be much clearer if two types of modulation were noted and then it was laid out how that conclusion was reached.

Reviewer #2 (Public Review):

Summary:<br /> The authors analyze how individual amacrine cells in the salamander retina can affect the sensitivity of retinal ganglion cells to different visual features. They use simultaneous recordings of amacrine and ganglion cells and apply current injection into the amacrine cells to assess the evoked response modulation of ganglion cells. The resulting transmission filter is combined with the amacrine cell's temporal receptive field to determine a visual feature that stands for the visual signal processing from stimulus to a ganglion cell via the recorded amacrine cell. This sets the stage for analyzing how activation of this "amacrine pathway" affects the encoding of other (orthogonal) visual features by the ganglion cell.

Strengths:<br /> The direct measurements of amacrine cell signals and their signal transmission to ganglion cells in challenging dual recordings is certainly a strength of this paper. In addition, the authors use an original and intriguing computational framework to analyze interactions of different visual features encoded by a ganglion cell and ask important questions about how inhibitory interneurons modulate stimulus encoding. The concept of distinct types of amacrine cell function with feature-specific modulation of input sensitivity and global modulation of output strength is thought-provoking and an interesting concept for follow-up investigations.

Weaknesses:<br /> However, despite the emphasis on a causal approach and direct measurements of amacrine cell effects, the paper does not use actual amacrine cell signals for the main analyses, but rather a proxy given by visual signals that are consistent with the amacrine-to-ganglion signal transmission. In doing so, it is largely disregarded that visual filters of other pathways (including, e.g., fatigue or desensitization in the excitatory signals) may overlap with the deduced amacrine pathways. It thus remains unclear how much such alternative pathways may contribute to the signals assigned to the amacrine pathway and how this might influence the findings and their interpretations. In addition, the analysis and interpretation of the amacrine pathway are hard to follow and easy to misunderstand, because the paper often applies ambiguous language by referring to the visual stimulus dimension of the amacrine pathway as "amacrine output" and "amacrine effects" and by equating activation or deactivation of the amacrine pathway with hyperpolarization or depolarization of the amacrine cell.

Some other interpretations are also unclear, by taking the results a bit too far. For example, the emphasis on divisive normalization remains unclear, as divisive normalization seems more specific than the general suppressive effects described here. Similarly, the connection to the previously observed reversal of preferred contrast by ganglion cells is somewhat tenuous. Here, the potential reversal in the analyzed response nonlinearities only concerns specific features that nonlinearly interact with other features and therefore do not easily translate to the contrast sensitivity of the ganglion cell as a whole, as is suggested in the text. In addition, the two examples of reversals shown in the figures are not fully convincing.

Regarding the clustering analysis of the pairs of amacrine cells and ganglion cell features (Fig. 4), a specific concern is that it is unclear how well the analyzed parameters can actually be extracted from the firing rate response nonlinearities. From the examples in Fig. 4A, it looks like many nonlinearities do not show a clear saturation (but might still yield a good fit by the piece-wise linear model and thus be included in the analysis). It seems plausible that this could result in a bias towards lower gain (defined via the saturation level) when nonlinearities are shifted rightward (higher threshold). It is thus not entirely clear how strong the evidence is for the correlation between gain and threshold changes.

Further, minor caveats are that only 11 amacrine cells go into the analysis, and it remains uncertain to what degree they cover the diversity of amacrine cells in the retina or rather represent a specific subset of types. Also, the restriction to visual signals with no spatial structure, though understandable, limits the generality of the findings. The extracted temporal features remain rather abstract with unspecified significance, in particular since quite a large number of features are extracted per ganglion cell (a total of 321 features, which presumably come from 39 ganglion cells that had a significant amacrine transmission filter).

Reviewer #3 (Public Review):

This study aims to provide a generalizable definition of retinal amacrine cell function in visual processing. The authors used larval tiger salamander retinas and white noise stimulus to measure the retinal ganglion cell responses with multielectrode array recording, while either measuring individual amacrine cell membrane potential or stimulating the amacrine cell by injecting white noise currents using a sharp electrode. Modulatory effects of an amacrine cell on ganglion cells are analyzed by a computational framework that parses the signaling processing underlying ganglion cell responses into multiple conceptual pathways that are differentially subject to the amacrine cell signaling. The authors conclude that an individual amacrine cell can have diverse modulatory effects on ganglion cell responses. One class of effects modulates the sensitivity of the ganglion cell to specific visual features, while the other class of effects modulates the gain of responses to all features.

Amacrine cells are known for their remarkable cell type diversity and serve as key players underlying the complexity of computations performed by the vertebrate retina. However, their functions largely remain a mystery except for a few better-studied cell types. Therefore, the topic of this study is important. Furthermore, the study aims to extract general computational functions from these neurons, which will have broader applications to sensory processing beyond the retina. My main questions are centered around the interpretation of the computational analysis. First of all, the definition of a "visual feature" in this study using the white noise stimulus is different from that used in many other retinal studies using more structured stimuli than white noise. In this study, a major finding is that amacrine cells can control the sensitivity of specific visual features of the ganglion cell. However, it is difficult to gain intuition about how such feature specificity is related to the processing of other artificial and natural stimuli. More discussion along this line will help to clarify the significance of this result.

Another concern is the assumption that the somatic membrane potential of the amacrine cell represents its transmission property to ganglion cells. There are compelling examples that amacrine cells often exhibit local response properties that dramatically differ across the dendritic arbor and the soma (e.g. AIIs, Vlgut3+ ACs, starburst amacrine cells, A17s). This potential (and likely) complication should be addressed.

The dataset in this study is from 8 sustained and 3 transient amacrine cells. Immediate questions are: do all sustained or all transient cells belong to the same cell type in terms of functional properties or morphology? Is there any difference in the modulatory effects between the sustained and transient groups?

There is a rich body of literature on the functions of various amacrine cell types in the mammalian retina in shaping the receptive field properties, gain, and sensitivity of retinal ganglion cells. It would help the reader if the novelty of the current study is adequately discussed in the context of previous work.

Technical:<br /> One concern of sharp electrode recordings is the dialysis of intracellular solution into the cytoplasm, causing changes in membrane properties over time (e.g. Hooper et al., 2015). Have the authors examined the data obtained at the earlier and later phases of the recording to assess the potential effect of dialysis?

Reviewer #1 (Public Review):

In this systematic and elegant structure-function analysis study, the authors delve into the intricate involvement of syntaxin 1 in various pivotal stages of synaptic vesicle priming and fusion. The authors use an original and fruitful approach based on the side-by-side comparison of the specific contributions of the two isoforms syntaxin 1 and syntaxin 2, and their respective SNARE domains, in priming, spontaneous, and Ca2+-dependent glutamate release. The experimental approach, mastered by the authors, offers an ideal means of unraveling the molecular roles played by syntaxins. Although it is not easy to come up with a model explaining all the observed phenotypes, the authors carefully restrict their conclusions to the role of the C-terminal half of the syntaxin1 C-terminal SNARE domain in the maintenance of the RRP and the clamping of neurotransmitter release. The study is carefully carried out, the conclusions are supported by high-quality data, and the manuscript is clearly written. In addition, the study clearly sets new questions that open new paths for future experimental work.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Salazar-Lázaro et al. systematically dissects the different functional properties of the SNARE-domains of syntaxin-1 and syntaxin-2. By systematically substituting the SNARE-domain (or its C- or N-terminal half) into the non-cognate counterpart, the authors find that the C-terminal half of the SNARE-complex is especially important for maintaining RRP size and clamping spontaneous release. They also mutate single residues, to further nail down the effect. Overall, this is an interesting manuscript, which sheds light on the functionality of different co-expressed SNARES.

Strengths:<br /> The strength of the manuscript is the systematic dissection, using substitution of either SNARE-domain into the other syntaxin, together with the state-of-the art methods. The authors follow up with a substitution of single and paired residues. This is a large undertaking, which has been very well carried out.

Weaknesses:<br /> No major weaknesses. The large number of experiments paint a somewhat complicated picture. The writing could be improved in places to increase clarity.

Reviewer #3 (Public Review):

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

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

Weaknesses:<br /> One obvious weakness is that the authors did not explore the underlying mechanism. I think it is easy for the authors to carry out some simple assays to verify their hypothesis for the mechanism, instead of just talking about it in the discussion section.

Reviewer #1 (Public Review):

Summary:<br /> In this paper, the effects of two sensory stimuli (visual and somatosensory) on fMRI responsiveness during absence seizures were investigated in GEARS rats with concurrent EEG recordings. SPM analysis of fMRI showed a significant reduction in whole-brain responsiveness during the ictal period compared to the interictal period under both stimuli, and this phenomenon was replicated in a structurally constrained whole-brain computational model of rat brains.

The conclusion of this paper is that whole-brain responsiveness to both sensory stimuli is inhibited and spatially impeded during seizures.

I also suggest the manuscript should be written in a way that is more accessible to readers who are less familiar with animal experiments. In addition, the implementation and interpretation of brain simulations need to be more careful and clear.

Strengths:<br /> 1. ZTE imaging sequence was selected over traditional EPI sequence as the optimal way to perform fMRI experiments during absence seizures.

2. A detailed classification of stimulation periods is achieved based on the relative position in time of the stimulation period with respect to the brain state.

3. A whole-brain model embedded with a realistic rat connectome is simulated on the TVB platform to replicate fMRI observations.

Weaknesses:<br /> 1. The analysis in this paper does not directly answer the scientific question posed by the authors, which is to explore the mechanisms of the reduced brain responsiveness to external stimuli during absence seizures (in terms of altered information processing), but merely characterizes the spatial involvement of such reduced responsiveness. The same holds for the use of mean-field modeling, which merely reproduces experimental results without explaining them mechanistically as what the authors have claimed at the head of the paper.

2. The implementations of brain simulations need to be more specific.

Contribution:<br /> The contribution of this paper is performing fMRI experiments under a rare condition that could provide fresh knowledge in the imaging field regarding the brain's responsiveness to environmental stimuli during absence seizures.

Reviewer #2 (Public Review):

Summary:<br /> This study examined the possible effect of spike-wave discharges (SWDs) on the response to visual or somatosensory stimulation using fMRI and EEG. This is a significant topic because SWDs often are called seizures and because there is non-responsiveness at this time, it would be logical that responses to sensory stimulation are reduced. On the other hand, in rodents with SWDs, sensory stimulation (a noise, for example) often terminates the SWD/seizure.

In humans, these periods of SWDs are due to thalamocortical oscillations. A certain percentage of the normal population can have SWDs in response to photic stimulation at specific frequencies. Other individuals develop SWDs without stimulation. They disrupt consciousness. Individuals have an absent look, or "absence", which is called absence epilepsy.

The authors use a rat model to study the responses to stimulation of the visual or somatosensory systems during and in between SWDs. They report that the response to stimulation is reduced during the SWDs. While some data show this nicely, the authors also report on lines 396-8 "When comparing statistical responses between both states, significant changes (p<0.05, cluster-) were noticed in somatosensory auditory frontal..., with these regions being less activated in interictal state (see also Figure 4). That statement is at odds with their conclusion.

They also conclude that stimulation slows the pathways activated by the stimulus. I do not see any data proving this. It would require repeated assessments of the pathways in time.

The authors also study the hemodynamic response function (HRF) and it is not clear what conclusions can be made from the data.

Finally, the authors use a model to analyze the data. This model is novel and while that is a strength, its validation is unclear. The conclusion is that the modeling supports the conclusions of the study, which is useful.

Strengths:<br /> Use of fMRI and EEG to study SWDs in rats.

Weaknesses:<br /> Several aspects of the Methods and Results are unclear.

Reviewer #3 (Public Review):

Summary:<br /> This is an interesting paper investigating fMRI changes during sensory (visual, tactile) stimulation and absence seizures in the GAERS model. The results are potentially important for the field and do suggest that sensory stimulation may not activate brain regions normally during absence seizures. However the findings are limited by substantial methodological issues that do not enable fMRI signals related to absence seizures to be fully disentangled from fMRI signals related to the sensory stimuli.

Strengths:<br /> Investigating fMRI brain responses to sensory stimuli during absence seizures in an animal model is a novel approach with the potential to yield important insights.

The use of an awake, habituated model is a valid and potentially powerful approach.

Weaknesses:<br /> The major difficulty with interpreting the results of this study is that the duration of the visual and auditory stimuli was 6 seconds, which is very close to the mean seizure duration per Table 1. Therefore the HRF model looking at fMRI responses to visual or auditory stimuli occurring during seizures was simultaneously weighting both seizure activity and the sensory (visual or auditory) stimuli over the same time intervals on average. The resulting maps and time courses claiming to show fMRI changes from visual or auditory stimulation during seizures will therefore in reality contain some mix of both sensory stimulation-related signals and seizure-related signals. The main claim that the sensory stimuli do not elicit the same activations during seizures as they do in the interictal period may still be true. However the attempts to localize these differences in space or time will be contaminated by the seizure-related signals.

The claims that differences were observed for example between visual cortex and superior colliculus signals with visual stim during seizures vs. interictal are unconvincing due to the above.

The maps shown in Figure 3 do not show clear changes in the areas claimed to be involved.

Reviewer #2 (Public Review):

This work investigates the possible association between language experience and morphology of the superior temporal cortex, a part of the brain responsible for the processing of auditory stimuli. Previous studies have found associations between language and music proficiency as well as language learning aptitude and cortical morphometric measures in regions in the primary and associated auditory cortex. These studies have most often, however, focused on finding neuroanatomical effects of difference between features in a few (often two) languages or from learning single phonetic/phonological features and have often been limited in terms of N. On this background, the authors use more sophisticated measures of language experience that take into account the age of onset and the differences in phonology between languages the subjects have been exposed to as well as a larger number of subjects (N = 146 + 69) to relate language experience to the shape and structure of the superior temporal cortex, measured from T1-weighted MRI data. It shows solid evidence for there being a negative relationship between language experience and the right 2nd transverse temporal gyrus as well as some evidence for the relationship representing phoneme-level cross-linguistic information.

Strengths<br /> The use of entropy measures to quantify language experience and include typological distance measures allows for a more general interpretation of the results and is an important step toward respecting and making use of linguistic diversity in neurolinguistic experiments.

A relatively large group of subjects with a range of linguistic backgrounds.

The full analysis of the structure of the superior temporal cortex including cortical volume, area, as well as the shape of the transverse gyrus/gyri. There is a growing literature on the meaning of the shape and number of the transverse gyri in relation to language proficiency and the authors explore all measures given the available data.

The authors chose to use a replication data set to verify their data, which is applaudable. However, see the relevant point under "Weaknesses".

Weaknesses<br /> The authors fail to explain how a thinner cortex could reflect the specialization of the auditory cortex in the processing of diverse speech input. The Dynamic Restructuring Model (Pliatsikas, 2020) which is referred to does not offer clear guidance to interpretation. A more detailed discussion of how a phonologically diverse environment could lead to a thinner cortex would be very helpful.

It is difficult to understand what measure of language experience is used when. Clearer and more explicit nomenclature would assist in the interpretation of the results.

There is a lack of description of the language backgrounds of the included subjects. How many came from each of the possible linguistic backgrounds? How did they differ in language exposure? This would be informative to evaluate the generalizability of the conclusions.

Only the result from the multiple transverse temporal gyri (2nd TTG) is analyzed in the replicated dataset. Only the association in the right hemisphere 2nd TTG is replicated but this is not reflected in the discussion or the conclusions. The positive correlation in the right TTG is thus not attempted to be replicated.

The replication dataset differed in more ways than the more frequent combination of English and German experience, as mentioned in the discussion. Specifically, the fraction of monolinguals was higher in the replication dataset and the samples came from different scanners. It would be better if the primary and replication datasets were more equally matched.

Even if the language experience and typological distance measures are a step in the right direction for correctly associating language exposure with cortical plasticity, it still is a measure that is insensitive to the intensity of the exposure. The consequences of this are not discussed.

Reviewer #3 (Public Review):

Summary:<br /> The study uses structural MRI to identify how the number, degree of experience, and phonemic diversity of language(s) that a speaker knows can influence the thickness of different sub-segments of the auditory cortex. In both a primary and replication sample of adult speakers, the authors find key differences in cortical thickness within specific subregions of the cortex due to either the age at which languages are acquired (degree of experience), or the diversity of the phoneme inventories carried by that/those language(s) (breadth of experience).

Strengths:<br /> The results are first and foremost quite fascinating and I do think they make a compelling case for the different ways in which linguistic experience shapes the auditory cortex.

The study uses a number of different measures to quantify linguistic experience, related to how many languages a person knows (taking into account the age at which each was learned) as well as the diversity of the phoneme inventories contained within those languages. The primary sample is moderately large for a study that focuses on brain-behaviour relationships; a somewhat smaller replication sample is also deployed in order to test the generality of the effects.

Analytic approaches benefit from the careful use of brain segmentation techniques that nicely capture key landmarks and account for vagaries in the structure of STG that can vary across individuals (e.g., the number of transverse temporal gyri varies from 1-4 across individuals).

Weaknesses:<br /> The specificity of these effects is interesting; some effects really do appear to be localized to the left hemisphere and specific subregions of the auditory cortex e.g., TTG. However because analyses only focus on auditory regions along the STG and MTG, one could be led to the conclusion that these are the only brain regions for which such effects will occur. The hypothesis is that these are specifically auditory effects, but that does make a clear prediction that non-auditory regions should not show the same sort of variability. I recognize that expanding the search space will inflate type-1 errors to a point where maybe it's impossible to know what effects are genuine. And the fine-grained nature of the effects suggests a coarse analysis of other cortical regions is likely to fail. So I don't know the right answer here. Only that I tend to wonder if some control region(s) might have been useful for understanding whether such effects truly are limited to the auditory cortex. Otherwise one might argue these are epiphenomenal or some hidden factor unrelated to auditory experience predicting that we'd also see them in the non-auditory cortex as well, either within or outside the brain's speech network(s).

The reason(s) why we might find a link between cortical thickness and experience is not fully discussed. The introduction doesn't really mention why we'd expect cortical thickness to be correlated (positively or negatively) with speech experience. There is some discussion of it in the Discussion section as it relates to the Pliatsikas' Dynamic Restructuring Model, though I think that model only directly predicts thinning as a function of experience (here, negative correlations). It might have less to say about observed positive correlations e.g., HG in the right hemisphere. In any case, I do think that it's interesting to find some relationship between brain morphology and experience but clearer explanations for why these occur could help, and especially some mention of it in the intro so readers are clearer on why cortical thickness is a useful measure.

One pitfall of quantifying phoneme overlap across languages is that what we might call a single 'phoneme', shared across languages, will, in reality, be realized differently across them. For instance, English and French may be argued to both use the vowel /u/ although it's realized differently in English vs. French (it's often fronted and diphthongized in many English speaker groups). Maybe the phonetic dictionaries used in this study capture this using a close phonetic transcription, but it's hard to tell; I suspect they don't, and in that case, the diversity measures would be an underestimate of the actual number of unique phonemes that a listener needs to maintain.

Discussion of potential genetic differences underlying the findings is interesting. One additional data point here is a study finding a relationship between the number of repeats of the READ1 (a factor of the DCDC2 gene) in populations of speakers, and the phoneme inventory of language(s) predominant in that population (DeMille, M. M., Tang, K., Mehta, C. M., Geissler, C., Malins, J. G., Powers, N. R., ... & Gruen, J. R. (2018). Worldwide distribution of the DCDC2 READ1 regulatory element and its relationship with phoneme variation across languages. Proceedings of the National Academy of Sciences, 115(19), 4951-4956.) Admittedly, that paper makes no claim about the cortical expression of that regulatory factor under study, and so more work needs to be done on whether this has any bearing at all on the auditory cortex. But it does represent one alternative account that does not have to do with plasticity/experience.

The replication sample is useful and a great idea. It does however feature roughly half the number of participants meaning statistical power is weaker. Using information from the first sample, the authors might wish to do a post-hoc power analysis that shows the minimum sample size needed to replicate their effect; given small effects in some cases, we might not be surprised that the replication was only partial. I don't think this is a deal breaker as much as it's a way to better understand whether the failure to replicate is an issue of power versus fragile effects.

Reviewer #1 (Public Review):

Summary:<br /> Very systematic generation of phosphosite-specific antisera to monitor FFA2 phosphorylation in native cells and tissues. Provides evidence that FFA2 phosphorylation is tissue-specific.

Strengths:<br /> Technical tour de force, rigorous experimental approaches taking advantage of wt and DREADD versions of FFA2 to make sure that ligand-and receptor-dependent phosphorylations are indeed specific to FFA2.

Weaknesses:<br /> In this reviewer's opinion, the only shortcoming is that the implications of tissue-selective phosphorylation barcoding remain unexplored. However, I understand that tool development is required before tools are used to provide insight into the functional outcomes of receptor regulation by phosphorylation. The study is a technical tour de force to generate highly valuable tools. I have no major criticisms but suggest adding an additional aspect to the discussion as specified below.

Arrestins are highly flexible and dynamic phosphate sensors. If two arrestins have to recognize 800 different phosphorylated GPCRs, is it possible that any barcode serves the same purpose: arrestin recognition followed by signal arrest and internalization? Because phosphorylation barcoding is linked to G protein-independent signaling, which is claimed by some but is experimentally unsupported, and because arrestins don't transduce receptor signals on their own (they only scaffold signaling components and shuttle receptors within cellular compartments), I would also include this option in the discussion, i.e. that the different barcodes are a way nature may have chosen to regulate the location of 800 GPCRs by only 2 arrestins.

Reviewer #2 (Public Review):

The strengths of this paper begin with the topic. Specifically, this approaches the question of how GPCR signals are directed to different outcomes under different conditions. There is rich complexity within this question; there are potentially billions of molecules that could interact with >800 human GPCRs and thousands of molecular effectors that may be activated. However, these outcomes are filtered through a small number of GPCR-interacting proteins that direct the signal.

Experimentally, strengths include the initial experimental controls employed in characterizing their ever-important antisera, on which their conclusions hinge. In showing strong agonist-dependent and phosphosite-dependent recognition, as well as the addition of GRK inhibitors and eventually an antagonist and phosphatase treatment, the authors substantiate the role of the antiserum in recognizing their intended motifs. When employed, those antisera overall give clear indications of differences across variables in immunoblots, and while the immunocytochemical studies are qualitative and at times not visually significantly different across all variables, they are in large part congruent with the results of the immunoblots and provide secondary supporting evidence for the author's major claims. One confounding aspect of the immunocytochemical images is the presence of background pThr306/pThr310, like in Figures 4C and 6A and B. In 4A and C, while the immunoblot shows a complete absence of pThr306/pThr310, Figure 4C's immuno image does not. In 6A and B, a similar presence of pThr306/pThr310 is seen in the vehicle image, which is not strikingly over-shown by the MOMBA-treated image. In addition, only Ser/Thr residues of the C-terminus were investigated, while residues of ICL3 have long been known to direct signaling in many GPCRs. Because of the presentations of sequences, it was not clear whether there were residues of ICL3 that have the possibility of being involved.

It may be possible and further testable to show whether the residues that maintain basal phosphorylation could also be tissue-specific, especially considering the presence of pThr306/pThr310 detection in both the Figure 6A immunoblot's vehicle lane (but not MOMBA lane). The aforementioned detection in the immunocytochemical vehicle image could support differential basal phosphorylation in the enteroendocrine cells. Should this be the case, it could have confounded the initial mass-spec screen wherein the Ser residues were basally active in that cell type, while in a distinct cell type that may not be the case. Lastly, should normalized quantification of these images be possible, it may help in clearing up these hard-to-compare visual images.

It is noted that aspects of the writing and presentation may lead to confusion for some readers, but this does not affect the overall significance of the work.

Nevertheless, in terms of the global goal of the authors, the indication of differences in phosphorylation states between tissues is still evident across the experiments. Accordingly, the paper is overall strongly well-researched, well-controlled, and the conclusions made by the authors are data-grounded and not overly extrapolated. Providing direct evidence for the tissue-based branch of the barcode hypothesis is both novel and significant for the field, and the paper leaves room for much more exciting research to be done in the area, opening the door for new questions and hypotheses.

Reviewer #3 (Public Review):

Summary:<br /> The authors generate and characterize two phosphospecific antisera for FFA2 receptor and claim a "bar code" difference between white fat and Peyers patches.

Strengths:<br /> The question is interesting and the antibody characterization is convincing.

Weaknesses:<br /> The mass spectrometry analysis is not convincing because the method is not quantitative (no SILAC, TMT, internal standards etc). Figure 1 shows single tryptic peptides with one and two phosphorylation fragmentations as claimed, but there is no data testing the abundance of these so the differences claimed between cell treatment conditions are not established.

The blot analysis cannot distinguish 296/7 but it does convincingly show an agonist increase. Can the authors clarify why the amount of constitutive phosphorylation is much higher in the example blot in Figure 2 than in Figure 3? It would be helpful to quantify this across more than one example, like in Figures 4 and 5 for tissue.

Compound 101 is shown in Figure 2 to block barrestin recruitment. I agree this suggests phosphorylation mediated by GRK2/3 but this is not tested. The new antibodies should be good for this so I don't understand why the indirect approach.

The conditions used to inhibit dephosphorylation are not specified, the method only says "phosphatase inhibitors". How do the authors know that low P at 306/7 in white fat is not a result of dephosphorylation during sample preparation? If these sites are GRK2/3 dependent (see above) then does adipose tissue lack this GRK?

Reviewer #1 (Public Review):

Summary:

A description of a modern protocol for cervical screening that likely could be used in any country of the world, based on self-sampling, extended HPV genotyping and AI-assisted visual inspection - which is probably the best available combination today.

Strengths:

Modern, optimised protocol, designed for global use. Innovative.

Weaknesses:

The protocol is not clear. I could not even find how many women were going to be enrolled, the timelines of the study, the statistical methods ("comparing" is not statistics) or the power calculations.

Tables 2 and 3 are too schematic - surely the authors must have an approximate idea of what the actual numbers are behind the green, red and yellow colors.

Figure 1 comparing screening and vaccination is somewhat misleading. They screen 20 birth cohorts but vaccinate only 5 birth cohorts. Furthermore, the theoretical gains of screening has not really been attained in any country in practice. Modelling can be a difficult task and the commentary does not provide any detail on how to evaluate what was done. It just seems unnecessary to attack vaccination as a motivation on why screening needs to be modernised.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the study protocol, structure and logic of the PAVE strategy. The PAVE study is a multicentric study to evaluate a novel cervical screen-triage-treat strategy for resource-limited settings as part of a global strategy to reduce cervical cancer burden. The PAVE strategy involves: 1) screening with self-sampled HPV testing; 2) triage of HPV-positive participants with a combination of extended genotyping and visual evaluation of the cervix assisted by deep-learning-based automated visual evaluation (AVE); and 3) treatment with thermal ablation or excision (Large Loop Excision of the Transformation Zone). The PAVE study has two phases: efficacy (2023-2024) and effectiveness (planned to begin in 2024-2025). The efficacy phase aims to refine and validate the screen-triage portion of the protocol. The effectiveness phase will examine implementation of the PAVE strategy into clinical practice.

Strengths and weaknesses:

The Pave Study develops and evaluates a novel strategy that combines HPV self-collection, that has been proven effective to increase screening coverage in different settings, with genotyping and Automated Visual Evaluation as triage. The proposed strategy combined three key innovations to improve an important step in the cervical cancer care continuum. If the strategy is effective it will contribute to enhancing cervical cancer prevention in low resource settings.

As the authors mentioned, despite the existence of effective preventive technologies (e.g., HPV vaccine and HPV test) translation of the HPV prevention methods has not yet occurred in many Low-Middle-Income Countries. So, in this context, new screen-triage-treat strategies are needed and if PAVE strategy were effective, it could be a landmark for cervical cancer prevention.

The PAVE Study is a solid and important study that is aimed to be carried out in nine countries and recruit tens of thousands of women. It is a study with a large and diverse sample that can provide useful information for the development of this new screen-triage-treat strategy. Another strength is the fact that the PAVE project is integrated into the screening activities placed in the selected countries that will allow to evaluate efficacy and effectiveness in real-word context.

The manuscript does not present results because its aim is to describe the study protocol, structure and logic of the PAVE strategy.

Phase 1 aims to evaluate the efficacy of the strategy. Methods are well described and are consistent with the study aims.

Phase 2 aims to evaluate the implementation of the PAVE strategy in clinical practice. The inclusion of implementation evaluation in this type of studies is an important milestone in the field of cervical cancer prevention. It has been shown that many strategies that have proven to be effective in controlled studies face barriers when they are implemented in real life. In that sense, the results of phase 2 are key to ensure the future implementation of the strategy.

However, some aspects of Phase 2 need to be clarified and extended. Although authors mentioned that implementation outcomes, such as acceptability and feasibility will be evaluated, more information is needed about method (i.e. qualitative/quantitative), data collection tools (i.e., survey, semi-structure interviews, focus groups, etc.) and frameworks that will be used to evaluate these implementation outcomes.

Reviewer #3 (Public Review):

Summary:

Despite being preventable and treatable, cervical cancer remains the second most common cause of cancer death globally. This cancer, and associated deaths, occur overwhelmingly in low- and middle-income countries (LMIC), reflecting a lack of access to vaccination, screening and treatment services. Cervical screening is the second pillar in the WHO strategy to eliminate cervical cancer as a public health problem and will be critical in delivering early gains in cervical cancer prevention as the impact of vaccination will not be realized for several decades. However, screening strategies implemented in high income countries are not feasible or affordable in LMICs. This ambitious multi-center study aims to address these issues by developing and systematically evaluating a novel approach to cervical screening. The approach, based on primary screening with self-collected specimens for HPV testing, is focused on optimizing triage of people in whom HPV is detected, so that sensitivity for the detection of pre-cancer and cancer is maximized while treatment of people without pre-cancer or cancer is minimized.

Strengths:

The triage proposed for this study builds on the authors' previously published work in designing the ScreenFire test to appropriately group the 13 detected genotypes into four channels and to develop automated visual evaluation (AVE) of images of the cervix, taken by health workers.

The move from mobile telephone devices to a dedicated device to acquire and evaluate images overcomes challenges previously encountered whereby updates of mobile phone models required retraining of the AVE algorithm.

The separation of the study into two phases, an efficacy phase in which screen positive people will be triaged and treated according to local standard of care and the performance of AVE will be evaluated against biopsy outcomes will be followed by the second phase in which the effectiveness, cost-effectiveness, feasibility and acceptability will be evaluated.

The setting in a range of low resource settings which are geographically well spread and reflective of where the global cancer burden is highest.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript the authors use ATAC-seq to find regions of the genome of rat embryonic striatal neurons in culture that show changes in regulatory element accessibility following stimulation by KCl-mediated membrane depolarization. The authors compare 1hr and 4hr transcriptomes to see both rapid and late response genes. When they look at ATAC-seq data they see no changes in accessibility at 1hr but strong changes at 4hr. The differentially accessible sites were enriched for the AP-1 site, suggesting regulation by Fos-Jun family members, and consistent with the requirement for IEG expression, anisomycin blocked the increase in accessibility. To test the functional importance of this regulation the authors focus on a putative enhancer 45kb upstream of the activity-induced gene encoding the neuromodulator dynorphin (Pdyn). To test the function of this region, the authors recruited CRISPRi to the site, which blocked KCL-dependent Pdyn induction, or CRISPRa, which selectively increased Pdyn expression in the absence of KCl. Finally the authors reanalyze other human and rat datasets to show cell-type specific function of this enhancer correlated to Pdyn expression.

The idea that stimuli that induce expression of Fos in neurons can change accessibility of regulatory elements bound from Fos has been shown before, but almost all the data are from hippocampal neurons so it is nice to see the different cell type used here. The most interesting part of the study is the identification of the Pdyn enhancer because of the importance of this gene product in the function of striatal neurons. Overall the conclusions appear to be well supported by the data.

Reviewer #2 (Public Review):

This study aims to characterize transcriptional and epigenetic activity-dependent striatal neuronal adaptations using rat primary cultures, a model still poorly characterized up to date. In addition, the authors aim to interrogate regulatory mechanisms that could modulate the expression of a highly-striatal enriched gene responding to neuronal activation in striatal neuronal cells, the Pdyn gene.

Among the major strengths of the article there is the generation of high quality neuronal RNA-seq and ATAC-seq data in rat striatal neuronal cells in basal level and upon neuronal activity, a experimental setup that has not been so characterized as other more common ones such as mouse hippocampal neuronal cells. In this model, the authors clearly demonstrate the need of protein translation to induce the transcriptional waves of late response genes. In addition, the functional characterization of an enhancer of the Pdyn gene might be of great interest for translational applications in which alterations of this gene might be occurring in neurological disorders.

On the other hand, the manuscript presents some limitations to be considered. One of the major points in this regard is that, at least in part, some of the conclusions reached by the study related to the induction of particular transcriptional programs upon neuronal activation, the changes in chromatin state, and the need of protein translation for proper induction of LRGs have been already previously described in the literature, affecting the novelty of the study. However, it is needed to be mentioned, that these previous studies were not conducted using the same model (rat striatal neurons), which can make some differences in the final outputs. The other major cautionary point in the study is the selection of the time point for distinguishing early versus late response genes, as the short difference in time and the overlap of part of the transcriptional signature between them suggest that the transcriptional waves are somehow partially overlapping (also probably in part because of the recurrent stimulation of the primary cultures with KCl), which could result in missing part of the late-response genes.

Despite this, the conclusions raised in the study are well supported by the data generated in it.

In summary, the study presents a useful set of transcriptomic and epigenomic data of activity-dependent striatal neuronal programs in rats, which will be of great use for the scientific community working in this not so well characterized model. In addition, the characterization of a Pdyn distal regulatory genomic region involved in its transcriptional regulation, both at basal levels and upon neuronal activation in this particular system, can present translational relevance for striatal disorders such as Huntington's disease or other neuropsychiatric disorders.

Reviewer #3 (Public Review):

This work contributes to the literature characterizing early and late waves of transcription and associated chromatin remodeling following neuronal depolarization, here in cultured embryonic striatum. While they find IEG transcription 1 h after depolarization, they find chromatin remodeling is slower (opening at the 4 h time point). While this is not the first paper to describe chromatin changes in response to neuronal activity, this paper ties previous findings all together in one place using novel sequencing analyses and visualizations. Previous work has found remodeling occurring at the 1 h time point, so the lack of differences at that early time point in the current study needs to be better understood and the "temporal decoupling" described by authors should be further explored. Differences may be due to chromatin at IEG regulatory regions already being open in embryonic tissue (here) vs generally more closed in adult tissue (previous), or due to previous studies using protocols to specifically silence neurons prior to activation. The authors next show that the chromatin remodeling that occurs at the late (4 h) stage is largely in putative regulatory regions of the genome (rather than gene bodies), and is dependent on translation, which validates and extends the prior literature. The authors then transition from genome-wide basic neuroscience to focus on a specific gene of interest, prodynorphin (Pdyn), and a putative enhancer they identify from their chromatin analysis. They target CRISPR-activating and -inhibiting complexes to the putative enhancer and demonstrate that accessibility of this locus is necessary and sufficient for Pdyn transcription. They then show that at least one PDYN enhancer is conserved from rodents to humans, and is only activity-regulated in human GABAergic but not glutamatergic neurons. Finally, the authors generate snATAC-seq and show Pdyn gene and enhancer activity is also cell-type-specific in rat striatum. The Pdyn work, in particular, is thorough and novel, and demonstrates a translational aspect of this work.

Joint Public Review:

In this study the authors confirm that one of the genes classified as essential in a Tn-mutagenesis study in A. baumannii is in fact an essential gene. It is also present in other closely related Gram negative bacteria and the authors designated it Aeg1.

The strength of the work is that it discovered that the depletion of Aeg1 leads to cell filamentation and that the requirement for Aeg1 can be suppressed by activation mutations in various cell division genes. These results suggest that Aeg1 plays an important role in cell division.

The weakness of the work is that it lacks convincing evidence to define Aeg1 place or role in the divisome assembly pathway. It is unclear what proteins are at the division site when Aeg1 is depleted and what proteins are required for Aeg1 to localize to the division site.

Reviewer #1 (Public Review):

In this manuscript the authors performed experiments and simulations which showed that substrate evaporation is the main driver of early construction in termites. Additionally, these experiments and simulations were designed taking into account several different works, so that the current results shine a light on how substrate evaporation is a sufficient descriptor of most of the results seen previously.

Through simulations and ingenious experiments the authors have shown how curvature is extremely correlated with evaporation, and therefore, how results coming from these 2 environmental factors can be explained through evaporation alone. The authors have continued to use their expertise of numerical simulations and a previously developed model for termite construction, to highlight and verify their findings. On my first pass of the manuscript I felt the authors were missing an experiment: an array of humidity probes to measure evaporation in the three spatial dimensions and over time. Technologically such an experiment is not out of reach, but the author's alternative (a substrate made with a saline solution and later measuring the salt deposits on the surface) was a very ingenious low tech solution to the problem.

The authors agree that future experiments should tackle finely controlled humidity levels and curvature in order to have a more quantitative measure termite behaviour, but the work done so far is more than sufficient to justify their current claims.

The results presented here are so far the best attempt on characterizing multiple cues that induce termite construction activity, and that possibly unifies the different hypothesis presented in the last 8 years into a single factor. More importantly, even if these results come from different species of termites than some of the previous works, they are relatable and seem to be mostly consistent, improving the strength of the author's claims.

Reviewer #2 (Public Review):

The revised paper addresses most of my major comments and concerns. The authors have added more detail explaining their model, they have added more background information, citations, and discussion for termite humidity sensing capabilities. With these modifications, this paper now provides a convincing presentation of valuable results of the drivers of nest construction for one termite species, and they briefly discuss possible relevance to other termite species. However, the authors have not yet addressed how their results may be important outside the field of termite nest construction. I could imagine the significance of the paper being elevated to important if there is a broader discussion about the impact of this work, e.g., the relevance of the results, the approach, and/or next steps to related fields outside of termite nest construction. Similarly, on a related note, as someone not directly in the field of termite nest construction but wanting to understand the system (and the results) presented here in a broader context, I found the additional information about species and natural habitat very helpful and interesting, though I was rather disappointed to find it relegated to supplementary material where most readers will not see it.

Joint Public Review:

This concise review provides a clear and instructive picture of the state-of-the-art understanding of protein kinases' activity and sets of approaches and tools to analyse and regulate it.

Three major parts of the work include: methods to map allosteric communications, tools to control allostery, and allosteric regulation of protein kinases. The work provides an important and timely view of the current status of our understanding of the function of protein kinases and state-of-the-art methods to study its allosteric regulation and to develop allosteric approaches to control it.

Reviewer #1 (Public Review):

This work describes a structural analysis of the tripartite HipBST toxin-antitoxin (TA) system, which is related to the canonical two-component HipBA system composed of the HipA serine-threonine kinase toxin and the HipB antitoxin. The crystal structure of the kinase-inactive HipBST complex of the Enteropathogenic E. coli O127:H6 was solved and revealed that HipBST forms a hetero-hexameric complex composed of a dimer of HipBST heterotrimers that interact via the HipB subunit. The HipS antitoxin shows a structural resemblance to HipA N-terminal region and the HipT toxin represents to the core kinase domain of HipA, indicating that in HipBST the hipA toxin gene was likely split in two genes, namely hipS and hipT.<br /> -The structure also reveals a conserved and essential Trp residue within the HipS antitoxin, which likely prevents the conserved "Gly-rich loop" of HipT from adopting an inward conformation needed for ATP binding. This work also shows that the regulating Gly-rich loop of the HipT toxin contains conserved phosphoserine residues essential for HipT toxicity that are key players within the HipT active site interacting network and which likely control antitoxin binding and/or activity.

Strengths:

The manuscript is well written and the experimental work well executed. It shows that major features of the classical two-component HipAB TA system have somehow been rerouted in the case of the tripartite HipBST. This includes the N-terminal domain of the HipA toxin, which now functions as bona fide antitoxin, and the partly relegated HipB antitoxin, which could only function as a transcription regulator. In addition, this work shows a new mode of inhibition of a kinase toxin and highlights the impact of the phosphorylation state of key toxin residues in controlling the activity of the antitoxin.

Weaknesses:

The authors have convincingly addressed the previously raised weaknesses in their revised version of the manuscript.

Reviewer #2 (Public Review):

The work by Bærentsen et al., entitled "Structural basis for regulation of a tripartite toxin-antitoxin system by dual phosphorylation" deals with the structural aspects of the control of the hipBST TA operon, the role of auto-phosphorylation in the activation and neutralisation of the enzyme and the direct effects of HipS and HipB in neutralisation. This is a follow-up to the Vang Nielsen et al., and Gerdes et al., papers from the same authors on this very unique TA module, that brings forth a thorough and well written dissection of an unusually complex regulatory system.

Reviewer #1 (Public Review):

The authors develop reporter constructs in E. coli where gene expression, presumably translation, is repressed by MSI-1. This is a potentially useful tool for synthetic biologists, with the advantage over transcriptional regulation that one gene in an operon could be targeted. That being said, an important caveat of translational regulation that is not addressed in the manuscript is the potential for downstream effects on RNA stability and/or transcription termination. The authors' MSI-1-regulated reporter constructs could also be useful for mechanistic studies of MSI-1.

The author's initial construct design led to only weak regulation by MSI-1, presumably because the MSI-1 binding sites were not suitably positioned to repress translation initiation. A more rationally designed construct led to considerably greater repression. One weakness of the paper is that the authors did not use their redesigned construct that is more strongly repressed to demonstrate allosteric regulation by oleic acid using a comparable assay (e.g., flow cytometry) to that used in other experiments. The potential for allosteric regulation is a major strength of the MSI-1 system, so this is a significant gap. Similarly, the authors use the weakly regulated constructs to assess the effect of MSI-1 binding site mutations and for their mathematical modeling; these experiments would be better suited to the more strongly regulated construct.

Reviewer #2 (Public Review):

Summary:<br /> Dolcemascolo and colleagues describe the use of the mammalian RNA-binding protein Musashi-1 (MSI-1) to implement translational regulation systems in E. coli. They perform detailed in vitro studies of MSI-1 and its binding to different RNA sequences. They provide compelling evidence of the effectiveness of the regulatory system in multiple circuits using different mRNA sequence motifs. They harness allosteric inhibition of MSI-1 by omega-9 monounsaturated fatty acids to demonstrate a fatty-acid-responsive circuit in E. coli.

Strengths:<br /> The experimental results are compelling and the characterization of the binding between MSI-1 and different RNA sequences is thorough and performed via multiple complementary techniques. Several new useful circuit components are demonstrated.

Weaknesses:<br /> MSI-1 provides 8.6-fold downregulation of sfGFP with an optimized mRNA sequence. In some applications, a larger degree of repression may be required.

Reviewer #3 (Public Review):

Summary:<br /> In this work, the authors co-opt the RRM-binding protein Musashi-1 to act as a translational repressor. The novelty of the work is in the adoption of the allosteric RRM protein Musashi-1 into a translational reporter and the demonstration that RRM proteins, which are ubiquitous in eukaryotic systems, but rare in prokaryotic ones, may act effectively as post-translational regulators in E. coli. The extent of repression achieved by the best design presented in this work is not substantially improved compared to other synthetic regulatory schemes developed for E. coli, even those that similarly regulate translation (eg. native PP7 repression is approximately 10-fold, Lim et al. J. Biol. Chem. 2001 276:22507-22513). Furthermore, the mechanism of regulation is not established due to missing key experiments. The work would be of broader interest if the allosteric properties of Musashi-1 were more effective in the context of regulation. Unfortunately, the authors do not demonstrate that fatty acids can completely de-repress expression in the experimental system used for most of their assays, nor do they use this ability in their provided application (NIMPLY gate).

Strengths:<br /> The first major achievement of this work is the demonstration that a eukaryotic RRM protein may be used to post-transcriptionally regulate expression in bacteria. In my limited literature search, this appears to be the first engineering attempt to design an RBP to directly regulate translation in E. coli, although engineered control of translation via other approaches including alterations to RNA structure or via trans-acting sRNAs have been previously described (for review see Vigar and Wieden Biochim Biophys. Acta Gen. Subj. 2017, 1861:3060-3069). Additionally, several viral systems (e.g. MS2 and PP7) have been directly co-opted to work in a similar fashion in the past (utilized recently in Nguyen et al. ACS Synthetic Biol 2022, 11:1710-1718).

The second achievement of this work is the demonstration that the allosteric regulation of Musashi-1 binding can be utilized to modulate the regulatory activity. However, the liquid culture demonstration (Suppl. Fig 8) shows that this is not a very effective switch, with de-repressed reporter activity showing substantial change but not approaching un-repressed activity. This effect is stronger when colonies are grown on a solid medium (Fig. 5).

Weaknesses:<br /> In this work, the authors codon optimize the mouse Musashi-1 coding sequence for expression in E. coli and demonstrate using an sfGFP reporter that an engineered Musashi-1 binding site near the translational start site is sufficient to enable a modest reduction in reporter gene expression. The authors postulate that the reduction in expression due to inhibition of ribosome translocation along the transcript (lines 134/135), as an expression of a control transcript (mScarlet) driven by the same promoter (Plac) but without the Musashi-1 recognition site does not demonstrate the same repression. However, the situation could be more complex. Other possibilities include inhibition of translation initiation rather than elongation, as well as accelerated mRNA decay of transcripts that are not actively translated. The authors do not present any measurements of sfGFP mRNA levels.

In subsequent sections of the work, the authors create a series of point mutations to assess RNA-protein binding and assess these via both a sfGFP reporter and in vitro binding assays (switchSENSE). Ultimately, it is difficult to fully rationalize and interpret the behavior of these mutants in the context provided. The authors do identify a relationship between equilibrium constant (1/KD) and fold-repression. However, it is not clear from the narrative why this relationship should exist. Fold-repression is one measure of regulator efficacy, but it is an indirect measure determined from unrepressed and repressed expression. It is not clear why unrepressed expression (in the absence of the protein) is expected to be a function of the equilibrium constant.

Subsequent rational redesign of the Musashi-1 binding sequence to produce three alternative designs shows that fold-repression may be improved to approximately 8.6-fold. However, the rationalization of why the best design (red3) achieves this increase based on either the extensive modelling or in vitro measured binding constants is not well articulated. Furthermore, this extent of regulation is approximately that which can be achieved from the PP7 system with its native components (Lim et al. J. Biol. Chem. 2001 276:22507-22513).

The application provided for this regulator (NIMPLY gate), is not an inherently novel regulatory paradigm, and it does not capitalize on the allosteric properties of Musashi-1, but rather treats Musashi-1 as a non-allosteric component of a regulatory circuit.

This whole document feels like it could have been written more compactly.

Reviewer #1 (Public Review):

Muscle models are important tools in the fields of biomechanics and physiology. Muscle models serve a wide variety of functions, including validating existing theories, testing new hypotheses, and predicting forces produced by humans and animals in health and disease. This paper attempts to provide an alternative to Hill-type muscle models that includes contributions of titin to force enhancement over multiple time scales. Due to the significant limitations of Hill-type models, alternative models are needed and therefore the work is important and timely.

The effort to include a role for titin in muscle models is a major strength of the methods and results. The results clearly demonstrate the weaknesses of Hill models and the advantages of incorporating titin into theoretical treatments of muscle mechanics. Another strength is to address muscle mechanics over a large range of time scales. Weaknesses include the decision to use a MTU model to simulate experiments from single muscle fibers, and failure to systematically address the limitations of the model, including equations for activation dynamics with no length dependence. It would also be useful for readers if the authors provided a discussion of the types of data that can be simulated using the model, along with potential pitfalls and how to determine model parameters.

The authors succeed in demonstrating the need to incorporate titin in muscle models. However, it remains unclear whether it will be practical for others to use this particular model for different types of data. Several ad hoc modifications were described in the paper, and the degree to which the model requires parameter optimization for different muscles, preparations and experiment types is also unclear.

Reviewer #2 (Public Review):

This model of skeletal muscle includes springs and dampers which aim to capture the effect of crossbridge and titin stiffness during the stretch of active muscle. While both crossbridge and titin stiffness have previously been incorporated, in some form, into models, this model is the first to simultaneously include both. The authors suggest that this will allow for the prediction of muscle force in response to short-, mid- and long-range stretches. All these types of stretch are likely to be experienced by muscle during in vivo perturbations, and are known to elicit different muscle responses. Hence, it is valuable to have a single model which can predict muscle force under all these physiologically relevant conditions. In addition, this model dramatically simplifies sarcomere structure to enable this muscle model to be used in multi-muscle simulations of whole-body movement.

In order to test this model, its force predictions are compared to 3 sets of experimental data which focus on short-, mid- and long-range perturbations, and to the predictions of a Hill-type muscle model. The choice of data sets is excellent and provide a robust test of the model's ability to predict forces over a range of length perturbations. However, I find the comparison to a Hill-type muscle model to be somewhat limiting. It is well established that Hill-type models do not have any mechanism by which they can predict the effect of active muscle stretch. Hence, that the model proposed here represents an improvement over such a model is not a surprise. Many other models, some of which are also simple enough to be incorporated into whole-body simulations, have incorporated mechanistic elements which allow for the prediction of force responses to muscle stretch. It is not clear from the results presented here that this model would outperform such models.

The paper begins by outlining the phenomenological vs mechanistic approaches taken to muscle modelling, historically. It appears, although is not directly specified, that this model combines these approaches. A somewhat mechanistic model of the response of the crossbridges and titin to active stretch is combined with a phenomenological implementation of force-length and force-velocity relationships. This combination of approaches may be useful in improving the accuracy of predictions of muscle models and whole-body simulations, which is certainly a worthy goal. However, it also may limit the insight that can be gained. For example, it does not seem that this model could reflect any effect of active titin properties on muscle shortening. In addition, it is not clear to me, either physiologically or in the model, what drives the shift from the high stiffness in short-range perturbations to the somewhat lower stiffness in mid-range perturbations.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public Review):

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

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

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

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

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

Reviewer #1 (Public Review):

Aiming at the problem that Staphylococcus aureus can cause apoptosis of macrophages, the author found and verified that drug (R)-DI-87 can inhibit mammalian deoxycytidine kinase (dCK), weaken the killing effect of staphylococcus aureus on macrophages, and reduce the apoptosis of macrophages. And increase the infiltration of macrophages to the abscess, thus weakening the damage of Staphylococcus aureus to the host. This work provides new insights and ideas for understanding the effects of Staphylococcus aureus infection on host immunity and discovering corresponding therapeutic interventions.

The logic of the study is commendable, and the design is reasonable.

Some data related to the conclusion of the paper need to be supplemented, and some experimental details need to be described.

Reviewer #2 (Public Review):

Summary:

In this study, Winstel and colleagues test if the deoxycytidine kinase inhibitor, (R)-DI-87 provides therapeutic benefit during infection with Staphylococcus aureus. The premise behind the current work is a series of prior studies that found that S. aureus can disable functional immune clearance by generating NET-derived deoxyribonucleosides to induce macrophage apoptosis via purine salvage. Here, the authors use in vitro and in vivo experiments with (R)-DI-87 to demonstrate that inhibition of deoxycytidine kinase prevents S. aureus-induced deoxyribonucleoside-mediated macrophage cell death, to bolster immune cell function and promote more effective clearance during infection. The authors conclude that (R)-DI-87 represents and potentially important Host-Directed Therapy (HDT) with good potential to promote natural clearance of infection without targeting the bacterium. Overall, the study represents an important next step in the exploration of purine salvage and deoxyribonucleoside toxicity as a targetable pathway to bolster infection clearance and provides early-stage evidence of the therapeutic potential of (R)-DI-87 during S. aureus infection.

Strengths:

The study has several strengths that support its conclusions:<br /> 1. Well-controlled in vitro studies that firmly establish (R)-DI-87 is capable of blocking deoxyribonucleoside-mediated apoptosis of immune cell lines and primary cells.<br /> 2. Solid evidence to support that administration of (R)-DI-87 can have therapeutic benefits during infection (reduced number of abscesses and reduced CFU).<br /> 3. Controls included to ascertain the degree to which (R)-DI-87 might have secondary effects on immune cell distribution.<br /> 4. Controls included to ascertain whether or not (R)-DI-87 has intrinsic antibacterial properties.

Weaknesses:

However, there are several important weaknesses related to the rigor of the research and the conclusions drawn. The most relevant weaknesses noted by this reviewer are:

1. Drawing firm conclusions about the therapeutic potential of (R)-DI-87 using only S. aureus strain Newman, a methicillin-susceptible S. aureus, that while a clinical isolate is not clearly representative of the strains of S. aureus causing infection in hospitals and communities. Newman also harbors an unusual mutation in a regulator that dramatically changes virulence factor gene expression. While the data with Newman remains valuable, the absence of consideration of other strains, including MRSA, makes it more difficult to support the relatively broad conclusions about therapeutic potential made by the authors.

2. In vitro (R)-DI-87 efficacy studies with dAdo and dGuo are strong, however, the authors do not test the in vitro efficacy of (R)-DI-87 using S. aureus. They have done this type of work in prior studies (See doi: 10.1073/pnas.1805622115 - Figure 5). If included it would greatly strengthen their argument that (R)-DI-87 is directly affecting the S. aureus --> Nuclease --> AdsA macrophage-killing pathway. Without it, the evidence provided remains indirect, and several conclusions may be overstated.

3. Caspase-3 immunoblot experiments seem to suggest an alternative conclusion to what was made by the authors. They point out that Caspase-3 cleavage does not occur upon treatment with (R)-DI-87. However, the data seem to argue that there is almost no caspase-3 present in (R)-DI-87 treated cells (cleaved or uncleaved). Might this suggest that caspase-3 is not even produced when cells are not experiencing deoxyribonucleoside toxicity? Perhaps the authors could reconsider the interpretation of this data.

4. There are some concerns over experimental rigor and clarity of the experimental design in the methods. The most important points noted by this reviewer are included here. (a.) There is no description of the number of replicates or representation of the Western blots and no uncropped blots are provided. (b.) the methods describing the treatment conditions for in vivo studies are not sufficiently clear. For example, it is hard to tell when (R)-DI-87 is first administered to mice. Is it immediately before the infection, immediately after, or at the same time? This has important implications for interpreting the results in terms of therapeutic potential. (c.) There are several statements made that (R)-DI-87 does not have a negative impact on the mice however, it is not sufficiently clear that the studies conducted are sufficient to make this broader claim that (R)-DI-87 has no impact on the animal, except as it relates to the distribution of immune cells, which is directly tested. (d.) there are no quantitative measures of apoptosis or macrophage infiltration, which impacts the rigor of these imaging experiments. (d.) only female mice are used in the in vivo studies. There is no justification provided for this choice; however, the rigor of the study design and the ability to draw conclusions about therapeutic potential is impacted in the absence of consideration of both sexes.

5. Animal studies show significant disease burden (CFU) even after administration of (R)-DI-87. Given the absence of robust clearance of infection, the author's claims read as an overstatement of the data. The authors may wish to reframe their conclusions to better highlight the potential benefit of this therapy at reducing severe disease but also to point out relevant limitations, especially considering that it does not lead to clearance in this model. In general, the consideration of the limitations of the proposed therapeutic approach, as uncovered by the data, is not present. A more nuanced consideration of the data and its interpretations, including both strengths and limitations, would greatly help to frame the study.

Reviewer #2 (Public Review):

Summary:

Zhang et al investigated the biophysical mechanism of potassium-mediated chemotactic behavior in E coli. Previously, it was reported by Humphries et al that the potassium waves from oscillating B subtilis biofilm attract P aeruginosa through chemotactic behavior of motile P aeruginosa cells. It was proposed that K+ waves alter PMF of P aeruginosa. However, the mechanism was this behaviour was not elusive. In this study, Zhang et al demonstrated that motile E coli cells accumulate in regions of high potassium levels. They found that this behavior is likely resulting from the chemotaxis signalling pathway, mediated by an elevation of intracellular pH. Overall, a solid body of evidence is provided to support the claims. However, the impacts of pH on the fluorescence proteins need to be better evaluated. In its current form, the evidence is insufficient to say that the fluoresce intensity ratio results from FRET. It may well be an artefact of pH change. Nevertheless, this is an important piece of work. The text is well written, with a good balance of background information to help the reader follow the questions investigated in this research work.

In my view, the effect of pH on the FRET between CheY-eYFP and CheZ-eCFP is not fully examined. The authors demonstrated in Fig. S3 that CFP intensity itself changes by KCl, likely due to pH. They showed that CFP itself is affected by pH. This result raises a question of whether the FRET data in Fig3-5 could result from the intensity changes of FPs, but not FRET. The measured dynamics may have nothing to do with the interaction between CheY and CheZ. It should be noted that CFP and YFP have different sensitivities to pH. So, the measurement is likely confounded by the change in intracellular pH. Without further experiments to evaluate the effect of pH on CFP and YFP, the data using this FRET pair is inconclusive.

The data in Figure 1 is convincing. It would be helpful to include example videos. There is also ambiguity in the method section for this experiment. It states 100mM KCl was flown to the source channel. However, it is not clear if 100 mM KCl was prepared in water or in the potassium-depleted motility buffer. If KCl was prepared with water, there would be a gradient of other chemicals in the buffer, which confound the data.

The authors show that the FRET data with both KCl and K2SO4, and concluded that the chemotactic response mainly resulted from potassium ions. However, this was only measured by FRET. It would be more convincing if the motility assay in Fig1 is also performed with K2SO4.

Methods:

- Please clarify the promotes used for the constitutive expression of FliCsticky and LacI.<br /> - Fluorescence filters and imaging conditions (exposure time, light intensity) are missing.<br /> - Please clarify if the temperature was controlled in motility assays.<br /> - L513. It is not clear how theta was selected. Was theta set to be between 0 and pi? If not, P(theta) can be negative?<br /> - Typo in L442 (and) and L519 (Koff)

Reviewer #1 (Public Review):

Summary:

This paper shows that E. coli exhibits a chemotactic response to potassium by measuring both the motor response (using a bead assay) and the intracellular signaling response (CheY phosporylation level via FRET) to step changes in potassium concentration. They find increase in potassium concentration induces a considerable attractant response, with an amplitude larger than aspartate, and cells can quickly adapt (but possibly imperfectly). The authors propose that the mechanism for potassium response is through modifying intracellular pH; they find both that potassium modifies pH and other pH modifiers induce similar attractant responses. It is also shown, using Tar- and Tsr-only mutants, that these two chemoreceptors respond to potassium differently. Tsr has a standard attractant response, while Tar has a biphasic response (repellent-like then attractant-like). Finally, the authors use computer simulations to study the swimming response of cells to a periodic potassium signal secreted from a biofilm and find a phase delay that depends on the period of oscillation.

Strengths:

The finding that E. coli can sense and adapt to potassium signals and the connection to intracellular pH is quite interesting and this work should stimulate future experimental and theoretical studies regarding the microscopic mechanisms governing this response. The evidence (from both the bead assay and FRET) that potassium induces an attractant response is convincing, as is the proposed mechanism involving modification of intracellular pH.

Weaknesses:

The authors show that changes in pH impact fluorescent protein brightness and modify the FRET signal; this measurement explains the apparent imprecise adaptation they measured. However, this effect reduces confidence in the quantitative accuracy of the FRET measurements. For example, part of the potassium response curve (Fig. 4B) can be attributed to chemotactic response and part comes from the pH modifying the FRET signal. Measuring the full potassium response curve of the no-receptor mutants as a control would help quantify the true magnitude of the chemotactic response and the adaptation precision to potassium.

The measured response may also be impacted by adaptation. For other strong attractant stimuli, the response typically shows a low plateau before it recovers (adapts). However, in the case of Potassium, the FRET signal does not have an obvious plateau following the stimuli. Do the authors have an explanation for that? One possibility is that the cells may have already partially adapted when the response reaches its minimum, which could indicate a different response and/or adaptation dynamics from that of a regular chemo-attractant? In any case, directly measuring the response to potassium in mutants without adaptation enzymes (CheR, CheB) and with the receptors in different methylation levels would shed more light on the problem.

There seems to be an inconsistency between the FRET and bead assay measurements, the CW bias shows over-adaptation, while the FRET measurement does not. The small hill coefficient of the potassium response curve and the biphasic response of the Tar-only strain, while both very interesting, require further explanation since these are quite different than responses to more conventional chemoattractants.

Reviewer #2 (Public Review):

Summary:

Guan and colleagues address the question of how a single neuroblast produces a defined number of progeny, and what influences its decommissioning. The focus of the experiments are two well-studied RNA-binding proteins: Imp and Syp. The Authors find that these factors play an important role in determining the number of neurons in their preferred model system of VNC motor neurons coming from a single lineage (LinA/15) by separate functions taking place at specific stages of development of this lineage: influencing the life-span of the LinA neuroblast to control its timely decommissioning and functioning in the Late-born post-mitotic neurons to influence cell death after the appropriate number of progeny is generated. The post-mitotic role of Imp/Syp in regulating programmed-cell death (PCD) is also correlated with a specific code of key transcription factors that are suspected to influence neuronal identity, linking the fate of neuronal survival with its specification. This paper addresses a wide scope of phenotypes related to the same factors, thus providing an intriguing demonstration of how the nervous system is constructed by context-specific changes in key developmental regulators.

The bulk of conclusions drawn by the authors are supported by careful experimental evidence, and the findings are a useful addition to an important topic in developmental neuroscience.

Strengths:

A major strength is the use of a genetic labeling tool that allows the authors to specifically analyze and manipulate one neuronal lineage. This allows for simultaneous study of both the progenitors and post-mitotic progeny. As a result the paper conveys a lot of useful information for this particular neuronal lineage. Furthermore addressing the association of cell fate specification, taking advantage of this lab's extensive prior work in the system, with developmentally-regulated programmed cell-death is an important contribution to the field.<br /> Beyond Imp/Syp, additional characterization of this model system is provided in characterizing a previously unrecognized death of a hemilineage in early-born neurons.

Weaknesses:

The main observations that distinguish this study from others that have investigated Imp/Syp in the fly nervous system is the role played in late-born post-mitotic neurons to regulate programmed cell-death. This is an important and plausible (based on the presented findings) newly discovered role for these proteins. However the precision of experiments is not particularly strong, which limits the authors claims. The genetic strategy used to manipulate Imp/Syp or the TF code appears to be done throughout the entire lineage, or all neuronal progeny, and not restricted to only the late born cells. Can the authors rule out survival of the early born hemi-lineage normally fated to die? Therefore statements such as this: To further investigate this possibility, we used the MARCM technique to change the TF code<br /> of last-born MNs without affecting the expression of Imp and Syp<br /> should be qualified to specify that the result is obtained by misexpressing these factors throughout the entire lineage.

The authors make an observation that differs from other systems in which Imp/Syp have been studied: that the expression of the two proteins appears to be independent and not influenced by cross-regulation. However there is a lack of investigation as to what effect this may have on how Imp/Syp regulate temporal identity. A key implication of the previously observed cross-regulation in the fly mushroom body is that the ratio of Imp/Syp could change over the life of the NB which would permit different neuronal identities. Without cross-regulation, do the authors still observe a gradient in the expression pattern of time? Because the data is presented with Imp and Syp stained in different brain samples, and without quantification across different stages, this is unclear. The authors use the term 'gradient' but changes in levels of these factors are not evident from the presented data.

Reviewer #1 (Public Review):

This study addresses the temporal patterning of a specific Drosophila CNS neuroblast lineage, focusing on its larval development. They find that a temporal cascade, involving the Imp and Syb genes changes the fate of one daughter cell/branch, from glioblast (GB) to programmed cell death (PCD), as well as gates the decommissioning of the NB at the end of neurogenesis.

Reviewer #3 (Public Review):

This study by Guan and co-workers focuses on a model neuronal lineage in the developing Drosophila nervous system, revealing interesting aspects about: a) the generation of supernumerary cells, later destined for apoptosis; and, b) new insights into the mechanisms that regulate this process. The two RNA-binding proteins, Imp and Syp, are shown to be expressed in temporally largely complementary patterns, their expression defining early vs later born neurons in this lineage, and thus also regulating the apoptotic elimination. Moreover, neuronal 'fate' transcription factors that are downstream of Imp and signatures of early-born neurons, can also be sufficient to convert later born cells to an earlier 'fate', including survival.

The authors provide solid evidence for most of their statements, including the temporal windows during which the early and the later-born motoneurons are generated by this model lineage, how this relates to patterns of cell death by apoptosis and that mis-expression of early-born transcription factors in later-born cells can be sufficient to block apoptosis (part of, and perhaps indicative of the late-born identity).

Other studies have previously outlined analogous, mutually antagonistic roles for Imp and Syp during nervous system development in Drosophila, in different parts and at different stages, with which the working model of this study aligns.

Overall, this study adds to and extends current working models and evidence on the developmental mechanisms that underlie temporal cell fate decisions.

Reviewer #1 (Public Review):

Despite numerous studies on quinidine therapies for epilepsies associated with GOF mutant variants of Slack, there is no consensus on its utility due to contradictory results. In this study Yuan et al. investigated the role of different sodium selective ion channels on the sensitization of Slack to quinidine block. The study employed electrophysiological approaches, FRET studies, genetically modified proteins and biochemistry to demonstrate that Nav1.6 N- and C-tail interacts with Slack's C-terminus and significantly increases Slack sensitivity to quinidine blockade in vitro and in vivo. This finding inspired the authors to investigate whether they could rescue Slack GOF mutant variants by simply disrupting the interaction between Slack and Nav1.6. They find that the isolated C-terminus of Slack can reduce the current amplitude of Slack GOF mutant variants co-expressed with Nav1.6 in HEK cells and prevent Slack induced seizures in mouse models of epilepsy. This study adds to the growing list of channels that are modulated by protein-protein interactions, and is of great value for future therapeutic strategies.

Reviewer #2 (Public Review):

This is a very interesting paper about the coupling of Slack and Nav1.6 and the insight this brings to the effects of quinidine to treat some epilepsy syndromes.

Slack is a sodium-activated potassium channel that is important to hyperpolarization of neurons after an action potential. Slack is encoded by KNCT1 which has mutations in some epilepsy syndromes. These types of epilepsy are treated with quinidine but this is an atypical antiseizure drug, not used for other types of epilepsy. For sufficient sodium to activate Slack, Slack needs to be close to a channel that allows robust sodium entry, like Nav channels or AMPA receptors. but more mechanistic information is not available. Of particular interest to the authors is what allows quinidine to be effective in reducing Slack.

In the manuscript, the authors show that Nav, not AMPA receptors, are responsible for Slack's sensitization to quinidine blockade, at least in cultured neurons (HeK293, primary cortical neurons). Most of the paper focuses on the evidence that Nav1.6 promotes Slack sensitivity to quinidine.

Reviewer #3 (Public Review):

Yuan et al., set out to examine the role of functional and structural interaction between Slack and NaVs on the Slack sensitivity to quinidine. Through pharmacological and genetic means they identify NaV1.6 as the privileged NaV isoform in sensitizing Slack to quinidine. Through biochemical assays, they then determine that the C-terminus of Slack physically interacts with the N- and C-termini of NaV1.6. Using the information gleaned from the in vitro experiments the authors then show that virally-mediated transduction of Slack's C-terminus lessens the extent of SlackG269S-induced seizures. These data uncover a previously unrecognized interaction between a sodium and a potassium channel, which contributes to the latter's sensitivity to quinidine.

Reviewer #1 (Public Review):

Summary:<br /> In this work the authors provide evidence that impairment of cell envelope protein homeostasis through blocking the machinery for disulfide bond formation restores the efficacy of antibiotics including beta-lactam drugs and colistin against AMR in Gram-negative bacteria.

Strengths:

The authors employ a thorough approach to showcase the restoration of antibiotic sensitivity through inhibition of the DSB machinery, including the evaluation of various antibiotics on both normal and Dsb-deficient pathogenic bacteria (i.e. Pseudomonas and Stenotrophomonas). The authors corroborate these findings by employing Dsb inhibitors in addition to delta dsbA strains. The methodology is appropriate and includes measuring MICs as well as validating their observations in vivo using the Galleria model.

Weaknesses:

The study would benefit from presenting raw data in some cases, such as MIC values and SDS-PAGE gels, by clarifying the number of independent experiments used, as well as further clarification on statistical significance for some of the data.

Reviewer #3 (Public Review):

Summary:<br /> In the face of emerging antibiotic resistance and slow pace of drug discovery, strategies that can enhance the efficacy of existing clinically used antibiotics are highly sought after. In this manuscript, through genetic manipulation of a model bacterium (Escherichia coli) and clinically isolated and antibiotic resistant strains of concern (Pseudomonas, Burkholderia, Stenotrophomonas), an additional drug target to combat resistance and potentiate existing drugs is put forward. These observations were validated in both pure cultures, mixed bacterial cultures and in worm models. The drug target investigated in this study appears to be broadly relevant to the challenge posed by lactamases enzyme that render lactam antibiotics ineffective in the clinic. The compounds that target this enzyme are being developed already, some of which were tested in this study displaying promising results and potential for further optimization by medicinal chemists.

Strengths:<br /> The work is well designed and well executed and targets an urgent area of research with the unprecedented increase in antibiotic resistance.

Weaknesses:<br /> The impact of the work can be strengthened by demonstrating increased efficacy of antibiotics in mice models or wound models for Pseudomonas infections. Worm models are relevant, but still distant from investigations in animal models.

Reviewer #2 (Public Review):

Summary:

This work by Kadeřábková et al. demonstrates the importance of a specific protein folding system to effectively folding β-lactamase proteins, which are responsible for resistance to β-lactam antibiotics, and shows that inhibition of this system sensitize multidrug-resistant pathogens to β-lactam treatment. In addition, the authors extend these observations to a two-species co-culture model where β-lactamases provided by one pathogen can protect another, sensitive pathogen from β-lactam treatment. In this model, disrupting the protein folding system also disrupted protection of the sensitive pathogen from antibiotic killing. Overall, the data presented provide a solid foundation for subsequent investigations and development of inhibitors for β-lactamases and other resistance determinants. This and similar strategies may have particular application to polymicrobial contexts, but the present state of knowledge regarding the existence and clinical effects of microbial interactions in disease, both specifically regarding S. maltophilia and P. aeruginosa as well as generally, is significantly overstated.

Strengths:

The authors use clear and reliable molecular biology strategies to show that β-lactamase proteins from P. aeruginosa and Burkholderia species, expressed in E. coli in the absence of the dsbA protein folding system, are variably less capable of resisting the effects of different β-lactam antibiotics compared to the dsbA-competent parent strain (Figure 1). The appropriate control is included in the supplemental materials to demonstrate that this effect is specifically dependent on dsbA, since complementing the mutant with an intact dsbA gene restores antibiotic resistance (Figure S1). The authors subsequently show that this lack of activity can be explained by significantly reduced protein levels and loss-of-function protein misfolding in the dsbA mutant background (Figure 2). These data support the importance of this protein folding mechanism in the activity of multiple clinically relevant β-lactamases.

Native bacterial species are used for subsequent experiments, and the authors provide important context for their antibiotic choices and concentrations by referencing the breakpoints that guide clinical practice. In Figure 4, the authors show that loss of the DsbA system in P. aeruginosa significantly sensitizes clinical isolates expressing different classes of β-lactamases to clinically relevant antibiotics. The appropriate control showing that the dsbA1 mutation does not result in sensitivity to a non-β-lactam antibiotic is included in Figure S2. The authors further show, using an in vivo model for antibiotic treatment, that treatment of a dsbA1 mutant results in moderate and near-complete survival of the infected organisms. The importance of this system in S. maltophilia is then investigated similarly (Figure 5), showing that a dsbA dsbL mutant is also sensitive to β-lactams and colistin, another antibiotic whose resistance mechanism is dependent on the DsbA protein folding system. Importantly, the authors show that a small-molecule inhibitor that disrupts the DsbA system, rather than genetic mutations, is also capable of sensitizing S. maltophilia to these antibiotics. It should be noted that while the sensitization is less pronounced, this molecule has not been optimized for S. maltophilia and would be expected to increase in efficacy once this is done. Together, the data support that interference with the DsbA system in native hosts can sensitize otherwise resistant pathogens to clinically relevant antibiotic therapy.

Finally, the authors investigate the effects of co-culturing S. maltophilia and P. aeruginosa (Figure 5E). These assays are performed in synthetic cystic fibrosis sputum medium (SCFM), which provides a nutritional context similar to that in CF but without the presence of more complex components such as mucin. The authors show that while P. aeruginosa alone is sensitive to the antibiotic, it can survive moderate concentrations in the presence of S. maltophilia and even grow in higher concentrations where S. maltophilia appears to overproduce its β-lactamases. However, this protection is lost in S. maltophilia without the DsbA protein folding system, showing that the protective effect depends on functional production of β-lactamase. The data support a protective role for DsbA-dependent β-lactamase under these co-culture conditions.

Weaknesses:

While Figure 5E demonstrates a protective effect of DsbA-dependent β-lactamase, the omission of CFU data for S. maltophilia makes it difficult to assess the applicability of the polymicrobial strategy. Since S. maltophilia is pre-cultured prior to the addition of P. aeruginosa and antibiotics, it is unclear whether the protective effect is dependent on high S. maltophilia CFU. It is also unclear what the fate of the S. maltophilia dsbA dsbL mutant is under these conditions. If DsbA-deficient S. maltophilia CFU is not impacted, then this treatment will result in the eradication of only one of the pathogens of interest. If the mutant is lost during treatment, then it is not clear whether the loss of protection is due specifically to the production of non-functional β-lactamase or simply the absence of S. maltophilia.

The alleged clinical relevance and immediate, theoretical application of this approach should be properly contextualized. At multiple junctures, the authors state or suggest that interactions between S. maltophilia and P. aeruginosa are known to occur in disease or have known clinical relevance related to treatment failure and disease states. For instance, the citations provided for S. maltophilia protection of P. aeruginosa in the CF lung environment both describe simplified laboratory experiments rather than clinical or in vivo observations. Similarly, the citations provided for both the role of S. maltophilia in treatment failure and CF disease severity do not support either claim. The role of S. maltophilia in CF is currently unsettled, with more recent work reporting conflicting results that support S. maltophilia as a marker, rather than cause, of severe disease. These citations also do not support the suggestion that S. maltophilia specifically contributes to treatment failure. While it is reasonable to pursue these ideas as a hypothesis or potential concern, there is no evidence provided that these specific interactions occur in vivo or that they have clinical relevance.

Reviewer #1 (Public Review):

Nitrogen metabolism is of fundamental importance to biology. However, the metabolism and biochemistry of guanidine and guanidine containing compounds, including arginine and homoarginine, have been understudied over the last few decades. Very few guanidine forming enzymes have been identified. Funck et al define a new type of guanidine forming enzyme. It was previously known that 2-oxogluturate oxygenase catalysis in bacteria can produce guanidine via oxidation of arginine. Interestingly, the same enzyme that produces guanidine from arginine also oxidises 2-oxogluturate to give the plant signalling molecule ethylene. Funck et al show that a mechanistically related oxygenase enzyme from plants can also produce guanidine, but instead of using arginine as a substrate, it uses homoarginine. The work will stimulate interest in the cellular roles of homoarginine, a metabolite present in plants and other organisms including humans and, more generally, in the biochemistry and metabolism of guanidines.

1. Significance<br /> Studies on the metabolism and biochemistry of the small nitrogen rich molecule guanidine and related compounds including arginine have been largely ignored over the last few decades. Very few guanidine forming enzymes have been identified. Funck et al define a new guanidine forming enzyme that works by oxidation of homoarginine, a metabolite present in organisms ranging from plants to humans. The new enzyme requires oxygen and 2-oxogluturate as cosubstrates and is related, but distinct from a known enzyme that oxidises arginine to produce guanidine, but which can also oxidise 2-oxogluturate to produce the plant signalling molecule ethylene.

Overall, I thought this was an exceptionally well written and interesting manuscript. Although a 2-oxogluturate dependent guanidine forming enzyme is known (EFE), the discovery that a related enzyme oxidises homoarginine is really interesting, especially given the presence of homoarginine in plant seeds. There is more work to be done in terms of functional assignment, but this can be the subject of future studies. I also fully endorse the authors' view that guanidine and related compounds have been massively understudied in recent times. I would like to see the possibility that the new enzyme makes ethylene explored. Congratulations to the authors on a very nice study.

Reviewer #2 (Public Review):

In this study, Dietmar Funck and colleagues have made a significant breakthrough by identifying three isoforms of plant 2-oxoglutarate-dependent dioxygenases (2-ODD-C23) as homo/arginine-6-hydroxylases, catalyzing the degradation of 6-hydroxyhomoarginine into 2-aminoadipate-6-semialdehyde (AASA) and guanidine. This discovery marks the very first confirmation of plant or eukaryotic enzymes capable of guanidine production.

The authors selected three plant 2-ODD-C23 enzymes with the highest sequence similarity to bacterial guanidine-producing (EFE) enzymes. They proceeded to clone and express the recombinant enzymes in E coli, demonstrating capacity of all three Arabidopsis isoforms to produce guanidine. Additionally, by precise biochemical experiments, the authors established these three 2-ODD-C23 enzymes as homoarginine-6-hydroxylases (and arginine-hydroxylase for one of them). Furthermore, the authors utilized transgenic plants expressing GFP fusion proteins to show the cytoplasmic localization of all three 2-ODD-C23 enzymes. Most notably, using T-DNA mutant lines and CRISPR/Cas9-generated lines, along with combinations of them, they demonstrate the guanidine-producing capacity of each enzyme isoform in planta. These results provide robust evidence that these three 2-ODD-C23 Arabidopsis isoforms are indeed homoarginine-6-hydroxylases responsible for guanidine generation.<br /> The findings presented in this manuscript are a significant contribution for our understanding of plant biology, particularly given that this work is the first demonstration of enzymatic guanidine production in eukaryotic cells. However, there are a couple of concerns and potential ways for further investigation that the authors should (consider) incorporate.

Firstly, the observation of cytoplasmic and nuclear GFP signals in the transgenic plants may also indicate cleaved GFP from the fusion proteins. Thus, the authors should perform Western blot analysis to confirm the correct size of the 2-ODD-C23 fusion proteins in the transgenic protoplasts.

Secondly, it may be worth measuring pipecolate (and proline?) levels under biotic stress conditions (particularly those that induce transcript changes of these enzymes, Fig S8). Given the results suggesting a potential regulation of the pathway by biotic stress conditions (eg. meJA), these experiments could provide valuable insights into the physiological role of guanidine-producing enzymes in plants. This additional analysis may give a significance of these enzymes in plant defense mechanisms.

Reviewer #3 (Public Review):

Summary: The paper aims to investigate the relationship between anti-S protein antibody titers with the phenotypes&clonotypes of S-protein-specific T cells, in people who receive SARS-CoV2 mRNA vaccines. To do this, the paper recruited a cohort of Covid-19 naive individuals who received the SARS-CoV2 mRNA vaccines and collected sera and PBMCs samples at different timepoints. Then they mainly generate three sets of data: 1). Anti-S protein antibody titers on all timepoints. 2) Single-cell RNAseq/TCRseq dataset for divided T cells after stimulation by S-protein for 10 days. 3) Corresponding epitopes for each expanded TCR clones. After analyzing these results, the paper reports two major findings & claims: A) Individuals having sustained anti-S protein antibody response also have more so-called Tfh cells in their single-cell dataset, which suggests Tfh-polarization of S-specific T cells can be a marker to predict the longevity of anti-S antibody. B). S-reactive T cells do exist before the vaccination, but they seem to be unable to respond to Covid-19 vaccination properly.

The paper's strength is it uses a very systemic and thorough strategy trying to dissect the relationship between antibody titers, T cell phenotypes, TCR clonotypes and corresponding epitopes, and indeed it reports several interesting findings about the relationship of Tfh/sustained antibody and about the S-reactive clones that exist before the vaccination. However, the main weakness is these interesting claims are not sufficiently supported by the evidence presented in this paper. I have the following major concerns:

1) The biggest claim of the paper, which is the acquisition of S-specific Tfh clonotypes is associated with the longevity of anti-S antibodies, should be based on proper statistical analysis rather than just a UMAP as in Fig2 C, E, F. The paper only shows the pooled result, but it looks like most of the so-called Tfh cells come from a single donor #27. If separating each of the 4 decliners and sustainers and presenting their Tfh% in total CD4+ T cells respectively, will it statistically have a significant difference between those decliners and sustainers? I want to emphasize that solid scientific conclusions need to be drawn based on proper sample size and statistical analysis.

2) The paper does not provide any information to justify its cell annotation as presented in Fig 2B, 4A. Moreover, in my opinion, it is strange to see that there are two clusters of cells sit on both the left and right side of UMAP in Fig2B but both are annotated as CD4 Tcm and Tem. Also Tfh and Treg belong to a same cluster in Fig 2B but they should have very distinct transcriptomes and should be separated nicely. Therefore I believe the paper can be more convincing if it can present more information and discussion about the basis for its cell annotation.

3) Line 103-104, the paper claims that the Tfh cluster likely comes from cTfh cells. However considering the cells have been cultured/stimulated for 10 days, cTfh cells might lose all Tfh features after such culture. To my best knowledge there is no literature to support the notion that cTfh cells after stimulated in vitro for 10 days (also in the presence of IL2, IL7 and IL15), can still retain a Tfh phenotype after 10 days. It is possible that what actually happens is, instead of having more S-specific cTfh cells before the cell culture, the sustainers' PBMC can create an environment that favors the Tfh cell differentiation (such as express more pro-Tfh cytokines/co-stimulations). Thus after 10-days culture, there are more Tfh-like cells detected in the sustainers. The paper may need to include more evidence to support cTfh cells can retain Tfh features after 10-days' culture.

4) It is in my opinion inaccurate to use cell number in Fig4B to determine whether such clone expands or not, given that the cell number can be affected by many factors like the input number, the stimulation quality and the PBMC sample quality. A more proper analysis should be considered by calculating the relative abundance of each TCR clone in total CD4 T cells in each timepoint.

5) It is well-appreciated to express each TCR in cell line and to determine the epitopes. However, the author needs to make very sure that this analysis is performed correctly because a large body of conclusions of the paper are based on such epitope analysis. However, I notice something strange (maybe I am wrong) but for example, Table 4 donor #8 clonotype post_6 and _7, these two clonotypes have exactly the same TRAV5 and TRAJ5 usage. Because alpha chain don't have a D region, in theory these clonotypes, if have the same VJ usage, they should have the same alpha chain CDR3 sequences, however, in the table they have very different CDR3α aa sequences. I wish the author could double check their analysis and I apologize in advance if I raise such questions based on wrong knowledge.

Reviewer #1 (Public Review):

• A summary of what the authors were trying to achieve.

The authors cultured pre- and Post-vaccine PBMCs with overlapping peptides encoding S protein in the presence of IL-2, IL-7, and IL-15 for 10 days, and extensively analyzed the T cells expanded during the culture; by including scRNAseq, scTCRseq, and examination of reporter cell lines expressing the dominant TCRs. They were able to identify 78 S epitopes with HLA restrictions (by itself represents a major achievement) together with their subset, based on their transcriptional profiling. By comparing T cell clonotypes between pre- and post-vaccination samples, they showed that a majority of pre-existing S-reactive CD4+ T cell clones did not expand by vaccinations. Thus, the authors concluded that highly-responding S-reactive T cells were established by vaccination from rare clonotypes.

• An account of the major strengths and weaknesses of the methods and results.

Strengths<br /> • Selection of 4 "Ab sustainers" and 4 "Ab decliners" from 43 subjects who received two shots of mRNA vaccinations.<br /> • Identification of S epitopes of T cells together with their transcriptional profiling. This allowed the authors to compare the dominant subsets between sustainers and decliners.

Weaknesses<br /> • Fig. 3 provides the epitopes, and the type of T cells, yet the composition of subsets per subject was not provided. It is possible that only one subject out of 4 sustainers expressed many Tfh clonotypes and explained the majority of Tfh clonotypes in the sustainer group. To exclude this possibility, the data on the composition of the T cell subset per subject (all 8 subjects) should be provided.<br /> • S-specific T cells were obtained after a 10-day culture with peptides in the presence of multiple cytokines. This strategy tends to increase a background unrelated to S protein. Another shortcoming of this strategy is the selection of only T cells amenable to cell proliferation. This strategy will miss anergic or less-responsive T cells and thus create a bias in the assessment of S-reactive T cell subsets. This limitation should be described in the Discussion.<br /> • Fig. 5 shows the epitopes and the type of T cells present at baseline. Do they react to HCoV-derived peptides? I guess not, as it is not clearly described. If the authors have the data, it should be provided.<br /> • As the authors discussed (L172), pre-existing S-reactive T cells were of low affinity. The raw flow data, as shown in Fig. S3, for pre-existing T cells may help discuss this aspect.

Reviewer #2 (Public Review):

Summary: A short-term comparison of durability of S antibody levels after 2-dose vaccination, showing that better or more poorly sustained responses correlate with the presence of Tfh cells.

Strengths:<br /> Novelty of approach in expanding, sequencing and expressing TCRs for functional studies from the implicated populations.

Weaknesses:<br /> Somewhat outdated question, short timeline, small numbers, over-interpretation of sequence homology data.

Reviewer #2 (Public Review):

Summary: The authors of this manuscript are interested in discovering and functionally characterizing genes that might cause obesity. To find such genes, they conducted a forward genetic screen in mice, selecting strains which displayed increased body weight and adiposity. They found a strain, with germ-line deficiency in the gene Spag7, which displayed significantly increased body weight, fat mass, and adipose depot sizes manifesting after the onset of adulthood (20 weeks). The mice also display decreased organ sizes, leading to decreased lean body mass. The increased adiposity was traced to decreased energy expenditure at both room temperature and thermoneutrality, correlating with decreased locomotor activity and muscle atrophy. Major metabolic abnormalities such as impaired glucose tolerance and insulin sensitivity also accompanied the phenotype. Unexpectedly, when the authors generated an inducible, whole body knockout mouse using a globally expressed Cre-ERT2 along with a globally floxed Spag7, and induced Spag7 knockout before the onset of obesity, none of the phenotypes seen in the original strain were recapitulated. The authors trace this discrepancy to the major effect of Spag7 being on placental development.

Strengths: Strengths of the manuscript are its inherently unbiased approach, using a forward genetic screen to discover previously unknown genes linked to obesity phenotypes. Another strong aspect of the work was the generation of an independent, complementary, strain consisting of an inducible knockout model, in which the deficiency of the gene could be assessed in a more granular form. This approach enabled the discovery of Spag7 as a gene involved in the establishment of the mature placenta, which determines the metabolic fate of the offspring. Additional strengths include the extensive array of physiological parameters measured, which provided a deep understanding of the whole-body metabolic phenotype and pinpointed its likely origin to muscle energetic dysfunction.

Weaknesses: Weaknesses that can be raised are the lack of molecular mechanistic understanding of the numerous phenotypic observations. For example, the specific role of Spag7 to promote placental development remains unclear. Also, the reason why placental developmental abnormalities lead to muscle dysfunction, and whether indeed the entire metabolic phenotype of the offspring can be attributed solely to decreased muscle energetics is not fully explored.

Overall, the authors achieved a remarkable success in identifying genes associated with development of obesity and metabolic disease, discovering the role of Spag7 in placental development, and highlighting the fundamental role of in-utero development in setting future metabolic state of the offspring.

Reviewer #1 (Public Review):

Drawing on insights from preceding studies, the researchers pinpointed mutations within the spag7 gene that correlate with metabolic aberrations in mice. The precise function of spag7 has not been fully described yet, thereby the primary objective of this investigation is to unravel its pivotal role in the development of obesity and metabolic disease in mice. First, they generated a mice model lacking spag7 and observed that KO mice exhibited diminished birth size, which subsequently progressed to manifest obesity and impaired glucose tolerance upon reaching adulthood. This behaviour was primarily attributed to a reduction in energy expenditure. In fact, KO animals demonstrated compromised exercise endurance and muscle functionality, stemming from a deterioration in mitochondrial activity. Intriguingly, none of these effects was observed when using a tamoxifen-induced KO mouse model, implying that Spag7's influence is predominantly confined to the embryonic developmental phase. Explorations within placental tissue unveiled that mice afflicted by Spag7 deficiency experienced placental insufficiency, likely due to aberrant development of the placental junctional zone, a phenomenon that could impede optimal nutrient conveyance to the developing fetus. Overall, the authors assert that Spag7 emerges as a crucial determinant orchestrating accurate embryogenesis and subsequent energy balance in the later stages of life.

The study boasts several noteworthy strengths. Notably, it employs a combination of animal models and a thorough analysis of metabolic and exercise parameters, underscoring a meticulous approach. Furthermore, the investigation encompasses a comprehensive evaluation of fetal loss across distinct pregnancy stages, alongside a transcriptomic analysis of skeletal muscle, thereby imparting substantial value. However, a pivotal weakness of the study centres on its translational applicability. While the authors claim that "SPAG7 is well-conserved with 97% of the amino acid sequence being identical in humans and mice", the precise role of spag7 in the human context remains enigmatic. This limitation hampers a direct extrapolation of findings to human scenarios. Additionally, the study's elucidation of the molecular underpinnings behind the spag7-mediated anomalous development of the placental junction zone remains incomplete. Finally, the hypothesis positing a reduction in nutrient availability to the fetus, though intriguing, requires further substantiation, leaving an aspect of the mechanism unexplored.

Hence, in order to fortify the solidity of their conclusions, these concerns necessitate meticulous attention and resolution in the forthcoming version of the manuscript. Upon the comprehensive addressing of these aspects, the study is poised to exert a substantial influence on the field, its significance reverberating significantly. The methodologies and data presented undoubtedly hold the potential to facilitate the community's deeper understanding of the ramifications stemming from disruptions during pregnancy, shedding light on their enduring impact on the metabolic well-being of subsequent generations.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Flaherty III S.E. et al identified SPAG7 gene in their forward mutagenetic screening and created the germline knockout and inducible knockout mice. The authors reported that the SPAG7 germline knockout mice had lower birth weight likely due to intrauterine growth restriction and placental insufficiency. The SPAG7 KO mice later developed obesity phenotype as a result of reduced energy expenditure. However, the inducible SPAG7 knockout mice had normal body weight and composition.

Strengths:<br /> In this reviewer's opinion, this study has high significance in the field of metabolic research for the following reasons.<br /> (1) The authors' findings are significant in the field of obesity research, especially from the perspective of maternal-fetal medicine. The authors created and analyzed the SPAG7 KO mice and found that the KO mice had a "thrifty phenotype" and developed obesity.<br /> (2) SPAG7 gene function hasn't been thoroughly studied. The reported phenotype will fill the gap of knowledge.<br /> Overall, the authors have presented their results in a clear and logically organized structure, clearly stated the key question to be addressed, used the appropriate methodology, produced significant and innovative main findings.

Weaknesses:<br /> The manuscript can be further strengthened with more clarification on the following points.<br /> 1. The germline whole-body KO mice were female mice (Line293), however the inducible knockout mice were male mice (Line549). Sexual dimorphism is often observed in metabolic studies, therefore the metabolic phenotype of both female and male mice needs to be reported for the germline and inducible knockouts in order to make the justified conclusion.<br /> 2. SPAG7 has an NLS. Does this protein function in gene expression? Whether the overall metabolic phenotype is the direct cause of SPAG7 ablation is unclear. For example, the Hsd17b10 gene was downregulated in all tissues in the KO mice. Could this have been coincidentally selected for and thus be the cause of the developmental issues and adulthood obesity? Do the iSpag7 mice demonstrate reduced expression of Hsd17b10?<br /> 3. Figure 2c should display the energy expenditure normalized to body weight (or lean body mass).<br /> 4. Please provide more information for the figure legend, including the statistical test that was conducted for each data set, animal numbers for each genotype and sexes.<br /> 5. The authors should report how long after treatment the data was collected for figures 4F-M.<br /> 6. The authors should justify ending the data collection after 8 weeks for the iSPAG7 mice in Figures 4C-E. In the WT vs germline KO mice, there was no clear difference in body weight or lean mass at 15 weeks of age.

Reviewer #1 (Public Review):

Summary:<br /> Cincotta et al set out to investigate the presence of glucocorticoid receptors in the male and female embryonic germline. They further investigate the impact of tissue-specific genetically induced receptor absence and/or systemic receptor activation on fertility and RNA regulation. They are motivated by several lines of research that report inter and transgenerational effects of stress and or glucocorticoid receptor activation and suggest that their findings provide an explanatory mechanism to mechanistically back parental stress hormone exposure-induced phenotypes in the offspring.

Strengths:<br /> - A chronological immunofluorescent assessment of GR in fetal and early life oocyte and sperm development.<br /> - RNA seq data that reveal novel cell type specific isoforms validated by q-RT PCR E15.5 in the oocyte.<br /> - 2 alternative approaches to knock out GR to study transcriptional outcomes. Oocytes: systemic GR KO (E17.5) with low input 3-tag seq and germline-specific GR KO (E15.5) on fetal oocyte expression via 10X single cell seq and 3-cap sequencing on sorted KO versus WT oocytes - both indicating little impact on polyadenylated RNAs<br /> - 2 alternative approaches to assess the effect of GR activation in vivo (systemic) and ex vivo (ovary culture): here the RNA seq did show again some changes in germ cells and many in the soma.<br /> - They exclude oocyte-specific GR signaling inhibition via beta isoforms.<br /> - Perinatal male germline shows differential splicing regulation in response to systemic Dex administration, results were backed up with q-PCR analysis of splicing factors.

Weaknesses:<br /> - The presence of a protein cannot be entirely excluded based on IF data (staining of spermatids is referred to but not shown).<br /> - The authors do not consider post-transcriptional level a) modifications also trigged by GR activation b) non-coding RNAs (not assessed by seq).<br /> - Sequencing techniques used are not total RNA but either are focused on all polyA transcripts (10x) or only assess the 3' prime end and hence are not ideal to study splicing, The number of replicates in the low input seq is very low and hence this might be underpowered. Since Dex treatment showed some (modest) changes in oocyte RNA - effects of GR depletion might only become apparent upon Dex treatment as an interaction.<br /> - Effects in oocytes following systemic Dex might be indirect due to GR activation in the soma.<br /> - Even though ex vivo culture of ovaries shows GR translocation to the nucleus it is not sure whether the in vivo systemic administration does the same.

The conclusion that fetal oocytes are "intrinsically buffered to GR signalling" is very strong, given that "only" poly A sequencing and few replicates of 3-prime sequencing have been analyzed and information is lacking on whether GR is activated in germ cells in the systemically dex-injected animals.

This work is a good reference point for researchers interested in glucocorticoid hormone signaling fertility and RNA splicing. It might spark further studies on germline-specific GR functions and the impact of GR activation on alternative splicing.

While the study provides a characterization of GR and some aspects of GR perturbation, and the negative findings in this study do help to rule out a range of specific roles of GR in the germline, there is still a range of other potential unexplored options. The introduction of the study eludes to implications for intergenerational effects via epigenetic modifications in the germline, however, it does not mention that the indirect effects of reproductive tissue GR signaling on the germline have indeed already been described in the context of intergenerational effects of stress. Also, the study does not assess epigenetic modifications.

The conclusion that the persistence of a phenotype for up to three generations suggests that stress can induce lasting epigenetic changes in the germline is misleading. For the reader who is unfamiliar with the field, it is important to define much more precisely what is referred to as "a phenotype". Furthermore, this statement evokes the impression that the very same epigenetic changes in the germline have been observed across multiple generations.

The evidence of the presence of GR in the germline is also somewhat limited - since other studies using sequencing have detected GR in the mature oocyte and sperm.

The discussion ends again on the implications of sex-specific differences of GR signaling in the context of stress-induced epigenetic inheritance. It states that the observed differences might relate to the fact that there is more evidence for paternal lineage findings, without considering that maternal lineage studies in epigenetic inheritance are generally less prevalent due to some practical factors - such as more laborious study design making use of cross-fostering or embryo transfer. Since the authors comment on RNA-mediated inheritance it seems inevitable to again consider indirect effects.

Reviewer #2 (Public Review):

Summary: There is increasing evidence in the literature that rodent models of stress can produce phenotypes that persist through multiple generations. Nevertheless, the mechanism(s) by which stress exposure produces phenotypes are unknown in the directly affected individual as well as in subsequent offspring that did not directly experience stress. Moreover, it has also been shown that glucocorticoid stress hormones can recapitulate the effects of programmed stress. In this manuscript, the authors test the compelling hypothesis that glucocorticoid receptor (GR)-signaling is responsible for the transmission of phenotypes across generations. As a first step, the investigators test for a role of GR in the male and female germline. Using knockouts and GR agonists, they show that although germ cells in male and female mice have GR that appears to localize to the nucleus when stimulated, oocytes are resistant to changes in GR levels. In contrast, the male germline exhibits changes in splicing but no overt changes in fertility.

Strengths: Although many of the results in this manuscript are negative, this is a careful and timely study that informs additional work to address mechanisms of transmission of stress phenotypes across generations and suggests a sexually dimorphic response to glucocorticoids in the germline. The work presented here is well-done and rigorous and the discussion of the data is thoughtful. Overall, this is an important contribution to the literature.

Reviewer #1 (Public Review):

This is a well-designed study that explores the BEF relationships in fragmented landscapes. Although there are massive studies on BEF relationships, most of them were conducted at local scales, few considered the impacts of landscape variables. This study used a large dataset to specifically address this question and found that habitat loss weakened the BEF relationships. Overall, this manuscript is clearly written and has important implications for BEF studies as well as for ecosystem restoration.

My only concern is that the authors should clearly define habitat loss and fragmentation. Habitat loss and fragmentation are often associated, but they are different terms. The authors consider habitat loss a component of habitat fragmentation, which is not reasonable. Please see my specific comments below.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Yan et al. assess the effect of two facets of habitat fragmentation (i.e., habitat loss and habitat fragmentation per se) on biodiversity, ecosystem function, and the biodiversity-ecosystem function (BEF) relationship in grasslands of an agro-pastoral ecotone landscape in northern China. The authors use stratified random sampling to select 130 study sites located within 500m-radius landscapes varying along gradients of habitat loss and habitat fragmentation per se. In these study sites, the authors measure grassland specialist and generalist plant richness via field surveys, as well as above-ground biomass by harvesting and dry-weighting the grass communities in each 3 x 1m2 plots of the 130 study sites. The authors find that habitat loss and fragmentation per se have different effects on biodiversity, ecosystem function and the BEF relationship: whereas habitat loss was associated with a decrease in plant richness, fragmentation per se was not; and whereas fragmentation per se was associated with a decrease in above-ground biomass, habitat loss was not. Finally, habitat loss, but not fragmentation per se was linked to a decrease in the magnitude of the positive biodiversity-ecosystem functioning relationship, by reducing the percentage of grassland specialists in the community.

Strengths:<br /> This study by Yan et al. is an exceptionally well-designed, well-written, clear and concise study shedding light on a longstanding, important question in landscape ecology and biodiversity-ecosystem functioning research. Via a stratified random sampling approach (cf. also "quasi-experimental design" Butsic et al. 2017), Yan et al. create an ideal set of study sites, where habitat loss and habitat fragmentation per se (usually highly correlated) are decorrelated and hence, separate effects of each of these facets on biodiversity and ecosystem function can be assessed statistically in "real-world" (and not experimental, cf. Duffy et al. 2017) communities. The authors use adequate and well-described methods to investigate their questions. The findings of this study add important empirical evidence from real-world grassland ecosystems that help to advance our theoretical understanding of landscape-moderation of biodiversity effects and provide important guidelines for conservation management.

Weaknesses:<br /> I found only a few minor issues, mostly unclear descriptions in the study that could be revised for more clarity.

References:<br /> Butsic, V., Lewis, D. J., Radeloff, V. C., Baumann, M., & Kuemmerle, T. (2017). Quasi-experimental methods enable stronger inferences from observational data in ecology. Basic and Applied Ecology, 19, 1-10.

Duffy, J.E., Godwin, C.M. & Cardinale, B.J. (2017). Biodiversity effects in the wild are common and as strong as key drivers of productivity. Nature.

Reviewer #3 (Public Review):

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

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

Weaknesses:<br /> 1. The authors used five fragmentation metrics in their study. However, the choice of these fragmentation metrics was not well justified. The ecological significance of each fragmentation metric needs to be differentiated clearly. Also, these fragmentation metrics may be highly correlated with each other and redundant. I suggest author test the collinearity of these fragmentation metrics for influencing biodiversity and ecosystem function.<br /> 2. I found the local environmental factors were not considered in the study. As the author mentioned in the manuscript, temperature and water also have important impacts on biodiversity and ecosystem function in the natural ecosystem. I suggest authors include the environmental factors in the data analysis to control their potential impact, especially the structural equation model.

Joint Public Review:

This work by Liu CSC et al. is an extension of the author's previous work on the role of Piezo1 mechano-sensor in human T cell activation. In this study, the authors address whether Piezo1 plays a role in T-cell chemotactic migration.

The authors used CD4+ T cells or Jurkat T cells to test the effects of siRNA-mediated depletion of Piezo1 on chemotactic migration. They establish that Piezo1 is implicated in chemotactic migration, although the effects of depletion are relatively moderate.

They show that Piezo1 is redistributed to the leading edge of T-cells.

They identify that relocation of Piezo1 to the leading edge follows an increase in membrane tension.

In Piezo-1 depleted cells, they observe a moderate reduction of LFA-1 polarity. With the use of specific inhibitors, they propose Piezo1 activation to be downstream of focal adhesion formation and upstream of calpain-mediated LFA-1, integrin alpha L beta 2, or CD11a/CD18 recruitment at the leading edge.

Strengths:<br /> Together with their 2018 paper, this study presents Pieszo1 as a regulator of T-cell activation, implicating it as a player in the coordination of the chemotactic immune response.

Weaknesses:<br /> Most of the effects observed are relatively modest. The authors did not challenge the cells with various physico-mechanical conditions to see when Piezo-1 might become really important. For instance, there are no experiments that expose T cells to varying counter-acting forces to see how piezo1 might affect migration.

Technical weaknesses:<br /> The authors state that "these high tension edges are usually further emphasized at later time points", but after ten minutes the median tension and tension (Figure 2C and Supplementary Figure 2C respectively) reduce down to the pretreatment time point. It would be clearer if the author stated within which timeframe the tension edges are "further emphasised".

Figures 3 and 4 - The author states the number of cells quantified from the images, but it is not clear whether the data is actually from 3 biological replicates.

Some of the data has no representative images or videos included. there is no video in the supplementary for Figures 1 A and B. There are no representative images of transwell migration assay in Figures 1 D and E.

Reviewer #1 (Public Review):

Summary:

In this work, Frank, Bergamasco, Mlodzianoski et al study two microcephaly-associated patient variants in TRABID to identify and characterize a previously unrecognized role of this deubiquitylation enzyme during neurodevelopment. The authors generate TRABID p.R438W and p.A451V knock in mice, which exhibit smaller neuronal and glial cell densities as well as motor deficits, phenotypes that are consistent with the congenital defects observed in the patients. Through in vitro and cellular immunoprecipitation assays, the authors demonstrate that the p.R438W variant impairs the K29- and K63-chain cleavage activity of TRABID, while the p.A451V variant reduces binding to the STRIPAK complex, a previously identified TRABID interactor with established functions in cytoskeletal organization and neural development. Ubiquitylation assays performed in HEK293T cells further reveal that the hypomorphic patient variants are deficient in deubiquitylating APC, a previously identified substrate of TRABID that has been shown to control the neuronal cortical cytoskeleton during neurite outgrowth. Ex vivo experiments provide evidence that axonal APC trafficking and neurite outgrowth is disturbed in differentiating neural progenitors isolated from mouse embryos carrying Trabid patient alleles. From these experiments the authors propose a model in which TRABID- and STRIPAK-dependent APC deubiquitylation regulates its axonal trafficking to ensure faithful neurite outgrowth and misregulation of this function leads to neurodevelopmental phenotypes in TRABID/ZRANB1 patients.

Strengths:

This study describes a previously unrecognized function of TRABID in neurodevelopment and establishes knock in mice as model to study congenital defects of TRABID/ZRANB1 patients. In addition, the authors identify control of axonal trafficking of APC by deubiquitylation as a potential mechanism through which TRABID regulates neurite outgrowth and whose dysregulation could be the molecular basis of the neurodevelopmental phenotypes observed in TRABID/ZRANB1 patients.

Weaknesses:

While the proposed underlying mechanism of how hypomorphic TRABID mutations lead to the patient phenotypes is conceivable and supported by the author's data, there is no functional evidence provided that the mouse phenotypes (reduced neuron/glia densities or motor deficits) are indeed due to aberrant APC deubiquitylation and trafficking. In addition, some aspects of the proposed mechanism, i.e. the claim that APC deubiquitylation is STRIPAK-dependent, should be strengthened by orthogonal approaches.

Reviewer #2 (Public Review):

Summary:

Although Trabid missense mutations are identified across a range of neurodevelopmental disorders, its role in neurodevelopment is not understood. Here the authors study two different patient mutations and implicate defects in its deubiquitylating activity and interactions with STRIPAK. Knockin mice for these mutations impaired trafficking of APC to microtubule plus ends, with consequent defects in neuronal growth cone and neurite outgrowth.

The authors focus on R438W and A451V, two missense mutations seen in patients. Recombinant fragments showed R438W is nearly completely DUB-dead whereas A451V showed normal activity but failed to efficiently precipitate STRIPAK. Knockin of these mutations showed a partially penetrant reduced cortical neuronal and glial cell numbers and reduced TH+ neurons and their neuronal processes. Cell culture demonstrated that both DUB and STRIPAK-binding activities of Trabid are required for efficient deubiquitylation of APC in cells, and alter APC transport along neurites. APC-tdTomato fluorescent reporter mice crossed with the Trabid mutants confirmed these results. The results suggest that Trabid's mechanism of action is to suppress APC ubiquitylation to regulate its intracellular trafficking and neurite formation.

Strengths:

Solid manuscript with in vivo and in vitro demonstration of mechanism of action

Weaknesses:

Much of the work relies on prior discoveries of Trabid's role in STRIPAK and APC related functions, so the novelty is somewhat reduced.

Reviewer #1 (Public Review):

Summary:

A novel serine protease and an inhibitor pair regulate cell migration in the neural crest. This is a very important study that describes a novel pathway controlling neural crest migratory behavior through a pair of protease and inhibitor regulators that act in the extracellular space. Using very high technical standards in Xenopus embryos they show that knockdown of the inhibitor SerpinE2 prevents cell migration and that this is restored by simultaneous knockdown of the serine protease HtrA1.

Strengths:

The reproduction of classical cranial neural crest extirpations and their phenocopy by SerpinE2 morpholino is remarkable. The experiments provided must represent many years of work, and the paper is written in a very scholarly fashion. The data is of the highest quality.

Weaknesses:

The paper is very long and contains many years of experiments, making it at times difficult to read. The paper contains so much data that it would help the readership if the present version were revised in order to make it more digestible.

Reviewer #2 (Public Review):

Summary:

The authors conducted research on the role of SerpinE2 and HtrA1 in neural crest migration using Xenopus embryos. The data presented in this study was of high quality and supported the authors' conclusions. The discovery of the potential molecular connection between SerpinE2 and HtrA1 in neural crest cell migration in vivo is significant, as understanding this pathway could potentially lead to treatments for aggressive cancers and pregnancy-related disorders.

Strengths:

Previous research has shown that SerpinE2 and HtrA1 can have both positive and negative effects on cell migration, but their molecular interplay and role in neural crest migration are not well-established. This study is the first to reveal a potential connection between these two proteins in neural crest cell migration in vivo. The authors found that SerpinE2 promotes neural crest migration by inhibiting HtrA1. Additionally, overexpression of Sdc4 partly alleviates neural crest migration issues caused by SerpinE2 knockdown or HtrA1 overexpression. These findings suggest that the SeprinE2-HtrA1-Sdc4 pathway is crucial for neural crest migration.

Weaknesses:

To further increase the study's credibility, the authors could use techniques like western blotting, qRT-PCR, or in situ hybridization to verify the efficiency of SerpinE2 and HtrA1 knockdown and/or overexpression. Furthermore, determining whether the observed craniofacial phenotypes in SerpinE2 and/or HtrA1 mutants were solely due to modified cranial neural crest migration or affected by other factors such as cell proliferation, cell survival, and chondrogenic differentiation could provide more clarity. Lastly, it is unclear whether the SeprinE2-HtrA1-Sdc4 pathway is constant in both cranial and trunk neural crest migration.

Reviewer #1 (Public Review):

Pathogenic mutations of mTOR pathway genes have been identified in patients with malformation of cortical development and intractable epilepsy. Nguyen et al., established an in vivo rodent model to investigate the impact of different mTOR pathway gene dysfunction on neuronal intrinsic membrane excitability and cortical network activity. The results demonstrate that activation of mTORC1 activators or inactivation of mTORC1 repressors leads to convergent mTOR pathway activation and alterations of neuronal morphology, the key pathological feature of human FCD and hemimegalencephaly. However, different mTOR pathway gene mutations also exhibited variations in modulating Ih current and synaptic activity in rodent cortical neurons. These findings provide novel insights into the mechanism of seizure generation associated with cortical malformation.

1. The authors found differences in the initial spike doublet of action potentials between cortical neurons in experimental and control conditions (Figure 2e). The action potential firing frequency of the first two APs (instant firing frequency) of recorded neurons shall be quantified to investigate whether there are statistical differences between the action potential firing frequency in cortical neurons in different experimental groups versus control conditions.

2. The mTORS12215Y induced the largest changes in Ih current amplitudes in cortical neurons compared with other experimental conditions. Whether the HCN4 channel expression is regulated by mTOR pathway activation, or could there be possible interactions between the HCN channel and mTORS12215Y mutant protein?

3. A comparison of the electrophysiological characteristics of cortical neurons in different experimental conditions in the present study and pathological neurons in human FCD reported in previous literature could be interesting. Inducing pathological gene mutations or knocking out key genes in mTOR pathway in the rodent cortex - which approach could better model human FCD?

Reviewer #2 (Public Review):

Summary:<br /> The study provides valuable and compelling evidence that while activation of the mTOR cascade confers some similarities in alterations in cell size, mTOR pathway activation, cortical lamination, baseline firing properties, and synaptic activity, there are distinctions that could account for clinical differences in seizure and epilepsy phenotypes in patients harboring these mutations. These findings could have important implications going forward as we design clinical therapeutic strategies to modulate mTOR activity in these individuals to treat seizures.

This study presents a valuable finding on the role that distinct mTOR pathway genes play in altered cell shape, cortical laminar migration, and cellular excitability in the mouse medial prefrontal cortex (mPFC). The evidence supporting the claims of the authors is solid, although analysis of the role of the mTORC2 pathway and consideration of distinct metabolic states i.e., amino acid levels would have strengthened the study. The work will be of interest to neuroscientists working on human epilepsy. These genes have each been assayed in previous independent studies and thus the direct comparison is what provides the innovation and interest.

The manuscript by Nguyen and colleagues attempts to define both the common and differential roles of mTOR pathway genes, both by gene knockout (KO) and activation, on cortical neuronal size, cortical lamination, and excitability. They focused on 5 genes that have been linked to human malformations of cortical development (MCD) and epilepsy: RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO. The RhebY35L, mTORS2215Y are known and pathogenic human gain-of-function variants. Each of these genes is known to modulate the activity of mTORC1 and either KO or activation will lead to abnormal and persistent hyperactivation of mTOR activity. Using in utero electroporation they transfected plasmids containing these gene constructs into fetal mouse brains at E15.5 and then assessed neuronal shape and size, laminar positioning, spontaneous activity, synaptic activity, and expression of a novel voltage-gated potassium channel (HCN4) at varying time postnatally e.g., P7-9 (neonates) and P28-43 (young adults).

The study clearly achieves its stated aims i.e., that disruption of each of five distinct mTOR pathway genes, Rheb, mTOR, Depdc5, Pten, and Tsc1, individually impacts pyramidal neuron development and electrophysiological function in the mouse mPFC. The data from each of the 5 genes provides strong support to the notion that mTOR pathway gene mutations yield the unifying clinical parcellation of mTORopathies, likely as a consequence of mTOR pathway activation. The data also provide interesting evidence that subtle or even overt differences in clinical phenotypes between RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO in humans could be due to effects of these genes either on mTOR or on yet to be defined alternative pathways. Assuredly follow-up studies to examine how Rheb, mTOR, Dedpdc5, Pten, and Tsc1 engage with other protein binding partners or other pathways will be warranted in future studies.

Strengths:<br /> The investigators demonstrate that gene KO or activation leads to common changes in cell size (enlargement) though with different effects across each gene subtype suggesting distinct genetic effects despite a common effect on mTOR signaling. The major effect was seen in forebrain neurons expressing mTORS2215Y. They also report gene-specific effects of each mTOR pathway gene on cortical lamination. For example, while RhebY35L, mTORS2215Y, Dedpdc5KO, and Tsc1KO significantly disrupted laminar positioning of neurons in layer 2/3, PtenKO had minimal effects on laminar positioning. This finding is intriguing since it means that simply activating mTOR during fetal brain development will not necessarily alter cortical lamination and that an increase in cell size by itself doesn't disrupt laminar fidelity. To verify that the expression of plasmids led to mTORC1 hyperactivation, phosphorylated levels of S6 (i.e., p-S6), a downstream substrate of mTORC1, were assayed by immunohistochemistry in P28-43 mice. Expression of the RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO plasmids all led to significantly increased p-S6 staining intensity, supporting that the expression of each of these plasmids leads to increased mTORC1 signaling.

Whole-cell current- and voltage-clamp recordings were performed in P25-P51 mice in acute brain slice preparations. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to decreased depolarization-induced excitability, but only RhebY35L, mTORS2215Y, and Tsc1KO expression led to depolarized resting membrane potentials. Interestingly, expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to the abnormal presence of HCN4 channels with variations in functional expression suggesting a common cellular mechanism that could confer excitability. Treatment with rapamycin, an mTOR inhibitor, reversed the expression changes in HCN4. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to different impacts on sEPSC properties. Effects of treatment with the selective HCN channel blocker zatebradine on hyperpolarization-induced inward currents in mTORS2215Y neurons confirmed the identity of ΔI as Ih.

Overall the data presented provides a convincing and compelling direct comparison of the roles that select mTOR pathway genes play on brain development and network excitability. It is critical to directly compare these gene effects in mouse models because although these genes are part of the mTOR pathway and clearly cause augmentation of mTOR activation, there are mechanistic differences in how these gees modify mTOR and how they interact with other proteins and phenotypic differences in humans harboring mutations in these same genes.

Weaknesses:<br /> There are a few limitations to an otherwise solid study. First, the authors postulate that all the findings are dependent on mTORC1-related effects but don't assess whether some of the differences could be due to effects on mTORC2 signaling. mTORC2 is an important and poorly understood alternative isoform of mTOR (due to rictor binding) that has effects on distinct cell signaling pathways and in particular actin polymerization. This doesn't diminish the effects of the current analysis of mTORC1 but could explain genotypic differences in each variable. A few prior studies have assessed the role of mTORC2 in epileptogenesis and Cortical malformations (Chen et al., 2019)

Second, the slice recordings were performed in the usual recording aCSF buffer conditions but there is no assessment of the role of amino acids or nutrients in the bath. While it is clear that valuable and viable acute slice recordings can be made in aCSF, the role of the mTOR pathway is to modulate cell growth in response to nutrient conditions. Thus, one variable that could be manipulated and assessed currently in this study is the levels of amino acids i.e., leucine and arginine added to the bath since DEPDC5 and TSC1 are responsive to ambient amino acid levels.

Third, the analysis concedes that the role of somatic mutations in cortical malformations may depend not only on genotypic effects but also on allelic load and cellular subtype affected by the mutation. Thus, it would interesting to see if electroporation either at E14 or E16, thereby affecting a distinct pool of progenitors, would mitigate or accentuate differences between mTOR pathway genes.

Treatment with rapamycin and zatebradine in each condition would have added to the strength of the findings to determine the mTOR-dependence and reversibility of HCN4 effects.

Reviewer #1 (Public Review):

Summary:

The authors study the appearance of oscillations in motifs of linear threshold systems, coupled in specific topologies. They derive analytical conditions for the appearance of oscillations, in the context of excitatory and inhibitory links. They also emphasize the higher importance of the topology, compared to the strength of the links. Finally, the results are confirmed with WC oscillators, which are also linear. The findings are to some extent confirmed with spiking neurons, though here results are less clear, and they are not even mentioned in the Discussion.

Overall, the results are sound from a theoretical perspective, but I still find it hard to believe that they are of significant relevance for biological networks, or in particular for the oscillations of BG-thalamus-cortex loop in PD. I find motifs in general to be too simplistic for multiscale and generally large networks as is the case in the brain. Moreover, the division of regions is more or less arbitrary by definition, and having such a strong dependence on an odd/even number of inhibitory links is far from reality. Another limitation is the fact that the cortex is considered a single node. Similarly, decomposing even such a coarse network in all possible (238 in this case) motifs doesn't seem of much relevance, when I assume that the emergence of pathological rhythms is more of an emergent phenomenon.

Strengths:

From the point of view of nonlinear dynamics, the results are solid, and the intuition behind the proofs of the theorems is well explained.

Weaknesses:

As stated in the summary, I find the work to be too theoretical without a real application in biological systems or the brain, where the networks are generally very large. It is not the problem in the simplicity of the model or of the topology, it is often the case that the phenomena are explained by very reduced systems, but the problem is that the applicability of the finding cannot be extended. E.g. the Kuramoto model uses all-to-all coupling, or similar with QIF neurons which also need to follow a Lorentzian distribution in order to derive a mean field. But in those cases, relaxing the strict conditions that were necessary for the derivations, still conserves the main findings of the analysis, which I don't see being the case here. The odd/even number rule is too strict, and talking about a fixed and definite number of cycles in the actual brain seems too simplistic.

Being linear is another strong assumption, and it is not clear how much of the results are preserved for spiking neurons, even though there is such an analysis, or maybe for other nonlinear types of neuronal masses.

Delays are also mentioned, and their impact on the oscillatory networks is as expected: it reduces the amplitude, but there is no link to the literature, where this is an established phenomenon during synchronization. Finally, the authors should also discuss the time-delays as a known phenomenon to cause or amplify oscillations at different frequencies in a network of coupled oscillators, e.g Petkoski & Jirsa Network Neuroscience 2022, Tewarie et al. NeuroImage 2019, Davis et al. Nat Commun 2021.

Reviewer #2 (Public Review):

Summary:

The authors present here a mathematical and computational study of the topological/graph theory requirements to obtain sustained oscillations in neural network models. A first approach mathematically demonstrates that, a given network of interconnected neural populations (understood in the sense of dynamical systems) requires an odd number of inhibitory populations to sustain oscillations. The authors extend this result via numerical simulations of (i) a simplified set of Wilson-Cowan networks, (ii) a simplified circuit of the cortico-basal ganglia network, and (iii) a more complex, spike-based neural network of basal ganglia network, which provides insight on experimental findings regarding abnormal synchrony levels in Parkinson's Disease (PD).

Strengths:

The work elegantly and effectively combines solid mathematical proof with careful numerical simulations at different levels of description, which is uncommon and provides additional layers of confidence to the study. Furthermore, the authors included detailed sections to provide intuition about the mathematical proof, which will be helpful for readers less inclined to the perusal of mathematical derivations. Its insightful and well-informed connection with a practical neuroscience problem, the presence of strong beta rhythms in PD, elevates the potential influence of the study and provides testable predictions.

Weaknesses:

In its current form, the study lacks a more careful consideration of the role of delays in the emergence of oscillations. Although they are addressed at certain points during the second part of the study, there are sections in which this could have been done more carefully, perhaps with additional simulations to solidify the authors' claims. Furthermore, there are several results reported in the main figures which are not explained in the main text. From what I can infer, these are interesting and relevant results and should be covered. Finally, the text would significantly benefit from a revision of the grammar, to improve the general readability at certain sections. I consider that all these issues are solvable and this would make the study more complete.

Reviewer #1 (Public Review):

Summary:<br /> The Drosophila wing disc is an epithelial tissue, the study of which has provided many insights into the genetic regulation of organ patterning and growth. One fundamental aspect of wing development is the positioning of the wing primordia, which occurs at the confluence of two developmental boundaries, the anterior-posterior and the dorsal-ventral. The dorsal-ventral boundary is determined by the domain of expression of the gene apterous, which is set early in the development of the wing disc. For this reason, the regulation of apterous expression is a fundamental aspect of wing formation.

In this manuscript, the authors used state-of-the-art genomic engineering and a bottom-up approach to analyze the contribution of a 463 base pair fragment of apterous regulatory DNA. They find compelling evidence about the inner structure of this regulatory DNA and the upstream transcription factors that likely bind to this DNA to regulate apterous early expression in the Drosophila wing disc.

Strengths:<br /> This manuscript has several strengths concerning both the experimental techniques used to address the problem of gene regulation and the relevance of the subject. To identify the mode of operation of the 463 bp enhancer, the authors use a balanced combination of different experimental approaches. First, they use bioinformatic analysis (sequence conservation and identification of transcription factors binding sites) to identify individual modules within the 463 bp enhancer. Second, they identify the functional modules through genetic analysis by generating Drosophila strains with individual deletions. Each deletion is characterized by looking at the resulting adult phenotype and also by monitoring apterous expression in the mutant wing discs. They then use a clever method to interfere in a more dynamic manner with the function of the enhancer, by directing the expression of catalytically inactive Cas9 to specific regions of this DNA. Finally, they recur to a more classical genetic approach to uncover the relevance of candidate transcription factors, some of them previously known and others suggested by the bioinformatic analysis of the 463 bp sequence. This workflow is clearly reflected in the manuscript, and constitutes a great example of how to proceed experimentally in the analysis of regulatory DNA.

Weaknesses:<br /> There are several caveats with the data that might be constructed as weaknesses, some of them are intrinsic to this detailed analysis or to the experimental difficulties of dealing with the wing disc in its earliest stages, and others are more conceptual and are offered here in case the authors may wish to consider them.

1) The primordium of the wing region of the wing imaginal disc is defined by the expression of the gen vestigial, which is regulated by inputs coming from the dorsal-ventral boundary (Notch and wg) and from the anterior-posterior boundary (Dpp). Having such a principal role in wing primordium specification and expansion, I am surprised that this manuscript does not mention this gene in the main text and only contains indirect references to it. I consider that the manuscript would have benefited a lot by including vestigial in the analysis, at least as a marker of early wing primordium. This might allow us to visualize directly the positioning of the primordium in the apterous mutants generated in this study, adding more verisimilitude to the interpretations that place this domain based on indirect evidence.

2) The authors place some emphasis on the idea that their work addresses possible coordination between setting the D/V boundary and the A/P boundary:

Abstract: "Thus, the correct establishment of ap expression pattern with respect to en must be tightly controlled", "...challenging the mechanism by which apE miss-regulation leads to AP defects." "Detailed mutational analyses using CRISPR/Cas revealed a role of apE in positioning the DV boundary with respect to the AP boundary"<br /> Introduction: "However, little is known about how the expression pattern of ap is set up with respect that of en. In other words, how is the DV boundary positioned with respect to the AP boundary?"<br /> "How such interaction between ap and the AP specification program arises is unknown."<br /> Results: "Some of these phenotypes are reminiscent of those reported for apBlot (Whittle, 1979) and point towards a yet undescribed crosstalk between ap early expression and the AP specification program."

At the same time, they express the notion, with which this reviewer agrees, that all defects observed in A/P patterning arising as a result of apterous miss-regulation are due to the fact that in their mutants, apterous expression is lost mainly in the posterior dorsal compartment, bringing novel confrontations between the A/P and the D/V boundaries.

To me, the key point is why the expression of apterous in different mutants of the OR463 enhancer affects only the posterior compartment. This should be discussed because it is far from obvious that apterous expression has different regulatory requirements in the anterior and posterior compartments.

3) The description of gene expression in the wing disc of novel apterous mutants is only carried out in late third instar discs (Figs. 2, 3, 5, and 7). This is understandable given the technical difficulties of dealing with early discs, as those shown in the analysis of candidate apterous regulatory transcription factors (Fig. 4F, Fig. 6 C-D). However, because the effects of the mutants on apterous expression are expected to occur much earlier than the time of expression analysis, this fact should be discussed.

Reviewer #2 (Public Review):

In their manuscript, "Transcriptional control of compartmental boundary positioning during Drosophila wing development," Aguilar and colleagues do an exceptional job of exploring how tissue axes are established across Drosophila development. The authors perform a series of functional perturbations using mutational analyses at the native locus of apterous (ap), and perform tissue-specific enhancer disruption via dCas9 expression. This innovative approach allowed them to explore the spatio-temporal requirements of an apterous enhancer. Combining these techniques allowed the authors to explore the molecular basis of apterous expression, connecting the genotypes to the phenotypical effects of enhancer perturbations. To me, this paper was a beautiful example of what can be done using modern drosophila genetics to understand classic questions in developmental biology and transcriptional regulation.

In sum, this was a rigorous paper bridging scales from the molecular to phenotypes, with new insight into how enhancers control compartmental boundary positioning during Drosophila wing development.

Reviewer #3 (Public Review):

In this manuscript, authors use the Drosophila wing as a model system and combine state-of-the-art genetic engineering to identify and validate the molecular players mediating the activity of one of the cis-regulatory enhancers of the apterous gene involved in the regulation of its expression domain in the dorsal compartment of the wing primordium during larval development.

(1) The authors raise two very important questions in the Introduction: (1) who is locating the relative position of the AP and DV boundaries in the developing wing, and (2) who is responsible for the maintenance of the apterous expression domain late in larval development. None of these two questions have been responded to and, indeed, the summary of the work (as stated in the conclusions of the last paragraph of the Introduction) does not resolve any of these questions.

(2) The authors have identified two different regions whose deletions give very interesting phenotypes in the adult wing (AP identify change & outgrowths, and loss of wing), and have bioinformatically identified and functionally verified 4 TFs that mediate the activity of these regions by their capacity to phenocopy the wing phenotype. While identification of the 2 TFs acting on the m1 is incremental with respect to previous work on the identification of the enhancer responsible for the early expression of Ap, identification of Antp and Grn does not explain the loss of function phenotype of the m3 enhancer. Does any of these results shed any light on the first two Qs? Do these results explain the compartment boundary position in the wing as stated in the title? Expression of lacZ reporter assays is fundamental to demonstrate their model of Figure 8. The reduction of the PD compartment is difficult to understand by the sole reduction in ap expression in this region (which has not been demonstrated).

(3) The authors state in one of the sections "Spatio-temporal analysis of apE via dCas9 ". No temporal manipulation of gene activity is shown. The authors should combine GAL4/UAs with the Gal80ts to demonstrate the temporal requirements of Antp/Grn and Pnt/Hth as depicted in their model of Figure 8.

(4) The authors have not managed to explain the AP phenotype. Thus, this work opens many unresolved questions and does not resolve the title, which is a big overstatement. Thus, strengths (technically excellent), weakness (there is not much to learn about wing development and apterous regulation from these results besides the incremental identification of 4 additional TFs mediating the regulation of ap expression by their ability to phenocopy regulatory mutations of the apterous gene).

Joint Public Review:

In this work Wu, J., et al., highlight the importance of a previously overlooked region on kinases: the αC-β4 loop. Using PKA as a model system, the authors extensively describe the conserved regulatory elements within a kinase and how the αC-β4 loop region integrates with these important regulatory elements. Previous biochemical work on a mutation within the αC-β4 loop region, F100A showed that this region is important for the synergistic high affinity binding of ATP and the pseudo substrate inhibitor PKI. In the current manuscript, the authors assess the importance of the αC-β4 loop region using computational methods such as Local Spatial Pattern Alignment (LSP) and MD simulations. LSP analysis of the F100A mutant showed decreased values for degree centrality and betweenness centrality for several key regulatory elements within the kinase which suggests a loss in stability/connectivity in the mutant protein as compared to the WT. Additionally, based on MD simulation data, the side chain of K105, another residue within the αC-β4 loop region had altered dynamics in the F100A mutant as compared to the WT protein. While these changes in the αC-β4 loop region seem to be consistent with the previous biochemical data, the results are preliminary and the manuscript can be strengthened (as the authors themselves acknowledge) with additional experiments. Specific comments/concerns are listed below.

1. MD simulations were carried out using a binary complex of the catalytic subunit of PKA and ATP/Mg and not the ternary complex of PKA, ATP/Mg and PKI. MD simulations carried out using the ternary complex instead of the binary complex would be more informative, especially on the role of the αC-β3 loop region in the synergistic binding of ATP/Mg and PKI.

2. The LSP analysis shows a decrease in degree centrality for the αC-β4 loop region in the F100A mutant compared to the WT protein which suggests a gain in stability in this region for the F100A mutant (Fig. 8A). These results seem to be contradictory to the MD simulation data which shows the side chain dynamics of K105 destabilizes the αC-β4 loop region in the F100A mutant (Fig. 10B). It would be helpful if the authors could clarify this apparent discrepancy.

3. The foundation for the experiments carried out in this paper are based on previous NMR and computational data for the F100A mutant. However, the specific results and conclusions from these previous experiments are not clearly described.

Reviewer #1 (Public Review):

Summary:<br /> This work seeks to isolate the specific effects of phosphoinositide 3-kinase (PI3K) on the trafficking of the ion channel TRPV1, distinct from other receptor tyrosine kinase-activated effectors. It builds on earlier studies by the same group (Stein et al. 2006; Stratiievska et al. 2018), which described the regulatory relationship between PI3K, nerve growth factor (NGF), and TRPV1 trafficking. A central theme of this study is the development of methods that precisely measure the influence of PI3K on TRPV1 trafficking and vice versa. The authors employ a range of innovative methodologies to explore the dynamics between TRPV1 and PI3K trafficking.

Strengths:<br /> A major strength of this study is the application of innovative methods to understand the interaction between PI3K and TRPV1 trafficking. The key techniques presented include:

1) The optogenetic trafficking system based on phytochrome B, introduced in this research. Its interaction mechanism, dependent on reversible light activation, is comprehensively explained in Figures 1 and 2, with the system's efficacy demonstrated in Figure 3.

2) An extracellular labeling method using click chemistry, which although not exclusive to this study, introduces specific reagents engineered for membrane impermeability.

The central biological insight presented here is the sufficiency of PI3K activation to guide TRPV1 trafficking to the plasma membrane. An additional notable discovery is the potential regulation of insulin receptors via this mechanism.

The paper's strengths are anchored in its innovative methodologies and the valuable collaboration between groups specializing in distinct areas of research.

Weaknesses:<br /> The paper might benefit from a more streamlined structure and a clearer emphasis on its findings. A possible way to enhance its impact might be to focus more on its methodological aspects. The methodological facets stand out as both innovative and impactful. These experiments are well-executed and align with biological expectations. It's evident how these techniques could be tailored for many protein trafficking studies, a sentiment echoed in the manuscript (lines 287-288). When seen through a purely biological lens, some findings, like those concerning the PI3K-TRPV1 interaction, are very similar to previous work (Stratiievska et al. 2018). A biological focus demands further characterization of this interaction through mutagenesis. Also, the incorporation of insights on the insulin receptor feels somewhat tangential. A cohesive approach could be to reshape the manuscript with a primary focus on methodology, using TRPV1 and InsR as illustrative examples.

Reviewer #2 (Public Review):

Summary:<br /> The authors hypothesized that the interaction between TRPV1 and PI3K directly influenced PI3K activity along with increasing TRPV1 trafficking to the membrane. Previous results showed that PI3K could interact with one of the ankyrin repeat domains, however it was unclear whether the direct interaction influenced PI3K activity.

Strengths:<br /> A major strength of the paper is the innovative combination of techniques. The first technique used the optogenetic PhyB/PIF system. They anchored PhyB to the membrane and fused PIF with the interSH2 domain from PI3K. This allowed them to use 650nm light to induce an interaction between the PhyB and PIF resulting in a recruitment of the endogenous PI3K to the membrane through the iSH2 domain without actual activation of an RTK. This allowed them to dissect out one function, just PI3K recruitment/activation from the vast number of RTK downstream cascades.

The second technique was the development of a new non-canonical amino acid that is cell-impermeant. The authors synthesized the sTSO-sulfa-Cy5 compound that will react with the Tet3 ncAA through click chemistry. They showed that the sulfa-Cy5 did not cross the membrane and would be used to track protein production over time, though the reaction rates were slow as noted by the authors. The comparison of the sulfa-Cy5 data with the standard GFP with TIRF showed a clear difference indicating the useful information that is gained with the ncAA.

Weaknesses:<br /> To monitor the phosphatidylinositol-3,4,5-trisphosphates, the pleckstrin homology (PH) domain from Akt was used. This PH domain is not specific for just PI(3,4,5)P3 as stated by the authors. The Akt PH domain also binds PI(3,4)P2. The observed PI3K localization increase will also increase PI(3,4)P2 concentrations so the observed responses may not be solely because of PI(3,4,5)P3.

The data in Figure 4 supplement was confusing to interpret since it is unclear whether a membrane protein with the Tet3 is being expressed at the same time as the ncAA for labeling or if the observed labeling is endogenous. If the observed labeling in Figure 4 supplement D is endogenous, then significant concerns come up regarding the background labeling of the sTCO-sulfo-Cy5 used in the rest of the experiments.

Even with the weaknesses, I believe the authors did achieve their goal of investigating the reciprocity between TRPV1 and PI3K. Their results support their conclusions and will help understand how TRPV1 is regulated by signals other than the traditional channel activators. The tools developed in the article will be of use to the broader cell biology and biophysics community, not just the channel community. The opto control of the PhyB/PIF system makes it more convenient than other systems since it does not take the typical wavelengths needed for fluorescence. The cell-impermeant ncAA will also be a great tool for those studying membrane proteins, protein trafficking and protein dynamics.

Reviewer #3 (Public Review):

Summary: In this manuscript, Koh, Stratiievska, and their colleagues investigate the mechanism by which TRPV1 channels are delivered to the plasma membrane following the activation of receptor tyrosine kinases, specifically focusing on the NGF receptor. They demonstrate that the activation of the NGF receptor's PI3K pathway alone is sufficient to increase the levels of TRPV1 at the plasma membrane.

Strengths: The authors employ cutting-edge optogenetic, imaging, and chemical-biology techniques to achieve their research goals. They ingeniously use optogenetics to selectively activate the PI3K pathway without affecting other NGF pathways. Additionally, they develop a novel, membrane-impermeable fluorescent probe for labeling cell-surface proteins through click-chemistry.

Weaknesses: Previous research, including work by the authors themselves, has already established that PI3K activation is required for NGF-induced TRPV1 trafficking to the plasma membrane. Moreover, the paper suffers from issues such as subpar writing quality, a lack of statistical analysis, and insufficient control experiments, which dampen the reviewer's enthusiasm.

Reviewer #1 (Public Review):

The authors start from the premise that neural circuits exhibit "representational drift" -- i.e., slow and spontaneous changes in neural tuning despite constant network performance. While the extent to which biological systems exhibit drift is an active area of study and debate (as the authors acknowledge), there is enough interest in this topic to justify the development of theoretical models of drift.

The contribution of this paper is to claim that drift can reflect a mixture of "directed random motion" as well as "steady state null drift." Thus far, most work within the computational neuroscience literature has focused on the latter. That is, drift is often viewed to be a harmless byproduct of continual learning under noise. In this view, drift does not affect the performance of the circuit nor does it change the nature of the network's solution or representation of the environment. The authors aim to challenge the latter viewpoint by showing that the statistics of neural representations can change (e.g. increase in sparsity) during early stages of drift. Further, they interpret this directed form of drift as "implicit regularization" on the network.

The evidence presented in favor of these claims is concise. Nevertheless, on balance, I find their evidence persuasive on a theoretical level -- i.e., I am convinced that implicit regularization of noisy learning rules is a feature of most artificial network models. This paper does not seem to make strong claims about real biological systems. The authors do cite circumstantial experimental evidence in line with the expectations of their model (Khatib et al. 2022), but those experimental data are not carefully and quantitatively related to the authors' model.

To establish the possibility of implicit regularization in artificial networks, the authors cite convincing work from the machine-learning community (Blanc et al. 2020, Li et al., 2021). Here the authors make an important contribution by translating these findings into more biologically plausible models and showing that their core assumptions remain plausible. The authors also develop helpful intuition in Figure 4 by showing a minimal model that captures the essence of their result.

In Figure 2, the authors show a convincing example of the gradual sparsification of tuning curves during the early stages of drift in a model of 1D navigation. However, the evidence presented in Figure 3 could be improved. In particular, 3A shows a histogram displaying the fraction of active units over 1117 simulations. Although there is a spike near zero, a sizeable portion of simulations have greater than 60% active units at the end of the training, and critically the authors do not characterize the time course of the active fraction for every network, so it is difficult to evaluate their claim that "all [networks] demonstrated... [a] phase of directed random motion with the low-loss space." It would be useful to revise the manuscript to unpack these results more carefully. For example, a histogram of log(tau) computed in panel B on a subset of simulations may be more informative than the current histogram in panel A.

Reviewer #2 (Public Review):

Summary:

In the manuscript "Representational drift as a result of implicit regularization" the authors study the phenomenon of representational drift (RD) in the context of an artificial network that is trained in a predictive coding framework. When trained on a task for spatial navigation on a linear track, they found that a stochastic gradient descent algorithm led to a fast initial convergence to spatially tuned units, but then to a second very slow, yet directed drift which sparsified the representation while increasing the spatial information. They finally show that this separation of timescales is a robust phenomenon and occurs for a number of distinct learning rules.

Strengths:

This is a very clearly written and insightful paper, and I think people in the community will benefit from understanding how RD can emerge in such artificial networks. The mechanism underlying RD in these models is clearly laid out and the explanation given is convincing.

Weaknesses:

It is unclear how this mechanism may account for the learning of multiple environments. The process of RD through this mechanism also appears highly non-stationary, in contrast to what is seen in familiar environments in the hippocampus, for example.

Reviewer #3 (Public Review):

Summary:

Single-unit neural activity tuned to environmental or behavioral variables gradually changes over time. This phenomenon, called representational drift, occurs even when all external variables remain constant, and challenges the idea that stable neural activity supports the performance of well-learned behaviors. While a number of studies have described representational drift across multiple brain regions, our understanding of the underlying mechanism driving drift is limited. Ratzon et al. propose that implicit regularization - which occurs when machine learning networks continue to reconfigure after reaching an optimal solution - could provide insights into why and how drift occurs in neurons. To test this theory, Ratzon et al. trained a Feedforward Network to perform the oft-utilized linear track behavioral paradigm and compare the changes in hidden layer units to those observed in hippocampal place cells recorded in awake, behaving animals.

Ratzon et al. clearly demonstrate that hidden layer units in their model undergo consistent changes even after the task is well-learned, mirroring representational drift observed in real hippocampal neurons. They show that the drift occurs across three separate measures: the active proportion of units (referred to as sparsification), spatial information of units, and correlation of spatial activity. They continue to address the conditions and parameters under which drift occurs in their model to assess the generalizability of their findings. However, the generalizability results are presented primarily in written form: additional figures are warranted to aid in reproducibility. Last, they investigate the mechanism through which sparsification occurs, showing that the flatness of the manifold near the solution can influence how the network reconfigures. The authors suggest that their findings indicate a three-stage learning process: 1) fast initial learning followed by 2) directed motion along a manifold which transitions to 3) undirected motion along a manifold.

Overall, the authors' results support the main conclusion that implicit regularization in machine learning networks mirrors representational drift observed in hippocampal place cells. However, additional figures/analyses are needed to clearly demonstrate how different parameters used in their model qualitatively and quantitatively influence drift. Finally, the authors need to clearly identify how their data supports the three-stage learning model they suggest. Their findings promise to open new fields of inquiry into the connection between machine learning and representational drift and generate testable predictions for neural data.

Strengths:

1) Ratzon et al. make an insightful connection between well-known phenomena in two separate fields: implicit regularization in machine learning and representational drift in the brain. They demonstrate that changes in a Feedforward Network mirror those observed in the brain, which opens a number of interesting questions for future investigation.

2) The authors do an admirable job of writing to a large audience and make efforts to provide examples to make machine learning ideas accessible to a neuroscience audience and vice versa. This is no small feat and aids in broadening the impact of their work.

3) This paper promises to generate testable hypotheses to examine in real neural data, e.g., that drift rate should plateau over long timescales (now testable with the ability to track single-unit neural activity across long time scales with calcium imaging and flexible silicon probes). Additionally, it provides another set of tools for the neuroscience community at large to use when analyzing the increasingly high-dimensional data sets collected today.

Weaknesses:

1) Neural representational drift and directed/undirected random walks along a manifold in ML are well described. However, outside of the first section of the main text, the analysis focuses primarily on the connection between manifold exploration and sparsification without addressing the other two drift metrics: spatial information and place field correlations. It is therefore unclear if the results from Figures 3 and 4 are specific to sparseness or extend to the other two metrics. For example, are these other metrics of drift also insensitive to most of the parameters as shown in Figure 3 and the related text? These concerns could be addressed with panels analogous to Figures 3a-c and 4b for the other metrics and will increase the reproducibility of this work.

2) Many caveats/exceptions to the generality of findings are mentioned only in the main text without any supporting figures, e.g., "For label noise, the dynamics were qualitatively different, the fraction of active units did not reduce, but the activity of the units did sparsify" (lines 116-117). Supporting figures are warranted to illustrate which findings are "qualitatively different" from the main model, which are not different from the main model, and which of the many parameters mentioned are important for reproducing the findings.

3) Key details of the model used by the authors are not listed in the methods. While they are mentioned in reference 30 (Recanatesi et al., 2021), they need to be explicitly defined in the methods section to ensure future reproducibility.

4) How different states of drift correspond to the three learning stages outlined by the authors is unclear. Specifically, it is not clear where the second stage ends, and the third stage begins, either in real neural data or in the figures. This is compounded by the fact that the third stage - of undirected, random manifold exploration - is only discussed in relation to the introductory Figure 1 and is never connected to the neural network data or actual brain data presented by the authors. Are both stages meant to represent drift? Or is only the second stage meant to mirror drift, while undirected random motion along a manifold is a prediction that could be tested in real neural data? Identifying where each stage occurs in Figures 2C and E, for example, would clearly illustrate which attributes of drift in hidden layer neurons and real hippocampal neurons correspond to each stage.

Reviewer #1 (Public Review):

C. elegans is a pre-eminent model for developmental genetics, and its invariant lineage makes it possible in theory to define molecular features such as gene expression comprehensively and at single cell resolution across the organism.

Previously published single-cell RNA-seq studies have mapped gene expression across the lineage through the 16-cell stage (Tintori et al 2017, Hashimshony et al 2016), and at later stages (Packer et al 2019, with good coverage starting at the 100-cell stage and some coverage at the ~50-cell stage). This left the critical period around gastrulation (~28-cell and ~50-cell) without comprehensive transcriptome data. This study covers this gap with a heroic effort involving the manual isolation and analysis of over 800 cells from embryos of known stage, combined with painstaking curation using known markers from small scale studies and larger imaging-based expression atlases. Importantly, the dataset overlaps at early and late stages with data prior studies.

The data quality and overlap with Tintori and Packer datasets both appear high, but to make this inference required additional analysis from Supplemental Table 6 by this reviewer as it is not explored or described in the manuscript. Analyses demonstrating continuity with these datasets would greatly increase the value of the resource.

The authors show that specific lineages and stages preferentially express TFs with different classes of DNA binding domains. This extends previous work implicating homeodomains as preferentially involved in nervous system patterning and as enriched in neural and muscle progenitors in mid-stage embryos.

They also show that C. elegans homologs of Drosophila early embryonic regulators (which function based on spatial position in that system) tend to also be patterned in early C. elegans embryos, but with lineage-specific patterns. This conserved use of regulators would be fairly remarkable given the dramatically different developmental modes in these two species, although this observation is not backed up by quantitative analyses.

Finally, there is an argument that combinations of TFs expressed in lineage-specific patterns give rise to "stripe" patterns. This section is also not based on statistical analyses but suggests the possibility that lineage and positional regulation may be more convoluted than was previously thought.

Reviewer #2 (Public Review):

The C. elegans embryo has been model system of study for more than 30 years because of the ease of doing forward and reverse genetics, coupled with its nearly invariant lineage which allows a description of development at high resolution. 4D time lapse imaging coupled with spatially resolved gene expression has enabled identification of transcriptional signatures of cells in space and time, and in the past decade this has been advanced with single-cell transcriptomics methods, using individually isolated embryonic cells (which can retain their identity) or by deconvolving complex mixtures of early cells. Recent work using these methods has resolved spatiotemporal expression patterns for many genes, defining cells up to gastrulation stage, but then changing to more tissue-specific patterns during morphogenesis. A key paradigm of specification in C. elegans and other systems is that early maternal factors initiate or restrict patterns of transcription factor expression from the zygotic genome. Combinatorial expression patterns and some symmetries broken by autonomous or extrinsic cell inductions ultimately program lineages towards their fates. To date, only simple networks have been elucidated, as the increasing complexity of these networks and the high level of redundancy has made functional dissection of such pathways difficult. Hence, almost all of the work in recent years has been descriptive.

In this work the authors fill a knowledge gap from the early embryo (~16 cells) to the ~100-cell stage and describe new patterns of gene expression. They reconcile their findings with that of others who have defined expression patterns using other methods, such as scRNA-Seq from complex mixtures of cells, and from transcription factor expression analyses. The resulting description of embryonic develop is the most precise to date, and offers a potentially useful resource for other researchers.

The authors attempt to use their results to find patterns of gene expression that could hint at phylogenetic conservation of specification mechanisms. They find some supporting evidence that expression of homeobox genes occurs in anterior-posterior stripes, which recalls the elaborate A/P patterning system elucidated in the Drosophila embryo, which belongs to the sister phylum Arthropoda in the Ecdysozoan clade of molting animals. It felt as if the authors chose the Hox genes they need to support this conclusion.

Some caveats exist to the work. The expression patterns seem to be well-validated, and following prior work from the Yanai group are likely to be strongly correlated with expression in living embryos. When cells are separated, they could lose some expression patterns that require cell-cell interactions, so it is expected that there might be a small minority of expression patterns that are more complex than what has been documented here.

A major caveat is the idea of the stripes of Hox expression. I just did not find these arguments to be compelling. Seeing these 'stripes' requires organizing the data in a way that maximizes their appearance, for one. Since there is not a lot of movement of cells away from their birth in the early embryo, the AB descendants are anterior to those of MS, anterior to those of E, anterior to those of C, D, and P4. Lineage-specific expression will just naturally fall into 'stripes'. Second, the conservation of Hox expression patterns typically comes with collinearity of the genes along the length of a chromosome (i.e. the so-called Hox clusters) with expression along the body axis, as well as posterior-to-anterior fate transformations when Hox specification is disrupted.

A minor note is the detection of an enrichment of GATA factors in the early E lineage. This has now been found to be a derived condition even within the genus (see Broitman-Maduro et al. Development 149 (21): dev200984, as other species like C. angaria show only a simpler network of elt-3 -> elt-2. This suggests that many of the other patterns of gene expression, particularly in the early embryo, could be highly derived as well; some caution is warranted in generalizing the results as being conserved with arthropods as some of this could be convergent.

Given what the authors are proposing about Hox stripes, some omissions of prior work were surprising (or maybe I missed them). For example, a comprehensive study of Hox genes in C. elegans by Hench et al. (2015) (PLoS One 10(5): e0126947) evaluated all the homeobox genes and examined their genomic locations and expression patterns in the embryo at high spatiotemporal resolution. Work from the Hobert lab (Nature 2020, 584(7822):595-601) showed how homeobox codes specify classes of C. elegans neurons, and the Murray lab (PLoS Genet. 18(5):e1010187) examined Hox control of posterior lineage specification at high resolution, with functional assays.

The Discussion section of the paper is brief, consistent with the descriptive nature of the work overall, but it would have been nice to see the findings related to other published studies as indicated above.

Reviewer #3 (Public Review):

The authors claim that this dataset covers a timepoint of embryogenesis that is not well covered in the other published single cell datasets (Tintori et al 2016 and Packer et al 2019). The Tintori data indeed do not cover the 28-102-cell stages sufficiently, but it is unclear how the data presented here compare to the Packer et al data. It is true that the Packer et al data have fewer cells at earlier timepoints than at later ones, but given that they sequenced tens of thousands of cells, they report that they still have ~10,000 cells <210 min of embryogenesis. It seems that if the authors want to make any claims about how their data enables exploration of a stage that was previously not accessible, this would require a better comparison to the available data.

The authors provide thorough support for how they assigned cell identities in their data. It is surprising though that at the 102-cell stage they only identify 37 unique cell identities. They suggest that this is because there are many equivalence groups at this stage. However, I would strongly encourage the authors to perform a similar analysis or otherwise compare their obtained identities with the data from Packer et al. 2019. It seems possible that given the low number of cells in this dataset, the authors are missing certain identities and it would be important to know this.

The main analysis the authors perform is to look at expression patterns of various classes of TFs and ask whether they are enriched in particular lineages or at specific timepoints. This analysis is interesting but would be more informative if the authors provided in Figure 3d the numbers of each class of TFs. The authors then focus on the homeodomain class of TFs as they display interesting lineage-specific expression patterns, which when mapped on the embryo form stripes. The stripe pattern however is not that obvious, at least not as shown in Figure 4b. Perhaps separate embryo schematics showing the different TF expression patterns would show this more clearly. Moreover, given the relatively small number of cell identities found in this dataset (particularly at the 102-cell stage), a similar analysis using the Packer data would provide further support to these patterns. The localization of cells with shared expression patterns does show a stripe pattern at the 28-cell stage, but also not so clearly beyond this timepoint.

I am also unsure about the validity/value of the comparison of the stripes to Drosophila and the centrality of homeodomain TFs to anterior-posterior positional identity. First, it would be important to map other TFs, very likely there are several other TFs that correlate with positional identity. Also, even if the expression of the homeodomain TFs in C. elegans form stripes, there are still several cells within that stripe that do not express these TFs, it is thus unclear whether these TFs encode positional information or the identity of cells with different positions in the embryo.

Reviewer #4 (Public Review):

This is an admirable piece of work. The authors build on a previous dataset they assembled, but expand it to include all stages of early development in the nematode Caenorhabditis elegans. Cell collection was done manually, which is very impressive, and is clearly far better than pooled unidentified cells. I will not comment on the specific sequencing and analysis, since this is not my expertise, but will comment on the general conclusions and comparative framework in which the authors place their results.

While the Introduction and Discussion sections are actually fairly short, much of the presentation of the results is based on a certain comparative framework, which is explicitly a comparison between C. elegans and Drosophila melanogaster. This is an important perspective, but I feel the authors' interpretation is in some places exaggerated and in other places almost trivial.

Drosophila and C. elegans are two of the main models for developmental biology. However, it has been clear for over two decades that both species are highly derived and specialized and therefore, treating them as representative for their taxa is problematic. Much of the authors' discussion hinges on the question of comparing syncytial and lineage-dependent development. The syncytial early development of Drosophila is very specific and is clearly a recent innovation within a restricted group of flies. The canonical Drosophila segmentation cascade is mostly a novelty and most elements within the cascade are recent. Specifically, the expression of gap genes in regional stripes is not found very broadly. Conversely, the polarizing role of Caudal is very ancient and is probably found in all Bilateria. When making comparisons with a distantly related species, it is important to keep this in mind. Not as much is known about development of other nematodes, but the little that is known indicates that C. elegans is also unusual, and specifically the eutelic development (conserved cell lineages in development) is not found in all nematodes.

The authors suggest that regional expression of transcription factors in stripes is a conserved characteristic of development. This is true for Hox genes and has been known for decades. The regional expression they show for other genes is not convincing as "stripes". It is no surprise that developmental transcription factors are regionalized, but linking this to the stripes of Drosophila gap genes and even more so to Drosophila pair-rule and segment-polarity genes is a bit far-fetched. Yes, many genes are expressed in restricted domains along the A-P axis, but that is all that can be said based on the data. Calling them "Drosophila-like" is unfounded.

Reviewer #2 (Public Review):

There are reports that patients experience hematologic improvement after treatment with iron chelators but the mechanism of this improvement and the specific patient category that benefits are not known. This article uses a mouse model of MDS to explore the mechanism by which chelator therapy may lead to improved erythropoiesis. Although many changes were seen in the MDS mouse model treated with deferiprone, a causal mechanism was not demonstrated.

The authors provide solid evidence for the following:<br /> 1. The NUP98-HOXD13 mouse model of MDS recapitulates spontaneous (non-transfusion related) iron overload seen in some subtypes of MDS<br /> 2. In this model, iron chelation with deferiprone (DFP) improves not only iron overload but also improves anemia, decreases splenomegaly, decreases erythropoietin concentrations and makes erythropoiesis more effective<br /> 3. DFP treatment does not change hepcidin mRNA but increases it relative to the iron load. Consistently, DFP treatment also lowers the expression of erythroferrone mRNA in erythroblasts.<br /> 4. DFP lowers erythroblast reactive oxygen species

The authors identify a number of changes that result from iron chelation in their model but do not causally link them to the improvements in iron overload, anemia or ineffective erythropoiesis:<br /> 5. DFP alters the expression of GATA-1, Bcl-XI, EpoR, TfR1 but not TfR2, as well as intracellular iron chaperone Pcbp1, and the cargo receptor Ncoa4<br /> 6. Analyses of the same genes in human CD34+ selected bone marrow samples from unclassified MDS patients are shown but no conclusion or comparison is (or can be) made to the mouse data.<br /> 7. The data therefore do not provide a mechanistic explanation of the effect of DFP on anemia and ineffective erythropoiesis

The manuscript has significant strengths and several substantial weaknesses. The strengths include the establishment of a mouse MDS model that manifests anemia, ineffective erythropoiesis and non-transfusional iron overload, with increased erythroferrone and inadequate hepcidin response to iron overload, features that improve after treatment with deferiprone. The main structural weakness is that the many changes in erythroid pathways documented in the manuscript do not establish the mechanism by which deferiprone mediates these beneficial effects.

Reviewer #1 (Public Review):

Myelodysplastic syndrome (MDS) represents as a rather complex and serious hematologic malignancy that affects the production of normal blood cells in the bone marrow. Some types of MDS could stay mild for years and other types of MDS could be more serious and progressed into AML. Tremendous efforts have been made to investigate the pathogenesis and treatment of MDS. For instance, a pile of papers has found that iron chelation therapy could benefit the overall survival in low risk MDS patients. Yet, the risk and benefit of this therapy remain in much debate. The authors demonstrated that erythrocyte precursors could re-gain EPO responsiveness after DFP chelation therapy. In addition, the authors investigated iron trafficking in erythroblasts using the MDS mouse model. The paper is rather interesting as it discussed the biological effects and underlying mechanisms of DFP for the treatment of low-risk MDS. More importantly, the paper adds practical values and theoretical evidences for chelation therapy towards low-risk MDS. The paper is overall well-written.

Reviewer #3 (Public Review):

Myelodysplastic syndrome (MDS) is a heterogenous, clonal hematopoietic stem cell disorder characterized by morphological dysplasia in one or more hematopoietic lineages, cytopenias (most frequently anemia), and ineffective hematopoiesis. In patients with MDS, transfusion therapy treatment causes clinical iron overload; however it has been unclear if treatment with iron chelation yields clinical benefits. In the present study, the authors use a transgenic mouse model of MDS, NUP98-HOXD13 (referred to here as "MDS mice") to investigate this area. Starting at 5 months of age (before MDS mice progress to acute leukemia), the authors administered DFP in the drinking water for 4 weeks, and compared parameters to untreated MDS mice and WT controls.

The authors first show that MDS mice exhibit systemic iron overload and macrocytic anemia that is improved by treatment with the iron chelator deferiprone (DFP). They then perform a detailed characterization the effects of DFP treatment on erythroid differentiation and various parameters related to iron transport and trafficking in MDS erythroblasts. Strengths of the work are the use of a well-characterized mouse model of MDS with appropriate animal group sizes and detailed analyses of systemic iron parameters and erythroid subpopulations. A remediable weakness is that in certain areas of the Results and Discussion, the authors overinterpret their findings by inferring causation when they have only shown a correlation. Additionally, when drawing conclusions based on changes in erythroblast mRNA expression levels between groups, the authors should consider that translation efficiency may be altered in MDS and that the NUP98 fusion protein itself, by acting as a chimeric transcription factor, may also impact gene expression profiles. Given that the application of chelators for treatment of MDS remains controversial, this work will be of interest to scientists focused on erythroid maturation and iron dysregulation in MDS, as well as clinicians caring for patients with this disorder.

Major Comments

1. The authors define the stages of erythroblast differentiation using the CD44-FSC method, which assumes that CD44 expression levels during the stages of erythroid differentiation are not altered by MDS itself. Are morphologically abnormal erythroblasts, such as bi-nucleate forms, captured in this analysis, and if so, are they classified in the appropriate subset? The percentage of erythroblasts in the bone marrow of MDS mice in this current study is lower than that reported by Suragani et al (Nat Med 2014), who employed a different strategy to define erythroid precursors. While representative erythroblast gating is presented as Supplemental Figure 17, it would be important to present representative gating from all 3 animal groups: WT, MDS, and MDS+DFP mice.

2. Methods, "Statistical analysis." The authors state that all comparisons were done with 2-tailed student paired t test, which would not be appropriate for comparisons being made between independent animals groups (i.e. when groups are not "paired").

3. The Results (p.7) indicates that both sexes showed similar responses to DFP; however, the figure legends do not indicate sex. Given that systemic iron metabolism in mice shows sex-related differences, sex should be specified.

Reviewer #1 (Public Review):

In this manuscript, the authors have performed extensive imaging analysis of six human histone H1 variants, their enrichment and localization, their differential dynamics during interphase and mitosis, and their association with lamina-associated domains (LADs) or nucleolus-associated domains. The manuscript is well-written with high-quality confocal and super-resolution images. Various interesting observations are made on distribution patterns of H1 variants. H1.2, H1.3, and H1.5 are shown to be universally enriched at the nuclear periphery whereas H1.4 and H1X are found to be distributed throughout the nucleus. Interestingly, H1X was the only H1 variant found to be abundant in nucleoli. Depletion of H1 variants has been shown to affect chromatin structure in a variant-specific manner, with H1.2 knock-down resulting in global chromatin decompaction. Overall, the study presents several interesting insights on H1 variants conducted in a large number of cell lines.

Major Comments:<br /> 1) Though the co-immunostaining of a nucleolar marker (NPM1) is performed with H1X, it would be interesting to explore the localization of H1 variants with respect to some of the proteins critically involved in chromatin organization such as PC4 or HP1alpha. Since the phosphorylated form of PC4 has been shown to interact with H1, which variants specifically interact with PC4 and how their dynamic changes in interphase and mitosis would be worth exploring.

2) The manuscript would be a complete study if any physiological significance with the H1 variant distribution could be shown.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Salinas-Pena et. al examines the distribution of a subgroup of histone H1 variants primarily with the use of high-resolution microscopy. The authors find that while some H1s have a universal distribution pattern, some display a preference for discrete regions within the nuclear landscape namely, the periphery, the center, or the nucleolus. They also show that using the various H1s within a cell did not colocalize significantly with each other, rather, they occupy discrete 'nanodomains' throughout the nucleus which is visualized as a punctate signal.

The authors present evidence relating to a long-standing question in the field regarding the spatial distribution of the different H1 variants. Since reliable, specific antibodies toward the variants were unavailable, this question was unable to elicit a definitive answer. This study uses more recently available antibodies against endogenous H1s to put together a systematic and comprehensive view of a group of H1 variant distribution inside a nucleus and ties it with previously generated genome-wide data to demonstrate localization and some functional heterogeneity.

Strengths of the study.<br /> 1. First systematic, high-resolution view of H1 variants providing a significant advance towards the long hypothesized functional differences between H1 variants.<br /> 2. The use of endogenous antibodies allows the authors to bypass the need to use tagged proteins or overexpression strategies to study H1 distribution.<br /> 3. The availability of genome-wide H1 distribution data for the variants using the endogenous H1 antibodies to strengthen the presented visual data.

Weakness of the study.<br /> One of the major reasons for slow progress in deciphering variant-specific function has been the dearth of quality, specific, antibodies. This study is heavily dependent on the antibody function and its ability to accurately report on the distribution. However, appropriate controls to confirm the specificity were not included. Commercially available antibodies are equally susceptible to quality issues.

Impact:<br /> This study sets the stage for an exciting avenue of H1 study where variant-specific cellular functions can be explored which has otherwise been severely understudied.

Reviewer #3 (Public Review):

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

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

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

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

Another uncertainty in both the ChIP and immunofluorescence datasets is the accessibility of the epitope. This weakness is highlighted by the apparent loss of H1.2 and H1.4 in mitotic chromosomes which is revealed to be false by the detection of the phosphorylated species. The distributions relative to the surface of chromosomes in mitosis and the depletion of H1.2, H1.3, and H1.5 from the central regions of interphase nuclei reveal an unusual dissipation of the staining that is suggestive of antibody accessibility or potentially overstaining and quenching of the fluorescence in the center of highly stained structures. The overall image quality of the immunofluorescence images is poor.

Reviewer #1 Public Review

Summary<br /> This paper presents a new, but simple and low-cost technique for multimodal EM imaging that combines the strengths of both volume scanning electron microscopy (SEM) and electron microscopic tomography. The novel ATUM-Tomo approach enables the consecutive inspection of selected areas of interest by correlated serial SEM and TEM, optionally in combination with CLEM, as demonstrated here. The most important feature of ATUM-Tomo, particularly of correlative ATUM-Tomo, is that it can bridge scales, from the cellular to the high-resolution subcellular scale, from micrometer to low nanometer resolution. This is particularly important for ultrastructural analyses of biological regions of interest, which is demonstrated here for focal pathologies or rare cellular and subcellular events. Both imaging modalities are non-destructive, thus allowing re-imaging and hierarchical imaging at the SEM and TEM levels. This is particularly important for precious samples, including human biopsies and samples from complex CLEM experiments. Beyond the demonstrated neuropathology-related application, further use in investigating normal and pathologically altered brains, including human brain tissue samples that require high-resolution SEM and TEM in combination with immunohistochemistry, and virus or tracer injections, would be possible. Thus, ATUM-Tomo provides new possibilities in multimodal volume EM imaging for diverse areas of biological research.

Strengths<br /> This paper is a very nice piece of work, bringing together modern high-end state-of-the-art technology that will allow us to investigate diverse biological questions in different areas of interest and at different scales. The paper is clear and well-written, although some additions are necessary to the methods section and the scientific results as exemplified by investigations of the blood-brain barrier. The discussion would benefit from an expansion of the part dealing with the scientific results. The paper is accompanied by excellent figures, supplemental information, and colored 3D-reconstructions, which makes it easy for the reader to follow the experimental procedure and the scientific context. The authors may consider moving the supplemental figures into the main body of the paper, which would then still contain 'only' eight figures.

Weaknesses<br /> There is some imbalance between the description of the state-of-the-art methodology and the scientific context.

Reviewer #2 Public Review

Summary<br /> Kislinger et al. present a method permitting a targeted, multiscale ultrastructural imaging approach to bridge the resolution gap between large-scale scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The key methodological development consists of an approach to recover sections of resin-embedded material produced by Automated Tape Collecting Ultramicrotomy (ATUM), thereby permitting regions of interest identified by serial section SEM (ATUM-SEM) screening to be subsequently re-examined at higher resolution by TEM tomography (ATUM-Tomo). The study shows that both formvar and permanent marker coatings are in principle compatible with the solvent-based release of pre-screened sections from ATUM tape (carbon nanotubule or Kapton tape). However, a comparative analysis of potential limitations and artifacts introduced by these respective coatings revealed permanent marker to provide a superior coating; permanent marker coatings are more easily and reliably applied to tape with only minor contaminants affecting the recovered section-tape interface with negligible influence on tomogram interpretation. Proof-of-principle is provided by integrating this novel ATUMTomo technique into a technically impressive correlated light and electron microscopy (CLEM) approach specifically tailored to investigate ultrastructural manifestations of trauma-induced changes in blood-brain barrier permeability (Khalin et al., 2022).

Strengths<br /> Schematics and well-constructed figures clearly illustrate the general workflow, light and electron microscope image data are of excellent quality, and the efficacy of the ATUM-Tomo approach is documented by qualitative assessment of ATUM-SEM performance using coated tape variants and a convincing correlation between scanning and transmission electron microscopy imaging modalities. Potential ultrastructural artifacts induced via solvent exposure and any subsequent mechanical stress incurred during section detachment were systematically investigated using appropriate methods and transparently reported. In summary, the presented data are consistent with the study's claims. A major strength of this work includes its general applicability to a broad range of biological questions and ultrastructural targets demanding resolutions exceeding that obtained via serial section and block-face imaging approaches alone. Importantly, this relatively simple and cost-effective technique is widely adopted by electron microscopy laboratories. Its integration into existing ATUM-SEM workflows supports a versatile and non-destructive imaging regime enabling high-resolution details of targeted structures to be interpreted within anatomical and subcellular contexts.

Weaknesses<br /> Given the identified importance of glow-discharge treatment of precoated tape to the flat deposition of sections during ATUM, a corresponding schematic or appropriate reference(s) providing more information about the custom-built tape plasma device would likely be a prerequisite for effective reproduction of this technique in other laboratories.

Reviewer #1 (Public Review):

Sun and co-authors have determined the crystal structures of EHEP with/without phlorotannin analog, TNA, and akuBGL. Using the akuBGL apo structure, they also constructed model structures of akuBGL with phlorotannins (inhibitor) and laminarins (substrate) by docking calculation. They clearly showed the effects of TNA on akuBGL activity with/without EHEP and resolubilization of the EHEP-phlorotannin (eckol) precipitate under alkaline conditions (pH >8). Based on this knowledge, they propose the molecular mechanism of the akuBGL-phlorotannin/laminarin-EHEP system at the atomic level. Their proposed mechanism is useful for further understanding of the defensive-offensive association between algae and herbivores.

Reviewer #2 (Public Review):

In this study the authors try to understand the interaction of a 110 kDa ß-glucosidase from the mollusk Aplysia kurodai, named akuBGL, with its substrate, laminarin, the main storage polysaccharide in brown algae. On the other hand, brown algae produce phlorotannin, a secondary metabolite that inhibits akuBGL. The authors study the interaction of phlorotannin with the protein EHEP, which protects akuBGL from phlorotannin by sequestering it in an insoluble complex.

The strongest aspect of this study is the outstanding crystallographic structures they obtained, including akuBGL (TNA soaked crystal) structure at 2.7 Å resolution, EHEP structure at 1.15 Å resolution, EHEP-TNA complex at 1.9 Å resolution, and phloroglucinol soaked EHEP structure at 1.4 Å resolution. EHEP structure is a new protein fold, constituting the major contribution of the study.

The drawback on EHEP structure is that protein purification, crystallization, phasing and initial model building were published somewhere else by the authors, so this structure represents incremental research.

One concern remains unanswered to me. If the mechanism of action of EHEP is to precipitate together with TNA in a 1:1 insoluble complex, then it does not matter if there are multiple mechanisms involved in the activity assay, the protection of 4uM EHEP against 40uM TNA simply requires a different stoichiometry.

Reviewer #3 (Public Review):

The manuscript by Sun et al. reveals several crystal structures that help underpin the offensive-defensive relationship between the sea slug Aplysia kurodai and algae. These centre on TNA (a algal glycosyl hydrolase inhibitor), EHEP (a slug protein that protects against TNA and like compounds) and BGL (a glycosyl hydrolase that helps digest algae). The hypotheses generated from the crystal structures herein are supported by biochemical assays.

The crystal structures of apo and TNA-bound EHEP reveals the binding (and thus protection) mechanism. The authors then demonstrate that the precipitated EHEP-TNA complex can be resolubilised at an alkaline pH, potentially highlighting a mechanism for EHEP recycling in the A. kurodai midgut. The authors also present the crystal structures of akuBGL, a beta-glucosidase utilised by Aplysia kurodai to digest laminarin in algae into glucose. The structure revealed that akuBGL is composed of two GH1 domains, with only one GH1 domain having the necessary residue arrangement for catalytic activity, which was confirmed via hydrolytic activity assays. Docking was used to assess binding of the substrate laminaritetraose and the inhibitors TNA, eckol and phloroglucinol to akuBGL. The docking studies revealed that the inhibitors bound akuBGL at the glycone-binding suggesting a competitive inhibition mechanism. Overall, most of the claims made in this work are supported by the data presented.

Reviewer #1 (Public Review):

Gambelli et al. provide a structural study of the SlaA/SlaB S-layer of the archaeon Sulfolobus acidocaldarius. S-layers form an essential component of most archaeal cell envelopes, where their self-assembling properties and activity as cell envelope support structures have raised substantial interest, both from researchers seeking to understand the fundamental biology of archaea, as well as researchers seeking to exploit the biomaterial properties of S-layers in biotechnological applications. Both interests are hampered by the paucity of structural information on archaeal S-layer assembly, structure, and function to date, in large part due to technical difficulties in their study.

In this study, Gambelli and coworkers overcome these difficulties and report the high-resolution 3D cryoEM structures of the purified SlaA monomers at three different pH, as well as the medium resolution 3D cryoET structures of the SlaA/SlyB lattices determined from S-layer fragments isolated from the Sulfolobus cells.

The structural work is generally well executed, although lacks in detail in places to allow a proper review, particularly in the cryoET. A further drawback of the current manuscript is that the structural work remains rather descriptive and speculative, with little validation of the proposed models.

The authors run a plethora of representation, analyses, prediction, and simulation software on their structures resulting in an abundance of Figures that risk overloading the reader and in several cases bring little new insight beyond unsubstantiated speculation.

The structural description of the S. acidocaldarius S-layer will be of high general interest and the authors have made a substantial leap forward, but the current manuscript would benefit from a better validation and basic atomic description of the SlaA/SlaB S-layer.

Specific points.

- It is not possible to review the quality of the SlaA and SlaA/SlaB models in the cryoET reconstruction. No detailed fits of the map and model are shown, and no correlation statistics are given (the latter is also true for the higher resolution 3D reconstructions at pH4, 7, and 10). To be of use to the community, the S-layer model and cryoET maps should also be deposited in PDB and EMDB, and an autodep report and ideally the cryoET maps should be available.

- The authors spend a great deal on the MD simulation of the SlaA glycans and the description of the 'glycan shield' and its possible role in subunit electrostatics and intersubunit contacts. This does not result in testable hypotheses, however, and does not bring much more than vague speculation on the role of the glycans or the subunits contacts in S-layer assembly and stability. For the primary description of the SlaA/B S-layer, more important would be a detailed atomic description and validation of the intermolecular contacts in the proposed lattice model. Given the low resolution of the cryoET, this would require MD simulation of the contacts. Lattice stability during MD simulation and/or the confirmation of lattice contacts by cross-linking mass spectrometry would go a great way in validating the proposed lattice model.

- The discussion of the subunit electrostatics and the role they could play in subunit assembly/disassembly remains superficial and speculative. No real model or hypothesis is put forward, let alone validated.

- The authors solve the cryoEM structure of SlaA released and purified form S. acidocaldarius S-layers by an alkaline pH shift. When shifted back to acidic pH, does this native material self-assemble in vitro? If not, do the authors have an explanation for this? Are components missing or could the solved structures represent SlaA conformations that are no longer assembly competent?

Reviewer #2 (Public Review):

Gambelli et al. investigated the surface layer (S-layer) of Sulfolobus acidocaldarius by using combined single particle cryo-electron microscopy (cryoEM), cryo-electron tomography (cryoET), and Alphafold2 predictions to generate an atomic model of this outermost cell envelope structure. As known from previous studies, the two-dimensional lattice comprises two distinct S-layer glycoproteins (SLPs) termed SlaA, the outer component interacting with the harsh living environment of this archaeon, and SlaB, comprising a dominant hydrophobic domain, which anchors this SLP in the cytoplasmic membrane, respectively. The interwoven S-layer lattice of S. acidocaldarius shows a hexagonal lattice symmetry with a p3 topography. It is built very complex as the unit cell constitutes of one SlaB trimer and three SlaA dimers (SlaB3/3SlaA2). Despite the complexity of this distinct proteinaceous S-layer lattice, the authors not only investigated the SLP structures but also considered the glycans in their structure predictions.

The strengths of this study are that it was possible, and the first approach taken, to divide the Y-shaped SlaA SLP, starting from the N-terminus into six domains, D1 to D6. As previous studies revealed that SlaA assembly and disassembly are pH-sensitive processes, the structure of SlaA was investigated at different pH conditions. This approach led to the striking result that the cryoEM maps of SlaA D1 to D4 are virtually identical at the three pH conditions, demonstrating remarkable pH stability of these protein domains. For SlaA at low pH, however, the domains D5 and D6 were too flexible to be resolved in the cryoEM maps. Nevertheless, the authors were able to hypothesize that jackknife-like conformational changes of a link between domains D4 and D5, as well as pH-induced alterations in the surface charge of SlaA play important roles in S-layer assembly.<br /> This study showed in addition, that the surface charges of SlaA shift significantly from positive at acidic pH to negative at basic pH. A comparison of the surface charge between glycosylated and non-glycosylated SlaA showed that the glycans contribute considerably to the negative charge of the protein at higher pH values. This change in electrostatic surface potential may therefore be a key factor in disrupting protein-protein interactions within the S-layer, causing its disassembly as it is highly desired for new practical applications in biomolecular nanotechnology and synthetic biology.<br /> An excellent approach was to use exosomes to determine the structure of the entire S-layer structure comprising of SlaA and SlaB. By this approach, effectively two zones in the SlaA assembly could be distinguished: an outer zone constituted by D1 to D4, and one inner zone formed by D5 and D6. Moreover, for the first time, deeper insights into how SlaA forms the hexagonal and triangular pores within the S-layer lattice of S. acidocaldarius are provided. Very interesting are the found SlaA dimers, which are suggested to be formed by two SlaA monomers through the D6 domains, with each SlaA dimer spanning two adjacent hexagonal pores.

The weaknesses in this work are in the introduction, where the citation is incomplete. In the comparisons drawn between archaeal and bacterial S-layers, basic citations are missing for the latter. One gets the impression that there is a deliberate avoidance of citing individual prominent S-layer research groups here. The same is true for citations of glycosylation of archaeal S-layer proteins and Sulfolobus mutants lacking SlaB.<br /> The authors show many pictures and schematic drawings of high quality. In the main text, these illustrations should be briefly commented on if there is any ambiguity. For example, it is somewhat difficult to understand that in one schematic drawing the angle between the SlaA longitudinal axis and the membrane plane is 28 degrees and at the same time in another schema, the angle of the longitudinal axes in SlaA dimers is given as 160 degrees.<br /> The authors argue that by a pH shift to 10, SlaA disassembles and exists exclusively as a single molecule. The presence of exclusively single SlaA proteins and the purity of the fractions were assessed by SDS/PAGE analysis and cryoEM micrographs. However, one can doubt that, due to the strong denaturing effect of SDS and the subsequent dissociation of protein complexes, SlaA dimers or oligomers could have been determined with SDS/PAGE. Moreover, the shown representative micrographs (supplementary figure 2, a-c) show a heterogeneous structure and thus, do not support the exclusive presence of disassembled SlaA monomers.<br /> An interesting finding is SlaA dimerization. SlaA dimers can obviously be found in co-existence with SlaA-only S-layer as shown in supplementary figure 15. A short discussion on whether dimers are an intermediate structure in the process of S-layer lattice formation from monomeric SlaA or if this structure was just a coincident observation could help the reader to better understand the meaning of these dimeric structures and at which stage they are formed.

Reviewer #1 (Public Review):

The manuscript by Royall et al. builds on previous work in the mouse that indicates that neural progenitor cells (NPCs) undergo asymmetric inheritance of centrosomes and provides evidence that a similar process occurs in human NPCs, which was previously unknown.

The authors use hESC-derived forebrain organoids and develop a novel recombination tag-induced genetic tool to birthdate and track the segregation of centrosomes in NPCs over multiple divisions. The thoughtful experiments yield data that are concise and well-controlled, and the data support the asymmetric segregation of centrosomes in NPCs. These data indicate that at least apical NPCs in humans undergo asymmetric centrosome inheritance. The authors attempt to disrupt the process and present some data that there may be differences in cell fate, but this conclusion would be better supported by a better assessment of the fate of these different NPCs (e.g. NPCs versus new neurons) and would support the conclusion that younger centriole is inherited by new neurons.

Reviewer #2 (Public Review):

Royall et al. examine the asymmetric inheritance of centrosomes during human brain development. In agreement with previous studies in mice, their data suggest that the older centrosome is inherited by the self-renewing daughter cell, whereas the younger centrosome is inherited by the differentiating daughter cell. The key importance of this study is to show that this phenomenon takes place during human brain development, which the authors achieved by utilizing forebrain organoids as a model system and applying the recombination-induced tag exchange (RITE) technology to birthdate and track the centrosomes.

Overall, the study is well executed and brings new insights of general interest for cell and developmental biology with particular relevance to developmental neurobiology. The Discussion is excellent, it brings this study into the context of previous work and proposes very appealing suggestions on the evolutionary relevance and underlying mechanisms of the asymmetric inheritance of centrosomes. The main weakness of the study is that it tackles asymmetric inheritance only using fixed organoid samples. Although the authors developed a reasonable mode to assign the clonal relationships in their images, this study would be much stronger if the authors could apply time-lapse microscopy to show the asymmetric inheritance of centrosomes.

Reviewer #3 (Public Review):

In this manuscript, the authors report that human cortical radial glia asymmetrically segregates newly produced or old centrosomes after mitosis, depending on the fate of the daughter cell, similar to what was previously demonstrated for mouse neocortical radial glia (Wang et al. 2009). To do this, the authors develop a novel centrosome labelling strategy in human ESCs that allows recombination-dependent switching of tagged fluorescent reporters from old to newly produced centrosome protein, centriolin. The authors then generate human cortical organoids from these hESCs to show that radial glia in the ventricular zone retains older centrosomes whereas differentiated cells, i.e. neurons, inherit the newly produced centrosome after mitosis. The authors then knock down a critical regulator of asymmetric centrosome inheritance called Ninein, which leads to a randomization of this process, similar to what was observed in mouse cortical radial glia.

A major strength of the study is the combined use of the centrosome labelling strategy with human cortical organoids to address an important biological question in human tissue. This study is similarly presented as the one performed in mice (Wang et al. 2009) and the existence of the asymmetric inheritance mechanism of centrosomes in another species grants strength to the main claim proposed by the authors. It is a well-written, concise article, and the experiments are well-designed. The authors achieve the aims they set out in the beginning, and this is one of the perfect examples of the right use of human cortical organoids to study an important phenomenon. However, there are some key controls that would elevate the main conclusions considerably.

1) The lack of clonal resolution or timelapse imaging makes it hard to assess whether the inheritance of centrosomes occurs as the authors claim. The authors show that there is an increase in newly made non-ventricular centrosomes at a population level but without labelling clones and demonstrating that a new or old centrosome is inherited asymmetrically in a dividing radial glia would grant additional credence to the central conclusion of the paper. These experiments will put away any doubt about the existence of this mechanism in human radial glia, especially if it is demonstrated using timelapse imaging. Additionally, knowing the proportions of symmetric vs asymmetrically dividing cells generating old/new centrosomes will provide important insights pertinent to the conclusions of the paper. Alternatively, the authors could soften their conclusions, especially for Fig 2.<br /> 2) Some critical controls are missing. In Fig. 1B, there is a green dot that does not colocalize with Pericentrin. This is worrying and providing rigorous quantifications of the number of green and tdTom dots with Pericentrin would be very helpful to validate the labelling strategy. Quantifications would put these doubts to rest. Additionally, an example pericentrin staining with the GFP/TdTom signal in figure 4 would also give confidence to the reader. For figure 4, having a control for the retroviral infection is important. Although the authors show a convincing phenotype, the effect might be underestimated due to the incomplete infection of all the analyzed cells.<br /> 3) It would be helpful if the authors expand on the presence of old centrosomes in apical radial glia vs outer radial glia. Currently, in figure 3, the authors only focus on Sox2+ cells but this could be complemented with the inclusion of markers for outer radial glia and whether older centrosomes are also inherited by oRGCs. This would have important implications on whether symmetric/asymmetric division influences the segregation of new/old centrosomes.

Reviewer #1 (Public Review):

In this manuscript, Kim et al. investigate the molecular basis for hindbrain segmentation by performing combined single cell nucleus RNAseq and ATACseq (scMultiome) on zebrafish embryonic hindbrain tissue. Hindbrain segmentation is fundamental to head development in vertebrate species. Decades of research have provided many insights into the gene regulatory cascades that control the progressive subdivision of the hindbrain territory into segments (rhombomeres). These studies have enabled the formulation of gene regulatory network (GRN) models that depict these regulatory interactions. However, many aspects of the GRN need further clarification, including the early steps of pre-rhombomeric patterning, and the factors that respond to axial signaling pathways such as RA and FGF. The dataset in this study provides a comprehensive view of gene expression and chromatin states during hindbrain segmentation, thus it is a valuable resource for characterizing the underlying GRN. The authors demonstrate the utility of this data by comparing the molecular profiles between different rhombomeres and tracing when and how these profiles arise during development.

Four main findings are presented:

1. Each rhombomere has a unique molecular profile.<br /> 2. There is no clear molecular signature for odd versus even rhombomeres, nor any overt repeating two-segment molecular identities.<br /> 3. The mature rhombomeres emerge through the subdivision of three mixed-identity 'primary hindbrain progenitor domains' (PHPDs) that correspond to r2/r3, r4, and r5/r6, respectively.<br /> 4. RA and FGF signaling control formation of the primary hindbrain progenitor domains.

These findings are well supported by the data but in my opinion they mainly confirm what was already known and do not significantly advance our mechanistic understanding of rhombomere formation, which is the aim of the paper.

Strengths:<br /> This comprehensive dataset will be very valuable to researchers in the field. The authors successfully demonstrate its utility by resolving unique molecular profiles for each rhombomere and identifying some novel markers.

The authors make excellent use of HCR to validate their findings, such as the co-expression of vgll3 and egr2b in r2/r3 cells at 10hpf, which implies mixed identities of PHPD cells.

The performance of scMultiome analysis on tissue from DEAB-treated embryos (depleted RA signaling) is exciting and holds much promise for identifying RA-dependent gene regulatory cascades that govern caudal hindbrain patterning. Assessing the contribution of control versus DEAB-treated cells to the various UMAP clusters is a very nice way to identify the altered cell states in the RA-depleted hindbrain. This confirms a complete absence of r5 and r6 in the DEAB-treated embryos at this developmental stage, as was inferred from in-situ approaches in earlier studies.

Weaknesses:<br /> The major weakness of this work is that it only provides an incremental mechanistic advance to our current understanding of the molecular basis for rhombomere formation. The descriptions of gene expression are useful but for the most part they are rather shallow lines of enquiry that confirm what was already known from previous, less comprehensive studies of gene expression. For example, regarding the identification of PHPDs, it has long been known that r5/r6 share a progenitor domain that is demarcated by mafba expression. Similarly, RA and Fgf signaling have already been shown to be required for anterior-posterior patterning in the pre-rhombomeric hindbrain. The identification of mixed-identity progenitors in PHPDs, and the characterisation of the changes in transcription and chromatin state in response to RA signaling perturbation are really exciting starting points for deeper analysis of the underlying GRN. However, it is a shame that no effort is made to glean mechanistic insights from this dataset by computational GRN inference.

Reviewer #2 (Public Review):

The hindbrain is one of three primary anatomical domains of the developing brain, and is thought to be important for motor activity, respiratory rhythm, and sleep and wake behavior. The purpose of this study was to analyse spatiotemporal changes in gene expression during early development of the hindbrain. The authors used single cell RNA sequencing and ATAC sequencing at three developmental stages of zebrafish embryo development to characterize the transcriptomic changes that occur as the hindbrain neuroepithelium resolves into rhombomeres and the expression of a small number of genes was validated by in situ hybridization. The bulk of the "omic" dataset potentially provides a resource for the field to functionally analyze, but otherwise only incrementally advances our understanding of hindbrain rhombomere development and patterning. The primary conclusion from the work is that hindbrain progenitor domains contain mixed identity progenitors that eventually resolve into individual mature rhombomeres. This concept has been known historically for quite some time based on the expression of many genes of the Hox and other gene families, despite the authors describing this at higher resolution through analyses of whole genome expression. Unfortunately, the paper is largely a descriptive resource of transcriptomic data which in the absence of functional experimentation tells us very little that's new about the fundamental development or function of rhombomeres.

Reviewer #3 (Public Review):

Rhombomeres are key organizational structures for building cell type and even functional diversity in the brainstem. How these rhombmeres ultimately arise from a broad neuro-epithilium remains unclear. While genetic, cellular, tissue, and morphogen manipulations have revealed key processes in rhombomere development the hierarchical organization of neuron-epithelium into individual rhombomeres was less well understood. For example it is thought that rhombomeres are organized in an even odd fashion where two base identities i.e. even or odd where laminated with paired identifies i.e. rhombomeres 1 and 2 being paired and so on. However, there are many exceptions to these organizing constructs at the gene expression levels.

To further interrogate early development of the hindbrain neuro-epithelium and gain insight as to how rhombomere identities emerge at the earliest stages, Kim et al used ATACseq and RNAseq to query chromatin landscapes and gene expression for single nuclei at different developmental stages of zebrafish hindbrain development. The goal of the two pronged approach termed scMultiome analysis was to gain additional insight beyond either method individually for characterizing early events in rhombomere differentiation.

Using scMultiome, three stages of zebrafish hindbrain development were examined at 10hpf(whole embryos), 13hpf, and 16hpf. In the early hindbrain, the data shows that at 13hpf early rhombomere identities can be resolved but that the typical markers seen later are not fully expressed or resolved. At 10hpf clear rhombomere identities are not present. Rather at very early stages, the analysis suggests that three domains for pre-rhombomeres encompassing HB1 - r2+r3 (possibly r1, but this remains to be resolved); HB2 - r5+r6; and HB3 - 4 are present. These clusters or PHPDs are mixed populations that presumably resolve later as the embryo matures. They are shown to be responsive to developmental signals that pattern the neuroepithelium supporting the premise that these are rhombomeric organization structures.

Altogether the use of two methods of transcriptional interrogation i.e. ATACseq and RNA seq are strengths for the presented work to offer increased resolution of cell type characterization. The data analysis is reasonably supported by expression studies using in situ Hybridization Chain Reaction (HCR) to show mixed markers in the early stages. the PHPDs are also responsive to perturbation in retinoid acid, supporting the overall premise.

Overall, the work is well executed and analyzed. The impact in the field largely resides in bringing increasing resolution to earlier stages of rhombomere development and re-examining long held paradigms about when and potentially how rhombomere periodicity and pairing are established at the earliest stages. The premise that pre-rhombomeres may first establish large domains that sort or otherwise resolve themselves into rhombomeres is the most notable outcome from the work and will be seen as impactful in the field.

Reviewer #1 (Public Review):

This manuscript by Proskurin, Manakov, and Karpova, posits a unique role for the anterior cingulate cortex (ACC) in the flexible control of learned sequences of motor actions. The authors marshall evidence from behavioral-electrophysiological analyses in support of two major claims: 1) that action encoding by ACC ensembles tracks 1) the current "context", i.e., which behavioral sequence is rewarded, and 2) the "prevalence", i.e., number of repetitions of one specific sequence. An important aspect of this later point is that the authors propose prevalence encoding is not strictly dependent on trial-by-trial reward receipt.

In this work, the authors wish to focus on self-initiated behavior when the correct behavioral sequence, out of four or fewer (mostly two it appears), changes across blocks in an unsignaled manner. Rats learn to enter a left and right nose poke in a sequence of three responses, with a required entry into a central port prior to each intra-sequence response, with correct sequence completion reinforced by a sucrose delivery in the relevant side nose poke port. Extracellular spike activity is acquired from well-trained rats performing this task. The authors' analyses of the behavior of well-trained rats show rats adjust their behavior when the block switches to a different one of the sequences in the known 'library'. The rats also perform non-reinforced responses/sequences within a given block which the authors suggest is exploration likely not triggered by changes in reinforcement in contrast to behavior change after a block switch.

The authors next provide a very rich set of analyses to examine the encoding of responses and sequences by ACC neural activity. Overall, these data provide intriguing support for ACC's integral contributions to flexible behavioral control. However, some of the individual analyses are a bit difficult to follow and could be clarified with greater detail within the results section of the paper, permitting an easier evaluation of the quality of the supporting data. Second, there are some proposals that could be strengthened by fuller analysis, in particular the authors' suggestion that "prevalence" encoding is distinct from reward encoding and/or is not impacted by reward presence or omission. Given the likely rich data set in hand, the authors could do more to demonstrate how "prevalence" encoding interacts with reinforcement parameters or perhaps be more specific in their word choice. More importantly, I was left unclear on how "prevalence" encoding intersects with the decision to repeat the same behavioral sequence on the next trial or not. These issues aside, this work provides further information on the physiology of ACC during flexible behavior and will add importance to this field.

Below are specific issues:

1. Some greater attention to the behavioral parameters could be helpful, especially regarding the impact of reward rate on behavior. For example, looking at some of the figures of individual rat behavior, exploratory sequences seemed triggered by reward omission. Is this just a chance for the examples chosen or is there something systematic here? Upon block switch, how exactly does the switch in sequences emitted by the rat track with reinforcement history? The authors mention that reinforcement probability differed across sessions, and one would thus expect switching behavior would as well. Because of the interesting existence of sometimes quite long 'tails' of performance of the original sequence after a block switch, I am wondering how the length of such tails relates to reinforcement rate parameters.

2. The authors provide strong data indicating that a given L or R response is associated with distinct ACC activity depending on which sequence that response is embedded within, a finding reminiscent of other reports in multiple brain regions. While not a criticism per se, I was interested in the center port responses, also embedded within unique sequences, yet never preceding reward. A key difference in the performance of a given R or L response is that it is sometimes the terminal response, and thus the rat knows a given R or L response to be sometimes reinforced in one of the contexts, but not the other, in each of these comparisons. I wonder if there was an opportunity to cleanly demonstrate the context dependence of a given individual action by comparing center port responses across distinct sequences.

3. In analyzing neural activity accompanying the behavioral persistence of the dominant sequence after a block change, the authors find that the ACC ensemble firing pattern is closer to the original dominant sequence pattern during reinforcement and less like this pattern during exploration. This makes sense and must be the case, as, in the example shown in the figure, the rat does not "know" the block has switched since no reward has yet been delivered that would signal that switch. (As an aside, it would be interesting to know, given a specific reward schedule in a given session, what would be the maximum number of unrewarded trials within the block, and how might that impact the performance/reward expectation during the tails?)<br /> As time, and trials, progress the rat is approaching the point at which it explores another strategy. The authors find strengthened "prevalence" encoding with increasing sequence repetition, but if this parameter is related to behavioral change/flexibility, this was not clear to me. Might there be something unique about the last trials in a tail "predicting" an upcoming switch? Can the authors please expand?<br /> Relatedly, if the prediction of upcoming behavioral change is not observed in the neural activity from sequence steps 2-6, it is notable that these are the steps 'within' the sequence, that leaves out the initiation (first center poke) and termination (reward/reward omission). Thus one could imagine this information is "missed" in the current analysis given that both the reward period and the initiation of a trial at the center are not analyzed. This does lead me to suggest a softening of some claims made of identifying "unifying principles" of ACC function, as the authors state, based on the analyses included in the current report, since the neural activity related to the full unit of behavior is not considered. (I appreciate the motivation behind this focus on within-sequence behavior - the wish to compare time periods with similar movement parameters .)

4. The variance in neural activity explained by the prevalence models is on average quite low. However, the authors find that the variance explained differs quite dramatically by anatomical coordinate within ACC. Would it make sense to focus the control analyses (vigor, reward history, and so on) on those sessions/ensembles with greater variance explained, ie, perhaps there might be greater sensitivity to detecting interactions among variables within ensembles recorded more rostrally?

5. A very intriguing aspect of this work is the position that (from the abstract): "Prevalence encoding in the ACC is ...independent of reward delivery." This is a novel aspect of the current work. However, I am wondering if the authors can refine and expand upon this. I find it difficult to disentangle prevalence encoding and impacts of reward in the way the data and interpretation are presented in some areas of the text. While neural encoding may not reflect trial-by-trial reward receipt, clearly the rat's decision to repeat a given sequence or initiate a new sequence is impacted by reinforcement parameters and reward expectation. Thus being very exact in the interpretation would be helpful.

Reviewer #2 (Public Review):

Correctly keeping track of behavioral strategies allows for flexible context-appropriate behaviors. Several brain regions, including the anterior cingulate cortex (ACC), have been proposed to be involved in this process. But its neural correlates and computation principles still need to be uncovered, especially at the neural population level.

In this manuscript, to find such neural correlates, the authors create a behavioral task in which rats must discover a strategy and use it to obtain a reward. Specifically, the authors train rats to perform a self-initiated nose-poking task in which, within every 250-500 trials, rats performing a target '3-step action sequence' leads to sucrose reward delivery. The target action sequence is viewed as 'latent' because it is un-signaled, and rats have to infer it based on past choices and outcomes. Behavioral analyses show that rats' actions comply with the target action sequence after training. However, even at the expert level, rats sometimes show deviations from choosing the target action sequence and instead choose the alternative action sequence. Based on several criteria, the authors identify most of these deviations to reflect an 'exploratory' nature of the rats' behavior in this task. Tetrode recordings in these trained rats show that most ACC neurons encode 'strategy prevalence,' basically, a signal telling which strategy dominates rats' sequential nose-poking actions. Such representation is not restricted to ACC and is also found in M2 and SMC, though with less pronounced correlations. Beyond encoding such a 'global' strategy, the ACC neurons also show activity related to 'local' fluctuations in rats' choices, which the authors argue cannot be explained by several commonly considered behavioral variables, including movement kinematics and vigor and reward expectation. Interestingly, the strategy prevalence is decodable across sequence execution time with a weight-fixed decoder, even though most neurons show transient selectivity to strategy prevalence at the single-cell level, showing the importance of neural population representation.

The behavioral task design is complicated yet appealing. In this task, rats must constantly adjust their behavioral strategy to align with the un-signaled target sequence changes. The task design and the following neural data analyses represent a technical strength of the current study. After controlling for many confounding factors, the ACC neural activities distinguish between 'dominant' vs. 'exploratory' sequence prevalence and contain the specific sequence identities. Building upon their previous work, in this study, the authors reveal more detailed neural dynamics mechanisms for the involvement of ACC in signaling subjective behavioral strategy other than the actual task rule. These findings are conceptually important and would greatly draw the attention of many interested in the neural mechanisms of higher-order brain functions at the systems level.

The primary weakness of the study, however, is that the behavioral and data analyses cannot eliminate all the confounding factors, although, in certain conditions, such influences can be minimized to an acceptable level. That said, the current analyses only partially support the authors' conclusions. Nevertheless, despite these limitations, this study aiming at isolating neural correlates of the 'strategy prevalence' has substantial value in its methodology and proposed hypothesis on ACC behavioral functions and would likely have a significant impact on the field. The innovative data analysis methods implemented in the study can be helpful for related behavioral electrophysiological and imaging studies. Besides, mapping the putative SMC and ACC area to primate SMC and 32D helps to connect the research in rodents and primates.

Reviewer #3 (Public Review):

Proskurin and colleagues aim to test if neurons in rat medial prefrontal cortex encode strategy in a serial choice task. They recorded neural activity as rats performed a nose-poke task for reward. Rats were required to discover, without explicit instruction, which of the possible 3-action sequences were rewarded. One of several possible sequences remained the target (thereby triggering reward delivery) over a block of trials, before switching to an alternate sequence. The authors then used analysis of single neurons and ensembles of neural activity to determine if neural activity reflected whether a sequence was the dominant strategy in a block or an explorative test.

The strengths of the work include the timely and important hypothesis, and the use of appropriate methodologies to test it.

I commend the authors for endeavouring to tackle this challenging topic. The weaknesses of the work derive from the difficulties of studying such a challenging topic. It is extremely difficult to ascribe the variance of neural activity to a latent variable such as strategy, particularly in freely-moving animals motivated by reward. This is because of the plethora of potential confounders. For instance, the authors compare the encoding of one action (L) in two sequences (RLL and LLR). However, the analyzed action occurs in different local contexts. In the first, it is the middle action, and in the second it is the first action following a reward omission. Even though the reward is withheld, the rat presumably has some reward expectation. Because strategy is a latent variable, the evidentiary threshold is high, and alternate explanations of neural variance needed to be rejected. This is particularly important given the neural structures under investigation are involved in regulating motor output, suggesting that differences in response speed, body position, and related variables may explain considerable variance in neural activity. Other potential explanatory variables are rule certainty, position in the sequence, side chosen, preceding choice, and changes in firing rate as the session progresses due to changes in motivation, fatigue, or drift in the signal. The authors attempt to address some of these, but this is done in a very condensed presentation near the end of the results. This needs to be unpacked (and visualized) in order for readers to evaluate whether the strategy is the most likely explanation of neural variance, as proposed by the authors. The paper would benefit from analyses, such as multiple regression over all possible predictive variables, to evaluate the relative amount of neural signal variance attributable to strategy dominance compared to other information.

An additional weakness of the manuscript is the absence of some fundamental checks on data quality, particularly for bias in animal behavior, stability of neural activity during sessions, and bias in data sampling for classifier sampling.

In sum, the experimental methodology appears sufficient to address the authors' aim of evaluating the encoding of strategy by neurons in the medial prefrontal cortex. Alternate interpretations of the data, however, are not sufficiently ruled out by the analysis to strongly support the claim that the exploration of strategy is the primary driver of altered neural signalling. The data and methodologies are valuable to behavioral and systems neuroscientists. The task and the finding that rats appear to spontaneously explore alternate strategies are elegant, and a very nice paradigm for studying the neural mechanisms of strategy shifting. Moreover, the finding that many neurons in the medial prefrontal cortex change their firing rate during the task is an important new contribution. Future analysis and experiments will undoubtedly better resolve the information encoded by these changes in firing rate.

Reviewer #1 (Public Review):

Summary:

Fox, Dan, and Loewenstein investigated how people explored six maze-like environments. They show that roughly one-third of their participants make choices now that increase the potential for future information gain and also temporally discount potential information gain based on how far in the future potential gains might be. The authors argue that rather than valuing exploration in its own right, participant behavior is most consistent with using exploration as a way to reduce uncertainty. They then propose a reinforcement learning (RL) model in which agents estimate an "exploration value" (the expected cumulative information gained by taking a given action in a given state) using standard RL techniques for estimating value (expected cumulative reward). They find that this model exhibits several qualitative similarities with human behavior and that it best captures the temporal dynamics of human exploration when propagating information through the entire history of a behavioral episode (as opposed to merely propagating it in a single step as some of the simplest RL models do).

While the core insight and basic method of the paper are compelling, the way in which both the behavioral experiment and computational modeling were conducted raise concerns that mean that, in their present form, the results do not fully justify the conclusions. After resolving these issues, the work would demonstrate how human exploration is sensitive to long-range dependencies in information gain, as well as valuable insights about how best to characterize this behavior computationally. I am not particularly well-versed in the literature on exploration so cannot comment on novelty here.

Strengths:<br /> The entire paper is logically well-motivated. It builds on a valuable basic insight, namely that while bandit tasks are an ideally minimal platform for testing certain questions about decision-making and exploration, richer paradigms are needed to capture the long-range informational dependencies distinguishing between various approaches to exploration.

Even so, the maze navigation paradigm explored here remains simple. Participants navigate a maze with two main branches which are identical save for minimal, theoretically motivated differences. Moreover, the tested differences are designed to clearly and explicitly test well-identified questions. The task, and really the entire paper, is clearly organized, and each component is logically connected to a larger argument.

The proposed model is also simple, clearly presented, and a clever way of applying ideas typically used to reason about reward-motivated behavior to reason here about information-motivated behavior.

One other strength of this work is that it combines behavioral experiments with computational modeling. This approach pairs a detailed and objectively specified theory (i.e. the model) with novel data specifically designed to test that theory and thus in principle presents a particularly strong test of the authors' hypotheses.

Weaknesses:<br /> Despite many strengths in the underlying logic of the paper, the presented evidence does not provide compelling support for the conclusions. In particular:

- The main claims are based on the behavior of 452 participants classed as good explorers, out of 1,052 participants included in the analyses and 1,336 participants who completed the study. That is, the authors' broad claims about human exploration are based on a third of their total sample; the other two-thirds displayed very different behavior, including 20% who performed at or below chance levels. That is, while a significant sub-population may demonstrate the claimed abilities, it is far from clear that they are universal.

- While the experimental manipulations are elegant, the behavioral study seems underpowered. In each of the primary manipulations, key theoretical predictions are not statistically validated. For example, in Experiment 1, the preference for the right door increases from the 4:3 condition to the 5:2 condition, but not when moving from the 5:2 condition to the 6:1 condition, as predicted (Figure 1c). Similar results can be seen for other analyses in Figures 3b and 4b. Relatedly, the experiments comprised just 20 episodes, and it is unclear whether that was sufficiently long for participants to demonstrate asymptotic behavior (e.g. Figure 5b). Either more participants or greater differences between conditions (e.g. testing 9:8, 12:5, and 15:2 conditions in a revised Experiment 1), as well as running a greater number of total episodes, would be needed to resolve this concern.

- The model is presented after the behavioral results, giving the impression that it was perhaps constructed to fit the data. No attempt is made to fit the model to a subset of the data and then validate the rest or give any clear indication as to how the model parameters were set. Moreover, as noted, even where the model is successful, it only explains the behavior of a minority of the total participants. No modeling work is done to explain the behavior of the other two-thirds of the participants.

- The authors helpfully discuss several meaningful alternative models of exploration, such as visit-counting and incorporating an objective function sensitive to information gain. They do not, however, compare their model against these or any other meaningful baselines. Moreover, the comparison between model and human participants is qualitative rather than quantitative. These issues could be resolved by introducing a more rigorous analysis quantitatively comparing a variety of theoretically relevant models as quantitative explanations of the human data.

Reviewer #2 (Public Review):

Summary:<br /> In this article, the authors develop an algorithm for exploration inspired by the classic, state-action-reward-state-action (SARSA) reinforcement learning algorithm. Designed to account for exploration in multi-state environments, this algorithm computes the expected discounted return from selecting an action in a state and uses that value to update the cached value of taking a given action in a given state. The value represents the uncertainty in a given state, and the backed-up value is computed from the discounted future return plus the immediate reduction in uncertainty regarding the state.

Strengths:<br /> The article is ambitious and seeks to characterize human exploration in a novel task using zero rewards. That characterization is useful.

Weaknesses:<br /> The paper suffers from many problems. Here, I will mention three. First, the algorithm is very poorly motivated-exploration is central to many behaviors, but the algorithm computes the value of exploration independent of any long-run considerations of exploitation. Second, the article attempts to recover the observed exploratory behavior in two different multi-state choice tasks. But the algorithm does not explain that behavior, and there is no performance metric on the model, nor a comparison to other models. Third, the article frames the algorithm in terms of uncertainty, but there is no measure of uncertainty.

In short, in many ways this manuscript is 'half an article', and the authors have much work to do. They could decide to dive into the convergence proofs and other theoretical properties of the model. However, as far as I understand the model, it is literally an optimistic SARSA, whose characteristics are well-understood. Or, they could compare the model's performance to a number of other exploration models (UCB, Thompson sampling, infomax, infotaxis-there are so many!). However the authors need to choose one or the other. I urge the authors to properly compare their model to other models.

1. Motivation<br /> The algorithm is poorly motivated. Exploration is valuable for a time but quickly becomes less valued as more is learned about the environment. The algorithm attempts to account for this by the ad hoc nature of the backup: the immediate outcome is -E(s,a), which represents a reduction in uncertainty. So in the long run, the exploratory value will decrease to zero. But this is ad hoc; why not add E(s,a)? In addition, exploration values are set to 1. But this is also ad hoc; why should E(s,a) start at 1? They have cherry-picked their starting values and the nature of the back-up to yield exploratory behavior.

2. Performance<br /> The authors wish to compare the model's performance to observed exploration behavior. However, their model does a poor job of explaining the behavior. What's confusing is that the authors note the ways the model deviates. There are two principal deviations. First, the model exhibits an exploratory transient, but it is too wide to match the humans. Second, the model fails to exhibit the low-level persistent exploration characteristic of humans in their task.

The next natural step would be to augment the model in different ways to attempt to describe the behavior. The authors do attempt to import td-λ aspects into their exploration model. They determine that importation fails to capture the observed behavior. But why stop there? Why not continue? Why not follow through and change the model in a way that can capture the dynamics of exploration?

In addition, a natural complement would be to compare the model's ability to describe human performance to other models. This would require model fitting, recovery, and validation. However the authors don't engage in that model fitting exercise.

They note that a model-based learning strategy could account for the speed of learning in humans. However they don't comment generally on how model-based strategies could explain their findings nor how they relate to their model. They should comment on this. In particular, the participants are likely learning a model of their environment, and this can be done using non-parametric Bayesian inference (along the lines of Gershman or Collins's work). The authors should model their task using these models and compare this to their algorithm.

The authors state that there was no reward. Were subjects paid for their time? Also, the lack of a reward is unusual, and even if unconsciously, participants may have been engaged in reward-seeking. The authors should try to model the behavior with a pseudo-reward to see how that accounts for their findings. This is especially true from the perspective of computational RL. On that theory, the only object 'in' the agent is the policy; everything else is considered 'in' the environment. This means that rewards in RL need not be from environmental returns but could also be from inside the organism (even if modeled as 'outside' the agent in the RL framework). So they need to model the behavior using 'pseudorewards' to see if that can account for their findings. Finally, though trivially, a reward of 0 is technically a reward, and the model's exploratory drive comes from settling on the true values of the states (i.e., 0).

3. Uncertainty<br /> The authors frame their model in terms of uncertainty, but their model does not measure uncertainty at all. The model makes choices on the basis of optimistic initial Q-values and then searches on that basis, backing up the 0 rewards until the true values are more or less hit upon. But that is not a measure of uncertainty in any sense; rather, it is an optimistic Q-value bias that drives exploration. However, I may simply fail to understand their model.

Reviewer #3 (Public Review):

Summary:<br /> In this article, Fox and colleagues describe the results of a novel and innovative task, coupled with a modified computational model, to explore pure directed exploration (not quite a pun, but intended nonetheless). In their task, participants make a series of discrete choices, importantly with no reward feedback, to navigate a nested series of rooms in a virtual environment. The initial 2-door choice is used as the primary probe and the complexity of the series of rooms behind each choice is used as the critical independent variable. The authors find that, as the number of follow-up options behind a door increases, "good" participants are more likely to choose the door that leads to the more complex choices. As the depth of the search increased (i.e. the room with the most doors was presented "farther" down the search), these same participants were less likely to choose the door leading to the more complex route. Finally, these same "good" participants showed an initial boost in preference towards the more complex exploration option after a few learning episodes that settled down after about 10 episodes, with a modest reliable preference towards the more complex route. This reflected the fact that information value decays over time in stable situations. Using an adaptation of standard Q-learning, with a proxy of information value being substituted for reward value, the authors show how their model can qualitatively capture most of the observed experimental effects, although with some critical differences in the temporal dynamics of learning, suggesting that the memory horizon for humans is longer than in the adapted Q-learning model.

Strengths:<br /> 1. Clever experimental design<br /> The novel task is really clever and gets around many of the limitations for understanding directed exploration that have plagued prior research (which typically involve some use of reward feedback). Finding a way to provide direct information that can be experimentally manipulated, without needing to provide any explicit reward feedback, makes this one of the few pure exploration tasks that I am aware of.

2. Compelling results<br /> The effect of manipulating choice complexity and depth on initial choice probability for "good" directed learners seems fairly strong, as do the learning dynamics. The heterogeneity in exploration style across participants is also interesting and brings up more questions that are useful for follow-up research.

3. Simple model<br /> The computational model used is a simple adaptation of standard reinforcement learning models, specifically Q-learning models. This is elegant as it doesn't require major changes in the dynamics of learning, simply a revision of the variables going into the update. The simplicity of this change, coupled with the ability to capture the results of the "good" directed explorers makes a strong case that information seeking and reward-seeking may share common underlying mechanisms (as shown previously by Kobayashi, K., & Hsu, M. (2019). Common neural code for reward and information value. Proceedings of the National Academy of Sciences, 116(26), 13061-13066.).

Weaknesses:

1. "Good" vs. "poor"<br /> There is an odd circularity, and implicit value judgment, in the classification of participants into "good" and "poor" directed explorers. The logic, based on the visit-counter model of directed exploration, is that the probability of repeating a choice (at the initial decision trial) should be low for directed explorers vs. random explorers. Doing the median split on repetition probability seems intuitively fine here, but it does bring up two issues. First, the labels "good" vs. "poor" seem arbitrarily judgemental, after all random exploration is a viable exploration strategy in many contexts. Would "directed" vs. "random" be more appropriate labels based on how the decision was made to categorize participants? Second, how much of the "good" participant performance is driven by the extreme non-repeaters? For example, if a tertiary split was performed instead of a binary median split, would the middle group show a weaker version of the effects seen in the "good" group or appear more like the "poor" group?

2. Characterization of information value<br /> The authors discuss primarily methods that can be summarized by visit counters as a description for all directed exploration models. However, that doesn't seem to be a good summary of the overall literature in this space. There are also entropy-based approaches, that quantify information value based on the statistics of the feedback. For example, in machine learning methods like the KL divergence are often used to represent the information value of a channel. A few such papers are highlighted below. Now it is entirely possible that these approaches can be extrapolated to simple visit-count approaches, but I am unaware of anything showing this. I think it would be good to broaden the discussion on directed exploration models beyond visit-counter methods like UCB, highlighting the other methods used to promote directed exploration.

Houthooft, R., Chen, X., Duan, Y., Schulman, J., De Turck, F., & Abbeel, P. (2016). Vime: Variational information maximizing exploration. Advances in neural information processing systems, 29.

Eysenbach, B., Gupta, A., Ibarz, J., & Levine, S. (2018). Diversity is all you need: Learning skills without a reward function. arXiv preprint arXiv:1802.06070.

Hazan, E., Kakade, S., Singh, K., & Van Soest, A. (2019, May). Provably efficient maximum entropy exploration. In International Conference on Machine Learning (pp. 2681-2691). PMLR.

3. Model vetting<br /> The model used to simulate the behavioral results is interesting and intuitive. However, there seem to be some things left on the table and unresolved. First, the definition of information value (E) that is maximized is assumed to satisfy the same constraints as typical reward does in the Bellman solution for reinforcement learning. This is the only way it can be substituted into the typical Q-learning method. Is that true here?

Second, the advantage of these simpler computational-level models is that they can be effectively fit to behavior. The model outlined in the paper has only a few free parameters (some of which can be fixed for convenience purposes). Was there an attempt to fit each participant's data into the model? This would be a powerful way of highlighting where exactly the differences between the "good" and "bad" participants arise.

Reviewer #2 (Public Review):

Summary: This work presented by Kudo and colleagues is of great importance to strengthen our understanding of electrophysiological changes in the course of AD. Although the main conclusions regarding functional connectivity and spectral power change through the course of the disease are not new and have been largely studied and theorised on, this article offers an innovative approach that certainly consolidates previous knowledge on the topic. Not only that, this article also broadens our knowledge presenting useful and important details on the specificity of frequency and cortical distribution of these early alterations. The main take-home message of this work is the early disruption of electrophysiological signatures that precedes detectable alterations in other more commonly used pathology markers (i.e. gray matter atrophy and cognitive impairment). More specifically, these signatures include long-range connectivity in the alpha and beta bands, and local synchrony (spectral power) in the same frequency bands.

Strengths: The present work has some major strengths that make it paramount for the advance of our understanding of AD electrophysiology. It is a very well written manuscript that, despite the complexity of the analyses employed, runs the reader through the different steps of the analysis in a pedagogic and clever way, making the points raised by the results easy to grasp. The methodology itself is carefully chosen and appropriate to the nature of the question posed by the researchers, as event-based models are well-suited for cross-sectional data.

The quality of the figures is outstanding; not only are they aesthetic but, more importantly, the figures convey information exceptionally well and facilitate comprehension of the main results.<br /> The conclusions of the paper are, in general, well described and discussed, and consider the state-of-the-art works of AD electrophysiology. Furthermore, even though the conclusions themselves are not groundbreaking at all (synaptic damage preceding structural and cognitive impairment is one of the epitomes of the pathological cascading model proposed by Jack in 2010), this article is innovative and groundbreaking in the way they address with clever analyses in a relatively large sample for neuroimaging standards.

Weaknesses: The main limitation of the work revolves around sample definition and inclusion criteria that are somewhat confusing obscuring some of the points of the analyses. Firstly it is not clear why the purely clinical approach is employed to diagnose the "probable Alzheimer´s Disease" for the 78 participants in the "AD group". In the same paragraph, it is stated that 67 out of the 78 participants show biomarker positivity, thus allowing a more biologically guided diagnosis that is preferred according to current NIA-AA criteria. This would avoid highly possible mixing of different subtypes of dementia etiologies. One might wonder, why would those 11 participants be included if we have strong indications that their symptoms are not due to AD? Furthermore, the real pathological status of the control group is somewhat questionable. The authors do not specify whether common AD biomarkers are available for this subgroup. In that case, it would have highly increased the clarity and interpretability of the results if this group was subdivided in a preclinical and completely healthy control group. This would be particularly interesting since a significant proportion of the control group is labeled as belonging to stages 2,3,4 (MCI) and even 5 (mild dementia). This raises the question of whether these participants are true healthy controls mislabeled by the EBM model, or actual cognitive controls with actual underlying AD pathology well identified by the model proposed. On this note, Figure 2 (C and D) and Figure 3 (C, G and K) show a cortical surface depicting the mean difference of each stage vs the control group, which again, is formed by subjects that can be included (and in fact, are included) in all of those stages, obscuring the meaning and interpretability of these cortical distributions.

Reviewer #1 (Public Review):

Summary:<br /> The authors aimed to infer the trajectories of long range and local neuronal synchrony across the Alzheimer's disease continuum, relative to neurodegeneration and cognitive decline. The trajectories are inferred using event-based models, which infer a set of data-driven disease stages from a given dataset. The authors develop an adapted event-based modelling approach, in which they characterise each stage as a particular biomarker increasing by a particular z-score deviation from controls. Fitting infers the optimal set of z-scores to use for each biomarker and the order in which each biomarker reaches each z-score. The authors apply this approach to data from 148 individuals (70 cognitively unimpaired older adults and 78 individual with mild cognitive impairment or Alzheimer's disease), identifying trajectories in which long-range (amplitude-envolope correlation) and local (regional spectral power) neuronal synchrony in the alpha and beta bands becomes abnormal prior to neurodegeneration (measured as the volume of the parahippocampal gyrus) and cognitive decline (measured using the mini-mental state examination).

Strengths:<br /> - The main strength is that the authors assess two models. In the first they derive a staging system based only on the volume of the parahippocampal gyrus and mini-mental state examination score. They then investigate how neuronal synchrony metrics change compared to this staging system. In the second they derive a staging system that also includes an average (combined long-range and local) neuronal synchrony metric and investigate how long-range and local synchrony metrics change relative to this staging system. This is a strength as the first model provides confidence that there is not overfitting to the neuronal synchrony data, and the second provides more detailed insights into the dynamics of the early neuronal synchrony changes.<br /> - Another strength is that the authors automatically infer the optimal z-scores to choose, rather than having to pre-select them manually, as in previous approaches.

Weaknesses:<br /> - The dataset is small and no external validation is performed.<br /> - A high proportion of the data is from controls (nearly 50%) with no biomarker evidence of Alzheimer's disease, and so the changes may be driven by aging or other non-Alzheimer's effects.<br /> - Inferring the optimal z-scores is a strength, however as different sets of z-scores are allowed per biomarker, there is a concern that the changes reflected are mainly driven by the choice of z-score, rather than the markers themselves (e.g. if lower z-scores are selected for one marker than another, then changes in that marker will appear to be detected earlier, even if both markers change at the same time).<br /> - In equation 2 it is unclear why the gaussian is measured based on a sum over I. The more obvious choice would be to use a multivariate gaussian with no covariance, which would mean taking the product rather than the sum over I.<br /> - In the original event-based model, k is a hidden variable. Presumably that is also the case here, however the notation k=stage(j) makes it seem like each subject is assigned a stage during the sequence optimisation.<br /> - Typically for event-based modelling, positional variance diagrams are created from the markov chain monte carlo samples of the event sequence, enabling visualisation of the uncertainty in the sequence, but these are not included in the study.<br /> - Many of the figures in the manuscript (e.g. Figure 1E/G, Figure 2A/B, Figure 3A/B/E/F/I/J, Figure 4 A/B/E/F/I/J) are based on averages in both the x and the y axis. In the x dimension, individuals have a weighted contribution to the value on the y axis, depending on their stage probability. In the y dimension, the values are averages across those individuals, and the error bars represent the standard error rather than the standard deviation. Whilst the trajectories themselves are interesting, they may not be discriminative at the individual level and may be more heterogeneous than it appears.<br /> - The bootstrapped statistical analyses comparing metrics between the stages do not consider the variability in the sequence.

Reviewer #3 (Public Review):

This study examines how the correlation structure of a perceptual decision-making task influences history biases in responding. By manipulating whether stimuli were more likely to be repetitive or alternating, they found evidence from both behavior and a neural signal of decision formation that history biases are flexibly adapted to the environment. On the whole, these findings are supported across an impressive range of detailed behavioral and neural analyses. The methods and data from this study will likely be of interest to cognitive neuroscience and psychology researchers. The results provide new insights into the mechanisms of perceptual decision-making.

The behavioral analyses are thorough and convincing, supported by a large number of experimental trials (~600 in each of 3 environmental contexts) in 38 participants. The psychometric curves provide clear evidence of adaptive history biases. The paper then goes on to model the effect of history biases at the single trial level, using an elegant cross-validation approach to perform model selection and fitting. The results support the idea that, with trial-by-trial accuracy feedback, the participants adjusted their history biases due to the previous stimulus category, depending on the task structure in a way that contributed to performance.

The paper then examines MEG signatures of decision formation, to try to identify neural signatures of these adaptive biases. Looking specifically at motor beta lateralization, they found no evidence that starting-level bias due to the previous trial differed depending on the task context. This suggests that the adaptive bias unfolds in the dynamic part of the decision process, rather than reflecting a starting level bias. This is supported by analysis of lateralization relative to the chosen hand as a proxy for a decision variable (DV), whose slope is shown to be influenced by these adaptive biases.

Reviewer #1 (Public Review):

This paper aims to study the effects of choice history on action-selective beta band signals in human MEG data during a sensory evidence accumulation task. It does so by placing participants in three different stochastic environments, where the outcome of each trial is either random, likely to repeat, or likely to alternate across trials. The authors provide good behavioural evidence that subjects have learnt these statistics (even though they are not explicitly told about them) and that they influence their decision-making, especially on the most difficult trials (low motion coherence). They then show that the primary effect of choice history on lateralised beta-band activity, which is well-established to be linked to evidence accumulation processes in decision-making, is on the slope of evidence accumulation rather than on the baseline level of lateralised beta.

The strengths of the paper are that it is: (i) very well analysed, with compelling evidence in support of its primary conclusions; (ii) a well-designed study, allowing the authors to investigate the effects of choice history in different stochastic environments.

There are no major weaknesses to the study. On the other hand, investigating the effects of choice/outcome history on evidence integration is a fairly well-established problem in the field. As such, I think that this provides a valuable contribution to the field, rather than being a landmark study that will transform our understanding of the problem.

The authors have achieved their primary aims and I think that the results support their main conclusions. One outstanding question in the analysis is the extent to which the source-reconstructed patches in Figure 2 are truly independent of one another (as often there is 'leakage' from one source location into another, and many of the different ROIs have quite similar overall patterns of synchronisation/desynchronisation.). A possible way to investigate this further would be to explore the correlation structure of the LCMV beamformer weights for these different patches, to ask how similar/dissimilar the spatial filters are for the different reconstructed patches.

The revised paper now states explicitly how source-reconstructed patches are indeed affected by leakage, but also why the focus of the authors on differences (rather than similarities) between patches leaves their findings and conclusions essentially unaffected by this intrinsic limitation of cortical source reconstruction from surface MEG data.

Reviewer #2 (Public Review):

In this work, the authors use computational modeling and human neurophysiology (MEG) to uncover behavioral and neural signatures of choice history biases during sequential perceptual decision-making. In line with previous work, they see neural signatures reflecting choice planning during perceptual evidence accumulation in motor-related regions, and further show that the rate of accumulation responds to structured, predictable environments suggesting that statistical learning of environment structure in decision-making can adaptively bias the rate of perceptual evidence accumulation via neural signatures of action planning. The data and evidence show subtle but clear effects, and are consistent with a large body of work on decision-making and action planning.

Overall, the authors achieved what they set out to do in this nice study, and the results, while somewhat subtle in places, support the main conclusions. This work will have an impact within the fields of decision-making and motor planning, linking statistical learning of structured sequential effects in sense data to evidence accumulation and action planning.

Strengths:

- The study is elegantly designed, and the methods are clear and generally state-of-the-art<br /> - The background leading up to the study is well described, and the study itself conjoins two bodies of work - the dynamics of action-planning processes during perceptual evidence accumulation, and the statistical learning of sequential structure in incoming sense data<br /> - Careful analyses effectively deal with potential confounds (e.g., baseline beta biases)

Weaknesses (after revision):

- The treatment of "awareness" of task structure is left as a somewhat open, potentially important question.

Reviewer #1 (Public Review):

In this study, the authors utilise different chemical inhibitors and celular markers to examine the roles of macropinocytosis in WNT signalling activation in development (Xenopus), cell culture (3T3 cells) and cancer (CRC sections). Furthermore, they investigate the effect of the inflammation inducer Phorbol-12-myristate-13-acetate (PMA) in WNT signalling activation through macropinocytosis. The authors show 1) that PMA induces macropinocytosis-dependent WNT signalling activation, and 2) that CRC development correlates with increased levels and co-localisation of macropinocytosis components and b-catenin.

I found the analyses and conclusions compelling. Additional epistatic analyses could be done in the future to further disentangle the roles of macropinocytosis during WNT signalling activation, especially upon oncogenic alterations (e.g. in APC). The studies on CRC samples open interesting questions for specialists in tumour progression.

Reviewer #2 (Public Review):

Tejeda Muñoz et al. investigate the intersection of Wnt signaling, macropinocytosis, lysosomes, focal adhesions and membrane trafficking in embryogenesis and cancer. Following up on their previous papers, the authors present evidence that PMA enhances Wnt signaling and embryonic patterning through macropinocytosis. Strikingly, PMA and Wnt ligand act synergistically to trigger macropinocytosis in fibroblasts. Proteins that are associated with the endo-lysosomal pathway and Wnt signaling are co-increased in colorectal cancer samples, consistent with their pro-tumorigenic action. The function of macropinocytosis is not well understood in most physiological contexts, and its role in Wnt signaling is intriguing. The authors use a wide range of models - Xenopus embryos, cancer cells in culture and in xenografts and patient samples to investigate several endolysosomal processes that appear to act upstream or downstream of Wnt. This broad approach has the downside that results are often validated only in a subset of biological systems and that experiments tend to lack of mechanistic depth. The connections between PMA, Wnt signaling, Rac stabilization, FAK signaling and macropinocytosis remain unclear. Nevertheless, the results provide intriguing insights into a novel connection of the tumor promoting agent PMA and Wnt signaling in development and cancer.

The authors demonstrate striking, additive effects of Wnt3a and PMA in inducing macropinocytosis in 3T3 cells (Fig. 1 K-P). In the APC-mutant colorectal cancer line SW480, the authors show that PMA treatment increases macropinocytosis (Fig. S1). While these data provide additional confirmation that PMA can trigger macropinocytosis, they do not address the role of Wnt signaling directly. This could be done by restoring APC function in SW480 cells, or by ectopically activating Wnt signaling in a CRC cell line that lacks activating mutations in the Wnt pathway. These experiments would help to strengthen the cancer angle and validate the connection between Wnt signaling and PMA in macropinocytosis induction in additional cell lines.

The authors conclude that PMA enhances Wnt signaling based on experiments in Xenopus embryos where co-treatment with PMA and the Wnt activator LiCl increases Wnt target gene expression. This is an interesting observation, but large parts of the paper focus on mammalian cells / cancer cells. It would be important to demonstrate the ability of PMA to enhance Wnt signaling in these contexts as well.

Reviewer #3 (Public Review):

In this improved version of the manuscript, Chang et al set out to find direct interactions with the Eph-B2 receptor, as our knowledge of its function/regulation is still incomplete. Using proteomic analysis of Hela cells expressing EPHB2, they identified MYCBP2 a potential binder, which they then confirm using extensive biochemical analyses, an interaction that seems to be negatively affected by binding of ephrin-B2 (but not B1). Furthermore, they find that FBXO45, a known MYCBP2 interaction, strongly facilitates its binding to EPHB2. Intriguingly, these interactions depend on the extracellular domains of EPHB2, suggesting the involvement of additional proteins as MYCBP2 is thought to be a cytoplasmic protein. Finally, they find that, in contrast to what could be expected given the known function of MYCBP2 as a ubiquitin E3 ligase, it actually positively regulates EPHB2 protein stability, and function.

The strength of this manuscript is the extensive biochemical analysis of the EPHB2/MYCBP2/FBXO43 interactions. The vast majority of the conclusions supported by the data.

The attempt to extend the study to an in vivo animal using the worm is important, however the additive insight is, unfortunately, minimal.

Reviewer #1 (Public Review):

The Eph receptor tyrosine kinase family plays a critical function in multiple physiological and pathophysiological processes. Hence, understating the regulation of these receptors is highly important question. Through extensive experiments in cell lines and cultured neurons Chang et.al show that the signaling hub protein, MYCBP2 positively regulates the overall stability of a specific member of the family, EPHB2, and by that the cellular response to ephrinBs.<br /> Overall, this work sheds light on the divergent in the regulatory mechanisms of the Eph receptors family. Although the physiological importance of this new regularly mechanism in mammals awaits to be discovered, the authors provide genetic evidence using C.elegans that it is evolutionarily conserved.

Reviewer #2 (Public Review):

Members of the EphB family of tyrosine kinase receptors are involved in a multitude of diverse cellular functions, ranging from the control of axon growth to angiogenesis and synaptic plasticity. In order to provide these diverse functions, it is expected that these receptors interact in a cell-type specific manner with a diverse variety of downstream signalling molecules.

The authors have used proteomics approaches to characterise some of these molecules in further detail. This molecule, myc-binding protein 2 (MYCBP2) is also known as highwire, has been identified in the context of establishment of neural connectivity. Another molecule coming up on this screen was identified as FBXO45.

The authors use classical methods of co-IP to show a kinase-independent binding of MYCBP2 to EphB2. They further showed that FBXO45 within a ternary complex increased the stability of the EphB2/MYCBP2 complex.

To define the interacting domains, they used clearly designed swapping experiments to show that the extracellular and transmembrane domains are necessary and sufficient for the formation of the ternary complex.

Using a cellular contraction assay, the authors showed the necessity of MYCBP2 in mediating the cytoskeletal response of EphB2 forward signalling. Furthermore, they used the technically challenging stripe assay of alternating lanes of ephrinB-Fc and Fc to show that also in this migration-based essay MYCBP2 is required for EphB mediated differential migration pattern.

MYCBP2 in addition is necessary to stabilize EphB2, that is in the absence of MYCBP2, EphB2 is degraded in the lysosomal pathway.

Interestingly, the third protein in this complex, Fbxo45, was further characterized by overexpression of the domain of MYCBP2, known to interact with Fbxo45. Here the authors showed that this approach led to the disruption of the EphB2 / MYCBP2 complex, and also abolished the ephrinB mediated activation of EphB2 receptors and their differential outgrowth on ephrinB2-Fc / Fc stripes.

Finally, the authors demonstrated an in vivo function of this complex using another model system, C elegans where they were able to show a genetic interaction.

Data show in a nice set of experiments a novel level of EphB2 forward signalling where a ternary complex of this receptor with multifunctional MYCBP2 and Fbxo45 controls the activity of EphB2, allowing a further complex regulation of this important receptors. Additionally, the authors challenge pre-existing concepts of the function of MYCBP2 which might open up novel ways to think about this protein.<br /> Of interest is this work also in terms of development of the retinotectal projection in zebrafish where MYCBP2/highwire plays a crucial role, and thus might lead to a better understanding of patterning along the DV axis, for which it is known that EphB family members are crucial.

Overall, the experiments are classical experiments of co-immunoprecipitations, swapping experiments, collapse assays, and stripe assays which all are well carried out and are convincing.

Reviewer #1 (Public Review):

Summary:<br /> Ngoune et al. present compelling evidence that Slender cells are challenged to infect tsetse flies. They explore the experimental context of a recent important paper in the field, Schuster et al., that presents evidence suggesting the proliferative Slender bloodstream T.brucei can infect juvenile tsetse flies. Schuster et al. were disruptive to the widely accepted paradigm that the Stumpy bloodstream-form is solely responsible for tsetse infection and T.brucei transmission potential.

Evidence presented here shows that in all cases, Stumpy form parasites are exponentially more capable of infecting tsetse flies. They further show that Slender cells do not infect mature flies.

However, they raise questions of immature tsetse immunological potential and field transmission potential that their experiments do not address. Specifically, they do not show that teneral tsetse flies are immunocompromised, that tsetse flies must be immunocompromised for Slender infection nor that younger teneral tsetse infection is not pertinent to field transmission.

Strengths:<br /> Experimental Design is precise and elegant, outcomes are convincing. Discussion is compelling and important to the field. This is a timely piece that adds important data to a critical discussion of host: parasite interactions, of relevance to all parasite transmission.

Weaknesses:<br /> As above, the authors dispute the biological relevance of teneral tsetse infection in the wild, without offering evidence to the contrary. Statements need to be softened for claims regarding immunological competence or relevance to field transmission.

Reviewer #2 (Public Review):

Summary:<br /> Contrary to findings recently reported by Schuster S et al., this short paper shows evidence that the stumpy form of T. brucei is probably the most pre-adapted form to progress with the life cycle of this parasite in the tsetse vector.

Strengths:<br /> One of the most important pieces of experimental evidence is that they conduct all fly infection experiments in the absence of metabolites like GlcNAc or S-glutathione; by doing so, the infection rates in flies infected with slender trypanosomes seem very low or nonexistent. This, on its own, is a piece of important experimental evidence that the Schuster S et al findings may need to be revisited.

Weaknesses:<br /> I consider that the authors should have included their own experiments demonstrating that the addition of these chemicals enhances the infection rates in flies receiving bloodmeals containing slender trypanosomes.

Reviewer #3 (Public Review):

The dogma in the Trypanosome field is that transmission by Tsetse flies is ensured by stumpy forms. This has been recently challenged by the Engstler lab (Schuster et al. ), which showed that slender forms can also be transmitted by teneral flies. In this work, the authors aimed to test whether transmission by slender forms is possible and frequent.

For this, the authors repeated Tsetse transmission experiments but with some key critical differences relative to Schuster et al. First, they infected teneral and adult flies. Second, their infective meals lacked two components (N-acetylglucosamine and glutathione), which could have boosted the infection rates in the Schuster et al. work. In these conditions, the authors observed that most stumpy form infections with teneral and adult flies were successful while only 1 out of 24 slender-form infections was successful. Adult flies showed a lower infection rate, which is probably because their immune system is more developed.

Given that in Tsetse-infested areas most transmission is likely ensured by adult flies, the authors conclude that the parasite stage that will have a significant epidemiologic impact on transmission is the stumpy form.

Strengths:<br /> • This work tackles an important question in the field.<br /> • The Rotureau laboratory has well-known expertise in Tsetse fly transmission experiments.<br /> • Experimental setup is robust and data is solid.<br /> • The paper is concise and clearly written.

Weaknesses:<br /> • The reason(s) for why this work has lower infection rates with slender forms than Schuster et al. remain unknown. The authors suggested it could be because of the absence of N-acetylglucosamine and/or glutathione, but this was not formally tested. Could another source of variation be the clone of EATRO1125 AnTat1.1 (Paris versus Munich origin)? To reduce the workload, such additional experiments could be done with just one dose of parasites.<br /> • The characterization of what is slender and stumpy is critical. The authors used PAD1 protein expression as the sole reporter. While this is a robust assay to confirm stumpy, an analysis of the cell cycle would have been helpful to confirm that slender forms have not initiated differentiation (Larcombe S et al. 2023, preprint).<br /> • Statistical analysis is missing. Is the difference between adult and teneral infections statistically significant?

Reviewer #1 (Public Review):

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

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

Reviewer #1 (Public Review):

Summary:<br /> Van der Heijden et al perform an ambitious analysis of single-unit activity in the interposed nuclei of multiple mouse models of cerebellar dysfunction. Based on these recordings, they develop a classifier to predict the behavioral phenotype (ataxic, dystonic, or tremor) of each model, suggesting that highly regular spiking is associated with ataxia, irregular spiking is associated with dystonia and rhythmic spiking is associated with tremor. After developing this classifier, they show that activating Purkinje neurons in different patterns that evoke interposed nuclear activity similar to their "ataxic", "dystonic", and "tremor" firing patterns induce similar behaviors in healthy mice. These results show convincingly that specific patterns of cerebellar output are sufficient to cause specific movement abnormalities. The extent to which cerebellar nuclear firing patterns are solely responsible for phenotypes in human disease remains to be established, however.

Strengths:<br /> Major strengths are the recordings across multiple phenotypic models including genetic and pharmacologic manipulations, and the robust phenotypes elicited by Purkinje neuron stimulation.

Weaknesses:<br /> The number of units recorded was small for each model (on the order of 20), limiting the conclusions that can be drawn from the recording/classifier experiments.

Reviewer #2 (Public Review):

Cerebellar diseases can manifest as various behavioral phenotypes, such as ataxia, dystonia, and tremor. In this study, Heijden and colleagues aim to understand whether these differing behavioral phenotypes are associated with disease-specific changes in the firing patterns of cerebellar output neurons in the cerebellar nuclei (CN). The authors effectively demonstrate that across different mouse models of cerebellar disease, there are distinct changes in the firing properties of CN neurons. They take a crucial step further by attempting to replicate disease-specific firing patterns in the cerebellar output neurons of healthy (control) mice using optogenetics. When Purkinje cells are stimulated in a manner that results in similar firing properties in CN neurons, the authors observe a variety of atypical behavioral responses, many of which align with the behavioral phenotypes observed in mouse models of the respective diseases.

Overall, the primary results are quite convincing. Specifically, they show that (1) different mouse models of cerebellar disease exhibit different statistics of firing in CN neurons, and (2) driving CN neurons in a time-varying manner that mimics the statistics measured in disease models results in behavioral phenomena reminiscent of the disease states. These findings suggest that aberrant activity in the CN can originate from various sources (e.g., developmental circuit deficits, abnormal plasticity, insult), but ultimately, these changes are funneled through the CN neurons, whose firing rates are affected, and this, in turn, drives aberrant behavior. This is a noteworthy observation that underscores the potential of targeting these output neurons in the treatment of cerebellar disease. Moreover, this manuscript provides valuable insights into the firing patterns associated with the most common cerebellar-dependent disease phenotypes.

However, the paper falls short in terms of the classifier model itself. The current implementation of this classifier appears to be rather weak. For instance, the cross-validated performance on the same disease line mouse model for tremor is only 56%. While I understand that the classifier aims to simplify a high-dimensional dataset into a more manageable decision tree, its rather poor performance undermines the authors' main objectives. In a similar vein, although focusing on three primary features of spiking statistics identified by the decision tree model (CV, CV2, and median ISI) is useful for understanding the primary differences between the firing statistics of different mouse models, it results in an overly simplistic view of this complex data. The classifier and its reliance on the reduced feature set are the weakest points of the paper and could benefit from further analysis and a different classification architecture. Nevertheless, it is commendable that the authors have collected high-quality data to validate their classifier. Particularly impressive is their inclusion of data from multiple mouse models of ataxia, dystonia, and tremor, enabling a true test of the classifier's generalizability.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript looks at the single-cell spike signatures taken from in vivo cerebellar nuclear neurons from awake mice suffering from 3 distinct diseases and uses a sophisticated classifier model to predict disease based on a number of different parameters about the spiking patterns, rather than just one or two. Single read-outs of spike firing patterns did not show significant differences between all 4 groups meaning that you need to analyze multiple parameters of the spike trains to get this information. The results are really satisfying and intriguing, with some diseases separating very well, and others having more overlap. It also represents a significant advancement for the rigor and creativity used for analyzing cerebellar output spike patterns. I really like this paper, it's a clever idea and has been done very well.

The authors examine multiple distinct forms of different diseases, including different types of ataxia, dystonia, and tremor. While some of the interpretation of this work remains unclear to this reviewer (in particular Figure 2, with ataxia models), I applaud the rigor and sharing of complex data that is not always straightforward to understand.

Strengths:<br /> The work is technically impressive and the analysis pushes the envelope of how cerebellar dysfunction is classified, which makes it an important paper for the field. It's well written. The approach it is taking is clever. The analysis is thorough, and the authors examine a wide array of different disease models, which is time-consuming, costly, and very challenging to do. It's a very strong manuscript.

Weaknesses:<br /> Weaknesses are few and quite minor. Some rewriting could be done to make certain sections clearer.

Joint Public Review:

Summary<br /> This is a very meticulous and precise anatomical description of the external sensory organs (sensillia) in Drosophila larvae. Extending on their previous study (Rist and Thum 2017) that analyzed the anatomy of the terminal organ, a major external taste organ of fruit fly larva, the authors examined the anatomy of the remaining head sensory organs - the dorsal organ, the ventral organ, and the labial organ-also described the sensory organs of the thoracic and abdominal segments. Improved serial electron microscopy and digital modeling are used to the fullest to provide a definitive and clear picture of the sensory organs, the sensillia, and adjacent ganglia, providing an integral and accurate map, which is dearly needed in the field. The authors revise all the data for the abdominal and thoracic segments and describe in detail, for the first time, the head and tail segments and construct a complete structural and neuronal map of the external larval sensilla.

Strengths<br /> It is a very thorough anatomical description of the external sensory organs of the genetically amenable fruitfly. This study represents a very useful tool for the research community that will definitely use it as a reference paper. In addition to the classification and nomenclature of the different types of sensilla throughout the larval body, the wealth of data presented here will be valuable to the scientific community. It will allow for investigating sensory processing in depth. Serial electron microscopy and digital modeling are used to the fullest to provide a comprehensive, definitive, and clear picture of the sensory organs. The discussion places the anatomical data into a functional and developmental frame. The study offers fundamental anatomical insights, which will be helpful for future functional studies and to understand the sensory strategies of Drosophila larvae in response to the external environment. By analyzing different larval stages (L1 and L3), this work offers some insights into the developmental aspects of the larval sense organs and their corresponding sensory cells.

Weaknesses<br /> There are no apparent weaknesses, although it is not a complete novel anatomical study. It revisits many data that already existed, adding new information. However, the repetitiveness of some data and prior studies may be avoided for easy readability.

Reviewer #1 (Public Review):

In this manuscript, Lee et al. compared encoding of odor identity and value by calcium signaling from neurons in the ventral pallidum (VP) in comparison to D1 and D2 neurons in the olfactory tubercle (OT).

Strengths: They utilize a strong comparative approach, which allows the comparison of signals in two directly connected regions. First, they demonstrate that both D1 and D2 OT neurons project strongly to the VP, but not the VTA or other examined regions, in contrast to accumbal D1 neurons which project strongly to the VTA as well as the VP. They examine single unit calcium activity in a robust olfactory cue conditioning paradigm that allows them to differentiate encoding of olfactory identity versus value, by incorporating two different sucrose, neutral and air puff cues with different chemical characteristics. They then use multiple analytical approaches to demonstrate strong, low-dimensional encoding of cue value in the VP, and more robust, high-dimensional encoding of odor identity by both D1 and D2 OT neurons, though D1 OT neurons are still somewhat modulated by reward contingency/value. Finally, they utilize a modified conditioning paradigm that dissociates reward probability and lick vigor to demonstrate that VP encoding of cue value is not dependent on encoding of lick vigor during sucrose cues, and that separable populations of VP neurons encode cue value/sucrose probability and lick vigor.

Weaknesses: The conclusions of the data are mostly well supported by the analyses, but the statistical analysis is somewhat limited and needs to be clarified and extended.

1) The manuscript includes limited direct statistical comparison of the neural populations, and many of the comparisons between the subregions are descriptive, including descriptions of the percentage of neurons having specific response types, or differences in effect sizes or differing "levels" of significance. An additional direct comparison of data from each subpopulation would help to confirm whether the differences reported are statistically meaningful.

2) When hypothesis tests are conducted between the neural populations, it is not clear whether the authors have accounted for the random effect of the subject, or whether individual units were treated as fully independent. For instance, pairwise differences are reported in Figures 4I, 5G/I/L, and others, but the statistical methods are unclear. Assessment of the statistics is further limited by the lack of reporting of degrees of freedom.

Reviewer #2 (Public Review):

Summary:<br /> This work is interesting since the authors provide an in vivo analysis into how odor-associations may change as represented at the level of olfactory tubercle (presynaptic) and next at the level of the ventral pallidum (postsynaptic). First the authors start-off with a seemingly careful characterization of the anterograde and retrograde connectivity of dopamine 1 receptor (D1) and dopamine 2 receptor (D2) expressing medium spiny neurons in the olfactory tubercle and neurons in the ventral pallidum. From this work they claim that regardless of D1 or D2 expression, tubercle neurons mainly project to the lateral portion of the ventral pallidum. Next, to compare how odor-associated neuronal activity in the ventral pallidum and the olfactory tubercle (D1 vs D2 MSNs) transforms across association learning, the authors performed 2-photon calcium imaging while mice engaged in a lick / no-lick task wherein two odors are associated with reward, two odors are associated with no outcome, and two odors are associated with an air puff.

This manuscript builds off of prior work by several groups indicating that the olfactory tubercle neurons form flexible learned associations to odors by looking at outputs into the pallidum (but without looking specifically at palladial neurons that truly get input from tubercle I should highlight) and with that, this work is novel. We appreciated the use of a straight-forward odor-outcome behavioral paradigm and the careful computational methods and analyses utilized to disentangle the contributions of single neurons vs population level responses to behavior. With one exception from the Murthy lab, 2P imaging in the tubercle is a new frontier and that is appreciated - as is the 2P imaging in the pallidum which was well-supported by the histology. The anatomical work is also well presented.

Overall the approach and methods are superb. The issues come when considering how the authors present the story and what conclusions are made from these data. Several key points before going into specifics about each are: 1) The authors can not conclude that their results are contradictory to prior results, 2) The authors over-interpret the results and do not discuss several key methodological issues. We were concerned with the ability to make strong claims regarding the circuitry presented, especially given how much the presented claims contradict prior work. There were also issues with the interpretability of neuronal encoding of value vs valence based on the present behavior (in which a distinction between the air puff and neutral trial types was not clear) and the imaging methodology (in which the neuronal populations analyzed were not clearly defined). In addition to toning down and rectifying some of the language and interpretations, we suggest including a study limitations section where these methodological and interpretation issues are discussed. Over-interpreting and playing up the significance of this work is unnecessary. Readers should be given a sufficiently detailed and nuanced presentation of these thought-provoking results, and from there allowed to interpret the results as they want.

Strengths:<br /> State-of-the-art approaches (as detailed above)

Possible conceptual innovation in terms of looking into output from the olfactory tubercle which has yet to be investigated in this avenue.

Weaknesses:<br /> On the first point regarding the authors repeated and unsupported claims that their results are contradictory. There are papers by numerous groups, in respected journals including this one, all together which used 5 different methods (cfos, photometry, 2P, units, fMRI), in animals ranging from humans to mice, which support that tubercle neurons reflect the emotional association of an odor, whether spontaneous or learned. With that, it is on the authors to not claim that their results contradict as if the other papers are suspect, but instead, from our standpoint it is on the authors to explain how and why their results differ from these other papers versus just simply saying they found something different [which at present is framed in a way that is 'correct' due to primacy if nothing else].

Second, onto the points of interpretation of results, there are several specific areas where this should be rectified. As is, the authors overinterpret their results and draw too far-reaching conclusions. This needs to be corrected.

In particular, the claims that D1 and D2 neurons of the olfactory tubercle nearly exclusively send projections to the ventral pallidum must be interpreted with caution given that the authors injected an anterograde AAV into the anteromedial olfactory tubercle, and did not examine the projections from either the posterior or lateral portions of the olfactory tubercle. This is especially significant since the retrograde tracing performed from the ventral pallidum indicates that the lateral olfactory tubercle, not the medial olfactory tubercle, primarily projects to the ventral pallidum (Fig 1D-F), however this may be due to leakage into the nucleus accumbens, as seen in the supplementary figure, S1G. The same caution must be advised when interpreting the retrograde tracing performed in Fig 1G-I, since the neuronal tracer used and the laterality and rostral-caudal injection site within the VTA could result in different projection patterns and under- or over-labelling. Additionally, the metric used, %Fiber Density (Figure 1C), as in the percentage of 16-bit pixels within the region of interest with an intensity greater than 200, is semi-quantitative, and is more applicable for examining axonal fibers that pass through a region rather than the synaptic terminals (like with a synaptophysin fusion protein-based tracing paradigm) found within a region (puncta). The statements made in contrast to prior studies should therefore be softened, and these concerns should be addressed in the introduction, discussion, and the limitations section if added.

The other major concern is whether the behavioral data generated is indicative of the full spectrum of valence. The authors appropriately state that the mice "perceive" the air puff, yet based on their data the mice did not clearly experience the puff-associated odor as emotionally aversive (viz., negative valence). The way the authors describe these results, it seems they agree with this. With that, the authors can't say the puff is aversive without data to show such - that is an assumption which, while seemingly intuitive, is not supported by the data unfortunately. To elaborate more since this is important to the messaging of the paper: The authors utilized a simple behavioral design, wherein two molecular classes of odors were included in either a sucrose rewarded, neutral no outcome, or air puff punished trial type. The odor-outcome pairs were switched after three days, allowing the authors to compare neuronal responses on the basis of odor identity and the later associated outcome. While the mice showed clear learning of the rewarded trial types by an increase in anticipatory licking during the odor, they did not show any significant changes in behavior that indicated learning of the air puff trial type (change in running velocity or % maximal eye size), especially in contrast to the neutral trial type. This brings up the concern that either the odor-air puff aversive associations (to odors) were not learned, or that the neutral trial types, in which a reward was omitted, were just as aversive as the air puff to the rear, despite the lack of startle response - perhaps due to stimulus generalization between neutral and air puff odor. The possibility of lack of learning is addressed in the paragraph starting at line 578, but does not account for the possibility that the lack of reward is also sufficiently punishing. The authors also address the possibility that laterality in the VP contributed to the lack of neural responsivity observed, but should also include a statement regarding laterality in the olfactory tubercle, as described in https://doi.org/10.7554/eLife.25423 and https://doi.org/10.1523/JNEUROSCI.0073-15.2015, since the effects of modulating the lateral portion of the olfactory tubercle are not yet reported. Lastly, use of the term "reward processing" should be avoided/omitted since the authors did not specifically study the processing of reinforcers.

Also, I would appreciate justification of the term "value". How specifically does the assay used assess value versus a more simplistic learned association which influences perceived hedonics or valence of the odors.

More information is needed regarding how neurons are identified day-to-day, both in textual additions to the Methods and also in terms of elaborating more in the results and/or figure legends about what neurons are included:<br /> a) The ROI maps for identifying/indicating cells in the FOVs are nice to see and at the same time raise some concerns about how cells are identified and/or borders for those specific ROIs drawn. For instance, Figure 4, A & D, ROI #13 (cell #13) between those two panels is VERY different in shape/size. Also see ROIs 15 and 4. Why was an ROI map not made on day 1 and then that same map applied and registered to frames from consecutive imaging days in that same mouse? As it is new ROIs are drawn, smaller for some "cells" and larger for others. And at least in ROI #13 above, one ROI is about twice as large as the other. This inconsistency in the work flow and definition of the ROIs is needing to be addressed in Methods. Also, the authors should address if and how this could possibly impact their results.<br /> b) Also, more details are needed in results and/or figure legends regarding the changes in cell numbers over days that are directly compared in the results. Some days there are 10% or more or less cells. Why? It is not the same population being compared in this case and so some Discussion of this is needed.

Reviewer #3 (Public Review):

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

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

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

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

Weaknesses:

The authors' interpretation of the physiologic results - that a novel framework is needed to interpret the OT's role - requires more careful treatment.

Reviewer #2 (Public Review):

The authors applied two visual working memory tasks, a memory-guided localization (MGL), examining short-term memory of the location of an item over a brief interval, and an N-back task, examining orientation of a centrally presented item, in order to test working memory performance in patients with multiple sclerosis (including a subgroup with relapsing-remitting and one with secondary progressive MS), compared with healthy control subjects. The authors used an approach in testing and statistically modelling visual working memory paradigm previously developed by Paul Bays, Masud Husain and colleagues. Such continuous measure approaches make it possible to quantify the precision, or resolution, of working memory, as opposed to measuring working memory using discretised, all-or-none measures. This represents an advance beyond prior work in this area.

The authors of the present study found that both MS subgroups performed worse than controls on the N-back task and that only the secondary progressive MS subgroup was significantly impaired on the MGL task. The underlying sources of error including incorrect association of an object's identity with its location or serial order, were also examined.

The application of more precise psychophysiological methods to test visual working memory in multiple sclerosis should be applauded. It has the potential to lead to more sensitive and specific tests which could potentially be used as useful outcome measures in clinical trials of disease-modifying drugs, for example.

The present study does not compare the continuous-report testing with a discrete measure task so it is unclear whether the former is more sensitive, or more feasible in this patient group, although this may not have been the purpose of the study.

Comments on the revised submission: My previous comments have been answered to the extent that is possible with the data available.

Reviewer #1 (Public Review):

This study compares visuospatial working (VWM) memory performance between patients with MS and healthy controls, assessed using analog report tasks that provide continuous measures of recall error. The aim is to advance on previous studies of VWM in MS that have used binary (correct/incorrect) measures of recall, such as from change detection tasks, that are not sensitive to the resolution with which features can be recalled, and to use mixture modelling to disentangle different contributions to overall performance. The results identify a specific decrease in the precision of VWM recall in MS, although the possibility that visual and/or motor impairments contribute to performance decrements on the memory task cannot be ruled out.

Reviewer #1 (Public Review):

Summary:<br /> Ever-improving techniques allow the detailed capture of brain morphology and function to the point where individual brain anatomy becomes an important factor. This study investigated detailed sulcal morphology in the parieto-occipital junction. Using cutting-edge methods, it provides important insights into local anatomy, individual variability, and local brain function. The presented work advances the field and will stimulate future research into this important area.

Strengths:<br /> Detailed, very thorough methodology. Multiple raters mapped detailed sulci in a large cohort. The identified sulcal features and their functional and behavioural relevance are then studied using various complementary methods. The results provide compelling evidence for the importance of the described sulcal features and their proposed relationship to cortical brain function.

Weaknesses:<br /> A detailed description/depiction of the various sulcal patterns is missing. A possible relationship between sucal morphology and individual demographics might provide more insight into anatomical variability. The unique dataset offers to opportunity to provide insights into laterality effects that should be explored.

Reviewer #2 (Public Review):

Summary: After manually labelling 144 human adult hemispheres in the lateral parieto-occipital junction (LPOJ), the authors 1) propose a nomenclature for 4 previously unnamed highly variable sulci located between the temporal and parietal or occipital lobes, 2) focus on one of these newly named sulci, namely the ventral supralateral occipital sulcus (slocs-v) and compare it to neighbouring sulci to demonstrate its specificity (in terms of depth, surface area, gray matter thickness, myelination, and connectivity), 3) relate the morphology of a subgroup of sulci from the region including the slocs-v to the performance in a spatial orientation task, demonstrating behavioural and morphological specificity. In addition to these results, the authors propose an extended reflection on the relationship between these newly named landmarks and previous anatomical studies, a reflection about the slocs-v related to functional and cytoarchitectonic parcellations as well as anatomic connectivity and an insight about potential anatomical mechanisms relating sulcation and behaviour.

Strengths:<br /> - To my knowledge, this is the first study addressing the variable tertiary sulci located between the superior temporal sulcus (STS) and intra-parietal sulcus (IPS).<br /> - This is a very comprehensive study addressing altogether anatomical, architectural, functional and cognitive aspects.<br /> - The definition of highly variable yet highly reproducible sulci such as the slocs-v feeds the community with new anatomo-functional landmarks (which is emphasized by the provision of a probability map in supp. mat., which in my opinion should be proposed in the main body).<br /> - The comparison of different features between the slocs-v and similar sulci is useful to demonstrate their difference.<br /> - The detailed comparison of the present study with state of the art contextualises and strengthens the novel findings.<br /> - The functional study complements the anatomical description and points towards cognitive specificity related to a subset of sulci from the LPOJ<br /> - The discussion offers a proposition of theoretical interpretation of the findings<br /> - The data and code are mostly available online (raw data made available upon request).

Weaknesses:<br /> - While three independent raters labelled all hemispheres, one single expert finalized the decision. Because no information is reported on the inter-rater variability, this somehow equates to a single expert labelling the whole cohort, which could result in biased labellings and therefore affect the reproducibility of the new labels.<br /> - 3 out of the 4 newly labelled sulci are only described in the very first part and never reused. This should be emphasized as it is far from obvious at first glance of the article.<br /> - The tone of the article suggests a discovery of these 4 sulci when some of them have already been reported (as rightfully highlighted in the article), though not named nor studied specifically. This is slightly misleading as I interpret the first part of the article as a proposition of nomenclature rather than a discovery of sulci.<br /> - The article never mentions the concept of merging of sulcal elements and the potential effect it could have on the labelling of the newly named variable sulci.<br /> - The definition of the new sulci is solely based on their localization relative to other sulci which are themselves variable (e.g. the 3rd branch of the STS can show different locations and different orientation, potentially affecting the definition of the slocs-v). This is not addressed in the discussion.<br /> - The new sulci are only defined in terms of localization relative to other sulci, and no other property is described (general length, depth, orientation, shape...), making it hard for a new observer to take labelling decisions in case of conflict.<br /> - The very assertive tone of the article conveys the idea that these sulci are identifiable certainly in most cases, when by definition these highly variable tertiary sulci are sometimes very difficult to take decisions on.<br /> - I am not absolutely convinced with the labelling proposed of a previously reported sulcus, namely the posterior intermediate parietal sulcus.

Assuming that the labelling of all sulci reported in the article is reproducible, the different results are convincing and in general, this study achieves its aims in defining more precisely the sulcation of the LPOJ and looking into its functional/cognitive value. This work clearly offers a finer understanding of sulcal pattern in this region, and lacks only little for the new markers to be convincingly demonstrated. An overall coherence of the labelling can still be inferred from the supplementary material which support the results and therefore the conclusions, yet, addressing some of the weaknesses listed above would greatly enhance the impact of this work. This work is important to the understanding of sulcal variability and its implications on functional and cognitive aspects.

Reviewer #3 (Public Review):

Summary: 72 subjects, and 144 hemispheres, from the Human Connectome Project had their parietal sulci manually traced. This identified the presence of previously undescribed shallow sulci. One of these sulci, the ventral supralateral occipital sulcus (slocs-v), was then demonstrated to have functional specificity in spatial orientation. The discussion furthermore provides an eloquent overview of our understanding of the anatomy of the parietal cortex, situating their new work into the broader field. Finally, this paper stimulates further debate about the relative value of detailed manual anatomy, inherently limited in participant numbers and areas of the brain covered, against fully automated processing that can cover thousands of participants but easily misses the kinds of anatomical details described here.

Strengths:<br /> - This is the first paper describing the tertiary sulci of the parietal cortex with this level of detail, identifying novel shallow sulci and mapping them to behaviour and function.<br /> - It is a very elegantly written paper, situating the current work into the broader field.<br /> - The combination of detailed anatomy and function and behaviour is superb.

Weaknesses:<br /> - the numbers of subjects are inherently limited both in number as well as in being typically developing young adults.<br /> - while the paper begins by describing four new sulci, only one is explored further in greater detail.<br /> - there is some tension between calling the discovered sulci new vs acknowledging they have already been reported, but not named.<br /> - the anatomy of the sulci, as opposed to their relation to other sulci, could be described in greater detail.

Overall, to summarize, I greatly enjoyed this paper and believe it to be a highly valued contribution to the field.

Reviewer #1 (Public Review):

Summary:<br /> The authors provide very compelling evidence that the lateral septum (LS) engages in theta cycle skipping.

Strengths:<br /> The data and analysis are highly compelling regarding the existence of cycle skipping.

Weaknesses:<br /> The manuscript falls short on describing the behavioral or physiological importance of the witnessed theta cycle skipping, and there is a lack of attention to detail with some of the findings and figures:

More/any description is needed in the article text to explain the switching task and the behavioral paradigm generally. This should be moved from only being in methods as it is essential for understanding the study.

An explanation is needed as to how a cell can be theta skipping if it is not theta rhythmic.

The most interesting result, in my opinion, is the last paragraph of the entire results section, where there is more switching in the alternation task, but the reader is kind of left hanging as to how this relates to other findings. How does this relate to differences in decoding of relative arms (the correct or incorrect arm) during those theta cycles or to the animal's actual choice? Similarly, how does it relate to the animal's actual choice? Is this phenomenon actually behaviorally or physiologically meaningful at all? Does it contribute at all to any sort of planning or decision-making?

The authors state that there is more cycle skipping in the alternation task than in the switching task, and that this switching occurs in the lead-up to the choice point. Then they say there is a higher peak at ~125 in the alternation task, which is consistent. However, in the final sentence, the authors note that "This result indicates that the representations of the goal arms alternate more strongly ahead of the choice point when animals performed a task in which either goal arm potentially leads to reward." Doesn't either arm potentially lead to a reward (but different amounts) in the switching task, not the alternation task? Yet switching is stronger in the alternation task, which is not constant and contradicts this last sentence.

Additionally, regarding the same sentence - "representations of the goal arms alternate more strongly ahead of the choice point when the animals performed a task in which either goal arm potentially leads to reward." - is this actually what is going on? Is there any reason at all to think this has anything to do with reward versus just a navigational choice?

Similarly, the authors mention several times that the LS links the HPC to 'reward' regions in the brain, and it has been found that the LS represents rewarded locations comparatively more than the hippocampus. How does this relate to their finding?

Reviewer #2 (Public Review):

Summary<br /> Recent evidence indicates that cells of the navigation system representing different directions and whole spatial routes fire in a rhythmic alternation during 5-10 Hz (theta) network oscillation (Brandon et al., 2013, Kay et al., 2020). This phenomenon of theta cycle skipping was also reported in broader circuitry connecting the navigation system with the cognitive control regions (Jankowski et al., 2014, Tang et al., 2021). Yet nothing was known about the translation of these temporally separate representations to midbrain regions involved in reward processing as well as the hypothalamic regions, which integrate metabolic, visceral, and sensory signals with the descending signals from the forebrain to ensure adaptive control of innate behaviors (Carus-Cadavieco et al., 2017). The present work aimed to investigate theta cycle skipping and alternating representations of trajectories in the lateral septum, neurons of which receive inputs from a large number of CA1 and nearly all CA3 pyramidal cells (Risold and Swanson, 1995). While spatial firing has been reported in the lateral septum before (Leutgeb and Mizumori, 2002, Wirtshafter and Wilson, 2019), its dynamic aspects have remained elusive. The present study replicates the previous findings of theta-rhythmic neuronal activity in the lateral septum and reports a temporal alternation of spatial representations in this region, thus filling an important knowledge gap and significantly extending the understanding of the processing of spatial information in the brain. The lateral septum thus propagates the representations of alternative spatial behaviors to its efferent regions. The results can instruct further research of neural mechanisms supporting learning during goal-oriented navigation and decision-making in the behaviourally crucial circuits entailing the lateral septum.

Strengths<br /> To this end, cutting-edge approaches for high-density monitoring of neuronal activity in freely behaving rodents and neural decoding were applied. Strengths of this work include comparisons of different anatomically and probably functionally distinct compartments of the lateral septum, innervated by different hippocampal domains and projecting to different parts of the hypothalamus; large neuronal datasets including many sessions with simultaneously recorded neurons; consequently, the rhythmic aspects of the spatial code could be directly revealed from the analysis of multiple spike trains, which were also used for decoding of spatial trajectories; and comparisons of the spatial coding between the two differently reinforced tasks.

Weaknesses<br /> Possible in principle, with the present data across sessions, longitudinal analysis of the spatial coding during learning the task was not performed. Without using perturbation techniques, the present approach could not identify the aspects of the spatial code actually influencing the generation of behaviors by downstream regions.

Reviewer #3 (Public Review):

Summary:<br /> Bzymek and Kloosterman carried out a complex experiment to determine the temporal spike dynamics of cells in the dorsal and intermediate lateral septum during the performance of a Y-maze spatial task. In this descriptive study, the authors aim to determine if inputting spatial and temporal dynamics of hippocampal cells carry over to the lateral septum, thereby presenting the possibility that this information could then be conveyed to other interconnected subcortical circuits. The authors are successful in these aims, demonstrating that the phenomenon of theta cycle skipping is present in cells of the lateral septum. This finding is a significant contribution to the field as it indicates the phenomenon is present in neocortex, hippocampus, and the subcortical hub of the lateral septal circuit. In effect, this discovery closes the circuit loop on theta cycle skipping between the interconnected regions of the entorhinal cortex, hippocampus, and lateral septum. Moreover, the authors make 2 additional findings: 1) There are differences in the degree of theta modulation and theta cycle skipping as a function of depth, between the dorsal and intermediate lateral septum; and 2) The significant proportion of lateral septum cells that exhibit theta cycle skipping, predominantly do so during 'non-local' spatial processing.

Strengths: The major strength of the study lies in its design, with 2 behavioral tasks within the Y-maze and a battery of established analyses drawn from prior studies that have established spatial and temporal firing patterns of entorhinal and hippocampal cells during these tasks. Primary among these analyses, is the ability to decode the animal's position relative to locations of increased spatial cognitive demand, such as the choice point before the goal arms. The presence of theta cycle skipping cells in the lateral septum is robust and has significant implications for the ability to dissect the generation and transfer of spatial routes to goals within and between the neocortex and subcortical neural circuits.

Weaknesses: There are no major discernable weaknesses in the study, yet the scope and mechanism of the theta cycle phenomenon remain to be placed in the context of other phenomena indicative of spatial processing independent of the animal's current position. An example of this would be the ensemble-level 'scan ahead' activity of hippocampal place cells (Gupta et al., 2012; Johnson & Redish, 2007). Given the extensive analytical demands of the study, it is understandable that the authors chose to limit the analyses to the spatial and burst firing dynamics of the septal cells rather than the phasic firing of septal action potentials relative to local theta oscillations or CA1 theta oscillations. Yet, one would ideally be able to link, rather than parse the phenomena of temporal dynamics. For example, Tingley et al recently showed that there was significant phase coding of action potentials in lateral septum cells relative to spatial location (Tingley & Buzsaki, 2018). This begs the question as to whether the non-uniform distribution of septal cell activity within the Y-maze may have a phasic firing component, as well as a theta cycle skipping component. If so, these phenomena could represent another means of information transfer within the spatial circuit during cognitive demands. Alternatively, these phenomena could be part of the same process, ultimately representing the coherent input of information from one region to another. Future experiments will therefore have to sort out whether theta cycle skipping, is a feature of either rate or phase coding, or perhaps both, depending on circuit and cognitive demands.

The authors have achieved their aims of describing the temporal dynamics of the lateral septum, at both the dorsal extreme and the intermediate region. All conclusions are warranted.

Reviewer #1 (Public Review):

Summary:

This manuscript describes the development of an oral THC consumption model in mice where THC is added to a chocolate flavored gelatin. The authors compared the effects of THC consumed in this highly palatable gelatin (termed E-gel) to THC dissolved in a less palatable gelatin (CTR-gel), and to i.p. injections of multiple doses of THC, on the classic triad of CB1R dependent behaviors (hypolocomotion, antinociception, and body temperature).

The authors found that they could achieve consumption of higher concentrations of THC in the E-gel than the CTR-gel, and that this led to larger total dose exposure and decreases in locomotor activity, antinociception, and body temperature reductions similar to 3-4 mg/kg THC when tested after 2 hour consumption and roughly 10 mg/kg if tested immediately after 1 hour consumption. The majority of THC E-gel consumption was found to occur in the first hour on the first exposure day. THC E-gel consumption was lower than VEH E-gel consumption and this persisted on a subsequent consumption day, suggesting that the animals may form a taste aversion and that THC at the dose consumed likely has aversive properties, consistent with the literature on i.p. dosing. The authors also report the pharmacokinetics in brain and plasma of THC and metabolites after 1 or 2 hour consumption, finding high levels of THC in the brain that begins to dissipate at 2.5 hours is gone 24 hours later. Finally, the authors tested THC effects on the acoustic startle response and found an inverted dose response that was more pronounced in males than females after i.p. dosing and a greater startle response in males after E-gel dosing.

Overall, the authors find that voluntary oral consumption of THC can achieve levels of intake that are consistent with the present and prior reported literature on i.p. dosing.

Strengths:

The strengths of the article include a direct comparison of voluntary oral THC consumption to noncontingent i.p. administration, the use of multiple THC doses and oral THC formulations, the inclusion of multiple assays of cannabinoid agonist effects, and the inclusion of males and females. Additional strengths include monitoring intake over 10 minute intervals and validating that effects are CB1R dependent via antagonist studies.

Weaknesses:

1. The abstract does not discuss the reduction of E-gel consumption that occurs after multiple days of exposure to the THC formulation, but rather implies that a new model for chronic oral self-administration has been developed. Given that only two days of consumption was assessed, it is not clear if the model will be useful to determine THC effects beyond the acute measures presented here. The abstract should clarify that there was evidence of reduced consumption/aversive effects with repeated exposures.<br /> 2. In the results section, the authors sometimes describe effects in terms of the concentration of gel as opposed to the dose consumed in mg/kg, which can make interpretation difficult. For example, the text describing Figure 1i states that significant effects on body temperature were achieved at 4 mg CTR-gel and 5 mg THC-gel, but were essentially equivalent doses consumed? It would be helpful to describe what average dose of THC produced effects given that consumption varied within each group of mice assigned to a particular concentration.<br /> 3. The description of the PK data in Figure 3 did not specify if sex differences were examined. Prior studies have found that males and females can exhibit stark differences in brain and plasma levels of THC and metabolites, even when behavioral effects are similar. However, this does depend on species, route, timing of tissue collection. It would be helpful to describe the PK profile of males and females separately.<br /> 4. In Figure 5, it is unclear how the predicted i.p. THC dose could be 30 mg/kg when 30 mg/kg was not tested by the i.p. route according to the figure, and if it had been it would have likely been almost zero acoustic startle, not the increased startle that was observed in the 2 hr gel group. It seems more likely that it would be equivalent to 3 mg/kg i.p. Could there be an error in the modeling, or was it based on the model used for the triad effects? This should be clarified.

Reviewer #2 (Public Review):

Summary:<br /> The work fruitfully adds to the tools to study cannabinoid action and pharmacology specifically, but also this method is applicable to other drugs, in particular, if lipophilic in nature.

Strengths:<br /> The addition of chocolate flavor overcomes aversive reactions which are often experienced in pharmacological treatments, leading to possible caveats in the interpretation of the behavioral outcomes.

Weaknesses:<br /> Certainly, more THC mediated behavioral outcomes could have been tested, but the work presents a proof-of-concept study to investigate acute THC treatment.<br /> It would have been interesting if this application form is also possible for chronic treatment regimen

Reviewer #3 (Public Review):

Summary: This manuscript explores the development of a rodent voluntary oral THC consumption model. The authors use the model to demonstrate that similar effect levels of THC can be observed to what has previously been described for i.p. THC administration.

Strengths: Overall this is an interesting study with compelling data presented. There is a growing need within the field of cannabinoid research to explore more 'realistic' routes of cannabinoid administration, such as oral consumption or inhalation. The evidence presented here shows the utility of this oral administration model.

Weaknesses: The main weaknesses of the manuscript revolve around clarification of the Methods section. All of these weaknesses are described in the "Recommendations to authors" section. Revising the manuscript would account for many of these weaknesses.

Reviewer #1 (Public Review):

Prior research demonstrated that vocal learning is sexually dimorphic in zebra finches; female song nuclei atrophy and fail to develop, but can be rescued with exogenous 17-𝛃-estradiol (E2) treatment. In previous research, the authors treated both male and female birds with exogenous E2. They laser-captured dissected tissue samples from the E2-treated individuals as well as untreated controls. They then extracted RNA and used RNA-seq to characterize the transcriptomes within and adjacent to four major song nuclei (HVC, LMAN, RA, Area X) in these birds. In this study, Davenport et al. remapped this massive amount of transcriptome data (n=3 birds per sex/treatment group) to fully resolve the genomic location of differentially expressed genes, which they assigned to several modules based on co-expression. Adequate read mapping to all chromosomes was previously impossible with zebra finch genome assemblies lacking W chromosome data. Using the high-quality zebra finch genome assembly with Z and W chromosomes (bTaeGut2.pat.W.v2), the authors were able to demonstrate the enrichment of certain modules on certain chromosomes; most interestingly, Z chromosome gene expression was increased in E2-treated females. This research greatly improves our understanding of the ontology and location of genes involved in song development in E2-treated females, providing insight into the development of vocal learning in the zebra finch.

The authors' main conclusions on the importance of certain gene modules in the vocal learning process are well warranted by their excellent data and thorough analyses, but should not be too broadly interpreted as necessarily applying to the gene expression involved in vocal learning in other species. While the data here further supports convergent evolution in vocal learning genes in humans and zebra finches, vocal learning is unusually sexually dimorphic in zebra finches compared to most other vocal learners.

The authors note the possibility of female haploinsufficiency of Z-linked genes such as the growth hormone receptor (GHR) and also imply there are potential effects of the fission of the ancestral chromosome into passerine chromosomes 1 and 1A impacting the typical development of male zebra finch song and the lack thereof in females. These thoughts are intriguing and should prompt further transcriptomic research in avian species with the same genomic features (ZW females, split 1 and 1A chromosomes) where females also learn song, i.e. female-singing passerine species. Currently, it is impossible to say if female-singing species are, as is likely with the E2-treated zebra finch females, using estrogen signaling pathways to regulate an increase in dosage of these genes. Alternately, these female-singing birds may be using different gene modules, which is also worthy of investigation. This research excels at elucidating the genomic underpinnings of vocal learning in a model organism; further research will demonstrate how broadly applicable these authors' findings are across other species.

Reviewer #2 (Public Review):

This work tried to identify genes involved in the song learning of zebra finches by looking at gene expression from individuals who could learn to sing (males and E2-treated females) or not learn to sing (untreated females). They use extensive RNAseq data from one of their previous publications, but this time align the reads to a female genome (from another of their previous publications). Here they use traditional Weighted Gene Correlation Network Analysis (WGCNA) to identify modules (sets of genes whose expression co-varies across all samples) and then find how these sets of genes collectively differ between brain regions involved in song learning and the surrounding tissues not involved in song learning. This approach identified modules that were significantly different in expression between males and females, and the authors interpret this as sex chromosomes being involved in song learning. However, this approach is highly skewed by unrelated patterns of gene expression from the sex chromosomes due to a lack of dosage compensation in birds. In short, by generating WGCNA modules from males and females, all sex chromosome genes will be expected to be artificially pulled into one module due to methodological artifacts and not true biologically relevant differences.

Strengths:<br /> It's nice to see large datasets being reevaluated with updated genomes.

Weaknesses:<br /> Zebra finches (like all birds) do not have XX/XY sex determination, but instead have ZZ/ZW, which means that males have two copies of the Z chromosome and females have one copy of the Z and one copy of the W. This is important because it means that if males and females express all their genes at the same rate, then expression of Z genes will always be twice as high in males relative to females. [While mammals have mechanisms to equalize expression of X chromosome genes between males and females (aka. dosage compensation), birds do not have such chromosome-scale mechanisms.] Therefore, the expression of genes on the sex chromosomes of birds will always differ dramatically between males and females, without necessarily indicating any biologically meaningful difference. WGCNA-based approaches (such as those used here) form modules based on differences in gene expression across all samples. Since this manuscript used all samples to generate their WGCNA modules then all (or nearly all) of the expressed genes on the sex chromosomes would be expected to be pulled into the same module - which is precisely what happened: the reported 'module E' contained 904 genes, while there are only 1,078 genes annotated on the Z chromosome of the reference genome used. Some of these genes may 'belong' in other modules if there are regional differences, but the dosage-driven-differences between sexes across all regions will overwhelm these signals. Therefore great care needs to be taken when interpreting the results of this study until such time as independent analyses can verify these results.

Reviewer #3 (Public Review):

Summary:<br /> Davenport et al have investigated how the administration of a masculinizing dose of estrogen changes the transcriptomes of several key song nuclei song and adjacent brain areas in juvenile zebra finches of both sexes. Only male zebra finches sing, learn song, and normally have a fully developed song control circuitry, so the study was aimed at further understanding how genetic and hormonal factors contribute to the dimorphism in song behavior and related brain circuitry in this species. Using WGCNA and follow-up correlations to re-analyze published transcriptome datasets, the authors provide evidence that the main variance of several identified gene co-expression modules shows significant correlations with one or some of the factors examined, including sex, estrogen treatment, regional neuroanatomy, or occurrence of vocal learning.

Strengths:<br /> Among the main strengths are the thorough gene co-expression module and correlation analyses, and the inclusion of both song nuclei and adjacent areas, the latter serving as sort of controls for areas that are not dimorphic and likely broadly present in birds in general. The most relevant finding is arguably the identification of some modules where gene expression variation within song nuclei correlates with hormonal effects and/or gene location on sex chromosomes, which are present at different dosages between sexes. The study also shows how a published RNA-seq dataset can be reanalyzed in novel and informative ways.

Weaknesses:<br /> Among its main weaknesses, the study relies entirely on one set of transcriptomic data and lacks effort to validate the inferred direction of regulation in the identified co-expression modules using other molecular methods or approaches on independent samples. The study shows that some representative and/or highly significant genes in some of the main modules that correlate with anatomical, sex, or hormone treatment group comparisons indeed differ in expression when comparing song nuclei vs surroundings, male vs female, or E2- vs VEH-treated tissues in independent samples by qPCR or in situ hybridization would provide important validation and enhance experimental rigor for the analyses presented. In the absence of this further validation, the WGCNA data need to be interpreted with caution.

The findings related to ex-chromosome genes (i.e. module E) are a significant strength of the study. Two points, however, need to be taken into account more closely. First, sex differences in gene expression in areas that are not song nuclei are likely related to functions other than song behavior or vocal learning, thus not related to the main question posed by the study. Furthermore, an alternative interpretation with regard to sex chromosome gene expression is that the higher male expression for a large number of Z chromosome genes may not significantly or fundamentally affect brain cell function and can be tolerated, thus not requiring active compensation. This alternative interpretation (mentioned for song nucleus RA in Friedrich et al, Cell Reports, 2022) suggesting that the higher male dosage of many of these genes might not affect or contribute to sex differences in brain function, cannot at present be discarded, and should at least be acknowledged.

Friedrich et al, Cell Reports, 2022 (Table S3 ) presented an extensive manual curation of W chromosome genes in zebra finches. BLAST alignments showed that a large proportion of W chromosome genes are also on the Z, noting that only a small subset of these are annotated as Z:W pairs. The genes that are truly W-specific and present at a higher dosage in females are thus only a fraction of W-chromosome genes. This creates a complication when examining the mapping of RNA-seq reads to sex chromosomes: to conclude about higher expression of W genes in female tissue samples one needs to take into account reads that may also map to the homologous genes on the Z, if that gene is present as a W:Z pair. Because Friedrich et al mapped reads to a male genome assembly, W genes were not assessed, thus the present study provides novel info. However, the issues above need to be acknowledged and taken into account to accurately assess sex differences in W chromosome gene expression.

Reviewer #1 (Public Review):

Summary:<br /> This paper presents an innovative decoding approach for brain-computer interfaces (BCIs), introducing a new method named MINT. The authors develop a trajectory-centric approach to decode behaviors across several different datasets, including eight empirical datasets from the Neural Latents Benchmark. Overall, the paper is well written and their method shows impressive performance compared to more traditional decoding approaches that use a simpler approach. While there are some concerns (see below), the paper's strengths, particularly its emphasis on a trajectory-centric approach and the simplicity of MINT, provide a compelling contribution to the field.

Strengths:<br /> The adoption of a trajectory-centric approach that utilizes statistical constraints presents a substantial shift in methodology, potentially revolutionizing the way BCIs interpret and predict neural behaviour. This is one of the strongest aspects of the paper.

The thorough evaluation of the method across various datasets serves as an assurance that the superior performance of MINT is not a result of overfitting. The comparative simplicity of the method in contrast to many neural network approaches is refreshing and should facilitate broader applicability.

Weaknesses:<br /> Scope: Despite the impressive performance of MINT across multiple datasets, it seems predominantly applicable to M1/S1 data. Only one of the eight empirical datasets comes from an area outside the motor/somatosensory cortex. It would be beneficial if the authors could expand further on how the method might perform with other brain regions that do not exhibit low tangling or do not have a clear trial structure (e.g. decoding of position or head direction from hippocampus)

When comparing methods, the neural trajectories of MINT are based on averaged trials, while the comparison methods are trained on single trials. An additional analysis might help in disentangling the effect of the trial averaging. For this, the authors could average the input across trials for all decoders, establishing a baseline for averaged trials. Note that inference should still be done on single trials. Performance can then be visualized across different values of N, which denotes the number of averaged trials used for training.

Reviewer #2 (Public Review):

Summary:<br /> The goal of this paper is to present a new method, termed MINT, for decoding behavioral states from neural spiking data. MINT is a statistical method which, in addition to outputting a decoded behavioral state, also provides soft information regarding the likelihood of that behavioral state based on the neural data. The innovation in this approach is neural states are assumed to come from sparsely distributed neural trajectories with low tangling, meaning that neural trajectories (time sequences of neural states) are sparse in the high-dimensional space of neural spiking activity and that two dissimilar neural trajectories tend to correspond to dissimilar behavioral trajectories. The authors support these assumptions through analysis of previously collected data, and then validate the performance of their method by comparing it to a suite of alternative approaches. The authors attribute the typically improved decoding performance by MINT to its assumptions being more faithfully aligned to the properties of neural spiking data relative to assumptions made by the alternatives.

Strengths:<br /> The paper did an excellent job critically evaluating common assumptions made by neural analytical methods, such as neural state being low-dimensional relative to the number of recorded neurons. The authors made strong arguments, supported by evidence and literature, for potentially high-dimensional neural states and thus the need for approaches that do not rely on an assumption of low dimensionality.

The paper was thorough in considering multiple datasets across a variety of behaviors, as well as existing decoding methods, to benchmark the MINT approach. This provided a valuable comparison to validate the method. The authors also provided nice intuition regarding why MINT may offer performance improvement in some cases and in which instances MINT may not perform as well.

In addition to providing a philosophical discussion as to the advantages of MINT and benchmarking against alternatives, the authors also provided a detailed description of practical considerations. This included training time, amount of training data, robustness to data loss or changes in the data, and interpretability. These considerations not only provided objective evaluation of practical aspects but also provided insights to the flexibility and robustness of the method as they relate back to the underlying assumptions and construction of the approach.

Weaknesses:<br /> The authors posit that neural and behavioral trajectories are non-isometric. To support this point, they look at distances between neural states and distances between the corresponding behavioral states, in order to demonstrate that there are differences in these distances in each respective space. This supports the idea that neural states and behavioral states are non-isometric but does not directly address their point. In order to say the trajectories are non-isometric, it would be better to look at pairs of distances between corresponding trajectories in each space.

With regards to the idea of neural and behavioral trajectories having different geometries, this is dependent on what behavioral variables are selected. In the example for Fig 2a, the behavior is reach position. The geometry of the behavioral trajectory of interest would look different if instead the behavior of interest was reach velocity. The paper would be strengthened by acknowledgement that geometries of trajectories are shaped by extrinsic choices rather than (or as much as they are) intrinsic properties of the data.

The approach is built up on the idea of creating a "mesh" structure of possible states. In the body of the paper the definition of the mesh was not entirely clear and I could not find in the methods a more rigorous explicit definition. Since the mesh is integral to the approach, the paper would be improved with more description of this component.

Impact:<br /> This work is motivated by brain-computer interfaces applications, which it will surely impact in terms of neural decoder design. However, this work is also broadly impactful for neuroscientific analysis to relate neural spiking activity to observable behavioral features. Thus, MINT will likely impact neuroscience research generally. The methods are made publicly available, and the datasets used are all in public repositories, which facilitates adoption and validation of this method within the greater scientific community.

Reviewer #3 (Public Review):

Summary:

This manuscript develops a new method termed MINT for decoding of behavior. The method is essentially a table-lookup rather than a model. Within a given stereotyped task, MINT tabulates averaged firing rate trajectories of neurons (neural states) and corresponding averaged behavioral trajectories as stereotypes to construct a library. For a test trial with a realized neural trajectory, it then finds the closest neural trajectory to it in the table and declares the associated behavior trajectory in the table as the decoded behavior. The method can also interpolate between these tabulated trajectories. The authors mention that the method is based on three key assumptions: (1) Neural states may not be embedded in a low-dimensional subspace, but rather in a high-dimensional space. (2) Neural trajectories are sparsely distributed under different behavioral conditions. (3) These neural states traverse trajectories in a stereotyped order.

The authors conducted multiple analyses to validate MINT, demonstrating its decoding of behavioral trajectories in simulations and datasets (Figures 3, 4). The main behavior decoding comparison is shown in Figure 4. In stereotyped tasks, decoding performance is comparable (M_Cycle, MC_Maze) or better (Area 2_Bump) than other linear/nonlinear algorithms (Figure 4). However, MINT underperforms for the MC_RTT task, which is less stereotyped (Figure 4).

This paper is well-structured and its main idea is clear. The fact that performance on stereotyped tasks is high is interesting and informative, showing that these stereotyped tasks create stereotyped neural trajectories. The task-specific comparisons include various measures and a variety of common decoding approaches, which is a strength. However, I have several major concerns. I believe several of the conclusions in the paper, which are also emphasized in the abstract, are not accurate or supported, especially about generalization, computational scalability, and utility for BCIs. MINT is essentially a table-lookup algorithm based on stereotyped task-dependent trajectories and involves the tabulation of extensive data to build a vast library without modeling. These aspects will limit MINT's utility for real-world BCIs and tasks. These properties will also limit MINT's generalizability from task to task, which is important for BCIs and thus is commonly demonstrated in BCI experiments with other decoders without any retraining. Furthermore, MINT's computational and memory requirements can be prohibitive it seems. Finally, as MINT is based on tabulating data without learning models of data, I am unclear how it will be useful in basic investigations of neural computations. I expand on these concerns below.

Main comments:

1. MINT does not generalize to different tasks, which is a main limitation for BCI utility compared with prior BCI decoders that have shown this generalizability as I review below. Specifically, given that MINT tabulates task-specific trajectories, it will not generalize to tasks that are not seen in the training data even when these tasks cover the exact same space (e.g., the same 2D computer screen and associated neural space).

First, the authors provide a section on generalization, which is inaccurate because it mixes up two fundamentally different concepts: 1) collecting informative training data and 2) generalizing from task to task. The former is critical for any algorithm, but it does not imply the latter. For example, removing one direction of cycling from the training set as the authors do here is an example of generating poor training data because the two behavioral (and neural) directions are non-overlapping and/or orthogonal while being in the same space. As such, it is fully expected that all methods will fail. For proper training, the training data should explore the whole movement space and the associated neural space, but this does not mean all kinds of tasks performed in that space must be included in the training set (something MINT likely needs while modeling-based approaches do not). Many BCI studies have indeed shown this generalization ability using a model. For example, in Weiss et al. 2019, center-out reaching tasks are used for training and then the same trained decoder is used for typing on a keyboard or drawing on the 2D screen. In Gilja et al. 2012, training is on a center-out task but the same trained decoder generalizes to a completely different pinball task (hit four consecutive targets) and tasks requiring the avoidance of obstacles and curved movements. There are many more BCI studies, such as Jarosiewicz et al. 2015 that also show generalization to complex real-world tasks not included in the training set. Unlike MINT, these works can achieve generalization because they model the neural subspace and its association to movement. On the contrary, MINT models task-dependent neural trajectories, so the trained decoder is very task-dependent and cannot generalize to other tasks. So, unlike these prior BCIs methods, MINT will likely actually need to include every task in its library, which is not practical.

I suggest the authors remove claims of generalization and modify their arguments throughout the text and abstract. The generalization section needs to be substantially edited to clarify the above points. Please also provide the BCI citations and discuss the above limitation of MINT for BCIs.

2. MINT is shown to achieve competitive/high performance in highly stereotyped datasets with structured trials, but worse performance on MC_RTT, which is not based on repeated trials and is less stereotyped. This shows that MINT is valuable for decoding in repetitive stereotyped use-cases. However, it also highlights a limitation of MINT for BCIs, which is that MINT may not work well for real-world and/or less-constrained setups such as typing, moving a robotic arm in 3D space, etc. This is again due to MINT being a lookup table with a library of stereotyped trajectories rather than a model. Indeed, the authors acknowledge that the lower performance on MC_RTT (Figure 4) may be caused by the lack of repeated trials of the same type. However, real-world BCI decoding scenarios will also not have such stereotyped trial structure and will be less/un-constrained, in which MINT underperforms. Thus, the claim in the abstract or lines 480-481 that MINT is an "excellent" candidate for clinical BCI applications is not accurate and needs to be qualified. The authors should revise their statements according and discuss this issue. They should also make the use-case of MINT on BCI decoding clearer and more convincing.

3. Related to 2, it may also be that MINT achieves competitive performance in offline and trial-based stereotyped decoding by overfitting to the trial structure in a given task, and thus may not generalize well to online performance due to overfitting. For example, a recent work showed that offline decoding performance may be overfitted to the task structure and may not represent online performance (Deo et al. 2023). Please discuss.

4. Related to 2, since MINT requires firing rates to generate the library and simple averaging does not work for this purpose in the MC_RTT dataset (that does not have repeated trials), the authors needed to use AutoLFADS to infer the underlying firing rates. The fact that MINT requires the usage of another model to be constructed first and that this model can be computationally complex, will also be a limiting factor and should be clarified.

5. I also find the statement in the abstract and paper that "computations are simple, scalable" to be inaccurate. The authors state that MINT's computational cost is O(NC) only, but it seems this is achieved at a high memory cost as well as computational cost in training. The process is described in section "Lookup table of log-likelihoods" on line [978-990]. The idea is to precompute the log-likelihoods for any combination of all neurons with discretization x all delay/history segments x all conditions and to build a large lookup table for decoding. Basically, the computational cost of precomputing this table is O(V^{Nτ} x TC) and the table requires a memory of O(V^{Nτ}), where V is the number of discretization points for the neural firing rates, N is the number of neurons, τ is the history length, T is the trial length, and C is the number of conditions. This is a very large burden, especially the V^{Nτ} term. This cost is currently not mentioned in the manuscript and should be clarified in the main text. Accordingly, computation claims should be modified including in the abstract.

6. In addition to the above technical concerns, I also believe the authors should clarify the logic behind developing MINT better. From a scientific standpoint, we seek to gain insights into neural computations by making various assumptions and building models that parsimoniously describe the vast amount of neural data rather than simply tabulating the data. For instance, low-dimensional assumptions have led to the development of numerous dimensionality reduction algorithms and these models have led to important interpretations about the underlying dynamics (e.g., fixed points/limit cycles). While it is of course valid and even insightful to propose different assumptions from existing models as the authors do here, they do not actually translate these assumptions into a new model. Without a model and by just tabulating the data, I don't believe we can provide interpretation or advance the understanding of the fundamentals behind neural computations. As such, I am not clear as to how this library building approach can advance neuroscience or how these assumptions are useful. I think the authors should clarify and discuss this point.

7. Related to 6, there seems to be a logical inconsistency between the operations of MINT and one of its three assumptions, namely, sparsity. The authors state that neural states are sparsely distributed in some neural dimensions (Figure 1a, bottom). If this is the case, then why does MINT extend its decoding scope by interpolating known neural states (and behavior) in the training library? This interpolation suggests that the neural states are dense on the manifold rather than sparse, thus being contradictory to the assumption made. If interpolation-based dense meshes/manifolds underlie the data, then why not model the neural states through the subspace or manifold representations? I think the authors should address this logical inconsistency in MINT, especially since this sparsity assumption also questions the low-dimensional subspace/manifold assumption that is commonly made.

References

Weiss, Jeffrey M., Robert A. Gaunt, Robert Franklin, Michael L. Boninger, and Jennifer L. Collinger. 2019. "Demonstration of a Portable Intracortical Brain-Computer Interface." Brain-Computer Interfaces 6 (4): 106-17. https://doi.org/10.1080/2326263X.2019.1709260.

Gilja, Vikash, Paul Nuyujukian, Cindy A. Chestek, John P. Cunningham, Byron M. Yu, Joline M. Fan, Mark M. Churchland, et al. 2012. "A High-Performance Neural Prosthesis Enabled by Control Algorithm Design." Nature Neuroscience 15 (12): 1752-1757. https://doi.org/10.1038/nn.3265.

Jarosiewicz, Beata, Anish A. Sarma, Daniel Bacher, Nicolas Y. Masse, John D. Simeral, Brittany Sorice, Erin M. Oakley, et al. 2015. "Virtual Typing by People with Tetraplegia Using a Self-Calibrating Intracortical Brain-Computer Interface." Science Translational Medicine 7 (313): 313ra179-313ra179. https://doi.org/10.1126/scitranslmed.aac7328.

Darrel R. Deo, Francis R. Willett, Donald T. Avansino, Leigh R. Hochberg, Jaimie M. Henderson, and Krishna V. Shenoy. 2023. "Translating Deep Learning to Neuroprosthetic Control." BioRxiv, 2023.04.21.537581. https://doi.org/10.1101/2023.04.21.537581.

Reviewer #1 (Public Review):

This EEG study probes the prediction of a mechanistic account of P300 generation through the presence of underlying (alpha) oscillations with a non-zero mean. In this model, the P300 can be explained by a baseline shift mechanism. That is, the non-zero mean alpha oscillations induce asymmetries in the trial-averaged amplitudes of the EEG signal, and the associated baseline shifts can lead to apparent positive (or negative) deflections as alpha becomes desynchronized at around P300 latency. The present paper examines the predictions of this model in a substantial data set (using the typical P300-generating oddball paradigm and careful analyses). The results show that all predictions are fulfilled: the two electrophysiological events (P300, alpha desynchronization) share a common time-course, anatomical sources (from inverse solutions), and covariations with behaviour; plus relate (negatively) in amplitude, while the direction of this relationship is determined by the non-zero-mean deviation of alpha oscillations pre-stimulus (baseline shift index, BSI). This is indictive of a link of the P300 with underlying alpha oscillations through a baseline shift account, and hence that the P300 can be explained, at least in parts, by non-zero mean brain oscillations as they undergo post-stimulus changes.

Reviewer #2 (Public Review):

The authors show that event related changes in the alpha band, namely a decrease in alpha power over parieto/occipital areas, explains the P300 during an auditory target detection task. The proposed mechanism by which this happens is a baseline-shift, where ongoing oscillations which have a non-zero mean undergo an event-related modulation in amplitude which then mimics a low frequency event-related potential. In this specific case, it is a negative-mean alpha band oscillation which decreases in power post-stimulus and thus mimics a positivity over parieto-occipital areas, i.e. the P300. The authors lay out 4 criteria that should hold, if indeed alpha modulation generates the P300, which they then go about providing evidence for.

Strengths:<br /> - The authors do go about showing evidence for each prediction rigorously, which is very clearly laid out. In particular I found the 3rd section connecting resting-state alpha BSI to the P300 quite compelling.<br /> - The study is obviously very well-powered.<br /> - Very well-written and clearly laid out. Also the EEG analysis is thorough overall, with sensible analysis choices made.<br /> - I also enjoyed the discussion of the literature.<br /> - The mediation analyses make a convincing argument for behavioural effects being related to BSI also.

Weaknesses:<br /> In general, if one were to be trying to show the potential overlap and confound of alpha-related baseline shift and the P300, as something for future researchers to consider in their experimental design and analysis choices, the four predictions hold well. However, if one were to assert that the P300 is "generated" via alpha baseline shift, even partially, then the predictions either do not hold, or if they do, they are not sufficient to support that hypothesis. Thankfully, the authors no longer make this stronger claim in the revised print. Weaknesses pertaining to the previous draft can be found in the prior review.

In reviewing this paper, I have found the authors have made a convincing case that alpha amplitude modulation potentially confounds with P300 amplitude via baseline shift, and this is a valuable finding.

Reviewer #1 (Public Review):

Colin et al demonstrated that condensin is a key factor for the disjunction of sister-telomeres during mitosis and proposed that it is due to that condensin restrains the telomere association of cohesin. The authors first showed that condensin binds telomeres in mitosis evidenced by ChIP-qPCR and calibrated ChIP-seq. They further demonstrated that compromising condensin's activity leads to a failure in the disjunction of telomeres, with convincing cytological and HI-seq evidence. Two telomeric proteins Taz1 and Mit1 were identified to specifically regulate the telomere association of cohesin. Deletion of these genes decreased/increased condensin's telomere association and exacerbated/remedied the defected telomere disjunction in a condensin mutant, echoing the role of condensin in telomere disjunction. They proposed that the underlying mechanism is that condensin inhibits cohesin's accumulation at telomeres. However, the evidence for this claim might need to be further strengthened. Nevertheless, this study uncovered a novel role of condensin in the separation of telomeres of sister chromosomes and open a question of how condensin regulates the structure of chromosomal ends.

Reviewer #2 (Public Review):

This manuscript presents a comprehensive investigation into the role of condensin complexes in telomere segregation in fission yeast. The authors employ chromatin immunoprecipitation analysis to demonstrate the enrichment of condensin at telomeres during anaphase. They then use condensin conditional mutants to confirm that this complex plays a crucial role in sister telomere disjunction. Interestingly, they show that condensin role in telomere disjunction is unlikely related to catenation removal but rather related to the organization of telomeres in cis and/or the elimination of structural constraints or proteins that hinder separation.

The authors also investigate the regulation of condensin localization to telomeres and reveal the involvement of the shelterin subunit Taz1 in promoting condensin's association with telomeres while demonstrating that the chromatin remodeler Mit1 prevents excessive loading of condensin onto telomeres. Finally, they show that cohesin acts as a negative regulator of telomere separation, counteracting the positive effects of condensin.

Overall, the manuscript is well-executed, and the authors provide sufficient supporting evidence for their claims. There are a couple of aspects that arise from this study that when fully elucidated will lead to mechanistic understanding of important biological processes. For instance, the exact mechanism by which Taz1 affects condensin loading or the mechanistic link between cohesin and condensin, especially in the context of their opposing roles, are exciting prospects for the future and it is possible that future work within the context of telomeres might provide valuable insights to these questions .

Reviewer #3 (Public Review):

This study explores how condensin and telomere proteins cooperate to facilitate sister chromatid disjunction at chromosome ends during anaphase. Building upon previous results published by the same group (Reyes et al. 2015, Berthezene et al. 2020), the authors demonstrate that condensin is essential for sister telomere disjunction in anaphase in fission yeast. The primary role of condensin appears to be counteracting cohesin, which holds sister telomeres together. Furthermore, condensin is found to be enriched at telomeres, and this enrichment partially relies on Taz1, the principal telomere factor in S. pombe. The loss of Taz1 does not cause an obvious defect in sister telomere disjunction, which prevents drawing strong conclusions about its role in this process.

Reviewer #1 (Public Review):

Summary:<br /> In this paper the authors present genome-wide association analyses of 11 different cancers including time-to-event analyses. The authors use two recently published Bayesian methods, one of which is constructed to handle time-to-event data. The authors demonstrate that polygenic risk scores trained on these models give nominally better predictions than standard polygenic risk scores. Further they show that performing 11 GWASs in UKB while adjusting for the polygenic effects estimated by their improved predictor, they find seven novel loci are implicated by one or both of these methods of which the authors find that three replicate in Estonian Biobank.

Strengths:<br /> A clear strength is that the authors evaluate the performance of the model in a completely different dataset (Estonian Biobank) than the one it is trained in.

Weaknesses:<br /> The 11 phenotypes that the authors chose have the challenge that they are rare, particularly in healthy biobank participants, which means that (i) the benefit of modeling it as a time-to-event analysis is expected to be smaller and (ii) that models have to be stable under imbalanced case/control fractions. In GWAS analyses authors handle this second problem by using a recently published association test, which is robust to imbalanced data, which likely means that they avoid inflated test statistics, but also that they do not leverage the actual time-to-event information to its full potential.

The authors chose not to use the recently published methods BayesRR-RC and BayesW, but instead they run these models and then add an extra step where they run a logistic regression with an offset term set to the LOCO genomic values as estimated by GRMR-BayesW and GRMR-BayesRR-RC respectively. They write that this was because of the imbalanced case/control proportion, but not how the problem was detected. If the authors have insight about when the standard GRMR-BayesW and GRMR-BayesRR-RC become unreliable, I think it would be helpful to share in this paper. Further, if the associations implicated by standard GRMR-BayesW and GRMR-BayesRR-RC are not reliable, I think we need some justification that the variance components reported in Figure 1 are still reliable.

The authors chose to compare the two new GWAS methods, GMRM-BayesW-adjusted and GMRM-BayesRR-RC-adjusted, to REGENIE, so an obvious first question in my opinion is if GMRM-BayesW-adjusted and GMRM-BayesRR-RC-adjusted find more signal than REGENIE.<br /> a. We see that 7 loci where found by GMRM-BayesW but not by REGENIE, but how many were found by REGENIE but not by GMRM-BayesW?<br /> b. Figure S5 as I understand it is showing that the mean -log(p-value) is lower in GMRM-BayesW than REGENIE for variants that have a p-value in GMRM-BayesW that is lower than 5e-8. I don't think this is a valid way to check if GMRM-BayesW has more power. I have a feeling that there could be a winner's curse-like phenomenon here. I think a more principled comparison could be provided.

The title of the paper ("Novel discoveries and enhanced genomic prediction from modelling genetic risk of cancer age-at-onset") seems to imply that the age of onset informed model (GMRM-BayesW) does better. But I think the foundation for that statement could be strengthened.<br /> Figure S6 shows that 261 previously reported loci were replicated by GMRM-BayesW-adjusted whereas 256 were replicated by GMRM-BayesRR-RC. How were previously reported loci defined? did they include UKB data? and how many where there in total?<br /> In the PRS analyses presented in Figure 3a GMRM-BayesW does better than GMRM-BayesRR-RC in 8/11 phenotypes, which does not itself appear significant to me. And with overlapping confidence intervals the significance of the improvement is hard to see.

In Table 1 it says that rs35763415, rs117972357 and rs7902587 replicated in the Estonian Biobank but Figure 3b it says that rs35763415, rs117972357 and rs1015362 replicated in the Estonian Biobank. What is the difference between these two analyses? In the methods it says that you checked your findings for replication in FinnGen, but I don't see any results from FinnGen anywhere?

Reviewer #2 (Public Review):

Summary: Maksimova, Ojavee, and colleagues extend two of their methods, BayesW and BayesRR-RC to be used as mixed-model association methods by combining them with a similar approach as in step 2 of REGENIE. BayesW handles time-to-event data whereas BayesRR-RC works for case-control phenotypes. They provide UKBB results for 11 cancers and replicate findings and assess predictions in the Estonian biobank.

Strengths: Age-of-onset is becoming more and more available, and developing methods that make the best use of this additional information is valuable.

Weaknesses: In this work, there is (for now) limited validation of results and comparison with other existing methods.

Reviewer #1 (Public Review):

Summary<br /> The authors investigated the antigenic diversity of recent (2009- 2017) A/H3N2 influenza neuraminidases (NAs), the second major antigenic protein after haemagglutinin. They used 27 viruses and 43 ferret sera and performed NA inhibition. This work was supported by a subset of mouse sera. Clustering analysis determined 4 antigenic clusters, mostly in concordance with the genetic groupings. Association analysis was used to estimate important amino acid positions, which were shown to be more likely close to the catalytic site. Antigenic distances were calculated and a random forest model was used to determine potential important sites.

This has the potential to be a very interesting piece of work. At present, there are inconsistencies in the methods, results and presentation that limit its impact. In particular, there are weaknesses in some of the computational work.

Strengths<br /> 1. The data cover recent NA evolution and a substantial number (43) of ferret (and mouse) sera were generated and titrated against 27 viruses. This is laborious experimental work and is the largest publicly available neuraminidase inhibition dataset that I am aware of. As such, it will prove a useful resource for the influenza community.

2. A variety of computational methods were used to analyse the data, which give a rounded picture of the antigenic and genetic relationships and link between sequence, structure and phenotype.

Weaknesses<br /> 1. Inconsistency in experimental methods<br /> Two ferret sera were boosted with H1N2, while recombinant NA protein for the others. This, and the underlying reason, are clearly explained in the manuscript. The authors note that boosting with live virus did not increase titres. Nevertheless, these results are included in the analysis when it would be better to exclude them (Figure 2 shows much lower titres to their own group than other sera).

2. Inconsistency in experimental results<br /> Clustering of the NA inhibition results identifies three viruses which do not cluster with their phylogenetic group. Again this is clearly pointed out in the paper. Further investigation of this inconsistency is required to determine whether this has a genetic basis or is an experimental issue. It is difficult to trust the remaining data while this issue is unresolved.

3. Inconsistency in group labelling<br /> A/Hatay/4990/2016 & A/New Caledonia/23/2016 are in phylogenetic group 1 in Figure 2 and phylogenetic group 1 in Figure 5 - figure supplement 1 panel a.<br /> A/Kansas/14/2017 is selected as a representative of antigenic group 2, when in Figure 2 it is labelled as AC1 (although Figure 2 - supplement 4 which the text is referring to shows data for A/Singapore/Infimh-16-0019/2016 as the representative of AC2). A/Kansas/14/2017 is coloured and labelled as AC2 in Figure 2 - supplement 5.<br /> The colouring is changed for Figure 3a at the bottom. A/Heilongjiang-Xiangyang/1134/2011 is coloured the same as AC4 viruses when it is AC1 in Figure 2.<br /> This lack of consistency makes the figures misleading.

4. Data not presented, without explanation<br /> The paper states that 44 sera and 27 H6N2 viruses were used (line 158). However, the results for the Kansas/14/2017 sera do not appear to be presented in any of the figures (e.g. Figure 2 phylogenetic tree, Figure 5 - figure supplement 1). It is not obvious why these data were not presented. The exclusion of this serum could affect the results as often the homologous titre is the highest and several heatmaps show the fold down from the highest titre.

5. The cMDS plot does not have sufficient quality assurance<br /> A cMDS plot is shown in Figure 5 - figure supplement 1, generated using classical MDS. The following support for the appropriateness of this visualisation is not given.<br /> a. Goodness of fit of the cMDS projection, including per point and per titre.<br /> b. Testing of the appropriate number of dimensions (the two sera from phylogenetic group 3 are clustered with phylogenetic group 2; additional dimensions might separate these groups).<br /> c. A measure of uncertainty in positioning, e.g. bootstrapping.<br /> d. A sensitivity analysis of the assumption about titres below the level of detection (i.e. that <20 = 10).<br /> Without this information, it is difficult to judge if the projection is reliable.

6. Choice of antigenic distance measure<br /> The measure of antigenic distance used here is the average difference between titres for two sera. This is dependent on which viruses have been included in the analysis and will be biased by the unbalanced number of viruses in the different clusters (12, 8, 2, 5).

7. Association analysis does not account for correlations<br /> For each H6N2 virus and position, significance was calculated by comparing the titres between sera that did or did not have a change at that position. This does not take into account the correlations between positions. For haemagglutinin, it can be impossible to determine the true antigenic effects of such correlated substitutions with mutagenesis studies.

8. Random forest method<br /> 25 features are used to classify 43 sera, which seems high (p/3 is typical for classification). By only considering mismatches, rather than the specific amino acid changes, some signals may be lost (for example, at a given position, one amino acid change might be neutral while another has a large antigenic effect). Features may be highly, or perfectly correlated, which will give them a lower reported importance and skew the results.

Reviewer #2 (Public Review):

Summary:<br /> The authors characterized the antigenicity of N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 using ferret and mice immune sera. Four antigenic groups were identified, which correlated with their respective phylogenic/ genetic groups. Among 102 amino acids differed by the 44 selected N2 proteins, the authors identified residues that differentiate the antigenicity of the four groups and constructed a machine-learning model that provides antigenic distance estimation. Three recent A(H3N2) vaccine strains were tested in the model but there was no experimental data to confirm the model prediction results.

Strengths:<br /> This study used N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 and generated corresponding panels of ferret and mouse sera to react with the selected strains. The amount of experimental data for N2 antigenicity characterization is large enough for model building.

Weaknesses:<br /> The main weakness is that the strategy of selecting 44 A(H3N2) viruses from 2009-2017 was not explained. It is not clear if they represent the overall genetic diversity of human A(H3N2) viruses circulating during this time. A comprehensive N2 phylogenetic tree of human A(H3N2) viruses from 2009-2017, with the selected 44 strains labeled in the tree, would be helpful to assess the representativeness of the strains included in the study. The second weakness is the use of double-immune ferret sera (post-infection plus immunization with recombinant NA protein) or mouse sera (immunized twice with recombinant NA protein) to characterize the antigenicity of the selected A(H3N2) viruses. Conventionally, NA antigenicity is characterized using ferret sera after a single infection. Repeated influenza exposure in ferrets has been shown to enhance antibody binding affinity and may affect the cross-reactivity to heterologous strains (PMID: 29672713). The increased cross-reactivity is supported by the NAI titers shown in Table S3, as many of the double immune ferret sera showed the highest reactivity not against its own homologous virus but to heterologous strains. Although the authors used the post-infection ferret sera to characterize 5 viruses (Figure 2, Figure Supplement 4), the patterns did not correlate well. If the authors repeat the NA antigenic analysis using the post-infection ferret sera with lower cross-reactivity, will the authors be able to identify more antigenic groups instead of 4 groups? Another weakness is that the authors used the newly constructed model to predict the antigenic distance of three recent A(H3N2) viruses but there is no experimental data to validate their prediction (eg. if these viruses are indeed antigenically deviating from group 2 strains as concluded by the authors).

Reviewer #3 (Public Review):

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

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

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

Reviewer #1 (Public Review):

Summary:<br /> In the present study, the authors examined the possibility of using phosphatidyl-inositol kinase 3-kinase alpha (PI3Ka) inhibitors for heterotopic ossification (HO) in fibrodysplasia ossificans progressiva (FOP). Administration of BYL719, a chemical inhibitor of PI3Ka, prevented HO in a mouse model of FOP that expressed a mutated ACVR1 receptor. Genetic ablation of PI3Ka (p110a) also suppressed HO in mice. BYL719 blocked osteochondroprogenitor specification and reduced inflammatory responses, such as pro-inflammatory cytokine expression and migration/proliferation of immune cells. The authors claimed that inhibition of PI3Ka is a safe and effective therapeutic strategy for HO.

Strengths:<br /> This manuscript reports an interesting finding that BYL719 inhibits HO in a mouse model of FOP.

Weaknesses:<br /> The molecular mechanisms of BYL719 were still unclear because BYL719 affected multiple events and many types of cells. Additional experimental data would be needed to show more clearly how PI3Ka regulates HO.

Reviewer #2 (Public Review):

Summary:<br /> The authors in this study previously reported that BYL719, an inhibitor of PI3Kα, suppressed heterotopic ossification in mice model of a human genetic disease, fibrodysplasia ossificans progressive, which is caused by the activation of mutant ACVR1/R206H by Activin A. The aim of this study is to identify the mechanism of BYL719 for the inhibition of heterotopic ossification. They found that BYL719 suppressed heterotopic ossification in two ways: one is to inhibit the specification of precursor cells for chondrogenic and osteogenic differentiation and the other is to suppress the activation of inflammatory cells.

Strengths:<br /> This study is based on the authors' previous reports and the experimental procedures including the animal model are established. In addition, to confirm the role of PI3Kα, the authors used the conditional knock-out mice of the subunit of PI3Kα. They clearly demonstrated the evidence indicating that the targets of PI3Kα are not members of TGFBR by a newly established experimental method.

Weaknesses:<br /> Overall, the presented data were closely related to those previously published by the authors' group or others, and there were very few new findings.<br /> Heterotopic ossification in the mice model was not stable and was inappropriate for scientific evaluation.<br /> The method for chondrogenic differentiation was not appropriate, and the scientific evidence of successful differentiation was lacking.<br /> The design of the gene expression profile comparison was not appropriate and failed to obtain the data for the main aim of this study.<br /> The experiments of inflammatory cells were performed in cell lines without ACVR1/R206H mutation, and therefore the obtained data were not precisely related to the inflammation in FOP.

Reviewer #1 (Public Review):

The manuscript aims to provide mechanistic insight into the activation of PI3Kbeta by its known regulators tyrosine phosphorylated peptides, GTP-loaded Rac1 and G-protein beta-gamma subunits. To achieve this the authors have used supported lipid bilayers, engineered recombinant peptides and proteins (often tagged with fluorophores) and TIRF microscopy to enable bulk (averages of many molecules) and single molecule quantitation. The great strength of this approach is the precision and clarity of mechanistic insight. Although the study does not use "in transfecto" or in vivo models the experiments are performed using "physiologically-based" conditions and provide a powerful insight into core regulatory principles that will be relevant in vivo.

The results are beautiful, high quality, well controlled and internally consistent (and with other published work that overlaps on some points) and as a result are compelling. The primary conclusion is that the primary regulator of PI3Kbeta are tyrosine phosphorylated peptides (and by inference tyrosine phsophorylated receptors/adaptors) and that the other activators can synergise with that input but have relatively weak impacts on their own.

Although the methodology is not easily imported, for reasons of both cost and the experience needed to execute them well, the results have broad importance for the field and reverse an impression that had built in large parts of the broader signalling and PI3K communities that all of the inputs to PI3Kbeta were relatively equivalent, however, these conclusions were based on "in cell" or in vivo studies that were very difficult to interpret clearly.

Reviewer #3 (Public Review):

Summary: In this paper, Ruan et al. studied the long-term impact of warming and altered precipitations on the composition and growth of the soil microbial community. The researchers adopted an experimental approach to assess the impact of climate change on microbial diversity and functionality. This study was carried out within a controlled environment, wherein two primary factors were assessed: temperature (in two distinct levels) and humidity (across three different levels). These factors were manipulated in a full factorial design, resulting in a total of six treatments. This experimental setup was maintained for ten years. To analyze the active microbial community, the researchers employed a technique involving the incorporation of radiolabeled water into biomolecules (particularly DNA) through quantitative stable isotope probing. This allowed for the tracking of the active fraction of microbes, accomplished via isopycnic centrifugation, followed by Illumina sequencing of the denser fraction. This study was followed by a series of statistical analysis to identify the impact of these two variables on the whole community and specific taxonomic groups. The full factorial design arrangement enabled the researchers to discern both individual contributions as well as potential interactions among the variables

Strengths: This work presents a timely study that assesses in a controlled fashion the potential impact of global warming and altered precipitations on microbial populations. The experimental setup, experimental approach and data analysis seem to be overall solid. I consider the paper of high interest for the whole community as it provides a baseline to the assessment of global warming on microbial diversity.

Weaknesses: While taxonomic information is interesting, it would have been highly valuable to include transcriptomics data as well. This would allow us to understand what active pathways become enriched under warming and altered precipitations. Non-metabolic OTUs hold significance as well. The authors could have potentially described these non-incorporators and derived hypotheses from the gathered information. The work would have benefited from using more biological replicates of each treatment.

Reviewer #2 (Public Review):

Summary: The authors aimed to describe the effect of different temperature and precipitation regimes on microbial growth responses in an alpine grassland ecosystem using quantitative 18O stable isotope probing. It was found that all climate manipulations had negative effects on microbial growth, and that single-factor manipulations exerted larger negative effects as compared to combined-factor manipulations. The degree of antagonism between factors was analyzed in detail, as well as the differential effect of these divergent antagonistic responses on microbial taxa that incorporated the isotope. Finally, a hypothetical functional profiling was performed based on taxonomic affiliations. This work gives additional evidence that altered warming and precipitation regimes negatively impact microbial growth.

Strengths: A long term experiment with a thorough experimental design in apparently field conditions is a plus for this work, making the results potentially generalisable to the alpine grassland ecosystem. Also, the implementation of a qSIP approach to determine microbial growth ensures that only active members of the community are assessed. Finally, particular attention was given to the interaction between factors and a robust approach was implemented to quantify the weight of the combined-factor manipulations on microbial growth.

Weaknesses: The methodology does not mention whether the samples taken for the incubations were rhizosphere soil, bulk soil or a mix between both type of soils. If the samples were taken from rhizosphere soil, I wonder how the plants were affected by the infrared heaters and if the resulting shadow (also in the controls with dummy heaters) had an effect on the plants and the root exudates of the parcels as compared to plants outside the blocks? If the samples were bulk soil, are the results generalisable for a grassland ecosystem? In my opinion, it is needed to add more info on the origin of the soil samples and how these were taken.

The qSIP calculations reported in the methodology for this work are rather superficial and the reader must be experienced in this technique to understand how the incorporators were identified and their growth quantified. For instance, the GC content of taxa was calculated for reads clustered in OTUs, and it is not discussed in the text the validity of such approach working at genus level.

The selection of V4-V5 region over V3-V4 region to quantify the number of copies of the 16S rRNA gene should be substantiated in the text. Classic works determined one decade ago that primer pairs that amplify V3-V4 are most suitable to assess soil bacterial communities. Hungate et al. (2015), worked with the V3-V4 region when establishing the qSIP method. Maybe the number of unassigned OTUs is related with the selection of this region.

Report of preprocessing and processing of the sequences does not comply state of the art standards. More info on how the sequences were handled is needed, taking into account that a significant part of the manuscript relies on taxonomic classification of such sequences. Also, an OTU approach for an almost species-dependent analysis (GC contents) should be replaced or complemented with an ASV or subOTUs approach, using denoisers such as DADA2 or deblur. Usage of functional prediction tools underestimates gene frequencies, including those related with biogeochemical significance for soil-carbon and nitrogen cycling.

Reviewer #1 (Public Review):

Warming and precipitation regime change significantly influences both above-ground and below-ground processes across Earth's ecosystems. Soil microbial communities, which underpin the biogeochemical processes that often shape ecosystem function, are no exception to this, and although research shows they can adapt to this warming, population dynamics and ecophysiological responses to these disturbances are not currently known. The Qinghai-Tibet Plateau, the Third Pole of the Earth, is considered among the most sensitive ecosystems to climate change. The manuscript described an integrated, trait-based understanding of these dynamics with the qSIP data. The experimental design and methods appear to be of sufficient quality. The data and analyses are of great value to the larger microbial ecological community and may help advance our understanding of how microbial systems will respond to global change. There are very few studies in which the growth rates of bacterial populations from multifactorial manipulation experiments on the Qinghai-Tibet Plateau have been investigated via qSIP, and the large quantity of data that comprises the study described in this manuscript, will substantially advance our knowledge of bacterial responses to warming and precipitation manipulations.

Joint Public Review:

Using Ts65Dn - the most commonly used mouse model of Down syndrome (DS) - the goal of this study is two-pronged: 1) to conduct a thorough assessment of DS-related genotypic, physiological, behavioral, and phenotypic measures in a longitudinal manner; and 2) to measure the effects of chronic GTE-EGCG on these measures in the Ts65Dn mouse model. Corroborating results from several previous studies on Ts65Dn mice, findings of this study show confirm the Ts65Dn mouse model exhibits the suite of traits associated with DS. The findings also suggest that the mouse model might have experienced drift, given the milder phenotypes than those reported by earlier studies. Results of the GTE-EGCG treatment do not support its therapeutic use and instead show that the treatment exacerbated certain DS-related phenotypes.

Strengths:<br /> The authors performed a rigorous assessment of treatment and examined treatment and genotypic alterations at multiple time points during growth and aging. Detailed analysis shows differences in genotype during aging as well as genotype with treatment. This study is solid in the overarching methodological approach (with the exception of RNAseq, described below). The biggest strength of the study is its approach and dataset, which corroborate results from a multitude of past studies on Ts65Dn mice, albeit on adult specimens. It would be beneficial for the dataset to be made available to other researchers using a public data repository.

Weaknesses:<br /> There are several primary weaknesses, described below:

Sex was not considered in the analyses<br /> The number of experimental animals of each sex are not clearly represented in the paper, but are buried in supplemental tables, and the Ns for the RNAseq are unclear. No analyses were done to examine sex differences in male/female DS or WT animals with or without treatment. Body measurements will greatly vary by sex, but this was not taken into consideration during assessments. As such, there is a high amount of variability within each cohort measured for body assessments (tibia, body weight, skeletal development etc.). Supplemental table 14 had the list of each animal, but not collated by sex, genotype or treatment, making it difficult to assess the strength of each measurement.

Key results are not clearly depicted in the main figures<br /> Rigorous assessment of each figure and the clarity of the figure to convey the results of the analysis needs to be performed. Many of the figures do not clearly represent the findings, with authors heavily relying on supplemental figures to present details to explain results. Figure legends do not adequately describe figures; rather, they are limited to describing how the analysis is performed. For example, LDA plots in Figure 4 do not clearly convey the results of metabolite analysis.<br /> Overall, the amount of data presented here is overwhelming, making it difficult to interpret the findings. Some assessments that do not add to the overall paper need to be removed. Clarifying the text, figures and trimming the supplement to represent the data in a manner that is easily understood will improve the readability of the paper. For example, perhaps measures which are not strongly impacted by genotype could be moved to the supplement, because they are not directly relevant to the question of whether GTE-EGCG reverses the impact of trisomy on the measures.

Lack of clarity in the behavioral analyses<br /> Behavioral assessments are not clearly written in the methods. For example, for the novel object recognition task, it isn't clear how preference was calculated. Is this simply the percent of time spent with the novel object, or is this a relative measure (novel:familiar ratio)? This matters because if it is simply the percent of time, the relevant measure is to compare each group to 50% (the absence of a preference). The key measures for each test need to be readily distinguished from the control measures.<br /> There are also many dependent behavioral measures. For example, speed and distance are directly related to each other, but these are typically reported as control measures to help interpret the key measure, which is the anxiety-like behavior. Similarly, some behavioral tests were used to represent multiple behavioral dimensions, such as anxiety and arousal. In general, the measurements of arousal seem atypical (speed and distance are typically reported as control measures, not measures of arousal). Similarly, measures of latency during training would not typically be used as a measure of long-term memory but instead reported as a control measure to show learning occurred. LDA analysis requires independence of the measures, as well as normality. It does not appear that all of the measures fed into this analysis would have met these assumptions, but the methods also do not clearly describe which measures were actually used in the LDA.

Unclear value of RNAseq<br /> RNAseq was performed in cerebellum, a relatively spared region in DS pathology at an early time point in disease. Further, the expression of 125 genes triplicated in DS was shown in a PCA plot to highly overlap with WT, indicating that there are minimal differences in gene expression in these genes. If these genes are not critical for cerebellar function, perhaps this could account for the lack of differences between WT and Ts65Dn mice. If the authors are interested in performing RNAseq, it would have made more sense to perform this in hippocampus (to compare with metabolites) and to perform more stringent bioinformatic analysis than assessment by PCA of a limited subset of genes. Supplementary Table S14, which shows the differentially expressed genes, appears to be missing from the manuscript and cannot be evaluated. Additionally, the methods of the RNAseq are not sufficiently described and lack critical details. For example, what was the normalization performed, and which groups were compared to identify differentially expressed genes? It would also be worthwhile to describe how animals were identified for RNAseq-were those animals representative of their groups across other measures?

Reviewer #1 (Public Review):

Wheeler et al. have discovered a new RNA circuit that regulates T-cell function. They found that the long non-coding RNA Malat1 sponges miR-15/16, which controls many genes related to T cell activation, survival, and memory. This suggests that Malat1 indirectly regulates T-cell function. They used CRISPR to mutate the miR-15/16 binding site in Malat1 and observed that this disrupted the RNA circuit and impaired cytotoxic T-cell responses. While this study presents a novel molecular mechanism of T-cell regulation by Malat1-miR-15/16, the effects of Malat1 are weaker compared to miR-15/16. This could be due to several reasons, including higher levels of miR-15/16 compared to Malat1 or Malat1 expression being mostly restricted to the nucleus. Although the role of miR15/16 in T-cell activation has been previously published, if the authors can demonstrate that miR15/16 and/or Malat1 affect the clearance of Listeria or LCMV, this will significantly add to the current findings and provide physiological context to the study.

Reviewer #2 (Public Review):

This study connects prior findings on MicroRNA15/16 and Malat1 to demonstrate a functional interaction that is consequential for T cell activation and cell fate.

The study uses mice (Malat1scr/scr) with a precise genetic modification of Malat1 to specifically excise the sites of interaction with the microRNA, but sparing all other sequences, and mice with T-cell specific deletion of miR-15/16. The effects of genetic modification on in vivo T-cell responses are detected using specific mutations and shown to be T-cell intrinsic.

It is not known where in the cell the consequential interactions between MicroRNA15/16 and Malat1 take place. The authors depict in the graphical abstract Malat1 to be a nuclear lncRNA. Malat 1 is very abundant, but it is unclear if it can shuttle between the nucleus and cytoplasm. As the authors discuss future work defining where in the cell the relevant interactions take place will be important.

In addition to showing physiological phenotypic effects, the mouse models prove to be very helpful when the effects measured are small and sometimes hard to quantitate in the context of considerable variation between biological replicates (for example the results in Figure 4D).