Reviewer #2 (Public Review):

Summary:<br /> In this manuscript the authors examine the question of whether discrete action sequences and coarticulated continuous sequential actions can be produced from the same controller, without having to derive separate control policies for each sequential movement. Using modeling and behavioral experiments, the authors demonstrate that this is indeed possible if the constraints of the policy are appropriately specified. These results are of interest to those interested in motor sequences, but it is unclear whether these findings can be interpreted to apply to the control of sequences more broadly (see weaknesses below).

Strengths:<br /> The authors provide an interesting and novel extension of the stochastic optimal control model to demonstrate how different temporal constraints can lead to either individual or coarticulated movements. The authors use this model to make predictions about patterns of behavior (e.g., in response to perturbations), which they then demonstrate in human participants both by measuring movement kinematics as well as EMG. Together this work supports the authors' primary claims regarding how changes in task instructions (i.e., task constraints) can result in coarticulated or separated movement sequences and the extent to which the subsequent movement goal affects the planning and control of the previous movement.

Weaknesses:<br /> Although this work is quite interesting, it remains unknown whether there is a fundamental distinction between a coarticulated sequence and a single movement passing through a via point (or equivalently, avoiding an obstacle). The notion of a coarticulated sequence brings with it the notion of sequential (sub)movements and temporal structure, whereas the latter can really be treated as more of a constraint on the production of a single continuous movement. The authors suggest that these are not truly different kinds of movements at the level of a control policy, but this remains to be tested experimentally.

It also remains unclear for the theory of optimal feedback control as a whole where and how the cost function and constraints are specified to guide the optimization process. That is, presumably there is the ability for higher-level or explicit description of these constraints, but how they then become incorporated into a control policy remains unclear. With regard to the kind of multi-target constraints proposed here, in typical sequence tasks, while some movements become coarticulated, people also tend to form chunks with distinct chunk boundaries. This presumably means that there is at least some specification of the sequential ordering of these chunks that must exist beyond the control policy and that multiple control policies may still be warranted to execute an entire sequence (otherwise the authors' model might suggest that people can coarticulate forever without needing to exhibit any chunk boundaries). Hence, while the authors fairly convincingly show that a single control policy can lead to separated or coarticulated movements given an appropriate set of constraints, their work does not speak to where or how those constraints are specified, nor to how longer sequences are controlled.

Reviewer #1 (Public Review):

Summary:

The authors sought to investigate the associations of age at breast cancer onset with the incidence of myocardial infarction (MI) and heart failure (HF). They employed a secondary data analysis of the UK Biobank. They used descriptive and inferential analysis including Cox proportional hazards models to investigate the associations. Propensity score matching was also used. They found that Among participants with breast cancer, younger onset age was significantly associated with elevated risks of MI (HR=1.36, 95%CI: 1.19 to 1.56, P<0.001) and HF (HR=1.31, 95% CI: 1.18 to 1.46, P<0.001). the reported similar findings after propensity matching.

Strengths:

The use of a large dataset is a strength of the study as the study is well-powered to detect differences. Reporting both the unmatched and the propensity-matched estimates was also important for statistical inference.

Weaknesses:

The authors have addressed all my previous comments. I have no further comments.

Reviewer #3 (Public Review):

Summary:

Bell and colleagues studied how different splice isoforms of voltage-gated CaV2 calcium channels affect channel expression, localization, function, synaptic transmission, and locomotor behavior at the larval Drosophila neuromuscular junction. They reveal that one mutually exclusive exon located in the fourth transmembrane domain encoding the voltage sensor is essential for calcium channel expression, function, active zone localization, and synaptic transmission. Furthermore, a second mutually exclusive exon residing in an intracellular loop containing the binding sites for Caβ and G-protein βγ subunits promotes the expression and synaptic localization of around ~50% of CaV2 channels, thereby contributing to ~50% of synaptic transmission. This isoform enhances release probability, as evident from increased short-term depression, is vital for homeostatic potentiation of neurotransmitter release induced by glutamate receptor impairment, and promotes locomotion. The roles of the two other tested isoforms remain less clear.

Strengths:

The study is based on solid data that was obtained with a diverse set of approaches. Moreover, it generated valuable transgenic flies that will facilitate future research on the role of calcium channel splice isoforms in neural function.

Weaknesses:

(1) Based on the data shown in Figures 2A-C, and 2H, it is difficult to judge the localization of the cac isoforms. Could they analyze cac localization with regard to Brp localization (similar to Figure 3; the term "co-localization" should be avoided for confocal data), as well as cac and Brp fluorescence intensity in the different genotypes for the experiments shown in Figure 2 and 3 (Brp intensity appears lower in the dI-IIA example shown in Figure 3G)? Furthermore, heterozygous dIS4B imaging data (Figure 2C) should be quantified and compared to heterozygous cacsfGFP/+.

(2) They conclude that I-II splicing is not required for cac localization (p. 13). However, cac channel number is reduced in dI-IIB. Could the channels be mis-localized (e.g., in the soma/axon)? What is their definition of localization? Could cac be also mis-localized in dIS4B? Furthermore, the Western Blots indicate a prominent decrease in cac levels in dIS4B/+ and dI-IIB (Figure 1D). How do the decreased protein levels seen in both genotypes fit to a "localization" defect? Could decreased cac expression levels explain the phenotypes alone?

(3) Cac-IS4B is required for Cav2 expression, active zone localization, and synaptic transmission. Similarly, loss of cac-I-IIB reduces calcium channel expression and number. Hence, the major phenotype of the tested splice isoforms is the loss of/a reduction in Cav2 channel number. What is the physiological role of these isoforms? Is the idea that channel numbers can be regulated by splicing? Is there any data from other systems relating channel number regulation to splicing (vs. transcription or post-transcriptional regulation)?

(4) Although not supported by statistics, and as appreciated by the authors (p. 14), there is a slight increase in PSC amplitude in dIS4A mutants (Figure 2). Similarly, PSC amplitudes appear slightly larger (Figure 3J), and cac fluorescence intensity is slightly higher (Figure 3H) in dI-IIA mutants. Furthermore, cac intensity and PSC amplitude distributions appear larger in dI-IIA mutants (Figures 3H, J), suggesting a correlation between cac levels and release. Can they exclude that IS4A and/or I-IIA negatively regulate release? I suggest increasing the sample size for Canton S to assess whether dIS4A mutant PSCs differ from controls (Figure 2E). Experiments at lower extracellular calcium may help reveal potential increases in PSC amplitude in the two genotypes (but are not required). A potential increase in PSC amplitude in either isoform would be very interesting because it would suggest that cac splicing could negatively regulate release.

(5) They provide compelling evidence that IS4A is required for the amplitude of somatic sustained HVA calcium currents. However, the evidence for effects on biophysical properties and activation voltage (p. 13) is less convincing. Is the phenotype confined to the sustained phase, or are other aspects of the current also affected (Figure 2J)? Could they also show the quantification of further parameters, such as CaV2 peak current density, charge density, as well as inactivation kinetics for the two genotypes? I also suggest plotting peak-normalized HVA current density and conductance (G/Gmax) as a function of Vm. Could a decrease in current density due to decreased channel expression be the only phenotype? How would changes in the sustained phase translate into altered synaptic transmission in response to AP stimulation?

(6) Why was the STED data analysis confined to the same optical section, and not to max. intensity z-projections? How many and which optical sections were considered for each active zone? What were the criteria for choosing the optical sections? Was synapse orientation considered for the nearest neighbor Cac - Brp cluster distance analysis? How do the nearest-neighbor distances compare between "planar" and "side-view" Brp puncta?

(7) Cac clusters localize to the Brp center (e.g., Liu et al., 2011). They conclude that Cav2 localization within Brp is not affected in the cac variants (p. 8). However, their analysis is not informative regarding a potential offset between the central cac cluster and the Brp "ring". Did they/could they analyze cac localization with regard to Brp ring center localization of planar synapses, as well as Brp-ring dimensions?

(8) Given the accelerated PSC decay/ decreased half width in dI-IIA (Fig. 5Q), I recommend reporting PSC charge in Figure 3, and PPR charge in Figures 5A-D. The charge-based PPRs of dI-IIA mutants likely resemble WT more closely than the amplitude-based PPR. In addition, miniature PSC decay kinetics should be reported, as they may contribute to altered decay kinetics. How could faster cac inactivation kinetics in response to single AP stimulation result in a decreased PSC half-width? Is there any evidence for an effect of calcium current inactivation on PSC kinetics? On a similar note, is there any evidence that AP waveform changes accelerate PSC kinetics? PSC decay kinetics are mainly determined by GluR decay kinetics/desensitization. The arguments supporting the role of cac splice isoforms in PSC kinetics outlined in the discussion section are not convincing and should be revised.

(9) Paired-pulse ratios (PPRs): On how many sweeps are the PPRs based? In which sequence were the intervals applied? Are PPR values based on the average of the second over the first PSC amplitudes of all sweeps, or on the PPRs of each sweep and then averaged? The latter calculation may result in spurious facilitation, and thus to the large PPRs seen in dI-IIB mutants (Kim & Alger, 2001; doi: 10.1523/JNEUROSCI.21-24-09608.2001).

(10) Could the dI-IIB phenotype be simply explained by a decrease in channel number/ release probability? To test this, I propose investigating PPRs and short-term dynamics during train stimulation at lower extracellular Ca2+ concentration in WT. The Ca2+ concentration could be titrated such that the first PSC amplitude is similar between WT and dI-IIB mutants. This experiment would test if the increased PPR/depression variability is a secondary consequence of a decrease in Ca2+ influx, or specific to the splice isoform.

(11) How were the depression kinetics analyzed? How many trains were used for each cell, and how do the tau values depend on the first PSC amplitude? Time constants in the range of a few (5-10) milliseconds are not informative for train stimulations with a frequency of 1 or 10 Hz (the unit is missing in Figure 5H). Also, the data shown in Figures 5E-K suggest slower time constants than 5-10 ms. Together, are the data indeed consistent with the idea that dI-IIB does not only affect cac channel number, but also PPR/depression variability (p. 9)?

(12) The GFP-tagged I-IIA and mEOS4b-tagged I-IIB cac puncta shown in Figure 6N appear larger than the Brp puncta. Endogenously tagged cac puncta are typically smaller than Brp puncta (Gratz et al., 2019). Also, the I-IIA and I-IIB fluorescence sometimes appear to be partially non-overlapping. First, I suggest adding panels that show all three channels merged. Second, could they analyze the area and area overlap of I-IIA and I-IIB with regard to each other and to Brp, and compare it to cac-GFP? Any speculation as to how the different tags could affect localization? Finally, I recommend moving the dI-IIA and dI-IIB localization data shown in Figure 6N to an earlier figure (Figure 1 or Figure 3).

Reviewer #1 (Public Review):

Summary:

The manuscript by Bell et. al. describes an analysis of the effects of removing one of two mutually exclusive splice exons at two distinct sites in the Drosophila CaV2 calcium channel Cacophony (Cac). The authors perform imaging and electrophysiology, along with some behavioral analysis of larval locomotion, to determine whether these alternatively spliced variants have the potential to diversify Cac function in presynaptic output at larval neuromuscular junctions. The author provided valuable insights into how alternative splicing at two sites in the calcium channel alters its function.

Strengths:

The authors find that both of the second alternatively spliced exons (I-IIA and I-IIB) that are found in the intracellular loop between the 1st and 2nd set of transmembrane domains can support Cac function. However, loss of the I-IIB isoform (predicted to alter potential beta subunit interactions) results in 50% fewer channels at active zones and a decrease in neurotransmitter release and the ability to support presynaptic homeostatic potentiation. Overall, the study provides new insights into Cac diversity at two alternatively spliced sites within the protein, adding to our understanding of how regulation of presynaptic calcium channel function can be regulated by splicing.

Weaknesses:

The authors find that one splice isoform (IS4B) in the first S4 voltage sensor is essential for the protein's function in promoting neurotransmitter release, while the other isoform (IS4A) is dispensable. The authors conclude that IS4B is required to localize Cac channels to active zones. However, I find it more likely that IS4B is required for channel stability and leads to the protein being degraded, rather than any effect on active zone localization. More analysis would be required to establish that as the mechanism for the unique requirement for IS4B.

Reviewer #2 (Public Review):

This study by Bell et al. focuses on understanding the roles of two alternatively spliced exons in the single Drosophila Cav2 gene cac. The authors generate a series of cac alleles in which one or the other mutually exclusive exons are deleted to determine the functional consequences at the neuromuscular junction. They find alternative splicing at one exon encoding part of the voltage sensor impacts the activation voltage as well as localization to the active zone. In contrast, splicing at the second exon pair does not impact Cav2 channel localization, but it appears to determine the abundance of the channel at active zones. Together, the authors propose that alternative splicing at the Cac locus enables diversity in Cav2 function generated through isoform diversity generated at the single Cav2 alpha subunit gene encoded in Drosophila.

Overall this is an excellent, rigorously validated study that defines unanticipated functions for alternative splicing in Cav2 channels. The authors have generated an important toolkit of mutually exclusive Cac splice isoforms that will be of broad utility for the field, and show convincing evidence for distinct consequences of alternative splicing of this single Cav2 channel at synapses. Importantly, the authors use electrophysiology and quantitative live sptPALM imaging to determine the impacts of Cac alternative splicing on synaptic function. There are some outstanding questions regarding the mechanisms underlying the changes in Cac localization and function, and some additional suggestions are listed below for the authors to consider in strengthening this study. Nonetheless, this is a compelling investigation of alternative splicing in Cav2 channels that should be of interest to many researchers.

Reviewer #2 (Public Review):

Summary:

This work describes a new pharmacological targeting approach to inhibit selective functions of the ubiquitously expressed chemokine receptor CXCR4, a potential target of immunomodulatory or anti-cancer treatments. Overall, the results build a strong case for the potential of this new compound to target specific functions of CXCR4, particularly linked to tumorigenesis. However, a more thorough evaluation of the function of the compound as well as future studies in mammalian model systems are needed to better assess the promise of the compound.

Strengths:

The work elegantly utilizes in silico drug modelling to propose new small molecule compounds with specific features. This way, the authors designed compound AGR1.137, which abolishes ligand-induced CXCR4 receptor nanoclustering and the subsequent directed cell migration without affecting ligand-binding itself or some other ligand-induced signaling pathways. The authors have used a relatively broad set of experiments to validate and demonstrate the effects of the drug. Importantly, the authors also test AGR1.137 in vivo, using a zebra fish model of tumorigenesis and metastasis. A relatively strong inhibitory effect of the compound is reported.

Weaknesses:

The authors have been able to significantly strengthen their data from the first submission. The content of this manuscript is pretty solid, although studies in mammalian model systems are naturally needed in the future to better assess the promise of the compound.

Reviewer #2 (Public Review):

Summary:

This paper addresses an important computational problem in learning and memory. Why do related memory representations sometimes become more similar to each other (integration) and sometimes more distinct (differentiation)? Classic supervised learning models predict that shared associations should cause memories to integrate, but these models have recently been challenged by empirical data showing that shared associations can sometimes cause differentiation. The authors have previously proposed that unsupervised learning may account for these unintuitive data. Here, they follow up on this idea by actually implementing an unsupervised neural network model that updates the connections between memories based on the amount of coactivity between them. The authors use their modeling framework to simulate three recent empirical studies, showing that their model captures aspects of these findings that are hard to account for with supervised learning.

Overall, this is a strong and clearly described work that is likely to have a positive impact on computational and empirical work in learning and memory. While the authors have written about some of the ideas discussed in this paper previously, a fully implemented and openly available model is a clear advance that will benefit the field. It is not easy to translate a high-level description of a learning rule into a model that actually runs and behaves as expected. The fact that the authors have made all their code available makes it likely that other researchers will extend the model in numerous interesting ways, many of which the authors have discussed and highlighted in their paper.

Strengths:

The authors succeed in demonstrating that unsupervised learning with a simple u-shaped rule can produce results that are qualitatively in line with the empirical reports. In each of the three models, the authors manipulate stimulus similarity (following Chanales et al.), shared vs distinct associations (following Favila et al.), or learning strength (a stand-in for blocked versus interleaved learning schedule; following Schlichting et al.). In all cases, with hand-tuning of additional parameters, the authors are able to produce model representations that fit the empirical results, but that can't easily be accounted for by supervised learning. Demonstrating these effects isn't trivial and a formal modeling framework for doing so is a valuable contribution. Overall, the work is very thorough. The authors investigate many different aspects of the learning dynamics (learning rate, oscillation strength, hidden layer overlap etc) in these models and produce several key insights. Of particular value are their demonstrations that when differentiation occurs, it occurs very quickly and asymmetrically and results in anti-correlated representations, as well as the distinction between symmetric and asymmetric integration in their model. The authors thoroughly acknowledge the relative difficulty of producing differentiation in their models relative to integration, and are now more clear about why they don't necessarily view this as mismatch with the empirical data. The authors are also more clear about the complicated activation dynamics in their model and why critical ranges for some parameters can't be given -- the number of interacting parameters mean that there are many combinations that could produce the critical activation dynamics and thus the same result. Despite this complexity, the paper is very clearly written; the authors do a good job of both formally describing their model as well as giving readers a high level sense of how many of their critical model components work.

Weaknesses:

Though the u-shaped learning rule is essential to this framework, the paper doesn't do any formal investigation of this learning rule or comparison with other learning rules. The authors do have a strong theoretical interest in this rule as well as experimental precedent for testing this rule, which they now thoroughly discuss in the paper. Still, a stronger argument in support of the non monotonic plasticity hypothesis could have been made by comparing this learning rule to alternatives. Additionally, the authors' choice of strongly prewiring associations makes it difficult to think about how their model maps onto experimental contexts where associations are only weakly learned. However, the authors thoroughly acknowledge why this was necessary and discuss this limitation in the paper.

Reviewer #1 (Public Review):

Ritvo and colleagues present an impressive suite of simulations that can account for three findings of differentiation in the literature. This is important because differentiation-in which items that have some features in common, or share a common associate are less similar to one another than are unrelated items-is difficult to explain with classic supervised learning models, as these predict the opposite (i.e., an increase in similarity). A few of their key findings are that differentiation requires a high learning rate and low inhibitory oscillations, and is virtually always asymmetric in nature.

This paper was very clear and thoughtful-an absolute joy to read. The model is simple and elegant, and powerful enough to re-create many aspects of existing differentiation findings. The interrogation of the model and presentation of the findings were both extremely thorough. The potential for this model to be used to drive future work is huge.

The authors have been very responsive to my previous reviews and I have no further concerns and identify no major weaknesses.

Reviewer #3 (Public Review):

This paper proposes a computational account for the phenomenon of pattern differentiation (i.e., items having distinct neural representations when they are similar). The computational model relies on a learning mechanism of the nonmonotonic plasticity hypothesis, fast learning rate and inhibitory oscillations. In the revised paper, the authors justified the initialization of the model, added empirical evidence supporting the use of two turning points in the NMPH function and provided details of the learning mechanisms of the model. The relatively simple architecture of the model makes its dynamics accessible to the human mind. Furthermore, using similar model parameters, this model produces simulated data consistent with empirical data of pattern differentiation. The authors also provide insightful discussion on the factors contributing to differentiation as opposed to integration.

Reviewer #1 (Public Review):

Using a combination of cutting-edge high-resolution technologies (expansion microscopy, SIM, and CLEM) and biochemical approaches (in vitro translocation of actin filaments, cargo uptake assays, and drug treatment), the authors revisit and update previous results about TbMyo1 and TbACT in the bloodstream form (BSF) of Trypanosoma brucei. They show that a great part of the myosin motor is cytoplasmic but the fraction associated with organelles is in proximity to the endosomal system and in glycosomes. In addition, they show that TbMyo1 can move actin filaments in vitro and visualize for the first time this actomyosin system using specific antibodies, a "classical" antibody for TbMyo1, and a chromobody for actin. Finally, using latrunculin A, which sequesters G-actin and prevents F-actin assembly, the authors show the delocalization and eventually the loss of the filamentous actin signal and the concomitant loss of the endosomal system integrity.<br /> Overall this well-conducted and convincing study paves the way toward the elucidation of the role of an actomyosin system in the maintenance of the endosomal network in T. brucei.

Strengths:

The work is of high quality and uses advanced technologies to determine the involvement TbMyo1 and actin in the integrity of the endosomal system. The conclusions are not over-interpreted and are supported by the experimental results and their quantification.

Weaknesses:

Although disruption of the actomyosin system using either the actin-depolymerizing drug latrunculin A or the TbMyo1-RNAi cell line established an effect on the endosomal system integrity, it remains to understand how this occurs mechanistically and what are the intracellular components involved.

Reviewer #2 (Public Review):

The study by Link et al. advances our understanding of the actomyosin system in T. brucei, focusing on the role of TbMyo1, a class I myosin, within the parasite's endosomal system. Using a combination of biochemical fractionation, in vitro motility assays, and advanced imaging techniques such as correlative light and electron microscopy (CLEM), this paper demonstrates that TbMyo1 is dynamically distributed across early and late endosomes, the cytosol, is associated with the cytoskeleton, and a fraction has an unexpected association with glycosomes. Notably, the study shows that TbMyo1 can translocate actin filaments at velocities suggesting an active role in intracellular trafficking, potentially higher than those observed for similar myosins in other cell types. This work not only elucidates the spatial dynamics of TbMyo1 within T. brucei but also suggests its broader involvement in maintaining the complex architecture of the endosomal network, underscoring the critical role of the actomyosin system in a parasite that relies on high rates of endocytosis for immune evasion.

A key strength of the study is its exceptional rigor and successful integration of a wide array of sophisticated techniques, such as in vitro motility assays, and advanced imaging methods, e.g. CLEM. This combination of approaches underscores the study's comprehensive approach to examining the ultrastructural organization of the trypanosome endomembrane system. The application of functional data using inhibitors, such as latrunculin A for actin depolymerization, further strengthens the study by providing insights into the dynamics and regulatory mechanisms of the endomembrane system. This demonstrates how the actomyosin system contributes to cellular morphology and trafficking processes. Furthermore, the discovery of TbMyo1 localization to glycosomes introduces a novel aspect to the potential roles of myosin I proteins within the cell, particularly in the context of organelles analogous to peroxisomes. This observation not only broadens our understanding of myosin I functionality but also opens up new avenues for research into the cell biology of trypanosomatids, marking a significant contribution to the field.

A significant initial weakness was the reliance on spatial association data to infer functional relationships without direct demonstration of biochemical activities in vivo. The authors have since addressed this by including new evidence from TbMyo1 RNAi cell lines and EM data that show the effects of TbMyo1 depletion on cellular ultrastructure. The authors' responses and additional data reinforce their initial conclusions and address previous concerns. Several new, elegant hypotheses are proposed in the discussion that warrant further investigation to fully understand TbMyo1's interactions and regulatory mechanisms in vivo.

Reviewer #3 (Public Review):

Summary:

In this work, Link and colleagues have investigated the localization and function of the actomyosin system in the parasite Trypanosoma brucei, which represents a highly divergent and streamlined version of this important cytoskeletal pathway. Using a variety of cutting-edge methods, the authors have shown that the T. brucei Myo1 homolog is a dynamic motor that can translocate actin, suggesting that it may not function as a more passive crosslinker. Using expansion microscopy, iEM, and CLEM, the authors show that MyoI localizes to the endosomal pathway, specifically the portion tasked with internalizing and targeting cargo for degradation, not the recycling endosomes. The glycosomes also appear to be associated with MyoI, which was previously not known. An actin chromobody was employed to determine the localization of filamentous actin in cells, which was correlated with the localization of Myo1. Interestingly, the pool of actomyosin was not always closely associated with the flagellar pocket region, suggesting that portions of the endolysomal system may remain at a distance from the sole site of parasite endocytosis. Lastly, the authors used actin-perturbing drugs to show that disrupting actin causes a collapse of the endosomal system in T. brucei, which they have shown recently does not comprise distinct compartments but instead a single continuous membrane system with subdomains containing distinct Rab markers.

Strengths:

Overall, the quality of the work is extremely high. It contains a wide variety of methods, including biochemistry, biophysics, and advanced microscopy that are all well deployed to answer the central question. The data is also well quantitated to provide additional rigor to the results. The main premise, that actomyosin is essential for the overall structure of the T. brucei endocytic system, is well supported and is of general interest, considering how uniquely configured this pathway is in this divergent eukaryote and how important it is to the elevated rates of endocytosis that are necessary for this parasite to inhabit its host.

Comments on revised version:

The revised manuscript has addressed the main issue, the lack of TbMyo1 functional data that was brought up during the first round of review. I find it interesting that Myo1 depletion has what appears to be a limited effect on endocytosis while producing a similar fragmentation of the endocytic pathway to what is seen with the LatA treatments. As CCV remains in both LatA treatments and TbMyo1 RNAi, it seems apparent that the organization of the endocytic pathway is not required for at least basal levels of endocytosis.

My other points were well addressed by the rebuttal. I am satisfied with the update.

Reviewer #2 (Public Review):

Summary:

The authors set out to uncover which brain regions might support the continuous updating of semantic associations thereby showing a system of semantic plasticity. Using fMRI data from participants viewing thousands of natural scene images over 30 recording sessions, they hoped to establish how objects co-occuring with each other within images influences the semantic representations in the human brain that relate to those object concepts.

Strengths:

There is a lot to like about the paper. A major strength of the methods and results is the convincing demonstration of many of the results. This includes showing item representations in the ventral visual pathway and medial temporal lobes (MTL), as we would expect. They also show semantic effects - defined using the word co-occurrence vectors from word2vec, along the posterior and anterior ventral visual pathway and MTL - replicating various past studies. The authors use a creative approach to show that the item representations measured within each session are modulated by the co-occurrence structure in previous trials, becoming more closely related. And that item representations seem to subtly change over the course of the 30 sessions, in that they become less related to each other with increasing distance. However, the semantic effects within each session itself are claimed to remain unchanged.

Weaknesses:

This leads to what I see as a weakness in the study. The conclusions relate to semantic plasticity and the changes in semantic (associative) representations. The drift analyses do appear to show representational changes across the sessions, but this is based on the item representations. The inference is that this is due to an updating of knowledge about the associations each item has had with other items. Yet, in the same regions, the authors suggest that semantic associative effects, as tested using word2vec for each session, remain stable. Doesn't this seem to contradict the claims about semantic plasticity?

Some of this is difficult to unpick as the semantic stability analysis using word2vec in each session is only very briefly mentioned, and the data is not shown (I would include it). So, at present, I feel they show evidence of representational changes but do not show evidence of what the nature of the change is. If the neural representations consistently reflect the long-term semantic associations (which is what word2vec captures), then how does this combine with the drift effects of item representations?

Does it mean that the changes in item representations do not reflect semantic associative knowledge? And reflect some other non-specified type of information (perhaps as the participants are doing an image memory test).

Another potential weakness is the robustness of the drift analysis itself. For the drift analysis, item representations in each session are compared to all other sessions and then averaged according to the number of intervening sessions. This means the data for item representation with a session difference of 1 will be based on 29 data points, a session difference of 2 on 28 data points ... and a session difference of 29 based on 1 data point. So there is a huge imbalance in the amount of data that goes into the analysis for the different numbers of intervening sessions. This leads me to wonder if it could impact the validity of the results. An alternative might be to use 1 datapoint for each session (or a suitable value, I imagine 5 would still give enough data to analyse drifts) and calculate drift, and then repeat this with different partitions of the data to see how stable it is, and if drift is reliably occurring. Alternatively, the analyses they use might have been used and validated previously.

To be clear, I do think this is a very nice study and will have a positive impact on researchers interested in object processing, semantic knowledge, statistical learning, and schemas. But think there are some gaps between what the data shows evidence for, and the ultimate inferences made.

Reviewer #3 (Public Review):

Summary:

This study characterizes the relative stability of semantic representations in the human brain using functional magnetic resonance imaging (fMRI) data. The authors suggest that representations in the early stages of processing within the visual system are stable over hours, weeks, and months, while representations in later stages of processing - within the medial temporal lobe - change more rapidly, sometimes within the span of a single fMRI session.

To make this claim, the authors conduct a series of analyses using a well-established fMRI dataset. This begins with a decoding analysis to identify regions that contain reliable object-specific information. This approach identifies early stages within canonical visual cortices (e.g., primary visual cortex, V1), as well as downstream regions within the medial temporal lobe (MTL); this includes perirhinal cortex (PRC), parahippocampal cortex (PHC), and several subfields within the hippocampal cortex (e.g., CA1). Next, they identify regions that are correlated with "semantic features" associated with these objects, determined using word2vec embeddings of each of these object names. Several regions within the MTL (CA1, PRC, PHC) were significantly correlated with these word2vec embeddings. The authors then turn their analyses to representational change across two different timescales. Between scan sessions, regions at early stages of visual processing (e.g., V1) contain relatively stable representations, while regions within the MTL decreased their auto-correlation across sessions, suggesting that there is increased representational change/drift in the MTL. Finally, the authors demonstrate that there is representational change with PHC within a single scan session - changes that reflect the statistics of visual experiences.

Strengths:

The analyses conducted in this study are solid and creative and they yield compelling theoretical results. Beyond the paper's central claims, this study also highlights the utility of publicly available datasets (i.e., NSD) in exploring and evaluating novel theoretical ideas.

Especially compelling is the combined analysis used to estimate reliable item-level representations, first, and then the long-term drift of item representations (i.e., between sessions). The design choices for modeling the fMRI data (e.g., the cross-validated approach to predicting voxel-level responses) reflect state-of-the-art analysis methods, while the control regions used in these analyses (e.g., V1) provide compelling contrasts to the experimental effects. This makes it clear that the observed representational drift/instability is not present throughout the visual system. These results indicate that this effect is worthy of future experiments, while also providing auxiliary information related to effect size, etc.

Weaknesses:

The concerns outlined here do not challenge the central claim within this study, relating to the relative instability of representations within the MTL as compared to V1. Instead, these concerns focus on whether these representations should be described as "semantic," the importance we should give to the distinction between PHC and other MTC structures, and the lack of systematic analysis in relation to the "gradient" from posterior to anterior regions. In each case, I have provided suggestions as to how these concerns might be addressed. Finally, I've made a note about whether these data should be interpreted in terms of neural "plasticity" given the lack of behavioral change in relation to these fMRI data.

(1) No reason to believe that representations within the MTL are necessarily 'semantic.'

The authors suggest "evoked object representations in CA1, PHC, and PRC are semantic in nature." However, the correlation between fMRI responses and word2vec embeddings-the only evidence for "semantic" representations-is ambiguous. These structures might contain high-dimensional features that are associated with these objects for other reasons; concretely, there might be visual information that is not semantic but relates to the reliable visual properties of these objects (e.g., texture, shape, location in the image). Yet there are no analyses to disambiguate between these alternative accounts. As such, labeling these as "semantic" representations is suggestive but premature. Nonetheless, developing such a control analysis should be relatively straightforward. I outline one possible approach below.

While "semantic" information is a relatively nebulous term in the cognitive neurosciences, contemporary deep-learning methods might offer unambiguous ways to characterize such representations. If we assume that "semantics" relate to the meaning of an object/entity and not the "low-level" sensory attributes related to encoding this information, this leads to a straightforward implementation of object semantics: the reliable variance that can be isolated within the residuals of a sensory encoder. For example, do word2vec embeddings explain variance within the medial temporal lobe above and beyond the variance explained by a vision-only image encoder? Of course, care must be taken to use a visual encoder which is not itself a crystallization of object semantics (e.g., encoders optimized using a classification objective), but this is all very feasible given contemporary computer vision methods. Adding such a control analysis would offer a significant improvement over the current approach, clarifying the nature of the stimulus-driven representations within the medial temporal lobe by disentangling "semantic" properties of reliable visual features.

Additionally, it is not clear whether results from the current "object encoding" analysis and "semantic detection" analysis differ because of underlying differences in representational content in these regions or because of design choices in these analyses themselves. That is, while the object encoding analysis learns a linear projection from a one-hot 80-dimensional vector to hemodynamic responses in each brain region, the semantic detection analysis correlates these predicted hemodynamic responses with word2vec embeddings associated with each of these 80 objects. These different analysis methods result in different outcomes: not all regions identified by the object encoding analysis are also identified in the semantic detection analysis (e.g., hippocampal subfields). It is not clear to what degree these different outcomes are a function of "semantic" information, or are simply a consequence of differences in analytic approaches. It would be useful to know the results by repeating the logic from the object encoding analysis, but instead of 1-hot vectors for each object, use the word2vec embeddings.

(2) Unclear if the differences between PHC and other MTL structures are driven by SNR.

Parahippocampal cortex (PHC) is a region reliably identified by the analyses in this study: PHC is identified in the analysis of item encoding, semantic content, and representational drift across long (between-session) and short (within-session) timescales. Control regions here provide a convincing contrast to PHC in each of these analyses, and so the role of PHC appears clear in these analyses. However, it is unclear how to interpret the difference between PHC and other structures within the MTC - namely, the observation that PHC alone is influenced by representational drift across shorter timescales. It's possible that these effects are common throughout the MTL, but are only evident in PHC because of increased SNR. This concern seems plausible when observing PHC's "encoding success" and "semantic content," both visually and statistically, relative to other MTL structures: the magnitude of PHC's effect appears greater, which could simply be an artifact of PHC's relatively high SNR. In fMRI data, for example, PRC typically has relatively low SNR due to field inhomogeneities related to dropout, due to PRC's relative proximity to the ear canal-which is exacerbated in 7T (vs 3T) scanners, which was the case for the data in this study.

Addressing this concern could be relatively straightforward. For example, including information about the SNR in each respective brain region would be very helpful. If the SNR across brain regions within the MTL is relatively uniform, then this already addresses the concern above. regardless, it would be useful to report the experimental effects in relation, for example, the split-half reliability of signal in each brain region. That is, instead of simply reporting that that results are significant across brain regions, the authors might estimate how reliable the variance is across brain regions, and use this reliable variance as a ceiling which can be used to normalize the amount of variance explained in each analysis. By providing an account of the differences in the reliability/SNR of different regions, we would have a much better estimate of the relative importance of differences in the results reported for different regions within the MTL.

(3) Need for more systematic analysis/visualization of "posterior" vs. "anterior" regions.

The authors report that "Whole-brain analyses revealed a gradient of plasticity in the temporal lobe, with drift more evident in anterior than posterior areas." However, the only contrast provided in the main text is between MTL structures and V1-there is no "gradient" in any of these analyses. There are other regions visualized in Supplemental Figure 3, but there is not a systematic evaluation of the gradient along a "posterior/anterior" axis. It would be helpful to see the results in Figures 3A, 4A, 5A, and 6A to include other posterior visual regions (e.g., V4, LOC, PPA, FFA) beyond V1.

(4) Without behavioral data, not a direct relationship with "stability-plasticity tradeoff"

The results from this study are framed in relation to a "stability-plasticity tradeoff." As argued in this manuscript, this tradeoff is central to animal behavior - our ability to rapidly deploy prior knowledge to respond to the world around us. Given that there are no behavioral measures used in the current study, however, no claims can be made about how these fMRI data might relate to learning, or behavior more generally. As such, framing these results in terms of a stability-plasticity tradeoff is tenuous. "Representational drift," on the other hand, is a term that is relatively agnostic in its relationship with behavior, and aptly describes the results presented here. The authors refer to this term as well. Considering the lack of behavioral evidence, alongside the core findings from these neuroimaging data, "representational stability" or "representational "drift" seems to be a more direct description of the available data than "neural plasticity" or a "stability-plasticity tradeoff."

Reviewer #1 (Public Review):

Summary:

This research used cell-based signaling assay and Gaussian-accelerated molecular dynamics (GaMD) to study peptide-mediated signaling activation of Polycystin-1 (PC1), which is responsible for the majority of autosomal dominant polycystic kidney disease (ADPKD) cases. Synthetic peptides of various lengths derived from the N-terminal portion of the PC1 C-terminal fragment (CTF) were applied to HEK293T cells transfected with stalkless mouse CTF expression construct. It was shown that peptides including the first 7, 9, and 17 residues of the N-terminal portion could activate signaling to the NFAT reporter. To further understand the underlying mechanism, docking and peptide-GaMD simulations of peptides composed of the first 9, 17, and 21 residues from the N-terminal portion of the human PC1 CTF were performed. These simulations revealed the correlation between peptide-CTF binding and PC1 CTF activation characterized by the close contact (salt bridge interaction) between residues R3848 and E4078. Finally, a Potts statistical model was inferred from diverged PC1 homologs to identify strong/conserved interacting pairs within PC1 CTF, some of which are highly relevant to the findings from the peptide GaMD simulations. The peptide binding pockets identified in the GaMD simulations may serve as novel targets for design of therapeutic approaches for treating ADPKD.

Strengths:

(1) The experimental and computational parts of this study complement and mostly support each other, thus increasing the overall confidence in the claims made by the authors.

(2) The use of exogenous peptides and a stalkless CTF in the GaMD is a step forward compared to earlier simulations using the full CTF, CTF mutants, or the stalkless CTF alone. And it led to findings of novel binding pockets.

(3) Since the PC1 shares characteristics with the Adhesion class of GPCRs, the approaches used in this work may be extended to other similar systems.

Weaknesses:

(1) Only results for selective peptides (p9, p17 p21) binding with the protein were shown. It would be interesting to see the interaction between some (if not all) of the other peptides with the protein.

(2) The convergence of the simulations is not very good. The results should be interpreted more qualitatively rather than quantitively because large variations in the free energy profile were seen between different replicates. Although these simulations might have identified representative low-energy binding conformations of the peptides, whether they have explored all possible conformations is still a question.

Reviewer #2 (Public Review):

Summary:

This manuscript, "Activation of Polycystin-1 Signaling by Binding of Stalk-derived Peptide Agonists", by Miao and coworkers. The autosomal dominant polycystic kidney disease (ADPKD) is a major form of polycystic kidney disease (PKD). To provide better treatment and avoid side effects associated with currently available options, the authors investigated an interesting GPCR, polycystin-1 (PC1), as a potential therapeutic target. In vitro and in silico studies were combined to identify peptide agonists for PC1 and to elucidate their roles in PC1 signaling. Overall, regarding the significance of the findings, this work described valuable peptide agonists for PC1 and the combined in vitro and in silico approach can be useful to study a complex system like PC1. However, the strength of the evidence is incomplete, as more experiments are needed as controls to validate the computational observations. The work appears premature.

Strengths:

(1) This work first described the experimental discovery of short peptides designed to mimic the stalk region of PC1, followed by computational investigation using docking and MD simulations. PC1 is a complex membrane protein and an emerging target for ADPKD, but it can be challenging to study. The knowledge and the peptide discovery can be valuable and useful to understand the mechanism and potential modulation of PC1.<br /> (2) The authors published the mechanistic study of PC1 and identified key interacting residues such as N3074-S3585 and R3848-E4078, using very similar techniques (PNAS 2022, 119(19), e2113786119). This work furthers this research by identifying peptides that are stalk mimics for PC1 activation.<br /> (3) Eight peptides were designed and tested experimentally first; three were computationally studied with docking and GaMD simulations to understand their mechanism (s).

Weaknesses:

(1) The selectivity of the peptides between PC1 and PC2 remains unknown in this revision.

Overall, my comments were mostly addressed properly.

Reviewer #3 (Public Review):

Summary:

The authors demonstrate the activation of Polycystin-1 (PC1), a G-protein coupled receptor, using small peptides derived from its original agonist, the stalk TA protein. In the experimental part of the study, the authors performed cellular assays to check the peptide-induced reactivation of a mutant form of PC1 which does not contain the stalk agonist. The experimental data is supported by computational studies using state-of-the-art Gaussian accelerated Molecular Dynamics (GaMD) and bioinformatics analysis based on sequence covariance. The computer simulations revealed the mechanistic details of the binding of the said peptides with the mutant PC1 protein and discovered different bound, unbound, and intermediate conformations depending on the peptide size and sequence. Due to the use of reliable and well-established molecular simulation algorithms and the physiological relevance of this protein autosomal dominant polycystic kidney disease (ADPKD) make this work particularly valuable.

Strengths:

This work is exploratory and its goal is to establish that small peptides can be used to probe the PC1 signaling process. The authors have provided sufficient evidence to justify this claim. Their GaMD simulations have produced free-energy landscapes that differentiate the interaction of PC1 with three different synthetic peptides and demonstrate the associated conformational dynamics of the receptor protein. Their trajectory analysis and sequence covariance analysis could identify residue-specific interactions that facilitate this process. The authors also performed residue-wise and total interaction energy calculations to substantiate their findings.

Weaknesses:

The reported free energy landscapes are not fully converged. But they are still sufficient to gain biological insight.

Reviewer #1 (Public Review):

Summary:

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

Strengths:

- Comprehensive characterization of the causes of scoliosis in ciliary transition zone mutants rpgrip1l and cep290<br /> - Comparison of rpgrip1l mutants pre- and post-scoliosis onset allowed authors to identify specific phenotypes as being correlated with spine curvature, including brain ventricle dilations, loss of Reissner fiber, and loss of cilia in proximity to the subcommissural organ<br /> - Elegant genetic demonstration that increased urotensin peptide levels do not account for spinal curvature in rpgrip1l mutants<br /> - The identification of astrogliosis and Annexin over-expression in glial cells surrounding diencephalic and rhombencephalic ventricles as being correlated with scoliosis onset and severe curve progression is a very interesting finding, which may ultimately inform pathogenic mechanisms driving spine curvature

Weaknesses:

- The fact that cilia loss/dysfunction and Reissner fiber defects cause scoliosis in zebrafish is already well established in the literature, as is the requirement for cilia in foxj1a-expressing cells<br /> - Neuroinflammation has already been identified as the underlying pathogenic mechanism in at least 2 previously published scoliosis models (zebrafish ptk7a and sspo mutants)<br /> - Anti-inflammatory drugs like aspirin, NAC and NACET have also previously been demonstrated to suppress scoliosis onset and severe curve progression in these models<br /> Therefore, although similar observations in rpgrip1l and cep290 mutants (as reported here) add to a growing body of literature that supports a common biological mechanism underlying spine curvature in zebrafish, novelty of reported findings is diminished.<br /> - Although authors demonstrate that astrogliosis and/or macrophage or microglia cell recruitment are correlated with scoliosis, they do not formally demonstrate that these events are sufficient to drive spine curvature. Thus, the functional consequences of astrogliosis and microglia infiltration remain uncertain.<br /> - Authors do not investigate the effect of anti-inflammatory treatments on other phenotypes they have correlated with spinal curve onset (like ventricle dilation, Reissner fiber loss, and multi-cilia loss around the subcommissural organ). This would help to identify causal events in scoliosis.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

Very clear and comprehensive analysis of the mutant zebrafish.

Reviewer #1 (Public Review):

This manuscript by Tyler and colleagues describes a thorough analysis of IR-induced changes in nascent RNA transcripts, and a genome-wide screening effort to identify the responsible proteins. The findings extend previous work describing DNA damage-induced transcriptional repression from DNA breaks in cis to bulk genomic DNA damage. A significant discovery is the inability of arrested cells to undergo DNA damage-induced gene silencing, which, at least at the rDNA locus, is attributed to an inability to mediate ATM-induced transcriptional repression. While the findings add to our knowledge of how DNA damage affects gene expression, there are several limitations to the current study that remain inadequately addressed. In addition, some of the proposed conclusions seem speculative and should be marked as such, omitted or experimentally supported.

Two major concerns were as follows and have been addressed as outlined in the authors' response to this review:

(1) The CIRSPR screen designed to detect regulators of damage-induced transcriptional repression is based on EU incorporation following a 7-day selection of stable knockout cells. As the authors point out, cell cycle arrest reduces rDNA transcription on its own. The screen, which assesses changes in sgRNA distribution in EU high cells, is thus likely to be dominated by factors that affect cell cycle progression. This is exemplified in the analyses of top hits related to neddylation. The screen's limitations in terms of identifying DDR effectors of damage-induced silencing needs to be clearly stated.

(2) The authors confirm previous findings of DNA damage-induced repression of rDNA and histone gene transcription. The authors propose that these highly transcribed genes are more susceptible to silencing than the bulk of protein coding genes and propose a global damage-induced signaling event that is independent of DNA breaks in cis. While this is possible, it is not demonstrated in this manuscript, and the authors should acknowledge alternative explanations. For example, the loci found to be repressed by bulk IR are highly repetitive gene arrays that tend to form nuclear sub-compartments (nucleoli, histone bodies). As such, their likelihood of being in the vicinity of DNA damage is high, at least for a fraction of gene copies. The findings, therefore, remain consistent with cis-induced silencing. Moreover, silencing may spread through the relevant nuclear sub-compartments, consistent with the formation of DNA damage compartments described recently (PMID: 37853125).

Other comments - also addressed in the authors' response:

(1) The statement that silencing is due to transcription initiation rather than elongation is not sufficiently supported by the data. Could equivalent nascent transcript reduction not be the result of the suppression of elongating RNA PolII? To draw the proposed conclusion, the authors would need to demonstrate that RNA PolII initiation is altered, using RNA PollII ChIP and/or analysis of relevant RNA PolII phosphorylation patterns.

(2) The lack of rDNA silencing in arrested cells is interesting, though the underlying mechanism remains unclear. To further corroborate the proposed defect in ATM-mediated signaling, the authors should look directly at ATM and Treacle phosphorylation upstream of TOPBP1.

(3) The "change in relative heights of the EU low (G1) and EU high (S/G2) peaks" in Figs 5D, 5E and 6B is central to the proposed model of transcriptional changes being affected by cell cycle arrest. These differences should be visualized more clearly and quantified across independent experiments. Ideally, cell cycle stage should be dissected as in Fig. 2B. How do the authors envision cell cycle arrest triggers the defect in transcriptional silencing?

Reviewer #2 (Public Review):

In this manuscript, the authors attempted to study mechanisms of transcription inhibition in cells treated with IR. They observed that unlike transcription inhibition induced by UV damage that depends on histone chaperone HIRA, IR induced transcription inhibition is independent on HIRA. Through a CRISPR/Cas9 screen, they identified protein neddylation is important for transcription inhibition. By sequencing nascent RNA, they observed that down-regulated transcripts upon IR treatment are largely highly transcribed genes including histone genes and rDNA.

This study utilized comprehensive approaches to fill in knowledge gap of IR-induced transcription inhibition.

Comments on current version:

The revised manuscript largely addressed my concerns.

Reviewer #2 (Public Review):

Summary:

In the manuscript by Oestreicher et al, the authors use patch-clamp electrophysiology, immunofluorescent imaging of the cochlea, auditory function tests, and single-unit recordings of auditory afferent neurons to probe the unique properties of calcium signaling in cochlear hair cells that allow rapid and sustained neurotransmitter release. The calcium binding proteins (CaBPs) are thought to modify inactivation of the Cav1.3 calcium channels in IHCs that initiate vesicle fusion, reducing the calcium-dependent inactivation (CDI) of the channels to allow sustained calcium influx to support neurotransmitter release. The authors use knockout mice of Cabp1 and Cabp2 in a double knockout (Cabp1/2 DKO) to show that these molecules are required for enabling sustained calcium currents by reducing CDI, enabling proper IHC neurotransmitter release. They further support their evidence by re-introducing Cabp2 using injection of AAV containing the Cabp2 sequence into the cochlea, which restores some of the auditory function and reduces CDI in patch-clamp recordings.

Strengths:

Overall the data is convincing that Cabp1/2 is required for reducing CDI in cochlear hair cells, allowing their sustained neurotransmitter release and sound encoding. Figures are well-prepared, recordings are careful and stats are appropriate, and the manuscript is well written. The discussion appropriately considers aspects of the data that are not yet explained and await further experimentation.

Weaknesses:

There are some sections of the manuscript that pool data from different experiments with slightly different conditions (wt data from a previous paper, different calcium concentrations, different holding voltages, tones vs clicks, etc). This makes the work harder to follow and more complicated to explain. However, the major conclusion, that that cabp1 and 2 work together to reduce calcium dependent inactivation of L-type calcium channels in cochlear inner hair cells, still holds and is well supported. Another minor weakness is that the authors used injections of AAV containing sequences for Cabp2, but do not present data from sham surgeries. In most cases, the improvement of hearing function with AAV injection is believable and should be attributed to the cabp2 function. However, in at least one instance (Figure 4B), the results of the AAV injection experiments may be overinterpreted - the authors show that upon AAV injection, the hair cells have a much longer calcium current recovery following a large, long depolarization to inactivate the calcium channels. Without comparison to a sham surgery, it is not known if this result could be a subtle result of the surgery or indeed due to the Cabp2 expression. The authors have added text acknowledging this, as appropriate.

Reviewer #1 (Public Review):

Summary:

This manuscript dissects the contribution of the CaBP 1 and 2 on the calcium current in the cochlear inner hair cells. The authors measured the calcium current inactivation from the double knock-out CaBP1 and 2 and show that both proteins contribute to the voltage-dependent and calcium-dependent inactivation. Synaptic release was reduced in the double KO. As a consequence, the authors observed a depressed activity within the auditory nerve. Taken together, this study identifies a new player that regulates the stimulation-secretion coupling in the auditory sensory cells.

Strengths:

In this study, the authors bring compelling evidence that CaBP 1 and 2 are both involved in the inactivation of the calcium current, from cellular up to system level and by taking care to probe different experimental conditions such as different holding potentials and by rescuing the phenotype with the re-expression of CaBP2. Indeed, while changing the holding potential worsen the secretion, it completely changes the kinetics of the inactivation recovery. It alerts the reader that probing different experimental conditions that may be closer to physiology are better suited to uncover any deleterious phenotype. This gave pretty solid results.

Weaknesses:

Although this study clearly points that CaBP1 is involved in the calcium current inactivation, it is not clear how CaBP1 and CaBP2 act together (but this is probably beyond the scope of the study). Another point is that the authors re-express CaBP2 to largely rescue the phenotype in the double KO but no data are available to know whether the re-expression of both CaBP1 and CaBP2 would achieve a full recovery and what would be the effect of the sole re-expression of CaBP1 in the double KO.

Reviewer #3 (Public Review):

Summary:

The authors attempted to unravel the role of the Ca2+-binding proteins CaBP1 and CaBP2 for the hitherto enigmatic lack of Ca2+-dependent inactivation of Ca2+ currents in sensory inner hair cells (IHCs). As Ca2+ currents through Cav1.3 channels are crucial for exocytosis, the lack of inactivation of those Ca2+ currents is essential for the indefatigable sound encoding by IHCs. Using a deaf mouse model lacking both CaBP1 and CaBP2, the authors convincingly demonstrate that both CaBP1 and CaBP2 together confer a lack of inactivation, with CaBP2 being far more effective. This is surprising given the mild phenotype of the single knockouts, which has been published by the authors before. Re-admission of CaBP2 through viral gene transfer into the inner ear of double-knockout mice largely restored hearing function, normal Ca2+ current properties, and exocytosis.

Comments on the revised version:

The authors improved the quality of the figures as requested.

Reviewer #1 (Public Review):

Summary:

In this work, Wang and colleagues used Drosophila-Serratia as a host-microbe model to investigate the impact of the host on gut bacteria. The authors showed that Drosophila larvae reduce S. marcescens abundance in the food likely due to a combination of mechanical force and secretion of antimicrobial peptides. S. marcescens exposed to Drosophila larvae lost virulence to flies and could promote larval growth similar to typical Drosophila gut commensals. These phenotypic changes were reflected in the transcriptome and metabolome of bacteria, suggesting that the host could drive the switch from pathogenicity to commensalism in bacteria. Further, the authors used single-cell bacterial RNA-seq to demonstrate the heterogeneity in gut bacterial populations.

Strengths:

This is a valuable work that addresses an important question of the impact of the host on its gut microbes. The authors could convincingly demonstrate that gut bacteria are strongly affected by the host with important consequences for both interacting partners. Moreover, the authors used state-of-the-art bacterial single-cell RNA-seq to reveal heterogeneity in host-associated commensal populations.

Overall most parts of the study are solid and clear.

Reviewer #3 (Public Review):

In this study, Wang and coworkers established a model of Drosophila-S. marcescens interactions and thoroughly examined host-microbe bidirectional interactions. They found that:

(1) Drosophila larvae directly impact microbial aggregation and density;<br /> (2) Drosophila larvae affect microbial metabolism and cell wall morphology, as evidenced by reduced prodigiosin production and EPS production, respectively;<br /> (3) Drosophila larvae attenuate microbial virulence;<br /> (4) Drosophila larvae modulate the global transcription of microbes for adaptation to the host;<br /> (5) Microbial single-cell RNA sequencing (scRNA-seq) analysis revealed heterogeneity in microbial pathogenicity and growth;<br /> (6) AMPs are key factors controlling microbial virulence phenotypes.

Taken together, they concluded that host immune factors such as AMPs are directly involved in the pathogen-to-commensal transition by altering microbial transcription.

In general, in this revised version, I feel that the authors addressed all the points raised in the previous review process. Specifically, they demonstrated that sub-lethal doses of antibiotics such as kanamycin or ampicillin is sufficient to induce the virulence switch in S. marcescens. Furthermore, by testing IMD pathway mutant animals, they concluded that AMP plays a major role in the commensal-to-pathogen transition. In summary, I appreciate the authors' efforts, and I am satisfied with the revision.

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 #2 (Public Review):

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.

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):

This study introduces an innovative method for assessing the mean kurtosis, utilizing the mathematical foundation of the sub-diffusion framework. In particular, a new fitting technique that incorporates two different diffusion times is proposed to estimate the parameters of the sub-diffusion model. The evaluation of this technique, which generates kurtosis maps based on the sub-diffusion framework, is conducted through simulations and the examination of data obtained from human subjects.

The authors have revised the manuscript to address the initial critiques. However, there appears to be some confusion regarding the following responses.

"The comment "... using the new sub-diffusion model -an approximation of the DKI-based signal expression..." is a bit misleading. In fact we propose that the reverse interpretation is the more suitable way to view the relationship: the DKI model is a degree-2 approximation of the sub-diffusion model, as in eq. (7).<br /> We appreciate the suggestion. However, unfortunately, it is not appropriate to generate data with the DKI model, as the maximum b-value is limited to 2000~3000s/mm^2 and hence the DKI model cannot represent diffusion MRI signals from a full spectrum of b-values. A key strength of our proposed model is that it removes this limitation. "

The main motivation of this study is to investigate the feasibility of the sub-diffusion model, which was proposed in Yang et al., NeuroImage 2022, to provide fast and robust estimation of kurtosis model parameters. I understand that mathematically, the DKI model can be written as a degree two approximation of the sub-diffusion model. However, the hypothesis is that the proposed sub-diffusion model can be used to obtain practically useful mapping of mean kurtosis. Therefore, unless the authors use a different parameter or phenomenon as the "true" or "ground-truth kurtosis," this study examines whether the sub-diffusion model parameters can serve as an approximation to the conventional DKI parameters.

With the current simulation study design, 1) the data is generated by the proposed sub-diffusion model, 2) the "ground-truth" or "true" D* and K* are computed based on the proposed equality (Eq.7); 3) and then the data is fit with the conventional DKI model and also with the proposed sub-diffusion model. Since the data is generated by the proposed model, and the ground truth (or true) values calculated by the proposed equality, as expected, the fitted kurtosis values by the sub-diffusion model match better with the simulated ones compared to the conventional DKI model.

Furthermore, as the authors noted, the sub-diffusion model eliminates the restriction on b-value selection, allowing for DWI data acquisition with higher b-values. However, it is unclear how the new K* and D* values, calculated directly from the sub-diffusion model using a higher b-value DWI protocol, are superior to the K and D values from the conventional DKI model, which uses a DWI protocol limited to b-values of 2000-3000 s/mm². In clinical practice, b-values of 2000-3000 s/mm² are generally considered "high b-value."

Reviewer #2 (Public Review):

Summary:

The authors present an interesting technique for analysis of diffusion magnetic resonance images (dMRI) using a sub-diffusion model of the diffusion process. They show that the results of their technique when fitted to dMRI with two diffusion times provide robust diffusion coefficient and kurtosis measures.

Strengths:

The measures provided by the sub-diffusion technique are robust and can be reliably estimated from short dMRI data acquisitions. This is potentially useful in application to clinical studies.

Weaknesses:

The authors do not fully demonstrate that their D* and K* measures are not affected by diffusion time. Potential limitations of the technique are not considered.

This reviewer suggests that the paper would benefit from considerations of the limitations of the applied techniques. This would include consideration of:<br /> (i) The use of the sub-diffusion model in the simulation studies - there are circular arguments that should be considered.<br /> (ii) The time dependence of D* and K*. This is because the human data provided in Tables 3 and 4 (for Δ=19ms and Δ=49ms) seem to show that<br /> D* and K* are time dependent.

With respect to the second point this reviewer acknowledges the authors' argument that when the fitting is performed over the higher dimensional space that includes multiple diffusion times then this leads to a more robust estimation of sub-diffusion measures. However, the authors only include two diffusion times in their in-vivo human analysis (Δ=19ms and Δ=49ms) so it is not possible for them to show here that different pairs of diffusion times lead to invariant D* and K* values. This is a limitation of the study as the authors show there is time dependence of D* and K* in tables 3 and 4 (when the model is fitted to single diffusion times). Potentially the larger apparent time dependence of K* in white matter compared to grey matter (tables 3 and 4) could lead to the tissue specific differences in root mean squared error shown in Figure 7.

This reviewer requests that the authors discuss their results more clearly with respect to these potential limitations and include some discussion of their single (and multiple) diffusion time results (for D_SUB and K*) in comparison with the time dependent DKI literature.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript entitled A Modified BPaL Regimen for Tuberculosis Treatment<br /> replaces Linezolid with Inhaled Spectinamides by Malik Zohaib Ali et al. is an extension of previous studies by this group looking at the new drug spectinamide 1599. The authors directly compare therapy with BPaL (bedaquiline, pretomanid, linezolid) to a therapy that substitutes spectinamide for linezolid (BPaS). The Spectinamide is given by aerosol exposure and the BPaS therapy is shown to be as effective as BPaL without adverse effects. The work is rigorously performed and analyses of the immune responses are consistent with curative therapy.

Strengths:<br /> 1) This group uses 2 different mouse models to show the effectiveness of the BPaS treatment.<br /> 2)Impressively the group demonstrates immunological correlates associated with Mtb cure with the BPaS therapy.<br /> 3)Linezolid is known to inhibit ribsomes and mitochondria whereas spectinaminde does not. The authors clearly demonstrate the lack of adverse effects of BPaS compared to BPaL.

Weaknesses:<br /> 1) Although this is not a weakness of this paper, a sentence describing how the spectinamide would be administered by aerosolization in humans would be welcomed.

Reviewer #2 (Public Review):

Summary:<br /> Replacing linezolid (L) with the preclinical development candidate spectinamide 1599, administered by inhalation, in the BPaL standard of care regimen achieves similar efficacy, reduces hematological changes and por-inflammatory responses.

Strengths:<br /> The authors not only measure efficacy but also quantify histological changes, hematological responses and immune responses, to provide a comprehensive picture of treatment response and the benefits of the L to S substitution.

The authors generate all data in two mouse models of TB infection, each reproducing different aspects of human histopathology.

Extensive supplementary figures ensure transparency.

Weaknesses:<br /> Articulation of objectives and hypotheses can be improved, as suggested below.

Reviewer #3 (Public Review):

Summary:<br /> In this paper, the authors sought to evaluate whether the novel TB drug candidate, spectinamide 1599 (S), given via inhalation to mouse TB models, and combined with the drugs B (bedaquiline) and Pa (pretomanid), would demonstrate similar efficacy to that of BPaL regimen (where L is linezolid). Because L is associated with adverse events when given to patients longterm, and one of those is associated with myelosuppression (bone marrow toxicity) the authors also sought to assess blood parameters, effects on bone marrow, immune parameters/cell effects following treatment of mice with BPaS and BPaL. They conclude that BPaL and BPaS have equivalent efficacy in both TB models used and that BPaL resulted in weight loss and anemia (whereas BPaS did not) under the conditions tested, as well as effects on bone marrow.

Strengths:<br /> The authors used two mouse models of TB that are representative of different aspects of TB in patients (which they describe well), intending to present a fuller picture of the activity of the tested drug combinations. They conducted a large body of work in these infected mice to evaluate efficacy and also to survey a wide range of parameters that could inform the effect of the treatments on bone marrow and on the immune system. The inclusion of BPa controls (in most studies) and also untreated groups led to a large amount of useful data that has been collected for the mouse models per se (untreated) as well as for BPa - in addition to the BPaS and BPaL combinations which are of particular interest to the authors. Many of these findings related to BPa, BPaL, untreated groups etc corroborate earlier findings and the authors point this out effectively and clearly in their manuscript. To go further, in general, it is a well written and cited article with an informative introduction.

Weaknesses:<br /> The authors performed a large amount of work with the drugs given at the doses and dosing intervals stated, but there is no exposure data available at this time. The authors intend to evaluate exposure-effect relationships in future work. An understanding of the exposures at which the efficacy and adverse effects are seen will assist in the translation of these findings to the clinic.<br /> In addition, it is always challenging to interpret findings for combinations of drugs and for now, the data available cannot attribute confidence to the weight loss seen for only the BPaL group to L specifically, as opposed to a PK interaction leading to an elevated exposure and weight loss due to B or Pa. It is not yet possible, then to state that what is seen are "L-associated AEs" - this is assumed only.<br /> The evaluations of activity in the BALB/c mouse model as well as the spleens of the Kramnik model resulted in CFU below/at the limit of detection so comparisons between BPaL and BPaS cannot be made and so the conclusion of equivalent efficacy in BALB/c is not supported with the data shown. There is no BPa control in the BALB/c study, therefore it is not possible to discern whether L or S contributed to the activity of BPaL or BPaS. The same is true for the assessment of lesions - unfortunately, there was no BPa control meaning that even where equivalency is seen for BPaL and BPaS, the reader is unable to deduce whether L or S made a contribution to this activity.<br /> Although these weaknesses limit what we can learn from the current body of data, the authors note that further studies will be done to increase understanding of the points above.

Reviewer #3 (Public Review):

Summary:

ImmCellTyper is a new toolkit for Cytometry by time-of-flight data analysis. It includes BinaryClust, a semi-supervised clustering tool (which takes into account the prior biological knowledge), designed for automated classification and annotation of specific cell types and subpopulations. ImmCellTyper also integrates a variety of tools to perform data quality analysis, batch effect correction, dimension reduction, unsupervised clustering, and differential analysis.

Strengths:

The proposed algorithm takes into account the prior knowledge.<br /> The results on different benchmark indicates competitive or better performance (in terms of accuracy and speed) depending on the method.

Reviewer #1 (Public Review):

Summary:

Insects inhabit diverse environments and have neuroanatomical structures appropriate to each habitat. Although the molecular mechanism of insect neural development has been mainly studied in Drosophila, the beetle, Tribolium castaneum has been introduced as another model to understand the differences and similarities in the process of insect neural development. In this manuscript, the authors focused on the origin of the central complex. In Drosophila, type II neuroblasts have been known as the origin of the central complex. Then, the authors tried to identify those cells in the beetle brain. They established a Tribolium fez enhancer trap line to visualize putative type II neuroblasts and successfully identified 9 of those cells. In addition, they also examined expression patterns of several genes that are known to be expressed in the type II neuroblasts or their lineage in Drosophila. They concluded that the putative type II neuroblasts they identified were type II neuroblasts because those cells showed characteristics of type II neuroblasts in terms of genetic codes, cell diameter, and cell lineage.

Strengths:

The authors established a useful enhancer trap line to visualize type II neuroblasts in Tribolium embryos. Using this tool, they have identified that there are 9 type II neuroblasts in the brain hemisphere during embryonic development. Since the enhancer trap line also visualized the lineage of those cells, the authors found that the lineage size of the type II neuroblasts in the beetle is larger than that in the fly. They also showed that several genetic markers are also expressed in the type II neuroblasts and their lineages as observed in Drosophila.

Weaknesses:

I recommend the authors reconstruct the manuscript because several parts of the present version are not logical. For example, the author should first examine the expression of dpn, a well-known marker of neuroblast. Without examining the expression of at least one neuroblast marker, no one can say confidently that it is a neuroblast. The purpose of this study is to understand what makes neuroanatomical differences between insects which is appropriate to their habitats. To obtain clues to the question, I think, functional analyses are necessary as well as descriptive analyses.

Reviewer #2 (Public Review):

The authors address the question of differences in the development of the central complex (Cx), a brain structure mainly controlling spatial orientation and locomotion in insects, which can be traced back to the neuroblast lineages that produce the Cx structure. The lineages are called type-II neuroblast (NB) lineages and are assumed to be conserved in insects. While Tribolium castaneum produces a functional larval Cx that only consists of one part of the adult Cx structure, the fan-shaped body, in Drosophila melanogaster a non-functional neuropile primordium is formed by neurons produced by the embryonic type-II NBs which then enter a dormant state and continue development in late larval and pupal stages.

The authors present a meticulous study demonstrating that type-II neuroblast (NB) lineages are indeed present in the developing brain of Tribolium castaneum. In contrast to type-I NB lineages, type-II NBs produce additional intermediate progenitors. The authors generate a fluorescent enhancer trap line called fez/earmuff which prominently labels the mushroom bodies but also the intermediate progenitors (INPs) of the type-II NB lineages. This is convincingly demonstrated by high-resolution images that show cellular staining next to large pointed labelled cells, a marker for type-II NBs in Drosophila melanogaster. Using these and other markers (e.g. deadpan, asense), the authors show that the cell type composition and embryonic development of the type-II NB lineages are similar to their counterparts in Drosophila melanogaster. Furthermore, the expression of the Drosophila type-II NB lineage markers six3 and six4 in subsets of the Tribolium type-II NB lineages (anterior 1-4 and 1-6 type-II NB lineages) and the expression of the Cx marker skh in the distal part of most of the lineages provide further evidence that the identified NB lineages are equivalent to the Drosophila lineages that establish the central complex. However, in contrast to Drosophila, there are 9 instead of 8 embryonic type-II NB lineages per brain hemisphere and the lineages contain more progenitor cells compared to the Drosophila lineages. The authors argue that the higher number of dividing progenitor cells supports the earlier development of a functional Cx in Tribolium.

While the manuscript clearly shows that type-II NB lineages similar to Drosophila exist in Tribolium, it does not considerably advance our understanding of the heterochronic development of the Cx in these insects. First of all, the contribution of these lineages to a functional larval Cx is not clear. For example, how do the described type-II NB lineages relate to the DM1-4 lineages that produce the columnar neurons of the Cx? What is the evidence that the embryonically produced type-II NB lineage neurons contribute to a functional larval Cx? The formation of functional circuits could rely on larval neurons (like in Drosophila) which would make a comparison of embryonic lineages less informative with respect to understanding the underlying variations of the developmental processes. Furthermore, the higher number of progenitors (and consequently neurons) in Tribolium could simply reflect the demand for a higher number of cells required to build the fan-shaped body compared to Drosophila. In addition, the larger lineages in Tribolium, including the higher number of INPs could be due to a greater number of NBs within the individual clusters, rather than a higher rate of proliferation of individual neuroblasts, as suggested. What is the evidence that there is only one NB per cluster? The presented schemes (Fig. 7/12) and description of the marker gene expression and classification of progenitor cells are inconsistent but indicate that NBs and immature INPs cannot be consistently distinguished.

The main difference between Tribolium and Drosophila Cx development with regard to the larval functionality might be that Drosophila type-II NB lineage-derived neurons undergo quiescence at the end of embryogenesis so that the development of the Cx is halted, while a developmental arrest does not occur in Tribolium. However, this needs to be confirmed (as the authors rightly observe).

Reviewer #3 (Public Review):

Summary:

In this paper, Rethemeier et al capitalize on their previous observation that the beetle central complex develops heterochronically compared to the fly and try to identify the developmental origin of this difference. For this reason, they use a fez enhancer trap line that they generated to study the neuronal stem cells (INPs) that give rise to the central complex. Using this line and staining against Drosophila type-II neuroblast markers, they elegantly dissect the number of developmental progression of the beetle type II neuroblasts. They show that the NBs, INPs, and GMCs have a conserved marker progression by comparing to Drosophila marker genes, although the expression of some of the lineage markers (otd, six3, and six4) is slightly different. Finally, they show that the beetle type II neuroblast lineages are likely longer than the equivalent ones in Drosophila and argue that this might be the underlying reason for the observed heterochrony.

Strengths:

- A very interesting study system that compares a conserved structure that, however, develops in a heterochronic manner.

- Identification of a conserved molecular signature of type-II neuroblasts between beetles and flies. At the same time, identification of transcription factors expression differences in the neuroblasts, as well as identification of an extra neuroblast.

- Nice detailed experiments to describe the expression of conserved and divergent marker genes, including some lineaging looking into the co-expression of progenitor (fez) and neuronal (skh) markers.

Weaknesses:

- Comparing between different species is difficult as one doesn't know what the equivalent developmental stages are. How do the authors know when to compare the sizes of the lineages between Drosophila and Tribolium? Moreover, the fact that the authors recover more INPs and GMCs could also mean that the progenitors divide more slowly and, therefore, there is an accumulation of progenitors who have not undergone their programmed number of divisions.

- The main conclusion that the earlier central complex development in beetles is due to the enhanced activity of the neuroblasts is very handwavy and is not the only possible conclusion from their data.

- The argument for conserved patterns of gene expression between Tribolium and Drosophila type-II NBs, INPs, and GMCs is a bit circular, as the authors use Drosophila markers to identify the Tribolium cells.

An appraisal of whether the authors achieved their aims, and whether the results support their conclusions: Based on the above, I believe that the authors, despite advancing significantly, fall short of identifying the reasons for the divergent timing of central complex development between beetle and fly.

Reviewer #1 (Public Review):

Summary:

Hahn et al use bystander BRET, NanoBiT assays, and APEX2 proteomics to investigate endosomal signaling of CCR7 by two agonists, CCL19 and CCL21. The authors suggest that CCR7 signals from early endosomes following internalisation. They use spatial proteomics to try to identify novel interacting partners that may facilitate this signaling and use this data to specifically enhance a Rac1 signaling pathway. Many of the results in the first few figures showing simultaneous recruitment of Barr and G proteins by CCR7 have been shown previously (Laufer et al, 2019, Cell Reports), as has signaling from endomembranes, and Rac1 activation at intracellular sites. The new findings are the APEX2 proteomics studies, which could be useful to the scientific community. Unfortunately, the authors only follow up on a single finding, and the expansion of this section would improve the manuscript.

Strengths:

(1) The APEX2 resource will be valuable to the GPCR and immunology community. It offers many opportunities to follow up on findings and discover new biology. The resource could also be used to validate earlier findings in the current manuscript and in previous manuscripts. Was there enrichment of early endosomal markers, Barr and Gi as this would provide further evidence for their earlier claims regarding endosomal signaling? Previous studies have suggested signaling from the TGN, so it is possible that the different ligands also direct to different sites. This could easily be investigated using the APEX2 data.

(2) The results section is well written and can be followed very easily by the reader.

(3) Some findings verify previous studies (e.g. endomembrane signalling). This should be acknowledged as this shows the validity of the findings of both studies.

Weaknesses:

(1) The findings are interesting although the studies are almost all performed in HEK293 cells. I understand that these are commonly used in GPCR biology and are easy to transfect and don't express many GPCRs at high concentrations, but their use is still odd when there are many cell-lines available that express CCR7 and are more reflective of the endogenous state (e.g. they are polarised, they can perform chemotaxis/ migration). Some of the findings within the study should also be verified in more physiologically relevant cells. At the moment only the final figure looks at this, but findings need to be verified elsewhere.

(2) The authors acknowledge that the kinetic patterns of the signals at the early endosome are not consistent with the rates of internalisation. They mention that this could be due to trafficking elsewhere. This could be easily looked at in their APEX2 data. Is there evidence of proximity to markers of other membranes? Perhaps this could be added to the discussion. Similarly, previous studies have shown that CCR7 signaling may involve the TGN. Was there enrichment of these markers? If not, this could also be an interesting finding and should be discussed. It is also possible that the Rab5 reporter is just not as efficient as the trafficking one, especially as in later figures the very convincing differences in the two ligands are not as robust as the differences in trafficking.

(3) In the final sentence of paragraph 2 of the results the authors state that the internalisation is specific to CCR7 as there isn't recruitment to V2R. I'm not sure this is the best control. The authors can only really say it doesn't recruit to unrelated receptors. The authors could have used a different chemokine receptor which does not respond to these ligands to show this.

(4) The miniGi-Barr1 and imaging showing co-localisation could be more convincing if it was also repeated in a more physiological cell line as in the final figure. Imaging of CCR7, miniGi, and Barr1 would also provide further evidence that the receptor is also present within the complex.

(5) The findings regarding Rac1 are interesting, although an earlier paper found similar results (Laufer et al, 2019, Cell Reports), so perhaps following up on another APEX2-identified protein pathway would have been more interesting. The authors' statement that Rac1 is specifically activated, and RhoA and Cdc42 are not, is unconvincing from the current data. Only a single NanoBiT assay was used, and as raw values are not reported it is difficult for the reader to glean some essential information. The authors should show evidence that these reporters work well for other receptors (or cite previous studies) and also need evidence from an independent (i.e. non-NanoBiT or BRET) assay.

(6) At present, the studies in Figure 7 do not go beyond those in the previous Laufer et al study in which they showed blocking endocytosis affected Rac1 signalling. The authors could show that Rac1 signalling is from early endosomes to improve this, otherwise, it could be from the TGN as previously reported.

Reviewer #2 (Public Review):

Summary:

This manuscript describes a comprehensive analysis of signalling downstream of the chemokine receptor CCR7. A comprehensive dataset supports the authors' hypothesis that G protein and beta-arrestin signalling can occur simultaneously at CCR7 with implications for continued signalling following receptor endocytosis.

Strengths:

The experiments are well controlled and executed, employing a wide range of assays using - in the main - CCR7 transfectants. Data are well presented, with the authors' claims supported by the data. The paper also has an excellent narrative which makes it relatively easy to follow. I think this would certainly be of interest to the readership of the journal.

Weaknesses:

Since the authors show a differential enrichment of RhoGTPases by CCR7 stimulation with CCL19 versus CCL21, I think that they also need to show that the Gi/o coupling of HEK-292-CCR7-APEX2 cells to both CCL19 and CCL21 is not perturbed by the modification. Currently, the authors only show data for CCL19 signalling, which leaves the potential for a false negative finding in terms of CCL21 signalling being selectively impaired. This should be relatively easy to do and should strengthen the authors' conclusions.

The authors conclude the discussion by suggesting that their findings highlight endosomal signalling as a general mechanism for chemokine receptors in cell migration. I think this is an overreach. The authors chose several studies of CXC chemokine receptors to support their argument that C-terminal truncation or mutation of the C-terminal phosphorylation sites impairs endocytosis and chemotaxis (refs 40-42). However, in some instances e.g. at the related chemokine receptor CCR4, C-terminal removal of these sites impairs endocytosis but promotes chemotaxis (Nakagawa et al, 2014); Anderson et al, 2020). I therefore think that either the final statement needs to be tempered down or the counterargument discussed a little.

References:

Anderson, C. A. et al. A degradatory fate for CCR4 suggests a primary role in Th2 inflammation. J Leukocyte Biol 107, 455-466 (2020).

Nakagawa, M. et al. Gain-of-function CCR4 mutations in adult T cell leukaemia/lymphoma. Journal of Experimental Medicine 211, 2497-2505 (2014).

Reviewer #1 (Public Review):

Summary:

In this study, Nandy and colleagues examine neural, physiological and behavioral correlates of perceptual variability in monkeys performing a visual change detection task. They used a laminar probe to record from area V4 while two macaque monkeys detected a small change in stimulus orientation that occurred at a random time in one of two locations, focusing their analysis on stimulus conditions where the animal was equally likely to detect (hit) or not-detect (miss) a briefly presented orientation change (target). They discovered two behavioral and physiological measures that are significantly different between hit and miss trials - pupil size tends to be slightly larger on hits vs. misses, and monkeys are more likely to miss the target on trials in which they made a microsaccade shortly before target onset. They also examined multiple measures of neural activity across the cortical layers and found some measures that are significantly different between hits and misses.

Strengths:

Overall the study is well executed and the analyses are appropriate (though several issues still need to be addressed as discussed in Specific Comments).

Weaknesses:

My main concern with this study is that, with the exception of the pre-target microsaccades, the correlates of perceptual variability (differences between hits and misses) appear to be weak, potentially unreliable and disconnected. The GLM analysis of predictive power of trial outcome based on the behavioral and neural measures is only discussed at the end of the paper. This analysis shows that some of the measures have no significant predictive power, while others cannot be examined using the GLM analysis because these measures cannot be estimated in single trials. Given these weak and disconnected effects, my overall sense is that the current results provide limited advance to our understanding of the neural basis of perceptual variability.

Reviewer #2 (Public Review):

Strengths:

The experiments were well-designed and executed with meticulous control. The analyses of both behavioural and electrophysiological data align with the standards in the field.

Weaknesses:

Many of the findings appear to be subtle differences and incremental compared to previous literature, including the authors' own work. While incremental findings are not necessarily a problem, the manuscript lacks clear statements about the extent to which the dataset, analysis, and findings overlap with the authors' prior research. For example, one of the main findings, which suggests that V4 neurons exhibit larger visual responses in hit trials (as shown in Fig. 3), appears to have been previously reported in their 2017 paper.

Furthermore, the manuscript does not explore potentially interesting aspects of the dataset. For instance, the authors could have investigated instances where monkeys made 'false' reports, such as executing saccades towards visual stimuli when no orientation change occurred, which allows for a broader analysis that considers the perceptual component of neural activity over pure sensory responses. Overall, lacking broad interest with the current form.

Reviewer #1 (Public Review):

The authors investigate the role of chirping in a species of weakly electric fish. They subject the fish to various scenarios and correlate the production of chirps with many different factors. They find major correlations between the background beat signals (continuously present during any social interactions) or some aspects of social and environmental conditions with the propensity to produce different types of chirps. By analyzing more specifically different aspects of these correlations they conclude that chirping patterns are related to navigation purposes and the need to localize the source of the beat signal (i.e. the location of the conspecific).

The study provides a wealth of interesting observations of behavior and much of this data constitutes a useful dataset to document the patterns of social interactions in these fish. Some data, in particular the high propensity to chirp in cluttered environments, raises interesting questions. Their main hypothesis is a useful addition to the debate on the function of these chirps and is worth being considered and explored further.

After the initial reviewers' comments, the authors performed a welcome revision of the way the results are presented. Overall the study has been improved by the revision. However, one piece of new data is perplexing to me. The new figure 7 presents the results of a model analysis of the strength of the EI caused by a second fish to localize when the focal fish is chirping. From my understanding of this type of model, EOD frequency is not a parameter in the model since it evaluates the strength of the field at a given point in time. Therefore the only thing that matters is the phase relationship and strength of the EOD. Assuming that the second fish's EOD is kept constant and the phase relationship is also the same, the only difference during a chirp that could affect the result of the calculation is the potential decrease in EOD amplitude during the chirp. It is indeed logical that if the focal fish decreased its EOD amplitude the target fish's EOD becomes relatively stronger. Where things are harder to understand is why the different types of chirps (e.g. type 1 vs type 2) lead to the same increase in signal even though they are typically associated with different levels of amplitude modulations. Also, it is hard to imagine that a type 2 chirp that is barely associated with any decrease in EOD amplitude (0-10% maybe), would cause a doubling of the EI strength. There might be something I don't understand but the authors should provide a lot more details on how this result is obtained and convince us that it makes sense.

Finally, the reviewer is concerned about this sentence in the rebuttal - "The methods section has been edited to clarify the approach (not yet)". This section is unfinished, which suggests that it is difficult to explain the modeling results from a logical point of view. Thus the reviewer's major concern from the previous review remains unresolved. To summarize, the model calculates field strengths at an instant in time and integrates over time with a 500 ms window. This window is 10 times longer than the small chirps, while the longer chirps cover a much larger proportion of the window. Yet, the small chirps have a bigger impact on discriminability than the longer chirps. The authors should attempt to explain this seemingly contradictory result. This remains a major issue because this analysis was the most direct evidence that chirping could impact localization accuracy.

Reviewer #2 (Public Review):

Studying Apteronotus leptorhynchus (the weakly electric brown ghost knifefish), the authors provide evidence that 'chirps' (brief modulations in the frequency and amplitude of the ongoing wave-like electric signal) function in active sensing (specifically homeoactive sensing) rather than communication. Chirping is a behavior that has been well studied, including numerous studies on the sensory coding of chirps and the neural mechanisms for chirp generation. Chirps are largely thought to function in communication behavior, so this alternative function is a very exciting possibility that should have a great impact on the field.

The authors provide convincing evidence that chirps may function in homeoactive sensing. In particular, the evidence showing increased chirping in more cluttered environments and a relationship between chirping and movement are especially strong and suggestive. Their evidence arguing against a role for chirps in communication is not as strong. However, based on an extensive review of the literature, the authors conclude, I think fairly, that the evidence arguing in favor of a communication function is limited and inconclusive. Thus, the real strength of this study is not that it conclusively refutes the communication hypothesis, but that it calls this hypothesis into question while also providing compelling evidence in favor of an alternative function.

In summary, although the evidence against a role for chirps in communication is not as strong as the evidence for a role in active sensing, this study presents very interesting data that is sure to stimulate discussion and follow-up studies. The authors acknowledge that chirps could function as both a communication and homeactive sensing signal, and the language arguing against a communication function is appropriately measured. A given electrical behavior could serve both communication and homeoactive sensing. I suspect this is quite common in electric fish (not just in gymnotiforms such as the species studied here, but also in the distantly related mormyrids), and perhaps in other actively sensing species such as echolocating animals.

Reviewer #3 (Public Review):

Summary:<br /> This important paper provides the best-to-date characterization of chirping in weakly electric fish using a large number of variables. These include environment (free vs divided fish, with or without clutter), breeding state, gender, intruder vs resident, social status, locomotion state and social and environmental experience, without and with playback experiments. It applies state-of-the-art methods for reducing the dimensionality of the data and finding patterns of correlation between different kinds of variables (factor analysis, K-means). The strength of the evidence, collated from a large number of trials with many controls, leads to the conclusion that the traditionally assumed communication function of chirps may be secondary to its role in environmental assessment and exploration that takes social context into account. Based on their extensive analyses, the authors suggest that chirps are mainly used as probes that help detect beats caused by other fish as well as objects.

Strengths:<br /> The work is based on completely novel recordings using interaction chambers. The amount of new data and associated analyses is simply staggering, and yet, well organized in presentation. The study further evaluates the electric field strength around a fish (via modelling with the boundary element method) and how its decay parallels the chirp rate, thereby relating the above variables to electric field geometry. The BEM modelling also convincingly predicts how the electric image of a receiver conspecific on a sending fish is enhanced by a chirp.

The main conclusions are that the lack of any significant behavioural correlates for chirping, and the lack of temporal patterning in chirp time series, cast doubt on a primary communication goal for most chirps. Rather, the key determinants of chirping are the difference in frequency between two interacting conspecifics as well as individual subjects' environmental and social experience. The paper concludes that there is a lack of evidence for stereotyped temporal patterning of chirp time series, as well as of sender-receiver chirp transitions beyond the known increase in chirp frequency during an interaction. The authors carefully submit that the new putative echolocation function of chirps is not mutually exclusive with a possible communication function.

These conclusions by themselves will be very useful to the field. They will also allow scientists working on other "communication" systems to perhaps reconsider and expand the goals of the probes used in those senses. A lot of data are summarized in this paper, with thorough referencing to past work.

The alternative hypotheses that arise from the work are that chirps are mainly used as environmental probes for better beat detection and processing and object localization, and in this sense are self-directed signals. This led to their prediction that environmental complexity ("clutter") should increase chirp rate, which is fact was revealed by their new experiments. The authors also argue that waveform EODs have less power across high spatial frequencies compared to pulse-type fish, with a resulting relatively impoverished power of resolution. Chirping in wave-type fish could temporarily compensate for the lower frequency resolution while still being able to resolve EOD perturbations with a good temporal definition (which pulse-type fish lack due to low pulse rates).

The authors also advance the interesting idea that the sinusoidal frequency modulations caused by chirps are the electric fish's solution to the minute (and undetectable by neural wetware) echo-delays available to it, due to the propagation of electric fields at the speed of light in water. The paper provides a number of experimental avenues to pursue in order to validate the non-communication role of chirps.

Reviewer #1 (Public Review):

The present study provides a phylogenetic analysis of the size prefrontal areas in primates, aiming to investigate whether relative size of the rostral prefrontal cortex (frontal pole) and dorsolateral prefrontal cortex volume vary according to known ecological or social variables.

I am very much in favor of the general approach taken in this study. Neuroimaging now allows us to obtain more detailed anatomical data in a much larger range of species than ever before and this study shows the questions that can be asked using these types of data. In general, the study is conducted with care, focusing on anatomical precision in definition of the cortical areas and using appropriate statistical techniques, such as PGLS.

I have read the revised version of the manuscript with interest. I commend the authors for including the requested additional analyses. I believe these highlight some of the major debates in the field, such as the relationship between absolute and relative brain size of areas. Providing a full description of the data will help this field be more open about these issues. All too often, debates between different groups focus on narrow anatomical or statistical arguments, and having all the data here is important.

I do not agree with some of the statements of the other reviewers regarding development. Clearly, evolution works for a large part by tinkering (forgive the sense of agency) with development, but that does not mean that looking at the end result cannot provide insights. Ultimately, we will look at both phylogeny and ontogeny within the same framework, but the field is not quite there yet.

As I said before, I do believe this is a positive study. I am happy that we as a field are using imaging data to answer more wider phylogenetic questions. Combining detailed anatomy, big data, and phylogenetic statistical frameworks is an important approach.

Reviewer #1 (Public Review):

Summary:

This study further develops the potential of in vitro granulomas to study host-pathogen interactions in tuberculosis. It uses a human-based cellular model and a collection of M. tuberculosis isolates representative of the pathogen's diversity. It provides important methodologic information and some findings that help in defining protective responses in TB.

Strengths:

A strength of the study is the multitude of parameters addressed across different M. tuberculosis strains and donors. The inclusion of several strains of the same lineage shows that intra-lineage diversity is also relevant, illustrating how complex it is to model the immune response to M. tuberculosis.

Weaknesses:

A weakness of the study is that although several interesting findings are reported and a hypothesis proposed, the work is mainly descriptive and correlative. Some functional data based on the current observations would strengthen the findings.

Reviewer #2 (Public Review):

Summary:

This manuscript reports a comparison of microbial traits and host response traits in a laboratory model of infected granuloma using Mtb strains from different lineages. The authors report increased bacillary growth and granuloma formation, inversely associated with T cell activation that is characterized by CXCL9, granzyme B, and TNF expression. They therefore infer that these T cell responses are likely to be host-protective and that the greater virulence of modern Mtb lineages may be driven by their ability to avoid triggering these responses.

Strengths:

The comparison of multiple Mtb lineages in a granuloma model that enables evaluation of the potential role of multiple host cells in Mtb control offers a valuable experimental approach to studying the biological mechanisms that underpin differential virulence of Mtb lineages that have been previously reported in clinical and epidemiological studies.

Weaknesses:

The study is rather limited to descriptive observations and lacks experiments to test causal relationships between host and pathogen traits. Some of the presentation of the data is difficult to interpret, and some conclusions are not adequately supported by the data.

Reviewer #3 (Public Review):

Summary:

In "CXCL9, granzyme B, and TNF-α orchestrate protective in vitro granulomatous responses across Mycobacterium tuberculosis complex lineages", Arbués and colleagues describe the impact of mycobacterial genetic diversity on host-infection phenotypes. The authors evaluate Mtb infection and contextualize host responses, bacterial growth, and metabolic transitioning in vitro using their previously established model of blood-derived, primary human cells cultured on a collogen/fibronectin matrix. They seek to demonstrate the effectiveness of the model in determining mycobacterial strain-specific granuloma-dependent host-pathogen interactions.

Strengths and weaknesses:

Understanding the way mycobacterial genetic diversity impacts granuloma biology in tuberculosis is an important goal. One of this work's strengths is the use of primary human cells and two constituents of the pulmonary extracellular matrix to model Mtb infection. The authors and others have previously shown that Mtb-infected PBMC aggregates share important characteristics with early pulmonary TB granulomas (Arbues et al., Bio Protoc, 2020, PMID: 3659472; Guirado et al., mBio, 2015, PMID: 25691598; Kapoor et al., PloS One, 2013, PMID: 23308269). The use of multiple genetically distinct strains of Mtb defines this work and further bolsters its potential impact. However, the study is not comprehensive as lineages 6 and 7 are not tested. Experiments are primarily descriptive, and the methodologies are conventional. Correlative relationships are the manuscript's focus and functional validation is not conducted. Convoluted data presentation hampers the readers' ability to effectively evaluate many of the findings for significance. The effect sizes are generally small and most quantitative data are unitless. A further weakness of the study is a lack of any in vivo modeling.

Achievement of aims, and support for conclusions:

The main aim of this work is to extend an in vitro granuloma model to the study of a large collection of well-characterized, genetically diverse representatives of the mycobacterium tuberculosis complex (MTBC). I believe that they accomplish that aim. The work does investigate MTBC infection of aggregated PBMCs using three strains each of Mtb lineages 1-5 and H37Rv, which is not a trivial undertaking. The experimental aims are to show that MTBC genetic diversity impacts the growth and dormancy of granuloma-bound bacteria and, the host responses of granulomatous aggregation as well as macrophage apoptosis, lymphocyte activation, and soluble mediator release within granulomas. A lack of basic descriptive statistics for raw data makes it difficult to determine if benchmarks for most of the experimental aims have been reached. Although the methodologies employed should have been able to test most of these aims. The title's conclusion that CXCL9, granzyme B, and TNF orchestrate a protective granulomatous response is not tested and is not supported by the findings. Those molecules are not a focus of the work, their effects are not investigated effectively and their relationship to the granulomatous response is not determined. The authors' conclusions regarding their results are a mixed bag. Their conclusion that lineage impacts growth within granulomas is likely true and the data as presented reflect such a relationship. However, even without the basic descriptive statistics needed to evaluate the data supporting that claim, the methods employed for bacterial collection call into question whether all Mtb plated for CFU assay resided within granulomatous aggregates. Their conclusions regarding lineage's impact on dormancy are not supported, as their findings demonstrate that assays for dormancy identify replicating bacteria as being dormant. Their conclusion that strain diversity results in a spectrum of granulomatous responses in their model system is strongly supported by the results. Their conclusion that strain diversity impacts macrophage apoptosis is supported by the data but a relationship of apoptosis to the granulomatous response is not effectively evaluated. Their conclusion that lymphocyte activation is associated with reduced mycobacterial growth as an aspect of granulomas is well supported in the literature and a negative correlation between T cell activation and growth is supported by their results.

Impact on the field:

The authors contribute some valuable insights, particularly in Figure 3 and supplementary Figures 1 and 2, where data is more accessible to critique. Their identification of donor-dependent aggregation phenotypes by mycobacterial strain has the potential to enable future reverse-genetic screens for human and Mtb loci that contribute to granulomatous inflammation. Their model is a higher echelon relative to others in the field, but I don't believe that it possesses all of the necessary tissue and cellular components to effectively replicate the formation of granulomas in nature. The bulk of the data in its current form is not of high value to the community, but I think it has the potential to contribute additional novel insights if panels that display descriptive statistics are added to the figures.

Reviewer #1 (Public Review):

Summary:

The manuscript by Choi and co-authors presents "P3 editing", which leverages dual-component guide RNAs (gRNA) to induce protein-protein proximity. They explore three strategies for leveraging prime-editing gRNA (pegRNA) as a dimerization module to create a molecular proximity sensor that drives genome editing, splitting a pegRNA into two parts (sgRNA and petRNA), inserting self-splicing ribozymes within pegRNA, and dividing pegRNA at the crRNA junction. Among these, splitting at the crRNA junction proved the most promising, achieving significant editing efficiency. They further demonstrated the ability to control genome editing via protein-protein interactions and small molecule inducers by designing RNA-based systems that form active gRNA complexes. This approach was also adaptable to other genome editing methods like base editing and ADAR-based RNA editing.

Strengths:

The study demonstrates significant advancements in leveraging guide RNA (gRNA) as a dimerization module for genome editing, showcasing its high specificity and versatility. By investigating three distinct strategies-splitting pegRNA into sgRNA and petRNA, inserting self-splicing ribozymes within the pegRNA, and dividing the pegRNA at the repeat junction-the researchers present a comprehensive approach to achieving molecular proximity and reconstituting function. Among these methods, splitting the pegRNA at the repeat junction emerged as the most promising, achieving editing efficiencies up to 76% of the control, highlighting its potential for further development in CRISPR-Cas9 systems. Additionally, the study extends genome editing control by linking protein-protein interactions to RNA-mediated editing, using specific protein-RNA interaction pairs to regulate editing through engineered protein proximity. This innovative approach expands the toolkit for precision genome editing, demonstrating the feasibility of controlling genome editing with enhanced specificity and efficiency.

Weaknesses:

The initial experiments with splitting the pegRNA into sgRNA and petRNA showed low editing efficiency, less than 2%. Similarly, inserting self-splicing ribozymes within pegRNA was inefficient, achieving under 2% editing efficiency in all constructs tested, possibly hindered by the prime editing enzyme. The editing efficiency of the crRNA and petracrRNA split at the repeat junction varied, with the most promising configurations only reaching 76% of the control efficiency. The RNA-RNA duplex formation's inefficiency might be due to the lack of additional protein binding, leading to potential degradation outside the Cas9-gRNA complex. Extending the approach to control genome editing via protein-protein interactions introduced complexity, with a significant trade-off between efficiency and specificity, necessitating further optimization. The strategy combining RADARS and P3 editing to control genome editing with specific RNA expression events exhibited high background levels of non-specific editing, indicating the need for improved specificity and reduced leaky expression. Moreover, P3 editing efficiencies are exclusively quantified after transfecting DNA into HEK cells, a strategy that has resulted in past reproducibility concerns for other technologies. Overall, the various methods and combinations require further optimization to enhance efficiency and specificity, especially when integrating multiple synthetic modules.

Reviewer #2 (Public Review):

Choi et al. describe a new approach for enabling input-specific CRISPR-based genome editing in cultured cells. While CRISPR-Cas9 is a broadly applied system across all of biology, one limitation is the difficulty in inducing genome editing based on cellular events. A prior study, from the same group, developed ENGRAM - which relies on activity-dependent transcription of a prime editing guide RNA, which records a specific cellular event as a given edit in a target DNA "tape". However, this approach is limited to the detection of induced transcription and does not enable the detection of broader molecular events including protein-protein interactions or exposure to small molecules. As an alternative, this study envisioned engineering the reconstitution of a split prime editing guide RNA (pegRNA) in a protein-protein interaction (PPI)-dependent manner. This would enable location- and content-specific genome editing in a controlled setting.

The authors explored three different design possibilities for engineering a PPI-dependent split pegRNA. First, they tried splitting pegRNA into a functional sgRNA and corresponding prime editing transRNA, incorporating reverse-complementary dimerization sequences on each guide half. This approach, however, resulted in low editing efficiency across 7 different designs with various complementary annealing template lengths (<2% efficiency). They also tried inserting a self-splicing ribozyme within the pegRNA, which produces a functional pegRNA post-transcriptionally. The incorporation of a split-ribozyme, dependent on a PPI, could have been used to reconstitute the split pegRNA in an event-controlled manner. However again, only modest levels of editing were observed with the self-splicing ribozyme design (<2%). Finally, they tried splitting the pegRNA at the repeat:anti-repeat junction that was used to join the original dual-guide system comprised of a crRNA and tracrRNA, into a single-guide RNA. They incorporated the prime editing features into the tracrRNA half, to create petracrRNA. Dimerization was initially induced by different complementary RNA annealing sequences. Using this design, they were able to induce an editing efficiency of ~28% (compared to 37% efficiency using a positive control epegRNA guide).

Having identified a suitable split pegRNA system, they next sought to induce the reconstitution of the two halves in a PPI-dependent manner. They replaced the complementary RNA annealing sequences with two different RNA aptamers (MS2 and BoxB). MS2 detects the MCP protein, while BoxB detects the LambdaN protein. Close proximity between MCP and LambdaN would thus bring together the two split pegRNA halves, creating a functional pegRNA that would enable prime editing at a specific target site. They demonstrated that they could induce MCP-BoxB proximity by fusing them to different dimerizing protein partners: 1) constitutive epitope-nanobody/antibody pairs such as scFv/GCN4 or NbALFA/ALFA-Tag; 2) split-GFP; or 3) chemically-induced protein pairs such as FKBP/FRB or ABI/PYL. For all of these approaches, they could achieve between ~20-60% normalized editing efficiency (relative to positive control editing levels with epegRNA). Additional mutation of the linkers between the RNA and aptamers could increase editing efficiency but also increase non-specific background editing even in the absence of an induced PPI.

Additional applications of this overall strategy included incorporating the design with different DNA base editors, with the most promising examples shown with the base editors CBE4max and ABE8. It should be noted that these specific examples used a non-physiological LambdaN-MCP direct fusion protein as the "bait" that induced reconstitution of the two halves of the guideRNA, rather than relying on a true induced PPI. They also demonstrated that the recently reported RADARS strategy could be incorporated into their system. In this example, they used an ADAR-guide-RNA to drive the expression of a LambdaN-PCP fusion protein in the presence of a specific target RNA molecule, IL6. This induced LambdaN-PCP protein could then reconstitute the split peg-RNAs to drive prime editing. To enable this last application, they replaced the MS2 aptamer in their pegRNA with the PP7 aptamer that binds the PCP protein (this was to avoid crosstalk with RADARS, which also uses MS2/MCP interaction). Using this strategy, they observed a normalized editing efficiency of around 12% (but observed non-specific editing of around 8% in the absence of the target RNA).

Strengths:

The strengths of this paper include an interesting concept for engineering guide RNAs to enable activity-dependent genome editing in living cells in the future, based on discreet protein-protein interactions (either constitutively, spatially, or chemically induced). Important groundwork is laid down to engineer and improve these guide RNAs in the future (especially the work describing altering the linkers in Supplementary Figure 3 - which provides a path forward).

Weaknesses:

In its current state, the editing efficiency appears too low to be applied in physiological settings. Much of the latter work in the paper relies on a LambdaN-MCP direction fusion protein, rather than two interacting protein pairs. Further characterizations in the future, especially varying the transfection amounts/durations/etc of the various components of the system, would be beneficial to improve the system. It will also be important to demonstrate editing at additional sites; to characterize how long the PPI must be active to enable efficient prime editing; and how reversible the reconstitution of the split pegRNA is.

Reviewer #1 (Public Review):

Summary:

The main conclusion of this manuscript is that the mediator kinases supporting the IFN response in Downs syndrome cell lines represent an important addition to understanding the pathology of this affliction.

Strengths:

Mediator kinase stimulates cytokine production. Both RNAseq and metabolomics clearly demonstrate a stimulatory role for CDK8/CDK19 in the IFN response. The nature of this role, direct vs. indirect, is inferred by previous studies demonstrating that inflammatory transcription factors are Cdk8/19 substrates. The cytokine and metabolic changes are clear-cut and provide a potential avenue to mitigate these associated pathologies.

Weaknesses:

This study revealed a previously undescribed role for the CKM in splicing. The previous identification of splicing factors as substrates of CDK8/CDK19 is also intriguing. However, additional studies seem to be necessary in order to attach this new function to the CKM. As the authors point out, the changes in splicing patterns are relatively modest compared to other regulators. In addition, some indication that the proteins encoded by these genes exhibit reduced levels or activities would support their RNAseq findings.

Seahorse analysis is normally calculated with specific units for oxygen consumption, ATP production, etc. It would be of interest to see the actual values of OCR between the D21 and T21 cell lines rather than standardizing the results. This will address the specific question about relative mitochondrial function between these cells. Reduced mitochondrial function has been associated with DS patients. Therefore, it would be important to know whether mitochondrial function is reduced in the T21 cells vs. the D21 control. Importantly for the authors' goal of investigating the use of CDK8/19 inhibitors in DS patients, does CA treatment reduce mitochondrial function to pathological levels?

Reviewer #2 (Public Review):

Summary:

In this manuscript, Cozzolino et al. demonstrate that inhibition of the Mediator kinase CDK8 and its paralog CDK19 suppresses hyperactive interferon (IFN) signaling in Down syndrome (DS), which results from trisomy of chromosome 21 (T21). Numerous pathologies associated with DS are considered direct consequences of chronic IFN pathway activation, and thus hyperactive IFN signaling lies at the heart of pathophysiology. The collective interrogation of transcriptomics, metabolomics, and cytokine screens in sibling-matched cell lines (T21 vs D21) allows the authors to conclude that Mediator kinase inhibition could mitigate chronic, hyperactive IFN signaling in T21. To probe the functional outcomes of Mediator kinase inhibition, the authors performed cytokine screens, transcriptomic, and untargeted metabolomics. This collective approach revealed that Mediator kinases establish IFN-dependent cytokine responses at least in part through transcriptional regulation of cytokine genes and receptors. Mediator kinase inhibition suppresses cell responses during hyperactive IFN signaling through inhibition of pro-inflammatory transcription factor activity (anti-inflammatory effect) and alteration of core metabolic pathways, including upregulation of anti-inflammatory lipid mediators, which served as ligands for specific nuclear receptors and downstream phenotypic outcomes (e.g., oxygen consumption). These data provided a mechanistic link between Mediator kinase activity and nuclear receptor function. Finally, the authors also disclosed that Mediator kinase inhibition alters splicing outcomes.

Overall, this study reveals a mechanism by which Mediator kinases regulate gene expression and establish that its inhibition antagonizes chronic IFN signaling through collective transcriptional, metabolic, and cytokine responses. The data have implications for DS and other chronic inflammatory conditions, as Mediator kinase inhibition could potentially mitigate pathological immune system hyperactivation.

Strengths:

(1) One major strength of this study is the mechanistic evidence linking Mediator kinases to hyperactive IFN signaling through transcriptional changes impacting cell signaling and metabolism.

(2) Another major strength of this study is the use of sibling-matched cell lines (T21 vs D21) from various donors (not just one sibling pair), and further cross-referencing with data from large cohorts, suggesting that part of the data and conclusions are generalizable.

(3) Another major strength of this study is the combined experimental approach including transcriptomics, untargeted metabolomics, and cytokine screens to define the mechanisms underlying suppression of hyperactive interferon signaling in DS upon Mediator kinase inhibition.

(4) Another major strength of this study is the significance of the work to DS and its potential impact on other chronic inflammatory conditions.

Weakness:

(1) Genetic evidence linking the mentioned nuclear receptors to activation of an anti-inflammatory program upon Mediator kinase inhibition could improve the definition of the mechanism and overall impact of the work.

(2) Page 5 states that "Mediator kinases broadly regulate cholesterol and fatty acid biosynthesis and this was further confirmed by the metabolomics data", but a clear mechanistic explanation was lacking. Likewise, the data suggest but do not prove, that altered lipid metabolites influence the function of nuclear receptors to regulate an anti-inflammatory program in response to Mediator kinase inhibition (p. 6), despite the fact the gene expression changes elicited by Mediator kinase inhibition tracked with downstream metabolic changes.

(3) The figures are outstanding but dense.

(4) Figure 6 (PRO-Seq). The authors refer to pro-inflammatory TFs (e.g. NF-kB/RelA). It is not clear whether the authors have specifically examined TF binding at enhancers or more broadly at every region occupied by the interrogated TFs?

Reviewer #1 (Public Review):

Summary:

I have previously reviewed this manuscript as a submission to another journal in 2022. My recommendations here mirror those of my prior suggestions, now with further added details.

This manuscript describes the identification and isolation of several phage from deep sea isolates of Lentisphaerae strains WC36 and zth2. The authors observe induction of several putative chronic phages with the introduction of additional polysaccharides to the media. The authors suggest that two of the recovered phage genomes encode AMGs associated with polysaccharide use. The authors also suggest that adding the purified phage to cultures of Pseudomonas stutzeri 273 increased the growth of this bacteria due to augmented polysaccharide use genes from the phage.

Strengths:

Interesting isolate of deep sea Lentisphaerae strains which will undoubtedly further our understanding of deep sea microbial life.

The revisions have addressed the weaknesses raised in the previous review.

Reviewer #2 (Public Review):

Summary:

This paper investigates deep-sea bacteriophage systems which appear to employ a chronic replication mechanism that is induced or enhanced by polysaccharide addition. Some preliminary evidence for the potential role of auxiliary metabolic genes in aiding phage and/or host proliferation is also provided. The hypothesis being tested is fully supported with solid and convincing evidence and the findings are potentially generalizable with implications for our understanding of polysaccharide-mediated virus-host interactions and carbon cycling in marine ecosystems more broadly.

Strengths:

This paper synthesizes sequencing and phylogenic analyses of two Lentisphaerae bacteria and three phage genomes; electron microscopy imaging of bacterial/phage particles; differential gene expression analyses; differential growth curve analyses, and differential phage proliferation assays to extract insights into whether laminarin and starch can induce both host growth and phage proliferation. The data presented convincingly demonstrate that both host culture density and phage proliferation increase as a result having host, phage, and polysaccharide carbon source together in culture.

Weaknesses:

The AMG-centered elements of the article would be strengthened by more "mechanistic" experiments focusing on identifying "HOW" the polysaccharide processing, transport, and metabolism genes are being used by the phages to either directly increase viral infection/replication or else to indirectly do so by supporting the growth of the host (via mutualism). The concept of "selfishness" in bacterial systems and its potential role in viral life cycles could be more developed. Selfish bacteria are active throughout the water column of the ocean. ISME COMMUN. 3, 11 (2023) (see for instance https://doi.org/10.1038/s43705-023-00219-7) and such "selfish" bacteria sequester metabolizable polysaccharides in their periplasm to advantage (https://www.nature.com/articles/ismej201726). It is plausible that phages may be either hijacking such polysaccharide sequestration mechanisms to improve infectivity and ENTRY or else helping their hosts to grow and proliferate so they can reap the benefits of simply having more hosts to infect. The current work does not clearly distinguish between these two distinct mechanistic possibilities. The paper would be strengthened by a more detailed/clear discussion of this possibility.

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #2 (Public Review):

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

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

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

Strengths:

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

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

Oustanding questions that could lead to interesting follow-up work:

Like all great pieces of research, this article makes it clear where current limitations lie and therefore opens up opportunities for future work.

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

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

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

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

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

(6) More broadly, with the type of objectives that the authors assume the inputs fulfill, some M1 properties that lead to strong preparation - notably, limited readout controllability - may not be favorable for control in general, so it would be interesting if other objectives and assumptions could robustly lead to strong preparation under more general M1 properties.'

Reviewer #3 (Public Review):

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

As discussed in the prior round of reviews, the central constraint that the authors use is a mathematically tractable stand-in for a range of plausible (but often trickier to define and evaluate) constraints, such as simplicity of inputs (or inputs being things that other areas could provide). The manuscript now embraces this fact more explicitly and also gives some results showing that other constraints (such as on the derivative of activity, which is one component of complexity) can have the same effect. The manuscript also now discusses and addresses a modest weakness of the previous manuscript: the preparatory activity in their simulations is often overly complex temporally, lacking the (rough) plateau typically seen for data. Depending on your point of view, this is simply 'window dressing', but from my perspective it was important to know that their approach could yield more realistic-looking preparatory activity.

The most recent version of the manuscript also has a useful section in the Discussion on the topic of preparation when there is no external delay, which I found helpful given prior behavioral and physiological studies arguing that preparation can 1) be very brief, but 2) is always present. These findings mesh nicely with the authors' central result that preparation is a good network strategy, and that it would thus be normative for there to be at least a brief interval of preparation even when not imposed externally.

Reviewer #2 (Public Review):

Summary:

The authors investigated systemic inflammation induced by LPS in various tissues and also examined immune cells of the mice using tight junction protein-based PDZ peptide. They explored the mechanism of anti-systemic inflammatory action of PDZ peptides, which enhanced M1/M2 polarization and induced the proliferation of M2 macrophages. Additionally, they insisted the physiological mechanism that inhibited the production of ROS in mitochondria, thereby preventing systemic inflammation.

Strengths:

In the absence of specific treatments for septic shock or sepsis, the study demonstrating that tight junction-based PDZ peptides inhibit systemic inflammation caused by LPS is highly commendable. Whereas previous research focused on antibiotics, this study proves that modifying parts of intracellular proteins can significantly suppress symptoms caused by septic shock. The authors expanded the study of localized inflammation caused by LPS or PM2.5 in the respiratory tract to systemic inflammation, presenting promising results. They not only elucidated the physiological mechanism by identifying the transcriptome through RNA sequencing but also demonstrated that PDZ peptides inhibit the production of ROS in mitochondria and prevent mitochondrial fission. This research is highly regarded as an excellent study with potential as a treatment for septic shock or sepsis.

Weaknesses:

(1) They Focused intensively on acute inflammation for a short duration instead of chronic inflammation.

(2) LPS was used to induce septic shock but administrating actual microbes such as E.coli would yield more accurate results.

(3) The authors used pegylated peptides, but future research should utilize the optimized peptides to derive the optimal peptide, and further, PK/PD studies are also necessary.

Reviewer #1 (Public Review):

The manuscript introduces a bioinformatic pipeline designed to enhance the structure prediction of pyoverdines, revealing an extensive and previously overlooked diversity in siderophores and receptors. Utilizing a combination of feature sequence and phylogenetic approaches, the method aims to address the challenging task of predicting structures based on dispersed gene clusters, particularly relevant for pyoverdines.

Predicting structures based on gene clusters is still challenging, especially pyoverdines as the gene clusters are often spread to different locations in the genome. The revised manuscript has much improved in clarity and reproducibility. I believe that the method is not yet applicable to all NRPS in general and that there is a clear scalability issue when talking about Big Data. However, the method is highly useful for specific NRPS families such as the pyoverdines, so the manuscript presents a useful bioinformatic pipeline for pyoverdine structure prediction, showcasing a commendable exploration of siderophore diversity.

Reviewer #2 (Public Review):

Pyoverdines, siderophores produced by many Pseudomonads, are one of the most diverse groups of specialized metabolites and frequently used as model systems. Thousands of Pseudomonas genomes are available, but large scale analyses of pyoverdines are hampered by the biosynthetic gene clusters (BGCs) being spread across multiple genomic loci and existing tools' inability to accurately predict amino acid substrates of the biosynthetic adenylation (A) domains. The authors present a bioinformatics pipeline that identifies pyoverdine BGCs and predicts the A domain substrates with high accuracy. They tackled a second challenging problem by developing an algorithm to differentiate between outer membrane receptor selectivity for pyoverdines versus other siderophores and substrates. The authors applied their dataset to thousands of Pseudomonas strains, producing the first comprehensive overview of pyoverdines and their receptors and predicting many new structural variants.

The A domain substrate prediction is impressive, including the correction of entries in the MIBiG database. Their high accuracy came from a relatively small training dataset of A domains from 13 pyoverdine BGCs. The authors acknowledge that this small dataset does not include all substrates, and correctly point out that new sequence/structure pairs can be added to the training set to refine the prediction algorithm. The workflow unfortunately cannot differentiate between different variants of Asp and OHOrn. To validate their predictions, they elucidated structures of several new pyoverdines, and their predictions performed well. The authors tested their workflow on Burkholderiales A domains and had good results, suggesting it can be used on other taxa. Skimming through the source code and data, the algorithm itself appears to be sound and a clear improvement over existing tools for pyoverdine BGC annotation.

Predicting outer membrane receptor specificity is likewise a challenging problem and the authors have made a promising achievement by finding specific gene regions that differentiate the pyoverdine receptor FpvA from FpvB and other receptor families. Their predictions were not tested experimentally, but the finding that only predicted FpvA receptors were proximate to the biosynthesis genes lends credence to the predictive power of the workflow. The authors find predicted pyoverdine receptors across an impressive 468 genera, an exciting finding for expanding the role of pyoverdines as public goods beyond Pseudomonas. However, whether or not these receptors can actually recognize pyoverdines (and if so, which structures!) remains to be investigated.

In all, the authors have assembled a rich dataset that will enable large scale comparative genomic analyses. This dataset could be used by a variety of researchers, including those studying natural product evolution, public good eco/evo dynamics, and NRPS engineering.

Reviewer #2 (Public Review):

Summary:

One of the greatest challenges for the spliceosome is to be able to repress the many cryptic splice sites that can occur in both the intronic and exotic sequences of genes. Although many studies have focused on cryptic signals in introns (because of their common involvement in disease) the question still remained open as to the factors that repress cryptic exons in exons. Because exons are normally much shorter than introns, in many cases the problem does not exist. However, in human genes a significant proportion of exons can be considerably longer than the average 150 nt length and this raises the question of how cryptic splicing can be prevented in long exons. To address this question, the authors have focused on the possible role played by an ancient mammalian RBD protein called RBMX. Using a combination of high-throughput and classic splicing methodologies, they have shown that there is a class of RBMX-dependent ultra-long exons connected where the RBMX, RBMXL2 and RBMY paralogs have closely related functional activity in repressing cryptic splice site selection.

Strengths:

In general, the present work sheds light on what has been a rather understudied process in splicing research. The use of iCLIP and RNA-seq data has not only allowed to identify the long exons where cryptic splicing is prevented by the RBMX proteins but has also allowed to identify a network of genes mostly involved in genome stability and transcriptional control where these proteins seem to play a prominent role. This can therefore also shed additional information on the way splicing has shaped evolutionary processes in the mammalian lineage and will therefore be of interest to many researchers in this field.

Weaknesses:

There are no major weaknesses, although some specific aspects of the findings could be addressed more in-depth in the recommendations to authors.

Reviewer #1 (Public Review):

Summary:

The article by Siachisumo, Luzzi and Aldalaquan et al. describes studies of RBMX and its role in maintaining proper splicing of ultra-long exons. They combine CLIP, RNA-seq, and individual example validations with manipulation of RBMX and its family members RBMY and RBMXL2 to show that the RBMX family plays a key role in maintaining proper splicing of these exons.

I think one of the main strengths of the manuscript is its ability to explore a unique but interesting question (splicing of ultra-long exons), and derive a relatively simple model from the resulting genomics data. The results shown are quite clean, suggesting that RBMX plays an important role in proper regulation of these exons. The ability of family members to rescue this phenotype (as well as only particular domains) is also quite intriguing and suggests that the mechanisms for keeping these exons properly spliced may be a quite important and highly conserved mechanism.

The revised manuscript addresses many of my earlier critiques and does an effective job of arguing that RBMX plays a large-scale role in regulating splicing of long exons. I think there are obvious open questions for future work (the mechanism of how RBMX/RBMXL2 achieve this splicing control is perhaps hinted at but not fully explored here), but I think the article provides an intriguing analysis of the role of RBMX that will activate interesting future studies.

Reviewer #3 (Public Review):

The manuscript by Siachisumo et al builds upon a previous publication from the same group of collaborators that showed that depletion of mouse RBMXL2 leads to a block in spermatogenesis associated with mis-splicing, particularly of large exons in genes associated with genome stability (Ehrmann et al Elife 2019). RBMXL2 is an RNA-binding protein and an autosomal retrotransposed paralog of the X-chromosomally encoded RBMX. RBMXL2 is expressed during meiosis when RBMX and the more distantly related RBMY (on the Y chromosome) are silenced. It is therefore an appealing hypothesis that RBMXL2 might provide cover for RBMX function during meiosis. To address this hypothesis the authors analysed the transcriptomic consequences of RBMX depletion by RNA-Seq in human cells (MDA-MB-231 and existing RNA-Seq data from HEK293 cells), complemented by iCLIP to analyze the binding targets of FLAG-tagged RBMX in HEK293 cells. The findings convincingly demonstrate that - like RBMXL2 - RBMX mainly acts as a splicing repressor and that it particularly acts to protect the integrity of very long ("ultra-long") exons, defined as those over 1000 nt. Upon RBMX depletion, many of these exons are shortened due to the use of cryptic 5' and/or 3' splice sites. Moreover, affected genes are particularly enriched for functions associated with genome integrity - indeed "comet assays" show that RBMX depletion leads to DNA damage defects. Strikingly, RNA-Seq analysis showed that overexpression of RBMXL2 is able to complement the majority of splicing changes caused by RBMX depletion, particularly those involving ultra-long exons. In a smaller scale experiment RBMY was also able to complement effects of RBMX knockdown upon three target events in the ETAA1, REV3L and ATRX genes.

In addition to these core findings the manuscript also includes some experiments that begin to address more mechanistic questions, such as the potential for RBMX to sterically block access of spliceosome components to splice site elements, and preliminary structure-function analyses of RBMX showing that its RRM domain is not necessary for splicing regulatory activity on the ETAA1, REV3L and ATRX target events.

In summary, this manuscript provides clear and convincing evidence to support the role of RBMX in somatic cells as a repressor of cryptic splice sites in ultra-long exons, mirroring the function of RBMXL2 in meiotic cells. It therefore demonstrates how the RBMX/RBMXL2/RBMY family perform a key role in protecting the transcriptomic integrity of ultra-long exons.

Reviewer #1 (Public Review):

This manuscript remains an intriguing investigation of the elephant brainstem, with particular attention drawn to possible sensory and motor representation of the renowned trunk of African and Asian elephants. As the authors note, this area has traditionally been identified as part of the superior olivary complex and associated with the fine motor control of the trunk; however, notable patterns within myelin stripes suggest that its parcellation may relate to specific regions/folds found along the long axis of the trunk, including elaborated regions for the trunk "finger" distal end.

In this iteration of the manuscript, the researchers have provided peripherin antibody staining within the regions they have identified as the trigeminal nucleus and the superior olive. These data, with abundant peripherin expression within climbing fibers of the presumed superior olive and relatively lower expression within the trigeminal nucleus, bolster their interpretation of having comprehensively identified the trigeminal nucleus and trunk representation via a battery of neuroanatomical methods.

All other conclusions remain the same, and these data have provoked intriguing and animated discussion on classification of neuroanatomical structure, particularly in species with relatively limited access to specimens. Most significantly, these discussions have underscored the fundamental nature of comparative methods (from protein to cellular to anatomical levels), including interpreting homologous structures among species of varying levels of relatedness.

Reviewer #2 (Public Review):

Here I submit my previous review and a great deal of additional information following on from the initial review and the response by the authors.

* Initial Review *

Assessment:

This manuscript is based upon the unprecedented identification of an apparently highly unusual trigeminal nuclear organization within the elephant brainstem, related to a large trigeminal nerve in these animals. The apparently highly specialized elephant trigeminal nuclear complex identified in the current study has been classified as the inferior olivary nuclear complex in four previous studies of the elephant brainstem. The entire study is predicated upon the correct identification of the trigeminal sensory nuclear complex and the inferior olivary nuclear complex in the elephant, and if this is incorrect, then the remainder of the manuscript is merely unsupported speculation. There are many reasons indicating that the trigeminal nuclear complex is misidentified in the current study, rendering the entire study, and associated speculation, inadequate at best, and damaging in terms of understanding elephant brains and behaviour at worst.

Original Public Review:

The authors describe what they assert to be a very unusual trigeminal nuclear complex in the brainstem of elephants, and based on this, follow with many speculations about how the trigeminal nuclear complex, as identified by them, might be organized in terms of the sensory capacity of the elephant trunk.<br /> The identification of the trigeminal nuclear complex/inferior olivary nuclear complex in the elephant brainstem is the central pillar of this manuscript from which everything else follows, and if this is incorrect, then the entire manuscript fails, and all the associated speculations become completely unsupported.

The authors note that what they identify as the trigeminal nuclear complex has been identified as the inferior olivary nuclear complex by other authors, citing Shoshani et al. (2006; 10.1016/j.brainresbull.2006.03.016) and Maseko et al (2013; 10.1159/000352004), but fail to cite either Verhaart and Kramer (1958; PMID 13841799) or Verhaart (1962; 10.1515/9783112519882-001). These four studies are in agreement, but the current study differs.

Let's assume for the moment that the four previous studies are all incorrect and the current study is correct. This would mean that the entire architecture and organization of the elephant brainstem is significantly rearranged in comparison to ALL other mammals, including humans, previously studied (e.g. Kappers et al. 1965, The Comparative Anatomy of the Nervous System of Vertebrates, Including Man, Volume 1 pp. 668-695) and the closely related manatee (10.1002/ar.20573). This rearrangement necessitates that the trigeminal nuclei would have had to "migrate" and shorten rostrocaudally, specifically and only, from the lateral aspect of the brainstem where these nuclei extend from the pons through to the cervical spinal cord (e.g. the Paxinos and Watson rat brain atlases), the to the spatially restricted ventromedial region of specifically and only the rostral medulla oblongata. According to the current paper the inferior olivary complex of the elephant is very small and located lateral to their trigeminal nuclear complex, and the region from where the trigeminal nuclei are located by others appears to be just "lateral nuclei" with no suggestion of what might be there instead.

Such an extraordinary rearrangement of brainstem nuclei would require a major transformation in the manner in which the mutations, patterning, and expression of genes and associated molecules during development occur. Such a major change is likely to lead to lethal phenotypes, making such a transformation extremely unlikely. Variations in mammalian brainstem anatomy are most commonly associated with quantitative changes rather than qualitative changes (10.1016/B978-0-12-804042-3.00045-2).

The impetus for the identification of the unusual brainstem trigeminal nuclei in the current study rests upon a previous study from the same laboratory (10.1016/j.cub.2021.12.051) that estimated that the number of axons contained in the infraorbital branch of the trigeminal nerve that innervate the sensory surfaces of the trunk is approximately 400 000. Is this number unusual? In a much smaller mammal with a highly specialized trigeminal system, the platypus, the number of axons innervating the sensory surface of the platypus bill skin comes to 1 344 000 (10.1159/000113185). Yet, there is no complex rearrangement of the brainstem trigeminal nuclei in the brain of the developing or adult platypus (Ashwell, 2013, Neurobiology of Monotremes), despite the brainstem trigeminal nuclei being very large in the platypus (10.1159/000067195). Even in other large-brained mammals, such as large whales that do not have a trunk, the number of axons in the trigeminal nerve ranges between 400,000 and 500,000 (10.1007/978-3-319-47829-6_988-1). The lack of comparative support for the argument forwarded in the previous and current study from this laboratory, and that the comparative data indicates that the brainstem nuclei do not change in the manner suggested in the elephant, argues against the identification of the trigeminal nuclei as outlined in the current study. Moreover, the comparative studies undermine the prior claim of the authors, informing the current study, that "the elephant trigeminal ganglion ... point to a high degree of tactile specialization in elephants" (10.1016/j.cub.2021.12.051). While clearly the elephant has tactile sensitivity in the trunk, it is questionable as to whether what has been observed in elephants is indeed "truly extraordinary".

But let's look more specifically at the justification outlined in the current study to support their identification of the unusually located trigeminal sensory nuclei of the brainstem.

(1) Intense cytochrome oxidase reactivity<br /> (2) Large size of the putative trunk module<br /> (3) Elongation of the putative trunk module<br /> (4) Arrangement of these putative modules correspond to elephant head anatomy<br /> (5) Myelin stripes within the putative trunk module that apparently match trunk folds<br /> (6) Location apparently matches other mammals<br /> (7) Repetitive modular organization apparently similar to other mammals.<br /> (8) The inferior olive described by other authors lacks the lamellated appearance of this structure in other mammals

Let's examine these justifications more closely.

(1) Cytochrome oxidase histochemistry is typically used as an indicative marker of neuronal energy metabolism. The authors indicate, based on the "truly extraordinary" somatosensory capacities of the elephant trunk, that any nuclei processing this tactile information should be highly metabolically active, and thus should react intensely when stained for cytochrome oxidase. We are told in the methods section that the protocols used are described by Purkart et al (2022) and Kaufmann et al (2022). In neither of these cited papers is there any description, nor mention, of the cytochrome oxidase histochemistry methodology, thus we have no idea of how this histochemical staining was done. In order to obtain the best results for cytochrome oxidase histochemistry, the tissue is either processed very rapidly after buffer perfusion to remove blood or in recently perfusion-fixed tissue (e.g., 10.1016/0165-0270(93)90122-8). Given: (1) the presumably long post-mortem interval between death and fixation - "it often takes days to dissect elephants"; (2) subsequent fixation of the brains in 4% paraformaldehyde for "several weeks"; (3) The intense cytochrome oxidase reactivity in the inferior olivary complex of the laboratory rat (Gonzalez-Lima, 1998, Cytochrome oxidase in neuronal metabolism and Alzheimer's diseases); and (4) The lack of any comparative images from other stained portions of the elephant brainstem; it is difficult to support the justification as forwarded by the authors. It is likely that the histochemical staining observed is background reactivity from the use of diaminobenzidine in the staining protocol. Thus, this first justification is unsupported.<br /> Justifications (2), (3), and (4) are sequelae from justification (1). In this sense, they do not count as justifications, but rather unsupported extensions.

(4) and (5) These are interesting justifications, as the paper has clear internal contradictions, and (5) is a sequelae of (4). The reader is led to the concept that the myelin tracts divide the nuclei into sub-modules that match the folding of the skin on the elephant trunk. One would then readily presume that these myelin tracts are in the incoming sensory axons from the trigeminal nerve. However, the authors note that this is not the case: "Our observations on trunk module myelin stripes are at odds with this view of myelin. Specifically, myelin stripes show no tapering (which we would expect if axons divert off into the tissue). More than that, there is no correlation between myelin stripe thickness (which presumably correlates with axon numbers) and trigeminal module neuron numbers. Thus, there are numerous myelinated axons, where we observe few or no trigeminal neurons. These observations are incompatible with the idea that myelin stripes form an axonal 'supply' system or that their prime function is to connect neurons. What do myelin stripe axons do, if they do not connect neurons? We suggest that myelin stripes serve to separate rather than connect neurons." So, we are left with the observation that the myelin stripes do not pass afferent trigeminal sensory information from the "truly extraordinary" trunk skin somatic sensory system, and rather function as units that separate neurons - but to what end? It appears that the myelin stripes are more likely to be efferent axonal bundles leaving the nuclei (to form the olivocerebellar tract). This justification is unsupported.

(6) The authors indicate that the location of these nuclei matches that of the trigeminal nuclei in other mammals. This is not supported in any way. In ALL other mammals in which the trigeminal nuclei of the brainstem have been reported they are found in the lateral aspect of the brainstem, bordered laterally by the spinal trigeminal tract. This is most readily seen and accessible in the Paxinos and Watson rat brain atlases. The authors indicate that the trigeminal nuclei are medial to the facial nerve nucleus, but in every other species, the trigeminal sensory nuclei are found lateral to the facial nerve nucleus. This is most salient when examining a close relative, the manatee (10.1002/ar.20573), where the location of the inferior olive and the trigeminal nuclei matches that described by Maseko et al (2013) for the African elephant. This justification is not supported.

(7) The dual to quadruple repetition of rostro-caudal modules within the putative trigeminal nucleus as identified by the authors relies on the fact that in the neurotypical mammal, there are several trigeminal sensory nuclei arranged in a column running from the pons to the cervical spinal cord, these include (nomenclature from Paxinos and Watson in roughly rostral to caudal order) the Pr5VL, Pr5DM, Sp5O, Sp5I, and Sp5C. But, these nuclei are all located far from the midline and lateral to the facial nerve nucleus, unlike what the authors describe in the elephants. These rostrocaudal modules are expanded upon in Figure 2, and it is apparent from what is shown that the authors are attributing other brainstem nuclei to the putative trigeminal nuclei to confirm their conclusion. For example, what they identify as the inferior olive in figure 2D is likely the lateral reticular nucleus as identified by Maseko et al (2013). This justification is not supported.

(8) In primates and related species, there is a distinct banded appearance of the inferior olive, but what has been termed the inferior olive in the elephant by other authors does not have this appearance, rather, and specifically, the largest nuclear mass in the region (termed the principal nucleus of the inferior olive by Maseko et al, 2013, but Pr5, the principal trigeminal nucleus in the current paper) overshadows the partial banded appearance of the remaining nuclei in the region (but also drawn by the authors of the current paper). Thus, what is at debate here is whether the principal nucleus of the inferior olive can take on a nuclear shape rather than evince a banded appearance. The authors of this paper use this variance as justification that this cluster of nuclei could not possibly be the inferior olive. Such a "semi-nuclear/banded" arrangement of the inferior olive is seen in, for example, giraffe (10.1016/j.jchemneu.2007.05.003), domestic dog, polar bear, and most specifically the manatee (a close relative of the elephant) (brainmuseum.org; 10.1002/ar.20573). This justification is not supported.

Thus, all the justifications forwarded by the authors are unsupported. Based on methodological concerns, prior comparative mammalian neuroanatomy, and prior studies in the elephant and closely related species, the authors fail to support their notion that what was previously termed the inferior olive in the elephant is actually the trigeminal sensory nuclei. Given this failure, the justifications provided above that are sequelae also fail. In this sense, the entire manuscript and all the sequelae are not supported.

What the authors have not done is to trace the pathway of the large trigeminal nerve in the elephant brainstem, as was done by Maseko et al (2013), which clearly shows the internal pathways of this nerve, from the branch that leads to the fifth mesencephalic nucleus adjacent to the periventricular grey matter, through to the spinal trigeminal tract that extends from the pons to the spinal cord in a manner very similar to all other mammals. Nor have they shown how the supposed trigeminal information reaches the putative trigeminal nuclei in the ventromedial rostral medulla oblongata. These are but two examples of many specific lines of evidence that would be required to support their conclusions. Clearly tract tracing methods, such as cholera toxin tracing of peripheral nerves cannot be done in elephants, thus the neuroanatomy must be done properly and with attention to detail to support the major changes indicated by the authors.

So what are these "bumps" in the elephant brainstem?

Four previous authors indicate that these bumps are the inferior olivary nuclear complex. Can this be supported?

The inferior olivary nuclear complex acts "as a relay station between the spinal cord (n.b. trigeminal input does reach the spinal cord via the spinal trigeminal tract) and the cerebellum, integrating motor and sensory information to provide feedback and training to cerebellar neurons" (https://www.ncbi.nlm.nih.gov/books/NBK542242/). The inferior olivary nuclear complex is located dorsal and medial to the pyramidal tracts (which were not labelled in the current study by the authors but are clearly present in Fig. 1C and 2A) in the ventromedial aspect of the rostral medulla oblongata. This is precisely where previous authors have identified the inferior olivary nuclear complex and what the current authors assign to their putative trigeminal nuclei. The neurons of the inferior olivary nuclei project, via the olivocerebellar tract to the cerebellum to terminate in the climbing fibres of the cerebellar cortex.

Elephants have the largest (relative and absolute) cerebellum of all mammals (10.1002/ar.22425), this cerebellum contains 257 x109 neurons (10.3389/fnana.2014.00046; three times more than the entire human brain, 10.3389/neuro.09.031.2009). Each of these neurons appears to be more structurally complex than the homologous neurons in other mammals (10.1159/000345565; 10.1007/s00429-010-0288-3). In the African elephant, the neurons of the inferior olivary nuclear complex are described by Maseko et al (2013) as being both calbindin and calretinin immunoreactive. Climbing fibres in the cerebellar cortex of the African elephant are clearly calretinin immunopositive and also are likely to contain calbindin (10.1159/000345565). Given this, would it be surprising that the inferior olivary nuclear complex of the elephant is enlarged enough to create a very distinct bump in exactly the same place where these nuclei are identified in other mammals?

What about the myelin stripes? These are most likely to be the origin of the olivocerebellar tract and probably only have a coincidental relationship to the trunk. Thus, given what we know, the inferior olivary nuclear complex as described in other studies, and the putative trigeminal nuclear complex as described in the current study, is the elephant inferior olivary nuclear complex. It is not what the authors believe it to be, and they do not provide any evidence that discounts the previous studies. The authors are quite simply put, wrong. All the speculations that flow from this major neuroanatomical error are therefore science fiction rather than useful additions to the scientific literature.

What do the authors actually have?<br /> The authors have interesting data, based on their Golgi staining and analysis, of the inferior olivary nuclear complex in the elephant.

* Review of Revised Manuscript *

Assessment:

There is a clear dichotomy between the authors and this reviewer regarding the identification of specific structures, namely the inferior olivary nuclear complex and the trigeminal nuclear complex, in the brainstem of the elephant. The authors maintain the position that in the elephant alone, irrespective of all the published data on other mammals and previously published data on the elephant brainstem, these two nuclear complexes are switched in location. The authors maintain that their interpretation is correct, but this reviewer maintains that this interpretation is erroneous. The authors expressed concern that the remainder of the paper was not addressed by the reviewer, but the reviewer maintains that these sequelae to the misidentification of nuclear complexes in the elephant brainstem render any of these speculations irrelevant as the critical structures are incorrectly identified. It is this reviewer's opinion that this paper is incorrect. I provide a lot of detail below in order to provide support to the opinion I express.

Public Review of Current Submission:

As indicated in my previous review of this manuscript (see above), it is my opinion that the authors have misidentified, and indeed switched, the inferior olivary nuclear complex (IO) and the trigeminal nuclear complex (Vsens). It is this specific point only that I will address in this second review, as this is the crucial aspect of this paper - if the identification of these nuclear complexes in the elephant brainstem by the authors is incorrect, the remainder of the paper does not have any scientific validity.

The authors, in their response to my initial review, claim that I "bend" the comparative evidence against them. They further claim that as all other mammalian species exhibit a "serrated" appearance of the inferior olive, and as the elephant does not exhibit this appearance, what was previously identified as the inferior olive is actually the trigeminal nucleus and vice versa.

For convenience, I will refer to IOM and VsensM as the identification of these structures according to Maseko et al (2013) and other authors and will use IOR and VsensR to refer to the identification forwarded in the study under review.<br /> The IOM/VsensR certainly does not have a serrated appearance in elephants. Indeed, from the plates supplied by the authors in response (Referee Fig. 2), the cytochrome oxidase image supplied and the image from Maseko et al (2013) shows a very similar appearance. There is no doubt that the authors are identifying structures that closely correspond to those provided by Maseko et al (2013). It is solely a contrast in what these nuclear complexes are called and the functional sequelae of the identification of these complexes (are they related to the trunk sensation or movement controlled by the cerebellum?) that is under debate.

Elephants are part of the Afrotheria, thus the most relevant comparative data to resolve this issue will be the identification of these nuclei in other Afrotherian species. Below I provide images of these nuclear complexes, labelled in the standard nomenclature, across several Afrotherian species.

(A) Lesser hedgehog tenrec (Echinops telfairi)

Tenrecs brains are the most intensively studied of the Afrotherian brains, these extensive neuroanatomical studies were undertaken primarily by Heinz Künzle. Below I append images (coronal sections stained with cresol violet) of the IO and Vsens (labelled in the standard mammalian manner) in the lesser hedgehog tenrec. It should be clear that the inferior olive is located in the ventral midline of the rostral medulla oblongata (just like the rat) and that this nucleus is not distinctly serrated. The Vsens is located in the lateral aspect of the medulla skirted laterally by the spinal trigeminal tract (Sp5). These images and the labels indicating structures correlate precisely with that provided by Künzle (1997, 10.1016/S0168- 0102(97)00034-5), see his Figure 1K,L. Thus, in the first case of a related species, there is no serrated appearance of the inferior olive, the location of the inferior olive is confirmed through connectivity with the superior colliculus (a standard connection in mammals) by Künzle (1997), and the location of Vsens is what is considered to be typical for mammals. This is in agreement with the authors, as they propose that ONLY the elephants show the variations they report.

Peer Review Image 1.

(B) Giant otter shrew (Potomogale velox)

The otter shrews are close relatives of the Tenrecs. Below I append images of cresyl violet (left column) and myelin (right column) stained coronal sections through the brainstem with the IO, Vsens and Sp5 labelled as per standard mammalian anatomy. Here we see hints of the serration of the IO as defined by the authors, but we also see many myelin stripes across the IO. Vsens is located laterally and skirted by the Sp5. This is in agreement with the authors, as they propose that ONLY the elephants show the variations they report.

Peer Response Image 2.

(C) Four-toed sengi (Petrodromus tetradactylus)

The sengis are close relatives of the Tenrecs and otter shrews, these three groups being part of the Afroinsectiphilia, a distinct branch of the Afrotheria. Below I append images of cresyl violet (left column) and myelin (right column) stained coronal sections through the brainstem with the IO, Vsens and Sp5 labelled as per standard mammalian anatomy. Here we see vague hints of the serration of the IO (as defined by the authors), and we also see many myelin stripes across the IO. Vsens is located laterally and skirted by the Sp5. This is in agreement with the authors, as they propose that ONLY the elephants show the variations they report.

Peer Response Image 3.

(D) Rock hyrax (Procavia capensis)

The hyraxes, along with the sirens and elephants form the Paenungulata branch of the Afrotheria. Below I append images of cresyl violet (left column) and myelin (right column) stained coronal sections through the brainstem with the IO, Vsens and Sp5 labelled as per the standard mammalian anatomy. Here we see hints of the serration of the IO (as defined by the authors), but we also see evidence of a more "bulbous" appearance of subnuclei of the IO (particularly the principal nucleus), and we also see many myelin stripes across the IO. Vsens is located laterally and skirted by the Sp5. This is in agreement with the authors, as they propose that ONLY the elephants show the variations they report.

Peer Review Image 4.

(E) West Indian manatee (Trichechus manatus)

The sirens are the closest extant relatives of the elephants in the Afrotheria. Below I append images of cresyl violet (top) and myelin (bottom) stained coronal sections (taken from the University of Wisconsin-Madison Brain Collection, https://brainmuseum.org, and while quite low in magnification they do reveal the structures under debate) through the brainstem with the IO, Vsens and Sp5 labelled as per standard mammalian anatomy. Here we see the serration of the IO (as defined by the authors). Vsens is located laterally and skirted by the Sp5. This is in agreement with the authors, as they propose that ONLY the elephants show the variations they report.

Peer Review Image 5.

These comparisons and the structural identification, with which the authors agree as they only distinguish the elephants from the other Afrotheria, demonstrate that the appearance of the IO can be quite variable across mammalian species, including those with a close phylogenetic affinity to the elephants. Not all mammal species possess a "serrated" appearance of the IO. Thus, it is more than just theoretically possible that the IO of the elephant appears as described prior to this study.

So what about elephants? Below I append a series of images from coronal sections through the African elephant brainstem stained for Nissl, myelin, and immunostained for calretinin. These sections are labelled according to standard mammalian nomenclature. In these complete sections of the elephant brainstem, we do not see a serrated appearance of the IOM (as described previously and in the current study by the authors). Rather the principal nucleus of the IOM appears to be bulbous in nature. In the current study, no image of myelin staining in the IOM/VsensR is provided by the authors. However, in the images I provide, we do see the reported myelin stripes in all stains - agreement between the authors and reviewer on this point. The higher magnification image to the bottom left of the plate shows one of the IOM/VsensR myelin stripes immunostained for calretinin, and within the myelin stripes axons immunopositive for calretinin are seen (labelled with an arrow). The climbing fibres of the elephant cerebellar cortex are similarly calretinin immunopositive (10.1159/000345565). In contrast, although not shown at high magnification, the fibres forming the Sp5 in the elephant (in the Maseko description, unnamed in the description of the authors) show no immunoreactivity to calretinin.

Peer Review Image 6.

Peripherin Immunostaining

In their revised manuscript the authors present immunostaining of peripherin in the elephant brainstem. This is an important addition (although it does replace the only staining of myelin provided by the authors which is unusual as the word myelin is in the title of the paper) as peripherin is known to specifically label peripheral nerves. In addition, as pointed out by the authors, peripherin also immunostains climbing fibres (Errante et al., 1998). The understanding of this staining is important in determining the identification of the IO and Vsens in the elephant, although it is not ideal for this task as there is some ambiguity. Errante and colleagues (1998; Fig. 1) show that climbing fibres are peripherin-immunopositive in the rat. But what the authors do not evaluate is the extensive peripherin staining in the rat Sp5 in the same paper (Errante et al, 1998, Fig. 2). The image provided by the authors of their peripherin immunostaining (their new Figure 2) shows what I would call the Sp5 of the elephant to be strongly peripherin immunoreactive, just like the rat shown in Errant et al (1998), and moreover in the precise position of the rat Sp5! This makes sense as this is where the axons subserving the "extraordinary" tactile sensitivity of the elephant trunk would be found (in the standard model of mammalian brainstem anatomy). Interestingly, the peripherin immunostaining in the elephant is clearly lamellated...this coincides precisely with the description of the trigeminal sensory nuclei in the elephant by Maskeo et al (2013) as pointed out by the authors in their rebuttal. Errante et al (1998) also point out peripherin immunostaining in the inferior olive, but according to the authors this is only "weakly present" in the elephant IOM/VsensR. This latter point is crucial. Surely if the elephant has an extraordinary sensory innervation from the trunk, with 400,000 axons entering the brain, the VsensR/IOM should be highly peripherin-immunopositive, including the myelinated axon bundles?! In this sense, the authors argue against their own interpretation - either the elephant trunk is not a highly sensitive tactile organ, or the VsensR is not the trigeminal nuclei it is supposed to be.

Summary:

(1) Comparative data of species closely related to elephants (Afrotherians) demonstrates that not all mammals exhibit the "serrated" appearance of the principal nucleus of the inferior olive.

(2) The location of the IO and Vsens as reported in the current study (IOR and VsensR) would require a significant, and unprecedented, rearrangement of the brainstem in the elephants independently. I argue that the underlying molecular and genetic changes required to achieve this would be so extreme that it would lead to lethal phenotypes. Arguing that the "switcheroo" of the IO and Vsens does occur in the elephant (and no other mammals) and thus doesn't lead to lethal phenotypes is a circular argument that cannot be substantiated.

(3) Myelin stripes in the subnuclei of the inferior olivary nuclear complex are seen across all related mammals as shown above. Thus, the observation made in the elephant by the authors in what they call the VsensR, is similar to that seen in the IO of related mammals, especially when the IO takes on a more bulbous appearance. These myelin stripes are the origin of the olivocerebellar pathway and are indeed calretinin immunopositive in the elephant as I show.

(4) What the authors see aligns perfectly with what has been described previously, the only difference being the names that nuclear complexes are being called. But identifying these nuclei is important, as any functional sequelae, as extensively discussed by the authors, is entirely dependent upon accurately identifying these nuclei.

(4) The peripherin immunostaining scores an own goal - if peripherin is marking peripheral nerves (as the authors and I believe it is), then why is the VsensR/IOM only "weakly positive" for this stain? This either means that the "extraordinary" tactile sensitivity of the elephant trunk is non-existent, or that the authors have misinterpreted this staining. That there is extensive staining in the fibre pathway dorsal and lateral to the IOR (which I call the spinal trigeminal tract), supports the idea that the authors have misinterpreted their peripherin immunostaining.

(5) Evolutionary expediency. The authors argue that what they report is an expedient way in which to modify the organisation of the brainstem in the elephant to accommodate the "extraordinary" tactile sensitivity. I disagree. As pointed out in my first review, the elephant cerebellum is very large and comprised of huge numbers of morphologically complex neurons. The inferior olivary nuclei in all mammals studied in detail to date, give rise to the climbing fibres that terminate on the Purkinje cells of the cerebellar cortex. It is more parsimonious to argue that, in alignment with the expansion of the elephant cerebellum (for motor control of the trunk), the inferior olivary nuclei (specifically the principal nucleus) have had additional neurons added to accommodate this cerebellar expansion. Such an addition of neurons to the principal nucleus of the inferior olive could readily lead to the loss of the serrated appearance of the principal nucleus of the inferior olive and would require far less modifications in the developmental genetic program that forms these nuclei. This type of quantitative change appears to be the primary way in which structures are altered in the mammalian brainstem.

Reviewer #3 (Public Review):

Summary:

The study claims to investigate trunk representations in elephant trigeminal nuclei located in the brainstem. The researchers identify large protrusions visible from the ventral surface of the brainstem, which they examined using a range of histological methods. However, this ventral location is usually where the inferior olivary complex is found, which challenges the author's assertions about the nucleus under analysis. They find that this brainstem nucleus of elephants contains repeating modules, with a focus on the anterior and largest unit which they define as the putative nucleus principalis trunk module of the trigeminal. The nucleus exhibits low neuron density, with glia outnumbering neurons significantly. The study also utilizes synchrotron X-ray phase contrast tomography to suggest that myelin-stripe-axons traverse this module. The analysis maps myelin-rich stripes in several specimens and concludes that based on their number and patterning they likely correspond with trunk folds; however this conclusion is not well supported if the nucleus has been misidentified.

Strengths:

The strength of this research lies in its comprehensive use of various anatomical methods, including Nissl staining, myelin staining, Golgi staining, cytochrome oxidase labeling, and synchrotron X-ray phase contrast tomography. The inclusion of quantitative data on cell numbers and sizes, dendritic orientation and morphology, and blood vessel density across the nucleus adds a quantitative dimension. Furthermore, the research is commendable for its high-quality and abundant images and figures, effectively illustrating the anatomy under investigation.

Weaknesses:

While the research provides potentially valuable insights if revised to focus on the structure that appears to be an inferior olivary nucleus, there are certain additional weaknesses that warrant further consideration. First, the suggestion that myelin stripes solely serve to separate sensory or motor modules rather than functioning as an "axonal supply system" lacks substantial support due to the absence of information about the neuronal origins and the termination targets of the axons. Postmortem fixed brain tissue limits the ability to trace full axon projections. While the study acknowledges these limitations, it is important to exercise caution in drawing conclusions about the precise role of myelin stripes without a more comprehensive understanding of their neural connections.

Second, the quantification presented in the study lacks comparison to other species or other relevant variables within the elephant specimens (i.e., whole brain or brainstem volume). The absence of comparative data to different species limits the ability to fully evaluate the significance of the findings. Comparative analyses could provide a broader context for understanding whether the observed features are unique to elephants or more common across species. This limitation in comparative data hinders a more comprehensive assessment of the implications of the research within the broader field of neuroanatomy. Furthermore, the quantitative comparisons between African and Asian elephant specimens should include some measure of overall brain size as a covariate in the analyses. Addressing these weaknesses would enable a richer interpretation of the study's findings.

Reviewer #4 (Public Review):

Summary:

The authors report a novel isomorphism in which the folds of the elephant trunk are recognizably mapped onto the principal sensory trigeminal nucleus in the brainstem. Further, they identify the enlarged nucleus as being situated in this species in an unusual ventral midline position.

Strengths:

The identity of the purported trigeminal nucleus and the isomorphic mapping with the trunk folds is supported by multiple lines of evidence: enhanced staining for cytochrome oxidase, an enzyme associated with high metabolic activity; dense vascularization, consistent with high metabolic activity; prominent myelinated bundles that partition the nucleus in a 1:1 mapping of the cutaneous folds in the trunk periphery; near absence of labeling for the anti-peripherin antibody, specific for climbing fibers, which can be seen as expected in the inferior olive; and a high density of glia.

Weaknesses:

Despite the supporting evidence listed above, the identification of the gross anatomical bumps, conspicuous in the ventral midline, is problematic. This would be the standard location of the inferior olive, with the principal trigeminal nucleus occupying a more dorsal position. This presents an apparent contradiction which at a minimum needs further discussion. Major species-specific specializations and positional shifts are well-documented for cortical areas, but nuclear layouts in the brainstem have been considered as less malleable.

Reviewer #2 (Public Review):

Summary:

Overall this is an interesting innovative study that examines chromatin accessibility in an inhibitory iPSC model of Dravet Syndrome. The authors detect a potential intriguing development defect in the patient-specific neurons, however the correlation with gene expression or protein abundance is not compelling and the variability of the data is still difficult to determine.

Strengths:

(1) This is a novel and interesting study that aims to investigate the epigenetic changes that occur in a sodium channel model of epilepsy, these are oft ignored, but also an interesting area for future therapeutics.

(2) The paper is well written with good graphics and flow.

(3) With caveats noted below, there is an intriguing developmental defect in GABAergic neuron differentiation in this model. It would be interesting to see how this correlated with the expression of SCN1A, and I was surprised this was not addressed in the manuscript via RNA/protein abundance, nor how the absence of a sodium channel can accelerate differentiation when a priori I might expect the opposite (as less 'neuronal' signal)

(4) There is exploratory analysis that VPA alters chromatin accessibility at an individual-specific level. Though it was not noted if any of the DS patients,

Weaknesses addressed:

(1) Representative images for cell-identity markers are now shown for D19 and D65.

(2) The methods now state that three differentiations were performed.

(3) The authors address a possible role for cell death in data obtained from their cultures by assessing viability with trypan blue staining.

(4) Some features of ATAC signal normalization and enrichment analysis have been better documented.

(5) Some of the variability in key results is better documented.

Weaknesses poorly or not addressed:

(1) Although the authors include prior RNAseq data and report on qPCR measurements for SCN1A (Supp Fig 1)these do not on the surface appear to agree, with the RNAseq showing little apparent difference between patients and controls, while the qPCR seems to show a two-fold difference at D65. This is likely a misleading artifact of normalizing PCR expression to that at D0 when the gene is not expressed but has mildly different low levels in patients and controls. No measurement of the protein product or its function is included. This is a major weakness that casts doubt on the core hypothesis that epigenetic changes play a key causal role in Dravet syndrome.

(2) Although some QC on ATAC is described, QC performed on iPSC lines, i.e. karyotype/CNV analysis and confirmation of genotypes is not described in the paper.

(3) The authors describe a method for trying to diminish variability but do not adequately explain this method or how much variability remains in many of their measures.

(4) Given that VPA would be administered in patients with fully mature inhibitory neurons, it is difficult to determine the biological relevance of these findings.

Reviewer #1 (Public Review):

In this manuscript, entitled " Merging Multi-OMICs with Proteome Integral Solubility Alteration Unveils Antibiotic Mode of Action", Dr. Maity and colleagues aim to elucidate the mechanisms of action of antibiotics through combined approaches of omics and the PISA tool to discover new targets of five drugs developed against Helicobacter pylori.

Strengths:<br /> Using transcriptomics, proteomic analysis, protein stability (PISA), and integrative analysis, Dr. Maity and colleagues have identified pathways targeted by five compounds initially discovered as inhibitors against H. pylori flavodoxin. This study underscores the necessity of a global approach to comprehensively understand the mechanisms of drug action. The experiments conducted in this paper are well designed and the obtained results support the authors' conclusions.

Reviewer #1 (Public Review):

Summary:<br /> This work revealed an important finding that the blood-brain barrier (BBB) functionality changes with age and is more pronounced in males. The authors applied a non-invasive, contrast-agent-free approach of MRI called diffusion-prepared arterial spin labeling (DP-pCASL) to a large cohort of healthy human volunteers. DP-pCASL works by tracking the movement of magnetically labeled water (spins) in blood as it perfuses brain tissue. It probes the molecular diffusion of water, which is sensitive to microstructural barriers, and characterizes the signal coming from fast-moving spins as blood and slow-moving spins as tissue, using different diffusion gradients (b-values). This differentiation is then used to assess the water exchange rates (kw) across the BBB, which acts as a marker for BBB functionality. The main finding of the authors is that kw decreases with age, and in some brain regions, kw decreased faster in males. The neuroprotective role of the female sex hormone, estrogen, on BBB function is discussed as one of the explanations for this finding, supported by literature. The study also shows that BBB function remains stable until the early 60s and remarkably decreases thereafter.

Strengths:<br /> The two main strengths of the study are the MRI method used and the amount of data. The authors employed a contrast-agent-free MRI method called ASL, which offers the opportunity to repeat such experiments multiple times without any health risk-a significant advantage of ASL. Since ASL is an emerging field that requires further exploration and testing, a study evaluating blood-brain barrier functionality is of great importance. The authors utilized a large dataset of healthy humans, where volunteer data from various studies were combined to create a substantial pool. This strategy is effective for statistically evaluating differences in age and gender.

Weaknesses:<br /> The findings are of great interest as this assessment is the first of its kind to assess BBB function using ASL. Further studies are needed to compare DP-ASL findings with more established methods, such as PET and BBB molecular/ blood biomarkers.

Reviewer #2 (Public Review):<br /> Summary:<br /> This study used a novel diffusion-weighted pseudo-continuous arterial spin labelling (pCASL) technique to simultaneously explore age- and sex-related differences in brain tissue perfusion (i.e., cerebral blood flow (CBF) & arterial transit time (ATT) - a measure of CBF delivery to brain tissue) and blood-brain barrier (BBB) function, measured as the water exchange (kw) across the BBB. While age- and sex-related effects on CBF are well known, this study provides new insights to support the growing evidence of these important factors in cerebrovascular health, particularly in BBB function. Across the brain, decline in CBF and BBB function (kw) and elevation in ATT was reported in older adults, after the age of 60 and more so in males compared to females. This was also evident in key cognitive regions including the insular, prefrontal, and medial temporal regions, stressing the consideration of age and sex in these brain physiological assessments.

Strengths:<br /> Simultaneous assessment of CBF with BBB along with transit time and at the voxel-level helped elucidate the brain's vulnerability to age and sex-effects. It is apparent that the investigators carefully designed this study to assess regional associations of age and sex with attention to exploring potential non-linear effects.

Weaknesses:<br /> It appears that no brain region showed concurrent CBF and BBB dysfunction (kw), based on the results reported in the main manuscript and supplemental information. Was an association analysis between CBF and kw performed? There is a potential effect of the level of formal education on CBF (PMID: 12633147; 15534055), which could have been considered and accounted for as well, especially for a cohort with stated diversity (age, race, sex).

Reviewer #1 (Public Review):

In this manuscript, by using simulation, in vitro and in vivo electrophysiology, and behavioral tests, Peng et al. nicely showed a new approach for the treatment of neuropathic pain in mice. They found that terahertz (THz) waves increased Kv conductance and decreased the frequency of action potentials in pyramidal neurons in the ACC region. Behaviorally, terahertz (THz) waves alleviated neuropathic pain in the mouse model. Overall, this is an interesting study. The experimental design is clear, the data is presented well, and the paper is well-written.

I have a few suggestions.<br /> (1) The authors provide strong theoretical and experimental evidence for the impact of voltage-gated potassium channels by terahertz wave frequency. However, the modulation of action potential also relies on non-voltage-dependent ion channels. For example, I noticed that the RMP was affected by THz application (Fig. 3F) as well. As the RMP is largely regulated by the leak potassium channels (Tandem-pore potassium channels), I would suggest testing whether terahertz wave photons have also any impact on the Kleak channels as well.

(2) The activation curves of the Kv currents in Fig. 2h seem to be not well-fitted. I would suggest testing a higher voltage (>100 mV) to collect more data to achieve a better fitting.

(3) In the part of behavior tests, the pain threshold increased after THz application and lasted within 60 mins. I suggest conducting prolonged tests to determine the end of the analgesic effect of terahertz waves.

(4) Regarding in vivo electrophysiological recordings, the post-HFTS recordings were acquired from a time window of up to 20 min. It seems that the HFTS effect lasted for minutes, but this was not tested in vitro where they looked at potassium currents. This long-lasting effect of HFTS is interesting. Can the authors discuss it and its possible mechanisms, or test it in slice electrophysiological experiments?

(5) How did the authors arrange the fiber for HFTS delivery and the electrode for in vivo multi-channel recordings? Providing a schematic illustration in Fig. 4 would be useful.

(6) Language is largely OK, but some grammar errors should be corrected.

The authors have completely addressed my concerns. I have no further comments.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Peng et al., reported that 36THz high-frequency terahertz stimulation (HFTS) can suppress the activity of pyramidal neurons through enhancing the conductance of voltage-gated potassium channel. The authors also demonstrated the effectiveness of using 36THz HFTS for treating neuropathic pain.

Strengths:

The manuscript is well written and the conclusions are supported by robust results. This study highlighted the potential of using 36THz HFTS for neuromodulation.

Weaknesses:

More characterization of HFTS is needed, so the readers can have a better assessment of the potential usage of HFTS in their own applications.

Reviewer #3 (Public Review):

My summary of the manuscript remains the same and is as follows:

This manuscript by Peng et al. presents intriguing data indicating that high-frequency terahertz stimulation (HFTS) of the anterior cingulate cortex (ACC) can alleviate neuropathic pain behaviors in mice. Specifically, the investigators report that terahertz (THz) frequency stimulation widens the selectivity filter of potassium channels thereby increasing potassium conductance leading to a reduction in the excitability of cortical neurons. In voltage clamp recordings from layer 5 ACC pyramidal neurons in acute brain slice, Peng et al. show that HFTS enhances K current while showing minimal effects on Na current. Current clamp recording analyses show that the spared nerve injury model of neuropathic pain decreases the current threshold for action potential (AP) generation and increases evoked AP frequency in layer 5 ACC pyramidal neurons, which is consistent with previous studies. Data are presented showing that ex-vivo treatment with HFTS in slice reduces these SNI-induced changes to excitability in layer 5 ACC pyramidal neurons. The authors also confirm that HFTS reduces excitability of layer 5 ACC pyramidal neurons via in vivo multi-channel recordings from SNI mice. Lastly, the authors show that HFTS is effective at reducing mechanical allodynia in SNI using both the von Frey and Catwalk analyses. Overall, there is considerable enthusiasm for the findings presented in this manuscript given the need for non-pharmacological treatments for pain in the clinical setting.

Reviewer #1 (Public Review):

In this manuscript, Yoo et al describe the role of a specialized cell type found in muscle, Fibro-adipogenic progenitors (FAPs), in promoting regeneration following sciatic nerve injury. Using single-cell transcriptomics, they characterize the expression profiles of FAPs at various times after nerve crush or denervation. Their results reveal that a population of these muscle-resident mesenchymal progenitors up regulate the receptors for GDNF, which is secreted by Schwann cells following crush injury, suggesting that FAPs respond to this growth factor. They also find that FAPs increase expression of BDNF, which promotes nerve regeneration. The authors demonstrate FAP production of BDNF in vivo is up regulated in response to injection of GDNF and that conditional deletion of BDNF in FAPs results in delayed nerve regeneration after crush injury, primarily due to lagging remyelination. Finally, they also find reduced BDNF expression following crush injury in aged mice, suggesting a potential mechanism to explain the decrease in peripheral nerve regenerative capability in aged animals. These results are very interesting and novel and provide important insights into the mechanisms regulating peripheral nerve regeneration, which has important clinical implications for understanding and treating nerve injuries.

However, the authors should provide more compelling evidence that BDNF is produced by FAPs in response to GDNF signaling. The suggestion that Schwann cell-derived GDNF is responsible for up regulation of BDNF in the FAPs is primarily indirect, based on the data showing that injection of GDNF into the muscle is sufficient to up regulate BDNF (Fig. 4H). The authors more directly test their hypothesis by administering GDNF blocking antibody and find a trend toward reduced BDNF (Fig. 4S2), but it is not statistically significant at this point. Additional replicates should be performed to determine if BDNF levels are indeed reduced when GDNF is blocked.

Reviewer #1 (Public Review):

Summary:

Using a mouse model of head and neck cancer, Barr et al show that tumor-infiltrating nerves connect to brain regions via the ipsilateral trigeminal ganglion, and they demonstrate the effect this has on behavior. The authors show that there are neurites surrounding the tumors using a WGA assay and show that the brain regions that are involved in this tumor-containing circuit have elevated Fos and FosB expression and increased calcium response. Behaviorally, tumor-bearing mice have decreased nest building and wheel running and increased anhedonia. The behavior, Fos expression, and heightened calcium activity were all decreased in tumor-bearing mice following nociceptor neuron elimination.

Strengths:

This paper establishes that sensory neurons innervate head and neck cancers and that these tumors impact select brain areas. This paper also establishes that behavior is altered following these tumors and that drugs to treat pain restore some but not all of the behavior. The results from the experiments (predominantly gene and protein expression assays, cFos expression, and calcium imaging) support their behavioral findings both with and without drug treatment.

Comments on previously identified weaknesses:

The authors have addressed the majority of my concerns.

Reviewer #2 (Public Review):

Summary:

Cancer treatments are not just about the tumor - there is an ever-increasing need for treating pain, fatigue, and anhedonia resulting from the disease as patients are undergoing successful but prolonged bouts with cancer. Using an implantable oral tumor model in the mouse, Barr et al describe neural infiltration of tumors, and posit that these nerve fibers are transmitting pain and other sensory signals to the brain that reduce pleasure and motivation. These findings are in part supported by anatomical and transcriptional changes in the tumor that suggest sensory innervation, neural tracing, and neural activity measurements. Further, the authors conduct behavior assays in tumor-bearing animals and inhibit/ablate pain sensory neurons to suggest involvement of local sensory innervation of tumors in mediating cancer-induced malaise.

Strengths:

• This is an important area of research that may have implications for improving the quality of life of cancer patients.

• The studies use a combination of approaches (tracing and anatomy, transcriptional, neural activity recordings, behavior assays, loss-of-function) to support their claims.

• Tracing experiments suggest that tumor-innervating afferents are connected to brain nuclei involved in oral pain sensing. Consistent with this, the authors observed increased neural activity in those brain areas of tumor-bearing animals. It should be noted that some of these brain nuclei have also been implicated in cancer-induced behavioral alterations in non-head and neck tumor models.

• Experiments are well-controlled and approaches are validated.

• The paper is well-written and the layout was easy to follow.

Weaknesses/Future Directions:

• The main claim is that tumor-infiltrating nerves underlie cancer-induced behavioral alterations. While the studies are supportive of this conclusion, manipulations in the current study are non-specific, ablating all TRPV1 sensory neurons. A direct test would be to selectively inhibit/ablate nerve fibers innervating the tumor or mouth region.

Reviewer #3 (Public Review):

Summary:

The authors have tested for and demonstrated a physical (i.e., sensory nerves to brain) connection between tumors and parts of the brain which can provide some clues into why there is an increase in depressive disorders in HNSCC patients. While connections such as this have been suspected, this is a novel demonstration pointing to sensory neurons that is accompanied by a remarkable amount of complementary data.

Strengths:

There is substantial evidence provided for the hypotheses tested. The data are largely quite convincing.

Weaknesses:

The authors mention in their Discussion the need for additional experiments. that address some of the gaps in this analysis.

Reviewer #1 (Public Review):

The manuscript involves 11 research vignettes that interrogate key aspects of GnRH pulse generator in two established mouse models of PCOS (peripubertal and prenatal androgenisation; PPA and PNA) (9 of the vignettes focus on the latter model).

A key message of this paper is that the oft-quoted idea of rapid GnRH/LH pulses associated with PCOS is in fact not readily demonstrable in PNA and PPA mice. This is an important message to make known, but when established dogmas are being challenged, the experiments behind them need to be robust. In this case, underpowered experiments and one or two other issues greatly limit the overall robustness of the study.

General critiques

(1) My main concern is that many/most of the experiments were limited to 4-5 mice per group (PPA experiments 1 and 2, PNA experiments 3, 5, 6, 8, and 9). This seems very underpowered for trying to disprove established dogmas (sometimes falling back on "non-significant trends" - lines 105 and 239).

(2) Page 133-142: it is concerning that the PNA mice didn't have elevated testosterone levels, and this clearly isn't the fault of the assay as this was re-tested in the laboratory of Prof Handelsman, an expert in the field, using LCMS. The point (clearly made in lines 315-336 of the Discussion) that elevated testosterone in PNA mice has been shown in some but not other publications is an important concern to describe for the field. However, the fact remains that it IS elevated in numerous studies, and in the current study it is not so, yet the authors go on to present GnRH pulse generator data as characteristic of the PNA model. Perhaps a demonstration of elevated testosterone levels (by LCMS?) should become a standard model validation prerequisite for publishing any PNA model data.

(3) Line 191-196: the lack of a significant increase in LH pulse frequency in PNA mice is based on measurements using reasonable group sizes (7-8), although the sampling frequency is low for this type of analysis (10-minute intervals; 6-minute intervals would seem safer for not missing some pulses). The significance of the LH pulse frequency results is not stated (looks like about p=0.01). The authors note that LH concentration IS elevated (approximately doubled), and this clearly is not caused by an increase in amplitude (Figure 4 G, H, I). These things are worth commenting on in the discussion.

(4) An interesting observation is that PNA mice appear to continue to have cyclical patterns of GnRH pulse generator activity despite reproductive acyclicity as determined by vaginal cytology (lines 209-241). This finding was used to analyse the frequency of GnRH pulse generator SEs in the machine-learning-identified diestrous-like stage of PNA mice and compare it to diestrous control mice (as identified by vaginal cytology?) (lines 245-254). The idea of a cycle stage-specific comparison is good, but surely the only valid comparison would be to use machine-learning to identify the diestrous-like stage in both groups of mice. Why use machine learning for one and vaginal cytology for the other?

Specific points

(5) With regard to point 2 above, it would be helpful to note the age at which the testosterone samples were taken.

(6) Lines 198-205 and 258-266: I think these are repeated measures of ANOVA data? If so, report the main relevant effect before the post hoc test result.

(7) Line 415: I don't think the word "although" works in this sentence.

(8) Lines 514-518: what are the limits of hormone detection in the LCMS assay?

Reviewer #2 (Public Review):

Summary

The authors aimed to investigate the functionality of the GnRH (gonadotropin-releasing hormone) pulse generator in different mouse models to understand its role in reproductive physiology and its implications for conditions like polycystic ovary syndrome (PCOS). They compared the GnRH pulse generator activity in control mice, peripubertal androgen (PPA) treated mice, and prenatal androgen (PNA) exposed mice. The study sought to elucidate how androgen exposure affects the GnRH pulse generator and subsequent LH (luteinizing hormone) secretion, contributing to the pathophysiology of PCOS.

Strengths

(1) Comprehensive Model Selection: The use of both PPA and PNA mouse models allows for a comparative analysis that can distinguish the effects of different timings of androgen exposure.

(2) Detailed Methodology: The methods employed, such as photometry recordings and serial blood sampling, are robust and allow for precise measurement of GnRH pulse generator activity and LH secretion.

(3) Clear Results Presentation: The experimental results are well-documented with appropriate statistical analyses, ensuring the findings are reliable and reproducible.

(4) Relevance to PCOS: The study addresses a significant gap in understanding the neuroendocrine mechanisms underlying PCOS, making the findings relevant to both basic science and potentially clinical research.

Weaknesses

(1) Model Limitations: While the PNA mouse model is suggested as the most appropriate for studying PCOS, the authors acknowledge that it does not completely replicate the human condition, particularly the elevated LH response seen in women with PCOS.

(2) Complex Data Interpretation: The reduced progesterone feedback and its effects on the GnRH pulse generator in PNA mice add complexity to data interpretation, making it challenging to draw straightforward conclusions.

(3) Machine Learning (ML) Selection and Validation: While k-means clustering is a useful tool for pattern recognition, the manuscript lacks detailed justification for choosing this specific algorithm over other potential methods. The robustness of clustering results has not been validated.

(4) Biological Interpretability: Although the machine learning approach identified cyclical patterns, the biological interpretation of these clusters in the context of PCOS is not thoroughly discussed. A deeper exploration of how these clusters correlate with physiological and pathological states could enhance the study's impact.

(5) Sample Size: The study uses a relatively small number of animals (n=4-7 per group), which may limit the generalisability of the findings. Larger sample sizes could provide more robust and statistically significant results.

(6) Scope of Application: The findings, while interesting, are primarily applicable to mouse models. The translation to human physiology requires cautious interpretation and further validation.

Reviewer #3 (Public Review):

Summary:

Zhou and colleagues elegantly used pre-clinical mouse models to understand the nature of abnormally high GnRH/LH pulse secretion in polycystic ovary syndrome (PCOS), a major endocrine disorder affecting female fertility worldwide. This work brings a fundamental question of how altered gonadotropin secretion takes place upstream within the GnRH pulse generator core, which is defined by arcuate nucleus kisspeptin neurons.

Strengths:

The authors use state-of-the-art in vivo calcium imaging with fiber photometry and important physiological manipulations and measurements to dissect the possible neuronal mechanisms underlying such neuroendocrine derangements in PCOS. The additional use of unsupervised k-means clustering analysis for the evaluation of calcium synchronous events greatly enhances the quality of their evidence. The authors nicely propose that neuroendocrine dysfunction in PCOS might involve different setpoints through the hypothalamic-pituitary-gonadal (HPG) axis, and beyond kisspeptin neurons, which importantly pushes our field forward toward future investigations.

Weaknesses:

Although the authors provide important evidence, additional efforts are required to improve the quality of the manuscript and back up their claims. For instance, animal experiments failed to detect high testosterone levels in PNA female mice, a well-established PCOS mouse model. Considering that androgen excess is a hallmark of PCOS, this highly influences the subsequent evaluation of calcium synchronous events in arcuate kisspeptin neurons and the implications for neuroendocrine derangements. Authors also may need to provide LH data from another mouse model used in their work, the peripubertal androgen (PPA) model. Their claims seem to fall short without the pairing evidence of calcium synchronous events in arcuate kisspeptin neurons and LH pulse secretion. Another aspect that requires reviewing, is further exploration of their calcium synchronous events data and the increase of animal numbers in some of their experiments.

Reviewer #1 (Public Review):

Summary:

This paper investigates the mechanism of axon growth directed by the conserved guidance cue UNC-6/Netrin. Experiments were designed to distinguish between alternative models in which UNC-6/Netrin functions as either a short-range (haptotactic) cue or a diffusible (chemotactic) signal that steers axons to their final destinations. In each case, axonal growth cones execute ventrally directed outgrowth toward a proximal source of UNC-6/Netrin. This work concludes that UNC-6/Netrin functions as both a haptotactic and chemotactic cue to polarize the UNC-40/DCC receptor on the growth cone membrane facing the direction of growth. Ventrally directed axons initially contact a minor longitudinal nerve tract (vSLNC) at which UNC-6/Netrin appears to be concentrated before proceeding in the direction of the ventral nerve cord (VNC) from which UNC-6/Netrin is secreted. Time-lapse imaging revealed that growth cones appear to pause at the vSLNC before actively extending ventrally directed filopodia that eventually contact the VNC. Growth cone contacts with the vSLNC were unstable in unc-6 mutants but were restored by the expression of a membrane-tethered UNC-6 in vSLNC neurons. In addition, the expression of membrane-tethered UNC-6/Netrin in the VNC was not sufficient to rescue initial ventral outgrowth in an unc-6 mutant. Finally, dual expression of membrane-tethered UNC-6/Netrin in both vSLNC and VNC partially rescued the unc-6 mutant axon guidance defect, thus suggesting that diffusible UNC-6 is also required. This work is important because it potentially resolves the controversial question of how UNC-6/Netrin directs axon guidance by proposing a model in which both of the competing mechanisms, e.g., haptotaxis vs chemotaxis, are successively employed. The impact of this work is bolstered by its use of powerful imaging and genetic methods to test models of UNC-6/Netrin function in vivo thereby obviating potential artifacts arising from in vitro analysis.

Strengths:

A strength of this approach is the adoption of the model organism C. elegans to exploit its ready accessibility to live cell imaging and powerful methods for genetic analysis.

Weaknesses:

A membrane-tethered version of UNC-6/Netrin was constructed to test its haptotactic role, but its neuron-specific expression and membrane localization are not directly determined although this should be technically feasible. Time-lapse imaging is a key strength of multiple experiments but only one movie is provided for readers to review.

Reviewer #2 (Public Review):

Nichols et al studied the role of axon guidance molecules and their receptors and how these work as long-range and/or local cues, using in-vivo time-lapse imaging in C. elegans. They found that the Netrin axon guidance system works in different modes when acting as a long-range (chemotaxis) cue vs local cue (haptotaxis). As an initial context, they take advantage of the postembryonic-born neuron, PDE, to understand how its axon grows and then is guided into its target. They found that this process occurs in various discrete steps, during which the growth cone migrates and pauses at specific structures, such as the vSLNC. The role of the UNC-6/Netrin and UNC-40/DCC axon guidance ligand-receptor pair was then looked at in terms of its requirement for<br /> (1) initial axon outgrowth direction<br /> (2) stabilization at the intermediate target<br /> (3) directional branching from the sublateral region or<br /> (4) ventral growth from the intermediate target to the VNC.

They found that each step is disrupted in the unc-6/Netrin and unc-40/DCC mutants and observed how the localization of these proteins changed during the process of axon guidance in wild-type and mutant contexts. These observations were further supported by analysis of a mutant important for the regulation of Netrin signaling, the E3 ubiquitin ligase madd-2/Trim9/Trim67. Remarkably, the authors identified that this mutant affected axonal adhesion and stabilization, but not directional growth. Using membrane-tethered UNC-6 to specific localities, they then found this to be a consequence of the availability of UNC-6 at specific localities within the axon growth path. Altogether, this data and in-vivo analysis provide compelling evidence of the mechanistic foundation of Netrin-mediated axon guidance and how it works step by step.

The conclusions are well-supported, with both imaging and quantification of each step of axon guidance and localization of UNC-6 and UNC-40. Using a different type of neuron to validate their findings further supports their conclusions and strengthens their model. It's not yet known whether this model holds true for other ligand-receptor pairs, but the current work sets the stage for future analysis of other axon guidance molecules using time-lapse in-vivo imaging. There are still two outstanding questions that are important to address to support the authors' model and conclusions.

(1) The results of UNC-6-TM expression at different locations are clear and support the conclusions but need to consider that there's no diffusible UNC-6 available. What would happen if UNC-6 is tethered to the membrane in an otherwise completely 'normal' UNC-6 gradient. Does the axon guidance ensue normally or does it get stuck in the respective site of the membrane tethered-UNC-6 and doesn't continue to outgrow properly? This is an important control (expression of the UNC-6-TM at the vSLNC or VNC in the wild type background) that would help clarify this question and gain a better insight into the separability of both axon guidance steps and the ability to manipulate these.

(2) Axon guidance systems do not work in a vacuum and are generally competing against each other. For example, the SLT-1/Slit and SAX-3/ROBO axon guidance ligand-receptor pair is also required for PDE, and other post-embryonic neurons, axon guidance. It would be interesting to test mutants for these genes with the membrane tethered-UNC-6 to determine if the different steps of axon guidance are disrupted and if so, to what degree these are disrupted.

Reviewer #3 (Public Review):

Summary:

This manuscript from Nichols, Lee, and Shen tackles an important question of how unc6/netrin promotes axon guidance: i.e. haptotaxis vs chemotaxis. This has recently been a large topic of investigation and discussion in the axon guidance field. Using live cell imaging of unc6/netrin and unc40/DCC in several neurons that extend axons ventrally during development, as well as TM localized mutants of Unc6, they suggest that unc6 promotes first haptotaxis of the emerging growth cone followed by chemotaxis of the growth cone. This is timely, as a recent preprint from the Lundquist group, using a similar strategy to make only a TM anchored unc6 similarly found that this could rescue only the haptotaxis-like growth of the PDE neuron, but not the second phase of growth. However, their conclusions were quite different based on the overexpression of unc6 everywhere rescuing the second phase, and thus they conclude that a gradient is not present.

Strengths:

As this has been quite a controversy in both the invertebrate and vertebrate field, one strength of this paper is that they use an unc6-neon green to demonstrate unc6 localization, and show a gradient of localization.

Weaknesses:

This is important, although it could be strengthened by first showing a more zoomed-out image of unc6 in the animal, and second demonstrating the localization of the transmembrane anchored unc6 mutants, to help define what may be the "diffusible Unc6". I suggest two additional experimental or analysis suggestions: First, the authors clarify the phenotype of ventral emergence of the growth cone. Though the manuscript images suggest that no matter the mutant there is ventral emergence of the growth cone, but then later defects, yet they claim ventral emergence defects with the UNC6 tethered mutants, but there is no comparison of rose plots. This is confusing and needs to be addressed. Second, I have concerns that the analysis of unc40 polarization may be misleading in some cases when there appears to indeed be accumulation in the growth cone, but since the only analysis shown is relative to the rest of the cell, that can be lost.

Reviewer #1 (Public Review):

Summary:

In this study, Setogawa et al. employ an auditory discrimination task in freely moving rats, coupled with small animal imaging, electrophysiological recordings, and pharmacological inhibition/lesioning experiments to better understand the role of two striatal subregions: the anterior Dorsal Lateral Striatum (aDLS) and the posterior Ventrolateral Striatum (pVLS), during auditory discrimination learning. Attempting to better understand the contribution of different striatal subregions to sensory discrimination learning strikes me as a highly relevant and timely question, and the data presented in this study are certainly of major interest to the field. The authors have set up a robust behavioral task and systematically tackled the question about a striatal role in learning with multiple observational and manipulative techniques. Additionally, the structured approach the authors take by using neuroimaging to inform their pharmacological manipulation experiments and electrophysiological recordings is a strength.

However, the results as they are currently presented are not easy to follow and could use some restructuring, especially the electrophysiology. Also, the main conclusion that the authors draw from the data, that aDLS and pVLS contribute to different phases of discrimination learning and influence the animal's response strategy in different ways, is not strongly supported by the data and deserves some additional caveats and limitations of the study in the discussion.

Strengths:

See above. In addition, the electrophysiology data is a major strength.

Weaknesses:

(1) The authors have rigorously used PET neuroimaging, which is an interesting non-invasive method to track brain activity during behavioral states. However, in the case of a freely moving behavior where the scans are performed ~30 minutes after the behavioral task, it is unclear what conclusions can be drawn about task-specific brain activity. The study hinges on the neuroimaging findings that both areas of the lateral striatum (aDLS and pVLS) show increased activity during acquisition, but the DMS shows a reduction in activity during the late stages of behavior, and some of these findings are later validated with complementary experiments. However, the limitations of this technique can be further elaborated on in the discussion and the conclusions.

a) In commenting on the unilateral shifts in brain striatal activity during behavior, the authors use the single lever task as a control, where many variables affecting neuronal activity might be different than in the discriminatory task. The study might be better served using Day 2 measurements as a control against which to compare activity of all other sessions since the task structures are similar.<br /> b) From the plots in J, K, and L, it seems that shifts in activity in the different substructures are not unilateral but consistently bilateral, in contrast to what is mentioned in the text. Possibly the text reflects comparisons to the single lever task, and here again, I would emphasize comparing within the same task.

(2) In Figure 2, the authors present compelling data that chronic excitotoxic lesions with ibotenic acid in the aDLS, pVLS, and DMS produce differential effects on discrimination learning. However, the significant reduction in success rate of performance happens as early as Day 6 in both IBO groups in both aDLS and pVLS mice. This would seem to agree with conclusions drawn about the role of aDLS in the middle stages of learning in Figure 2, but not the pVLS, which only shows an increased activity during the late stages of the behavior.

(3) In Figure 4, the authors show interesting data with transient inactivation of subregions of the striatum with muscimol, validating their findings that the aDLS mediates the middle and the pVLS the late stages of learning, and the function of each area serves different strategies. However, the inference that aDLS inactivation suppresses the WSW strategy "moderately" is not reflected in the formal statistical value p=0.06. While there still may be a subtle effect, the authors would need to revise their conclusions appropriately to reflect the data. In addition, the authors could try a direct comparison between the success rate during muscimol inhibition in the mid-learning session between the aDLS and pVLS-treated groups in Figure 4C (middle) and 4D (middle). If this comparison is not significant, the authors should be careful to claim that inhibition of these two areas differentially affects behavior.

(4) The authors have used in-vivo electrophysiological techniques to systematically investigate the roles of the aDLS and the pVLS in discriminatory learning, and have done a thorough analysis of responses with each phase of behavior over the course of learning. This is a commendable and extremely informative dataset and is a strength of the study. However, the result could be better organized following the sequence of events of the behavioral task to give the reader an easier structure to follow. Ideally, this would involve an individual figure to compare the responses in both areas to Cue, Lever Press, Reward Sound, and First Lick (in this order).

(5) An important conceptual point presented in the study is that the aDLS neurons, with learning, show a reduction in firing rates and responsiveness to the first lick as well as the behavioral outcome, and don't play a role in other task-related events such as cue onset. However, the neuroimaging data in Figure 2 seems to suggest a transient enhancement of aDLS activity in the mid-stage of discriminatory learning, that is not reflected in the electrophysiology data. Is there an explanation for this difference?

(6) A significant finding of the study is that CO-HR and CO-LL responses are strikingly obvious in the pVLS, but not in the aDLS, in line with the literature that the posterior (sensory) striatum processes sound. This study also shows that responses to the high-frequency tone indicating a correct right-lever choice increase with learning in contrast to the low-frequency tone responses. To further address whether this difference arises from the task contingency, and not from the frequency representation of the pVLS, an important control would be to switch the cue-response association in a separate group of mice, such that high-frequency tones require a left lever press and vice versa. This would also help tease apart task-evoked responses in the aDLS, as I am given to understand all the recording sites were in the left striatum.

Reviewer #2 (Public Review):

The study by Setogawa et al. aims to understand the role that different striatal subregions belonging to parallel brain circuits have in associative learning and discrimination learning (S-O-R and S-R tasks). Strengths of the study are the use of multiple methodologies to measure and manipulate brain activity in rats, from microPET imaging to excitotoxic lesions and multielectrode recordings across anterior dorsolateral (aDLS), posterior ventral lateral (pVLS)and dorsomedial (DMS) striatum.

The main conclusions are that the aDLS promotes stimulus-response association and suppresses response-outcome associations. The pVLS is engaged in the formation and maintenance of the stimulus-response association. There is a lot of work done and some interesting findings however, the manuscript can be improved by clarifying the presentation and reasoning. The inclusion of important controls will enhance the rigor of the data interpretation and conclusions.

Reviewer #1 (Public Review):

In this study, Li et al. aim to determine the effect of navigational experience on visual representations of scenes. Participants first learn to navigate within simple virtual environments where navigation is either unrestricted or restricted by an invisible wall. Environments are matched in terms of their spatial layout and instead differ primarily in terms of their background visual features. In a later same/different task, participants are slower to distinguish between pairs of scenes taken from the same navigation condition (i.e. both restricted or both unrestricted) than different navigation conditions. Neural response patterns in the PPA also discriminate between scenes from different navigation conditions. These results suggest that navigational experience influences perceptual representations of scenes. This is an interesting study, and the results and conclusions are clearly explained and easy to follow. There are a few points that I think would benefit from further consideration or elaboration from the authors, which I detail below.

First, I am a little sceptical of the extent to which the tasks are able to measure navigational or perceptual experience with the scenes. The training procedure seems like it wouldn't require obtaining substantial navigational experience as the environments are all relatively simple and only require participants to follow basic paths, rather than encouraging more active exploration of a more complex environment. Furthermore, in the same/different task, all images show the same view of the environment (meaning they show the exact same image in the "same environment" condition). The task is therefore really a simple image-matching task and doesn't require participants to meaningfully extract the perceptual or spatial features of the scenes. An alternative would have been to present different views of the scenes, which would have prevented the use of image-matching and encouraged further engagement with the scenes themselves. Ultimately, the authors do still find a response time difference between the navigation conditions, but the effect does appear quite small. I wonder if the design choices could be obscuring larger effects, which might have been better evident if the navigational and perceptual tasks had encouraged greater encoding of the spatial and perceptual features of the environment. I think it would be helpful for the authors to explain their reasons for not employing such designs, or to at least give some consideration to alternative designs.

Figure 1B illustrates that the non-navigable condition includes a more complicated environment than the navigable condition, and requires following a longer path with more turns in it. I guess this is a necessary consequence of the experiment design, as the non-navigable condition requires participants to turn around and find an alternative route. Still, this does introduce spatial and perceptual differences between the two navigation conditions, which could be a confounding factor. What do the response times for the "matched" condition in the same/different task look like if they are broken down by the navigable and non-navigable environments? If there is a substantial difference between them, it could be that this is driving the difference between the matched and mismatched conditions, rather than the matching/mismatching experience itself.

In both experiments, the authors determined their sample sizes via a priori power analyses. This is good, but a bit more detail on these analyses would be helpful. How were the effect sizes estimated? The authors say it was based on other studies with similar methodologies - does this mean the effect sizes were obtained from a literature search? If so, it would be good to give some details of the studies included in this search, and how the effect size was obtained from these (e.g., it is generally recommended to take a lower bound over studies). Or is the effect size based on standard guidelines (e.g., Cohen's d ≈ 0.5 is a medium effect size)? If so, why are the effect sizes different for the two studies?

Reviewer #2 (Public Review):

Summary:

Li and colleagues applied virtual reality (VR) based training to create different navigational experiences for a set of visually similar scenes. They found that participants were better at visually discriminating scenes with different navigational experiences compared to scenes with similar navigational experiences. Moreover, this experience-based effect was also reflected in the fMRI data, with the PPA showing higher discriminability for scenes with different navigational experiences. Together, their results suggest that previous navigational experiences shape visual scene representation.

Strengths:

(1) The work has theoretical value as it provides novel evidence to the ongoing debate between visual and non-visual contributions to scene representation. While the idea that visual scene representation can encode navigational affordances is not new (e.g., Bonner & Epstein, 2017, PNAS), this study is one of the first to demonstrate that navigational experiences can causally shape visual scene representation. Thus, it serves as a strong test for the hypothesis that our visual scene representations involve encoding top-down navigational information.

(2) The training paradigm with VR is novel and has the potential to be used by the broader community to explore the impact of experience on other categorical visual representations.

(3) The converging evidence from behavioral and fMRI experiments consolidates the work's conclusion.

Weaknesses:

(1) While this work attempts to demonstrate the effect of navigational experience on visual scene representation, it's not immediately clear to what extent such an effect necessarily reflects altered visual representations. Given that scenes in the navigable condition were more explored and had distinct contextual associations than scenes in the non-navigable condition (where participants simply turned around), could the shorter response time for a scene pair with mismatched navigability be explained by the facilitation of different contextual associations or scene familiarities, rather than changes in perceptual representations? Especially when the visual similarity of the scenes was high and different visual cues might not have been immediately available to participants, the different contextual associations and/or familiarity could serve as indirect cues to facilitate participants' judgment, even if perceptual representations remained intact.

(2) Similarly, the above-chance fMRI classification results in the PPA could also be explained by the different contextual associations and/or scene familiarities between navigable and non-navigable scenes, rather than different perceptual processes related to scene identification.

(3) For the fMRI results, the specificity of the experience effect on the PPA is not strictly established, making the statement "such top-down effect was unique to the PPA" groundless. A significant interaction between navigational conditions and ROIs would be required to make such a claim.

(4) For the behavioral results, the p-value of the interaction between groups and the navigational conditions was 0.05. I think this is not a convincing p-value to rule out visual confounding for the training group. Moreover, from Figure 2B, there appears to be an outlier participant in the control group who deviates dramatically from the rest of the participants. If this outlier is excluded, will the interaction become even less significant?

(5) Experiment 1 only consists of 25 participants in each group. This is quite a small sample size for behavioral studies when there's no replication. It would be more convincing if an independent pre-registered replication study with a larger sample size could be conducted.

Reviewer #1 (Public Review):

The authors conducted cross-species comparisons between the human brain and the macaque brain to disentangle the specific characteristics of structural development of the human brain. Although previous studies had revealed similarities and differences in brain anatomy between the two species by spatially aligning the brains, the authors made the comparison along the chronological axis by establishing models for predicting the chronological ages with the inputting brain structural features. The rationale is actually clear given that brain development occurs over time in both. More interestingly, the model trained on macaque data was better able to predict the age of humans than the human-trained model was at predicting macaque age. This revealed a brain cross-species age gap (BCAP) that quantified the discrepancy in brain development between the two species, and the authors even found this BCAP measure was associated with performance on behavioral tests in humans. Overall, this study provides important and novel insights into the unique characteristics of human brain development. The authors have employed a rigorous scientific approach, reflecting diligent efforts to scrutinize the patterns of brain age models across species. The clarity of the rationale, the interpretability of the methods, and the quality of the presentation all contribute to the strength of this work.

Reviewer #2 (Public Review):

In the current study, Li et al. developed a novel approach that aligns chronological age to a cross-species brain age prediction model to investigate the evolutionary effect. This method revealed some interesting findings, like the brain-age gap of the macaque model in predicting human age will increase as chronological age increases, suggesting an evolutionary alignment between the macaque brain and the human brain in the early stage of development. This study exhibits ample novelty and research significance. However, I still have some concerns regarding the reliability of the current findings.

(1) Although the authors named their new method a "cross-species" model, the current study only focused on the prediction between humans and macaques. It would be better to discuss whether their method can also generalize to cross-species examination of other species (e.g., C. elegans), which may provide more comprehensive evolutionary insights. Also, other future directions with their new method are worth discussing.

(2) Algorithm of prediction model. In the method section, the authors only described how they chose features, but did no description about the algorithm (e.g., supporting vector regression) they used. Please add relevant descriptions to the methods.

(3) Sex difference. The sex difference results are strange to me. For example, in the second row of Figure Supplement 3A, different models show different correlation patterns, but why their Pearson's r is all equal to 0.3939? If they are only typo errors, please correct them. The authors claimed that they found no sex difference. However, the results in Figure Supplement 3 show that, the female seems to have poorer performance in predicting macaque age from the human model. Moreover, accumulated studies have reported sex differences in developing brains (Hines, 2011; Kurth et al., 2021). I think it is also worth discussing why sex differences can't be found in the evolutionary effect.

Reference:<br /> Hines, M. (2011). Gender development and the human brain. Annual review of neuroscience, 34, 69-88.<br /> Kurth, F., Gaser, C., & Luders, E. (2021). Development of sex differences in the human brain. Cognitive Neuroscience, 12(3-4), 155-162.

Reviewer #3 (Public Review):

SUMMARY:

The authors identified a series of WM and GM features that correlated with age in human and macaque structural imaging data. The data was gathered from the HCP and WA studies, which was parcellated in order to yield a set of features. Features that correlated with age were used to train predictive intra and inter-species models of human and macaque age. Interestingly, while each model accurately predicted the corresponding species age, using the macaque model to predict human age was more accurate than the inverse (using the human model to predict macaque age). In addition, the prediction error of the macaque model in predicting human age increased with age, whereas the prediction error of the human model predicting macaque age decreased with age.

After elaboration of the predictive models, the authors classified the features for prediction into human-specific, macaque-specific and common to human and macaque, where they most notably found that macaque-only and common human-macaque areas were located mainly in gray matter, with only a few human-specific features found in gray matter. Furthermore, the authors found significant correlations between BCAP and picture vocabulary (positive correlation) test and visual sensitivity (negative correlation) test. Several white matter tracts (AF, OR, SLFII) were also identified showing a correlation with BCAP.

STRENGTHS AND WEAKNESSES

The paper brings an interesting perspective on the evolutionary trajectories of human and non-human primate brain structure, and its relation to behavior and cognition. Overall, the methods are robust and support the theoretical background of the paper. However, the overall clarity of the paper could be improved. There are many convoluted sentences and there seems to be both repetition across the different sections and unclear or missing information. For example, the Introduction does not clearly state the research questions, rather just briefly mentions research gaps existing in the literature and follows by describing the experimental method. It would be desirable to clearly state the theoretical background and research questions and leave out details on methodology.<br /> In addition, the results section repeats a lot of what is already stated in the methods. This could be further simplified and make the paper much easier to read.<br /> In the discussion, authors mention that "findings about cortex expansion are inconsistent and even contradictory", a more convincing argument could be made by elaborating on why the cortex expansion index is inadequate and how BCAP is more accurate.

STUDY AIMS AND STRENGTH OF CONCLUSIONS

Overall, the methods are robust and support the theoretical background of the paper, but it would be good to state the specific research questions -even if exploratory in nature- more specifically. Nevertheless, the results provide support for the research aims.

IMPACT OF THE WORK AND UTILITY OF METHODS AND DATA TO THE COMMUNITY

This study is a good first step in providing a new insight into the neurodevelopmental trajectories of humans and non-human primates besides the existing cortical expansion theories.

ADDITIONAL CONTEXT:

It should be clearly stated both in the abstract and methods that the data used for the experiment came from public databases.

Reviewer #1 (Public Review):

Using structural analysis, Bonchuk and colleagues demonstrate that the TTK-like BTB/POZs of insects form stable hexameric assemblies composed of trimers of POZ dimers, a configuration observed consistently across both homomultimers and heteromultimers, which are known to be formed by TTK-like BTB/POZ domains. The structural data is comprehensive, unambiguous, and further supported by theoretical fold prediction analyses. In particular the judicious complementation of experiments and fold prediction is commendable. This study now adds an important cog that might help generalize the general principles of the evolution of multimerization in members of this fold family.

I strongly feel that enhancing the inclusivity of the discussion would strengthen the paper. Below, I suggest some additional points for consideration for the same.

Major points.<br /> (1) It would be valuable to discuss alternative multimer assembly interfaces, considering the diverse ways POZs can multimerize. For instance, the Potassium channel POZ domains form tetramers. A comparison of their inter-subunit interface with that of TTK and non-TTK POZs could provide insightful contrasts.

(2) The so-called TTK motif, despite its unique sequence signature, essentially corresponds to the N-terminal extension observed in other "non-TTK" proteins such as Miz-1. Given Miz-1's structure, it becomes evident that the utilization of the N-terminal extension for dimerization is shared with the TTK family, suggesting a common evolutionary origin in metazoan transcription factors. Early phylogenetic trees (e.g. in PMID: 9917379) support the grouping of the TTK-like POZs with other animal Transcription factors containing POZ domains such as those with Kelch repeats further suggesting that the extension might be ancestral. Structural investigations by modeling prominent examples or comparing known structures of similar POZ domains, could support this inference. Control comparisons with POZ domains from fungi, plants and amoebozoans like Dictyostelium could offer additional insights.

(3) Exploring the ancestral presence of the aforementioned extension in metazoan transcription factors could serve as a foundation for understanding the evolutionary pathway of hexamerization. This analysis could shed light on exposed structural regions that had the potential to interact post-dimerization with the N-terminal extension and also might provide insights into the evolution of multimer interfaces, as observed in the Potassium channel.

(4) Considering the role of conserved residues in the multimer interface is crucial. Reference to conserved residues involved in multimer formation, such as discussed in PMID: 9917379, would enrich the discussion.

Reviewer #1 (Public Review):

This report describes work aiming to delineate multi-modal MRI correlates of psychopathology from a large cohort of children of 9-11 years from the ABCD cohort. While uni-modal characterisations have been made, the authors rightly argue that multi-modal approaches in imaging are vital to comprehensively and robustly capture modes of large-scale brain variation that may be associated with pathology. The primary analysis integrates structural and resting-state functional data, while post-hoc analyses on subsamples incorporate task and diffusion data. Five latent components (LCs) are identified, with the first three, corresponding to p-factor, internal/externalising, and neurodevelopmental Michelini Factors, described in detail. In addition, associations of these components with primary and secondary RSFC functional gradients were identified, and LCs were validated in a replication sample via assessment of correlations of loadings.

This work is clearly novel and a comprehensive study of associations within this dataset. Multi-modal analyses are challenging to perform, but this work is methodologically rigorous, with careful implementation of discovery and replication assessments, and primary and exploratory analyses. The ABCD dataset is large, and behavioural and MRI protocols seem appropriate and extensive enough for this study. The study lays out comprehensive associations between MRI brain measures and behaviour that appear to recapitulate the established hierarchical structure of psychopathology.

The work does have weaknesses, some of them acknowledged. There is limited focus on the strength of observed associations. While the latent component loadings seem reliably reproducible in the behavourial domain, this is considerably less the case in the imaging modalities. A considerable proportion of statistical results focuses on spatial associations in loadings between modalities - it seems likely that these reflect intrinsic correlations between modalities, rather than associations specific to any latent component. Assessment of associations with functional gradients is similarly a little hard to interpret. Thus, it is hard to judge the implications for our understanding of the neurophysiological basis of psychopathology and the ability of MRI to provide clinical tools for, say, stratification. The observation of a recapitulation of psychopathology hierarchy may be somewhat undermined by the relatively modest strength of the components in the imaging domain. The task fMRI was assessed with a fairly basic functional connectivity approach, not using task timings to more specifically extract network responses.

Overall, the authors achieve their aim to provide a detailed multimodal characterisation of MRI correlations of psychopathology. Code and data are available and well organised and should provide a valuable resource for researchers wanting to understand MRI-based neural correlates of psycho-pathology-related behavioural traits in this important age group. It is largely a descriptive study, with comparisons to previous uni-modal work, but without particularly strong testing of neuroscience hypotheses.

Reviewer #2 (Public Review):

In "Multi-modal Neural Correlates of Childhood Psychopathology" Krebets et al. integrate multi-modal neuroimaging data using machine learning to delineate dissociable links to diverse dimensions of psychopathology in the ABCD sample. This paper had numerous strengths including a superb use of a large resource dataset, appropriate analyses, beautiful visualizations, clear writing, and highly interpretable results from a data-driven analysis. Overall, I think it would certainly be of interest to a general readership.

That being said, I do have several comments for the authors to consider.

- Out-of-sample testing: while the permutation testing procedure for the PLS is entirely appropriate, without out-of-sample testing the reported effect sizes are likely inflated.

- Site/family structure: it was unclear how site/family structure were handled as covariates.

- Anatomical features: I was a bit surprised to see volume, surface area, and thickness all evaluated - and that there were several comments on the correspondence between the SA and volume in the results section. Given that cortical volume is simply a product of SA and CT (and mainly driven by SA), this result may be pre-required.

- Ethnicity: the rationale for regressing ethnicity from the data was unclear and may conflict with current best practices.

- Data quality: the authors did an admirable job in controlling for data quality in the analyses of functional connectivity data. However, it is unclear if a comparable measure of data quality was used for the T1/dMRI analyses. This likely will result in inflated effect sizes in some cases; it has the potential to reduce sensitivity to real effects.

Reviewer #3 (Public Review):

In this study, the authors utilized the Adolescent Brain Cognitive Development dataset to investigate the relationship between structural and functional brain network patterns and dimensions of psychopathology. They identified multiple components, including a general psychopathology (p) factor that exhibited a strong association with multimodal imaging features. The connectivity signatures associated with the p factor and neurodevelopmental dimensions aligned with the sensory-to-transmodal axis of cortical organization, which is linked to complex cognition and psychopathology risk. The findings were consistent across two separate subsamples and remained robust when accounting for variations in analytical parameters, thus contributing to a better understanding of the biological mechanisms underlying psychopathology dimensions and offering potential brain-based vulnerability markers.

Strengths:<br /> - An intriguing aspect of this study is the integration of multiple neuroimaging modalities, combining structural and functional measures, to comprehensively assess the covariance with various symptom combinations. This approach provides a multidimensional understanding of the risk patterns associated with mental illness development.

- The paper delves deeper into established behavioral latent variables such as the p factor, internalizing, externalizing, and neurodevelopmental dimensions, revealing their distinct associations with morphological and intrinsic functional connectivity signatures. This sheds light on the neurobiological underpinnings of these dimensions.

- The robustness of the findings is a notable strength, as they were validated in a separate replication sample and remained consistent even when accounting for different parameter variations in the analysis methodology. This reinforces the generalizability and reliability of the results.

Weaknesses:

- Based on their findings, the authors suggest that the observed variations in resting-state functional connectivity may indicate shared neurobiological substrates specific to certain symptoms. However, it should be noted that differences in resting-state connectivity between groups can stem from various factors, as highlighted in the existing literature. For instance, discrepancies in the interpretation of instructions during the resting state scan can influence the results. Hence, while their findings may indicate biological distinctions, they could also reflect differences in behavior.

- The authors conducted several analyses to investigate the relationship between imaging loadings associated with latent components and the principal functional gradient. They found several associations between principal gradient scores and both within- and between-network resting-state functional connectivity (RSFC) loadings. Assessing the analysis presented here proves challenging due to the nature of relating loadings, which are partly based on the RSFC, to gradients derived from RSFC. Consequently, a certain level of correlation between these two variables would be expected, making it difficult to determine the significance of the authors' findings. It would be more intriguing if a direct correlation between the composite scores reflecting behavior and the gradients were to yield statistically significant results.

- Lastly, regarding the interpretation of the first identified latent component, I have some reservations. Upon examining the loadings, it appears that LC1 primarily reflects impulse control issues rather than representing a comprehensive p-factor. Furthermore, it is worth noting that within the field, there is an ongoing debate concerning the interpretation and utilization of the p-factor. An insightful publication on this topic is "The p factor is the sum of its parts, for now" (Fried et al, 2021), which explains that the p-factor emerges as a result of a positive manifold, but it does not necessarily provide insights into the underlying mechanisms that generated the data.

Reviewer #1 (Public Review):

In this manuscript, the authors present Tronko, a novel tool for performing phylogenetic assignment of DNA sequences using an approximate likelihood approach. Through a benchmark experiment utilizing several real datasets from mock communities with pre-known composition as well as simulated datasets, the authors show that Tronko is able to achieve higher accuracy than several existing best-practice methods with runtime comparable to the fastest existing method, albeit with significantly higher peak memory usage than existing methods. The benchmark experiment was thorough, and the results clearly support the authors' conclusions. However, the paper could be improved by exploring how certain design choices (e.g. tool selection and parameter choices) may impact Tronko's performance/accuracy, and some relevant existing phylogenetic placement tools are missing and should be included.

Reviewer #2 (Public Review):

This is, to my knowledge, the most scalable method for phylogenetic placement that uses likelihoods. The tool has an interesting and innovative means of using gaps, which I haven't seen before. In the validation the authors demonstrate superior performance to existing tools for taxonomic annotation (though there are questions about the setup of the validation as described below).

The program is written in C with no library dependencies. This is great. However, I wasn't able to try out the software because the linking failed on Debian 11, and the binary artifact made by the GitHub Actions pipeline was too recent for my GLIBC/kernel. It'd be nice to provide a binary for people stuck on older kernels (our cluster is still on Ubuntu 18.04). Also, would it be hard to publish your .zipped binaries as packages?

Thank you for publishing your source files for the validation on zenodo. Please provide a script that would enable the user to rerun the analysis using those files, either on zenodo or on GitHub somewhere.

The validations need further attention as follows.

First, the authors have not chosen data sets that are not well-aligned with real-world use cases for this software, and as a result, its applicability is difficult to determine. First, the leave-one-species-out experiment made use of COI gene sequences representing 253 species from the order Charadriiformes, which includes bird species such as gulls and terns. What is the reasoning for selecting this data set given the objective of demonstrating the utility of Tronko for large scale community profiling experiments which by their nature tend to include microorganisms as subjects? If the authors are interested in evaluating COI (or another gene target) as a marker for characterizing the composition of eukaryotic populations, is the heterogeneity and species distribution of bird species within order Charadriiformes comparable to what one would expect in populations of organisms that might actually be the target of a metagenomic analysis?

Second, It appears that experiments evaluating performance for 16S were limited to reclassification of sequencing data from mock communities described in two publications, Schirmer (2015, 49 bacteria and 10 archaea, all environmental), and Gohl (2016; 20 bacteria - this is the widely used commercial mock community from BEI, all well-known human pathogens or commensals). The authors performed a comparison with kraken2, metaphlan2, and MEGAN using both the default database for each as well as the same database used for Tronko (kudos for including the latter). This pair of experiments provide a reasonable high-level indication of Tronko's performance relative to other tools, but the total number of organisms is very limited, and particularly limited with respect to the human microbiome. It is also important to point out that these mock communities are composed primarily of type strains and provide limited species-level heterogeneity. The performance of these classification tools on type strains may not be representative of what one would find in natural samples. Thus, the leave-one-individual-out and leave-one-species-out experiments would have been more useful and informative had they been applied to extended 16S data sets representing more ecologically realistic populations.

Finally, the authors should describe the composition of the databases used for classification as well as the strategy (and toolchain) used to select reference sequences. What databases were the reference sequences drawn from and by what criteria? Were the reference databases designed to reflect the composition of the mock communities (and if so, are they limited to species in those communities, or are additional related species included), or have the authors constructed general purpose reference databases? How many representatives of each species were included (on average), and were there efforts to represent a diversity of strains for each species? The methods should include a section detailing the construction of the data sets: as illustrated in this very study, the choice of reference database influences the quality of classification results, and the authors should explain the process and design considerations for database construction.

Reviewer #3 (Public Review):

Pipes and Nielsen propose a valuable new computational method for assigning individual Next Generation Sequencing (NGS) reads to their taxonomic group of origin, based on comparison with a dataset of reference metabarcode sequences (i.e. using an existing known marker sequence such as COI or 16S). The underlying problem is an important one, with broad applications such as identifying species of origin of smuggled goods, identifying the composition of metagenomics/ microbiomics samples, or detecting the presence of pathogen variants of concern from wastewater surveillance samples. Pipes and Nielsen propose (and make available with open source software) new computational methods, apply those methods to a series of exemplar data analyses mirroring plausible real-life scenarios, and compare the new method's performance to that of various field-leading alternative methods.

In terms of methodology, the manuscript presents a novel computational analyses inspired by standard existing probabilistic phylogenetic models for the evolution of genome sequences. These form the basis for comparisons of each NGS read with a reference database of known examples spanning the taxonomic range of interest. The evolutionary aspects of the models are used (a) to statistically represent knowledge about the reference organisms (and uncertainty about their common ancestors) and their evolutionary relationships; and (b) to derive inferences about the relationship of the sample NGS reads that may be derived from reference organisms or from related organisms not represented in the reference dataset. This general approach has been considered previously and, while expected to be powerful in principle, the reliance of those methods on likelihood computations over a phylogenetic tree structure means they are slow to the point of useless on modern-sized problems that may have many thousands of reference sequences and many millions of NGS reads. Alternative methods that have been devised to be computationally feasible have had to sacrifice the phylogenetic approach, with a consequent loss of statistical power.

Pipes and Nielsen's methodology contribution in this manuscript is to make a series of approximations to the 'ideal' phylogenetic likelihood analysis, aimed at saving computational time and keeping computer memory requirements acceptable whilst retaining as much as possible of the expected power of phylogenetic methods. Their description of their novel methods is solid; as they are largely approximations to other existing methods, their value ultimately will rest with the success of the method in application.

Regarding the application of the new methods, to compare the accuracy of their method with a selection of existing methods the authors use 1) simulated datasets and 2) previously published mock community datasets to query sequencing reads against appropriate reference trees. The authors show that Tronko has a higher success at assigning query reads (at the species/genus/family level) than the existing tools with both datasets. In terms of computational performance, the authors show Tronko outperforms another phylogenetic tool, and is still within reasonable limits when compared with other 'lightweight' tools.

As a demonstration of the power of phylogeny-based methods for taxonomic assignment, this ms. could gain added importance by refocusing the community towards explicitly phylogenetic methods. We agree with the authors that this would be likely to give rise to the most powerful possible methods.

Strengths of this ms. are 1) the focus on phylogenetic approaches and 2) the reduction of a consequently difficult computational problem to a practical method (with freely available software); 3) the reminder that these approaches work well and are worthy of continued interest and development; and ultimately most-importantly 4) the creation of a powerful tool for taxonomic assignment that seems to be at least as good as any other and generally better.

Weaknesses of the manuscript at present are 1) lack of consideration of some other existing methods and approaches, as it would be interesting to know if other ideas had been tried and rejected, or were not compatible with the methods created; 2) some over-simplifications in the description of new methods, with some aspects difficult or impossible to reproduce and some claims unsubstantiated. Further, 3) we are not convinced enough weight has been given to the complexity of 'pre-processing' the reference dataset for each metabarcode (e.g. gene) of interest, which may give the impression that the method is easier to apply to new reference datasets than we think would be the case. Lastly, 4) we encountered some difficulties getting the software installed and running on our computers. It was not possible to resolve every issue in the time available to us to perform our review, and some processing options remain untested.

Overall, the methods that Pipes and Nielsen propose represent an important contribution that both creates a computational resource that is immediately valuable to the community, and emphasises the benefits of phylogenetic methods and provides encouragement for others to continue to work in this area to create still-better methods.

Reviewer #1 (Public Review):

In this manuscript, Perez-Lopez et al. examine the function of the chemokine CCL28, which is expressed highly in mucosal tissues during infection, but its role during infection is poorly understood. They find that CCL28 promotes neutrophil accumulation in the intestines of mice infected with Salmonella and in the lungs of mice infected with Acinetobacter. They find that Ccl28-/- mice are highly susceptible to Salmonella infection, and highly resistant and protected from lethality following Acinetobacter infection. They find that neutrophils express the CCL28 receptors CCR3 and CCR10. CCR3 was pre-formed and intracellular and translocated to the cell surface following phagocytosis or inflammatory stimuli. They also find that CCL28 stimulation of CCR3 promoted neutrophil antimicrobial activity, ROS production, and NET formation, using a combination of primary mouse and human neutrophils for their studies. Overall, the authors' findings provide new and fundamental insight into the role of the CCL28:CCR3 chemokine:chemokine receptor pair in regulating neutrophil recruitment and effector function during infection with the intestinal pathogen Salmonella Typhimurium and the lung pathogen Acinetobacter baumanii.

Reviewer #2 (Public Review):

In this manuscript by Perez-Lopez et al., the authors investigate the role of the chemokine CCL28 during bacterial infections in mucosal tissues. This is a well-written study with exciting results. They show a role for CCL28 in promoting neutrophil accumulation to the guts of Salmonella-infected mice and to the lung of mice infected with Acinetobacter. Interestingly, the functional consequences of CCL28 deficiency differ between infections with the two different pathogens, with CCL28-deficiency increasing susceptibility to Salmonella, but increasing resistance to Acinetobacter. The underlying mechanistic reasons for this suggest roles for CCL28 in enhanced neutrophil antimicrobial activity, production of reactive oxygen species, and formation of extracellular traps. However, additional experiments are required to shore up these mechanisms, including addressing the role of other CCL28-dependent cell types and further characterization of neutrophils from CCL28-deficient mice.

Reviewer #3 (Public Review):

The manuscript by Perez-Lopez and colleagues uses a combination of in vivo studies using knockout mice and elegant in vitro studies to explore the role of the chemokine CCL28 during bacterial infection on mucosal surfaces. Using the streptomycin model of Salmonella Typhimurium (S. Tm) infection, the authors demonstrate that CCL28 is required for neutrophil influx in the intestinal mucosa to control pathogen burden both locally and systemically. Interestingly, CCL28 plays the opposite role in a model lung infection by Acinetobacter baumanii, as Ccl28-/- mice are protected from Acinetobacter infection. Authors suggest that the mechanism by which CCL28 plays a role during bacterial infection is due to its role in modulating neutrophil recruitment and function.

The major strengths of the manuscript are:

The novelty of the findings that are described in the manuscript. The role of the chemokine CCL28 in modulating neutrophil function and recruitment in mucosal surfaces is intriguing and novel.

Authors use Ccl28-/- mice in their studies, a mouse strain that has only recently been available. To assess the impact of CCL28 on mucosal surfaces during pathogen-induced inflammation, the authors choose not one but two models of bacterial infection (S. Tm and A. baumanii). This approach increases the rigor and impact of the data presented.

Authors combine the elegant in vivo studies using Ccl28 -/- with in vitro experiments that explore the mechanisms by which CCL28 affects neutrophil function.

The major weaknesses of the manuscript in its present form are:

Authors use different time points in the S. Tm model to characterize the influx of immune cells and pathology. They do not provide a clear justification as to why distinct time points were chosen for their analysis.

Authors provide puzzling data that Ccl28-/- mice have the same numbers of CCR3 and CCR10-expressing neutrophils in the mucosa during infection. It is unclear why the lack of CCL28 expression would not affect the recruitment of neutrophils that express the ligands (CCR3 and CCR10) for this chemokine. Thus, these results need to be better explained.

The in vitro studies focus primarily on characterizing how CCL28 affects the function of neutrophils in response to S. Tm infection. There is a lack of data to demonstrate whether Acinetobacter affects CCR3 and CCR10 expression and recruitment to the cell surface and whether CCL28 plays any role in this process.

Reviewer #2 (Public Review):

This work describes a novel bipotent differentiation capacity of human muscle progenitors marked by CD56 and CD29. In addition to previously well-known myogenic differentiation potential, the authors discovered these progenitors could also be induced into tenocyte-like cells. They describe the sorted CD56+/CD29+ cells not only differentiate into tenocytes in vitro; they were also able to engraft into injured tendons and repair damaged tendons when transplanted into nude mice. Human MuSC transplantation improved the locomotor function and physiological strength of the tendon-injured mice. The authors further observed that this bipotent differentiation potential was specific to human MuSC, the same cell population isolated from mice remains unipotent to myogenic differentiation and not capable of tenocytic differentiation.

The discovery of the tenocyte differentiation potential of human CD56+/CD29+ MuSCs provides a potential cell therapeutic option for tendon injury. This work may have a significant clinical impact on improving treatment outcomes for patients suffering from tendon injury.

Strength of the paper:

Multimodal experimental approach using both in vitro and in vivo experiments provided strong proof for the differentiation capacity of the human MuSCs into tenocytes, and the potential clinical implication of these cells in the treatment of tendon injury in patients by in vivo transplantation assay. Using RNA sequencing to characterise the differentiated myocytic and tenocytic populations proved global expression profile data which have shown non-biased efficiency information to the in vitro differentiated cells.

The comparison of differentiation potentials of human and mouse MuSCs is interesting and clinically meaningful. This work illustrates that animal studies may not always be clinically relevant in studying human diseases and treatment modalities.

Weaknesses:

scRNAseq assay using total mononuclear cell population did not provide meaningful insight that enriched knowledge on CD56+/CD29+ cell population. CD56+/CD29+ cells information may have been lost due to the minority identity of these cells in the total skeletal muscle mononuclear population, especially given the total cell number used for scRNAseq was very low and no information on participant number and repeat sample number used for this assay. Using this data to claim a stem cell lineage relationship for MuSCs and tenocytes may not convincing, as seeing both cell types in the total muscle mononuclear population does not establish a lineage connection between them.

The TGF-b pathway assay uses a small molecular inhibitor of TGF-b to probe Smad2/3. The assay conclusion regarding Smad2/3 pathway responsible for tenocyte differentiation may be overinterpretation without Smad2/3 specific inhibitors being applied in the experiments.

Reviewer #3 (Public Review):<br /> Summary:

In this manuscript, the authors present compelling evidence that CD29+/CD56+ stem/progenitor cells from human muscle biopsies show tenogenic differentiation ability both in vitro and in vivo, alongside their myogenic potential.

Strengths:

The methodology and results are convincing. CD29+/CD56+ stem/progenitor cells were transplanted into immunodeficient mice with a tendon injury, and human cells expressing tenogenic markers contributed to the repair of the injured tendon. Furthermore, the authors also show better tendon biomechanical properties and plantarflexion force after transplantation.

Weaknesses:

This dual differentiation capability was not observed in mouse muscle stem cells.

Reviewer #1 (Public Review):

Through a combination of in vitro and in vivo analyses, the authors demonstrate that CD56/CD29 positive progenitor cells from human muscle can be driven towards muscle or tendon fate in vitro and are able to contribute to muscle and tendon fates following transplantation in injured mice. This is in contrast to Pax7-lineage cells from mice which do not contribute to tendon repair in vivo. While the data strongly support that a subset of cells captured by this sorting strategy has tenogenic potential, their claims of progenitor bi-potency are not fully supported by the data as currently presented.

As discussed below, some aspects of the data analysis and sample preparation are incomplete and should be clarified to fully support the claims of the paper.

For the colony analysis, it is unclear from the methods and main text whether the initial individual sorted colonies were split and subject to different conditions to support the claim of bi-potency. The finding that 40% of colonies displayed tenogenic differentiation, may instead suggest heterogeneity of the sorted progenitor population. The methods as currently described, suggest that two different plates were subject to different induction conditions. It is therefore difficult to assess the strength of the claim of bi-potency.

This group uses the well-established CD56+/CD29+ sorting strategy to isolate muscle progenitor cells, however recent work has identified transcriptional heterogeneity within these human satellite cells (ie Barruet et al, eLife 2020). Given that they identify a tenocyte population in their human muscle biopsy in Figure 1a, it is critical to understand the heterogeneity contained within the population of human progenitors captured by the authors' FACS strategy and whether tenocytes contained within the muscle biopsy are also CD56+/CD29+.

The bulk RNA sequencing data presented in Figure 3 to contrast the expression of progenitor cells under different differentiation conditions are not sufficiently convincing. In particular, it is unclear whether more than one sample was used for the RNAseq analyses shown in Figure 3. The volcano plots have many genes aligned on distinct curves suggesting that there are few replicates or low expression. There is also a concern that the sorted cells may contain tenocytes as tendon genes SCX, MKX, and THBS4 were among the genes upregulated in the myogenic differentiation conditions (shown in Figure 3b).

Reviewer #3 (Public Review):

Summary:

This study investigates the salt-dependent phase separation of A1-LCD, an intrinsically disordered region of hnRNPA1 implicated in neurodegenerative diseases. The authors employ all-atom molecular dynamics (MD) simulations to elucidate the molecular mechanisms by which salt influences A1-LCD phase separation. Contrary to typical intrinsically disordered protein (IDP) behavior, A1-LCD phase separation is enhanced by NaCl concentrations above 100 mM. The authors identify two direct effects of salt: neutralization of the protein's net charge and bridging between protein chains, both promoting condensation. They also uncover an indirect effect, where high salt concentrations strengthen pi-type interactions by reducing water availability. These findings provide a detailed molecular picture of the complex interplay between electrostatic interactions, ion binding, and hydration in IDP phase separation.

Strengths:

• Novel Insight: The study challenges the prevailing view that salt generally suppresses IDP phase separation, highlighting A1-LCD's unique behavior.<br /> • Rigorous Methodology: The authors utilize all-atom MD simulations, a powerful computational tool, to investigate the molecular details of salt-protein interactions.<br /> • Comprehensive Analysis: The study systematically explores a wide range of salt concentrations, revealing a nuanced picture of salt effects on phase separation.<br /> • Clear Presentation: The manuscript is well-written and logically structured, making the findings accessible to a broad audience.

Weaknesses:

• Limited Scope: The study focuses solely on the truncated A1-LCD, omitting simulations of the full-length protein. This limitation reduces the study's comparative value, as the authors note that the full-length protein exhibits typical salt-dependent behavior. A comparative analysis would strengthen the manuscript's conclusions and broaden its impact.

Overall, this manuscript represents a significant contribution to the field of IDP phase separation. The authors' findings provide valuable insights into the molecular mechanisms by which salt modulates this process, with potential implications for understanding and treating neurodegenerative diseases. While the study is well-conducted and clearly presented, further research is needed to validate the findings and explore their broader applicability.

Reviewer #1 (Public Review):

Summary:

The authors examined the salt-dependent phase separation of the low-complexity domain of hnRN-PA1 (A1-LCD). Using all-atom molecular dynamics simulations, they identified four distinct classes of salt dependence in the phase separation of intrinsically disordered proteins (IDPs), which can be predicted based on their amino acid composition. However, the simulations and analysis, in their current form, are inadequate and incomplete.

Strengths:

The authors attempt to unravel the mechanistic insights into the interplay between salt and protein phase separation, which is important given the complex behavior of salt effects on this process. Their effort to correlate the influence of salt on the low-complexity domain of hnRNPA1 (A1-LCD) with a range of other proteins known to undergo salt-dependent phase separation is an interesting and valuable topic.

Weaknesses:

(1) The simulations performed are not sufficiently long (Figure 2A) to accurately comment on phase separation behavior. The simulations do not appear to have converged well, indicating that the system has not reached a steady state, rendering the analysis of the trajectories unreliable.

(2) The majority of the data presented shows no significant alteration with changes in salt concentration. However, the authors have based conclusions and made significant comments regarding salt activities. The absence of error bars in the data representation raises questions about its reliability. Additionally, the manuscript lacks sufficient scientific details of the calculations.

(3) In Figures 2B and 2C, the changes in the radius of gyration and the number of contacts do not display significant variations with changes in salt concentration. The change in the radius of gyration with salt concentration is less than 1 Å, and the number of contacts does not change by at least 1. The authors' conclusions based on these minor changes seem unfounded.

Reviewer #2 (Public Review):

This is an interesting computational study addressing how salt affects the assembly of biomolecular condensates. The simulation data are valuable as they provide a degree of atomistic details regarding how small salt ions modulate interactions among intrinsically disordered proteins with charged residues, namely via Debye-like screening that weakens the effective electrostatic interactions among the polymers, or through bridging interactions that allow interactions between like charges from different polymer chains to become effectively attractive (as illustrated, e.g., by the radial distribution functions in Supplementary Information). However, this manuscript has several shortcomings: (i) Connotations of the manuscript notwithstanding, many of the authors' concepts about salt effects on biomolecular condensates have been put forth by theoretical models, at least back in 2020 and even earlier. Those earlier works afford extensive information such as considerations of salt concentrations inside and outside the condensate (tie-lines). But the authors do not appear to be aware of this body of prior works and therefore missed the opportunity to build on these previous advances and put the present work with its complementary advantages in structural details in the proper context. (ii) There are significant experimental findings regarding salt effects on condensate formation [which have been modeled more recently] that predate the A1-LCD system (ref.19) addressed by the present manuscript. This information should be included, e.g., in Table 1, for sound scholarship and completeness. (iii) The strengths and limitations of the authors' approach vis-à-vis other theoretical approaches should be discussed with some degree of thoroughness (e.g., how the smallness of the authors' simulation system may affect the nature of the "phase transition" and the information that can be gathered regarding salt concentration inside vs. outside the "condensate" etc.). Accordingly, this manuscript should be revised to address the following. In particular, the discussion in the manuscript should be significantly expanded by including references mentioned below as well as other references pertinent to the issues raised.

(1) The ability to use atomistic models to address the questions at hand is a strength of the present work. However, presumably because of the computational cost of such models, the "phase-separated" "condensates" in this manuscript are extremely small (only 8 chains). An inspection of Fig.1 indicates that while the high-salt configuration (snapshot, bottom right) is more compact and droplet-like than the low-salt configuration (top right), it is not clear that the 50 mM NaCl configuration can reasonably correspond to a dilute or homogeneous phase (without phase separation) or just a condensate with a lower protein concentration because the chains are still highly associated. One may argue that they become two droplets touching each other (the chains are not fully dispersed throughout the simulation box, unlike in typical coarse-grained simulations of biomolecular phase separation). While it may not be unfair to argue from this observation that the condensed phase is less stable at low salt, this raises critical questions about the adequacy of the approach as a stand-alone source of theoretical information. Accordingly, an informative discussion of the limitation of the authors' approach and comparisons with results from complementary approaches such as analytical theories and coarse-grained molecular dynamics will be instructive-even imperative, especially since such results exist in the literature (please see below).

(2) The aforementioned limitation is reflected by the authors' choice of using Dmax as a sort of phase-separation order parameter. However, no evidence was shown to indicate that Dmax exhibits a two-state-like distribution expected of phase separation. It is also not clear whether a Dmax value corresponding to the linear dimension of the simulation box was ever encountered in the authors' simulated trajectories such that the chains can be reliably considered to be essentially fully dispersed as would be expected for the dilute phase. Moreover, as the authors have noted in the second paragraph of the Results, the variation of Dmax with simulation time does not show a monotonic rank order with salt concentration. The authors' explanation is equivalent to stipulating that the simulation system has not fully equilibrated, inevitably casting doubt on at least some of the conclusions drawn from the simulation data.

(3) With these limitations, is it realistic to estimate possible differences in salt concentration between the dilute and condensed phases in the present work? These features, including tie-lines, were shown to be amenable to analytical theory and coarse-grained molecular dynamics simulation (please see below).

(4) In the comparison in Fig.2B between experimental and simulated radius of gyration as a function of [NaCl], there is an outlier among the simulated radii of gyration at [NaCl] ~ 250 mM. An explanation should be offered.

(5) The phenomenon of no phase separation at zero and low salt and phase separation at higher salt has been observed for the IDP Caprin1 and several of its mutants [Wong et al., J Am Chem Soc 142, 2471-2489 (2020) [https://pubs.acs.org/doi/full/10.1021/jacs.9b12208], see especially Fig.9 of this reference]. This work should be included in the discussion and added to Table 1.

(6) The authors stated in the Introduction that "A unifying understanding of how salt affects the phase separation of IDPs is still lacking". While it is definitely true that much remains to be learned about salt effects on IDP phase separation, the advances that have already been made regarding salt effects on IDP phase separation is more abundant than that conveyed by this narrative. For instance, an analytical theory termed rG-RPA was put forth in 2020 to provide a uniform (unified) treatment of salt, pH, and sequence-charge-pattern effects on polyampholytes and polyelectrolytes (corresponding to the authors' low net charge and high net charge cases). This theory offers a means to predict salt-IDP tie-lines and a comprehensive account of salt effect on polyelectrolytes resulting in a lack of phase separation at extremely low salt and subsequent salt-enhanced phase separation (similar to the case the authors studied here) and in some cases re-entrant phase separation or dissolution [Lin et al., J Chem Phys 152. 045102 (2020) [https://doi.org/10.1063/1.5139661]]. This work is highly relevant and it already provided a conceptual framework for the authors' atomistic results and subsequent discussion. As such, it should definitely be a part of the authors' discussion.

(7) Bridging interactions by small ions resulting in effective attractive interactions among polyelectrolytes leading to their phase separation have been demonstrated computationally by Orkoulas et al., Phys Rev Lett 90, 048303 (2003) [https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.90.048303]. This result should also be included in the discussion.

(8) More recently, the salt-dependent phase separations of Caprin1, its RtoK variants and phosphorylated variant (see item #5 above) were modeled (and rationalized) quite comprehensively using rG-RPA, field-theoretic simulation, and coarse-grained molecular dynamics [Lin et al., arXiv:2401.04873 [https://arxiv.org/abs/2401.04873]], providing additional data supporting a conceptual perspective put forth in Lin et al. J Chem Phys 2020 (e.g., salt-IDP tie-lines, bridging interactions, re-entrance behaviors etc.) as well as in the authors' current manuscript. It will be very helpful to the readers of eLife to include this preprint in the authors' discussion, perhaps as per the authors' discretion-along the manner in which other preprints are referenced and discussed in the current version of the manuscript.

Reviewer #2 (Public Review):

This manuscript offers significant insights into the impact of maternal obesity on oocyte methylation and its transgenerational effects. The study employs comprehensive methodologies, including transgenerational breeding experiments, whole genome bisulfite sequencing, and metabolomics analysis, to explore how high-fat diet (HFD)-induced obesity alters genomic methylation in oocytes and how these changes are inherited by subsequent generations. The findings suggest that maternal obesity induces hyper-methylation in oocytes, which is partly transmitted to F1 and F2 oocytes and livers, potentially contributing to metabolic disorders in offspring. Notably, the study identifies melatonin as a key regulator of this hyper-methylation process, mediated through the cAMP/PKA/CREB pathway.

Strengths:

The study employs comprehensive methodologies, including transgenerational breeding experiments, whole genome bisulfite sequencing, and metabolomics analysis, and provides convincing data.

Weaknesses:

The description in the results section is somewhat verbose. This section (lines 126~227) utilized transgenerational breeding experiments and methylation analysis to demonstrate that maternal obesity-induced alterations in oocyte methylation (including hyper-DMRs and hypo-DMRs) can be partially transmitted to F1 and F2 oocytes and livers. The authors should consider condensing and revising this section for clarity and brevity.

There is a contradiction with Reference 3, but the discrepancy is not discussed. In this study, the authors observed an increase in global methylation in oocytes from HFD mice, whereas Reference 3 indicates Stella insufficiency in oocytes from HFD mice. This Stella insufficiency should lead to decreased methylation (Reference 33). There should be a discussion of how this discrepancy can be reconciled with the authors' findings.

Reviewer #1 (Public Review):

With socioeconomic development, more and more people are obese which is an important reason for sub-fertility and infertility. Maternal obesity reduces oocyte quality which may be a reason for the high risk of metabolic diseases for offspring in adulthood. Yet the underlying mechanisms are not well elucidated. Here the authors examined the effects of maternal obesity on oocyte methylation. Hyper-methylation in oocytes was reported by the authors, and the altered methylation in oocytes may be partially transmitted to F2. The authors further explored the association between the metabolome of serum and the altered methylation in oocytes. The authors identified decreased melatonin. Melatonin is involved in regulating the hyper-methylation of high-fat diet (HFD) oocytes, via increasing the expression of DNMTs which is mediated by the cAMP/PKA/CREB pathway.

Strengths:

This study is interesting and should have significant implications for the understanding of the transgenerational inheritance of GDM in humans.

Weaknesses:

The link between altered DNA methylation and offspring metabolic disorders is not well elucidated; how the altered DNA methylation in oocytes escapes reprogramming in transgenerational inheritance is also unclear.

Reviewer #3 (Public Review):

Summary:

Maternal obesity is a health problem for both pregnant women and their offspring. Previous works including work from this group have shown significant DNA methylation changes for offspring of obese pregnancies in mice. In this manuscript, Chao et al digested the potential mechanisms behind the DNA methylation changes. The major observations of the work include transgenerational DNA methylation changes in offspring of maternal obesity, and metabolites such as methionine and melatonin correlated with the above epigenetic changes. Exogenous melatonin treatment could reverse the effects of obesity. The authors further hypothesized that the linkage may be mediated by the cAMP/PKA/CREB pathway to regulate the expression of DNMTs.

Strengths:

The transgenerational change of DNA methylation following HFD is of great interest for future research to follow. The metabolic treatment that could change the DNA methylation in oocytes is also interesting and has potential relevance to future clinical practice.

Weaknesses:

The HFD oocytes have more 5mC signal based on staining and sequencing (Fig 1A-1F). However, the authors also identified almost equal numbers of hyper- and hypo-DMRs, which raises questions regarding where these hypo-DMRs were located and how to interpret their behaviors and functions. These questions are also critical to address in the following mechanistic dissections as the metabolic treatments may also induce bi-directional changes of DNA methylation. The authors should carefully assess these conflicts to make the conclusions solid.

The transgenerational epigenetic modifications are controversial. Even for F0 offspring under maternal obesity, there were different observations compared to this work (Hou, YJ., et al. Sci Rep, 2016). The authors should discuss the inconsistencies with previous works.

In addition to the above inconsistencies, the DNA methylation analysis in this work was not carefully evaluated. Several previous works were evaluating the DNA methylation in mice oocytes, which showed global methylation levels of around 50% (Shirane K, et al. PLoS Genet, 2013; Wang L., et al, Cell, 2014). In Figure 1E, the overall methylation level is about 23% in control, which is significantly different from previous works. The authors should provide more details regarding the WGBS procedure, including but not limited to sequencing coverage, bisulfite conversion rate, etc.

Reviewer #3 (Public Review):

This study tests for dissociable neural representations of an observed action's kinematics vs. its physical effect in the world. Overall, it is a thoughtfully conducted study that convincingly shows that representations of action effects are more prominent in the anterior inferior parietal lobe (aIPL) than the superior parietal lobe (SPL), and vice versa for the representation of the observed body movement itself. The findings make a fundamental contribution to our understanding of the neural mechanisms of goal-directed action recognition, but there are a couple of caveats to the interpretation of the results that are worth noting:

(1) Both a strength of this study and ultimately a challenge for its interpretation is the fact that the animations are so different in their visual content than the other three categories of stimuli. On one hand, as highlighted in the paper, it allows for a test of action effects that is independent of specific motion patterns and object identities. On the other hand, the consequence is also that Action-PLD cross-decoding is generally better than Action-Anim cross-decoding across the board (Figure 3A) - not surprising because the spatiotemporal structure is quite different between the actions and the animations. This pattern of results makes it difficult to interpret a direct comparison of the two conditions within a given ROI. For example, it would have strengthened the argument of the paper to show that Action-Anim decoding was better than Action-PLD decoding in aIPL; this result was not obtained, but that could simply be because the Action and PLD conditions are more visually similar to each other in a number of ways that influence decoding. Still, looking WITHIN each of the Action-Anim and Action-PLD conditions yields clear evidence for the main conclusion of the study.

(2) The second set of analyses in the paper, shown in Figure 4, follows from the notion that inferring action effects from body movements alone (i.e., when the object is unseen) is easier via pantomimes than with PLD stick figures. That makes sense, but it doesn't necessarily imply that the richness of the inferred action effect is the only or main difference between these conditions. There is more visual information overall in the pantomime case. So, although it's likely true that observers can more vividly infer action effects from pantomimes vs stick figures, it's not a given that contrasting these two conditions is an effective way to isolate inferred action effects. The results in Figure 4 are therefore intriguing but do not unequivocally establish that aIPL is representing inferred rather than observed action effects.

Reviewer #1 (Public Review):

Summary:

The authors report a study aimed at understanding the brain's representations of viewed actions, with a particular aim to distinguish regions that encode observed body movements, from those that encode the effects of actions on objects. They adopt a cross-decoding multivariate fMRI approach, scanning adult observers who viewed full-cue actions, pantomimes of those actions, minimal skeletal depictions of those actions, and abstract animations that captured analogous effects to those actions. Decoding across different pairs of these actions allowed the authors to pull out the contributions of different action features in a given region's representation. The main hypothesis, which was largely confirmed, was that the superior parietal lobe (SPL) more strongly encodes movements of the body, whereas the anterior inferior parietal lobe (aIPL) codes for action effects of outcomes. Specifically, region of interest analyses showed dissociations in the successful cross-decoding of action category across full-cue and skeletal or abstract depictions. Their analyses also highlight the importance of the lateral occipito-temporal cortex (LOTC) in coding action effects. They also find some preliminary evidence about the organisation of action kinds in the regions examined.

Strengths:

The paper is well-written, and it addresses a topic of emerging interest where social vision and intuitive physics intersect. The use of cross-decoding to examine actions and their effects across four different stimulus formats is a strength of the study. Likewise, the a priori identification of regions of interest (supplemented by additional full-brain analyses) is a strength.

Weaknesses:

I found that the main limitation of the article was in the underpinning theoretical reasoning. The authors appeal to the idea of "action effect structures (AES)", as an abstract representation of the consequences of an action that does not specify (as I understand it) the exact means by which that effect is caused, nor the specific objects involved. This concept has some face validity, but it is not developed very fully in the paper, rather simply asserted. The authors make the claim that "The identification of action effect structure representations in aIPL has implications for theories of action understanding" but it would have been nice to hear more about what those theoretical implications are. More generally, I was not very clear on the direction of the claim here. Is there independent evidence for AES (if so, what is it?) and this study tests the following prediction, that AES should be associated with a specific brain region that does not also code other action properties such as body movements? Or, is the idea that this finding -- that there is a brain region that is sensitive to outcomes more than movements -- is the key new evidence for AES?

On a more specific but still important point, I was not always clear that the significant, but numerically rather small, decoding effects are sufficient to support strong claims about what is encoded or represented in a region. This concern of course applies to many multivariate decoding neuroimaging studies. In this instance, I wondered specifically whether the decoding effects necessarily reflected fully five-way distinction amongst the action kinds, or instead (for example) a significantly different pattern evoked by one action compared to all of the other four (which in turn might be similar). This concern is partly increased by the confusion matrices that are presented in the supplementary materials, which don't necessarily convey a strong classification amongst action kinds. The cluster analyses are interesting and appear to be somewhat regular over the different regions, which helps. However: it is hard to assess these findings statistically, and it may be that similar clusters would be found in early visual areas too.

Reviewer #2 (Public Review):

Summary:

This study uses an elegant design, using cross-decoding of multivariate fMRI patterns across different types of stimuli, to convincingly show a functional dissociation between two sub-regions of the parietal cortex, the anterior inferior parietal lobe (aIPL) and superior parietal lobe (SPL) in visually processing actions. Specifically, aIPL is found to be sensitive to the causal effects of observed actions (e.g. whether an action causes an object to compress or to break into two parts), and SPL to the motion patterns of the body in executing those actions.

To show this, the authors assess how well linear classifiers trained to distinguish fMRI patterns of response to actions in one stimulus type can generalize to another stimulus type. They choose stimulus types that abstract away specific dimensions of interest. To reveal sensitivity to the causal effects of actions, regardless of low-level details or motion patterns, they use abstract animations that depict a particular kind of object manipulation: e.g. breaking, hitting, or squashing an object. To reveal sensitivity to motion patterns, independently of causal effects on objects, they use point-light displays (PLDs) of figures performing the same actions. Finally, full videos of actors performing actions are used as the stimuli providing the most complete, and naturalistic information. Pantomime videos, with actors mimicking the execution of an action without visible objects, are used as an intermediate condition providing more cues than PLDs but less than real action videos (e.g. the hands are visible, unlike in PLDs, but the object is absent and has to be inferred). By training classifiers on animations, and testing their generalization to full-action videos, the classifiers' sensitivity to the causal effect of actions, independently of visual appearance, can be assessed. By training them on PLDs and testing them on videos, their sensitivity to motion patterns, independent of the causal effect of actions, can be assessed, as PLDs contain no information about an action's effect on objects.

These analyses reveal that aIPL can generalize between animations and videos, indicating that it is sensitive to action effects. Conversely, SPL is found to generalize between PLDs and videos, showing that it is more sensitive to motion patterns. A searchlight analysis confirms this pattern of results, particularly showing that action-animation decoding is specific to right aIPL, and revealing an additional cluster in LOTC, which is included in subsequent analyses. Action-PLD decoding is more widespread across the whole action observation network.

This study provides a valuable contribution to the understanding of functional specialization in the action observation network. It uses an original and robust experimental design to provide convincing evidence that understanding the causal effects of actions is a meaningful component of visual action processing and that it is specifically localized in aIPL and LOTC.

Strengths:

The authors cleverly managed to isolate specific aspects of real-world actions (causal effects, motion patterns) in an elegant experimental design, and by testing generalization across different stimulus types rather than within-category decoding performance, they show results that are convincing and readily interpretable. Moreover, they clearly took great care to eliminate potential confounds in their experimental design (for example, by carefully ordering scanning sessions by increasing realism, such that the participants could not associate animation with the corresponding real-world action), and to increase stimulus diversity for different stimulus types. They also carefully examine their own analysis pipeline, and transparently expose it to the reader (for example, by showing asymmetries across decoding directions in Figure S3). Overall, this is an extremely careful and robust paper.

Weaknesses:

I list several ways in which the paper could be improved below. More than 'weaknesses', these are either ambiguities in the exact claims made, or points that could be strengthened by additional analyses. I don't believe any of the claims or analyses presented in the paper show any strong weaknesses, problematic confounds, or anything that requires revising the claims substantially.

(1) Functional specialization claims: throughout the paper, it is not clear what the exact claims of functional specialization are. While, as can be seen in Figure 3A, the difference between action-animation cross-decoding is significantly higher in aIPL, decoding performance is also above chance in right SPL, although this is not a strong effect. More importantly, action-PLD cross-decoding is robustly above chance in both right and left aIPL, implying that this region is sensitive to motion patterns as well as causal effects. I am not questioning that the difference between the two ROIs exists - that is very convincingly shown. But sentences such as "distinct neural systems for the processing of observed body movements in SPL and the effect they induce in aIPL" (lines 111-112, Introduction) and "aIPL encodes abstract representations of action effect structures independently of motion and object identity" (lines 127-128, Introduction) do not seem fully justified when action-PLD cross-decoding is overall stronger than action-animation cross-decoding in aIPL. Is the claim, then, that in addition to being sensitive to motion patterns, aIPL contains a neural code for abstracted causal effects, e.g. involving a separate neural subpopulation or a different coding scheme? Moreover, if sensitivity to motion patterns is not specific to SPL, but can be found in a broad network of areas (including aIPL itself), can it really be claimed that this area plays a specific role, similar to the specific role of aIPL in encoding causal effects? There is indeed, as can be seen in Figure 3A, a difference between action-PLD decoding in SPL and aIPL, but based on the searchlight map shown in Figure 3B I would guess that a similar difference would be found by comparing aIPL to several other regions. The authors should clarify these ambiguities.

(2) Causal effect information in PLDs: the reasoning behind the use of PLD stimuli is to have a condition that isolates motion patterns from the causal effects of actions. However, it is not clear whether PLDs really contain as little information about action effects as claimed. Cross-decoding between animations and PLDs is significant in both aIPL and LOTC, as shown in Figure 4. This indicates that PLDs do contain some information about action effects. This could also be tested behaviorally by asking participants to assign PLDs to the correct action category. In general, disentangling the roles of motion patterns and implied causal effects in driving action-PLD cross-decoding (which is the main dependent variable in the paper) would strengthen the paper's message. For example, it is possible that the strong action-PLD cross-decoding observed in aIPL relies on a substantially different encoding from, say, SPL, an encoding that perhaps reflects causal effects more than motion patterns. One way to exploratively assess this would be to integrate the clustering analysis shown in Figure S1 with a more complete picture, including animation-PLD and action-PLD decoding in aIPL.

(3) Nature of the motion representations: it is not clear what the nature of the putatively motion-driven representation driving action-PLD cross-decoding is. While, as you note in the Introduction, other regions such as the superior temporal sulcus have been extensively studied, with the understanding that they are part of a feedforward network of areas analyzing increasingly complex motion patterns (e.g. Riese & Poggio, Nature Reviews Neuroscience 2003), it doesn't seem like the way in which SPL represents these stimuli are similarly well-understood. While the action-PLD cross-decoding shown here is a convincing additional piece of evidence for a motion-based representation in SPL, an interesting additional analysis would be to compare, for example, RDMs of different actions in this region with explicit computational models. These could be, for example, classic motion energy models inspired by the response characteristics of regions such as V5/MT, which have been shown to predict cortical responses and psychophysical performance both for natural videos (e.g. Nishimoto et al., Current Biology 2011) and PLDs (Casile & Giese Journal of Vision 2005). A similar cross-decoding analysis between videos and PLDs as that conducted on the fMRI patterns could be done on these models' features, obtaining RDMs that could directly be compared with those from SPL. This would be a very informative analysis that could enrich our knowledge of a relatively unexplored region in action recognition. Please note, however, that action recognition is not my field of expertise, so it is possible that there are practical difficulties in conducting such an analysis that I am not aware of. In this case, I kindly ask the authors to explain what these difficulties could be.

(4) Clustering analysis: I found the clustering analysis shown in Figure S1 very clever and informative. However, there are two things that I think the authors should clarify. First, it's not clear whether the three categories of object change were inferred post-hoc from the data or determined beforehand. It is completely fine if these were just inferred post-hoc, I just believe this ambiguity should be clarified explicitly. Second, while action-anim decoding in aIPL and LOTC looks like it is consistently clustered, the clustering of action-PLD decoding in SPL and LOTC looks less reliable. The authors interpret this clustering as corresponding to the manual vs. bimanual distinction, but for example "drink" (a unimanual action) is grouped with "break" and "squash" (bimanual actions) in left SPL and grouped entirely separately from the unimanual and bimanual clusters in left LOTC. Statistically testing the robustness of these clusters would help clarify whether it is the case that action-PLD in SPL and LOTC has no semantically interpretable organizing principle, as might be the case for a representation based entirely on motion pattern, or rather that it is a different organizing principle from action-anim, such as the manual vs. bimanual distinction proposed by the authors. I don't have much experience with statistical testing of clustering analyses, but I think a permutation-based approach, wherein a measure of cluster robustness, such as the Silhouette score, is computed for the clusters found in the data and compared to a null distribution of such measures obtained by permuting the data labels, should be feasible. In a quick literature search, I have found several papers describing similar approaches: e.g. Hennig (2007), "Cluster-wise assessment of cluster stability"; Tibshirani et al. (2001) "Estimating the Number of Clusters in a Data Set Via the Gap Statistic". These are just pointers to potentially useful approaches, the authors are much better qualified to pick the most appropriate and convenient method. However, I do think such a statistical test would strengthen the clustering analysis shown here. With this statistical test, and the more exhaustive exposition of results I suggested in point 2 above (e.g. including animation-PLD and action-PLD decoding in aIPL), I believe the clustering analysis could even be moved to the main text and occupy a more prominent position in the paper.

(5) ROI selection: this is a minor point, related to the method used for assigning voxels to a specific ROI. In the description in the Methods (page 16, lines 514-24), the authors mention using the MNI coordinates of the center locations of Brodmann areas. Does this mean that then they extracted a sphere around this location, or did they use a mask based on the entire Brodmann area? The latter approach is what I'm most familiar with, so if the authors chose to use a sphere instead, could they clarify why? Or, if they did use the entire Brodmann area as a mask, and not just its center coordinates, this should be made clearer in the text.

Reviewer #2 (Public Review):

Summary:

This work by Grogan and colleagues aimed to translate animal studies showing that acetylcholine plays a role in motivation by modulating the effects of dopamine on motivation. They tested this hypothesis with a placebo-controlled pharmacological study administering a muscarinic antagonist (trihexyphenidyl; THP) to a sample of 20 adult men performing an incentivized saccade task while undergoing electroengephalography (EEG). They found that reward increased vigor and reduced reaction times (RTs) and, importantly, these reward effects were attenuated by trihexyphenidyl. High incentives increased preparatory EEG activity (contingent negative variation), and though THP also increased preparatory activity, it also reduced this reward effect on RTs.

Strengths:

The researchers address a timely and potentially clinically relevant question with a within-subject pharmacological intervention and a strong task design. The results highlight the importance of the interplay between dopamine and other neurotransmitter systems in reward sensitivity and even though no Parkinson's patients were included in this study, the results could have consequences for patients with motivational deficits and apathy if validated in the future.

Weaknesses:

The main weakness of the study is the small sample size (N=20) that unfortunately is limited to men only. The generalizability and replicability of the conclusions remain to be assessed in future research with a larger and more diverse sample size and potentially a clinically relevant population. The EEG results do not shape a concrete mechanism of action of the drug on reward sensitivity.

Reviewer #1 (Public Review):

Summary:

The authors used a motivated saccade task with distractors to measure response vigor and reaction time (RT) in healthy human males under placebo or muscarinic antagonism. They also simultaneously recorded neural activity using EEG with event-related potential (ERP) focused analyses. This study provides evidence that the muscarinic antagonist Trihexyphenidyl (THP) modulates the motivational effects of reward on both saccade velocity and RT, and also increases the distractibility of participants. The study also examined the correlational relationships between reaction time and vigor and manipulations (THP, incentives) with components of the EEG-derived ERPs. While an interesting correlation structure emerged from the analyses relating the ERP biomarkers to behavior, it is unclear how these potentially epiphenomenal biomarkers relate to relevant underlying neurophysiology.

Strengths:

This study is a logical translational extension from preclinical findings of cholinergic modulation of motivation and vigor and the CNV biomarker to a normative human population, utilizing a placebo-controlled, double-blind approach.

While framed in the context of Parkinson's disease where cholinergic medications can be used, the authors do a good job in the discussion describing the limitations in generalizing their findings obtained in a normative and non-age-matched cohort to an aged PD patient population.

The exploratory analyses suggest alternative brain targets and/or ERP components that relate to the behavior and manipulations tested. These will need to be further validated in an adequately powered study. Once validated, the most relevant biomarkers could be assessed in a more clinically relevant population.

Weaknesses:

The relatively weak correlations between the main experimental outcomes provide unclear insight into the neural mechanisms by which the manipulations lead to behavioral manifestations outside the context of the ERP. It would have been interesting to evaluate how other quantifications of the EEG signal through time-frequency analyses relate to the behavioral outcomes and manipulations.

The ERP correlations to relevant behavioral outcomes were not consistent across manipulations demonstrating they are not reliable biomarkers to behavior but do suggest that multiple underlying mechanisms can give rise to the same changes in the ERP-based biomarkers and lead to different behavioral outcomes.

Reviewer #3 (Public Review):

Summary:

Grogan et al examine a role for muscarinic receptor activation in action vigor in a saccadic system. This work is motivated by a strong literature linking dopamine to vigor, and some animal studies suggesting that ACH might modulate these effects, and is important because patient populations with symptoms related to reduced vigor are prescribed muscarinic antagonists. The authors use a motivated saccade task with distractors to measure the speed and vigor of actions in humans under placebo or muscarinic antagonism. They show that muscarinic antagonism blunts the motivational effects of reward on both saccade velocity and RT, and also modulates the distractibility of participants, in particular by increasing the repulsion of saccades away from distractors. They show that preparatory EEG signals reflect both motivation and drug condition, and make a case that these EEG signals mediate the effects of the drug on behavior.

Strengths:

This manuscript addresses an interesting and timely question and does so using an impressive within-subject pharmacological design and a task well-designed to measure constructs of interest. The authors show clear causal evidence that ACH affects different metrics of saccade generation related to effort expenditure and their modulation by incentive manipulations. The authors link these behavioral effects to motor preparatory signatures, indexed with EEG, that relate to behavioral measures of interest and in at least one case statistically mediate the behavioral effects of ACH antagonism.

Weaknesses:

In full disclosure, I have previously reviewed this manuscript in another journal and the authors have done a considerable amount of work to address my previous concerns. However, I have a few remaining concerns that affect my interpretation of the current manuscript.

Some of the EEG signals (figures 4A&C) have profiles that look like they could have ocular, rather than central nervous, origins. Given that this is an eye movement task, it would be useful if the authors could provide some evidence that these signals are truly related to brain activity and not driven by ocular muscles, either in response to explicit motor effects (ie. Blinks) or in preparation for an upcoming saccade. For other EEG signals, in particular, the ones reported in Figure 3, it would be nice to see what the spatial profiles actually look like - does the scalp topography match that expected for the signal of interest?

A primary weakness of this paper is the sample size - since only 20 participants completed the study. The authors address the sample size in several places and I completely understand the reason for the reduced sample size (study halt due to COVID). That said, they only report the sample size in one place in the methods rather than through degrees of freedom in their statistical tests conducted throughout the results. In part because of this, I am not totally clear on whether the sample size for each analysis is the same - or whether participants were removed for specific analyses (ie. due to poor EEG recordings, for example). Beyond this point, but still related to the sample size, in some cases I worry that results are driven by a single subject. In particular, the interaction effect observed in Figure 1e seems like it would be highly sensitive to the single subject who shows a reverse incentive effect in the drug condition.

There are not sufficient details on the cluster-based permutation testing to understand what the authors did or whether it is reasonable. What channels were included? What metric was computed per cluster? How was null distribution generated?

The authors report that "muscarinic antagonism strengthened the P3a" - but I was unable to see this in the data plots. Perhaps it is because the variability related to individual differences obscures the conditional differences in the plots. In this case, event-related difference signals could be helpful to clarify the results.

For mediation analyses, it would be useful in the results section to have a much more detailed description of the regression results, rather than just reporting things in a binary did/did not mediate sort of way. Furthermore, the methods should also describe how mediation was tested statistically (ie. What is the null distribution that the difference in coefficients with/without moderator is tested against?).

Reviewer #1 (Public Review):

Summary:

In the manuscript entitled "Magnesium modulates phospholipid metabolism to promote bacterial phenotypic resistance to antibiotics", Li et al demonstrated the role of magnesium in promoting phenotypic resistance in V. alginolyticus. Using standard microbiological and metabolomic techniques, the authors have shown the significance of fatty acid biosynthesis pathway behind the resistance mechanism. This study is significant as it sheds light on the role of an exogenous factor in altering membrane composition, polarization, and fluidity which ultimately leads to antimicrobial resistance.

Strengths:

(1) The experiments were carried out methodically and logically.

(2) An adequate number of replicates were used for the experiments.

Weaknesses:

(1) The introduction section needs to be more informative and to the point.

(2) The weakest point of this paper is in the logistics through the results section. The way authors represented the figures and interpreted them in the results section (or the figure legends) does not match. The figures are difficult to interpret and are not at all self-explanatory.

(3) There are too many mislabeling of the figure panels in the main text which makes it difficult to find out which figures the authors are explaining. There should be more explanation on why and how they did the experiments and how the results were interpreted.

Reviewer #2 (Public Review):

Summary:

In this study, the authors aimed to identify if and how magnesium affects the ability of two particular bacteria species to resist the action of antibiotics. In my view, the authors succeeded in their goals and presented a compelling study that will have important implications for the antibiotic resistance research community. Since metals like magnesium are present in all lab media compositions and are present in the host, the data presented in this study certainly will inspire additional research by the community. These could include research into whether other types of metals also induce multi-drug resistance, whether this phenomenon can be observed in other bacterial species, especially pathogenic species that cause clinical disease, and whether the underlying molecular determinants (i.e. enzymes) of metal-induced phenotypic resistance could be new antimicrobial drug targets themselves.

Strengths:

This study's strengths include that the authors used a variety of methodologies, all of which point to a clear effect of exogenous Mg2+ on drug resistance in the targeted species. I also commend the authors for carrying out a comprehensive study, spanning evaluation of whole cell phenotypes, metabolic pathways, genetic manipulation, to enzyme activity level evaluation. The fact that the authors uncovered a molecular mechanism underlying Mg2+-induced phenotypic resistance is particularly important as the key proteins should be studied further.

Weaknesses:

I believe there are weaknesses in the manuscript, however. The authors take for granted that the reader is familiar with all the assays utilized, and do not properly explain some experiments, and thus I highly suggest that the authors add a brief statement in each situation describing the rationale for each selected methodology (more details are in the private review to the authors). The Results section is also quite long and bogs down at times, and I suggest that the authors reduce its length by 10 to 20%. In contrast, the Introduction is sparse and lacks key aspects, for example, there should be mention of the study's main purpose and approaches, plus an introduction to the authors' choice of species and their known drug resistance properties, as well as the drug of choice (balofloxacin). Another notable weakness is that the authors evaluated Mg2+-induced phenotypic resistance only against two closely related species, and thus the generalizability of this mechanism of drug resistance is not known. The paper would be strengthened if the authors could demonstrate this type of phenotypic resistance in at least one more Gram-negative species and at least one Gram-positive species (antimicrobial susceptibility evaluations would suffice), each of which should be pathogenic to humans. Demonstrating magnesium-induced phenotypic drug resistance in the WHO Priority Bacterial Pathogens would be particularly important.

In general, the conclusions drawn by the authors are justified by the data, except for the interpretation of some experiments. Importantly, this paper has discovered new antimicrobial resistance mechanisms and has also pointed to potential new targets for antimicrobials.

Reviewer #1 (Public Review):

I feel that the changes to the manuscript have significantly improved it. It's unfortunate that the single biotin/anti-biotin antibodies were not more illuminating but I think the attempts were worthwhile. My only comment is that the rebuttal to the second part of point 3 still does not fully deal with the issue. By marking proximal proteins other than the fusion with biotin, TurboID significantly increases the detectable signal, but it is formally no longer possible to be certain what the biotin is attached to. None of the controls that the authors suggest will actually give you certainty about what you are detecting while imaging. Mass spectrometry will give you an ensemble measurement of all the biotinylated proteins in the cell without being able to relate that back to what you are observing in a specific cellular region when you are imaging. Colocalization with a tagged protein/specific antibody could suggest that a portion of the signal could be attributable to the TurboID-biotin signal, but it could also be a tight binding partner or part of a larger protein complex. PLA assays would have similar issues- some of the protein could be labeled but it will be impossible to show what portion of the signal is attributable to the protein of interest and how much is attributable to other proximal proteins. I think the key thing here is that in this implementation, TurboID allows you to enhance the labeling of protein structures in cells, such as NUPS, but at the expense of certainty about the specific proteins you are labeling. I personally cannot think of a reasonable control that will allow you to avoid this issue. I feel that this point needs to be clearly made if people are going to use this method for signal enhancement, otherwise people may be misled about what they are actually looking at. The method should be useful, but the limitations need to be clear.

Reviewer #2 (Public Review):

I found the original paper to be of high quality and value. The revisions the authors have made (particularly with respect to the more cautious phraseology concerning the ability to track labelled proteins) are valuable additions. The other responses are well-argued and satisfactory to this reviewer.

Reviewer #1 (Public Review):

Summary:

This study demonstrates a key role of oxLDL in enhancing Ang II-induced Gq signaling by promoting the AT1/LOX1 receptor complex formation. Importantly, Gq-mediated calcium influx was only observed in LOX1 and AT1 both expressing cells, and AT1-LOX1 interaction aggravated renal damage and dysfunction under the condition of a high-fat diet with Ang II infusion, so this study indicated a new therapeutic potential of AT1-LOX1 receptor complex in CKD patients with dyslipidemia and hypertension.

Strengths:

This study is very exciting and the work is also very detailed, especially regarding the mechanism of LOX1-AT1 receptor interaction and its impact on oxidative stress, fibrosis, and inflammation.

Weaknesses:

The direct evidence for the interaction between AT1 and LOX1 receptors in cell membrane localization is relatively weak. Here I raise some questions that may further improve the study.

Major points:

(1) The authors hypothesized that in the interaction of AT1/LOX1 receptor complex in response to ox-LDL and AngII, there should be strong evidence of fluorescence detection of colocalization for these two membrane receptors, both in vivo and in vitro. Although the video evidence for AT1 internalization upon complex activation is shown in Figure S1, the more important evidence should be membrane interaction and enhanced signal of intracellular calcium influx.

(2) Co-IP experiment should be provided to prove the AT1/LOX1 receptor interaction in response to ox-LDL and AngII in AT1 and LOX1 both expressing cells but not in AT1 only expressing cells.

(3) The authors mentioned that the Gq signaling-mediated calcium influx may change gene expression and cellular characteristics, including EMT and cell proliferation. They also provided evidence that oxidative stress, fibrosis, and inflammation were all enhanced after activating both receptors and inhibiting Gq was effective in reversing these changes. However, single stimulation with ox-LDL or AngII also has strong effects on ROS production, inflammation, and cell EMT, which has been extensively proved by previous studies. So, how to distinguish the biased effect of LOX1 or AT1r alone or the enhanced effect of receptor conformational changes mediated by their receptor interaction? Is there any better evidence to elucidate this point?

(4) How does the interaction between AT1 and LOX1 affect the RAS system and blood pressure? What about the serum levels of rennin, angiotensin, and aldosterone in ND-fed or HFD-fed mice?

Reviewer #2 (Public Review):

Individuals with chronic kidney disease often have dyslipidemia, with the latter both a risk factor for atherosclerotic heart disease and a contributor to progressive kidney disease. Prior studies suggest that oxidized LDL (oxLDL) may cause renal injury through the activation of the LOX1 receptor. The authors had previously reported that LOX1 and AT1 interact to form a complex at the cell surface. In this study, the authors hypothesize that oxLDL, in the setting of angiotensin II, is responsible for driving renal injury by inducing a more pronounced conformational change of the AT1 receptor which results in enhanced Gq signaling.

They go about testing the hypothesis in a set of three studies. In the first set, they engineered CHO cell lines to express AT1R alone, LOX1 in combination with AT1R, or LOX1 with an inactive form of AT1R and indirectly evaluated Gq activity using IP1 and calcium activity as read-outs. They assessed activity after treatment with AngII, oxLDL, or both in combination and found that treatment with both agents resulted in the greatest level of activity, which could be effectively blocked by a Gq inhibitor but not a Gi inhibitor nor a downstream Rho kinase inhibitor targeting G12/13 signaling. These results support their hypothesis, though variability in the level of activation was dramatically inconsistent from experiment to experiment, differing by as much as 20-fold. In contrast, within the experiment, differences between the AngII and AngII/oxLDL treatments, while nominally significant and consistent with their hypothesis, generally were only 10-20%. Another example of unexplained variability can be found in Figures 1g-1j. AngII, at a concentration of 10-12, has no effect on calcium flux in one set of studies (Figure 1g, h) yet has induced calcium activity to a level as great as AngII + oxLDL in another (Figure 1i). The inconsistency of results lessens confidence in the significance of these findings. In other studies with the LOX1-CHO line, they tested for conformational change by transducing AT1 biosensors previously shown to respond to AngII and found that one of them in fact showed enhanced BRET in the setting of oxLDL and AngII compared to AngII alone, which was blocked by an antibody to AT1R. The result is supportive of their conclusions. Limiting enthusiasm for these results is the fact that there isn't a good explanation as to why only 1 sensor showed a difference, and the study should have included a non-specific antibody to control for non-specific effects.

The authors then repeated similar studies using publicly available rat kidney epithelial and fibroblast cell lines that have an endogenous expression of AT1R and LOX1. In these studies, oxLDL in combination with AngiI also enhanced Gq signaling, while knocking down either AT1R or LOX1, and treatment with inhibitors of Gq and AT1R blocked the effects. Like the prior set of studies, however, the effects are very modest and there was significant inter-experimental variability, reducing confidence in the significance of the findings. The authors then tested for evidence that the enhanced Gq signaling could result in renal injury by comparing qPCR results for target genes. While the results show some changes, their significance is difficult to assess. A more global assessment of gene expression patterns would have been more appropriate. In parallel with the transcriptional studies, they tested for evidence of epithelial-mesenchymal transition (EMT) using a single protein marker (alpha-smooth muscle actin) and found that its expression increased significantly in cells treated with oxLDL and AngII, which was blocked by inhibition of Gq inhibition and AT1R. While the data are sound, their significance is also unclear since EMT is a highly controversial cell culture phenomenon. Compelling in vivo studies have shown that most if not all fibroblasts in the kidney are derived from interstitial cells and not a product of EMT. In the last set of studies using these cell lines, the authors examined the effects of AngII and oxLDL on cell proliferation as assayed using BrdU. These results are puzzling---while the two agents together enhanced proliferation which was effectively blocked by an inhibitor to either AT1R or Gq, silencing of LOX1 had no effect.

The final set of studies looked to test the hypothesis in mice by treating WT and Lox1-KO mice with different doses of AngII and either a normal or high-fat diet (to induce oxLDL formation). The authors found that the combination of high dose AngII and a high-fat diet (HFD) increased markers of renal injury (urinary 8-ohdg and urine albumin) in normal mice compared to mice treated with just AngII or HFD alone, which was blunted in Lox1-KO mice). These results are consistent with their hypothesis. However, there are other aspects of these studies that are either inconsistent or complicating factors that limit the strength of the conclusions. For example, Lox1- KO had no effect on renal injury marker expression in mice treated with low-dose AngII and HFD. It also should be noted that Lox1-KO mice had a lower BP response to AngII, which could have reduced renal injury independent of any effects mediated by the AT1R/LOX1 interaction. Another confounding factor was the significant effect the HFD diet had on body weight. While the groups did not differ based on AngII treatment status, the HFD consistently was associated with lower total body weight, which is unexplained. Next, the authors sought to find more direct evidence of renal injury using qPCR of candidate genes and renal histology. The transcriptional results are difficult to interpret; moreover, there were no significant histologic differences between groups. They conclude the study by showing the pattern of expression of LOX1 and AT1R in the kidney by immunofluorescence and conclude that the proteins overlap in renal tubules and are absent from the glomerulus. Unfortunately, they did not co-stain with any other markers to identify the specific cell types. However, these results are inconsistent with other studies that show AT1R is highly expressed in mesangial cells, renal interstitial cells, near the vascular pole, JG cells, and proximal tubules but generally absent from most other renal tubule segments.

In sum, this study tackles an important clinical issue and provides some in vitro evidence to support a mechanism whereby dyslipidemia could accelerate renal functional decline through activation of the AT1R/LOX1 complex by oxLDL and AngII.

However, a very high degree of variability in the results, modest within-experiment differences, some internal inconsistencies that aren't explained, and the lack of compelling and strongly supportive in vivo results suggest this is still more a hypothesis than an established likely mechanism.

Reviewer #1 (Public Review):

Summary:

This article identifies ADGR3 as a candidate GPCR for mediating beige fat development. The authors use human expression data from the Human protein atlas and Gtex databases and combine this with experiments performed in mice and a murine cell line. They refer to a GPCR bioactivity screening tool PRESTO-Salsa, with which it was found that Hesperetin activates ADGR3. From their experiments, authors conclude that Hesperetin activates ADGR3, inducing a Gs-PKA-CREB axis resulting in adipose thermogenesis.

Strengths:

The authors analyze human data from public databases and perform functional studies in mouse models. They identify a new GPCR with a role in the thermogenic activation of adipocytes.

Weaknesses:

(1) Selection of ADGRA3 as a candidate GPCR relevant for mediating beiging in humans:

The authors identify genes upregulated in iBAT compared to iWAT in response to cold, and among these differentially expressed genes, they identify highly expressed GPCRs in human white adipocytes (visceral or subcutaneous). Finally, among these genes, they select a GPCR not previously studied in the literature.

If the authors are interested in beiging, why do they not focus on genes upregulated in iWAT (the depot where beiging is described to occur in mice), comparing thermoneutral to cold-induced genes? I would expect that genes induced in iWAT in response to cold would be extremely relevant targets for beiging. With their strategy, the authors exclude receptors that are induced in the tissue where beiging is actually described to occur.

Furthermore, the authors are comparing genes upregulated in cold in BAT (but not WAT) to highly expressed genes in human white adipocytes during thermoneutrality. Overall, the authors fail to discuss the logic behind their strategy and the obvious limitations of it.

(2) Relevance of ADGRA3 and comparison to established literature:

There has been a lot of literature and discussion about which receptor should be targeted in humans to recruit thermogenic fat. The current article unfortunately does not discuss this literature nor explain how it relates to their findings. For example, O'Mara et al (PMID: 31961826) demonstrated that chronic stimulation with the B3 adrenergic agonist, Mirabegron, resulted in the recruitment of thermogenic fat and improvement in insulin sensitivity and cholesterol. Later, Blondin et al (PMID: 32755608), highlighted the B2 adrenergic receptor as the main activation path of thermogenic fat in humans. There is also a recent report on an agonist activating B2 and B3 simultaneously (PMID: 38796310). Thus, to bring the literature forward, it would be beneficial if the current manuscript compared their identified activation path with the activation of these already established receptors and discussed their findings in relation to previous studies.

In Figures 1d and e, the authors show the expression of ADGRA3 in comparison to the expression of ADRB3. In human brown adipocytes, ADRB2 has been shown to be the main receptor through which adrenergic activation occurs (PMID: 32755608), thus authors should show the relative expression of this gene as well.

(3) Strategy to investigate the role of ADGRA3 in WAT beiging:

Having identified ADGRA3 as their candidate receptor, the authors proceed with investigations of this receptor in mouse models and the murine inguinal adipocyte cell line 3T3.

First of all, in Figure 1D, the authors show a substantially lower expression of ADGRA3 compared to ADRB3. It could thus be argued that a mouse would not be the best model system for studying this receptor. It would be interesting to see data from experiments in human adipocytes. Moreover, if the authors are interested in inducing beiging, why do they show expression in iBAT and not iWAT?

The authors perform in vivo experiments using intraperitoneal injections of shRNA or overexpression CMV-driven vectors and report effects on body temperature and glucose metabolism. It is here important to note that ADGRA3 is not uniquely expressed in adipocytes. A major advantage of databases like the Human Protein Atlas and Gtex, is that they give an overview of the gene expression across tissues and cell types. When looking up ADGRA3 in these databases, it is expressed in subcutaneous and visceral adipocytes. However, other cell types and tissues demonstrate an even higher expression. In the Human protein atlas, the enhanced cell types are astrocytes and hepatocytes. In the Gtex database tissues with the highest expression are Brain, Liver, and Thyroid.

With this information in mind, IP injections for modification of ADGRA3 receptor expression could be expected to affect any of these tissues and cells.

The manuscript report changes body temperature. However, temperature is regulated by the brain and also affected by thyroid activity. Did the authors measure the levels of circulating thyroid hormones? Gene expression changes in the brain? The authors report that Adgra3 overexpression decreased the TG level in serum and liver. The liver could be the primary targeted organ here, and the adipose effects might be secondary. The data would be easier to interpret if authors reported the effects on the liver, thyroid, and brain, and the gene expression across tissues should be discussed in the article.

Finally, the identification of Hesperetin using the PRESTO-Salsa tool, and how specific the effect of Hesperetin is on ADGRA3, is currently unclear. This should be better discussed, and authors should consider measuring the established effects of Hesperetin in their model systems, including apoptosis.

Reviewer #2 (Public Review):

Based on bioinformatics and expression analysis using mouse and human samples, the authors claim that the adhesion G-protein coupled receptor ADGRA3 may be a valuable target for increasing thermogenic activity and metabolic health. Genetic approaches to deplete ADGRA3 expression in vitro resulted in reduced expression of thermogenic genes including Ucp1, reduced basal respiration, and metabolic activity as reflected by reduced glucose uptake and triglyceride accumulation. In line, nanoparticle delivery of shAdgra3 constructs is associated with increased body weight, reduced thermogenic gene expression in white and brown adipose tissue (WAT, BAT), and impaired glucose and insulin tolerance. On the other hand, ADGRA3 overexpression is associated with an improved metabolic profile in vitro and in vivo, which can be explained by increasing the activity of the well-established Gs-PKA-CREB axis. Notably, a computational screen suggested that ADGRA3 is activated by hesperetin. This metabolite is a derivative of the major citrus flavonoid hesperidin and has been described to promote metabolic health. Using appropriate in vitro and in vivo studies, the authors show that hesperetin supplementation is associated with increased thermogenesis, UCP1 levels in WAT and BAT, and improved glucose tolerance, an effect that was attenuated in the absence of ADGRA3 expression.

Overall, the data suggest that ADGRA3 is a constitutively active Gs-coupled receptor that improves metabolism by activating adaptive thermogenesis in WAT and BAT. The conclusions of the paper are partly supported by the data, but some experimental approaches need further clarification.

(1) The in vivo approaches to modulate Adgra3 expression in mice are carried out using non-targeted nanoparticle-based approaches. The authors do not provide details of the composition of the nanomaterials, but it is highly likely that other metabolically active organs such as the liver are targeted. This is critical because Adgre3 is expressed in many organs, including the liver, adrenal glands, and gastrointestinal system. Therefore, many of the observed metabolic effects could be indirect, for example by modulating bile acids or corticosterone levels. Consistent with this, after digestion in the gastrointestinal tract, hesperetin is rapidly metabolized in intestinal and liver cells. Thus, hesperetin levels in the systemic circulation are likely to be insufficient to activate Adgra3 in thermogenic adipocytes/precursors. Overall, the authors need to repeat the key metabolic experiments in adipose-specific Adgra3 knockout/overexpression models to validate the reliability of the in vivo results. In addition, to validate the relevance of hesperetin supplementation for adaptive thermogenesis in BAT and WAT vivo, the levels of hesperetin present in the systemic circulation should be quantified.

(2) Standard measurements for energy balance are not presented. Quantitative data on energy expenditure, e.g. by indirect calorimetry, and food intake are missing and need to be included to validate the authors' claims.

(3) The thermographic images used to determine the BAT temperature are not very convincing. The distance and angle between the thermal camera and the BAT have a significant effect on the determination of the temperature, which is not taken into account, at least in the images presented.

(4) The 3T3-L1 cell line is not an adequate cell culture model to study thermogenic adipocyte differentiation. To validate their results, the key experiments showing that ADGRA3 expression modulates thermogenic marker expression in a hesperetin-dependent manner need to be performed in a reliable model, e.g. primary murine adipocytes.

(5) The experimental setup only allows the measurement of basal cellular respiration. More advanced approaches are needed to define the contribution of ADGRA3 versus classical adrenergic receptors to UCP1-dependent thermogenesis.

Reviewer #3 (Public Review):

Summary:

The manuscript by Zhao et al. explored the function of adhesion G protein-coupled receptor A3 (ADGRA3) in thermogenic fat biology.

Strengths:

Through both in vivo and in vitro studies, the authors found that the gain function of ADGRA3 leads to browning of white fat and ameliorates insulin resistance.

Weaknesses:

There are several lines of weak methodologies such as using 3T3-L1 adipocytes and intraperitoneal(i.p.) injection of virus. Moreover, as the authors stated that ADGRA3 is constitutively active, how could the authors then identify a chemical ligand?

Recommendations:

(1) Primary cultured cells should be used to perform gain and loss function analysis of ADGRA3, instead of using 3T3-L1. It is impossible to detect Ucp1 expression in 3T3-L1 cells.

(2) For virus treatment, the authors should consider performing local tissue injection, rather than IP injection. If it is IP injection, have the authors checked other tissues to validate whether the phenotype is fat-specific?

(3) The authors should clarify how constitutively active GPCR needs further ligands.

Reviewer #1 (Public Review):

Summary:

Qi and colleagues investigated the role of the Kallistatin pathway in increasing hippocampal amyloid-β plaque accumulation and tau hyperphosphorylation in Alzheimer's disease, linking the increased Kallistatin level in diabetic patients with a higher risk of Alzheimer's disease development. A Kallistatin-overexpressing animal model was utilized, and memory impairment was assessed using Morris water maze and Y-maze. Kallistatin-related pathway protein levels were measured in the hippocampus, and phenotypes were rescued using fenofibrate and rosiglitazone. The current study provides evidence of a novel molecular mechanism linking diabetes and Alzheimer's disease and suggests the potential use of fenofibrate to alleviate memory impairment. However, several issues need to be addressed before further consideration.

Strengths:

The findings of this study are novel. The findings will have great impacts on diabetes and AD research. The studies were well conducted, and the results were convincing.

Weaknesses:

(1) The mechanism by which fenofibrate rescues memory loss in Kallistatin-transgenic mice is unclear. As a PPARalpha agonist, does fenofibrate target the Kallistatin pathway directly or indirectly? Please provide a discussion based on literature supporting either possibility.

(2) The current study exclusively investigated the hippocampus. What about other cognitive memory-related regions, such as the prefrontal cortex? Including data from these regions or discussing the possibility of their involvement could provide a more comprehensive understanding of the role of Kallistatin in memory impairment.

(3) Fenofibrate rescued phenotypes in Kallistatin-transgenic mice while rosiglitazone, a PPARgamma agonist, did not. This result contradicts the manuscript's emphasis on a PPARgamma-associated mechanism. Please address this inconsistency.

(4) Most of the immunohistochemistry images are unclear. Inserts have similar magnification to the original representative images, making judgments difficult. Please provide larger inserts with higher resolution.

(5) The immunohistochemistry images in different figures were taken from different hippocampal subregions with different magnifications. Please maintain consistency, or explain why CA1, CA3, or DG was analyzed in each experiment.

(6) Figure 5B is missing a title. Please add a title to maintain consistency with other graphs.

(7) Please list statistical methods used in the figure legends, such as t-test or One-way ANOVA with post-hoc tests.

Reviewer #2 (Public Review):

Summary:

The study links Alzheimer's disease (AD) with metabolic disorders through elevated Kallistatin levels in AD patients. Kallistatin-overexpressing mice show cognitive decline, increased Aβ and tau pathology, and impaired hippocampal function. Mechanistically, Kallistatin enhances Aβ production via Notch1 and promotes tau phosphorylation through GSK-3β activation. Fenofibrate improves cognitive deficits by reducing Aβ and tau phosphorylation in these mice, suggesting therapeutic potential in AD linked to metabolic syndromes.

Strengths:

This study presents novel insights into AD pathogenesis and provides strong evidence about the mechanistic roles of Kallistatin, and the therapeutic potential of fenofibrate in AD.

Weaknesses:

It was suggested that Kallistatin is primarily produced by the liver. The study demonstrates increased Kallistatin levels in the hippocampus tissue of AD mice. It would be valuable to clarify if Kallistatin is also increased in the liver of AD mice, providing a comprehensive understanding of its distribution in disease states.

Does Kallistatin interact directly with Notch1 ligands? Clarifying this interaction mechanism would enhance understanding of how Kallistatin influences Notch1 signaling in AD pathology.

Is there any observed difference in AD phenotype between male and female Kallistatin-transgenic (KAL-TG) mice? Including this information would address potential gender-specific effects on cognitive decline and pathology.

It is recommended to include molecular size markers in Western blots for clarity and accuracy in protein size determination.

The language should be revised for enhanced readability and clarity, ensuring that complex scientific concepts are communicated effectively to a broader audience.

Reviewer #3 (Public Review):

Summary:

The authors investigated the role of kallistatin in metabolic abnormalities associated with AD. They found that Kallistatin promotes Aβ production by binding to the Notch1 receptor and upregulating BACE1 expression. They identified that Kallistatin is a key player that mediates Aβ accumulation and tau hyperphosphorylation in AD.

Strengths:

This manuscript not only provides novel insights into the pathogenesis of AD, but also indicates that the hypolipidemic drug fenofibrate attenuates AD-like pathology in Kallistatin transgenic mice.

Weaknesses:

The authors did not illustrate whether the protective effect of fenofibrate against AD depends on kallistatin.

The conclusions are supported by the results, but the quality of some results should be improved.

Reviewer #1 (Public Review):

Summary:

The authors report a study on how stimulation of receptive-field surround of V1 and LGN neurons affects their firing rates. Specifically, they examine stimuli in which a grey patch covers the classical RF of the cell and a stimulus appears in the surround. Using a number of different stimulus paradigms they find a long latency response in V1 (but not the LGN) which does not depend strongly on the characteristics of the surround grating (drifting vs static, continuous vs discontinuous, predictable grating vs unpredictable pink noise). They find that population responses to simple achromatic stimuli have a different structure that does not distinguish so clearly between the grey patch and other conditions and the latency of the response was similar regardless of whether the center or surround was stimulated by the achromatic surface. Taken together they propose that the surround-response is related to the representation of the grey surface itself. They relate their findings to previous studies that have put forward the concept of an 'inverse RF' based on strong responses to small grey patches on a full-screen grating. They also discuss their results in the context of studies that suggest that surround responses are related to predictions of the RF content or figure-ground segregation.

Strengths:

I find the study to be an interesting extension of the work on surround stimulation and the addition of the LGN data is useful showing that the surround-induced responses are not present in the feed-forward path. The conclusions appear solid, being based on large numbers of neurons obtained through Neuropixels recordings. The use of many different stimulus combinations provides a rich view of the nature of the surround-induced responses.

Weaknesses:

The statistics are pooled across animals, which is less appropriate for hierarchical data. There is no histological confirmation of placement of the electrode in the LGN and there is no analysis of eye or face movements which may have contributed to the surround-induced responses. There are also some missing statistics and methods details which make interpretation more difficult.

Reviewer #2 (Public Review):

Cuevas et al. investigate the stimulus selectivity of surround-induced responses in the mouse primary visual cortex (V1). While classical experiments in non-human primates and cats have generally demonstrated that stimuli in the surround receptive field (RF) of V1 neurons only modulate activity to stimuli presented in the center RF, without eliciting responses when presented in isolation, recent studies in mouse V1 have indicated the presence of purely surround-induced responses. These have been linked to prediction error signals. In this study, the authors build on these previous findings by systematically examining the stimulus selectivity of surround-induced responses.

Using neuropixels recordings in V1 and the dorsal lateral geniculate nucleus (dLGN) of head-fixed, awake mice, the authors presented various stimulus types (gratings, noise, surfaces) to the center and surround, as well as to the surround only, while also varying the size of the stimuli. Their results confirm the existence of surround-induced responses in mouse V1 neurons, demonstrating that these responses do not require spatial or temporal coherence across the surround, as would be expected if they were linked to prediction error signals. Instead, they suggest that surround-induced responses primarily reflect the representation of the achromatic surface itself.

The literature on center-surround effects in V1 is extensive and sometimes confusing, likely due to the use of different species, stimulus configurations, contrast levels, and stimulus sizes across different studies. It is plausible that surround modulation serves multiple functions depending on these parameters. Within this context, the study by Cuevas et al. makes a significant contribution by exploring the relationship between surround-induced responses in mouse V1 and stimulus statistics. The research is meticulously conducted and incorporates a wide range of experimental stimulus conditions, providing valuable new insights regarding center-surround interactions.

However, the current manuscript presents challenges in readability for both non-experts and experts. Some conclusions are difficult to follow or not clearly justified.

I recommend the following improvements to enhance clarity and comprehension:

(1) Clearly state the hypotheses being tested at the beginning of the manuscript.

(2) Always specify the species used in referenced studies to avoid confusion (esp. Introduction and Discussion).

(3) Briefly summarize the main findings at the beginning of each section to provide context.

(4) Clearly define important terms such as "surface stimulus" and "early vs. late stimulus period" to ensure understanding.

(5) Provide a rationale for each result section, explaining the significance of the findings.

(6) Offer a detailed explanation of why the results do not support the prediction error signal hypothesis but instead suggest an encoding of the achromatic surface.

These adjustments will help make the manuscript more accessible and its conclusions more compelling.

Reviewer #3 (Public Review):

Summary:

This paper explores the phenomenon whereby some V1 neurons can respond to stimuli presented far outside their receptive field. It introduces three possible explanations for this phenomenon and it presents experiments that it argues favor the third explanation, based on figure/ground segregation.

Strengths:

I found it useful to see that there are three possible interpretations of this finding (prediction error, interpolation, and figure/ground). I also found it useful to see a comparison with LGN responses and to see that the effect there is not only absent but actually the opposite: stimuli presented far outside the receptive field suppress rather than drive the neurons. Other experiments presented here may also be of interest to the field.

Weaknesses:

The paper is not particularly clear. I came out of it rather confused as to which hypotheses were still standing and which hypotheses were ruled out. There are numerous ways to make it clearer.

Reviewer #1 (Public Review):

Summary:

The study aimed to better understand the role of the H3 protein of the Monkeypox virus (MPXV) in host cell adhesion, identifying a crucial α-helical domain for interaction with heparan sulfate (HS). Using a combination of advanced computational simulations and experimental validations, the authors discovered that this domain is essential for viral adhesion and potentially a new target for developing antiviral therapies.

Strengths:

The study's main strengths include the use of cutting-edge computational tools such as AlphaFold2 and molecular dynamics simulations, combined with robust experimental techniques like single-molecule force spectroscopy and flow cytometry. These methods provided a detailed and reliable view of the interactions between the H3 protein and HS. The study also highlighted the importance of the α-helical domain's electric charge and the influence of the Mg(II) ion in stabilizing this interaction. The work's impact on the field is significant, offering new perspectives for developing antiviral treatments for MPXV and potentially other viruses with similar adhesion mechanisms. The provided methods and data are highly useful for researchers working with viral proteins and protein-polysaccharide interactions, offering a solid foundation for future investigations and therapeutic innovations.

Weaknesses:

However, some limitations are notable. Despite the robust use of computational methodologies, the limitations of this approach are not discussed, such as potential sources of error, standard deviation rates, and known controls for the H3 protein to justify the claims. Additionally, validations with methodologies like X-ray crystallography would further benefit the visualization of the H3 and HS interaction.

Reviewer #2 (Public Review):

Summary:

The manuscript presenting the discovery of a heparan-sulfate (HS) binding domain in monkeypox virus (MPXV) H3 protein as a new anti-poxviral drug target, presented by Bin Zhen and co-workers, is of interest, given that it offers a potentially broad antiviral substance to be used against poxviruses. Using new computational biology techniques, the authors identified a new alpha-helical domain in the H3 protein, which interacts with cell surface HS, and this domain seems to be crucial for H3-HS interaction. Given that this domain is conserved across orthopoxviruses, authors designed protein inhibitors. One of these inhibitors, AI-PoxBlock723, effectively disrupted the H3-HS interaction and inhibited infection with Monkeypox virus and Vaccinia virus. The presented data should be of interest to a diverse audience, given the possibility of an effective anti-poxviral drug. 

Strengths:

In my opinion, the experiments done in this work were well-planned and executed. The authors put together several computational methods, to design poxvirus inhibitor molecules, and then they test these molecules for infection inhibition.

Weaknesses:

One thing that could be improved, is the presentation of results, to make them more easily understandable to readers, who may not be experts in protein modeling programs. For example, figures should be self-explanatory and understood on their own, without the need to revise text. Therefore, the figure legend should be more informative as to how the experiments were done.

Reviewer #3 (Public Review):

Summary:

The article is an interesting approach to determining the MPOX receptor using "in silico" tools. The results show the presence of two regions of the H3 protein with a high probability of being involved in the interaction with the HS cell receptor. However, the α-helical region seems to be the most probable, since modifications in this region affect the virus binding to the HS receptor.

Strengths:

In my opinion, it is an informative article with interesting results, generated by a combination of "in silico" and wet science to test the theoretical results. This is a strong point of the article.

Weaknesses:

Has a crystal structure of the H3 protein been reported?

The following text is in line 104: "which may represent a novel binding site for HS". It is unclear whether this means this "new binding site" is an alternative site to an old one or whether it is the true binding site that had not been previously elucidated.

Reviewer #2 (Public Review):

In this manuscript, the authors analyze the shapes of cerebral cortices from several primate species, including subgroups of young and old humans, to characterize commonalities in patterns of gyrification, cortical thickness, and cortical surface area. The authors state that the observed scaling law shares properties with fractals, where shape properties are similar across several spatial scales. One way the authors assess this is to perform a "cortical melting" operation that they have devised on surface models obtained from several primate species. The authors also explore differences in shape properties between brains of young (~20 year old) and old (~80) humans. A challenge the authors acknowledge struggling with in reviewing the manuscript is merging "complex mathematical concepts and a perplexing biological phenomenon." This reviewer remains a bit skeptical about whether the complexity of the mathematical concepts being drawn from are justified by the advances made in our ability to infer new things about the shape of the cerebral cortex.

(1) The series of operations to coarse-grain the cortex illustrated in Figure 1 produces image segmentations that do not resemble real brains. The process to assign voxels in downsampled images to cortex and white matter is biased towards the former, as only 4 corners of a given voxel are needed to intersect the original pial surface, but all 8 corners are needed to be assigned a white matter voxel. The reason for introducing this bias (and to the extent that it is present in the authors' implementation) is not provided. The authors provide an intuitive explanation of why thickness relates to folding characteristics, but ultimately an issue for this reviewer is, e.g., for the right-most panel in Figure 2b, the cortex consists of several 4.9-sided voxels and thus a >2 cm thick cortex. A structure with these morphological properties is not consistent with the anatomical organization of typical mammalian neocortex.

(2) For the comparison between 20-year-old and 80-year-old brains, a well-documented difference is that the older age group possesses more cerebral spinal fluid due to tissue atrophy, and the distances between the walls of gyri becomes greater. This difference is born out in the left column of Figure 4b. It seems this additional spacing between gyri in 80 year olds requires more extensive down-sampling (larger scale values in Figure 4a) to achieve a similar shape parameter K as for the 20 year olds. The authors assert that K provides a more sensitive measure (associated with a large effect size) than currently used ones for distinguishing brains of young vs. old people. A more explicit, or elaborate, interpretation of the numbers produced in this manuscript, in terms of brain shape, might make this analysis more appealing to researchers in the aging field.

(3) In the Discussion, it is stated that self-similarity, operating on all length scales, should be used as a test for existing and future models of gyrification mechanisms. Given the lack of association between the abstract mathematical parameters described in this study and explicit properties of brain tissue and its constituents, it is difficult to envision how the coarse-graining operation can be used to guide development of "models of cortical gyrification."

(4) There are several who advocate for analyzing cortical mid-thickness surfaces, as the pial surface over-represents gyral tips compared to the bottoms of sulci in the surface area. The authors indicate that analyses of mid-thickness representations will be taken on in future work, but this seems to be a relevant control for accepting the conclusions of this manuscript.

Reviewer #3 (Public Review):

Summary: Through a rigorous methodology, the authors demonstrated that within 11 different primates, the shape of the brain followed a universal scaling law with fractal properties. They enhanced the universality of this result by showing the concordance of their results with a previous study investigating 70 mammalian brains, and the discordance of their results with other folded objects that are not brains. They incidentally illustrated potential applications of this fractal property of the brain by observing a scale-dependant effect of aging on the human brain.

Strengths:<br /> - New hierarchical way of expressing cortical shapes at different scales derived from previous report through implementation of a coarse-graining procedure<br /> - Investigation of 11 primate brains and contextualisation with other mammals based on prior literature<br /> - Proposition of tool to analyse cortical morphology requiring no fine tuning and computationally achievable<br /> - Positioning of results in comparison to previous works reinforcing the validity of the observation.<br /> - Illustration of scale-dependance of effects of brain aging in the human.

Weaknesses:<br /> - The notion of cortical shape, while being central to the article, is not really defined, leaving some interpretation to the reader<br /> - The organization of the manuscript is unconventional, leading to mixed contents in different sections (sections mixing introduction and method, methods and results, results and discussion...). As a result, the reader discovers the content of the article along the way, it is not obvious at what stages the methods are introduced, and the results are sometimes presented and argued in the same section, hindering objectivity.<br /> To improve the document, I would suggest a modification and restructuring of the article such that: 1) by the end of the introduction the reader understands clearly what question is addressed and the value it holds for the community, 2) by the end of the methods the reader understands clearly all the tools that will be used to answer that question (not just the new method), 3) by the end of the results the reader holds the objective results obtained by applying these tools on the available data (without subjective interpretations and justifications), and 4) by the end of the discussion the reader understands the interpretation and contextualisation of the study, and clearly grasps the potential of the method depicted for the better understanding of brain folding mechanisms and properties.

Reviewer #2 (Public Review):

Summary:

The manuscript focuses on comparison of two PLP-dependent enzyme classes that perform amino acyl decarboxylations. The goal of the work is to understand the substrate specificity and factors that influence catalytic rate in an enzyme linked to theanine production in tea plants.

Strengths:

The work includes x-ray crystal structures of modest resolution of the enzymes of interest. These structures provide the basis for design of mutagenesis experiments to test hypotheses about substrate specificity and the factors that control catalytic rate. These ideas are tested via mutagenesis and activity assays, in some cases both in vitro and in plants.

Weaknesses:

Although improved in a revision, the manuscript could be more clear in explaining the contents of the x-ray structures and how the complexes studied relate to the reactant and product complexes. Some of the figures lack sufficient clarity and description. Some of the claims about the health benefits of tea are not well supported by literature citations.

Reviewer #3 (Public Review):

In the manuscript titled "Structure and Evolution of Alanine/Serine Decarboxylases and the Engineering of Theanine Production," Wang et al. solved and compared the crystal structures of Alanine Decarboxylase (AlaDC) from Camellia sinensis and Serine Decarboxylase (SerDC) from Arabidopsis thaliana. Based on this structural information, the authors conducted both in vitro and in vivo functional studies to compare enzyme activities using site-directed mutagenesis and subsequent evolutionary analyses. This research has the potential to enhance our understanding of amino acid decarboxylase evolution and the biosynthetic pathway of the plant specialized metabolite theanine, as well as to further its potential applications in the tea industry.

Reviewer #2 (Public Review):

Significance:

Rubio et al. study the behavior of the transcription factor Hsf1 under ethanol stress, examining its distribution within the nucleus and the coalescence of heat shock response genes in budding yeast. In comparison to the heat shock response, the response to ethanol stress shows similar gene coalescence and Hsf1 binding. However, there is a notable delay in the transcriptional response to ethanol, and a disconnect between it and the appearance of irreversible Hsf1 condensates/puncta, highlighting important differences in how Hsf1 responds to these two related but distinct environmental stresses.

Overview and general concerns (from the original review):

The authors studied how yeast responds to ethanol stress (8.5%) and compared it to the heat shock response (from 25{degree sign}C to 39{degree sign}C). They observed a more gradual increase in the expression of heat shock response (HSR) genes during ethanol stress compared to heat shock. Additionally, the recruitment of Hsf1 and Pol II to HSR genes, and the inter- and intrachromosomal interactions among these genes, showed slower kinetics under ethanol stress. They attribute the delay in transcriptional response to chromatin compaction induced by ethanol. Despite this delay, these interactions persisted longer. Hsf1 clusters, previously documented during the heat shock response, were also observed during ethanol stress and persisted for an extended period. The conditional degradation of Hsf1 and Rpb1 eliminated most inter- and intrachromosomal interactions for heat shock responsive genes in both ethanol stress and heat shock conditions, indicating the importance of these factors for long distance interactions between HSR genes. Overall, this manuscript provides novel insights into the differential behavior of HSR genes under different stress conditions. This contributes to the broader understanding of how different stressors might elicit unique responses at the genomic and topographical level under the regulation of transcription factor Hsf1.

The central finding of the study highlights the different dynamics of Hsf1, Pol II, and gene organization in response to heat shock versus ethanol stress. However, one important limitation to consider is that the two chosen conditions may not be directly comparable. For a balanced assessment, the authors should ideally expose yeast to various ethanol concentrations and different heat shock temperatures, ensuring the observed differences stem from the nature of the stressor rather than suboptimal stress intensity. At the very least, an additional single ethanol concentration point on each side of 8.5% should be investigated to ensure that 8.5% is near the optimum. In fact, comparing the number of Hsp104 foci in the two conditions in Fig. 1E and F suggests that the yeast is likely experiencing different intensities of stress for the chosen heat shock condition and ethanol concentration used in this study.

A second significant concern is the use of the term "Hsf1 condensate". Chowdhary et al.'s 2022 Molecular Cell study highlighted an inhomogeneous distribution and rapid dynamics of Hsf1 clustering upon heat shock, with sensitivity to 1,6-hexandiol, which is interpreted as evidence for condensation by LLPS. But this interpretation has been criticized severely by McSwiggen at al. Genes Dev 2019 and Mussacchio EMBO J 2022. It is important to mention that 1,6-hexandiol is known to affect chromatin organization (Itoh et al. Life Science Alliance 2021). Describing such clusters as 'condensates' without further experimental evidence is premature. I encourage authors to settle on their neutral term 'puncta' which they use interchangeably with 'condensate' so as not to confuse the reader. The dynamic binding and unbinding of the low-abundance Hsf1 at coalescent chromatin target sites might explain the liquid-like properties of these clusters without the need for invoking the phase-separation hypothesis. While Hsf1 clusters exhibit features consistent with phase-separated condensates, other equally plausible alternative mechanisms, such as dynamic site-specific interactions (Musacchio, EMBO J, 2022), should also be considered. This is best left for the discussion where the underlying mechanism for puncta formation can be addressed.

Comments on revised version:

The authors have addressed the majority of my comments effectively. The new Sis1 experiment provides a clear illustration of a distinctive response to ethanol and heat. This work offers a comprehensive perspective on Hsf1 in stress response from multiple angles. I have two additional comments to improve the paper without re-review:

(Original point #3) Could the authors clarify the differences between DPY1561 and the original strain used? There appears to be missing statistical analysis for Figure 1E at the bottom.

(Original point #4) In the new Figure 7F, '% transcription' and '% coalescence' are presented. My understanding is that Figures 7D and 7E aim to demonstrate the correlation between HSP104 transcription (a continuous variable) and HSP104-HSP12 coalescence (a binary variable) at the single-cell level. However, averaging the data across cells masks individual variations and potential anti-correlations. The authors could explore statistical methods that handle correlations between a continuous variable and a binary variable. Alternatively, consider converting 'HSP104 transcription' to a binary variable and then performing a chi-square test to assess the association.

Reviewer #3 (Public Review):

This is an interesting manuscript that builds off of this group's previous work focused on the interface between Hsf1, heat shock protein (HSP) mRNA production, and 3D genome topology. Here the group subjects the yeast Saccharomyces cerevisiae to either heat stress (HS) or ethanol stress (ES) and examines Hsf1 and Pol II chromatin binding, Histone occupancy, Hsf1 condensates, HSP gene coalescence (by 3C and live cell imaging), and HSP mRNA expression (by RT-qPCR and live cell imaging). The manuscript is well written, and the experiments seem well done, and generally rigorous, with orthogonal approaches performed to support conclusions. The main findings are that both HS and ES result in Hsf1/Pol II-dependent intergenic interactions, along with formation of Hsf1 condensates. Yet, while HS results in rapid and strong induction of HSP gene expression and Hsf1 condensate resolution, ES result in slow and weak induction of HSP gene expression without Hsf1 condensate resolution. Thus, the conclusion is somewhat phenomenological - that the same transcription factor can drive distinct transcription, topologic, and phase-separation behavior in response to different types of stress. While identifying a mechanistic basis for these results would be a tough task perhaps beyond the scope of this study, it would nevertheless be helpful to place these results in context with a series of other studies demonstrating across various organisms showing Hsf1 driving distinct activities dependent on the context of activation. Perhaps even more importantly, this work left out PMID: 32015439 which is particularly relevant considering that it shows that it is human HSF1 condensate resolution rather than simple condensate formation that is associated with HSF1 transcriptional activity - which are similar to the findings here with this particular dose of HS resulting in resolution and high transcriptional activity versus ES resulting in resolution failure and lower activity. It is also worth noting that the stresses themselves are quite different - ethanol can be used as a carbon source and so beyond inducing proteotoxic stress, the yeast are presumably adapting to this distinct metabolic state. Basically, it is not clear whether these differences are due to the dose of stress, versus we are looking at an early timepoint as ES initiates a genome-wide chromatin restructuring and gene expression reprogramming that goes beyond a response to proteotoxic stress. This reviewer is not suggesting a barrage of new experiments, but perhaps discussion points to contextualize results.

Comments on latest version:

The authors have addressed my concerns.

Reviewer #1 (Public Review):

(1) Significance of the findings:

Cell-to-cell communication is essential for higher functions in bacterial biofilms. Electrical signals have proven effective in transmitting signals across biofilms. These signals are then used to coordinate cellular metabolisms or to increase antibiotic tolerance. Here, the authors have reported for the first time coordinated oscillation of membrane potential in E. coli biofilms that may have a functional role in photoprotection.

(2) Strengths of the manuscript:

- The authors report original data.<br /> - For the first time, they showed that coordinated oscillations in membrane potential occur in E. Coli biofilms.<br /> - The authors revealed a complex two-phase dynamic involving distinct molecular response mechanisms.<br /> - The authors developed two rigorous models inspired by 1) Hodgkin-Huxley model for the temporal dynamics of membrane potential and 2) Fire-Diffuse-Fire model for the propagation of the electric signal.<br /> - Since its discovery by comparative genomics, the Kch ion channel has not been associated with any specific phenotype in E. coli. Here, the authors proposed a functional role for the putative gated-voltage-gated K+ ion channel (Kch channel) : enhancing survival under photo-toxic conditions.

(3) Weakness:

- Contrarily to what is stated in the abstract, the group of B. Maier has already reported collective electrical oscillations in the Gram-negative bacterium Neisseria gonorrhoeae (Hennes et al., PLoS Biol, 2023).<br /> - The data presented in the manuscript are not sufficient to conclude on the photo-protective role of the Kch channel. The authors should perform the appropriate control experiments related to Fig4D,E, i.e. reproduce these experiments without ThT to rule out possible photo-conversion effects on ThT that would modify its toxicity. In addition, it looks like the data reported on Fig 4E are extracted from Fig 4D. If this is indeed the case, it would be more conclusive to report the percentage of PI-positive cells in the population for each condition. This percentage should be calculated independently for each replicate. The authors should then report the average value and standard deviation of the percentage of dead cells for each condition.<br /> - Although Fig 4A clearly shows that light stimulation has an influence on the dynamics of ThT signal in the biofilm, it is important to rule out possible contributions of other environmental variations that occur when the flow is stopped at the onset of light stimulation. I understand that for technical reasons, the flow of fresh medium must be stopped for the sake of imaging. Therefore, I suggest to perform control experiments consisting in stopping the flow at different time intervals before image acquisition (30min or 1h before). If there is no significant contribution from environmental variations due to medium perfusion arrest, the dynamics of ThT signal must be unchanged regardless of the delay between flow stop and the start of light stimulation.<br /> - To precise the role of K+ in the habituation response, I suggest using the ionophore valinomycin at sub-inhibitory concentrations (5 or 10µM). It should abolish the habituation response. In addition, the Kch complementation experiment exhibits a sharp drop after the first peak but on a single point. It would be more convincing to increase the temporal resolution (1min->10s) to show that there are indeed a first and a second peak. Finally, the high concentration (100µM) of CCCP used in this study completely inhibits cell activity. Therefore, it is not surprising that no ThT dynamics was observed upon light stimulation at such concentration of CCCP.<br /> - Since TMRM signal exhibits a linear increase after the first response peak (Supp Fig1D), I recommend to mitigate the statement at line 78.<br /> - Electrical signal propagation is an important aspect of the manuscript. However, a detailed quantitative analysis of the spatial dynamics within the biofilm is lacking. At minima, I recommend to plot the spatio-temporal diagram of ThT intensity profile averaged along the azimuthal direction in the biofilm. In addition, it is unclear if the electrical signal propagates within the biofilm during the second peak regime, which is mediated by the Kch channel: I have plotted the spatio-temporal diagram for Video S3 and no electrical propagation is evident at the second peak. In addition, the authors should provide technical details of how R^2(t) is measured in the first regime (Fig 7E).<br /> - In the series of images presented in supplementary Figure 4A, no wavefront is apparent. Although the microscopy technics used in this figure differs from other images (like in Fig2), the wavefront should be still present. In addition, there is no second peak in confocal images as well (Supp Fig4B) .<br /> - Many important technical details are missing (e.g. biofilm size, R^2, curvature and 445nm irradiance measurements). The description of how these quantitates are measured should be detailed in the Material & Methods section.<br /> - Fig 5C: The curve in Fig 5D seems to correspond to the biofilm case. Since the model is made for single cells, the curve obtained by the model should be compared with the average curve presented in Fig 1B (i.e. single cell experiments).<br /> - For clarity, I suggest to indicate on the panels if the experiments concern single cell or biofilm experiments. Finally, please provide bright-field images associated to ThT images to locate bacteria.<br /> - In Fig 7B, the plateau is higher in the simulations than in the biofilm experiments. The authors should add a comment in the paper to explain this discrepancy.

Reviewer #2 (Public Review):

The authors use ThT dye as a Nernstian potential dye in E. coli. Quantitative measurements of membrane potential using any cationic indicator dye are based on the equilibration of the dye across the membrane according to Boltzmann's law.

Ideally, the dye should have high membrane permeability to ensure rapid equilibration. Others have demonstrated that E.coli cells in the presence of ThT do not load unless there is blue light present, that the loading profile does not look like it is expected for a cationic Nernstian dye. They also show that the loading profile of the dye is different for E.coli cells deleted for the TolC pump. I, therefore, objected to interpreting the signal from the ThT as a Vm signal when used in E.coli. Nothing the authors have said has suggested that I should be changing this assessment.

Specifically, the authors responded to my concerns as follows:

(1) 'We are aware of this study, but believe it to be scientifically flawed. We do not cite the article because we do not think it is a particularly useful contribution to the literature.' This seems to go against ethical practices when it comes to scientific literature citations. If the authors identified work that handles the same topic they do, which they believe is scientifically flawed, the discussion to reflect that should be included.

(2)'The Pilizota group invokes some elaborate artefacts to explain the lack of agreement with a simple Nernstian battery model. The model is incorrect not the fluorophore.'<br /> It seems the authors object to the basic principle behind the usage of Nernstian dyes. If the authors wish to use ThT according to some other model, and not as a Nernstian indicator, they need to explain and develop that model. Instead, they state 'ThT is a Nernstian voltage indicator' in their manuscript and expect the dye to behave like a passive voltage indicator throughout it.

(3)'We think the proton effect is a million times weaker than that due to potassium i.e. 0.2 M K+<br /> versus 10-7 M H+. We can comfortably neglect the influx of H+ in our experiments.'<br /> I agree with this statement by the authors. At near-neutral extracellular pH, E.coli keeps near-neutral intracellular pH, and the contribution from the chemical concentration gradient to the electrochemical potential of protons is negligible. The main contribution is from the membrane potential. However, this has nothing to do with the criticism to which this is the response of the authors. The criticism is that ThT has been observed not to permeate the cell without blue light. The blue light has been observed to influence the electrochemical potential of protons (and given that at near-neutral intracellular and extracellular pH this is mostly the membrane potential, as authors note themselves, we are talking about Vm effectively). Thus, two things are happening when one is loading the ThT, not just expected equilibration but also lowering of membrane potential. The electrochemical potential of protons is coupled via the membrane potential to all the other electrochemical potentials of ions, including the mentioned K+.

(4) 'The vast majority of cells continue to be viable. We do not think membrane damage is dominating.' In response to the question on how the authors demonstrated TMRM loading and in which conditions (and while reminding them that TMRM loading profile in E.coli has been demonstrated in Potassium Phosphate buffer). The request was to demonstrate TMRM loading profile in their condition as well as to show that it does not depend on light. Cells could still be viable, as membrane permeabilisation with light is gradual, but the loading of ThT dye is no longer based on simple electrochemical potential (of the dye) equilibration.

(5) On the comment on the action of CCCP with references included, authors include a comment that consists of phrases like 'our understanding of the literature' with no citations of such literature. Difficult to comment further without references.

(6) 'Shielding would provide the reverse effect, since hyperpolarization begins in the dense centres of the biofilms. For the initial 2 hours the cells receive negligible blue light. Neither of the referee's comments thus seem tenable.'<br /> The authors have misunderstood my comment. I am not advocating shielding (I agree that this is not it) but stating that this is not the only other explanation for what they see (apart from electrical signaling). The other I proposed is that the membrane has changed in composition and/or the effective light power the cells can tolerate. The authors comment only on the light power (not convincingly though, giving the number for that power would be more appropriate), not on the possible changes in the membrane permeability.

(7) 'The work that TolC provides a possible passive pathway for ThT to leave cells seems slightly niche. It just demonstrates another mechanism for the cells to equilibrate the concentrations of ThT in a Nernstian manner i.e. driven by the membrane voltage.' I am not sure what the authors mean by another mechanism. The mechanism of action of a Nernstian dye is passive equilibration according to the electrochemical potential (i.e. until the electrochemical potential of the dye is 0).

(8) 'In the 70 years since Hodgkin and Huxley first presented their model, a huge number of similar models have been proposed to describe cellular electrophysiology. We are not being hyperbolic when we state that the HH models for excitable cells are like the Schrödinger<br /> equation for molecules. We carefully adapted our HH model to reflect the currently understood electrophysiology of E. coli.'

I gave a very concrete comment on the fact that in the HH model conductivity and leakage are as they are because this was explicitly measured. The authors state that they have carefully adopted their model based on what is currently understood for E.coli electrophysiology. It is not clear how. HH uses gKn^4 based on Figure2 here https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1392413/pdf/jphysiol01442-0106.pdf, i.e. measured rise and fall of potassium conductance on msec time scales. I looked at the citation the authors have given and found a resistance of an entire biofilm of a given strain at 3 applied voltages. So why n^4 based on that? Why does unknown current have gqz^4 form? Sodium conductance in HH is described by m^3hgNa (again based on detailed conductance measurements), so why unknown current in E.coli by gQz^4? Why leakage is in the form that it is, based on what measurement?

Throughout their responses, the authors seem to think that collapsing the electrochemical gradient of protons is all about protons, and this is not the case. At near neutral inside and outside pH, the electrochemical potential of protons is simply membrane voltage. And membrane voltage acts on all ions in the cell.

Authors have started their response to concrete comments on the usage of ThT dye with comments on papers from my group that are not all directly relevant to this publication. I understand that their intention is to discredit a reviewer but given that my role here is to review this manuscript, I will only address their comments to the publications/part of publications that are relevant to this manuscript and mention what is not relevant.

Publications in the order these were commented on.

(1) In a comment on the paper that describes the usage of ThT dye as a Nernstian dye authors seem to talk about a model of an entire active cell.<br /> 'Huge oscillations occur in the membrane potentials of E. coli that cannot be described by the SNB model.' The two have nothing to do with each other. Nernstian dye equilibrates according to its electrochemical potential. Once that happens it can measure the potential (under the assumption that not too much dye has entered and thus lowered too much the membrane potential under measurement). The time scale of that is important, and the dye can only measure processes that are slower than that equilibration. If one wants to use a dye that acts under a different model, first that needs to be developed, and then coupled to any other active cell model.

(2) The part of this paper that is relevant is simply the usage of TMRM dye. It is used as Nernstian dye, so all the above said applies. The rest is a study of flagellar motor.

(3) The authors seem to not understand that the electrochemical potential of protons is coupled to the electrochemical potentials of all other ions, via the membrane potential. In the manuscript authors talk about, PMF~Vm, as DeltapH~0. Other than that this publication is not relevant to their current manuscript.

(4) The manuscript in fact states precisely that PMF cannot be generated by protons only and some other ions need to be moved out for the purpose. In near neutral environment it stated that these need to be cations (K+ e.g.). The model used in this manuscript is a pump-leak model. Neither is relevant for the usage of ThT dye.

Further comments include, along the lines of:

'The editors stress the main issue raised was a single referee questioning the use of ThT as an indicator of membrane potential. We are well aware of the articles by the Pilizota group and we believe them to be scientifically flawed. The authors assume there are no voltage-gated ion channels in E. coli and then attempt to explain motility data based on a simple Nernstian battery model (they assume E. coli are unexcitable<br /> matter). This in turn leads them to conclude the membrane dye ThT is faulty, when in fact it is a problem with their simple battery model.'

The only assumption made when using a cationic Nernstian dye is that it equilibrates passively across the membrane according to its electrochemical potential. As it does that, it does lower the membrane potential, which is why as little as possible is added so that this is negligible. The equilibration should be as fast as possible, but at the very least it should be known, as no change in membrane potential can be measured that is faster than that.

This behaviour should be orthogonal to what the cell is doing, it is a probe after all. If the cell is excitable, a Nernstian dye can be used, as long as it's still passively equilibrating and doing so faster than any changes in membrane potential due to excitations of the cells. There are absolutely no assumptions made on the active system that is about to be measured by this expected behaviour of a Nernstian dye. And there shouldn't be, it is a probe. If one wants to use a dye that is not purely Nernstian that behaviour needs to be described and a model proposed. As far as I can find, authors do no such thing.

There is a comment on the use of a flagellar motor as a readout of PMF, stating that the motor can be stopped by YcgR citing the work from 2023. Indeed, there is a range of references such as https://doi.org/10.1016/j.molcel.2010.03.001 that demonstrate this (from around 2000-2010 as far as I am aware). The timescale of such slowdown is hours (see here Figure 5 https://www.cell.com/cell/pdf/S0092-8674(10)00019-X.pdf). Needless to say, the flagellar motor when used as a probe, needs to stay that in the conditions used. Thus one should always be on the lookout at any other such proteins that could slow it down and we are not aware of yet or make the speed no longer proportional to the PMF. In the papers my group uses the motor the changes are fast, often reversible, and in the observation window of 30min. They are also the same with DeltaYcgR strain, which we have not included as it seemed given the time scales it's obvious, but certainly can in the future (as well as stay vigilant on any conditions that would render the motor a no longer suitable probe for PMF).

Reviewer #3 (Public Review):

This manuscript by Akabuogu et al. investigates membrane potential dynamics in E. coli. Membrane potential fluctuations have been observed in bacteria by several research groups in recent years, including in the context of bacterial biofilms where they have been proposed to play a role in cellular communication. Here, these authors investigate membrane potential in E. coli, in both single cells and biofilms. I have reviewed the revised manuscript provided by the authors, as well as their responses to the initial reviews; my opinion about the manuscript is largely unchanged. I have focused my public review on those issues that I believe to be most pressing, with additional comments included in the review to authors. Although these authors are working in an exciting research area, the evidence they provide for their claims is inadequate, and several key control experiments are still missing. In some cases, the authors allude to potentially relevant data in their responses to the initial reviews, but unfortunately these data are not shown. Furthermore, I cannot identify any traveling wavefronts in the data included in this manuscript. In addition to the challenges associated with the use of Thioflavin-T (ThT) raised by the second reviewer, these caveats make the work presented in this manuscript difficult to interpret.

First, some of the key experiments presented in the paper lack required controls:

(1) This paper asserts that the observed ThT fluorescence dynamics are induced by blue light. This is a fundamental claim in the paper, since the authors go on to argue that these dynamics are part of a blue light response. This claim must be supported by the appropriate negative control experiment measuring ThT fluorescence dynamics in the absence of blue light- if this idea is correct, these dynamics should not be observed in the absence of blue light exposure. If this experiment cannot be performed with ThT since blue light is used for its excitation, TMRM can be used instead.

In response to this, the authors wrote that "the fluorescent baseline is too weak to measure cleanly in this experiment." If they observe no ThT signal above noise in their time lapse data in the absence of blue light, this should be reported in the manuscript- this would be a satisfactory negative control. They then wrote that "It appears the collective response of all the bacteria hyperpolarization at the same time appears to dominate the signal." I am not sure what they mean by this- perhaps that ThT fluorescence changes strongly only in response to blue light? This is a fundamental control for this experiment that ought to be presented to the reader.

(2) The authors claim that a ∆kch mutant is more susceptible to blue light stress, as evidenced by PI staining. The premise that the cells are mounting a protective response to blue light via these channels rests on this claim. However, they do not perform the negative control experiment, conducting PI staining for WT the ∆kch mutant in the absence of blue light. In the absence of this control it is not possible to rule out effects of the ∆kch mutation on overall viability and/or PI uptake. The authors do include a growth curve for comparison, but planktonic growth is a very different context than surface-attached biofilm growth. Additionally, the ∆kch mutation may have impacts on PI permeability specifically that are not addressed by a growth curve. The negative control experiment is of key importance here.

Second, the ideas presented in this manuscript rely entirely on analysis of ThT fluorescence data, specifically a time course of cellular fluorescence following blue light treatment. However, alternate explanations for and potential confounders of the observed dynamics are not sufficiently addressed:

(1) Bacterial cells are autofluorescent, and this fluorescence can change significantly in response to stress (e.g. blue light exposure). To characterize and/or rule out autofluorescence contributions to the measurement, the authors should present time lapse fluorescence traces of unstained cells for comparison, acquired under the same imaging conditions in both wild type and ∆kch mutant cells. In their response to reviewers the authors suggested that they have conducted this experiment and found that the autofluorescence contribution is negligible, which is good, but these data should be included in the manuscript along with a description of how these controls were conducted.

(2) Similarly, in my initial review I raised a concern about the possible contributions of photobleaching to the observed fluorescence dynamics. This is particularly relevant for the interpretation of the experiment in which catalase appears to attenuate the decay of the ThT signal; this attenuation could alternatively be due to catalase decreasing ThT photobleaching. In their response, the authors indicated that photobleaching is negligible, which would be good, but they do not share any evidence to support this claim. Photobleaching can be assessed in this experiment by varying the light dosage (illumination power, frequency, and/or duration) and confirming that the observed fluorescence dynamics are unaffected.

Third, the paper claims in two instances that there are propagating waves of ThT fluorescence that move through biofilms, but I do not observe these waves in any case:

(1) The first wavefront claim relates to small cell clusters, in Fig. 2A and Video S2 and S3 (with Fig. 2A and Video S2 showing the same biofilm.) I simply do not see any evidence of propagation in either case- rather, all cells get brighter and dimmer in tandem. I downloaded and analyzed Video S3 in several ways (plotting intensity profiles for different regions at different distances from the cluster center, drawing a kymograph across the cluster, etc.) and in no case did I see any evidence of a propagating wavefront. (I attempted this same analysis on the biofilm shown in Fig. 2A and Video S2 with similar results, but the images shown in the figure panels and especially the video are still both so saturated that the quantification is difficult to interpret.) If there is evidence for wavefronts, it should be demonstrated explicitly by analysis of several clusters. For example, a figure of time-to-peak vs. position in the cluster demonstrating a propagating wave would satisfy this. Currently, I do not see any wavefronts in this data.

(2) The other wavefront claim relates to biofilms, and the relevant data is presented in Fig. S4 (and I believe also in what is now Video S8, but no supplemental video legends are provided, and this video is not cited in text.) As before, I cannot discern any wavefronts in the image and video provided; Reviewer 1 was also not able to detect wave propagation in this video by kymograph. Some mean squared displacements are shown in Fig. 7. As before, the methods for how these were obtained are not clearly documented either in this manuscript or in the BioRXiv preprint linked in the initial response to reviewers, and since wavefronts are not evident in the video it is hard to understand what is being measured here- radial distance from where? (The methods section mentions radial distance from the substrate, this should mean Z position above the imaging surface, and no wavefronts are evident in Z in the figure panels or movie.) Thus, clear demonstration of these wavefronts is still missing here as well.

Fourth, I have some specific questions about the study of blue light stress and the use of PI as a cell viability indicator:

(1) The logic of this paper includes the premise that blue light exposure is a stressor under the experimental conditions employed in the paper. Although it is of course generally true that blue light can be damaging to bacteria, this is dependent on light power and dosage. The control I recommended above, staining cells with PI in the presence and absence of blue light, will also allow the authors to confirm that this blue light treatment is indeed a stressor- the PI staining would be expected to increase in the presence of blue light if this is so.

(2) The presence of ThT may complicate the study of the blue light stress response, since ThT enhances the photodynamic effects of blue light in E. coli (Bondia et al. 2021 Chemical Communications). The authors could investigate ThT toxicity under these conditions by staining cells with PI after exposing them to blue light with or without ThT staining.

(3) In my initial review, I wrote the following: "In Figures 4D - E, the interpretation of this experiment can be confounded by the fact that PI uptake can sometimes be seen in bacterial cells with high membrane potential (Kirchhoff & Cypionka 2017 J Microbial Methods); the interpretation is that high membrane potential can lead to increased PI permeability. Because the membrane potential is largely higher throughout blue light treatment in the ∆kch mutant (Fig. 3[BC]), this complicates the interpretation of this experiment." In their response, the authors suggested that these results are not relevant in this case because "In our experiment methodology, cell death was not forced on the cells by introducing an extra burden or via anoxia." However, the logic of the paper is that the cells are in fact dying due to an imposed external stressor, which presumably also confers an increased burden as the cells try to deal with the stress. Instead, the authors should simply use a parallel method to confirm the results of PI staining. For example, the experiment could be repeated with other stains, or the viability of blue light-treated cells could be addressed more directly by outgrowth or colony-forming unit assays.

The CFU assay suggested above has the additional advantage that it can also be performed on planktonic cells in liquid culture that are exposed to blue light. If, as the paper suggests, a protective response to blue light is being coordinated at the biofilm level by these membrane potential fluctuations, the WT strain might be expected to lose its survival advantage vs. the ∆kch mutant in the absence of a biofilm.

Fifth, in several cases the data are presented in a way that are difficult to interpret, or the paper makes claims that are different to observe in the data:

(1) The authors suggest that the ThT and TMRM traces presented in Fig. S1D have similar shapes, but this is not obvious to me- the TMRM curve has very little decrease after the initial peak and only a modest, gradual rise thereafter. The authors suggest that this is due to increased TMRM photobleaching, but I would expect that photobleaching should exacerbate the signal decrease after the initial peak. Since this figure is used to support the use of ThT as a membrane potential indicator, and since this is the only alternative measurement of membrane potential presented in text, the authors should discuss this discrepancy in more detail.

(2) The comparison of single cells to microcolonies presented in figures 1B and D still needs revision:

First, both reviewer 1 and I commented in our initial reviews that the ThT traces, here and elsewhere, should not be normalized- this will help with the interpretation of some of the claims throughout the manuscript.

Second, the way these figures are shown with all traces overlaid at full opacity makes it very difficult to see what is being compared. Since the point of the comparison is the time to first peak (and the standard deviation thereof), histograms of the distributions of time to first peak in both cases should be plotted as a separate figure panel.<br /> Third, statistical significance tests ought to be used to evaluate the statistical strength of the comparisons between these curves. The authors compare both means and standard deviations of the time to first peak, and there are appropriate statistical tests for both types of comparisons.

(3) The authors claim that the curve shown in Fig. S4B is similar to the simulation result shown in Fig. 7B. I remain unconvinced that this is so, particularly with respect to the kinetics of the second peak- at least it seems to me that the differences should be acknowledged and discussed. In any case, the best thing to do would be to move Fig. S4B to the main text alongside Fig. 7B so that the readers can make the comparison more easily.

(4) As I wrote in my first review, in the discussion of voltage-gated calcium channels, the authors refer to "spiking events", but these are not obvious in Figure S3E. Although the fluorescence intensity changes over time, these fluctuations cannot be distinguished from measurement noise. A no-light control could help clarify this.

(5) In the lower irradiance conditions in Fig. 4A, the ThT dynamics are slower overall, and it looks like the ThT intensity is beginning to rise at the end of the measurement. The authors write that no second peak is observed below an irradiance threshold of 15.99 µW/mm2. However, could a more prominent second peak be observed in these cases if the measurement time was extended? Additionally, the end of these curves looks similar to the curve in Fig. S4B, in which the authors write that the slow rise is evidence of the presence of a second peak, in contrast to their interpretation here.

Additional considerations:

(1) The analysis and interpretation of the first peak, and particularly of the time-to-fire data is challenging throughout the manuscript the time resolution of the data set is quite limited. It seems that a large proportion of cells have already fired after a single acquisition frame. It would be ideal to increase the time resolution on this measurement to improve precision. This could be done by imaging more quickly, but that would perhaps necessitate more blue light exposure; an alternative is to do this experiment under lower blue light irradiance where the first spike time is increased (Figure 4A).

(2) The authors suggest in the manuscript that "E. coli biofilms use electrical signalling to coordinate long-range responses to light stress." In addition to the technical caveats discussed above, I am missing a discussion about what these responses might be. What constitutes a long-range response to light stress, and are there known examples of such responses in bacteria?

(3) The presence of long-range blue light responses can also be interrogated experimentally, for example, by repeating the Live/Dead experiment in planktonic culture or the single-cell condition. If the protection from blue light specifically emerges due to coordinated activity of the biofilm, the ∆kch mutant would not be expected to show a change in Live/Dead staining in non-biofilm conditions. The CFU experiment I mentioned above could also implicate coordinated long-range responses specifically, if biofilms and liquid culture experiments can be compared (although I know that recovering cells from biofilms is challenging.)

4. At the end of the results section, the authors suggest a critical biofilm size of only 4 μm for wavefront propagation (not much larger than a single cell!) The authors show responses for various biofilm sizes in Fig. 2C, but these are all substantially larger (and this figure also does not contain wavefront information.) Are there data for cell clusters above and below this size that could support this claim more directly?

(5) In Fig. 4C, the overall trajectories of extracellular potassium are indeed similar, but the kinetics of the second peak of potassium are different than those observed by ThT (it rises minutes earlier)- is this consistent with the idea that Kch is responsible for that peak? Additionally, the potassium dynamics also include the first ThT peak- is this surprising given that the Kch channel has no effect on this peak according to the model?

Detailed comments:

Why are Fig. 2A and Video S2 called a microcluster, whereas Video S3, which is smaller, is called a biofilm?

"We observed a spontaneous rapid rise in spikes within cells in the center of the biofilm" (Line 140): What does "spontaneous" mean here?

"This demonstrates that the ion-channel mediated membrane potential dynamics is a light stress relief process.", "E. coli cells employ ion-channel mediated dynamics to manage ROS-induced stress linked to light irradiation." (Line 268 and the second sentence of the Fig. 4F legend): This claim is not well-supported. There are several possible interpretations of the catalase experiment (which should be discussed); this experiment perhaps suggests that ROS impacts membrane potential but does not indicate that these membrane potential fluctuations help the cells respond to blue light stress. The loss of viability in the ∆kch mutant might indicate a link between these membrane potential experiments and viability, but it is hard to interpret without the no light controls I mention above.

"The model also predicts... the external light stress" (Lines 338-341): Please clarify this section. Where does this prediction arise from in the modeling work? Second, I am not sure what is meant by "modulates the light stress" or "keeps the cell dynamics robust to the intensity of external light stress" (especially since the dynamics clearly vary with irradiance, as seen in Figure 4A).

"We hypothesized that E. coli not only modulates the light-induced stress but also handles the increase of the ROS by adjusting the profile of the membrane potential dynamics" (Line 347): I am not sure what "handles the ROS by adjusting the profile of the membrane potential dynamics" means. What is meant by "handling" ROS? Is the hypothesis that membrane potential dynamics themselves are protective against ROS, or that they induce a ROS-protective response downstream, or something else? Later the authors write that changes in the response to ROS in the model agree with the hypothesis, but just showing that ROS impacts the membrane potential does not seem to demonstrate that this has a protective effect against ROS.

"Mechanosensitive ion channels (MS) are vital for the first hyperpolarization event in E. coli." (Line 391): This is misleading- mechanosensitive ion channels totally ablate membrane potential dynamics, they don't have a specific effect on the first hyperpolarization event. The claim that mechanonsensitive ion channels are specifically involved in the first event also appears in the abstract.

Also, the apparent membrane potential is much lower even at the start of the experiment in these mutants (Fig. 6C-D)- is this expected? This seems to imply that these ion channels also have a blue light-independent effect.

Throughout the paper, there are claims that the initial ThT spike is involved in "registering the presence of the light stress" and similar. What is the evidence for this claim?

"We have presented much better quantitative agreement of our model with the propagating wavefronts in E. coli biofilms..." (Line 619): It is not evident to me that the agreement between model and prediction is "much better" in this work than in the cited work (reference 57, Hennes et al. 2023). The model in Figure 4 of ref. 57 seems to capture the key features of their data.

In methods, "Only cells that are hyperpolarized were counted in the experiment as live" (Line 745): what percentage of cells did not hyperpolarize in these experiments?

Some indication of standard deviation (error bars or shading) should be added to all figures where mean traces are plotted.

Video S8 is very confusing- why does the video play first forwards and then backwards? It is easy to misinterpret this as a rise in the intensity at the end of the experiment.

Reviewer #1 (Public Review):

Summary:

In this study of metabolism using Xenopus, explanted porcine hearts and limbs, and human organs-on-chips, Sperry et al studied the ability of WB3 to slow metabolism and mobility. The group developed WB3, an analog of SNC80, void of SNC80's delta-opioid receptor binding capacity and studied its metabolic impact. The authors concluded that SNC80 and its analog WB3 can induce "biostasis" and produce a hypometabolic state which holds promise for prolonging organ viability in transplant surgery as well as other potential clinical benefits.

Strengths:

This study also opens new avenues for therapeutic possibilities in areas such as trauma, acute infection, and brain injuries. The overall methodology is acceptable, but certain concerns should be addressed.

Weaknesses:

Major comments:

(1) In cardiac and renal transplantation, cold preservation in ice remains a common practice for transporting explanted hearts to donors which remains a cheap and easily accessible way of preserving organs. While ex-vivo mechanical circulatory platforms have been developed and are increasingly being utilized to prolong organ viability, cold preservation remains widely used. The authors perfused explanted hearts with oxygenated perfusion preservation devices at subnormothermic temperatures (20-23C) which is even much lower than routinely used in clinical cardiopulmonary bypass scenarios (28-32C) (in the discussion, the authors allude to SNC80's possible "protective effect" in cardiac bypass). It is unclear how much of the hypometabolic state is related to WB3 administration versus hypothermia. The study will benefit from a comparison of WB3 administration and hypothermia in Xenopus, explanted porcine organs versus cold preservation alone to show distinction in biostasis parameters.

(2) The authors selected SNC80 based on a literature survey where it was identified based on its ability to induce hypothermia and protect against the effects of spinal cord ischemia in rodents. While this makes sense, were other drugs (eg. Puerarin) considered? The induction of hypothermia and spinal cord protective effect of SNC80 may be multifactorial and not necessarily related to its biostatic effects as the authors describe. Please provide some more context into the background of SNC80.

(3) In most of the models, the primary metric that the authors utilize to characterize metabolic activity is oxygen consumption, which is a somewhat limited indicator. For instance, this does not provide any information, however, on anaerobic metabolic activity. In addition, the ATP/ADP ratio was found to decrease in the organ chips where SNC80 was utilized, but similar findings were not presented for the other models.

(4) The authors should provide a more detailed explanation of SNC80's mechanisms of interaction with proteins related to transmembrane transport, mitochondrial activity, and metabolic processes. What is the impact of SNC80 on mitochondrial function, particularly ATP production and mitochondrial respiration? Are there changes in mitochondrial membrane potential, electron transport chain activity, or oxidative phosphorylation? In this context, authors discuss the potential role of NCX1 as a binding target for SNC80 and its various mechanisms in slowing metabolism. However, no experiments have been done to confirm this binding in the present study. Co-immunoprecipitation studies using appropriate antibodies against SNC80 and NCX1 should be considered to demonstrate their direct binding. Additionally, surface plasmon resonance (SPR) or isothermal titration calorimetry (ITC) experiments could be employed to quantify the binding affinity between SNC80 and NCX1, providing further evidence of their interaction. These experiments would elucidate the binding mechanism between SNC80 and NCX1 and reveal more information on the mechanism of action for SNC80.

(5) The manuscript notes that histological analysis was conducted, but it seems that only example images are provided, such as Fig 4f. Quantified histological data would provide a more thorough understanding of tissue integrity.

(6) Some of the points mentioned in the discussion and conclusion are rather strong and based on possible associations such as SNC80's potential vasodilatory capacity conferring a cardioprotective effect, ability to reversibly suppress metabolism across different temperatures and species. Please tone this down and stay limited to the organs studied. Further, the reversibility of the findings may be more objectively assessed by biomarkers with decreased immunofluorescence in response to ischemia such as troponin I for heart and albumin for liver. Additionally, an investigation of proteins involved in inflammation, hypoxia, and key cell death pathways using immunohistochemistry analysis can better describe the impact of treatment on apoptosis/necroptosis.

(7) What could be the underlying cause of the observed increase in intercellular spacing after SNC80 administration in porcine limbs which also seems to be evident in the heart histology samples? This seems to be more prominent in the SNC80 compared to the vehicle group.

(8) In the Discussion section, it would be valuable to provide a concise interpretation of the lipidomic data, particularly explaining how changes in acylcarnitine and cholesterol ester levels may relate to tadpole metabolism, hibernation, or other biological processes.

(9) What are the limitations or disadvantages of the study? Does SNC80 possess any immunomodulatory properties that might affect the outcomes of organ transplantation? Are there specific organs for which SNC80 may not be a suitable preservation agent, and if so, what are the reasons behind this?

Comments on revised version:

The authors have satisfactorily addressed our comments in the rebuttal letter. The limitations described by the authors in point #9, however, need to be incorporated in the revised manuscript in detail as they are important in guiding interpretation of the present data. Congratulations again on the important study.

Reviewer #2 (Public Review):

Summary:

This manuscript titled "Identification of pharmacological inducers of a reversible hypometabolic state for whole organ preservation" reports the effects of delta opioid receptor activator SNC80 and its modified analog WB3 with ~1,000 times less delta opioid receptor binding activity on metabolic state.

Strengths:

This is an interesting study with potentially broad implications for organ preservation.

Weaknesses:

However, there are several limitations which raise concerns.

(1) The authors developed an analog of a known delta opioid receptor activator SNC80 with three orders of magnitude lesser binding with the delta opioid receptor WB3. This will likely reduce the undesirable effects of SNC80 while preserving metabolic slowing needed for organ preservation. Yet, most experiments were done with SNC80, not the superior modification, WB3, shown in only a limited set of experiments, Figure 3.

(2) The heart is one of the most challenging organs to preserve, and some experiments are done to establish the metabolic effects of SNC80. However, the biodistribution study, shown in Figure 2, conspicuously omitted the heart.

(3) I do not understand the design of the electrophysiology and contractility experiments with the porcine hearts. How did you defibrillate the hearts after removal and establishing perfusion? Lines 173-175 on Page 7 state: "After defibrillation with epinephrine, the P and QRS waveforms were visible in ECGs from 3 of 4 SNC80-treated hearts (Table S1), suggesting that those hearts regain atrial and ventricular polarization." Please clarify. Defibrillation is done with an electric shock. Also, please show the ECG recordings to support your conclusions about "polarization." What did you mean by "polarization"? Depolarization? Repolarization? Or resting potential. To establish a normal physiological state, please show ECG waveforms and present data on basic ECG characteristics: heart rate, PQ and QT intervals, and P and QRS durations. I recommend perfusion of the porcine heart with WB3, not only SNC80.

(4) Pathology data also raises concerns. The histology images shown in Figure 4f are not quantified, and they show apparently higher levels of tissue disruption in SNC80-treated tissue vs vehicle-treated. The test (lines 169-171) confirms this concern: "In some hearts treated with SNC80, greater waviness of muscle fibers was observed, possibly indicating a state of muscle contraction." It will be helpful to measure markers of apoptosis and necrosis and to apply TTC viability staining.

(5) The apparent state of contracture suggests a higher degree of myocardial damage and a high intracellular calcium level in SNC80-treated hearts. The authors suggested that the sodium-calcium exchanger NCX is a possible target of SNC80 and could be responsible for the "hypometabolic state." However, NCX1 is critically important in the extrusion of cytosolic Ca2+ during the diastolic phase. Failure to remove excessive calcium and restore ionic homeostasis would lead to calcium overload and heart failure.

(6) I am surprised the authors did not consider using the gold standard assay for measuring mitochondrial function in cells by the Seahorse Cell Mito Stress Test.

Comments on revised version:

I am satisfied with the revisions. The authors addressed major concerns with new data and/or provided satisfactory rebuttal.

Reviewer #3 (Public Review):

Summary:

Plasmacytoid dendritic cells (pDCs) represent a specialized subset of dendritic cells (DCs) known for their role in producing type I interferons (IFN-I) in response to viral infections. It was believed that pDCs originated from common DC progenitors (CDP). However, recent studies by Rodrigues et al. (Nature Immunology, 2018) and Dress et al. (Nature Immunology, 2019) have challenged this perspective, proposing that pDCs predominantly develop from lymphoid progenitors expressing IL-7R and Ly6D. A minor subset of pDCs arising from CDP has also been identified as functionally distinct, exhibiting reduced IFN-I production but a strong capability to activate T cell responses. On the other hand, clonal lineage tracing experiments, as recently reported by Feng et al. (Immunity, 2022), have demonstrated a shared origin between pDCs and conventional DCs (cDCs), suggesting a contribution of common DC precursors to the pDC lineage.

In this context, Araujo et al. investigated the heterogeneity of pDCs in terms of both development and function. Their findings revealed that approximately 20% of pDCs originate from lymphoid progenitors common to B cells. Using Mb1-Cre x Bcl11a floxed mice, the authors demonstrated that the development of this subset of pDCs, referred to as "B-pDCs," relied on the transcription factor BCL11a. Functionally, B-pDCs exhibited a diminished capacity to produce IFN-I in response to TLR9 agonists but secreted more IL-12 compared to conventional pDCs. Moreover, B-pDCs, either spontaneously or upon activation, exhibited increased expression of activation markers (CD80/CD86/MHC-II) and a heightened ability to activate T cell responses in vitro compared to conventional pDCs. Finally, Araujo et al. characterized these B-pDCs at the transcriptomic level using bulk and single-cell RNA sequencing, revealing them as a unique subset of pDCs expressing certain B cell markers such as Mb1, as well as specific markers (Axl) associated with cells recently described as transitional DCs.<br /> Thus, in contrast to previous findings, this study posits that a small proportion of pDCs derive from B cell-committed lymphoid progenitors, and this subset of B-pDCs exhibits distinct functional characteristics, being less specialized in IFN-I production but rather in T cell activation.

Strengths:

Previously, the same research group delineated the significance of BCL11a as a critical transcription factor in pDC development (Ippolito et al., PNAS, 2014). This study elucidates the precise stage during hematopoiesis at which BCL11a expression becomes essential for the emergence of a distinct subset of pDCs, substantiated by robust genetic evidence in vivo. Furthermore, it underscores the shared developmental origin between pDCs and B cells, reinforcing prior research in the field that suggests a lymphoid origin of pDCs. Finally, this works attributes specific functional properties to pDCs originating from these lymphoid progenitors shared with B cells, emphasizing the early imprinting of functional heterogeneity during their development.

Weaknesses:

Using their Mb1-reporter mice, the authors demonstrate that YFP pDCs originating from lymphoid progenitors are functionally distinct from conventional pDCs, mostly in vitro, but their in vivo relevance remains unknown. As underlined by both reviewers I believe that it is crucial to investigate how Bcl11a conditional deficiency in Mb1 expressing cells affects the anti-viral immune response, for example, using the M-CoV infection model as described by Sulczewski et al. in Nature Immunology, 2023. The current in vivo data using TLR9 agonist and in vitro data using B-pDCs co-cultures with T cells insufficiently address what B-pDCs might be doing in infectious contexts.

Revisions:

I thank the authors for their responses to my questions and for addressing most of my comments clearly and thoroughly. However, one major question remains unanswered: What is the functional relevance of the subset of B-pDCs that they have characterized? This key question, also highlighted by the other reviewer, requires further investigation. The current in vivo data using TLR9 agonist and in vitro data using B-pDCs co-cultures with T cells insufficiently address what B-pDCs might be doing in infectious contexts.

Reviewer #1 (Public Review):

Summary:<br /> In this study the authors advance their previous findings on the role of the SLAM-SAP signaling pathway in the development and function of multiple innate-like gamma-delta T cell subsets. Using high throughput single cell proteogenomics approach, the authors uncover SAP-dependent developmental checkpoints, and the role of SAP signaling in regulating the diversion of γδ T cells into the αβ T cell developmental pathway. Finally, the authors define TRGV4/TRAV13-4(DV7)-expressing T cells as a novel, SAP-dependent Vγ4 γδT1 subset.

Strengths:<br /> This study furthers our understanding of the importance and complexity of the SLAM-SAP signaling pathway not only in the development of innate-like γδ T cells but also the how it potentially balances the γδ/αβ T cell lineage commitment. Additionally, this study reveals the role of SAP-dependent events in generation of γδ TCR repertoire.

Comments on revised version:

The conclusions of the study are supported by well thought-out experiments and compelling data.

Weaknesses:<br /> There are no major weakness in the study.

A few minor points:<br /> (1) In the subsets of the γδ T cells that exhibit reduced BLK expression in B6. SAP KO mice, have the authors examined the expression of Lck and/or Fyn?<br /> (2) Does BLK directly associate with SLAM F1 and or SLAM F6 receptors?<br /> (3) Given the emerging role of γδ T cells in host immunity, it will be useful if the authors add a discussion of how their findings are relevant in disease conditions such as in cancer.

The author has adequately addressed all the reviewers' comments.

Reviewer #2 (Public Review):

Summary:<br /> Mistri et al explore the role of SLAM-SAP signaling in the developmental programming of innate-like gd T cell subsets. Using proteo-genomics, they determined that abrogation of SLAM-SAP signaling altered that programming, reducing some IL-17 producing subsets, including a novel Vγ4 γδT1 subset, and diverting gdTCR-expressing precursors to the ab fate. Altogether, this is a very thorough, thoughtfully interpreted study that adds significantly to our understanding of the contribution of the SLAM-SAP pathway to lineage specification. A particularly interesting element is the role of SLAM-SAP in preventing gd17 progenitors from switching fates and adopting the ab fate.

Comments on revised version:

The authors have addressed the minor issues raised in the original submission.

Reviewer #1 (Public Review):

Summary:

The manuscript by van Heerden et al. reports growth rate variations in the cell cycle of E. coli and links this variation to uneven ribosome concentrations in the cell at birth that arise from an uneven division of cell volumes between the daughter cells. The authors propose a model to explain the experimental data, whose main premises are the exclusion of ribosomes from the nucleoid volume and a linear dependence of the growth rate on ribosome concentration in the cell.

Strengths:

(1) The manuscript highlights an interesting aspect of growth rate variability in bacteria and proposes a mechanism for how this variation is homeostatically corrected.

(2) A sophisticated modeling to explain the experimental data.

Weaknesses:

(1) The experiments lack controls. A partially functional label (L9-mCherry) can make ribosomes much more limiting for growth than are not labeled ribosomes.

(2) The large variation of interdivision times 72-89 min in repeat experiments in Glc is problematic. Some parameters in the measurements related to cell growth appear not properly controlled. It is problematic for a work that aims to establish a new universal behavior related to cell growth.

(3) The authors have not provided convincing evidence that cells in their experiment grow in a steady state.

4) The findings are over-generalized. The existing data show the effects only at some growth rates, but the findings are presented as a new universal principle.

5) The model relies on many assumptions that are not clearly brought out and the choice of model parameters is questionable (in some cases, the parameters seem to contradict well-established experimental data, including the one from the experiments from the very same work). Small changes in parameters and various approximations can have large effects on the model's outcomes; without understanding these responses, the model has a rather limited value.

6) There appears to be a qualitative discrepancy between the model and the experimental data in Glc (the main condition studied). The model predicts that the cells born large have a specific elongation rate that is smaller than the average growth rate of cells, but it grows in time at the beginning of the cell cycle, while the experiments show a decreasing growth rate (Figure 1C, SI Figure S2).

Reviewer #2 (Public Review):

Summary:

This work demonstrates that when E. coli cells divide, and division is not quite symmetric, the smaller cell has a higher growth rate than the larger cell at the beginning, but not the end, of the cell cycle. The authors then demonstrate that smaller cells have a higher ribosome concentration than larger cells, which is consistent with the idea that the two cells receive roughly equal numbers of ribosomes at division because, as they also observe, ribosomes are excluded by the nucleoid from the middle of the mother cell. The experimental observations are reproduced by a mathematical model that assumes growth is driven by ribosome concentration, with contributions from metabolism and active feedback.

Strengths:

The work provides strong evidence in support of the growing consensus that cells correct size fluctuations by modulating growth rate, within a cell cycle and on a single-cell basis. It also offers a plausible explanation for the correction mechanism by showing that ribosomes are excluded from the middle of a mother cell and have a higher concentration in the smaller daughter cell. The work is clearly written and benefits from a strong coupling between the experimental and modeling results. It provides a solid contribution to the field of single-cell bacterial growth control.

Weaknesses:

Although the results strongly suggest it, the work does not explicitly demonstrate (e.g. by direct perturbation) that higher ribosome concentration is the cause of the higher growth rate. Also, it is unclear why an active compensation mechanism is needed in the model, i.e., why size-dependent growth (via ribosome concentration) does not correct growth rate perturbations within a cell cycle automatically.

Reviewer #1 (Public Review):

This article by Navratna et al. reports the first structure of human HGSNAT in an acetyl-CoA-bound state. Through careful structural analysis, the authors propose potential reasons why certain human mutations lead to lysosomal storage disorders and outline a catalytic mechanism. The structural data are of good quality, and the manuscript is clearly written. This study represents an important step toward understanding the mechanism of HGSNAT and is valuable to the field. I have the following suggestions:

(1) The authors should characterize whether the purified protein is active. Otherwise, how does one know if the detergent used maintains the protein in a biologically relevant state? The authors should at least attempt to do so. If these prove to be challenging, at the very least, the authors should try a cell-based assay to demonstrate that the GFP tag does not interfere with the function.

(2) In Figure 5, the authors present a detailed schematic of the catalytic cycle, which I find to be too speculative. There is no evidence to suggest that this enzyme undergoes isomerization, similar to a transporter, between open-to-lumen and open-to-cytosol states. Could it not simply involve some movements of side chains to complete the acetyl transfer?

Reviewer #2 (Public Review):

Summary:

This work describes the structure of Heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT), a lysosomal membrane protein that catalyzes the acetylation reaction of the terminal alpha-D-glucosamine group required for degradation of heparan sulfate (HS). HS degradation takes place during the degradation of the extracellular matrix, a process required for restructuring tissue architecture, regulation of cellular function and differentiation. During this process, HS is degraded into monosaccharides and free sulfate in lysosomes.

HGSNAT catalyzes the transfer of the acetyl group from acetyl-CoA to the terminal non-reducing amino group of alpha-D-glucosamine. The molecular mechanism by which this process occur has not been described so far. One of the main reasons to study the mechanism of HGSNAT is that multiple mutations spanning the entire sequence of the protein, such as, nonsense mutations, splice-site variants, and missense mutations lead to dysfunction that causes abnormal accumulation of HS within the lysosomes. This accumulation is a cause of mucopolysaccharidosis IIIC (MPS IIIC), an autosomal recessive neurodegenerative lysosomal storage disorder, for which there are no approved drugs or treatment strategies.<br /> This paper provides a 3.26A structure of HGSNAT, determined by single-particle cryo-EM. The structure reveals that HGSNAT is a dimer in detergent micelles, and a density assigned to acetyl-CoA. The authors speculate about the molecular mechanism of the acetylation reaction, map the mutations known to cause MPS IIIC on the structure and speculate about the nature of the HGSNAT disfunction caused by such mutations.

Strengths:

The paper describes a structure of HGSNAT a member of the transmembrane acyl transferase (TmAT) superfamily. The high-resolution of a HGSNAT bound to acetyl-CoA is important for our understanding of HGSNAT mechanism. The density map is of high-quality, except for the luminal domain. The location of the acetyl-CoA allows speculation about the mechanistic role of multiple residues surrounding this molecule. The authors thoroughly describe the architecture of HGSNAT and map the mutations leading to MPS IIIC.

Reviewer #3 (Public Review):

Summary:

Navratna et al. have solved the first structure of a transmembrane N-acetyltransferase (TNAT), resolving the architecture of human heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT) in the acetyl-CoA bound state using single particle cryo-electron microscopy (cryoEM). They show that the protein is a dimer, and define the architecture of the alpha- and beta-GSNAT fragments, as well as convincingly characterizing the binding site of acetyl-CoA.

Strengths:

This is the first structure of any member of the transmembrane acyl transferase superfamily, and as such it provides important insights into the architecture and acetyl-CoA binding site of this class of enzymes.

The structural data is of a high quality, with an isotropic cryoEM density map at 3.3Å facilitating building of a high-confidence atomic model. Importantly, the density for the acetyl-CoA ligand is particularly well-defined, as are the contacting residues within the transmembrane domain.

The structure of HSGNAT presented here will undoubtedly lay the groundwork for future structural and functional characterization of the reaction cycle of this class of enzymes.

Weaknesses:

While the structural data for the state presented in this work is very convincing, and clearly defines the binding site of acetyl-CoA, to get a complete picture of the enzymatic mechanism of this family, additional structures of other states will be required.

A weakness of the study is the lack of functional validation. The enzymatic activity of the enzyme characterized was not measured, and the enzyme lacks native proteolytic processing, so it is a little unclear whether the structure represents an active enzyme.

Reviewer #2 (Public Review):

Summary:

This paper utilizes a neural network model to investigate how the brain employs an adaptive chunking strategy to effectively enhance working memory capacity, which is a classical and significant question in cognitive neuroscience. By integrating perspectives from both the 'slot model' and 'limited resource models,' the authors adopted a neural network model encompassing the prefrontal cortex and basal ganglia, introduced an adaptive chunking strategy, and proposed a novel hybrid model. The study demonstrates that the brain can adaptively bind various visual stimuli into a single chunk based on the similarity of color features (a continuous variable) among items in visual working memory, thereby improving working memory efficiency. Additionally, it suggests that the limited capacity of working memory arises from the computational characteristics of the neural system, rather than anatomical constraints.

Strengths:

The neural network model utilized in this paper effectively integrates perspectives from both slot models and resource models (i.e., resource-like constraints within a slot-like system). This methodological innovation provides a better explanation for the limited capacity of working memory. By simulating the neural networks of the prefrontal cortex and basal ganglia, the model demonstrates how to optimize working memory storage and retrieval strategies through reinforcement learning (i.e., the efficient management of access to and from working memory). This biologically plausible simulation offers a novel perspective on human working memory and potentially provides a novel explanation for the working memory difficulties observed in patients with Parkinson's disease and other disorders. Furthermore, the effectiveness of the model is validated through computational simulation experiments, yielding reliable and robust predictions.

Weaknesses:

The model employs a spiking neural network, which is relatively complex. Additionally, while this paper validates the effectiveness of chunking strategies used by the brain to enhance working memory efficiency through computational simulations, further comparison with related phenomena observed in cognitive neuroscience experiments on limited working memory capacity, such as the recency effect, is necessary to verify its generalizability.

Reviewer #1 (Public Review):

Summary:

In this research, Soni and Frank investigate the network mechanisms underlying capacity limitations in working memory from a new perspective, with a focus on visual working memory (VWM). The authors have advanced beyond the classical neural network model, which incorporates the prefrontal cortex and basal ganglia (PBWM), by introducing an adaptive chunking variant. This model is trained using a biologically plausible, dopaminergic reinforcement learning framework. The adaptive chunking mechanism is particularly well-suited to the VWM tasks involving continuous stimuli and elegantly integrates the 'slot' and 'resource' theories of working memory constraints. The chunk-augmented PBWM operates as a slot-like system with resource-like limitations.

Through numerical simulations under various conditions, Soni and Frank demonstrate the performance of the chunk-augmented PBWM model surpasses the no-chunk control model. The improvements are evident in enhanced effective capacity, optimized resource management, and reduced error rates. The retention of these benefits, even with increased capacity allocation, suggests that working memory limitations are due to a combination of factors, including the efficient credit assignments that are learned flexibly through reinforcement learning. In essence, this work addresses fundamental questions related to a computational working memory limitation using a biologically-inspired neural network, and thus has implications for clinical conditions in which working memory is affected, such as Parkinson's disease, ADHD, and schizophrenia.

Strengths:

The integration of mechanistic flexibility, reconciling two theories for WM capacity into a single unified model, results in a neural network that is both more adaptive and human-like. Building on the PBWM framework ensures the robustness of the findings. The addition of the chunking mechanism tailors the original model for continuous visual stimuli. Chunk-stripe mechanisms contribute to the 'resource' aspect, while input-stripes contribute to the 'slot' aspect. This combined network architecture enables flexible and diverse computational functions, enhancing performance beyond that of the classical model.

Moreover, unlike previous studies that design networks for specific task demands, the proposed network model can dynamically adapt to varying task demands by optimizing the chunking gating policy through RL.

The implementation of a dopaminergic reinforcement learning protocol, as opposed to a hard-wired design, leads to the emergence of strategic gating mechanisms that enhance the network's computational flexibility and adaptability. These gating strategies are vital for VWM tasks and are developed in a manner consistent with ecological and evolutionary learning held by humans. Further examination of how reward prediction error signals, both positive and negative, collaborate to refine gating strategies reveals the crucial role of reward feedback in fine-tuning the working memory computations and the model's behavior, aligning with the current neuroscientific understanding that reward matters.

Furthermore, assessing the impact of a healthy balance of dopaminergic reward prediction error signals on information manipulation holds implications for patients with altered striatal dopaminergic signaling.

Weaknesses:

While I appreciate the novelty of the idea presented in this paper, which aligns with common interests in cognitive neuroscience, I believe there are several areas that require further clarification.

First, the method section appears somewhat challenging to follow. To enhance clarity, it might be beneficial to include a figure illustrating the overall model architecture. This visual aid could provide readers with a clearer understanding of the overall network model.

Additionally, the structure depicted in Figure 2 could be potentially confusing. Notably, the absence of an arrow pointing from the thalamus to the PFC and the apparent presence of two separate pathways, one from sensory input to the PFC and another from sensory input to the BG and then to the thalamus, may lead to confusion. While I recognize that Figure 2 aims to explain network gating, there is room for improvement in presenting the content accurately.

Still, for the method part, it would enhance clarity to explicitly differentiate between predesigned (fixed) components and trainable components. Specifically, does the supplementary material state that synaptic connection weights in striatal units (Go&NoGo) are trained using XCAL, while other components, such as those in the PFC and lateral inhibition, are not trained (I found some sentences in 'Limitations and Future Directions')?

I'm not sure about the training process shown in Figure 8. It appears that the training may not have been completed, given that the blue line representing the chunk stripe is still ascending at the endpoint. The weights depicted in panel d) seem to correspond with those shown in panels b) and c), no? Then, how is the optimization process determined to be finished? Alternatively, could it be stated that these weight differences approach a certain value asymptotically? It would be better to clarify the convergence criteria of the optimization process.

Reviewer #1 (Public Review):

Summary:

This manuscript reports the effects of a heterozygous mutation in the KCNT1 potassium channels on the properties of ion currents and firing behavior of excitatory and inhibitory neurons in the cortex of mice expressing KCNT1-Y777H. In humans, this mutation as well as multiple other heterozygotic mutations produce very severe early-onset seizures and produce a major disruption of all intellectual function. In contrast, in mice, this heterozygous mutation appears to have no behavioral phenotype or any increased propensity to seizures. A relevant phenotype is, however, evident in mice with the homozygous mutation, and the authors have previously published the results of similar experiments with the homozygotes. As perhaps expected, the neuronal effects of the heterozygous mutation presented in this manuscript are generally similar but markedly smaller than the previously published findings on homozygotes. There are, however, some interesting differences, particularly on PV+ interneurons, which appear to be more excitable than wild type in the heterozygotes but more excitable in the heterozygotes. This raises the interesting question, which has been explicitly discussed by the authors in the revised manuscript, as to whether the reported changes represent homeostatic events that suppress the seizure phenotype in the mouse heterozygotes or simply changes in excitability that do not reach the threshold for behavioral outcomes.

Strengths and Weaknesses:

(1) The authors find that the heterozygous mutation in PV+ interneurons increases their excitability, a result that is opposite from their previous observation in neurons with the corresponding homozygous mutation. They propose that this results from the selective upregulation of a persistent sodium current INaP in the PV+ interneurons. These observations are very interesting ones, and they raised some issues in the original submission:

A) The protocol for measuring the INaP current could potentially lead to results that could be (mis)interpreted in different ways in different cells. First, neither K currents nor Ca currents are blocked in these experiments. Instead, TTX is applied to the cells relatively rapidly (within 1 second) and the ramp protocol is applied immediately thereafter. It is stated that, at this time, Na currents and INaP are fully blocked but that any effects on Na-activated K currents are minimal. In theory this would allow the pre- to post- difference current to represent a relatively uncontaminated INaP. This would, however, only work if activation of KNa currents following Na entry is very slow, taking many seconds. A good deal of literature has suggested that the kinetics of activation of KNa currents by Na influx vary substantially between cell types, such that single action potentials and single excitatory synaptic events rapidly evoke KNa currents in some cell types. This is, of course, much faster than the time of TTX application. Most importantly, the kinetics of KNa activation may be different in different neuronal types, which would lead to errors that could produce different estimates of INaP in PV+ interneurons vs other cell types.

In their revised manuscript, the authors have provided good data demonstrating that, at least for the PV and SST neurons, loss of KNa currents after TTX application is slow relative to the time course of loss of INaP, justifying the use of this protocol for these neuronal types.

B) As the authors recognize, INaP current provides a major source of cytoplasmic sodium ions for the activation. An expected outcome of increased INaP is, therefore, further activation of KNa currents, rather than a compensatory increase in an inward current that counteracts the increase in KNa currents, as is suggested in the discussion.

The authors comment in the rebuttal that, despite the fact that sodium entry through INaP is known to activate KNa channels, an increase in INaP does not necessarily imply increased KNa current. This issue should be addressed directly somewhere in the text, perhaps most appropriately in the discussion.

C) The numerical simulations, in general, provide a very useful way to evaluate the significance of experimental findings. Nevertheless, while the in-silico modeling suggests that increases in INaP can increase firing rate in models of PV+ neurons, there is as yet insufficient information on the relative locations of the INaP channels and the kinetics of sodium transfer to KNa channels to evaluate the validity of this specific model.

The authors have now put in all of the appropriate caveats on this very nicely in the revised manuscript.

(2) The effects of the KCNT1 channel blocker VU170 on potassium currents are somewhat larger and different from those of TTX, suggesting that additional sources of sodium may contribute to activating KCNT1, as suggested by the authors. Because VU170 is, however, a novel pharmacological agent, it may be appropriate to make more careful statements on this. While the original published description of this compound reported no effect on a variety of other channels, there are many that were not tested, including Na and cation channels that are known to activate KCNT1, raising the possibility of off-target effects.

In the revised version, the authors have added more to the manuscript on this issue and have added a very clear discussion of this to the text (in the discussion section).

This is a very clear and thorough piece of work, and the authors are to be congratulated on this. My one remaining suggestion would be to make an explicit statement about whether increased sodium influx through INaP channels, which is thought to activate KNa channels, would be likely to increase KNa current in these neurons (see comment 1B).

Reviewer #2 (Public Review):

Summary:

In this manuscript, Shore et al. investigate the consequent changes in excitability and synaptic efficacy of diverse neuronal populations in an animal model of juvenile epilepsy. Using electrophysiological patch-clamp recordings from dissociated neuronal cultures, the authors find diverging changes in two major populations of inhibitory cell types, namely somatostatin (SST)- and parvalbumin (PV)-positive interneurons, in mice expressing a variant of the KCNT1 potassium channel. They further suggest that the differential effects are due to a compensatory increase in the persistent sodium current in PV interneurons in pharmacological and in silico experiments. It remains unclear why this current is selectively enhanced in PV-interneurons.

Strengths:

(1) Heterozygous KCNT1 gain of function variant was used which more accurately models the human disorder.

(2) The manuscript is clearly written, and the flow is easy to follow. The authors explicitly state the similarities and differences between the current findings and the previously published results in the homozygous KCNT1 gain of function variant.

(3) This study uses a variety of approaches including patch clamp recording, in silico modeling and pharmacology that together make the claims stronger.

(4) Pharmacological experiments are fraught with off-target effects and thus it bolsters the authors' claims when multiple channel blockers (TTX and VU170) are used to reconstruct the sodium-activated potassium current.

Weaknesses:

(1) This study mostly relies on recordings in dissociated cortical neurons. Although specific WT interneurons showed intrinsic membrane properties like those reported for acute brain slices, it is unclear whether the same will be true for those cells expressing KCNT1 variants, especially when the excitability changes are thought to arise from homeostatic compensatory mechanisms. The authors do confirm that mutant SST-interneurons are hypoexcitable using an ex vivo slice preparation which is consistent with work for other KCTN1 gain of function variants (e.g. Gertler et al., 2022). However, the key missing evidence is the excitability state of mutant PV-interneurons, given the discrepant result of reduced excitability of PV cells reported by Gertler et al in acute hippocampal slices.

Reviewer #3 (Public Review):

Summary:

The present manuscript by Shore et al. entitled Reduced GABAergic Neuron Excitability, Altered Synaptic Connectivity, and Seizures in a KCNT1 Gain-of-Function Mouse Model of Childhood Epilepsy" describes in vitro and in silico results obtained in cortical neurons from mice carrying the KCNT1-Y777H gain-of-function (GOF) variant in the KCNT1 gene encoding for a subunit of the Na+-activated K+ (KNa) channel. This variant corresponds to the human Y796H variant found in a family with Autosomal Dominant Nocturnal Frontal lobe epilepsy. The occurrence of GOF variants in potassium channel encoding genes is well known, and among potential pathophysiological mechanisms, impaired inhibition has been documented as responsible for KCNT1-related DEEs. Therefore, building on a previous study by the same group performed in homozygous KI animals, and considering that the largest majority of pathogenic KCNT1 variants in humans occur in heterozygosis, the Authors have investigated the effects of heterozygous Kcnt1-Y777H expression on KNa currents and neuronal physiology among cortical glutamatergic and the 3 main classes of GABAergic neurons, namely those expressing vasoactive intestinal polypeptide (VIP), somatostatin (SST), and parvalbumin (PV), crossing KCNT1-Y777H mice with PV-, SST- and PV-cre mouse lines, and recording from GABAergic neurons identified by their expression of mCherry (but negative for GFP used to mark excitatory neurons).

The results obtained revealed heterogeneous effects of the variant on KNa and action potential firing rates in distinct neuronal subpopulations, ranging from no change (glutamatergic and VIP GABAergic) to decreased excitability (SST GABAergic) to increased excitability (PV GABAergic). In particular, modelling and in vitro data revealed that an increase in persistent Na current occurring in PV neurons was sufficient to overcome the effects of KCNT1 GOF and cause an overall increase in AP generation.

Strengths:

The paper is very well written, the results clearly presented and interpreted, and the discussion focuses on the most relevant points.<br /> The recordings performed in distinct neuronal subpopulations (both in primary neuronal cultures and, for some subpopulations, in cortical slices, are a clear strength of the paper. The finding that the same variant can cause opposite effects and trigger specific homeostatic mechanisms in distinct neuronal populations is very relevant for the field, as it narrows the existing gap between experimental models and clinical evidence.

Weaknesses:

My main concern regarding the epileptic phenotype of the heterozygous mice investigated has been clarified in the revision, where the infrequent occurrence of seizures is more clearly stated. Also, a more detailed statistical analysis of the modeled neurons has been added in the revision.

Reviewer #1 (Public Review):

Summary:

Using chromaffin cells as a powerful model system for studying secretion, the authors study the regulatory role of complexin in secretion. Complexin is still enigmatic in its regulatory role, as it both provides inhibitory and facilitatory functions in release. The authors perform an extensive structure-function analysis of both the C- and N-terminal regions of complexin. There are several interesting findings that significantly advances our understanding of cpx/SNARe interactions in regulating release. C-terminal amphipathic helix interferes with SNARE complex assembly and thus clamps fusion. There are acidic residues in the C-term that may be seen as putative interaction partners for Synaptotagmin. The N-terminus of Complexin promoting role may be associated with an interaction with Syt1. In particular the putative interaction with Syt1 is of high interest and supported by quite strong functional and biochemical evidence. The experimental approaches are state of the art, and the results are of the highest quality and convincing throughout. They are adequate and intelligently discussed in the rich context of the standing literature. Whilst there are some concerns about whether the facilitatory actions of complexion have to be tightly linked to Syt1 interactions, the proposed model will significantly advance the field by providing new directions in future research.

Reviewer #2 (Public Review):

Summary:

Complexin (Cplx) is expressed at nearly all chemical synapses. Mammalian Cplx comes in four different paralogs which are differentially expressed in different neurons or secretory cell types, either selectively or in combination with one or two other Cplx isoforms. Cplx binds with high affinity to assembled SNARE complexes and promotes evoked synchronous release. Cplx is assumed to preclude premature SV fusion by preventing full SNARE assembly, thereby arresting subsequent SNARE-driven fusion ("fusion-clamp" theory). The protein has multiple domains, the functions of which are controversially discussed. Cplx's function has been studied in a variety of model organisms including mouse, fly, worm, and fish with seemingly conflicting results which led to partly contradicting conclusions.<br /> Makee et al. study the function of mammalian Cplx2 in chromaffin cells by making use of Cplx2 ko mice to overexpress and functionally characterize mutant Cplx2 forms in cultured chromaffin cells. The main conclusion of the present study are:

The hydrophobic character of the amphipathic helix in Cplx's C-terminal domain is essential for inhibiting premature vesicle fusion at a [Ca2+]i of several hundreds of nM (pre-flash [Ca2+]i). The Cplx-mediated inhibition of fusion under these conditions does not rely on expression of either Syt1 or Syt7.

Slow-down of exocytosis by N-terminally truncated Cplx mutants in response to a [Ca2+]i of several µM (peak flash [Ca2+]i) occurs regardless of the presence or absence of Syt7 demonstrating that Cplx2 does not act as a switch favoring preferential assembly of the release machinery with Syt1,2 rather than the "slow" sensor Syt7.

Cplx's N-terminal domain is required for the Cplx2-mediated increase in the speed of exocytosis and faster onset of exocytosis which likely reflect an increased apparent Ca2+ sensitivity and faster Ca2+ binding of the release machinery.

Strengths:

The authors perform systematic truncation/mutational analyses of Cplx2. They analyze the impact of single and combined deficiencies for Cplx2 and Syt1 to establish interactions of both proteins.<br /> State-of-the-art methods are employed: Vesicle exocytosis is assayed directly and with high resolution using capacitance measurements. Intracellular [Ca2+] is controlled by loading via the patch-pipette and by UV-light induced flash-photolysis of caged [Ca2+]. The achieved [Ca2+ ] is measured with Ca2+ -sensitive dyes.<br /> The data is of high quality and the results are compelling.

Weaknesses:

With the exception of mammalian retinal ribbon synapses (and some earlier RNAi knock down studies which had off-target effects), there is little experimental evidence for a "fusion-clamp"-like function of Cplxs at mammalian synapses. At conventional mammalian synapses, genetic loss of Cplx (i.e. KO) consistently decreases AP-evoked release, and generally either also decreases spontaneous release rates or does not affect spontaneous release, which is inconsistent with a "fusion-clamp" theory. This is in stark contrast to invertebrate (D. m. and C. e.) synapses where genetic Cplx loss is generally associated with a strong upregulation of spontaneous release.

There are alternative scenarios explaining how Cplx may phenomenological "clamp" vesicle fusion rates without mechanistically assigning a "clamping" function to Cplx (Neher 2010, Neuron). In fact, changes in asynchronous release kinetics following conditioning AP trains observed at Cplx1 ko calyx of Held synapses do not favor a "fusion clamp" model (Chang et al., 2015, J.Neurosci.), while an alternative model, assigning Cplx the role of a "checkpoint" protein in SNARE assembly, quantitatively reproduces all experimental observations (Lopez et al., 2024, PNAS). It might be helpful for a reader to mention such alternative scenarios.

Reviewer #1 (Public Review):

Summary:

This paper represents a huge amount of work on a condition whose patients' health and well-being have not always been prioritized, and only relatively recently has the immune dysregulation seen in patients with Down Syndrome (DS) been garnering major research interest.

This paper provides an unparalleled examination of immune disorders in patients with DS. The authors also report the results from a clinical trial with the JAK inhibitor tofacitinib in DS patients.

Strengths:

This manuscript reports a herculean effort and provides an unparalleled examination of immune disorders in a large number of patients with DS.

Weaknesses:

Not a major weakness but, apart from finding an elevation of CD4 T central memory cells and more differentiated plasmablast, several of the alterations reported in this manuscript had already been suggested by a few case reports and a very small series. On the other hand, the number of patients (and controls) utilized for this study is remarkable and allows for drawing much firmer conclusions.

Reviewer #2 (Public Review):

In this manuscript, Rachubinski and colleagues provide a comprehensive clinical, immunological, and autoantibody assessment of autoimmune/inflammatory manifestations of patients with Down syndrome (DS) in a large number of patients with this disorder. These analyses confirm prior results of excess interferon and cytokine signals in DS patients and extend these observations to highlight early-onset immunological aberrancies, far before symptoms occur, as well as characterizing novel autoantibody reactivities in this patient population. Then, the authors report the interim analysis of an open-label, Phase II, clinical trial of the JAK1/3 inhibitor, tofacitinib, that aims to define the safety, clinical efficacy, and immunological outcomes of DS patients who suffer from inflammatory conditions of the skin. The clinical trial analysis indicates that the treatment is tolerated without serious adverse effects and that the majority of patients have experienced clinical improvement or remission in their corresponding clinical cutaneous manifestations as well as improvement or normalization of aberrant immunological signals such as cytokines.

The major strength of the study is the recruitment and uniform, systematic evaluation of an impressive number of DS patients. Moreover, the promising early results from the tofacitinib clinical trial pave the way for analysis of a larger number of patients within the Phase II trial and otherwise, which may lead to improved clinical outcomes for affected patients. An inherent weakness of such studies is the descriptive nature of several parameters and the relatively small size of tofacitinib-treated DS patients. However, the descriptive nature of some of the correlative research analyses is of scientific interest and is useful to generate hypotheses for future additional (including mechanistic) work, and treatment of 10 DS patients in a formal clinical trial at interim analysis is not a trivial task for a disease like this. The manuscript achieves the aims of the authors and the results support their conclusions. The authors appropriately acknowledge areas that require more research and areas that are not well understood. The results are represented in a useful manner and statistical methods and analyses appear sound.

Reviewer #3 (Public Review):

Summary:

Individuals with Down syndrome (DS) have high rates of autoimmunity and can have exaggerated immune responses to infection that can unfortunately cause significant medical complications. Prior studies from these authors and others have convincingly demonstrated that individuals with DS have immune dysregulation including increased Type I IFN activity, elevated production of inflammatory cytokines (hypercytokinemia), increased autoantibodies, and populations of dysregulated adaptive immune cells that pre-dispose to autoimmunity. Prior studies have demonstrated that using JAK inhibitors to treat patient samples in vitro, in small case series of patients, and in mouse models of DS leads to improvement of immune phenotype and/or clinical disease. This manuscript provides two major advances in our understanding of immune dysregulation and therapy for patients. First, they perform deep immune phenotyping on several hundred individuals with DS and demonstrate that immune dysregulation is present from infancy. Second, they report a promising interim analysis of a Phase II clinical trial of a JAK inhibitor in 10 people with DS and moderate to severe skin autoimmunity.

Strengths and weaknesses:

The relatively large cohort and careful clinical annotation here provide new insights into the immune phenotype of patients with DS. For example, it is interesting that regardless of autoimmune disease or autoantibody status, individuals with DS have elevated cytokines and CRP. Analysis of the cohorts by age demonstrated that some cytokines are significantly elevated in people with DS starting in infancy (e.g., IL-9 and IL-17C). Nearly all adults with DS in this study had autoantibodies (98%) and most had six or more autoantibodies (63%), which differed significantly from euploid study participants. This implies that all patients with DS might benefit from early intervention with therapy to reduce inflammation. However, it is also worth considering that an alternative interpretation that since hypercytokinemia does not vary based on disease state in individuals with DS, this may not be a key factor driving autoimmunity (although it may be relevant for other clinical symptoms such as neuroinflammation).

Small case series have suggested the benefit of JAK inhibitors to treat autoimmunity in DS. This is the first report of a prospective clinical trial to test a JAK inhibitor in this setting. The clinical trial entry criteria included moderate to severe autoimmune skin disease in patients aged 12-50 years with DS, and treatment was with the JAK1/3 inhibitor tofacitinib. This clinical trial is a critically important step for the field. The early results support that treatment is well tolerated with an improvement of interferon scores in patients and reduction of autoantibodies. Most patients experienced clinical improvement, with alopecia areata having the greatest response. Treatment may not affect all skin diseases equally, for example of the 5 patients with hidradenitis suppurativa, only 1 showed clinical improvement based on skin score. While very promising, the clinical trial results reported here are preliminary and based on an interim analysis of 10 patients at 16 weeks. Individuals with DS have a lifelong risk of immune dysregulation and thus it is unclear how long therapy, if of benefit, would need to be continued. The results of longer-term therapy will be informative when considering the risks/benefits of this therapy.

Joint Public Review

Cav1.4 calcium channels control voltage-dependent calcium influx at photoreceptor synapses, and congenital loss of Cav1.4 function causes stationary night blindness CSNB2. Based on a broad portfolio of methodological approaches - genetic mouse models, immunolabeling and microscopic imaging, serial block-face-SEM, ERGs, and electrophysiology - the authors show that cone photoreceptor synapse development is strongly perturbed in the absence of Cav1.4 protein, and that expression of a nonconducting Cav1.4 channel mitigates these perturbations. Further data indicate that Cav3 channels are present, which, according to the authors, may compensate for the loss of Cav1.4 calcium currents and thus maintain cone synaptic transmission. These data, which are in agreement with a similar study by the same authors on rod photoreceptor synapses, help to explain what functional defects exactly cause CSNB2 and why it is accompanied by only mild visual impairment.

The strengths of the present study are its conceptual and experimental soundness, the broad spectrum of cutting-edge methodological approaches pursued, and the convincing differential analysis of mutant phenotypes. Weaknesses mainly concern the mechanism by which Cav3 channels might partially compensate for the loss of Cav1.4 calcium currents.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript the authors use the model organism Drosophila to explore sex and age impacts of a TBI method. They find age and sex differences: older age is susceptible to mild TBI and females are also more susceptible. In particular, they pursue a finding that virgin vs mated females show different responses: virgins are protected but mated females succumb to TBI with climbing deficits. In fact, virgin females compared to mated females are largely protected. They discover this is associated with exposure of the females to Sex Peptide in the reproductive neurons of the female reproductive tract. When they extend to RNAseq of brains, they show that there are very few genes in common between males, mated females, virgins and females mated with males lacking sex peptide. But what the few chronic genes associated with mated females seem associated with the immune system. These findings suggest that mated females have a compromised immune system, which might make them more vulnerable. In a bigger context, these findings point to the idea that the life status of the animal/individual may have an important impact on the outcome of a TBI - here illustrated by the differential state of virgin vs mated females in Drosophila.

Strengths:<br /> This is an interesting paper that allows a detailed comparison of sex and age in TBI which is largely only possible in such a simple model, where large numbers and many variations can be addressed. Overall the findings are interesting.

Weaknesses:<br /> Although the findings beyond Sex peptide are observational, the work sets the stage for more detailed studies to pursue the role of the genes they find by RNAseq and whether for example, boosting the innate immune system would protect the mated females, among other experiments.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors use the Drosophila model system to study the impact of mild head trauma on sex-dependent brain deficits. They identify Sex Peptide as a modulator of greater negative outcomes in female flies. Additionally, they observe that increased age at the time of injury results in worse outcomes, especially in females, and that this is due to chronic suppression of innate immune defense networks in mated females. The results demonstrate a novel signaling pathway that promotes age- and sex-dependent outcomes after head injury.

Strengths:<br /> The authors have modified their previously reported TBI model in flies to mimic mild TBI, which is novel. Methods are explained in detail, allowing for reproducibility. Experiments are rigorous with appropriate statistics. A number if important controls are included. The work tells a complete mechanistic story and adds important data to increase our understanding of sex-dependent differences in recovery after TBI. The Discussion is comprehensive and puts the work in context of the field.

Weaknesses: None<br /> The authors answered the following concerns, and I have no other concerns:<br /> A very minor weakness is that exact n values should be included in the figure legends. There should also be confirmation of knockdown by RNAi in female flies either by immunohistochemistry or qRT-PCR if possible.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors used a Drosophila model to show that exposure to repetitive mild TBI causes neurodegenerative conditions that emerge late in life and disproportionately affect females. In addition to the well-known age-dependent impact, the authors identified Sex Peptide (SP) signaling as a key factor in female susceptibility to post-injury brain deficits.

Strengths:<br /> The authors have presented a compelling set of results showing that female sex peptide signaling adversely affects late-life neurodegeneration after early-life exposure to repetitive mild head injury in Drosophila. They have compared the phenotypes of adult male and female flies sustaining TBI at different ages, and the phenotypes of virgin females and mated females, 2) compared the phenotypes of eliminating SP signaling in mating females and introducing SP-signaling into virgin females, 3) compared transcriptomic changes of different groups in response to TBI. The results are generally consistent and robust.

Weaknesses:<br /> The authors have made their claims largely based on assaying climbing index and vacuole formation as the only indicators of late-life neurodegeneration after TBI. Furthermore, it is also really surprising to see so few DEGs even in wild-type males and mated females and to see that none of DEGs overlap among groups or are even related to the SP-signaling. The authors state that the reason is their TBI is very minor. It is critical to independently verify their RNA-sequencing results and to add some more molecular evidence to support their conclusion. Finally, since similar sex peptide signaling is not present in mammalians or humans, its implication in humans remains unclear.