Reviewer #1 (Public Review):

The authors identified the gene encoding PBP-lipo by a Tn-Seq analysis of the Mycobacterium abscessus genome seeking genes required for viability. PBP-lipo essentiality was confirmed by CRSPRi knockdown (KD) studies and the mutant/KD phenotypes (cell shape and cytokinetic defects) observed by microscopy. The show that PBP-lipo localizes to the division plane and interacts genetically (by conditional CRISPRi partial KD) with other cell wall biosynthesis proteins that are known to act at the division plane. they also find PBP-lipo is also required to protect against antibiotics that target the cell wall machinery and also some antibiotics that act in the cytoplasm, therefore indicating that PBP-lipo KD mutants suffer from a permeability defect which they could recapitulate by calcein staining.

Importantly, they find that PBP-lipo is important in Mycobacterium abscessus (including clinical isolates) but not in Mycobacterium smegmatis and Mycobacterium tuberculosis lab strains. The authors show that Mycobacterium smegmatis PBP-lipo can, however, compensate for the loss of PBP-lipo in Mycobacterium abscessus, showing that the ortholog of Mycobacterium smegmatis has not lost its function, but that the idiosyncracies of the cell wall biosynthesis machineries and their interaction network in various mycobacteria differs. These findings set the stage for (combinatorial) beta-lactam based treatments of Mycobacterium abscessus infections.

The work is exceptionally well done, comprehensive, solid and clearly presented.

Reviewer #2 (Public Review):

In my view the authors used suitable methodologies to address important research questions in mycobacteria: What are the essential genes of Mab and why is one of these, the PBP-lipo gene essential in Mab despite the presence of a homologous gene. They also revealed differences in PBP requirements in different mycobacterial species. In my view, this is an excellent manuscript demonstrating the importance of a new PBP for Mab growth, morphology and sensitivity to antibiotics. However, I noticed that a recent publication has already reported the essential genes in Mab using a similar methodology. It is also fair to say that it is not a novelty that bacteria have different sets of PBPs and some PBPs are essential in one species but not in others, sometimes even closely related species. This wider aspect beyond mycobacteria is not well discussed in the manuscript. Nevertheless, I believe that the manuscripts provides an important step forward in understanding cell wall biogenesis in different mycobacteria, revealing an important cell wall enzyme in Mycobacterium abscessus that could be targeted by drugs against this pathogen.

Reviewer #3 (Public Review):

In this study, Akusobi et al., compare the inventory of Tn-seq-derived essential genes in M. abscessus, to those in M. tuberculosis and M. smegmatis and identify a set of genes that are 'uniquely essential' to Mab. A subset of these 'uniquely essential' genes are validated using CRISPRi knockdown. They select PBP-lipo, a putative Class B penicillin-binding lipoprotein, for further analyses. Using a combination of neat genetic and cell biology experiments they characterize the possible role of PBP-lipo in regulating growth and development of Mab. PBP-lipo localizes to the putative division site and depletion of PBP-lipo produces branched filamentous cells with decreased viability. Interestingly, expression of Msm PBP-lipo could reverse the developmental defects of PBP-lipo depleted Mab cells suggesting it may not be the property of the protein but its interacting network that might be unique in Mab. Genetic interaction studies using other annotated PBPs in Mab suggests that PBP-lipo may function in tandem with pbpB, dacB1 and MAB_0519, of which DacB1 and PbpB may localize to the same sub-cellular position as PBP-lipo. These genetic interactions are not seen in Msm and PBP-lipo does not have a synthetic lethal partner in Msm. Strikingly, PBP-lipo depletion renders both laboratory strain and clinical isolates of Mab susceptible to a subset of antibiotics.

This is an elegantly carried out study that demonstrates the unique role of PBP-lipo in maintaining envelope integrity of Mab. This exciting and timely finding not only opens up the possibility of using PBP-lipo as a putative drug target in treating Mab infections, it further goes onto set the stage for further in-depth analyses of species-specific developmental processes in Mab.

Reviewer #2 (Public Review):

Using in toto, multiview light-sheet imaging of the Drosophila midgut, the authors investigate how the endoderm and surrounding muscle layer interact to fold and elongate the developing organ. They find that the movements of both layers closely coincide and that cell flows and shape changes in the endodermal closely correlate with midgut constrictions. Optogenetic inhibition or stimulation of muscle contractility impairs folding patterns, consistent with localized contractility being the driving force for gut constriction and organ shape change. Using a GCAMP6 calcium sensor, they find that Hox-dependent calcium pulses spatially correlate and are required for local muscle contraction and midgut folding. This study represents a substantial advance in whole-organ imaging, between layers, in a deep internal organ. The image processing and analysis pipeline represent another important technical advance. The data are simply beautiful and presented in a clear and convincing way. Multiple parallel approaches are used to test the hypothesis that patterned midgut contractions generate whole organ shape changes in the developing midgut, and thus, the conclusions are well supported by the data. The main weakness of the paper in its current form is the overly-concise nature of the main text. Descriptions of the approach and results would need to be elaborated. Some terms are not well defined in the main text, particularly in the sections accompanying Figure 2, making it difficult to follow some of the logic and conclusions.

Reviewer #3 (Public Review):

This manuscript addresses important questions in developmental biology: how Hox codes are transformed into organ shapes and how different tissue layers mechanically interact during morphogenesis. The authors set up a deep tissue imaging system that allowed them to simultaneously track the endoderm and overlaying muscles during gut folding in Drosophila embryos. By combining the imaging system with optogenetic manipulation of muscle constriction, the authors showed that Hox genes are required to trigger Ca++ spikes and induce muscle constriction specifically in the future-fold region, which results in changes in endodermal cell shape. The authors' claims were supported by data. However, the quantification of endodermal cell behaviors, especially with respect to the link between cell- and tissue-scale deformations would benefit from comparisons of folded and unfolded regions that could be generated from existing data.

Reviewer #1 (Public Review):

This work provides solid in vitro evidence supporting the role of the phosphorylation of the EI domain of human AGO2 during the dynamic association/dissociation of the RISC complex to the target mRNAs. The evidence shows that the association of the RISC with a target mRNA, though the seed region, triggers CK1α phosphorylation of the EI region of AGO2, which in turn electrostatically promotes target release and AGO2 recycling. This effect becomes more evident when miRNA/target pairing extends to 3' supplemental regions besides the seed region. Furthermore, the phosphorylation of the EI starts in S828 then acts hierarchically to prime the phosphorylation of the remaining sites in the region. The paper provides strong in vitro evidence that will interest the gene silencing community. Perhaps the weaker aspect of the manuscript is the lack of in vivo evidence to support the conclusion, although this may be hard to achieve.

Reviewer #3 (Public Review):

Using an elegant combination of biochemical, structural and biophysical approaches, the authors nicely demonstrated that binding of miRNA-loaded hAgo2 to its targets triggers phosphorylation of the hAgo2 EI by CK1α.

They demonstrated an important role for hAgo2 release from its target allowing a turnover of target mRNAs. They also demonstrated a hierarchy in amino acid phosphorylation as well as a role of this phosphorylation in electrostatic repulsion between target mRNA and hAgo2 loaded with a miRNA.

These results could help to explain how cells could regulate several targets with a small amount of hAgo in comparison to the estimated number of the target.

They provide a nice view on how Ago proteins that are unable to cleave their target (which is the case with miRNAs and not with piRNAs or siRNAs) could be released from their target via an electrostatic destabilisation.

Overall the experiments are well done and nicely explained. The manuscript iswas also easy to read. Future experiments should be done in vivo to be fully conclusive about the global role of Ago phosphorylation in the off-rate of association with its target.

Reviewer #1 (Public Review):

Smith et al. investigated jaw development across three different species of birds. They found that quail have higher TRAP activity and Mmp13 expression than duck in the jaw bones. They have examined the TGFβ signaling activity in chick, quail and duck both in vitro and in vivo and found that quail and chick have higher TGFβ signaling activity than duck and are more sensitive to TGFβ signaling. They also analyzed the function of TGFβ signaling on its downstream target genes in these avian species. Interestingly, they found that two SNPs distinguish chick and quail from duck and that these two SNPs affect the differential species-specific response of the Mmp13 promoter. These data altogether provide an interesting perspective on jaw development and evolution.

Strengths: The authors used three different avian species to study jaw development and the mechanism uncovered in this work provides important clues about jaw evolution. The authors have also used different approaches to evaluate the TGFβ-Runx2-Mmp13 axis in jaw development in these three avian species. It has potential impact on both developmental biology and evolutionary biology.

Weaknesses: There should be more in vivo analysis to validate their findings. In addition, more evidence should be provided at the cellular level to support their conclusions.

Reviewer #2 (Public Review):

In this manuscript, the authors propose a novel mechanism by which jaw length might be regulated in vertebrates. The jaw skeleton is derived from neural crest mesenchyme. They demonstrate that in developing quail embryos, the lower jaw, which is significantly smaller compared to duck, actively upregulates TGFβ signaling pathway and in turn display a high MMP13 activity and this subsequently leads to increased bone remodeling. They further correlate this process to the smaller mandible size in quail embryos. The main point of the manuscript is therefore that active bone remodeling can regulate organ size and may contribute to size/ shape variation of mandible across species, however in its current form, this point does not come across so clearly. The manuscript provides further comparative data highlighting promoter elements in species-specific regulation of Mmp13 expression.

Reviewer #3 (Public Review):

Smith et al. evaluated a role of bone-resorbing enzyme Mmp13 in craniofacial structures development and the sensitivity of facial tissues to the activation of TGFβ signalling with aim to discover developmental processes driving formation of short beaks in chicken or quail versus long beaks in duck. The main topic can be interesting for broader audience as organ shape regulation during embryogenesis is still not well studied and the manuscript brings new findings to this field.

Authors uncovered that jaw-bone length is governed by neural crest cells-mediated bone resorption and revealed a mechanism contributing to the establishment of specific face shape in selected bird species.<br /> Differential gene expression level of TGFβ signaling was found to be associated with shorter beak formation and the activation of the TGFβ pathway was also confirmed by analyses on protein level.<br /> To identify mechanisms that control the differential regulation of Mmp13, authors evaluated the structure and function of the Mmp13 promoter in selected model species and determined several promoter domains, which contained RUNX2 and SMADs binding elements, which are the most probable to regulate MMP13 expression. Design of species-specific reporter constructs with or without these binding elements helped them to uncover differences in promoter activity among species. Higher activity of these binding elements was found for quail and chick with shorter beaks. Two single nucleotide polymorphisms were found directly downstream of the RUNX2 binding element, which again distinguished quail and chick from duck. Series of functional experiments, where these SNPs were switched between species, confirmed their role and direct involvement in the regulation of promoter activity.

The conclusions of this paper are well supported by convincing data.

Strengths:<br /> Main question was evaluated at multiple levels to target different aspects of gene regulation of the TGFβ pathway and Mmp13 function and their possible roles in bone resorption, which ultimately underlay the variation of jaw length and drive the species-specific beak morphology in birds.<br /> Using of three different models such as chick, quail, and duck embryos enable to associate individual findings with the distinct phenotype of these animals leading to clear outcomes.<br /> Careful and complex design of individual experiments enable to target possible role of individual components of MMP13 promoter by functional tests.

Weaknesses:<br /> Authors indicate possible evolutionary consequences of their main findings, however there is no discussion about more broad implications from EVO-DEVO perspective or about possible similarities or differences during endochondral skeletogenesis.

Reviewer #1 (Public Review):

This well written manuscript by Li et al. utilizes a comprehensive chemical screening library to identify compounds with anti-fibrotic activity in hepatic stellate cells. The authors were thorough in their investigation using both in vitro and ex vivo strategies in rodent and human cells. The authors identify the polyether ionophore nanchangmycin as possessing novel anti-fibrotic activities. The authors go on to show that nanchangmycin inhibits multiple aspects of hepatic stellate cell activation including migration, proliferation and activation genes. Finally, the authors provide a cellular/molecular mechanism underlying the anti-activation properties of nanchangmycin through inhibition of several signaling cascades. This study is of high priority given the lack of therapeutic options for the treatment of hepatic fibrosis.

Reviewer #2 (Public Review):

The manuscript aims at identifying compounds with liver antifibrogenic effect. To do so the authors perform a high-throughput drug screening on HSCs, the main fibrogenic cell type of the liver. The manuscript is a good resource for further studies on liver fibrosis, since it provides information on the effect of an important number of drugs on HSCs. However, the authors use only one readout (cytoplasmic lipid accumulation) for the first screening to evaluate the effect of drugs on HSCs, so for most compounds the data available is limited, and drugs acting though other mechanisms beside the accumulation of lipid droplets may not be detected. Moreover, the manuscript provides robust data that NCMC regulate HSCs activation.

The approach of the study is very interesting and provides novel information for the field. Overall, the authors obtained 19 compounds with a potential antifibrogenic effect, based on the effects on HSCs. However, it is surprising that out of more than 15000 compounds only 19 reduced the activation of HSCs.

The results on the effect of NCMC on HSCs are robust. However, there is no information on the induction of a quiescent phenotype, or on the effects of NCMC on disease models.

Reviewer #3 (Public Review):

Li et al. used a high throughput screening method and identified Nanchangmycin can inhibit hepatic stellate cell (HSC) activation and induced their inactivation through in vitro cell culture experiment. The study also determined that Nanchangmycin can increase cytosolic Ca concentration and inhibit FYN, FAK, and ERK activities, which are crucial for HSC activation. These findings suggest that Nanchangmycin has potential to treat liver fibrosis. Overall, the study should be of interest to the researchers who seek novel agents for treating liver fibrosis.

Strengths

1. The study used a high throughput screening method to identify Nanchangmycin from 15,867 compounds.<br /> 2. The study determined the effect of Nanchangmycin on HSC inactivation by assessing ECM production, HSC migration, and proliferation.<br /> 3. The study determined the effect of Nanchangmycin on and regulation of cytosolic Ca concentration and activation of FYN, FAK, ERK pathways.

Weaknesses

1. The study did not validate whether Nanchangmycin has a therapeutic effect using in vivo liver fibrosis model.

Reviewer #1 (Public Review):

The manuscript by Kanda GN, Natsume T et al. describes the development of a robotic artificial intelligence system with a batch Bayesian optimisation algorithm with the aim to optimise and reliably repeat cell culture protocols in an automated fashion.

The authors successfully achieve the overall goal of demonstrating the capacity and potential of the robotic system for protocol optimisation, reliable repetition and efficient cell product generation.

The major strength of the study is the advanced laboratory automation system developed, with seemingly superior flexibility, precision and efficiency to generate advanced cell products, compared with other systems described previously, or compared with manual handling.

The authors utilise induced pluripotent stem cell-derived retinal pigment epithelial cells as a proof-of-principle, model culture system. Using this system, they convincingly demonstrate the potential of this automated platform for multiple cell culture applications of broad interest in regenerative medicine.

The work presented here demonstrates the successful implementation of laboratory automation for a cell culture product used for regenerative medicine purposes. LabDroid Maholo robotic platform integrated advanced robotics capabilities to perform precise handling of equipment to replace skilled human operations in a repeatable and error-free manner. Integrated AI-based image analysis with batch Bayesian optimisation algorithm helped to identify required process changes to the cell culture protocol to improve the differentiation of induced pluripotent stem cells (iPS) cells to retinal pigment epithelial cells (RPE).

Reviewer #2 (Public Review):

Laboratory automation in life science laboratories to replace complex operations performed by skilled scientists with mechanisation or automation remains a major technical challenge. Since most of the cell culture process steps remain as an art and the parameters are undecoded to be amenable to a robotic system to operate, complex cell culture protocols remain as manual processes. Recent developments in laboratory automation advanced to perform simple process steps like cell culture media addition or removal, cell seeding and passaging using robotic platforms. Determination of cell confluence and assessment of the level of differentiation typically needs to be conducted offline and the process parameters to be fed into the robotic system manually to command further steps.

Natsume et.al. demonstrated by this work that the cell culture techniques conducted by skilled scientists can be replaced with laboratory automation. Work revealed that an effective combination of robotics and artificial intelligence can replace complex human operations of cell culture techniques with robots even in a complex cell differentiation process. While other similar studies demonstrated the use of robotics in cell culture protocol to mechanise repetitive process steps or liquid handing this work utilised an advanced robotic system with precision movements and the capacity to perform complex tasks required in a cell culture process. The robotic arms undertake several activities required in a cell culture lab with comparable precision to human counterparts yet with high repeatability of a robot. The capability of the robot to handle a micropipette, small tubes or using an incubator demonstrates its refined mechanical abilities. An effective combination of artificial intelligence with robotics enabled this platform to conduct analytics in real-time and the algorithms predicted the best process parameters to be used to improve the cell culture. Cell culture images generated by the integrated imaging suite within the Maholo system were analysed to calculate the rate of differentiation of iPS cells into RPE cells. In general, the integration of all necessary systems in a single platform with robotic arms that can perform refined activities like a human made the system highly suitable for the application.

This work showed that the LabDroid Maholo system is superior compared to the existing systems used in bioscience and cell culture applications. It is evident from the presented data that the system operates with high precision and repeatability with less chance of errors to generate differentiated RPE cells. Since the rate of differentiation consistently increased with the optimisation predicted by the Bayesian algorithm cell culture system which ensures the reliability of the system for this purpose. Iterative process improvements were undertaken based on the Bayesian algorithm resulting in an increased rate of differentiation. Results obtained from the screening experiments were validated multiple times with statistical significance, which proves the reliability of the Bayesian algorithm and robotics.

Although the LabDroid Maholo system presents a huge capability to replace several activities of a skilled scientist, the work presented here was a rather well-suitable process to exploit the capabilities of this highly precise robotic system. Despite the robot's ability to undertake complex laboratory tasks, an initial set of work including the cell seeding was conducted manually before it was suitable for a robot to operate. Although it is not far away from assigning such activities to a robot to conduct, it needs to be done to make the full process to be automated.

It is noteworthy that process parameters used in this work included duration of trypsinization, pipetting strength and speed along with the concentration of differentiation agents and their exposure time. With such parameters alone, it is not realistic to claim that the system can be utilised to optimise the cell culture or differentiation programme. Since a differentiation programme is developed by comparing against or modelling an in-vivo system, a lot more elements of that real biological environment and complex signalling mechanism need to be taken into consideration. Incorporation of such biological information into the presented robotic platform is impractical. In that sense, searching for optimal cell culture conditions must be considered within the limits of the existing system. Thus it may be argued that the capacity of the Maholo LabDriod system is limited to a pre-defined set of process parameters in terms of its process optimisation capacity.

Maholo LabDriod system utilises a precise robotic system with analytical power but here some components and operations remained traditional e.g. usage of manual micropipettes and especially to use the same pipette multiple times to dispense adequate volume. This seemed to be a combination of the most advanced system with an old tool. Dedicated electronic pipettes with defined volumes would have been used instead. While the process utilised here presented with a visible differentiation marker (melanin expressing cells upon differentiation) made it possible to measure differentiation and adjust the process parameters accordingly. In other cell culture products, where no such visible markers are available to determine differentiation, immunostaining or flow cytometry or other ways of determination will be required. In such cases, the LabDroid system might not work as efficiently as in the work presented here.

Although it was not directly within the scope of this work, another major aspect that is not considered in this study is the mode of cell culture. Due to the requirement of the large scale of cells required for regenerative medicine purposes, suspension-based cell culture replaces adherent cell cultures in several products. It would be interesting to see how the LabDroid Maholo system performs with suspension-based cultures. Although the Batch Bayesian optimization predicts millions of potential combinations of parameters, it is not clear how the selected 48 conditions provided the best differentiation conditions. It is not clear if the study did address selecting the parameters based on the Design of Experiment principle and if the selected parameters cover all necessary process parameter combinations.

Overall, the Maholo LabDroid system brings in more capable robotic control to mechanise and automate highly skilled human operations in the cell culture process in comparison to previously used robotic systems elsewhere. The cell culture imager and AI-based analytical capability provide options to identify process parameters for optimization and improved differentiation process.

It is fully appreciated that the robotic system is potentially the most advanced one used for cell culture protocols. The way it handles micropipettes and uses both arms to dispense liquid or to open the incubator etc. provides a view about how this type of robot is going to emerge. The study demonstrates the effective use of a combination of robotics and artificial intelligence to replace complex human operations of cell culture techniques with robots. Integrated AI could successfully analyse the state of cell culture to identify cell differentiation markers and enabled live modifications to the cell culture system to improve differentiation. Certainly, the Maholo LabDroid system brings in more capable robotic control to mechanise and automate highly skilled human operations in comparison to previously used robotic systems elsewhere.

Reviewer #1 (Public Review):

Salina, dos-Santos, Rodrigues, et al demonstrate that dying cells from SARS-CoV-2-infected cultures shift gene expression from an alternative activation-like state (characterized by CD206) towards a classical activation-like state (characterized by IL6) for primary human macrophages and the THP-1 macrophage cell line. These phenotypes of reduced CD206 expression and elevated IL6 expression were not induced by SARS-CoV-2 "AC" (loosely adherent cells in culture) after UV sterilization, annexin V treatment, cytochalasin treatment (to inhibit internalization), or fixation. These phenotypes were also not replicated by supernatant factors from SARS-CoV-2 infected cultures. Furthermore, coxsackievirus-infected dying cells did not induce similar effects on macrophages as SARS-CoV-2-infected dying cells. Uptake of SARS-CoV-2 ACs led to reduced macrophage expression of phosphatidylserine (PtSer) receptors and reduced uptake of more apoptotic cells. Upon autopsy of deceased COVID-19 patients, the authors found reduced CD36 and MERTK on lung phagocytes by microscopy, consistent with their in vitro findings. Furthermore, reanalyzed published scRNA-Seq data from broncheoalveolar lavage indicated that expression of several efferocytosis-related modules was decreased, especially in cells with SARS-CoV-2 mRNA. They also find that circulating monocytes from patient blood are altered in composition and show similar alterations. When circulating PMBC gene transcription was assessed by qPCR, they found similar reductions, which were not replicated in acute respiratory distress syndrome patients. This signature was correlated with more severe disease. Patient monocytes had specific defects in dead cell uptake. Taken together, Salina, dos-Santos, Rodrigues et al demonstrate that SARS-CoV-2-infected dying cells induce changes in efferocytosis that are dependent on live virus, internalization of the dying cell, and PtSer recognition. While the authors describe and characterize several true (and intriguing phenomenon), with careful use of controls, I have one major concern, as well as several other concerns with the manuscript as currently constructed.

Major:<br /> 1) The authors do not characterize the level of necrotic cells in their SARS-CoV-2 infected cultures. These will be present in their loosely adherent "AC" fraction and would be far more likely to induce IL-6. The authors never show costaining for Annexin V and a membrane impermeable dye (such as 7-AAD). This is a major oversight which must be addressed, as annexin V will stain both apoptotic and necrotic cells (in the first case, because PtSer is flipped. In the second case, because membrane integrity is lost). While their cleaved caspase 3 staining and use of zVAD is nice to address apoptosis more selectively, the annexin V staining as used is not sufficient. Most importantly, for their stimulation experiments, the authors need to find a way to separate the necrotic and apoptotic cell fractions, or otherwise address the role of necrotic cells. Otherwise, their findings could be due to necrotic cells (as would be more consistent with the considerable proinflammatory effects of the SARS-CoV-2 "AC" fraction).<br /> Minor<br /> 2) As acknowledged by the authors, there is a major disconnect between their in vitro data and their patient data. As the authors clearly and elegantly demonstrate, soluble factors from SARS-CoV-2 infected cultures are inadequate to show many of the described affects of SARS-CoV-2 AC. Yet, the patient comparison done by the authors is with circulating (i.e., non SARS-CoV-2 exposed) PBMC. While I appreciate that the authors are limited in the cell types they can obtain from SARS-CoV-2 infected patients, it is nonetheless a significant issue that the in vitro and (some) ex vivo portions of their study seemingly describe entirely different phenomenon.<br /> 3) Figure 1B. Why do the staining patterns of spike and CD68 look identical? What controls do the authors have to detect and compensate for spillover between channels? Please explain this anomaly and how images were processed post-acquisition (software, etc).

Reviewer #2 (Public Review):

This study defined the cellular mechanisms of macrophages in severe SARS-CoV-2 infection. Using patients' samples and cell culture experiments, they demonstrated that SARS-CoV-2 switched macrophages from anti-inflammatory to pro-inflammatory phenotypes. The process of clearing apoptotic cells by macrophages was impaired in severe SARS-CoV-2 infection. The macrophages accumulated the dying cells inside excessively expressed inflammatory genes. The study is significant, indicating the potential molecular targets to ameliorate severe SARS-CoV-2 infection. The logical demonstration that "sensing and engulfment of dying cells carrying viable SARS-CoV-2" (line 198) but not other pathogens switched macrophages toward the pro-inflammatory phenotypes is clear. The manuscript will be more improved if the authors test the impact of COVID19 pills and vaccines on their phenotypes in efferocytosis.

Reviewer #1 (Public Review): 

The authors found a switch between "retrospective", sensory recruitment-like representations in visual regions when a motor response could not be planned in advance, and "prospective" action-like representations in motor regions when a specific button response could be anticipated. The use of classifiers trained on multiple tasks - an independent spatial working memory task, spatial localizer, and a button-pressing task - to decode working memory representations makes this a strong study with straightforward interpretations well-supported by the data. These analyses provide a convincing demonstration that not only are different regions involved when a retrospective code is required (or alternatively when a prospective code can be used), but the retrospective representations resemble those evoked by perceptual input, and the prospective representations resemble those evoked by actual button presses. 

I have just a couple of points that could be elaborated on: 

1. While there is a clear transition from representations in visual cortex to representations in sensorimotor regions when a button press can be planned in advance, the visual cortex representations do not disappear completely (Figs 2B and C). Is the most plausible interpretation that participants just did not follow the cue 100% of the time, or that some degree of sensory recruitment is happening in visual cortex obligatorily (despite being unnecessary for the task) and leading to a more distributed, and potentially more robust code? 

2. To what extent might the prospective code reflect an actual finger movement (even just increased pressure on the button to be pressed) in advance of the button press? For instance, it could be the case that the participant with extremely high button press-trained decoding performance in 4B, especially, was using such a strategy. I know that participants were instructed not to make overt button presses in advance, but I think it would be helpful to elaborate a bit on the evidence that these action-related representations are truly "working memory" representations.

Reviewer #2 (Public Review): 

Henderson, Rademaker and Serences use fMRI to arbitrate between theories of visual working memory proposing fixed x flexible loci for maintaining information. By comparing activation patterns in tasks with predictable x unpredictable motor responses, they find different extents of information retrieval in sensory- x motor-related areas, thus arguing that the amount/format of retrospective sensory-related x prospective motor-related information maintained depends on what is strategically beneficial for task performance. 

I share the importance of this fundamental question and the enthusiasm for the conclusions, and I applaud the advanced methodology. I did, however, struggle with some aspects of the experimental design and (therefore) the logic of interpretation. I hope these are easily addressable. 

Conceptual points:

1. The main informative x non-informative conditions differ more than just in the knowledge about the response. In the informative case, participants could select both the relevant sensory information (light, dark shade) and the corresponding response. In essence, their task was done, and they just needed to wait for a later go signal - the second disk. (The activity in the delay could be considered to be one of purely motor preparation or of holding a decision/response.) In the uninformative condition, neither was sensory information at the spatial location relevant and nor could the response be predicted. Participants had, instead, to hold on to the spatial location to apply it to the second disk. These conditions are more different than the authors propose and therefore it is not straightforward to interpret findings in the framework set up by the authors. A clear demonstration for the question posed would require participants to hold the same working-memory content for different purposes, but here the content that needs to be held differs vastly between conditions. The authors may argue this is, nevertheless, the essence of their point, but this is a weak strawman to combat. 

2. Given the nature of the manipulation and the fact that the nature of the upcoming trial (informative x uninformative) was cued, how can effects of anticipated difficulty, arousal, or other nuisance variables be discounted? Although pattern-based analyses suggest the effects are not purely related to general effects (authors argue this in the discussion, page 14), general variables can interact with specific aspects of information processing, leading to modulation of specific effects. 

3. I see what the authors mean by retrospective and prospective codes, but in a way all the codes are prospective. Even the sensory codes, when emphasized, are there to guide future discriminations or to add sensory granularity to responses, etc. Perhaps casting this in terms of sensory/perceptual x motor/action~ may be less problematic. 

4. In interpreting the elevated univariate activation in the parietal IPSO-3 area, the authors state "This pattern is consistent with the use of a retrospective spatial code in the uninformative condition and a prospective motor code in the informative condition". (page 6) (Given points 1 and 3 above) Instead, one could think of this as having to hold onto a different type of information (spatial location as opposed to shading) in uninformative condition, which is prospectively useful for making the necessary decision down the line. 

Other points to consider:

1. Opening with the Baddeley and Hitch 1974 reference when defining working memory implicitly implies buying into that particular (multi-compartmental) model. Though Baddeley and Hitch popularised the term, the term was used earlier in more neutral ways or in different models. It may be useful to add a recent more neutral review reference too? 

2. The body of literature showing attention-related selection/prioritisation in working memory linked to action preparation is also relevant to the current study. There's a nice review by Heuer, Ohl, Rolfs 2020 in Visual Cognition.

Reviewer #1 (Public Review): 

In this study a large dataset of EEG recordings from children, adolescents and young adults between 6 and 22 years was analysed regarding developmental changes of alpha amplitude. Previous literature on this issue is incoherent, sometimes suggesting age-related decrease sometimes increase of alpha activity. The authors, therefore, separated periodic and aperiodic activity, suspecting that age-related decrease of alpha activity might be spuriously driven by aperiodic signals. And indeed this is what they could demonstrate nicely. In fact, when cleaning EEG from aperiodic signals alpha activity even shows an increase during development. Aperiodic-adjusted alpha activity is, moreover, reduced in participants with ADHD in the sample. 

What is particularly nice is that in a sub-sample where MRI scans were available alpha changes were associated with thalamic volume and thalamic white matter integrity. Only the latter, as was shown in the study, is associated with aperiodic-adjusted alpha power. This suggests that developmental changes of alpha activity might be driven by thalamic maturation. 

This is a really extremely well-done study. The idea is elaborated, and hypotheses well justified. The large sample provides good statistical power. The statistical modelling is a very smart way of analysing the data. The findings are definitely clarifying a lot of questions that can arise given the incoherent previous literature on this topic. I particularly like that a fundamental mechanism, namely maturation of the thalamus, was included to provide an explanation for developmental changes of alpha activity instead of simply speculating on the causes of the described EEG effect. 

All in all I think this is an amazing manuscript that will surely have a strong impact on the field.

Reviewer #2 (Public Review): 

Electrophysiological oscillations are a fundamental neural process that has rich implications in behavior. A major index of such activities is power (for a given frequency), which has substantiated a massive body of work in multiple domains. Conventional indices of power contain both the periodic component (reflecting oscillatory activity) and the aperiodic component (reflecting the exponential 1/f decay of power across the full spectrum). Recently, this confound in power indices has caught increasing attention. Therefore, it is time to address this potentially serious issue in the extant literature and promote the consideration of aperiodic signals in future research. 

Here, the authors decomposed the periodic and aperiodic components in the EEG alpha power measure. They demonstrated the confound of aperiodic signals in the total alpha power and elucidated the opposing relation of the periodic and aperiodic components with age. The approach is rigorous, including a large sample (N > 2500), validation in an independent sample, careful consideration of the effects of ADHD/clinical diagnoses. The results are largely supportive of the authors' claims. 

My main issue with the paper concerns the focus on "total" as opposed to "relative" power in the study. It has become standard in the literature to use "relative power", i.e., normalize power by dividing the total power by the average power of the full power spectrum. This normalization process effectively removes contamination/confounds of skull thickness and skin conductivity from total power. Therefore, the focus on a contaminated and thus rather obsolete measure of alpha power here is somewhat misplaced, undercutting the methodological and theoretical impact of the study. 

Another problem with the focus on total power is that its main contamination (skull thickness/skin conductivity) is shared by an aperiodic index, the aperiodic intercept. Therefore, the positive correlation between skull thickness and age can drive the negative correlation between age and both total power and aperiodic intercept. 

Relative alpha power and aperiodic slope are largely free of such signal contamination and should deserve more focused examination. Relatedly, it would shed useful light on the inherent association among these four major indices (total/relative alpha power, aperiodic intercept/slope) by running simple correlation among them. In fact, relative alpha power shows similar correlation with age as the aperiodic-adjusted alpha power. While the simulation results suggest that the former can lead to significant distortions, it is unclear, in real datasets and here in development, how the two indices of alpha power are related and whether the aperiodic confound merely weakens the validity of relative power, causing null findings. Such findings will inform the field as to how "distorted" the extant claims are and whether the extant literature suffers from false negatives or there is a high likelihood of alarming contradictions to true oscillatory activities such that a "new look" of previous findings is warranted.

Reviewer #3 (Public Review): 

In this paper, Troendle et al investigate changes in alpha oscillation across childhood and adolescence. The main goal of this investigation is to examine how alpha oscillations change across these age ranges, by investigating a large open dataset and adopting new methods that should help to address methodological limitations of many previous analyses. In particular, a key goal is to examine changes in periodic alpha power, and control for potential confounds due to changes in peak frequency and/or aperiodic activity. To do so, they employ a novel spectral parametrization method, and systematically compare measures of isolated periodic alpha activity to conventional measures. Overall, they find that they can replicate the age-related decrease of total alpha power when using conventional methods. However, when explicitly measuring and controlling for aperiodic activity, they find that periodic alpha activity actually increases with age. They suggest this discrepancy can be explained by changes in aperiodic activity, as the aperiodic slope and intercept are found to systematically change across age, in a way that likely drives the finding decrease of total alpha power, while the periodic alpha power actually increases. There are also some follow up analyses, including relating alpha power to anatomical measures of the thalamus, and to performance on an attention task. 

Strengths of this investigation include that it analyzes multiple, large datasets with well motivated methods. I think the goal of this paper addresses an important question, in terms of seeking to clarify some basic patterns of oscillation changes across development, and doing so in a rigorous way, both in terms of employing methods that are robust to estimating different features of the data, and in terms of using multiple, large datasets, including an internal replication of the main findings. I find the main goal and analysis compelling in terms of examining how alpha activity changes across this age range. 

I also find some limitations to some aspects of this paper and analysis that could be improved, as they do not always clearly describe the context or support the claims that are made for some of the follow-up analyses, as described in the following. 

1. Framing and prior literature 

I find some limitations in the organizing of this paper and it's relationship to prior work that could be improved, as I find that the paper could do better situating the analyses here with prior work, in particular in relation to the methodological issues it is addressing, and prior work on aperiodic activity. 

For example, in the abstract it is stated that "simulations in this study show that conventional measures of alpha power are confounded". Despite this statement, simulations are not a core feature of this study. There are a couple simulated examples in the supplement, which are referred to in lines 89-95, however it's worth nothing noting that while this section does not include any citations, the described issues, and related simulations, are very similar to points that have been made previously in the literature, that seem like they should be cited here: <br /> - Donoghue, T., Dominguez, J., & Voytek, B. (2020). Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity. ENeuro, 7(6), ENEURO.0192-20.2020. https://doi.org/10.1523/ENEURO.0192-20.2020 <br /> - Donoghue, T., Schaworonkow, N., & Voytek, B. (2021). Methodological considerations for studying neural oscillations. European Journal of Neuroscience, ejn.15361. https://doi.org/10.1111/ejn.15361 

The paper also understates previous work on aperiodic activity, and the degree to which it is known to vary with age, in line 116-117 stating "there is insufficient evidence for the reported significant association between age and aperiodic signal components". This seems to ignore the large number of studies that have replicated this finding, including (some non-exhaustive examples): <br /> - Thuwal, K., Banerjee, A., & Roy, D. (2021). Aperiodic and Periodic Components of Ongoing Oscillatory Brain Dynamics Link Distinct Functional Aspects of Cognition across Adult Lifespan. Eneuro, 8(5), ENEURO.0224-21.2021. https://doi.org/10.1523/ENEURO.0224-21.2021 <br /> - Voytek, B., Kramer, M. A., Case, J., Lepage, K. Q., Tempesta, Z. R., Knight, R. T., & Gazzaley, A. (2015). Age-Related Changes in 1/f Neural Electrophysiological Noise. Journal of Neuroscience, 35(38), 13257-13265. https://doi.org/10.1523/JNEUROSCI.2332-14.2015 <br /> Perhaps this claim is supposed to more specifically reflect the age-range analyzed here, in which case recent studies examining this (in relatively large datasets) are also not mentioned here, including, for example: <br /> - Donoghue, T., Dominguez, J., & Voytek, B. (2020). Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity. ENeuro, 7(6), ENEURO.0192-20.2020. https://doi.org/10.1523/ENEURO.0192-20.2020 <br /> - Hill, A. T., Clark, G. M., Bigelow, F. J., Lum, J. A. G., & Enticott, P. G. (2022). Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood. Developmental Cognitive Neuroscience, 54, 101076. https://doi.org/10.1016/j.dcn.2022.101076 

The notes above do not undermine the utility of examining alpha oscillations in detail, but I think the specific contribution of this work could be better contextualized in terms of other existing work. In the introduction, for example, the following review is an important piece of work that could be cited when introducing aperiodic activity: <br /> - He, B. J. (2014). Scale-free brain activity: Past, present, and future. Trends in Cognitive Sciences, 18(9), 480-487. https://doi.org/10.1016/j.tics.2014.04.003 

2. Model quality control 

A limitation to the methods employed in this study is a lack of description of if and how model fit quality was evaluated. For the method of parametrizing neural power spectra that is employed, it is important to validate that models fit the data well, otherwise the estimated parameters may be unreliable. This is especially important in developmental and clinical data, as analyzed here, as this data can be quite noisy, and differences in levels of noise across ages or between clinical groups could plausibly lead to differences in model fit quality. Useful quality checks for this kind of analysis would be to report the average r-squared (or model error) for the parametrized data, and to examine whether model fit quality is significantly related to age, or clinical status. 

Note that there is also a detailed guide for how best to apply spectral parametrization to developmental datasets, including notes on quality control, that may be useful: <br /> - Ostlund, B., Donoghue, T., Anaya, B., Gunther, K. E., Karalunas, S. L., Voytek, B., & Pérez-Edgar, K. E. (2022). Spectral parameterization for studying neurodevelopment: How and why. Developmental Cognitive Neuroscience, 54, 101073. https://doi.org/10.1016/j.dcn.2022.101073 

Not reporting any quality control metrics of the model fits also deviates from the analysis of the validation dataset as described in the pre-registered analysis (https://osf.io/7uwy2), which includes the note that the plan is for data to be excluded from the analysis if there is a bad model fit (R-squared < 0.9). It is unclear from the manuscript if this was done at all - and if so, why it was not described, and if not, why this deviates from the pre-registration. Note that though examining and reporting model fit quality is important, it is unclear where the value of 0.9 in the pre-registration came from, and it is unclear if this is an appropriate threshold for these specific datasets. 

3. The analysis of the relationship between the aperiodic intercept and aperiodic exponent 

There is an analysis in this paper that attempts to evaluate whether the change in aperiodic intercept that is observed is more than expected due to the measured change in aperiodic exponent. The approach taken for this analysis is ill-posed, and the interpretations made of this analysis are not supported. The issue is that the degree to which the intercept changes due to a change in exponent depend on the rotation frequency, which is not acknowledged or addressed in the analysis employed here. 

For example, for spectra rotated at 0 Hz, there is no measured change in offset from a change in exponent, whereas for a rotation at 100 Hz, there is a large influence of exponent on the change in offset, with different degrees of impact in between. The results of this analysis are therefore heavily influenced by the rotation frequency that is used. The analysis by the authors uses a rotation frequency of 19 Hz, however, there is no justification provided for this value. It is noted as being the middle point of the analyzed range, however, this itself is unrelated to whether it is an appropriate rotation frequency (since which frequency the spectrum rotates at is unrelated to the experimenter's decision of which frequency range to analyze). 

In real data, we don't a priori know what the rotation frequency point is, and in general it need not be a single, consistent point, and between subjects, is difficult to measure. To get a sense of what it might be, anecdotally, we can see in Figure 2C that in this particular subset, the rotation point is not at 19 Hz, and appears to be at a higher frequency. If the rotation point is actually higher than 19 Hz, then the analysis employed will systematically under-estimate the impact of the measured exponent change - leading to the conclusion that intercept is changing over and above the influence of the exponent. However, this conclusion is only valid if the rotation point of 19 Hz is accurate, and we would likely arrive at a different conclusion by picking a different rotation point. This analysis, by itself, is therefore invalid. Such an analysis would require a clear motivation of having measured the correct rotation frequency to be interpretable. 

4. Flanker Analysis 

Also relating to organization (similar to point 1) it is unclear why the analysis of the Flanker task, which is alluded to in the abstract, is only mentioned in the Discussion section. Given that this appears to be a key analysis, it is unclear why it is not presented in detail in the Results. The Flanker task and analysis is also not described in much detail in the methods. An issue with the Flanker analysis only being mentioned in the Discussion, with a link to supplemental table, is that the details of the results are somewhat obfuscated from the reader. When looking at these results, two key features seem notable - the first that though it is significant effect of aperiodic-adjusted alpha power, the beta value is very small (many times smaller than the coefficients for age and gender), and second, that although it doesn't quite pass significance, the estimated beta value for the total alpha power has the same magnitude as for the individualized alpha power. Between these two features, it is not clear if the relationship between aperiodic-adjusted alpha power and the Flanker performance is of sufficient magnitude to interpret that alpha power is related to attentional performance, and it's not clear that aperiodic-adjusted alpha power is more related to attentional performance than total alpha power (since a difference in significance does not necessarily imply a significant difference in the parameters). I think this analyses, as presented, therefore does not clearly support the claim made in the abstract that alpha power is found to relate to improved attentional performance.

Reviewer #2 (Public Review):

The authors have used the recently described mouse PV infection model to study early molecular and cellular events of PV infection at the site of virus inoculation. Cellular "tags" (YFP) are used to precisely track epithelium infected with MmuPV1.

The approach was to use a genetically tagged virus construct and a transgenic mouse model that generates a reported signal (YFP) at the sites of infection.

Novel findings are presented in this study including:<br /> (i) Viability and utility of the approach allowing the tracing of the sites of primary infection and the expansion of the infected cells in an authentic papillomavirus infection model.<br /> (ii) Careful assessment to show that the expression of the transgene (YFP) is matched in cells with authentic viral activity (viral RNA).<br /> (iii) Initial identification of several host-associated factors that have been identified in MmuPV1-infected mouse tissues.

The described research and model system expands nicely the opportunities to trace virally-infected cells in vivo and to isolate virally-infected from uninfected cells in these tissues to assess their genetic and cellular changes at the single cell level.

Reviewer #3 (Public Review):

This paper introduces a novel genetic model to study lineage tracing of papillomavirus infected cells in the mouse. The model has the potential to be highly useful in study of the biology of the intimate interaction between the epithelium and the papillomavirus life cycle. This sort of model could revolutionise papillomavirus life cycle study and is particularly relevant to cutaneous human papillomavirus infections where there are no good life cycle models. The authors aim to prove that their model can accurately recapitulate the MmuPV1 life cycle and that the reconstituted virus has phenotypic effects on the infected keratinocyte.

The major strength of the study is the creation of the in vivo model to generate infectious MmuPV1. However, a weakness of the study is that the data do not go far enough to be entirely convincing at this stage. The data analysing the Cre recombinase outcomes are not sufficiently detailed or robust to allow the reader to be certain that the recombination event has been completely successful. In addition, further data on the effects of the recombination event on viral gene expression and on the infected epithelium would be required to fully support the authors conclusions.

It is very interesting that the authors find a decrease in MHC class I presentation on the surface of infected cells. However, the finding could be taken further to understand the mechanism by which MmuPV1 achieves this. This would represent a major contribution to the MmuPV1 field which may have implications for both oncogenic and non-oncogenic human papillomaviruses.

Reviewer #1 (Public Review):

In the article by Yilmaz et al., the authors generated a system that will allow researchers to both identify and track the target cells of papillomavirus infection. Importantly, their approach enables lineage tracing to be performed in an in vivo setting, which more closely mimics the conditions present and required during a natural papillomavirus infection of its host. Using the recently discovered murine papillomavirus (MmuPV1), which infects common strains of the laboratory mouse Mus musculus, the authors genetically engineered the MmuPV1 genome to contain a lox-Cre-lox sequence. As part of their approach, the authors hypothesize that application of the plasmid DNA to murine skin of Rosa26-LSL-YFP reporter mice will achieve two major outcomes: 1) the Cre recombinase self-deletes the lox-Cre-lox sequence, which subsequently allows recircularization of the MmuPV1 circular dsDNA genome and ultimately, active viral infection of keratinocytes, and 2) Cre-induced excision of the LSL sequence upstream of the YFP reporter present in the murine skin, thus 'tagging' the infected target cell and its progeny and allowing longitudinal lineage tracing of this infected population.

Strengths:<br /> 1. The MmuPV1-lox-Cre-lox virus engineered by the authors represents a significant technological advancement in the MmuPV1 infection model system that will facilitate many fundamental and exciting experimental opportunities in the future.<br /> 2. The authors provide sufficient verification of delivery and recircularization of the MmuPV1-lox-Cre-lox virus using both in vitro and in vivo.<br /> 3. The time course nature of their in vivo studies provides important insight into the infection dynamics of the MmuPV1-lox-Cre-lox infection model.

Weaknesses:<br /> 1. The authors provide strong evidence of MmuPV1-lox-Cre-lox delivery, Cre expression/loss, and genome recircularization; however, their evidence of a productive MmuPV1 viral infection as a result can be strengthened.

Overall, the authors achieved their aims and provide sufficient data to support their conclusions. In the future, this new model system will be of significant interest to those in the HPV field and will likely have a demonstrable impact on our understanding of HPV pathogenesis, transmission, and the development of HPV-associated malignancies.

Reviewer #2 (Public Review):

The authors investigate the spatial dynamics of neural oscillations of the insula during the resting-state. They first analyze the amplitude and the power of the theta and beta frequency oscillations from an impressive amount of data directly recorded from the insula of drug-resistant epileptic patients. They find the existence of spatial gradients, mostly in the anteroposterior axis, that differ across frequencies and hemispheres. Their second analysis examines the phase dynamics of these two frequency oscillation bands. They report some traveling waves of spontaneous neural oscillations in the theta and the beta bands, which are uncorrelated with each other.

Overall, the conclusions of this paper are well supported by the data and the methodology.

Strengths:

Due to its location, the insula has always been hard to study. In this manuscript, the authors have access to a unique dataset of electrodes implanted directly in the insula of epileptic patients undergoing intraEEG procedure. The number of contacts included in the analysis is remarkable.

The methodological approach is novel and well adapted for the analysis of spontaneous neural oscillations. The authors have a thorough approach where they look at the frequency signal from different angles: the spatial distribution of frequency and power, and the phase modulations.

Weaknesses:

Despite having such an extensive amount of data, some results regarding the traveling waves are too sparse and not consistent across participants to be generalizable. Some spatiotemporal information could be added to clarify the results about the clusters of neural oscillations as well as the traveling waves.

Reviewer #1 (Public Review):

In this manuscript the authors investigate the spatiotemporal dynamics of oscillations in the human insula. The authors measure human intracranial EEG data in ten patients who had stereo EEG electrodes placed in the insula. They identify two dominant low frequency oscillations: a theta and a beta rhythm. The frequency and power gradients of these oscillations along the anterior-posterior and superior-inferior axes of the insula are then delineated. They find a beta power gradient that decreases anterior to posterior in both left and right insula. They also find that theta frequency increases and power decreases from anterior to posterior in the left insula. They show examples of traveling waves in some participants and using a cross-correlation analysis, they find that time-shifts between the amplitude and traveling wave strength indicate a functional role for these oscillations in the insula. The manuscript concludes that traveling waves have an important role in intra and inter insular communication.

These data contribute in an interesting way to the ongoing understanding of oscillations in human brain regions by taking a detailed approach of identifying oscillations in one specific region, the insula. Such careful delineation contributes to our overall understanding of neural oscillations in different brain regions.

The delineation of traveling waves in the human brain is a particularly challenging problem, where many lower-level analysis issues can affect the outcome statistics. The authors did a careful assessment of many of these analysis concerns, but several questions remain that may have a major impact on the outcomes and conclusions.

1) The authors should use additional metrics to ensure that results are not driven by individual subjects. For example, the theta frequency gradient shown in the left insula in figure 2A seems to be strongly driven by two sEEG probes with a lower frequency in the anterior insula. These seem to potentially correspond to subject 3 shown in figure 4C.

2) To establish the fundamental spatiotemporal dynamics of oscillations in the human insula, the authors should include the full range of lower frequencies for their analysis. It is unclear why the 9-15 Hz range is excluded. Moreover, the peak frequency estimates in figure 1C seem to be found most often in the middle of the theta 6-9Hz and the beta 15-30Hz range. The possibility that including a certain frequency range introduces bias in the algorithm towards finding a peak in the middle of the range should be excluded.

3) An assessment for the confidence of the power and frequency gradients should be presented. The authors carefully fit a 1/f function to the power spectrum to delineate the peak frequencies in the theta and beta range, but confidence intervals for the frequency and power estimates within each electrode should additionally be calculated to ensure that temporal outliers within an electrode do not drive the results. Moreover, while the peaks in figure 1 seem quite broad in the frequency range, varying in steps of about 0.25Hz, the frequencies of the oscillation clusters seem quite detailed, reported with 0.001Hz accuracy. These differ by several orders of magnitude. Information about the confidence for the frequency and power within individual electrodes compared to the variance across electrodes will provide better intuition about the relative variability of the estimates over time and space.

4) The overall signal level can vary across electrodes, especially when they have different distances from the white matter. It should be assessed that the reported power gradients are not simply driven by the relative position of the electrodes.

Reviewer #1 (Public Review):

In this manuscript, Müller and Ermler groups report an investigation of structures and functions of the electron-confurcation complex of Ldh-EtfAB by cryo-EM. Two conformations of the complex are elucidated in this report. One is the conformation related to the D (dehydrogenase conducting) state; this structure has been analyzed directly from the cryo-EM data. Another conformation is the B (bifurcation conducting) state which was derived by Alphafold2 calculations. Functions of residues proposed to be related to electron transfers in this complex were investigated using site-directly mutagenesis or peptide truncation. As electron-confurcation and electron-bifurcation have emerged as important paradigms of cellular bioenergetics, the data reported herein pave the way for future exploration of similar electron transfer systems and lay the ground for understanding structural biology related to them.

Reviewer #2 (Public Review):

This nice description of a new structure ties observations to a reasonable mechanism. The authors point out the significance of the fact that this complex operates in the direction of confurcation rather than bifurcation, and relates it to reduction midpoint potentials. The methods are appropriate including a combination of mutagenesis, catalytic assays and cryoEM.

Reviewer #3 (Public Review):

The NAD+-dependent lactate oxidation is thermodynamically not very favorable as the redox potentials of the NADH/NAD+ and lactate/pyruvate couples are quite similar. Therefore, there is no strong thermodynamic drive in either direction. Anaerobic fermentation solves this use through electron-bifurcation. Lactate dehydrogenase forms a "three-flavin" complex with an electron transferring flavoprotein. In the first reaction step, lactate reduces the flavin of the dehydrogenase. An electron is then transferred to the so-called shuttling flavin of the electron transferring flavoprotein. In the meantime, a high/medium potential ferredoxin donates an electron to the NAD-reducing flavin of the electron transferring flavoprotein, providing the energetic drive for the reaction. After two cycles, the NAD-reducing flavin becomes fully reduced and thereby able to transfer a hydride anion to the NAD+ acceptor. This is a complicated process that requires finely tuned redox potentials, strategies to prevent unwanted side and backward reactions, and a mobile electron shuttle that exchanges electrons from one site to the other.

Experimentally, the manuscript reports on a major result as the investigated enzymes are oxygen-labile and all the experiments had to be done anaerobically. Combined with mutagenesis, the three-dimensional structure reveals several interesting features such as the presence of an iron-sulfur cluster that mediates flavin reduction the ferredoxin. Moreover, the structure leads to predictions about the conformational changes that underpin electron-shuttling during the catalytic reaction. In general, this is excellent structural work that adds considerably to our understanding of electron bifurcation, a hot topic in current enzymology.

Reviewer #2 (Public Review):

LZTR1 mediated degradation modulates the signaling output of several GTPases and has important implications for health and disease as loss of function mutations have been implicated in the genetic disorders collectively referred to RASopathies. This study employs a series of elegant and rigorous approaches, combining phylogenetic analysis and cross-species biochemical and functional analysis to define that RIT1 is the preferential GTPase binding partner of Lztr1, that this preferential interaction and mode of regulation of RIT1 emerged early in evolution, and it is the major determinant of the pathobiological function of Lztr1. The authors also systematically characterize the biological consequences of heterozygous and homozygous deletion of Lztr1. Whereas previous studies had suggested that in the context of Noonan Syndrome, a major subgroup of RASopathies, Lztr1 is happloinsufficient, the authors data strongly indicates that Lztr1 is, instead, happlosufficient. Consisted with previous studies, homozygous deletion of Lztr1 is embryonic lethal. Extending these observations, the authors link lethality to developmental vascular and cardiac defects that are prominent characteristics of Noonan Syndrome, and also demonstrate that mechanistically, the embryonic lethal phenotype is driven by Lztr1 mediated regulation of Rit1. The study has several strengths, in particular the cross-species study of this interaction and evolution of functional output in organismal development and disease states, as well as rigorous and carefully executes experimental approaches. This study is likely to be of broad interest to the RasGTPase field and those studying Rasopathies.

Reviewer #1 (Public Review): 

This manuscript seeks to clarify which Ras GTPases are regulated by the Cullin adaptor protein LZTR1. Prior work from other groups identified Ras proteins (H/K/M/N-Ras) as substrates of Lztr1, whereas prior work from the authors has identified RIT1 as the major substrate. Here the authors take an evolutionary genetic approach by comparing the function of Lztr1 in Drosophila and mice. They find that Lztr1 appears to have co-evolved closely with RIT1, but not other Ras family members. This is supported by sequence conservation through evolution, and by an apparently higher binding affinity of Lztr1 to Rit1 than to other Ras GTPases. The authors go on to show that inactivation of Lztr1 in Drosophila and mice results in increased RIT1 protein abundance, but has a minimal effect on other Ras family members. Together, these data support the author's conclusion that Rit1 is the primary substrate of Lztr1. 

A strength of this work is the genetic epistasis experiment in mice, where the authors show that deletion of Rit1 partially rescues the embryonic lethality of Lztr1 mutant mice. Another strength is the very compelling effect on Rit1 upregulation observed across multiple species and experiments upon Lztr1 inactivation. 

The conclusions of the paper are mostly well supported by the data presented. An exception to this would be the signaling data in Figure 4g, in which the difference betweeen Lztr1/Rit1 double KO and Lztr1 single KO cells is minimal at best. Quantitative assessment of these signaling differences might help strengthen this weak point. The paper would benefit from more quantitative analyses in other areas, such as the description of fly and mouse phenotypes in Figure 2 and 3. In addition, some of the conclusions overlap with results in Castel et al., Science 2019, so the findings are not totally novel, though this reviewer does not find that to be a concern. Finally, inclusion of human data would further increase the impact of the work.

Reviewer #3 (Public Review): 

The paper of Cuevas-Navarro et al. strengthens the mechanistic and physiological link between RIT1 and LZTR1. 

They first performed an in silico analysis of the similarity of the RIT1, KRAS and LZTR1 protein sequences from a number of model organisms ranging from yeast to human. While KRAS is highly conserved, both RIT1 and LZTR1 show a higher divergence in simpler organisms. The co-evolution of RIT1 and LZTR1 is further supported by qualitative interaction data (pull-downs) showing that between four species the interaction preference of LZTR1-orthologues for RIT1-, as compared to KRAS-orthologues, is conserved. 

Next, they studied the effect of LZTR1 loss of function using two knockouts in Drosophila finding that RIT1-orthologue levels are much more increased than RAS-orthologue levels relative to the parental background. These data are supported by transgenic knock-in experiments with HA-tagged RAS- and RIT1-proteins that are again increased in the LZTR1 knockout background. 

Subsequent mouse experiments produced results that conflict with previously published data by Steklov et al. The authors find here that the heterozygous deletion, does not produce a NS-like phenotype. They comment that also in human NS patients bi-allelic LZTR1 loss is found. To address this, they go on asking the important question, whether the lethal phenotype that is observed in LZTR1-/- could depend on the mouse strain background. Indeed, only in the mixed background (of C57BL/6N and 129sv mouse strains) did they obtain a few viable homozygous LZTR1-/- mice, which display typical NS-like phenotypes and show increased RIT1 levels in all major tissues. This ko phenotype is further examined in late embryos of these mice with particular attention to the cardiovascular system, finding that it is broadly perturbed (vascularization defects leading to bleeding and heart growth defects). 

The authors then performed epistasis experiments, revealing that an additional RIT1 ko can rescue the LZTR1 ko lethality. Finally, they claim that serum stimulation of MEFs isolated from the double-ko animals results in a noticeable decrease in MAPK-levels, as compared to LZTR1-/-. 

Strengths: 

The evolutionary conservation of the stronger dependency between LZTR1 and RIT1 orthologs underscores that RIT1 is a major target of LZTR1. This is in line with the fact that RIT1 is constitutively GTP-bound and therefore regulated by proteolysis. The former conclusion is supported by qualitative interaction data (Fig. 1b), differential proteomics data in LZTR1 knockout and transgenic flies (Fig. 1c-e), mouse knockout (Fig. 3g) and epistasis experiments (Fig. 4). <br /> The use of two genetic model organisms, laborious breeding schemes in mouse and the state-of-the-art quantification of major RASopathy phenotypes in mice are a major strength. 

An implicit conclusion that could be more elaborated is that genetic modifiers seem to regulate the strength of the LZTR1 and RIT1 dependency. These may explain the discrepancies in the heterozygous LZTR1 phenotypes of the mice generated here as compared to those by Steklov et al. <br /> Such modifiers are suggested by both tissue-specific RIT1 levels (Fig. 3g), as well as mouse strain specific differences in the LZTR1-mutant phenotypes (Fig. 3e). 

Weaknesses:

While manuscript and data quality are overall very high, there are some important shortcomings. 

Most importantly, the rescue of the lethal LZTR1-/- phenotype by the additional bi-allelic knockout of RIT1 (Fig. 4d), is only insufficiently documented and open to alternative interpretations. While a rescue of the heart phenotype (Fig. 4e) is qualitatively indicated, a full phenotypic quantification as done in Fig. 3 is missing, albeit the authors claim 'resulting DKO mice appeared normal, were fertile, and were absent of any detectable phenotype that resembled other NS mouse models, as assessed by size, heart weight, and cranial morphology'. 

Furthermore, it should be noted by the authors that the rescue of the lethal phenotype and the limited assessment of phenotypes overall may not allow to detect more subtle RASopathy-like manifestations. This may be particularly relevant in the double-knockout animals, where the rescue from lethality may mostly relate to the rescue of the vascularization and heart defects. 

Finally, some Western blotting data need more repeats and quantification for proper interpretation. Notably, data shown in Fig. 4g need to be substantiated and possibly reinterpreted. In all LZTR1 wt conditions, LZTR1 is induced by serum, at later times than MAPK-output (pMEK and pERK), while RIT1 levels remain constant over time. A dependency between LZTR1 and RIT1 cannot be recognized here, and a modulation of MAPK-output by RIT1 abundance is also not seen (LZTR1+/+ and LZTR1-/- samples). The levels of the canonical Ras proteins should be investigated and the suggested relation between RIT1 elevation and increased MAPK-output re-examined; this is even more relevant, as previous reports did not suggest Raf as effector of RIT1.

Reviewer #2 (Public Review):

The manuscript describes the role of Rai14 in the brain in a comprehensive manner. Authors have studied the role of Rai14 in both dissociated primary neurons and in mice. They have also studied the Rai14 interactions with other proteins or effects of altered Rai14 expression to other protein expression by methods of biochemistry. Results carried out with different methods support well each other suggesting that driven conclusions are correct. There are still many open questions with mechanistic details but these can be the topic of the next study.

Reviewer #1 (Public Review):

The manuscript by Kim et al. identifies a new role for the F-actin binding protein Rai14 in dendritic spine dynamics. The authors demonstrate both in mice and in culture that Rai14-deficient neurons have decreased dendritic spine density, which corresponds with a reduction in excitatory synapse density and the frequency of miniature excitatory postsynaptic currents (mEPSCs). They also provide convincing evidence that Rai14 is protected from degradation through an interaction with another F-actin binding protein, Tara, and that the two proteins accumulate together in dendritic spines necks when overexpressed in neurons, resulting in enhanced spine maintenance. Characterization of Rai14+/- mice revealed that mice display learning and memory deficits and depressive-like behaviors, and that they have reduced expression of a number of genes identified in major depressive disorder gene set. Finally, the authors show that chronic restraint stress results in a decrease in mRNA and protein expression of Rai14, and that treatment with the antidepressant fluoxetine can rescue depressive-like behavior and reduced spine density in Rai14+/- mice as well as prevent a reduction in Rai14 expression following chronic restraint stress in wild-type (WT) mice. Together, these results identify Rai14 as a novel regulator of dendritic spine dynamics that may play a role in stress-induced depressive-like phenotypes. While the individual conclusions made by the authors are interesting and generally supported by the data (although in some cases missing important details/analyses), the evidence connecting the various findings together to provide proof that Rai14 is involved in regulating dendritic spine dynamics associated with depressive-like behaviors (as the title suggests) is still somewhat lacking and could be further strengthened.

1. In Figure 1, the authors use Golgi staining of WT and Rai14+/- mouse brain slices as well as primary neuron cultures from WT and Rai14-/- mice and shRNA knockdown of Rai14 to demonstrate that Rai14 loss leads to a reduction in dendritic spine density in cortical and hippocampal neurons. From this data, the authors conclude that Rai14 is required to maintain a normal number of dendritic spines. However, some important details and analyses are missing in these experiments. For instance, in Figure 1A and 1B, the authors do not specify which hippocampal or cortical brain regions (or cell types) they are analyzing in the WT or Rai14+/- mice. In Figure 1C-E, the authors claim there is a reduction in mature dendritic spine density in Rai14-/- neurons compared to WT neurons, but they do not detect differences in spine length or spine head width. It would be useful if the authors could include a description of how they are defining "mature spines". The authors also claim that the reduction in spine density on Rai14-deficient neurons is due to a maintenance phenotype, rather than a formation phenotype, but they do not present evidence to differentiate between these two possibilities. Have the authors examined younger Rai14+/- mice (or Rai14-/- neurons) to determine when the spine phenotype is first detected (i.e. do spines form and then are lost, or do they fail to form correctly in the first place)? The authors attempt to address this question in Figure 3 with experiments in neurons overexpressing Rai14 and Tara, but it might also be useful to look at earlier timepoints in Rai14+/- mice and/or time-lapse imaging of Rai14-deficient neurons.

2. In Figure 3, the authors report the interesting observation that overexpressed Rai14 and Tara accumulate in the necks of dendritic spines, which requires Rai14's ankyrin repeat domains, and that spines containing overexpressed Rai14 are less likely to be eliminated than spines lacking Rai14 clusters, and that neurons overexpressing Rai14 and Tara are resistant to spine loss caused by treatment with the actin destabilizer, latruculin A. Based on these results, the authors suggest in their model (Figure 6) that Rai14 regulates dendritic spine maintenance by stabilizing F-actin in the spine neck. While this is an interesting and feasible possibility, the authors do not directly assess how Rai14 affects F-actin dynamics. They do use RFP-LifeAct in Figure 3G, but only as a neuron fill and not to monitor F-actin dynamics. To better understand how Rai14 might be regulating dendritic spine dynamics, it would be beneficial to assess actin dynamics and/or organization in Rai14-deficient neurons.

3. The authors observe both learning and memory deficits and depressive-like behaviors in Rai14+/- mice compared to WT mice. Treatment with the antidepressant fluoxetine rescues Rai14+/- mouse behavior in the forced swim test to WT levels (i.e. decreases immobility time). Likewise, fluoxetine treatment rescues dendritic spine density in the prefrontal cortex of Rai14+/- mice to a level seen in WT saline-treated mice. Moreover, chronic restraint stress causes downregulation of Rai14 mRNA and protein expression in the prefrontal cortex, which is blocked by fluoxetine treatment. From these data, the authors conclude that Rai14 is important for the remodeling of synaptic connections relevant to depressive-like behaviors (and to the cognitive deficits possibly related to the depressive-like behavior). However, the link the authors are proposing between Rai14's role in regulating spine dynamics and stress-induced depression may be a bit premature. For instance, the analyses done to determine Rai14's role in regulating dendritic spine density and behavior were done using Rai14+/- mice, where Rai14 was deleted throughout development. Thus, it is not clear whether the behavior and spine defects in Rai14+/- mice are developmental, or whether they would arise from Rai14 loss in adulthood (such as in response to chronic stress). The results with fluoxetine treatment are encouraging, but the authors do not show whether fluoxetine treatment would have similar effects on WT mice (they only treated Rai14+/- mice with fluoxetine in their experiments). Since Rai14 is downregulated in the prefrontal cortex of chronic restraint stressed mice, would stabilized Rai14 (i.e. Rai14 948-967) rescue spine loss and/or depressive-like behavior in stressed mice?

Reviewer #1 (Public Review):

The authors compare metabolic states in one surface and two cave populations of the Mexican tetra (Astyanax mexicanus). This specis has a great appeal in that the derived cave populations present traits associated with human metabolic syndrome, insulin resistance and would generally be expected to be associated with a series of fitness-challenging conditions. However, extant cave populations seem to be resilient to such metabolic state, and the authors here provide an account of metabolic states in liver, muscle and brain.

The authors are able to pinpoint convergent metabolic signatures in cave populations respect to one surface population. Specifically, sugar phosphate metabolism appears somehow convergent among the cave populations, muscle-specific ascorbic acid is also more aboundant among cave populations.

Rather than validating novel mechanistic insights into cavefish biology (e..g explaining their resilience to the poor nutrient conditions of the cave environment), this work points towards plausible associations between metabolic states in cave populations and cavefish biology.

What strikes most about this work is the laudable effor to share this important resource with the community, via the development of a Shiny app.

Reviewer #2 (Public Review):

The goal of this study is to provide a broad, untargeted study of primary metabolites and lipids of long- and short-term fasting in two A. mexicanus cave populations and one surface population. The authors have tried to identify the molecular signatures underline the low-nutrient adaptation in cave-dwelling subpopulations, and clarify the metabolic differences between morphotypes that might explain A. mexicanus longevity.

In the last few years A. mexicanus has been advanced as a model to investigate metabolic strategies for survival in harsh cave environment, which are not currently well-understood. This paper provide new insights about the evolutionary and physiological implications of these metabolic changes. The hypothesis behind this study is that A. mexicanus troglomorphic populations exhibit similarities with human obesity and diabetes mellitus, but also evolved "biological counterbalance" in order to offset the negative effects of this pathological phenotype.

Strengths:

This study provides for the first time a large, untargeted metabolomics and lipidomics study of A. mexicanus surface and cave morphs, in different tissues and feeding regimes. This study confirms that cavefish morphs have an altered sugar metabolism, and exhibit higher levels of sugars and sugar phosphates. Interesting, the opposite trend occurs for uronic acids. Additionally, the authors have also found important differences in ascorbate and glutathione (which have been demonstrated to be effective modulators of antioxidant systems), α-KGn (which has been implicated in longevity in C. elegans) nicotinamide (which is a precursor to NAD` synthesis and hence is related to oxidative metabolism). Moreover, they have also shown via ROS staining that Pachòn cavefish presents a lower level of superoxide radicals in the liver after 30 days of fasting. All these results correlate with the cavefish physiological state, and suggests that selection in cave environments favours resistance to oxidative stress. In conclusion, these findings confirm in a reasonable manner the authors' hypothesis, but at the same time raise new questions about the molecular mechanisms underlines the low-nutrient adaptation in cave-dwelling subpopulations.

This data is useful for the cavefish field, especially the availability of an interactive app.

Weaknesses:

1) The conclusions of this paper are based almost exclusively on metabolomics data. Mass spectrometry techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the metabolome. However there are still many unsolved problems related to these techniques, such as the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given feeding regime. Therefore, metabolomics study should be always validated with alternative techniques (ex. transcriptomic analysis). In this study, the lack of a rigorous validation of the data represent a major issue. Validation would also allow the authors to be less speculative.

2) The authors have performed a comparative metabolomics analysis between A. mexicanus surface and cave morphs in three different tissues and feeding regimes. The large amounts of data with a high number of variables greatly complicates the understanding of the data. This issue emerges for example in figure 2: the authors show a complex system of Venn diagrams across different morphs, tissues and feeding conditions. This figure is confusing and does not provide a clear understanding of the result.

3) Another limitation of this study is the fish age. As the authors stated, the analysis was based on juvenile, pre-sexually mature fish. This early developmental stage does not take into account age-related hormonal variations, which may have an impact on the fish metabolism and homeostasis. Therefore, further studies are needed to confirm the results across different developmental stages.

Reviewer #3 (Public Review):

In this study Medley and colleagues study the remarkable metabolic phenotypes of cave-adapted Mexican tetra - Astyanax mexicanus. Cave adapted fish populations have adapted several ways to cope with cave environments including lower metabolic rate, increased appetite, fat storage, and starvation resistance. Simultaneously though they are insulin resistant, hyperglycemic, and take in more calories. These fish also have a mutation in insulin receptor that in humans results in extremely deleterious metabolic consequences - however, cavefish do not appear to exhibit adverse effects.

To understand the adaptations that have led to these remarkable phenotypes the authors performed metabolomic profiling on two cave-adapted, and one non-cave adapted population under three different experimental conditions. Overall, the experiment is really interesting and a wealth of data are generated from an important model system. However, I did not find the presented analyses of the data to be very convincing. While there are some interesting observations made, the individual results are often presented out of the context of the whole dataset - that is, it is hard to know how "significant" or important changes in any particular metabolite are when they are presented in isolation. There are a couple of places (Fig 4 and Fig 9), where a hypothesis is tested using the 'omics' data (see specific comments below) and I think focusing on these alongside presenting the data as a resource for the community would strengthen the manuscript.

Specific comments

The comment about "genetic ancestry" on page 5 is not correct I don't think - the shared homology between tissues would be better described as the "evolutionary conserved functions of individual tissues."

The increased similarity in metabolic profiles between cave-fish compared to surface fish presented in Fig 4 is very interesting but confusing in how it is presented. I think the text and the figure could be presented in a way that is more concise.

On page 5 the authors comment that fructose and fructose phosphates tend to be upregulated in the brain, but that does seem to be the case in Figure 5?

Are any of the results in figure 5 significant?

Throughout the paper there does not seem to be multiple testing corrections?

The entire section on Obesity and Inflammation-related metabolites refers the reader to supplementary data. It would be helpful to have some display items / tables for the reader to refer to here to interpret these results.

I'm not sure Fig 8 is significant after multiple testing correction.

I think a more robust approach is needed to compare the data from different organisms to the cavefish. Perhaps correlating the metabolites or projecting them into the PCA from these conditions? It's hard to know in the Obesity and Inflammation-related metabolites what to make of the similarities and differences between humans and cave fish. The observations are indeed intriguing, but, I can't tell how different / similar they are to expectation given the handful of examples presented.

The comment about positive selection (page 10) seems a bit out of place - suggest being more circumspect, "perhaps a locus under selection."

The statistical analyses for the section on Resistance to Nutrient Deprivation are very clear and the explicit "omics" test of a hypothesis is well laid out. I wish previous analyses had taken a similar approach. However, that said I think a multiple testing correction might need to be applied in Fig 9 data.

Fig S7 is quite interesting and seems well suited to the main text!

A lot of redundant information is in the figures - they could be streamlined quite a bit. There also seems to be a too many figures, and they could potentially be combined.

The observed overlap between cavefish metabolic adaptations and those found in naked mole rats seems tenuous - certainly there are similarities and this should be pointed out, but it's hard to judge how significant / important these are.

Reviewer #2 (Public Review):

In this manuscript Nakane et al investigate the phototaxis of the rod shaped bacteria Thermosynechococcus vulcanus. This is important because most our knowledge on phototaxis bacteria originates from study on round shaped cell. More precisely, the author's firstly convincingly demonstrate a positive and a negative phototaxis in T. vulcanus, regulated by a green to blue light ratio. Secondly, the author's show the implication of SesABC proteins in the negative phototaxis regulation, via a potential modulation of the C-di-GMP level in the cell. Finally, the author's characterised the T4P-dependant motility as the output for phototactic behaviours in T. vulcanus. The author's further investigated the T4P dynamics during negative phototaxis using fluorescent beads.<br /> Overall the work present in the manuscript is well carry out and conclusions drawn from experiments are largely correct. Nevertheless, my general impression is that the proposed manuscript is at this stage premature. The present work needs further experiments to strength the actual conclusions but also to get more molecular details. Ultimately, a final working model would be beneficial to summarise the proposed molecular links from SesABC to T4P regulation.

I- The author's attribute the defect of negative phototaxis observed in the SesA mutant to the level of C-di-GMP in the cell, mainly because a SesA mutant shows a two fold decrease in C-di-GMP concentration upon blue light treatment. However, this measurement has been realised in a batch culture and normalised to dry cell mass. At the opposite, the negative phototaxis observed at single cell level occurs in a range of less than a minute (Figure 2). It would be therefore important for the author's to strength the implication of C-di-GMP in the phototaxis regulation. For example, the author's could ectopically modulate the level of C-di-GMP in the cell, via the expression of ectopic a diguanylate cyclase or phosphodiesterase enzymes, and observe its effect on phototaxis.

II- The author's used fluorescent beads to visualize T4P dynamics. As it was previously described, the author's show that it is specific of the T4P activity and it also can reveal T4P retraction. Then, the author's used this method to convincingly show that cells that move perpendicular of the light source have only active pili at one half of the both cell poles (Fig6). It is an interesting observation but again it gets short of details.<br /> -The manuscript would definitively benefit from more general analysis of T4P dynamics during phototaxis. For example, during the switch from positive to negative phototaxis. What are the behaviours (T4P pole activation) of cells parallel to the light source?<br /> -Beside, as suggested by the author's in the discussion, having the intracellular localisation of the Atpase PilB would definitively be a plus.<br /> -Moreover, in the discussion section the author proposed the existence of "a specific signalling system with high special resolution" to explain the asymmetric polar T4P activation. Why could it not be a molecular mechanism similar to the one observed in round cell such as Synechocystis, where the light receptor PixD regulates T4P function at some part of the cell according to the direction of the light.

III- The links between the C-di-GMP concentration and T4P dynamics during the switch from positive to negative phototaxis is absent. The author's proposed in the discussion a potential binding of C-di-GMP to PilB as previously shown for some T4P. Could it be tested here by the author's since they seem to be able to handle C-di-GMP?

Reviewer #1 (Public Review):

The authors use a custom optical set up to visualize individual cells and microcolonies of T. vulcanus phototaxing towards teal/green light and away from blue-green light. This directed motility is dependent on T4P. They went on to identify the photoreceptors, SesA, SesB, and SesC which are required for negative phototaxis and these photoreceptors contain c-di-GMP synthesis and degradation domains. They showed that the concentration of the second messenger c-di-GMP correlates with the direction of phototaxis, with higher levels of c-di-GMP resulting in negative phototaxis. They also observed that the rod-shaped cells moving along the incident light axis can move consistently perpendicular to their long axis during phototaxis and suggest that this observation shows a polarity regulation coined "within-a-pole" polarity regulation of the polarly localized T4P.

The conclusions of this paper are mostly supported by the data. A major strength of this study is the careful microscopy and analysis. The experiments are clearly described in the text and the results are communicated well in the figures. The kymographs and movies are striking with the results of cells phototaxing towards green light and away from green light when blue light is present. The assays with the changing wavelengths and cell velocity responses are very clear. It is convincing that T4P are required for phototaxis of T. vulcanus.

The genetic link to phototaxis showing that SesA, SesB and SesC is convincing, but some details could strengthen the link. For example, the microcolony aggregation is an interesting but confounding factor. The conclusions would be strengthened if the authors could decouple the microcolony formation from phototaxis.

The observation that the cells are able to steadily move along the light axis but perpendicular to their long axis is very interesting considering the T4P appear to be bipolarly localized. There is some discussion on the micro-optic effect in single cells but it does not include the observation that the negative phototaxis to green light occurs no matter where the direction of blue light comes from or the micro-optic effect in a microcolony.

This work nicely illustrates how observing single cells can inform macroscopic phenotypes in the lab or in natural habitats.

Reviewer #1 (Public Review):

Persistence of the viral reservoir is hampering HIV cure. This study describes a possible way that HIV-infected cells in the reservoir may escape antibody killing. The reservoir cells tend to have less availability of a receptor that binds HIV antibodies that would ordinarily help in killing. These cells are not only less susceptible to antibody killing but also seem to be susceptible to proliferation, which helps maintain the reservoir. While there are likely many aspects of HIV reservoir persistence, these studies provide evidence for one aspect.

Reviewer #2 (Public Review):

The goal of this work was to explain previous observations as to why CD4 T cells expressing CD32, a Fc gamma receptor, are enriched in HIV in both untreated and treated HIV infection. The authors suggest that i) CD32 promotes resistance to NK mediated ADCC but not cytotoxicity ii) CD32lo cells have elevated HLA-E expression which is an inhibitory NK receptor and iii) that CD32lo cells exhibit stronger proliferation in response to gp120-Ab immune complexes. Overall, the authors' conclusions are supported by data presented.

Reviewer #3 (Public Review):

This study by Astorga-Gamaza et al. investigates the role that the receptor CD32 may play in active CD32dim HIV cell reservoirs. Using primary CD4 T cells from ART-treated and virologically suppressed individuals and autologous NK cells isolated from each donor, they show that CD32dim CD4 T cells were the most resistant to ADCC, both using coated and ex vivo infected cell elimination assays, and by killing of reactivated infected cells in the reservoir. They go on to demonstrate that infected cells expressing HLA-E, and particularly HLA-E+ CD4dim cells, were more resistant to ADCC. They hypothesize this may be due to antibodies or pentraxins binding to CD32 on these cells and consequently protecting these cells from HIV-specific ADCC-mediating antibodies. Using gp120 coated cell, they observe a decrease in A32 binding to CD32 dim cells compared to CD32- cells. This is further supported by an increase in CD32dim - NK cell doublets which the authors hypothesize may be due to inefficient elimination of infected CD32dim cells due to suboptimal antibody-induced immune synapses.

This study provides important data on a potentially difficult-to-target reservoir population that needs to be considered in cure strategies. While there is debate about the role of CD32 as a marker of latent infection, there is reasonable evidence that CD32+(dim) CD4 cells contribute to the reservoir and will consequently need to be targeted in cure strategies and the authors have shown this population may be difficult to target by ADCC. The authors have given the context of CD32dim cells in the total CD4 population well. In addition, the experiments have been designed and conducted in a careful and rigorous manner. Overall, the experiments support the conclusions the authors reach.

While the autologous CD4 and NK cell system used by the authors is interesting, it is unclear how useful it is in the context of assessing the impact of CD4dim cells in an ex vivo infection model. This is because, as the authors state, there is a substantial range of NK cell function in ART suppressed individuals. This difference is particularly observed in Figure 1C, where the resistance of gp120 coated CD32dim cells to ADCC mediated by NK cells from ART-treated individuals relative to other CD4 T cell populations is substantially lower compared to other groups. Since this study focuses on the target cell population, there is some concern the differences in effector cell function from individual to individual could be a confounder.

It is also interesting to note that in some cases the differences from individual to individual in some cases is stark, leading to statistical differences between cell populations being seemingly driven by bimodal populations (e.g. proliferation in Figure 5A and B) or a subset of individuals (e.g. killing in 1H, CD4-NK conjugation in Figure 4D). Specifically in the case of 1H, it would be useful to understand more clearly NK cell function in the two apparent groups to understand if differences observed are due to NK cell differences that somehow impact targeting of CD32dim cells.

Reviewer #1 (Public Review):

This work is an important contribution to simulator-based inference, substantially improving over previous work by Fengler et al. (2021) with ideas from other modern work in likelihood-free inference (largely driven by the authors' group).

The authors provide a technique, Mixed Neural Likelihood Estimator (MNLE) to efficiently build a likelihood emulator (i.e., an approximation of the likelihood function) for simulator-based models for which typically the likelihood is unavailable. The strength of this approach is that then the emulated likelihood then can be flexibly plugged in whenever a likelihood is needed, using *any* desired inference schema and hierarchical structure at inference time. Moreover, it is important to note that unlike other likelihood-free inference approaches, this method is learning an emulator of the likelihood per trial (or per observation), i.e., there are no summary statistics involved and modulo approximation errors this method could match exact inference (unlike methods based on non-sufficient summary statistics).

Another thing to note is that, unlike previous work from the authors, this approach amortizes the training of the likelihood emulator (which needs to be done once per model), but does not amortize inference itself (i.e., the modeller still needs to run MCMC or any other inference method).

MNLE is similar in spirit to the likelihood approximation networks (LANs) proposed by Fengler et al. (2021), but arguably better in any aspect. As well-argued by this paper, both in principle and empirically, the main issue of LANs is that they use density estimation to estimate the likelihood *independently* for each parameter setting, and then train a neural network to effectively interpolate between these density estimates. Instead, MNLE uses *conditional* density estimation which trains a density network while sharing information across different parameters settings, an approach that is orders of magnitude more efficient. MNLE performs conditional estimation with mixed observations (discrete and continuous) by first learning a model of the discrete variables and then a model of the continuous variables conditioned on the discrete observations.

On top of the humongous gain in efficiency of the training (10^5 simulations required for training MNLE vs 1011 for LAN), the paper shows that MNLE perform at least as well (and often better) than LANs on a variety of quality-of-approximation and quality-of-inference metrics (e.g., error, calibration, etc.). The authors also show results with a very useful technique, simulation-based calibration (SBC; Talts et al. 2018), which should become a gold standard.

Important limitations that are worth highlighting and could perhaps be discussed a bit more explicitly in the paper are:<br /> - The current example models (drift-diffusion models) have a very low-dimensional observation structure (one binary observation + one continuous observation per trial). This limitation is not necessarily a problem as many models in cognitive neuroscience have a very low-dimensional observation structure just like the one used in this example (one discrete + one continuous variable), but it is worth mentioning.<br /> - The method works for i.i.d. data. Any additional structure/dependence (e.g., adding parameters to characterize the stimulus shown in the trial) effectively increases the dimensionality of the likelihood approximation the network needs to learn. For reference, the current examples explore models with medium-low dimensionality (4-5 dimensions). This is mentioned briefly in Section 4.4.<br /> - Related to the two points above, the study does not truly discuss nor explore issues of scalability of the method. While previous related work (by some of the authors) has shown remarkable results, such as the ability to infer posteriors up to ~30 parameters (with carefully selected and tuning of the neural architecture; Gonçalves et al., 2020), the scalability of the current approach is not analyzed here.<br /> - Also related, like any neural-network based approach, it seems there is some art (and brute search) required in selecting the hyperparameters and architecture of the network, and it's unclear how much the method can be applied out-of-the-box for different models. For example, in Section 4.5 the authors say that they started with standard hyperparameter choices, but ended up having to perform a hyperparameter search over multiple dimensions (number of hidden layers, hidden units, neural spline transforms, spline bins) to achieve the results presented in the paper. In short, while training an MNLE *given the hyperparameters* might require a small number of simulations (10^5), in practice we would need to account for the further cost of finding the correct hyperparameters for training the emulator (presumably, requiring an exploration of at least 10-100 hyperparameter setting).

Notably, all these limitations also apply to LANs, so while it is important to acknowledge these, it is also clear that MNLE is a radical improvement over the previous approach along any axis.

In short, this is a strong contribution to the field of computational methods for statistical inference in the sciences (here applied to a common class of models in cognitive neuroscience) and I expect this method and others built on top of or inspired by it will have a large impact in the field, even more so since all code has been made available by the authors.

Reviewer #2 (Public Review):

This paper describes and evaluates a novel inference algorithm for "likelihood-free" models, i.e. models whose likelihood is difficult or impossible to evaluate analytically. A paradigmatic example, in the field of cognitive neuroscience, of a likelihood-free model, is a variant of drift-diffusion models (DDM) that has collapsing boundaries. In this case, no analytical solution to the joint probability of response time and choices is available, and one has to resort to computationally-intensive numerical methods. However, this computational burden typically prevents the use of such models for quantitative data analysis. In this work, authors propose a generic method for solving efficiently such problems, with the hope of significantly broadening the family of models that can be employed in computational cognitive neuroscience. Authors called their method "Mixed Neural Likelihood Estimation" or MNLE. They compare MNLE to a similar method called "Likelihood Approximation Network" (or LAN), which was recently proposed to solve the exact same sort of problem, in a very similar manner. The main result of the work is that MNLE seems to be more efficient than LAN.

Let me first reiterate the value I see with methods such as LAN or MNLE. In brief, I believe that the field of cognitive neuroscience currently suffers from the fact that researchers perform data analyses using a very restricted class of models: namely, those models that enjoy computationally-cheap likelihoods. This is problematic because this eventually reduces the investigators' scientific creativity in many ways. In fact, some -otherwise arguably overly simplistic- models have now become standards in the field, most likely because they are the only ones that can be easily fitted to empirical data. The "vanilla" DDM is such an example. In retrospect, it is somewhat absurd that even minor modifications to this model cannot be considered in most related empirical studies. Methods such as LAN or MNLE propose elegant (and generic) solutions to this problem. This makes the authors' contribution important, timely, and hence likely to be very well received by the community.

Now, the MNLE method does not do anything more than the LAN method. In fact, its core algorithmic principles are exactly identical to LAN. Both methods start with the premise that the cumbersome stochastic model simulations that are required for deriving a model's likelihood function are essentially the same, irrespective of the empirical data. In turn, both methods approximate the model's likelihood function by training artificial neural networks (ANNs) on massive model simulations that are performed beforehand, once and for all. When fitting model parameters on a given empirical dataset, one then uses the trained ANNs to compute the likelihood function, which is orders of magnitude cheaper than simulating the model. The only difference between MNLE and LAN lies in the way the underlying ANNs are trained.

This has one main implication, which triggers the main concern I have with this paper. In my view, the value of MNLE depends upon whether it is more efficient (or more robust) than LAN. However, authors report little evidence for this. This is why I think this paper would make a significant contribution to the field, provided authors improve their comparison of MNLE and LAN methods.

Reviewer #1 (Public Review):

This is an interesting article that uses the power of drosophila to explore how organisms work with their symbionts to adapt to a changing environment. The authors show that reducing some non-essential amino acids that cannot be produced by the "symbiont" Lactobacillus can nevertheless be rescued by the presence of this bacteria. They suggest it is not through provisioning from the bacteria using genetic screens in the bacteria, they find four bacterial strains that have a reduced ability to restore the delay. They then show that the mutants have transposon insertions in r/tRNA loci and reduced rRNA levels. These mutants and a newly generated deletion allele shows similar phenotypes (although very modest (~1day change). due to imabalance. Experiments next demonstrate that colonization with Lp leads to induction of an ATF4 reporter independent of diet. But that colonization of the mutant Lp, has reduced activation during a balanced diet but not in an imbalanced diet. This was also the case for a mutant identified in the screen. Next the authors explore the role of enterocyte GCN2. They show that there are selective requirements for GNC2 depending on the diet and aa imbalance. This is very complicated. As the depletion of GCN2 by one allele does not impact GF pupation on an imbalanced diet, it does for other alleles. And they find that this activity is independent of ATF4 and 4EBP, two known members of the pathway.

Major strengths include the screen for bacterial mutants and demonstration that depletion of specific amino acids have specific dependencies (both bacterial and host). However, there is a disconnect between the bacterial mutants and the host physiology. How do the mutants impact host biology? Is it through an RNA signal? If so how does this get sensed? Is GCN2 involved, and if so by what mechanism?

Reviewer #2 (Public Review):

This manuscript investigates an intriguing observation, the data are strong, and the manuscript is clearly written. The authors very convincingly demonstrate that regions of the chromosome that encode L. plantarum tRNAs are also necessary for activation of D. melanogaster GCN2 and accelerated development in the setting of AA imbalance and that this effect on development is dependent on GCN2. They further provide transcriptomic data that broaden our understanding of the host intestinal response to L. plantarum in the setting of AA imbalance. In other host-microbe interactions such as the squid-Vibrio fischeri symbiosis, the bacterial RNA has been visualized in host cells, suggesting transport. Here, experimental data demonstrating bacterial RNA in host cells is lacking and then direct interaction of GCN2 with prokaryotic tRNAs is hypothesized but not proven. As a result, the basis of the observed effect of bacterial tRNAS remains vague. Open questions such how/if the bacterial tRNA enters the host enterocytes, whether these interact with GCN2, and whether other bacterial products are required for the response remain to be answered.

Reviewer #3 (Public Review):

The strength of this study relies on the use of a chemically well-defined diet of the host and of the identification of Lp mutants that fail to rescue the noxious effects of an imbalanced amino-acid regimen. Thus, the genetic approach in both host and symbiont is a major asset of this study. The results are surprising as an imbalance of one essential amino-acid in the diet, valine, can nevertheless be compensated by Lp, even though it is itself unable to synthesize this amino-acid. The experiments are well-conducted and conclusions are appropriate.

This study however does not identify how GCN2 promotes growth in this context. There is just a descriptive transcriptomics approach that is however not validated at the functional level (and also not by RTqPCR experiments) as it does not provide obvious leads beyond a Gene Ontology exploitation of the data. The authors propose that Lp promotes a more thorough absorption of valine, a possibility that makes sense but is not backed up by any data. Also, how Lp release sr/tRNAs is not addressed experimentally.

A minor logical flaw is the use of GCN2 pathway activation read-outs that are actually not required to mediate Lp's beneficial action.

The authors claim that GCN2 action is not mediated through ATF4 or Thor based on RNA interference experiments. However, in contrast to the GCN2 case, they have not validated the RNAi lines and tested also only one for each.

Reviewer #1 (Public Review):

In this study by Moya-Alvarado et al. the authors examine whether BDNF acting on distal axons can regulate dendritic growth in the somatodendritic compartment. They demonstrate that TrkB activated in axons is required for dendritic growth and branching and that inhibition of TrkB kinase activity in cell bodies blocks the ability of axonally-applied BDNF to promote growth. This retrograde BDNF growth pathway is PI-3kinase-, mTOR- and CREB-dependent, and increases the level of translation in cell bodies and dendrites. While there are some minor technical problems in some of the experiments, overall this is a well-performed study using compartmentalized cultures of neurons from transgenic mice, a technically difficult model. The main limitation of this manuscript lies in the fact that all of these results have already been determined in other published studies on BDNF-TrkB signaling, or NGF-TrkA signaling in peripheral neurons. Therefore, while this is the first time all of these results have been presented in a single study, from TrkB in axons all the way to the dendrites, it represents an incremental advancement rather than a significant manuscript for the field. It would have been more surprising if they had obtained opposite results, in fact.

Reviewer #2 (Public Review):

The study is based on a cutting-edge microfluidics system in combination with neurons from genetically modified animals. Overall, the results are clear, well-controlled and of high quality.

Several comments:

Fig 1/ S1 the authors should consider incorporating it into Fig1, as the data is highly important to the understating of the experimental system that is used throughout the paper.

Most of the studies in the paper are based on pharmacological inhibitors, although this is a powerful approach that allows axonal vs cell body inhibition, off-target effects of these drugs should be considered.

Reviewer #3 (Public Review):

The manuscript presents the results from compartmentalized cortical cultures to follow the retrograde transport of BDNF/TrkB from the exon terminal to regulate dendritic morphology. In addition to the in vitro experiments using microfluidic chambers, they demonstrate in vivo using a dominant-negative CREB expressed in cortical euros reduced soma size and dendritic branching, Several studies have shown in peripheral neurons that NGF induces local synthesis of CREB, which is then retrogradely transported. In these cortical neurons, it is unclear if the CREB is present in the endosome with the BDNF-TrkB, or whether it is only phosphorylated when the endosome reaches the soma. Phosphorylation may be lost if the TrkB was inactivated in the soma, even if the CREB has been previously phosphorylated in the endosome.

Reviewer #1 (Public Review):

The tools and approaches in this manuscript are of broad interest, not only to protein engineers but also to the many researchers using genome-editing reagents. However, putting the work in the context of previous research, both through changing the writing and additional experiments, will be critical for taking advantage of that widespread applicability.

Strengths:

Overall, the data support the conclusions of the manuscript.

The most exciting product of this work is an engineered nuclease, Nsp2-SmuCas9, that has high activity and specificity in human cells and a relaxed PAM preference for a single C base. This chimeric enzyme can efficiently induce indels at endogenous sites. While other works have presented nucleases with minimal PAM preferences, Nsp2-SmuCas9 is a useful alternative and may be preferred. It is also more compact than the standard SpCas9, making it appealing for gene therapy applications.

Technologically, the presented approach of screening orthologs for new specificities and making chimeras to achieve further diversity is a good way to develop new genome-editing reagents. The authors used appropriate methods, such as GUIDE-seq, to complete their goals. Extending beyond the GFP-activation assay to determine activity at endogenous targets enhanced the value of the results.

Conceptually, it was important information to the field that proteins with very high sequence identity (93%) can have divergent PAM preferences. Through their engineering, the authors clearly demonstrate the advantage of characterizing such close orthologs with diverse amino acids in the area of PAM recognition.

Weaknesses:

An overall weakness with the work is that it is not clear how the activity level of the relaxed PAM enzyme, Nsp2-SmuCas9, compares to existing enzymes. Is it much better than the SpCas9 that has almost no PAM preference (SpRY) or the NGN PAM (SpG)? How does it compare to the most commonly used SpCas9 nuclease, which is known to be active in a wide variety of biological contexts? The activity assessment at endogenous sites seemed to have a long timeline, as the indel rate was measured 5 days after transfection. Clarifying the effectiveness of this new nuclease would increase the impact of this work.

In the presentation of the manuscript, there are several weaknesses. First, while it is true that allele-specific disruption is an important application of new CRISPR proteins, there are many other reasons why they would be useful. The specific focus on this single application throughout the abstract, introduction and discussion takes away from the widespread utility of these new tools. The writing would be more compelling if it targeted a broader audience. Allele-specific targeting is also possible beyond the PAM site if the mutation is in a position with high specificity. Second, the introduction is further missing a discussion of other research engineering new PAM specificity or even completely removing specificity. A more convincing narrative would include reasoning for why characterizing naturally occurring orthologs is a powerful and important approach. This information is in the discussion, but it would be helpful for the reader if these points were in the introduction.

A second concern with the presentation and analysis of the findings is a minimal connection to the structural context of the discoveries. Many readers will likely be interested in how the specificity shifts are occurring in these orthologs, which could be remedied by supplementary figures of homology models. Along the same lines, further structural analysis of the failures would be helpful for those embarking on similar projects. Are there any differences in the sequence or structure of the 4/29 orthologs that were not functional in the GFP-activation assay compared to those that were? Similarly, it was surprising that the Nsp2-NarCas9 chimera was not active, and it would be helpful if the authors could speculate based on the differences between SmuCas9 and NarCas9, such as at the interface of the domains that were fused. Structural models of the fusions would help the reader to visualize the strategy. Exploring the failures and challenges is important for understanding the generalizability of the presented approach.

Finally, the final sequence of Nsp2-SmuCas9 fusion, as well as other enzymes such as the failed Nsp2-NarCas9, are not obvious in the manuscript. I may have missed them, but I also did not see the primers used in the Methods section. Addgene submission is also encouraged and would be of great value to the scientific community.

Reviewer #2 (Public Review):

The versatile Cas9 has enabled creative genome editing applications. The targetable sequence space is limited by the PAM specificity of the Cas9 RNP. In this manuscript, the authors made a comprehensive attempt to explore the genome editing potential of the under-explored type II-C Cas9s. A positive selection assay was set up to define the PAM specificity of twenty nine different II-C Cas9 homologs. Twenty five of them were active in genome editing in human cells. Their distinct PAM specificities can be rationalized to some extent based on the identity of the key residues in the PAM-interaction domain. The authors then focused on Nsp2Cas9 and a few others. Nsp2Cas9 can be engineered to recognize a single C PAM by replacing the PI domain with that of the SmuCas9. Impressively, the resulting chimera retained the same level of editing efficiency. A slight drawback is that the Nsp2Cas9 and its chimera derivative had highly off-targeting activity than the benchmark, the previously characterized Nme2Cas9. Overall, the experiments were expertly performed. The work expands the Cas9 toolbox by defining the PAM specificity and genome editing activity of a large group of smaller-sized type II-C Cas9s. The success in making Cas9-PI chimeras points to one effective approach to expand the targeting space of the existing Cas9s.

Reviewer #3 (Public Review):

Searches for new types of CRISPR-Cas nucleases bring back enzymes with unique properties. Characterization of closely related Cas homologues can also be useful and result in discoveries of enzymes with properties that complement those of existing editors. The large-scale characterization of Cas9 orthologs by the Siksnys group, research by the Sontheimer, Zhang, and Doudna groups, as well as work from other laboratories, resulted in characterization of Cas9 enzymes which recognize distinct PAMs and can be used to edit a wide range of genomic targets. The authors of this paper contributed to the effort of expanding the Cas9 toolbox by characterizing BlatCas9 and SauriCas9, two enzymes that may be promising for genome engineering.

The main difficulty with most Cas9 orthologs is their low activity in human cells. In the current work, the authors decided to focus on Cas9 proteins highly similar to NmeCas9, which is highly active in eukaryotes, and search for enzymes with novel PAM requirements. The authors determined PAM sequences for 29 NmeCas9 orthologs through screening experiments in human cells. Direct determination of PAM in eukaryotes makes the results highly valuable in terms of the future use of these nucleases in genome editing, as PAM sequences determined in vitro, in bacteria, and in eukaryotic cells do not fully match sometimes.

The results of this work, along with the data of Gasiunas et al., can be used for developing of structure-based Cas9 PAM prediction tools given the new opportunities of protein structure modelling with AlphaFold2.

It is important to note that the Nme1Cas9 orthologs whose activity was considered by the authors as insufficient based on their PAM screening experiment in human cells, may actually be active and efficient enzymes, but poorly produced.

Reviewer #1 (Public Review):

This is a wonderful paper from the Kamp lab describing the work to develop defined surface coatings for cardiac cell differentiation. Kamp lab developed Matrigel overlay protocol for cardiac differentiation that is now widely used and adapted by many. Recent advances in directed cardiac differentiation resulted in a number of defined cytokine protocols that significantly advanced the field and made the cells accessible to many labs. The work on defined ECM preparation was less extensive, thus this paper contributes important new knowledge. The described experiments are convincingly supporting the role of fibronectin in early cardiac mesoderm induction, in particular the siRNA knock-down studies. I only have couple of questions that can improve this paper further.

1. In addition to direct signaling through cell surface receptors, in vivo ECM can sequester and then slowly release growth factors. It is know that cardiac differentiation cultures are sensitive to endogenously secreted signals. Besides direct signaling, is it possible that Fb is particularly suitable for sequestering and release of these factors in the context of early mesoderm induction and cardiac differentiation?<br /> 2. The experiments to delineate the role of integrin beta1 and ILK signaling in mediating effects of fibronectin coating are conceptually sound and well executed. However, beta1 integrins and ILK signaling are implicated in cell survival pathways. It is well know that cardiac differentiation cultures are cell density sensitive. Is it possible that blocking of integrin beta1/ILK results in lower cell viability that translates into lower cell density, ultimately resulting in the outcome of the cardiac differentiation?

Reviewer #2 (Public Review):

This paper is clearly written and represents a significant contribution to stem cell biology as it links fibronectin (FN) accumulation to mesoderm differentiation of PSCs. The exploration of FN as necessary for pre-cardiac mesoderm formation was explored using various other ECM conditions, endogenous FN knock-out, blocking antibodies against integrin subunits, and inhibition of ILK via small molecule cdp22. In the case of the FN knock-out, experiments included rescue conditions that established a causal link between FN and the formation of precardiac mesoderm. Particularly insightful was the tracking of FN deposition over time with or without exogenously provided FN (i.e., the LN-111 case).

There were several major weaknesses in the study. First, many of the studies were conducted with a single hiPSC line. Some studies were conducted with an hESC line, but not the most critical experiments including demonstration of a lack of FN at early time points when cultured on LN-111. These two lines with all critical experiments are required at a minimum; inclusion of multiple lines of each (ESC and iPSC) is suggested.

Second, it is not surprising that blocking of beta1 integrin inhibits cardiomyocyte differentiation. Beta 1 integrin subunit is necessary for engagement of most ECM proteins and therefore downstream outcomes can in no way be linked directly to FN. An opportunity is missed to identify the heterotrimer necessary for the differentiation outcome observed. In addition, it is likely that many cells underwent anoikis in the presence of the antibody making relative quantification meaningless. Further, a rescue condition is not included.

Third, the studies with cpd22 are weak. There is no small-molecule control, no direct knockdown to avoid off-target effects of the small molecule, and no indication of whether the effect is linked to GSK3b or PI3K or both. With the identification of the critical integrin heterodimer(s) above, it would be more compelling to block these and look at downstream phosphorylation of ILK and other potential downstream signaling players.

Finally, there was a missed opportunity for a thorough investigation of the ECM present in each condition via mass spectrometry or another proteomics approach. The only ECM that was specifically probed overtime was FN and with some limited analysis of LN.

Reviewer #1 (Public Review):

This paper address the "origins and drivers of Neotropical diversity." The Neotropics have high diversity of plants and animals relative to other global regions. There are also many hotspots of global biodiversity (species richness) within the Neotropics.

This paper aggregates 150 time-calibrated phylogenies from different groups of plants and animals that occur predominantly in the Neotropics. They analyze the diversification dynamics of these clades over time primarily using the method of Morlon et al. (2011; PNAS) as implemented in RPANDA (Morlon et al. 2016). The authors find that most clades have constant rates of speciation and extinction over time.

The strength of the paper is that it aggregates many previously published phylogenies of Neotropical organisms. However, it is unclear whether the method used gives meaningful inferences about diversification dynamics over time (e.g. Burin et al. 2019; Syst. Biol.). Therefore, the overall contribution of the study is somewhat questionable.

The design of the study is also somewhat problematic. There is no comparison to other regions outside the Neotropics, so the study cannot address why the Neotropics are so diverse relative to other continental regions. Similarly, within the Neotropics, the authors do not find significant differences in diversification rates or dynamics among regions. As far as I can tell, they do not attempt to relate patterns of diversification to patterns of species richness among regions within the Neotropics (and presumably they would find no significant patterns if they did).

The authors set up their study by claiming that most previous attempts to explain Neotropical diversity relied on two evolutionary models: cradles vs. museums of diversity. The justification cited for this thinking comes mostly from papers from the last century or before. I do not think that this represents the cutting edge of modern thinking about this topic. Many researchers moved on from this dichotomy long ago.

There are potentially interesting differences in the diversification dynamics of plants and animals, but this depends on whether we can believe the inferences of the diversification dynamics or not.

Reviewer #2 (Public Review):

In this study, the authors explored the evolution dynamics of Neotropical biodiversity by analyzing a very large data set, 150 phylogenies of seed plants and tetrapods. Furthermore, they compared diversification models with environment-dependent diversification models to seek potential drivers. Lastly, they evaluated the evolutionary scenarios across biogeographic regions and taxonomic groups. They found that most of the clades were supported by the expansion model and fewer were supported by saturation and declining models. The diversity dynamics do not differ across regions but differ substantially across taxa. The data set they compared is impressive and comprehensive, and the analysis is rigorous. The results broadened our understanding of the evolutionary history of the Neotropical biodiversity which is the richest in the world. It will attract broad interest to evolutionary biologists as well as the public interested in biodiversity.

Reviewer #3 (Public Review):

This manuscript seeks to address a series of questions about lineage diversification in the Neotropics. The authors first fit a range of lineage diversification models to over 150 neotropical seed plant and tetrapod phylogenies to characterize diversification dynamics. Their work indicates that a constant diversification model was most frequently the best fit model, while time-, temperature- and Andean uplift-dependent models were far less frequently favored. The authors then attempted to determine whether distinct biogeographic clusters existed by using clade abundance patterns as a proxy for long-term diversification within regions. They found that while clades were widespread across ecoregions, regional assemblages could be binned into five clusters reflecting clade endemism. Finally, they asked whether diversification dynamics of individual lineages varied by parent clade, by environment (temperature through time, and Andean uplift) and by biogeographic region, finding that diversity trajectories best explained by environmental drivers and parent clade identity, while no significant association was detected with biogeographic region. I especially appreciated the detailed model-testing procedure, the inclusion of pulled rates, tests for phylogenetic signal in the results, and the acknowledgment of caveats. By using a massive dataset and, and a battery of cutting-edge analyses, the authors provide new insight into questions that have intrigued biologists for decades.

1. The neotropics, as defined here, extends from Tierra del Fuego to Central Florida, rather than from the Tropic of Cancer-Capricorn. I was confused by this broad circumscription, and wondered whether the findings presented here could be biased by the inclusion of these exclusively or primarily extra-tropical regions (such as "elsewhere" and "Chaco+Temperate south America") and lineages.

2. Model categories and clade diversification dynamics were also linked to the size and age of the phylogeny, such that small and young clades tended to exhibit constant diversification, while exponential and declining dynamics were linked to more diverse and older clades. As one of the main conclusions is that seed plant diversification is more frequently characterized by constant diversification (relative to that of tetrapods), I cannot help but wonder if seed plant phylogenies tend to also be younger and less diverse than those of tetrapods. Figure S1 shows distributions an overview of the distribution but lacks a formal, statistical comparison.

3. I wondered whether it was possible to disentangle time-dependent decreasing diversification from decreasing temperature in young trees? I raise this because it appears that (generally speaking) most of the clades have diversified over periods in which temperature has generally been declining.

Reviewer #1 (Public Review):

This study interrogates the important topic of seipin droplet formation, and addresses a current lack of knowledge owing to limited information on the transmembrane (TM) domains of human seipin. In this study, the seipin TM domains, which are missing from the structure of the human system, are modelled in and evaluated using atomistic simulation. The authors discover a cage-like assembly, with a very high degree of dynamics. From the presented data however, it is unclear if these dynamics are a natural part of the seipin dynamical behaviour, or are a result of limitations in the input model.

Then, using coarse-grained simulations, the authors demonstrate that this cage-like assembly, as well as conserved basic residues at the ends of the TM helices, are necessary for the initial stages of lipid droplet formation, i.e. the transition from a lens to a more bulged structure. They demonstrate that conserved basic residues are necessary for this process, which they back up with confocal imaging experiments. These findings are convincing, but rely on very coarse simulations.

Reviewer #3 (Public Review):

The paper uses atomistic molecular dynamics simulations and selected cryo-EM imaging data to develop a phenomenological coarse-grained simulation model for studies of seipin and its role in lipid droplet formation. These coarse-grained simulations are complemented with atomistic molecular dynamics simulations and cell-based experiments. The aim of the paper is to clarify the role of seipin's transmembrane helices in the clustering of triglycerides, to form a triglyceride-rich lipid phase bound to seipin, and the importance of the transmembrane helices in the initial stages of lipid droplet formation.

A major strength of the simulation approach is the coupling of atomistic simulation results and cryo-EM imaging data, which are used to develop a phenomenological coarse-grained model. In this manner, the quality of the coarse-grained model reaches a level where it is expected to have predictive power. Meanwhile, the conclusions of atomistic simulations are based on a single, quite short simulation, hence the results of this atomistic simulation reflect the initial structure used in the simulation and sampling of atomistic simulations is not fully adequate.

The value of the paper is mainly based on the view produced by the coarse-grained model of the early stages of lipid droplet formation. These results are very interesting. They emphasize the importance of the chemical details of seipin's transmembrane structure, the interactions of seipin residues with lipids, and the effect of the lipid phase formed by triglycerides on the local physical properties of the cell membrane. As a result, seipin forms a neck-like structure that is likely to favor the formation of lipid droplets.

The key goal is to understand how lipid droplets are formed under native conditions. This paper will help to address precisely this challenge, and at the same time lay the groundwork for future research to find out how the formation of lipid droplets can fail and lead to various diseases.

Reviewer #1 (Public Review):

Kim et al. demonstrated biphasic roles of ERK-MAPK-mTOR pathway in osteoblast differentiation. They first showed the administration of the MEK inhibitor trametinib increased bone formation and prevented bone loss in OVX mice. They also confirmed the effect of MEK inhibition on late phases of osteoblast differentiation in the culture of human bone marrow-derived mesenchymal stromal cells (hBMSCs). They then focused on the action of ERK-MAPK pathway on the late phase. Indeed, deletion of MEK1 and MEK2 in mature osteoblasts and osteocytes (Dmp1-cre-dKO) led to increased bone mass with augmented osteoblast function, which was also confirmed by an in vitro culture of the mutants' osteoblasts; Ocn-cre-mediated inducible deletion of MEK1 and MEK2 in mature osteoblasts resulted in the similar phenotypes. However, osteocyte apoptosis was increased in Dmp1-cre-dKO. Gene expression profile obtained by RNA-seq supported the mutants' osteoblast phenotypes. Besides osteoblast differentiation-related genes, angiogenic factors were upregulated in the mutants. Conditioned medium of the mutants' osteoblasts enhanced osteogenic potential of mouse BMSCs and in vitro capillary formation of endothelial progenitors. They further found that ERK inhibition augmented glutamine metabolism and mitochondrial function, possibly leading to enhancement of osteoblast function. Lastly, they demonstrated that mTORC2 and its downstream factor SGK1 was involved in the ERK inhibition-mediated osteoblast phenotypes. Based on these data, they propose that the ERK-mTORC2 axis, where ERK inhibits mTORC2, regulates osteoblast differentiation and angiogenesis.

Overall this study is well performed, and the manuscript is clearly written.

Reviewer #2 (Public Review):

The authors found that the unique role of Erk signaling pathway that inhibited osteoblastogenesis and bone formation at the late stage, while Erk has widely shown to be essential for bone and osteoblast development. These data are also useful for the Readers. In vivo results including OVX experiments and phenotypes of Mek1/2 cKO mice are very interesting and useful information for the bone field, probably for other fields with some interest. The idea to show the mechanism by performing in vitro-based approaches sounds potentially interesting and novel. Conversely, although the authors claim that Erk-mTOR2-SGK1 pathway plays a role in the phenomenon found in these in vivo experiments, the evidence is very weak and preliminary. More appropriate and straightforward approaches and experimental design could strengthen their conclusion. The results shown in the manuscript in this part are still phenomenological. Several important questions were not solved. In particular, the linkage between MEK-Erk and mTOR2-SGK1 with mitochondria is still elusive. The rescue experiments in the cKO mice would be appreciated. Since in vivo and in vitro experiments for the early and late stage of bone formation did not reflect their purpose very much, the authors could re-write the manuscript.

Reviewer #1 (Public Review):

Combining functional MRI with a decoder, the authors probe the neural substrate of the double drift illusion in visual cortex. Their elegant behavioural paradigm keeps the actual retinal position of the stimulus stable while inducing the illusion with a combination of smooth pursuit and visual motion. The results show that the illusory drift path can be decoded from a signal in extrastriate visual area hMT+ but not other visual areas. Importantly, this can be done in the absence of spatial attention to the stimulus location.

The particular strengths of this study lie in the elegant paradigm and the clear attentional control. The methodology of the decoder is powerful and at the same time straightforward, well explained, and well accepted in the literature. A potential weakness of the study is the lack of simultaneous eye movement recordings in the scanner. Such data could have provided further clarification of the potential underlying neural mechanism and whether differences in eye movements could contribute to the decoding of the visual illusion path. There are some controls that mitigate this.

The authors provide important evidence for a potential neural substrate in the extrastriate visual cortex for encoding the perceived spatial location of a moving stimulus. This significantly extends previous studies that showed relevant spatiotopic signals outside visual cortex. Understanding the neural substrate and the underlying neural mechanisms for encoding perceived spatiotopic location are of broad importance for our understanding of the neural basis of sensory perception.

Reviewer #2 (Public Review):

This is a very cute experiment. The authors take advantage of the "double drift illusion", which works even when tracking, implying that non-retinal signals can drive the illusion; they then show that hMT+ can decode the direction of the illusory, non-retinal motion. They perform several important controls, confirming that hMT+ responds to non-retinal motion signals rather than retinal artifacts. Having said that the manuscript in its present form needs a major rewrite and reorganization. It has clearly been written for a short note, which does not do justice to the large literature on the subject.

Reviewer #3 (Public Review):

The authors studied the neural basis of the double drift illusion, an illusion in which a Gabor drifting both horizontally within an aperture and moving vertically along a path appears to follow a diagonal trajectory, perceptually displaced off its true vertical path in the direction of the horizontal drift. The illusion is strong and its neural basis is intriguing. The authors suggest it can be used to address the locus of spatiotopic processing in the brain. They find that fMRI BOLD activity in hMT+ can be used to decode the illusory drift direction of the stimulus, even under conditions of withdrawn attention. They internally replicate this result and ensure it is not due to local motion. They interpret the finding to indicate that hMT+ contains spatiotopic information. This was a carefully designed and conducted study, and the manuscript writing and figures are clear.

Despite the care that went into the study design and control experiments, I see some potential interpretational issues, and I am uncertain about the scientific advance. My main questions are about the interpretation of the findings, the possible confound of smooth pursuit eye movements, and the relation to previous studies, including previous fMRI studies of the same illusion. I also would like to see more thorough reporting of behavior.

Major comments

1. The authors motivate the study by saying that there have been conflicting results about which brain areas are involved in spatiotopic coding, but they did not give an indication about why there might be conflicting results or why the current study is suitable to address the previous discrepancies. Is this study simply adding another observation to the existing body of literature, or does it go beyond previous studies in a critical theoretical way?

2. The authors interpret the finding of illusory drift direction encoding in hMT+ to mean that hMT+ is coding the illusory spatial position of the stimulus. But could an alternative explanation be that hMT+ is coding the illusory global motion direction, and not the spatial position per se? If this is a possible account, then the result would still indicate that an illusory motion percept is reflected in hMT+ but it would seem not to answer the question about spatiotopic coding which motivated the paper.

3. It is good that the authors sought to rule out the possibility that smooth pursuit eye movements were driving the decoding results in hMT+, but I'm not sure they have yet convincingly done so. Decoding based on the pursuit selective voxels alone was very nearly significant (p = 0.052), which was not acknowledged in the text of the paper. Furthermore, because voxels that were both pursuit and stimulus selective were excluded from the pursuit selective ROI, decoding performance in that ROI may have been underestimated.

4. A previous fMRI study of the double drift illusion (Liu et al. 2019 Current Biology) also found above chance decoding of illusory drift direction in hMT+. The authors mention this study but do not discuss it, so it was unclear to me what the advance is of the current study over that study. The main differences I see are that in the current study, 1) the observer is also moving their eyes so that the double drift stimulus is theoretically stabilized on the retina, and 2) attention is withdrawn from the stimulus. But in both studies, hMT+ contains information about the illusory drift direction even though retinotopic information is the same, so it's not clear to me that the differences between these studies lead to fundamentally different interpretations.

Reviewer #1 (Public Review):

Authors propose here a detailed analysis of tongue macrophages and notably identify two populations of murine tongue macrophages. By combining scRNAseq, genetic mouse models and microscopy, they extensively characterize these two populations.

The study is original and very seriously conducted. Data reported are convincing and fit with author interpretations.

Reviewer #2 (Public Review):

Despite its anatomical location at the entry point of the gastrointestinal tract and the airways, its constant exposure to microbes and non-microbial compounds and its important role in articulation, mastication and taste perception, the tongue remains an understudied organ. Here, the authors undertook a tour-de-force to map the immune compartment of the murine tongue. By means of single cell RNAseq, in combination with bulk RNAseq, flow cytometry and microscopy, they established an atlas of 20 immune cell populations in the murine tongue during homeostasis and during systemic inflammation. Mononuclear phagocytes represent the majority of all CD45+ tongue cell subsets. Among the terminally differentiated macrophages, the authors identified two new subsets that can be distinguished on the basis of CX3CR1 and FLOR2/LYVE1 expression. When comparing the gene expression profile of these macrophage subsets with tissue resident macrophages in other tissues, it became clear that they are distinct from Langerhans cells in skin and tongue, from alveolar macrophages in the airways, from microglia in the CNS and from red pulp macrophages in the spleen, but rather resemble interstitial macrophages such as those in the heart. They occupy distinct anatomical niches in the tongue, with FLOR2/LYVE1-expressing macrophages, which are more numerous in adults. being found in the lamina propria and throughout the tongue, while CX3CR1-expressing macrophages are restricted to the lamina propria and found enriched in proximity to nerve fibres in taste buds. Moreover, the two macrophage subsets respond differently to systemic LPS challenge. When assessing the development of the two macrophage subsets, the authors detected CX3CR1+ macrophages from E17.5, while the FLOR2/LYVE1 expressing subset only emerged after birth from a CX3CR1+FOLR2+ subset. From modelling the developmental trajectories, the authors concluded that both subsets develop from proliferating myeloid precursors in the tongues that lose proliferative capacity during terminal differentiation. In immunocompromised animals, however, such as lethally irradiated mice, adoptively transferred bone marrow precursors were found to restore both macrophage populations. Together, this is an important study with impact for those interested in the biology of the tongue in healthy and diseased conditions. It provides the basis for exploring the role of macrophages (and other immune cell types) for physiological functions of the tongue and in disease context including infection and cancer. The identification of specific markers in each macrophage subsets also opens the path towards selectively targeting them for further dissecting their relevance.

Reviewer #1 (Public Review): 

Oscillations are common in gene regulatory networks, giving cell cycles, circadian clocks etc. They are often under the influence of biological noise. By varying different topologies, the authors found that the topologies containing the repressilator with positive auto-regulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive auto-regulation enhances the robustness against noise. They further found that the parameter variability from extrinsic noise is buffered by the long period, while the stochasticity of chemical reactions from intrinsic noises is filtered by the high amplitude. This demonstrates the crucial role of the topology of the network for influencing the quality of the oscillations. These may serve as design principles applicable to many oscillatory circuits.

Reviewer #2 (Public Review): 

The manuscript by Qiao et al studies the important problem of how to achieve accurate oscillation robustly in biological networks where noise level may be high. The authors adopted a comprehensive approach and studied how different network configurations affect osciillation. This is based on enumeration of all major architectures of 2- and 3-nodes<br /> networks.

This work makes important contributions to the field, as it offers the first comprehensive survey of networks motifs capable of oscillation, with further characterization of their robustness. The authors identified core motifs of repressilator with a positive autoregulation, and activator-inhibitor oscillator. In addition, the authors have identified different mechanisms of attenuation of different sources of noises. Overall, this is an important study reporting many new results.

The current stochastic model is based on the deterministic model shown in Fig 1D. However, there are a lot of assumptions in this ODE model. These include the assumption that the substrate is in instantaneous chemical equilibrium with the protein-ligand/DNA complex, and the reaction involving one receptor and n identical simultaneously binding ligands, with the Hill coefficient phenomenologically characterizing cooperativity. However, it is not clear what the specifics are when applied to the networks studied, i.e., what reactions are assumed instantaneous equilibrium, or why the important phenomenon of slow TF and promoter binding can be ignored and why that is reasonable? Also, what are the receptors and what are the binding reactions of multiple ligands that gives to the Hill coefficient? 

The described kinetic models based on ODE approximations may not be applicable to study strong intrinsic stochasticity arising at low copy number of molecules, where the Michelis-Menton/Hill-type of ODE models are not valid. A more straightforward model would be based on mass action but more detailed reactions, without additional assumptions, from which one can write down the corresponding master equation. 

In that light, it will be helpful to write out the set of equations for the stochastic networks, which is equivalent to the set of chemical master equations, from which Gillespie simulation samples. 

There may be another issue with the stochastic model for the intrinsic noise, as the reaction system do not model some of the important stochasticity occurring in the system. To study transcriptional regulation under different molecules, the binding of transcription factor to the DNA/promoter is an important source of stochasticity, as copy numbers of that specific regulating protein TF may vary, at the same time it also regulates the production rate of another protein. This process cannot be adequately modeled only by copy number change of the regulated protein. That is, the binding and unbinding of the transcription factor to the promoter plays important roles in stochasticity when modeling the intrinsic noise of the biochemical reactions. It would be desirable to account for the process explicitly. If the authors decide not to model such stochasticities, potential caveats should be pointed out. 

In addition, protein-gene interactions often involve dimerization, that is, gene product forms a dimer, which then interact with the other gene. This dimerization may also qualitatively affect stochastic behavior of a GRN. The authors may wish to discuss all these issues. 

A potential drawback of the study is that the oscillation behavior hinges upon the behavior of the ODE deterministic model. It is well known even for simple networks such as transcription regulation without feedback, or when protein binding is involved there can be significant divergency between ODE model and stochastic model, where the latter exhibit multistabilities and the former none (e.g., doi.org/10.1063/1.3625958,doi.org/10.1103/PhysRevE.91.042111,doi.org/10.1063/1.5124823). There is now an increasing body of literature documenting this. This issue and potential ramifications should be discussed. 

As an example, there is a new mechanism of stochastic oscillation found in toggle switch under weak promoter binding condition. This is not obvious from the corresponding ODE model and requires computation of the global map of discrete flux (doi.org/10.1063/1.5124823). It will be missed if protein-DNA binding is not modeled explicitly. It will be interesting if the authors can discuss the relationship of this type of oscillation with those based on repressilator/autoregulation and activator-inhibitor. Do they belong to perhaps different class of stochastic oscillations and if so, what are the differences? 

The authors decided to use Chemical Langevin Equation to model the stochastic process due to computational cost. However, recent development shows that computing cost may no longer be an issue, as the finite buffer ACME algorithm can generate full probability surfaces without running costly trajectories (doi: 10.1073/pnas.1001455107, doi: 10.1137/15M1034180 ). In fact, this has been done for 3-node networks (feedforward loops), where extensive parameter sweeps enables construction of 10^4 probability landscape, from which phase diagrams of multimodality can be constructed (doi.org/10.3389/fgene.2021.645640). I understand that the authors choose to use the Langevin model, but the probability surface governed by the chemical master equation can now be computed rather rapidly, without resorting time-consuming Gillespie simulations. Therefore, the rationale of high computing cost may not be justifiable. This advancement should be pointed out. 

For the reason that there are many differences between master equation model, Langevin model, and ODE model, the statement on p.8 "the system responds to the noise is usually linked to the deterministic features" should be modified/qualified.

Joint Public Review:

This is a well written paper that addresses an area of broad interest to researchers studying metabolism, development, and epigenetics. Strengths of this manuscript include the generation of a new mouse model that appears to recapitulate features of a human genetic disorder. The authors also employ a diverse array of approaches including single cell RNA sequencing, bioinformatic analyses, and whole genome bisulfite sequencing to propose a mechanism underlying their findings. Weaknesses of the manuscript include incomplete metabolic phenotyping of the mouse models and an over-reliance on correlative findings related to their transcriptomic and genomic studies. Addressing these limitations is necessary to provide further confidence that the findings here justify the conclusions made.

Reviewer #1 (Public Review): 

This article examines how individual cell properties govern the mechanics of spheroids of muscle precursor cells. For this, the authors develop an automated approach that allows to measure the surface tension and elasticity of mm sized aggregates. Through drug treatments and genetic manipulations, they then attempt to link change in single cell mechanics to changes in aggregate mechanics. They suggest that desmin aggregation leads to an increase in surface tension and elasticity. Understanding the relationship between tissue mechanics, single cell mechanics, and cytoskeletal organisation is a topical subject and the role of intermediate filaments remains less well explored. Most of the results are confirmatory but the role of desmins is novel.

Reviewer #2 (Public Review): 

In their study, Nagle and colleagues aim at understanding what molecular determinants would set the rheological properties of multicellular assemblies. To this end, they used magnetic flattening of spheroids, a technique the group masters (Mazuel, Phys Rev Lett, 2015), which has the double advantage of probing the physical properties of spheroids while retaining the capability to retrieve the sample to perform additional experiments. They coupled magnetic flattening with staining of cryosections of spheroids, which allowed them to investigate how rheological properties can emerge from molecular characteristics. In particular, they set out to investigate the role of an important intermediate filament, desmin. 

I find that the coupling of imaging techniques with rheological measurements is very interesting, and allows the authors, with clever drug treatments, to partly disentangle the various key cellular parameters that are known to define the rheological properties of spheroids (effective adhesion or cortical tension). I also found the results with desmin appealing: linking intermediate filaments to rheological properties will allow the community to also explore their role in these emerging parameters. 

That said, there are a number of unclear experimental procedures that limit the extent of the authors' claims. In particular, two key points lack detail: (i) the determination of the angle between cells, which is of utmost importance to disentangle effective adhesion from cortical tension, and (ii) the role of heat shock on the control and in general on the aforementioned parameters to understand how desmin could impact the rheological properties. 

If these points are clarified, I am convinced that this study will shed new light onto the determinants of rheological properties, as well as provide new insights on the role of intermediate filaments like desmin, and how some mutations can lead to some pathologies.

Reviewer #3 (Public Review): 

This study demonstrates that the formation of desmin aggregates results in an increased surface tension and increased Young's modulus of C2C12 myoblast spheroids. This result is in line with data from single cell measurements and muscle tissues reported by other groups.

Reviewer #1 (Public Review): 

In this study, Haiwei Zhang and colleagues test the effects of cell type-specific deletion of the transcriptional repressor REST on Kv7.4 ion channel activity in the cochlea and hearing. To achieve cell type-specific deletion of Rest (Rest cKO), they intercrossed two previously generated mouse lines: one that is homozygous for a floxed allele of Rest, and another that is hemizygous for a Cre-encoding transgene (i.e., Tg(Atoh1-Cre)). This transgene is expressed mainly (but not exclusively) in hair cells (HCs) and spiral ganglion neurons (SGNs) in the inner ear. The generated Rest cKO mice were used for a variety of tests, i.e., hearing tests, histological analysis of the cochlea, qRT-PCR tests, and electrophysiological tests. Based on these tests and analyses, the authors conclude that REST-dependent 'moderation' of Kv7.4 expression is critical in HCs and SGNs for hearing. This conclusion is interesting because it is the ~inverse of what is currently known about REST and Kv7.4. Specifically, alternative splicing-dependent suppression of REST activity is known to be important in HCs for hearing, and loss-of-function mutations (but not gain-of-function mutations) in the Kv7.4-encoding gene have been shown to cause hearing loss. The weaknesses of the manuscript are related to the experimental design of the analysis of cochlear REST expression, the Tg(Atoh1-Cre) expression pattern, the Kv7.4-unrelated effects of fasudil (which was used to activate Kv7.4 in vivo), and the lack of genetic evidence for the proposed hearing loss-causing effect of abnormally high Kv7.4 expression.

Reviewer #2 (Public Review): 

Zhang and colleagues show that the repressor element 1 silencing transcription factor (REST) regulates the expression of Kv7 potassium channels in the inner ear. REST knockout mice have elevated hearing thresholds and altered mechanics as probed by ABR and DPOAE thresholds. The authors combine patch-clamp recordings with pharmacological manipulation of Kv7 channels, single-cell RT-PCR, and immunohistochemistry to convincingly attribute the functional changes in auditory thresholds to an upregulation of Kv7.4 channels and Kv7 mediated potassium currents in both hair cells and auditory neurons in REST knockout animals. The data are clearly presented. 

By the third post-natal month, hair cells and SGN deteriorated in REST knockouts. The authors argue that this deterioration and a resulting progressive increase in thresholds is due to Kv7 upregulation. Since REST knockouts may influence more than Kv7 channels, I found this argument to be less convincing.

Reviewer #3 (Public Review): 

Genetic forms of deafness are a major health challenge. The causal genes for at least 140 isolated (non-syndromic) and 400 syndromic forms have already been uncovered. The study by Haiwei Zhang et al. deciphers the cochlear roles of Repressor element 1-silencing transcription factor (REST), a gene involved in the DFNA27 dominant form of deafness. The authors showed that the conditional inactivation of the Rest encoding gene in the cochlea and auditory nerve led to progressive deafness in mice. Rest, as a repressor element, has been shown to regulate the expression level of many neuronal genes. The authors could show that the inactivation of Rest upregulates the expression of Kv7.4, a channel protein encoded by Kcnq4 and involved in another genetic form of deafness. As a consequence, the function of sensory cells and the excitability of primary sensory neurons of the auditory nerve are impaired. The authors could further link Kv7.4 upregulation and the associated functional deficits in Rest conditional knock-out mice by showing that, on one hand, application of the Kv7.4 channel blocker XE991, rescued the auditory phenotype in Rest conditional knock-out mice, and on the other hand, application of the Kv7.4 activator fasudil, replicated in wild-type mice the hearing impairment observed in Rest conditional knock-out mice. 

The authors have convincingly demonstrated the relationship between Rest cochlear inactivation and the upregulation of Kv7.4 leading to progressive hearing loss using a genetic model and also pharmacological experiments. These findings are important in the field of auditory research for several reasons. This study elucidates another pathophysiological mechanism of deafness. In addition, it shows how genes involved in different forms of deafness may interact together and how their associated deafness may be in fact linked in some patients. The pharmacological study may give new hints for pharmacological regulation of Kv7.4 activity in patients. Finally, a major challenge in the upcoming years will be the development of gene therapies implying a fine dissection of gene regulatory networks to rescue defective genes in specific cell types. The study of Rest in the cochlea provides new insight into the genes regulating the expression of other key genes for cochlear function. I have no major concerns. The study has generally been well designed and conducted.

Reviewer #1 (Public Review):

Monitoring protein-protein interactions dynamically at the single-molecule level in live cells is of great importance for understanding various molecular mechanisms. Several approaches, including two-color single-particle tracking (SPT), smFRET, BiFC, and fluorescence cross-correlation spectroscopy (FCCS) have been developed for measuring protein-protein interactions in the living cell. In this work, the authors took a clever use of photoactivation properties of rhodamine dyes and developed a new approach to spotlight protein-protein interactions in live cells. The detected signal is based on proximity-assisted photoactivation (PAPA), in which excitation of a "sender" fluorophore (e.g., JF549) reactivates a nearby "receiver" fluorophore (e.g., JFX650) from a dark state. The work is very well done in terms of inspiration by accidental observations, experimental design and data analysis for method validation, as well as proof of concept applications.

Reviewer #2 (Public Review):

Assessing protein-protein interactions in live cells and in particular measuring dynamic properties of complexed proteins over a background of isolated proteins is challenging. Graham et al. demonstrate that a rhodamine dye in a dark state can be photoactivated by exciting another, low-wavelength fluorophore if this is nearby. The authors characterize this photoactivation process, which they call PAPA, in terms of distance dependence and find the process occurs over larger distances than FRET. Moreover, they demonstrate that PAPA enables detecting inducible dimerization and measuring distinct diffusion dynamics of slow and fast diffusing molecular species in single-molecule experiments. While reporting several highly useful applications of PAPA, the authors only provide limited insight into the physical nature of the photoactivation process. Moreover, they do not compare PAPA with previously published methods able to yield similar single-molecule insight into protein-protein interactions. Yet, the experiments are rigorously performed, outcomes critically tested and procedures comprehensively described. Thus, the application of the new method by other researchers should be straightforward and promises to yield hitherto inaccessible mechanistic insight.

Reviewer #3 (Public Review):

This is work by an internationally recognized group with strong expertise in sophisticated single-molecule microscopy assays in cells. They present here a single-molecule fluorescence-based assay for proximity in the nanometer range.

It has long been reported that cyanine dyes such as Cy3, Cy5 and derivatives such as AF555, AF647 can undergo a photoswitching mechanism by which the shorter wavelength dye when being excited can switch the longer wavelength dye which is in a dark state back into the bright state. And it has furthermore been reported that this switching mechanism is not based on FRET, as the distance requirement is more stringent (up to ~ 2 nm). However, this mechanism has not been fully explored for the investigation of molecular interactions yet.

The authors in the present work present a similar mechanism for a different class of rhodamine-based fluorophores, specifically JF549 and JFX650. They describe the discovery of this mechanism in dual-color labeling of a pentameric protein and initial characterization to distinguish it from UV-light-mediated recovery from a pumped dark state as reported for (d)STORM-like measurements. They extend their observation to TMR, JF529 as lower wavelength "senders" and JF646 and JFX646 as longer wavelength "receivers" that can become reactivated into the ground state upon illumination of a nearby "sender". The authors then test activation pulse length and distance dependence and find that longer pulses lead to more recovery and that PAPA of JF549/JFX650 has unlike previously observed for the Cy3/Cy5 pair a smaller distance dependence than FRET of the same fluorophore pair. The authors then move on to use both the UV-light mediated direct reactivation "DR" and proximity-assisted photoactivation "PAPA" to activate different molecules that are either double-labeled for PAPA or singly labeled with JFX650 for DR. They succeeded in four different cases to identify clear population shifts to distinguish molecules of different mobility.

Overall, I think the authors made an interesting discovery and characterizing this previously poorly characterised interaction for cellular single-molecule experiments is certainly an important effort. The authors make an honest and quite complete effort to work out the practical details of this interaction and designed experiments that convincingly highlight the basic capabilities this technique offers to the detection of verified interactions and the mobility of interacting molecules in cells.

The weakness is that these capabilities do not seem to be as clear-cut as the reviewer hoped for when starting to read this manuscript. It remains unclear to this reviewer, to what extant PAPA molecules can be separated from DR molecules. In all but the last diffusion experiment(s) in Figure 4, PAPA molecules seem to be significantly perturbed by DR molecules, casting doubt on the usefulness in real experiments. Similarly, in Figure 5, a difference is seen but does not allow for quantification. This certainly is not the case for other methods of sensing as well, but maybe the authors could more specifically compare their efforts and the dynamic range to other sensors for example in Figure 5? This would make it easier for the reader to make up their mind if the assay is worthwhile adopting for their system.

Reviewer #1 (Public Review):

In this manuscript, the authors use a budding yeast cell lysate-based reconstitution system to investigate the movement of intact kinetochore particles along microtubules polymerized from yeast tubulin. Using TIRF microscopy, the authors directly observe kinetochore particles moving along microtubules toward the plus ends. After arriving to the tips, the microtubules typically undergo depolymerization, and the authors report the majority of kinetochore particles track along with the depolymerizing ends. The authors go on to determine that the plus-end activity driving the initial movement is due to the kinesin-8 motor Kip3, and the activity is unique to this plus-end motor. They also demonstrate that Kip3's motor activity, but not its tail domain, which promotes microtubule depolymerization, is necessary for processive plus end-directed kinetochore particle movement. To my knowledge, this is the first direct observation of single kinetochore particles undergoing lateral-to-end on conversion in a reconstituted in vitro system. In addition, the authors use their lysate-based approach to characterize a new role for the budding yeast kinesin-8 Kip3 in powering lateral kinetochore movement along microtubules.

Reviewer #2 (Public Review):

The authors present microscopy data from observations of cell free yeast extracts demonstrating that kinetochores stably bind and translocate along the lattice of dynamic microtubules. This system is used to identify the process by which kinetochores convert from lateral association with microtubules to end-on attachment, a process that is difficult to study in vivo. Kinetochores in these experiments are labeled for imaging via fluorescent protein tags on endogenous kinetochore proteins. This provides the advantage of maintaining the endogenous stoichiometry of kinetochore proteins and their regulators in the in vitro imaging experiments. TIRF imaging of extracts from yeast with two different kinetochore complexes labeled, as well as correlative light and cryo-electron tomography experiments convincingly demonstrate that the kinetochores studied in this system are intact and contain all major subcomplexes. The directional movement of kinetochores described in this study has not been previously observed in vitro and could be an important mechanism contributing to the end-on attachment of kinetochores in vivo. Using extracts from yeast strains containing null mutations in the five kinesin genes found in budding yeast, the authors show that the directional movement depends, in large part, on the kinesin-8 Kip3. Studies of a Kip3 mutant deficient in promoting microtubule depolymerization suggest that this activity of Kip3 is also required for efficient end-on attachments. The authors provide an explanation for how these effects of Kip3 on kinetochores in the cell free extract could explain the unclustered kinetochore phenotype observed in Kip3 mutant mitotic cells, which has been a point of confusion in the field. The presented data highlight a potential new role for Kip3 in promoting end-on kinetochore attachments that could be relevant to understanding kinetochore microtubule attachment defects caused by loss of kinesin-8 function in other organisms, including Drosophila and mammals. Furthermore, the establishment of the cell free yeast extract system for mechanistic studies of kinetochore function is an important contribution.

Reviewer #3 (Public Review):

The authors use a yeast extract system coupled with in-vitro imaging by TIRF microscopy, to study encounters between kinetochores and microtubules in metaphase-arrested yeast extracts. Using fluorescent labels on different subunits spanning the kinetochore, they observe lateral binding to microtubules, while a sizeable fraction of kinetochores displays plus-end directed movement. Upon reaching the plus-end kinetochores remain attached to depolymerizing microtubules. Dual color labeling and Cryo-ET suggest that entire kinetochrores are observed in this situation. In extracts lacking the kinesin-8 Kip3, plus-end directed movement is almost entirely absent, while addition of Kip3 containing extracts restores plus-end movement.

Taken together, the development of an assay system to study kinetochore motility outside the context of a cell is an important step forward. The paper combines yeast extracts and the ability to use mutants and cell cycle arrests in an elegant manner and contains some interesting observations.

There are some limitations of the study: The Kip3 deletion phenotype suggests that this motor only has a relatively modest contribution to end-on attachment and bi-orientation in cells. The molecular basis for Kip3 dependent movement of kinetochores in the extract remains somewhat unclear. There are some further conceptual limitations to the extracts used. For example, while there are nuclear and cytoplasmic fractions of Kip3 in yeast cells, in the whole cell extracts used here this compartmentalization of the cell is lost which can complicate the interpretation of results obtained in this system.

Joint Public Review:

Fernandes et al. ask the question: "What are the evolutionary constraints on genomic sequence that encode two different proteins?" To this end, they compare the functional constraints on mutations in HIV Rev and Env, which are encoded in different reading frames from the same region of the viral genome. Interestingly, residues that are functionally constrained in one protein are, for the most part, not as constrained in the other. The elegance of this solution is attractive and will be of interest to the protein evolution and structure communities.

To address their questions, the authors (1) examined amino acid conservation in patient HIV sequences for both proteins, (2) performed deep mutational scanning of HIV Env to compare to published data on Rev, and (3) dissected the functional impact of key mutations for both proteins. This approach leads them to propose a model in which functionally important residues in one protein do not overlap with functionally important residues in the other protein.

While this approach and data generally support this model, there are two residues in Env (Y768 and L771) that are conserved, relatively mutationally intolerant, and overlap with functionally important residues in Rev. Because these residues are not found on the charged Env helical face, they are not considered critical residues in the proposed model. However, the authors should discuss the possibility that other constraints on protein evolution, such as stability and folding, could also affect their definition of 'critical'. On balance, however, their interpretations are reasonable.

Based on these experiments, it is concluded that part of each helix is mutable, while encoding important functional "constrained" residues in the other helix. The study is well done and the data of good quality and convincing. The conclusions are justified and of potential importance for future therapeutic strategies. These studies could facilitate the interpretation of genome evolution in other viruses, such as SARS-CoV-2, that encode open-readingframe overlaps. However, some parts of the manuscript need clarification and potential extension.

1) To measure the relative conservation of Env and Rev, the authors downloaded curated alignments of the Los Alamos Database. Information should be provided as to how many sequences were compared and whether this included viruses from all the different subtypes. This reviewer assumes they only looked at HIV 1 group M, but this needs to be clarified.

2) In the Rev reporter assays, the authors employ pCMV-GagPol-RRE, which contains an RRE from the pNL4-3 "lab" virus. Recent studies have shown that different Rev/RRE combinations can have different activities. The authors should discuss this information and its relevance to their findings.

Reviewer #1 (Public Review): 

This paper describes the characterization of fission yeast Rtf2 protein, which was previously shown to work on stalling of DNA replication forks at a fork barrier sequence, RTS1 in the yeast. By using a novel technique called Polymerase usage sequencing (Pu-seq), the authors confirmed the role of Rtf2 in the fork stalling at the RTS1 site (by looking at a change of DNA polymerase usage at the site). To elucidate the role of Rtf2 in the DNA replication fork stalling, the authors identified proteins that interact with Rtf2 protein and identified proteins involved in mRNA splicing. Indeed, cDNA sequencing revealed a defect in intron removal in some mRNAs in the rtf2 mutant. Interestingly, among RNAs affected in the absence of Rtf2, the authors found the Rtf1 RNA as a target for Rtf2 splicing. Indeed, the removal of the second intron of Rtf2 RNA is defective in the rtf2 mutant. Finally, the authors showed that an intronless Rtf1 gene suppressed the defect in the rtf2 mutant in the fork stalling. 

The experiments in the paper have been carried out in good quality and most of the data are convincing. The paper revealed the unique role of Rtf2 in the splicing of Rtf1 RNA.

Reviewer #2 (Public Review): 

Human RTF2 is a protein whose degradation from stalled forks is necessary to promote replication restart and maintain genome stability. The S. pombe homologue Rtf2 has been previously described as a factor that binds to the replication fork barrier (RFB) RTS1 to reinforce its barrier activity and limit replication restart. In this work, the authors have conducted a careful analysis of the function of Rtf2 in regulating the activity of the RFB. First, the authors have confirmed that the deletion of rtf2 reduces the RFB activity and leads to a less frequent replication restart using genetics and genomic assays. Then, they have established that Rtf2 does not regulate the activity of the RFB by direct binding to part A of the RTS1 sequence. To understand further the mechanism by which Rtf2 regulates the activity of the RFB, proteomics approaches were performed to reveal that most of the Rtf2 partners are related to mRNA processing and splicing. Then, the authors have identified that the absence of Rtf2 leads to the accumulation of mis-spliced rtf1 mRNA that encodes the Rtf1 protein that binds the RTS1 sequence to ensure replication fork arrest at the RFB. In a final demonstration, it is shown that when an intron-free Rtf1 form is expressed, Rtf2 is no longer necessary to regulate the activity of the RFB. Overall, the authors have conducted a remarkable work to disentangle the function of Rtf2 in regulating the activity of the RFB and establish that Rtf2 is a factor necessary for the correct splicing of Rtf1, thus regulating indirectly the activity of the RFB. 

This is a well-conducted study with robust conclusions based on solid data. The article is well written and the rationale of the work is logical and easy to follow. There is no major weakness.

Reviewer #3 (Public Review): 

Fission yeast RTS1 barrier activity is partially dependent on Rtf2 protein and human RTF2 was recently implicated in impeding fork restart, however, the exact role of Rtf2 at the stalled fork in fission yeast is not well understood. In this manuscript, the authors used a sophisticated system to control fork stalling, combined with the high-resolution Pu-seq to probe fork dynamics, they examined the detailed function of Rtf2 in fission yeast and confirmed that Rtf2 deletion reduces replication fork restart at RTS1. To further dissect the mechanism of Rtf2's function, surprisingly, they identified Rtf2 to be physically associated with mRNA processing and splicing factors and rtf2 deletion to cause increased intron retention. Indeed, they demonstrated that the presence of Rtf2 is essential for the correct splicing of Rtf1 to allow efficient barrier activity at RTS1, which is complemented by an intronless Rtf1 in the absence of Rtf2. 

The conclusions of this paper are mostly well supported by data, but additional discussions and some clarification of data analysis are needed. 

1. The authors identified Rtf2 as physically associating with general splicing factors, thus having a broader impact on splicing overall as shown in Fig 3A & 3B. Rtf1 is one of the many targets affected by intron retention, which was further characterized by reduced GC richness at the branch point and 3' SS as in Fig S3C. Please clarify the GC richness on Rtf1 introns affected for clarity. It is understandable that in a designed fork barrier model, the impact of Rtf1 stands out. It remains to be clarified if other mis-spliced genes may function in other biological processes, maybe explaining why they need to be finetuned by Rtf2, a short discussion on this will suffice, as well as some discussion about the functional divergence between yeast, plant and human Rtf2 homologs. 

2. The authors used the Pu-seq method in the RTS1 system to track non-canonical RDR forks. One caveat is that RTS1 is an artificially constructed system, whether impeded replication forks work in the same pattern in the whole genome needs to be discussed. 

3. A ChIP assay for Rtf1 at RTS1 (region B) between rtf2+ and rtf2∆ will help further prove the claimed impact of intron retention of Rtf1 at RTS1 barrier activity. If ChIP is not possible due to a lack of appropriate antibodies, it is ok to speculate but still needs to be made clear in the text.

Reviewer #1 (Public Review): 

Nandan et al. attempt to demonstrate how a phenomenology in the molecular signaling network inside a cell could translate to changes in the behavior of the cell and its ability to respond/adapt to changes in the environment over time and space. While this investigation is performed in the context of mammalian cells, the result holds significance for eukaryotic cells at large and demonstrates a mechanism by which cells may use transient memory states to respond robustly to complex environmental cues. To study such mechanisms, it is important to show how the cell may encode such transient memory, how this memory is generated from environmental cues, how it translates to cellular motion, and how it enables cells to have persistent directional motion in the case of transient disruptions in the signal while responding to significant and long-lasting disruptions. The authors attempt to answer all of these questions. 

Strengths: 

The manuscript attempts to combine mathematical theory, mechano-chemical models, numerical simulations, and experimental evidence. Thus, the investigation spans diverse methods and spatio-temporal scales (from receptors to continuum mechanical models to whole-cell motion) to answer a unified question. The mathematical theory of dynamic states and bifurcation theory provides the basis for the generation of "ghost" states that can encode transient memory; the mechano-chemical models show how such dynamical states can be realized in the EGFR signaling network; the numerical simulations show both how cells can respond to environmental cues by generating polarised states, and by navigating complex environmental cues, and experiments provide evidence that this may be the case for epithelial cells in the presence of growth factors. The manuscript is well-structured with the main conclusions clearly identified and separated from each other in the different sections. The theoretical investigation is thorough and the main text provides an intuition as to what the authors are trying to convey, while the Methods reveal the calculations performed and the approximations made. The modeling and numerical simulations are detailed and provide a baseline expectation for the system in different parameter regimes. The experiments and the analysis extensively characterize the system. I commend the authors for having delved into so many methods to answer this problem, and the authors demonstrate significant knowledge of the different methods with many novel contributions. 

Weaknesses: 

The key weakness of the results is in establishing clear distinctions between what would be expected (naively and based on results from other groups) from alternate explanations, and what is realized in the experimental results that support the hypothesis put forward by the authors. For example, the authors quote a relatively long time scale of persistence of polarisation, but it is unclear if this is longer than is expected from slow dephosphorylation to provide evidence for the existence of the "ghost" state from the saddle-node bifurcation. Further, key experimental results regarding the persistence of motion following gradient washout seem to differ from the authors' own predictions from simulations. 

There are several other models that attempt to describe eukaryotic chemotactic motion that persists despite brief disruptions and is able to adapt to changes in the environment over longer timescales. In my opinion, the main strength of the paper does not lie in providing another such model, but in providing a mechanistic understanding that bridges several scales. However, this places the burden on the authors to justify the link between the different scales. 

This is an ambitious manuscript and the authors are clearly very bold for attempting such a comprehensive treatment of such a complex system. The authors provide an excellent framework to understand mammalian cellular chemotaxis on multiple scales and attempt to justify the framework using several experiments and extensive analysis. However, they require further analysis and characterization to demonstrate that their experimental results provide the necessary justification for their conclusions as opposed to alternate possibilities.

Reviewer #2 (Public Review): 

Nandan, Das et al. set out to study the mechanism by which single cells are able to follow extracellular signals in variable environments generate persistent directional migration in the presence of changing chemoattractant fields. Importantly, cells are able to (1) maintain the orientation acquired during the initial signal despite disruptions or noise while still (2) adapting migrational direction in response to newly-encountered signals. Previous models have accounted for either of these properties, but not both simultaneously. To reconcile these observations, this work proposes an underlying mechanism in which cells utilize a form of working memory. 

The authors present a dynamical systems framework in which the presence of dynamical 'ghosts' in an underlying signaling network allow the cell to retain a memory of previously encountered signals. These are generated as follows: a pitchfork bifurcation confers a symmetry-breaking transition from a non-polarised to polarised signaling state/ direction-oriented cell shape. After a subsequent saddle-node bifurcation, a 'ghost' of the stable attractor emerges. This 'ghost' state is metastable, however, which is what allows cells to integrate new signals as well as to adapt their direction of migration. 

The authors demonstrate these dynamics in the Epidermal Growth Factor Receptor (EGFR) signaling network. This pathway is central in many embryonic and adult processes conserved in most animal groups, making it an ideal choice to characterise a phenomenon observed in such a diverse range of cells. The authors couple a mechanical model of the cell with the biochemical signaling model for EGFR, which nicely allows them to thoroughly simulate cellular deformations that they predict will occur during polarization and motility. 

Key features of the model are well-supported by empirical data from experiments: (1) quantitative live-cell imaging of polarised EGFR signaling shows the existence of a distinct polarised 'ghost' state after removal of extracellular signals and (2) motility experiments confirm the manifestation of this memory in allowing for persistent cell migration upon loss of a signal. In an extension of the latter experiment, the authors also show that cells displaying this working memory are still able to respond to changes in the chemoattractant field as necessary. 

The experiments using Lapatinib to disrupt the EGFR dynamics are less convincing. The authors show that subjecting cells to this inhibitor results in the absence of memory and removes the ability of cells to maintain their orientation after the gradient was disrupted. Clarification of which aspect(s) of the EGFR network within the context of the model are precisely disrupted by Lapatinib would be helpful in strengthening the authors' claims here that it is the mechanism of working memory and not other features of the EGFR network, that is responsible for the results shown.

Reviewer #3 (Public Review): 

Cell navigation in chemoattractant fields is important to many physiological processes, including in development and immunity. However, the mechanisms by which cells break symmetry to navigate up concentration gradients, while also adapting to new gradient directions, remain unclear. In this study, the authors propose a new theoretical model for this process: cells are poised near a subcritical pitchfork bifurcation, which allows them to simultaneously maintain the memory of a polarized state over intermediate timescales and respond to new cues. They show analytically that a model of EGFR phosphorylation dynamics has a subcritical pitchfork bifurcation, and use simulations of in silico cells to demonstrate both memory and adaptability in this system. They further measure EGFR phosphorylation profiles, as well as migration tracks under external gradients, in real cells. 

This work contributes an interesting new theoretical framework, bolstered by substantial analysis and simulations, as well as valuable measurements of cell behavior and polarization. Both the modeling and the measurements are careful and thorough, and each represents a substantial contribution to decoding the complex problem of cell navigation. The measurements support and quantify the phenomenon of directional memory. The main weakness is that it is not clear that they also support the mechanism proposed by the model. 

Theoretical framework:

One of the main strengths of this work is the thorough theoretical analysis of a model of symmetry breaking in EGFR phosphorylation. The authors perform linear stability analysis and a weakly nonlinear amplitude equation analysis to characterize the transition. Additionally, they convincingly demonstrate in simulations that this model can generate robust polarization, with memory over intermediate timescales and responsiveness to new gradient directions. However, the relationship between the full dynamical system and the bifurcation diagrams shown in Figure 1A and Figure 1-Figure Supplement 1B is not clear. In particular, there is an implicit reduction from an infinite dimensional system (continuous in space) to an ODE system. From Methods 5.15, it appears that this was accomplished by approximating the continuous cell perimeter as a diffusively-coupled two-component system, representing the left and right halves of the cell (Methods 5.15 Equation 18 to Equation 19). However, this is not stated explicitly in the methods, and not at all in the main text, making the argument difficult to follow. Additionally, the main text and methods describe the emergence of an unstable odd spatial eigenmode as the key requirement for the pitchfork bifurcation. It is not clear why it is sufficient to show this emergence in the two-component system. 

Relationship between the measurements and model:

The second main strength of this work is the contribution of controlled measurements of cell motility, polarization, and phosphorylated EGFR profiles. The measurements of cell migration presented here support the claim that the cells have a memory of past gradients. Additionally, the authors contribute very nice quantifications of the memory timescale. The Lapatinib experiments also support the claim that this memory is related to EGFR activity. However, there are a number of ways in which the real cells appear not to behave like the in silico cells. Polarization in phosphorylated EGFR is present only some of the time in the data, and if present, appears to be weak and/or variable, in magnitude and direction (phosphorylated EGFR profiles, figure 2C, Figure 2-Figure supplement 1D, E). Even for the subset of cells that display polarized EGFR phosphorylation profiles, the average profile is shown after aligning to the peak for each cell (Figure 2-Figure Supplement 1C), so it is not clear that they polarize in the direction of the gradient. The real cells also appear to track the gradient far less reliably than the in silico cells (e.g. Figure 4B vs. 4C). Thus the measurements demonstrate and quantify the phenomenon of directional memory, but it is not clear that they support the mechanism proposed by the model, i.e. a symmetry-breaking transition in phosphorylated EGFR. 

Additionally, in the authors' model, the features of memory and adaptability in cell navigation depend on the system being poised near a critical point. Thus, in silico, the sensing system 'breaks' when the system parameters are moved away from this point. In particular, cells with increased receptor concentration on their surface cannot adapt to new gradient directions (Section 1, final paragraph; Figure 1-Figure Supplement 1E-G). Based on this, the authors' theoretical framework makes a nonintuitive prediction: overexpression of the surface receptor EGFR in real cells should render them insensitive to changes in the concentration gradient. The fact that the model suggests a surprising, testable prediction is a strength of the framework. A weakness is that the consistency of this prediction with empirical data is not discussed (though the authors note similarities between this regime and unrealistic features of previous models).

Reviewer #1 (Public Review):

The integrated stress response (ISR) controls cellular protein synthesis in response to diverse stimuli. A set of related protein kinases, with distinct regulatory domains that respond to different stress conditions, share a common kinase domain that specifically phosphorylates the translation factor eIF2 on its alpha subunit. Phosphorylation of eIF2 inhibits translation by inactivating eIF2B, the guanine nucleotide exchange factor (GEF) for eIF2. The decameric eIF2B, a dimer of heteropentamers, is the key control hub of the ISR. Previously, a small molecule inhibitor of the ISR called ISRIB was found to bind to eIF2B and was proposed to reverse the impacts of eIF2 phosphorylation by increasing stabilizing the association of eIF2B heteropentamers into the functional decameric complex. However, more recently, an alternative model ISRIB action has been proposed. eIF2B is proposed to toggle between inactivate and active states. Binding of phosphorylated eIF2 to a regulatory site is proposed to trigger the inactive state by allosterically weakening binding of eIF2 at the active site. In the new model, ISRIB has been proposed to favor the active state conformation of eIF2B and thereby overcome the effects of eIF2 phosphorylation.

In this paper, the authors further study a previously described H160D mutation in the eIF2Bbeta subunit. This mutation at one of the dimer interfaces in eIF2B was previously proposed to inhibit eIF2B by weakening dimerization. Consistent with this hypothesis, the H160D mutation impaired dimerization of eIF2B(beta, gamma, delta, epsilon) tetramers. However, in this study, the authors show that the H160D mutation does not impair dimerization when eIF2Balpha is included; thus, the mutation impairs eIF2B activity without impairing dimerization. Using biochemical assays, the authors show that the H160D mutation impairs nucleotide exchange by eIF2B decamers and weakens the binding eIF2 to eIF2B. However, the binding of phosphorylated eIF2 to eIF2B is not weakened.

Cryo-EM structural analysis of the mutant eIF2B complex reveals a partial rocking of the decameric structure that resembles the structure of the eIF2B complex when bound to its inhibitor phosphorylated eIF2. In this partially rocked structure, both the ISRIB binding site at the dimer interface and the functional eIF2alpha binding sites are widened, providing a structural solution to why the mutation weakens eIF2 binding. Interestingly, the inhibitory binding site for phosphorylated eIF2 is not affected the H160D mutation. The authors propose that the H160D mutation in eIF2Bbeta induces an allosteric conformational change that mimics the effects of phosphorylated eIF2 binding to eIF2B.

Finally, the authors generated cell lines that exclusively express the mutant eIF2Bbeta subunit. The mutation impairs total protein synthesis and cell growth rate and leads to elevated expression of the ISR marker ATF4.

This is a high-quality study, the results are convincing and the authors conclusions are supported by the data. As the ISR has been implicated in a variety of diseases, further elucidation of the mechanism of action of eIF2B and ISRIB will be critical in the development of therapeutic interventions.

A weakness of the paper (that hopefully can be easily remedied) would be to show the quality control data to verify the mutant cell lines used in Figure 6. It would be good to see that the mutant allele is present in the cells and that no WT alleles remain. In addition, examination of eIF2alpha Ser51 phosphorylation in Figure 6A would strengthen the conclusion that the eIF2Bbeta mutation is activating ATF4 expression independent of changes in eIF2 phosphorylation. Also, use of ATF4 reporters in Figure 6A, in addition to the presented Western data, would provide a nice quantitative read-out for the impact of the H160D mutation on ATF4 mRNA translation. Finally, as the biochemical and structural data indicate that the H160D mutation impairs ISRIB activity, it would be worthwhile testing whether ISRIB will rescue the slow-growth of the H160D cell lines in Figure 6D (the anticipation is that this slow-growth phenotype will not be rescued by ISRIB).

Reviewer #2 (Public Review):

The integrated stress response (ISR) features eIF2 phosphorylation that invokes translational control in response to diverse stress conditions. The eIF2 combined with GTP is central for escorting the initiator tRNA to ribosomes and phosphorylation of eIF2 serves to repress its dedicated nucleotide exchange factor (eIF2B), those impairing the ability to recycle to the active eIF2-GTP that is required for global protein synthesis. There is much interest in the multisubunit eIF2B functions (five subunits in a decameric complex) including the mechanisms for its repression by phosphorylated eIF2 and small molecules render eIF2B insensitive to eIF2 phosphorylation or those that can repress eIF2B. This manuscript addresses the consequences of a missense mutation in eIF2B (beta subunit), with an eye towards delineating mechanisms regulating eIF2B in the ISR. Given that the important roles of eIF2B and the ISR in stress responses and different diseases, including neuropathologies, infectious and inflammatory diseases, and diabetes and metabolic disorders, this line of research is significant and is of broad interest.

Critique:

The beta subunit of eIF2B (H160D) was previously shown by this laboratory to block eIF2B tetramer assembly in vitro upon treatment with ISRIB. This study addressed how the residue substitution affects decamer formation and regulation of the ISR. Using a number of elegant biochemical and biophysical assays, along with cryo-EM imaging, the manuscript concludes that the H160D mutant retains the ability to form the decameric holoenzyme, but stabilizes eIF2B in an inhibited state, which would be typically induced by phosphorylated eIF2. This inhibited state is akin to the genetically defined gcd mutations in yeast by Hinnebusch and colleagues. Overall, the manuscript does support the activated/inhibited state eIF2B model for ISR regulation, although there are some concerns about the cryo-EM interpretations that should be considered and addressed. The manuscript will be of broad interest to the field.

Reviewer #1 (Public Review):

Parental specific gene expression is called imprinting and has been described in many mammals but also in plants. It relies on specific epigenetic marks such as DNA methylation or specific histone modifications that mark the chromatin of the gametes according to the parental origin. The different actors that maintain such imprints at the chromatin level are still to be better understood.

The authors previously published that SMCHD1 is one of such factors acting during mouse early development as a pool of maternally provided proteins within the oocyte (Vanigasuriya et al; eLife 2020;9:e55529). In particular, they showed its importance in the expression of a subset of imprinted genes whose regulation is based on histone modifications but not on DNA methylation, at least during preimplantation timing. In the present study, they now focus on regulation of one of such genes called Xist. Xist encodes for a long non-coding RNA that is necessary for X chromosome inactivation in female, a process allowing gene dosage compensation between the sexes. Different previous and independent studies have shown that inappropriate expression of maternal Xist could lead to aberrant X chromosome inactivation in male and female embryos, and lethality in the worse cases, highlighting the importance of an accurate expression pattern for this gene.

Here, the authors observe, using two independent approaches (allelic RNA seq and allelic RNA FISH), the partial reactivation of the normally silent maternal allele of Xist in male and female morula (16-32Cell stage) (Figure 1d and Figure 3) derived from maternally depleted SMCHD1 oocytes. Based on their allelic RNA FISH assays, they conclude that abnormal biallelic expression is only transient as it is resorbed by the next developmental stage (blastocyst). Different groups demonstrated previously that in wild type mouse morula and blastocysts, between 90 and 100% of nuclei in female embryos are harboring one single Xist cloud (covering the paternal X) per nuclei. The fact that the authors find up to 50% of nuclei without any signal in their controls and up to 75% in the mutants, (when one should expect at least one cloud in 90-100% of females nuclei in any case), questions the robustness of their RNA FISH. This possibly faulty assay questions the conclusion that the imprinted default observed earlier is resolved. In other word, Xist misregulation might last longer in maternal mutant SMCHD1 than what is presently concluded in this manuscript. One other point made with this study is that the DNA methylation status of the Xist locus is not impaired in mutant, ruling out the role of SMCHD1 on DNA metylation at that genomic place in early mouse embryos.

Maternal Xist could lead to abnormal maternal X linked gene silencing in blastocysts and later, and be associated with failure of embryonic development (Inoue et al 2018). Understanding if aberrant Xist expression has any consequences at the level of the X chromosome in the maternal SMCHD1 mutant is therefore very relevant, and the authors of the present study use their allelic RNA seq data to enquire this question. They conclude that X chromosome expression is altered during preimplantation as well as much later in the placenta. Their transcriptomic analysis seem however succinct to fully understand if these changes are due to silencing of the maternal X chromosome in male and female embryos, which genes might be abnormally regulated, and if the observed defect in morula have any linked with the other developmental stage they analyzed. A deeper analysis of their allelic transcriptomic data would at least strengthen our understanding of how a transient expression of SMCDH1 would reflect on adequate X chromosome expression.

This study is a nice preliminary description of the importance of maternal pool of SMCHD1 on maternal Xist expression and X chromosome expression/ inactivation in mouse embryos. It does not cover any further understanding on the chromatin changes that might be due to loss of maternal SMCDH1 on specific genomic locus such as Xist and more generally on the molecular mechanisms at work for the transiently imprinted gene regulation. These are challenging questions, given the developmental stages studied, and is beyond the scope of this manuscript, yet it place SMCHD1 as a new interesting player.

Reviewer #2 (Public Review):

SMCHD1 has a well-established role in the later stages of X-inactivation, but earlier functions, discoverable only from maternal SMCHD1 deletion, have never been performed. This study fills that gap, and shows roles for SMCHD1 in X-inactivation establishment and imprinting.

In this manuscript, Wanigasuriya et al investigate the role of SMCHD1 in mouse imprinted X-chromosome inactivation (XCI). Previous studies from this lab established a role for zygotic SMCHD1 in later stages of XCI, e.g. in regulating DNA methylation at a subset of X-genes. This study is distinct in that it investigates the effects of maternal SMCHD1 on XCI. Three phenotypes are noted: partial loss of maternal imprinted Xist silencing, as well as defective Xp silencing at E2.75, and defective Xp silencing in the placenta at E14.5. The novelty here is uncovering roles for maternal SMCHD1 early in the XCI process, and showing that the effects of maternal SMCHD1 loss persist later, even when zygotic SMCHD1 kicks in. The manuscript is well-written, and the analyses by and large well-performed, with allele-specific RNA FISH a particular highlight.

Reviewer #1 (Public Review):

Previous work by this research group has demonstrated that during a brief period after the onset of a visual target in an ant-saccade task, saccades tend to be directed obligatorily towards the target before they can be redirected to the correct location. In this study, Goldstein et al. tested whether these separate exogenous and endogenous processes are independent by examining the temporal evolution of saccade accuracy in pro- and anti-saccade tasks in the same subjects. They found that the results were consistent with a pair of models that differ only in terms of whether the exogenous and endogenous processes eventually lead to the saccade in the same direction or not. In addition, the temporal change in accuracy was also parsimoniously explained by the same model even when there is a systematic motor bias resulting from the recent trial history. Overall, these results provide further evidence for the independence of exogenous and endogenous processes responsible for the control of saccades. The manuscript is written clearly, and there are no major concerns.

Reviewer #2 (Public Review):

For clinicians, an informal method of evaluating frontal lobe function is to hold up a finger and ask (tell) the patient to look in the opposite direction. It is claimed that healthy controls can easily look away, while individuals with frontal lobe damage/dysfunction cannot overcome an overwhelming desire to look at the finger. This paradigm, known as the "anti-saccade," offers a simple but useful method to measure, model, and investigate neural correlates of response inhibition. Consequently, there has arisen a vast literature on the subject, to which the current study contributes.

If this reviewer understands correctly, the main contribution of the current study is to show that the anti-saccade plan is not triggered by the visual cue. Rather, equal and opposite pro- and anti-saccade plans evolve in parallel but with some stochastic variability. That is, at any given time, one plan may be closer to threshold than the other. When the cue comes along, it reinforces whichever plan is spatially congruent with the cue, and inhibits the other plan. The movement that is eventually produced is simply determined by whichever plan reaches threshold first. Thus, anti-saccades only happen when the anti-saccade plan has, by chance, achieved an insurmountable advantage over the pro-saccade plan.

This seems like a plausible model and it clarifies that anti-saccades are not a change of plan, but a selection from multiple competing plans. It further clarifies that the movement plans (which are endogenously generated) are independent of the exogenous cue, and that nothing about the cue, other than its congruence with the underlying plans, signals whether the subject should produce a pro- or anti-saccade. The model is simple enough that it generates clear and testable neurophysiological predictions.

Given the size of the extant literature, the reviewer is at a disadvantage to evaluate the novelty or impact of this, work and therefore leaves this aspect of the evaluation to the experts. To a non-expert, there are a few places where the authors seem to be using novel terminology for conventional ideas. This practice should be discouraged. The main concern is that the report is written at a very technical level, as if meant only for true afficionados.

Reviewer #3 (Public Review):

Goldstein et al. use computational modeling and human psychophysics to try to untangle the roles of exogenous capture of attention, cognition, and motor planning. The authors have already made considerable progress on this issue, most notably in their eLife paper (Salinas et al. 2019). The authors adapted a race-to-threshold model to their urgent pro- and anti-saccade task (Fig. 2). This model, employing a straighforward 'flip' on the exogenouos signal during pro vs anti saccades, produces clear predictions regarding the behavioral tachometric curves (Fig. 3), including fine-grained predictions about the relative timing of shifts in performance (Fig. 3b). The authors go on to demonstrate that this model does, in fact, capture the behavioral dynamics (Fig. 4). The agreement between model predictions and behavioral observations extends to individual subjects (Fig. 4c) and across stimulus luminance levels (Fig. 4e). Putative motor biases were likewise captured (across the population) by the model dynamics (Fig. 5), as well as the timing of individuals' performances across tasks (Fig. 6). The ability of the model to account for these various aspects of the data is impressive.

Strengths:<br /> The authors have previously demonstrated a specialized task that seems to facilitate a principled analysis. The task itself is well-controlled and simple, like most experimental tasks, but it provides robust behavioral effects, lending support to the authors' claims.

The manuscript is largely well-structured and clearly written throughout.

The behavioral results are clearly presented and the agreement between model and behavior is indeed remarkable.

Weaknesses:<br /> First, it is not clear to me what the major advance is beyond previous work. This is not a commentary on the quality of the current work. Given the results, it is interesting to consider the authors' assumption that the exogenous response "is entirely insensitive to behavorial context". The results are compelling but seem to fall short of that broad (assumed) claim.

There is an assumption that "saccade-related neural activity is ramping up" (Line 272) before the saccade goal is known. I understand the impetus for this reasoning, but I don't think it is the only (or maybe even, best) account of the phenomenon. It is unclear exactly how a motor plan, in its strictest neurobiological sense is prepared to an unknown location? In the current task, I imagine the argument would be that two rival motor plans are developed (i.e., Fig. 2) and the subject is effectively weighting their two guesses accordingly. But then that raises the question of whether the result is dependent on the constraints of the task. An alternative explanation is that the "readiness" to move is not purely motor and may be largely cognitive. This distinction is subtle and slippery, but it informs our understanding of the neural circuitry because, in this interpretation, ramping of saccade activity does not necessarily need to be true. I would have liked to have seen more discussion of the roles of motor preparation, visual-motor attention, and general arousal. These topics are often poorly defined and the authors' approach could help disambiguate the terms.

Reviewer #1 (Public Review):

Attaallah et al. report a detailed study about uncertainty processing in patients with subjective cognitive impairment (SCI). The task paradigm they developed recently (Petitet et al., 2021, Nature Human Behaviour) allowed a rigorous computational analysis of how SCI participants and matched controls differed in active sampling behaviour aimed at reducing uncertainty. The results show that to resolve uncertainty SCI participants sampled faster and obtained more information than matched controls. Importantly, in spite of this urgent sampling behaviour the SCI participants were equally efficient in reducing uncertainty as controls. In contrast, findings from a 'passive' task condition where participants estimated and valued uncertainty but were not able to actively reduce uncertainty, showed no group differences. This emphasizes the importance of agency over uncertainty in characterizing SCI participants.

So far I found the findings were highly robust and convincing. I was less enthusiastic about the authors' choice to summarize these findings as adults with SCI being 'hypersensitive' to uncertainty. If the SCI group was hypersensitive to uncertainty, then why did the SCI group not differ from controls in how they estimated and valued uncertainty in the 'passive' condition? In other places of the manuscript, the authors summarize the same key findings as the SCI group being 'hyperreactive' to uncertainty. Given the importance of agency and active sampling, I believe the term 'hyperreactivity' is far more appropriate in this context than 'hypersensitivity'. So I encourage the authors to adjust their terminology, also in the title of the paper.

In the second half of the results section, we first learn from fMRI data that the SCI group and control group differ in resting-state functional connectivity, specifically between bilateral insula and bilateral hippocampal/parahippocampal regions - a finding that may have interesting theoretical repercussions. Finally, the authors report cross-subject correlations between a number of variables that were found to differ between the two groups: (i) measures of hyperreactivity to uncertainty, (ii) affective burden and (iii) insular-hippocampal connectivity (Figure 5C and Figure 7). Here the authors make a critical methodological mistake. The mistake is that they draw conclusions from correlation analyses in which all study participants (SCI and control) were included. If you take two variables that both significantly differ between groups and then correlate the two variables across all study participants, you are almost bound to find a significant correlation, even when within each group there is no significant correlation. This problem is illustrated by the classic statistical textbook example of a spurious correlation between two random point clouds that are separated from each other along both axes. These correlations (grey numbers in Figures 5C and 7) should not be reported because they probably reflect little more than the significant main effects of the group on the two variables that were already reported in earlier parts of the results section.

The authors are 'lucky' because the correlations between measures of hyperreactivity and affective burden (purple numbers in Fig 5C) are also significant when only the SCI participants are included. The same is true for the correlation between hyperreactivity and insular-hippocampal connectivity (purple numbers in Fig 7). The problem is with the correlation between affective burden and insular-hippocampal connectivity (Fig 7): this correlation is significant when all participants are included but is clearly not present when only the SCI participants (or only the controls) are considered. This means that it cannot be concluded that these measures are related to each other and I am afraid that the same argument also invalidates the mediation analysis that includes all three variables (and corresponding conclusions). If the authors want to report a mediation analysis, they should base it only on the SCI participants.

Note that on page 16 the authors acknowledge that "Caution should be exercised when interpreting these [correlation] results as these models were performed with data from both groups included. This was done to take advantage of the larger sample size for this type of analysis, while also trying to explore inter-individual differences regardless of group assignment." While this may be true, the authors overlook the statistical problem associated with these correlation analyses. I would suggest that the authors remove these analyses including all participants and adjust the results/discussion sections accordingly. In my view, there are plenty of remaining (i.e. valid) results that are interesting and novel, and that together with the rigorous methods and appropriate discussion form a very strong paper.

I believe this paper could have a major impact on the community of SCI researchers but it also presents a showcase of how one can rigorously examine active sampling behaviours and sensitivity to uncertainty in other clinical populations.

Reviewer #2 (Public Review):

In this paper, the authors set out to clarify potential mechanisms underpinning subjective cognitive impairment (SCI) in the absence of objective impairment. Noting that individuals with (SCI) often present with high levels of depression and anxiety, which are linked to altered processing of uncertainty, the paper proposes that hypersensitivity to uncertainty may be a mechanism in SCI. Using an information-gathering task, the authors demonstrate that individuals with SCI sample more than controls before committing to a decision and sample faster, although this is not linked to subjective reports of uncertainty, suggesting is it not necessarily an adaptive response to exaggerated uncertainty estimation. Faster sampling was linked to symptoms of anxiety and depression, and to insular-hippocampal connectivity.

Strengths:<br /> 1) The task used provides an effective measure of information gathering.<br /> 2) The sample of individuals with SCI is well characterised and this study represents a rare and valuable attempt to understand the condition's cognitive mechanisms.<br /> 3) The resting-state fMRI provides some indication that exaggerated information gathering may be linked to altered function in a specific brain network.

Weaknesses:<br /> 1) The subjective reports of uncertainty in the passive task may not necessarily tap into the actual uncertainty used to guide decision-making in the active task.<br /> 2) While the claim that hypersensitivity to uncertainty is a reasonable interpretation of the results, this hypothesis isn't tested directly and so it remains a relatively speculative conclusion.

Reviewer #1 (Public Review):

Tiedemann et al. investigated internal generative models as a mechanistic explanation of one-shot learning of visual categories. To achieve this, they designed a clever paradigm where participants draw new Variations of a category based on a single presented shape (the Exemplar). They found that participants could successfully generate new Variations based on an Exemplar (Exp 1), that these vary in Similarity to the Exemplar (Exp 2), and are more than just mere copies of the Exemplar (Exp 2b). Next, they demonstrated that Variations are readily attributed to the correct corresponding Exemplar 'category' by naïve participants (Exp 3). Having established that novel Variations in a category can be generated as a result of one-shot learning, the authors turned to establishing what features drive these novel categories. To this end, they asked naïve participants to view pairings of a single Exemplar and Variation, and label overlapping features (Exp 4), or to view single Exemplars or Variations and label their distinctive parts (Exp 5). The authors find that each shape had distinctive features that were reliably reported across participants, that most features were shared among an Exemplar and its Variations, and that few features were shared with Variations of other Exemplars. To confirm the importance of these distinctive features, shapes were produced where the distinctive parts from two shapes were traded. Naïve participants sorting decisions now appeared to be biased toward the Exemplar that matched the swapped-in diagnostic feature, not the remainder of the shape (Exp 6).

These experiments were thoroughly run, they establish a rich basis for exploring one-shot learning, provide novel methodological approaches for quantifying information about complex shape comparisons, and contribute to our understanding of how novel categories can be extrapolated from individual objects - through internal generation driven by distinctive features. The conclusions drawn here are mostly consistent with what the data demonstrated, though could use some clarification and further justification. There are some instances where within- and across-experiment comparisons could have been used to drive further insights, allowing some of the proposed mechanisms to be clarified and better supported.

1) The authors present an interesting proposal for how the generative model operates when producing shapes in Fig 6, as well as some alternative strategies in Fig 7. It is not clear what evidence supports the idea that shapes are first broken down into parts, then modified and recombined. It is obvious from the data that distinctive features are preserved (in some cases), but some clarification on the rest would be useful. For instance, is it possible that conjunctions or combinations of features are processed in concert? What determines whether critical features are added or subtracted to the shape during generation? Some more justification for this proposed model is needed, as well as for how the exceptions and alternate strategies were determined.

2) Some claims are made in the manuscript about large changes being made to Variations without consequence to effective categorization. However, these appeal to findings derived from collapsing across all Variations, when it could be informative to investigate the edge cases in more detail. There is a broad range in the similarity of Variations to Exemplars, and this could have been profitably considered in some analyses, especially zooming in on the 'Low Similarity' Variations. For example, this would help determine whether classification performance and the confusion matrix change in predictable ways for high-, relative to medium- and low-similarity Variations. It could also indicate whether the features and feature overlap can tell us anything about how likely a Variation is to be perceived as from the correct category.

3) The authors cross-referenced data from Experiments 4 and 5 to draw the conclusion that the most distinct features are preserved in Variations. This was very compelling and raised the idea that there are further opportunities to perform cross-experiment comparisons to better support the existing claims. For example, perhaps the correspondence percentages in Exp 4, or the 'distinctive feature-ness' in E5, allow prediction of the confusion proportions in Exp 3.

4) The Variation generation task did not require any explicit discrimination between objects to establish category learning, which is a strength of the work that the authors highlighted. However, it's worth considering that discrimination may have had some lingering impact on Variation generation, given that participants were tasked with generating Variations for multiple exemplars. Specifically, when they are creating Variations for Exemplar B after having created Variations for Exemplar A, are they influenced both by trying to generate something that is very like Exemplar B but also something that is decidedly not like Exemplar A? A prediction that logically follows from this would be that there are order effects, such that metrics of feature overlap and confusion across categories decreases for later Exemplars.

Reviewer #2 (Public Review):

This study explores people's ability to perform one shot generalization - forming a category representation with just a single exemplar - and what features contribute to these categories. In order to avoid the biases that come with forced-choice discrimination tasks, the study employs an innovative drawing method, where participants see a single exemplar and then have to generate variations from the same inferred category. Then with a series of elegant online experiments, the study finds that these variations are successfully perceived as being from the same category by others, and that it is the most distinctive object parts (as well as curvature) that best delineate the object categories.

Overall, I find the paper compelling, the experiments methodologically rigorous, and the results clear and impactful. By using naïve online observers, the researchers are able to make compelling arguments about the generalizability of their effects. And, by creative methods such as swapping out the distinctive (vs. less distinctive) features and then testing categorization, they are able to successfully pinpoint some of the determinants of one-shot learning.

Reviewer #3 (Public Review):

In this manuscript, the authors aim to determine the mechanisms by which people generalize from novel shapes to categories of shapes. They showed participants novel shapes and asked them to draw a new object from the same category. A separate group of participants then categorized the drawn shapes. Exchanging distinctive parts between the exemplars and categorizing these chimeric shapes proved that the most distinctive parts were mainly responsible for assigning category membership.

This set of experiments is well conceived, executed, and analyzed. The manipulations are sensible, the construction of the chimeric shapes is an interesting concept, and the results are convincing. Specifically, the comparison between swapping the most versus the least distinctive part provides for a convincing control condition. The use of confusion matrices for the categorization experiment allows for the analysis of specific mis-classifications. All stimuli are publicly available.

Reviewer #1 (Public Review):

In this article, Miettinen and colleagues exploit the suspended microchannel resonator developed in their lab and optimize the method to be able to record single live mammalian cells for very long periods of times, across several cell division cycles, while performing a double measure of their buoyant mass in media of different densities (H2O and D2O). Because water exchanges fast enough inside the cell, it allows them to define a dry mass and a dry volume, and thus a density of dry material for single cells along the entire cell division cycle. These measures lead them to confirm and clarify some points from previous studies from their lab and others, such as exponential growth also in dry mass and the fact that buoyant mass and this new dry mass are the same thing in interphase cells. They then find that this is not true during mitosis, mostly because dry mass density increases in early mitosis (dry mass decreases and dry volume decreases even more, suggesting that there is a loss of material of density lower then the average dry mass density). The authors rule out a number of potential mechanisms and give evidence for a role of exocytosis, more precisely exocytosis of lysosomal content. Blocking this phenomenon prevents the change in dry mass density but does not affect cell division. They propose some potential function for this phenomenon, including the interesting hypothesis that this helps cleaning the lysosomal content which might contain some toxic components, so that daughter cells are born with 'clean' lysosomes. Cool idea! It is also quite amazing that the precision of their method allows them to detect this event.

The main question I have concerns the definition of dry mass and dry volume. The authors should discuss in more details what it represents physically. Technically, this is defined by their equation 1, which relates their measure of buoyant mass to a dry mass and a volume of water as parameters to fit from the buoyant mass data. One gets to this equation by writing the definition of buoyant mass as the mass of the cell minus the mass of the equivalent volume of the surrounding medium. But then, to get what the authors find, one has to write that the cell mass is the sum of the dry mass and the mass of water contained in the cell (which makes the dry mass easy to understand) and then to write that the cell volume is the sum of a volume of water and of a volume of dry material. This then defines a dry volume, as the difference between the volume of the cell and the volume of the water contained in the cell (which is the parameter Vwater in the equation 1). At least this is how I got to this equation. The question I asked myself then is: what is this dry volume? Is it really the volume occupied by the dry mass in the cell? This is probably not the case, since dry mass is solvated in the cell. One can estimate this solvated volume using the van't Hoff/Ponder relation, which can be found changing the osmolarity of the external medium. It defines an excluded volume, which is the total volume excluded by macromolecules (like for a van der Waals gas) - it is usually between 25 and 30% of the cell volume. This volume contains the dry mass plus a certain fraction of the water, so it is not exactly the dry mass volume as defined here by the authors. I am worried that this dry mass volume, which is mathematically defined here and calculated from the fit of the equation, is not a standard physical quantity and so it is not easy to relate it to standard biophysical theories (e.g. equations of state), and its behavior could be very unintuitive even for simple systems. This makes the variation in this quantity not easy to interpret, and thus also the variation in dry mass density is not easy to interpret in physical terms.

That being said, it is still clear that whatever this is, it changes in early mitosis, and it seems to be related to exocytosis, so I am not saying that the authors are wrong here. They potentially indeed detect this increase of exocytosis. But they should discuss more what they think this quantity is, either in the methods or in the discussion of the article. In particular, the sentence at the bottom of page 5, line 104, is not clear ('We are not aware of any other single cell methods capable of quantifying this biophysical feature of a cell'), since this measure is not really clearly a biophysical feature of a cell, but is defined a bit artificially from the equation which defines the dry mass volume from the measures of buoyant mass.

Reviewer #2 (Public Review):

The new suspended microchannel resonator (SMR)-based method described in this paper enables high precision and high temporal resolution single-cell measurements of key physical properties: cell dry mass and the density of cell dry mass, which depends on the macromolecular composition of the cell. The validity of the method is rigorously tested with several convincing control experiments. This method will be useful for future studies investigating cell size and growth regulation and the coordination of mass, volume and density in animal cells.

Using their method, the authors report two important results. First, they confirm that buoyant mass measurement is a valid proxy for cell mass in interphase, an important finding given that SMR measurements have been one of the best and most productive approaches to investigating cell mass growth regulation. Second, they provide evidence that some cell types lose dry mass during metaphase by a mechanism that involves exocytosis, emphasizing how mass, volume, and density dynamics are more complex than during the rest of the cell cycle.

While this paper presents very interesting results, it would benefit significantly from two main improvements. First, the different physical variables studied here (dry mass, dry density, dry mass density, dry volume) should be better defined, and the terminology revised to provide a more straightforward and intuitive description of their biological meaning. Several sections of the paper (especially the introduction and the discussion of Fig. 2-4) should be re-written to help the reader understand the message. Second, some of the drug treatments require more replicates to provide more conclusive answers.

Reviewer #3 (Public Review):

In this manuscript, the authors extend the Manalis lab's vibrating cantilever approach by adding the ability to rapidly exchange media with heavy water. This allows the authors to measure dry mass and its density in growth and proliferating cells. This resolves a previous discrepancy of the cantilever approach and quantitative phase imaging and shows that cells in early mitosis likely increase lysosomal exocytosis. This is an interesting piece of work.

The authors report that: "On average, the FUCCI L1210 cells lost ~4% of dry mass and increased dry density by ~2.5%, and these changes took place in approximately 15 minutes (Figure 3C). In extreme cases, cells lost ~8% of their dry mass while increasing dry density by ~4%". Although these changes may sound small, I believe they would require significant changes to the cell composition. I.e., to increase the overall dry mass density by 4% while losing 8% of the cell's dry mass, the cell would need to lose almost exclusively low-density components, which may not be typical for exocytosis. Moreover, even if all of those lost 8% of cell dry mass are exclusively lipids (or other low-density components), it is not intuitively obvious that such a loss would be sufficient to cause a 4% change to the dry density. To make this more convincing, the authors should provide a simple mathematical model that would roughly estimate how the cell composition (e.g., the contents of lipids vs proteins) needs to change and what the composition of the lost (secreted) components needs to be to provide the observed changes to the dry mass and density, given the existing information on average cell composition and the densities of different biomolecules (lipids, sugars, proteins, etc).

Reviewer #1 (Public Review): 

The manuscript by Wiesinger et al., demonstrates the differentiation of human induced pluripotent stem cells (iPSCs) into pacemaker cardiomyocytes. Authors have shown impressive analyses of sinoatrial node cardiomyocytes (SAN-CM) using scRNA-seq approach followed by a computational method namely Trajectory Inference (TI) to understand the diversification of SAN subtypes. The study further show a key role of Wnt signaling in the critical branching of pacemaker cardiomyocytes and/or pro-epicardial cells. Authors further went on to show the temporal role of Wnt and TGFbeta signaling in the formation of SAN-CM subtypes including SAN-head, SAN-tail and SAN-transitional (TZ) cells. 

Strengths:

The manuscript is well written with robust and detailed experimental approach wherein authors study the SAN-CM cell differentiation from iPS cells and reveal the role of specific signaling pathways in directing cell fate choices. The observations may lead to potential targets for disease condition pertaining to defective pacemaker cell activity and also facilitate understanding on cardiac regeneration in general. The results do support the conclusions that the authors made. The methods described in this manuscript can be used for other similar studies and cells types to identify cell fate choices. 

Weaknesses:

The study though well-executed do have a lack of conceptual novelty. The generation of SAN-CMs from iPS cells is a well-established method, so is the knowledge about SAN-head, SAN-tail and SAN-TZ subtypes and their general markers. The transcriptomic (mRNA repertoire) of SAN-CM cells of mice already shows the utility of one of the markers (VSNL1) described in the current manuscript, along with GNaO1 (Liang et al., 2021). Authors themselves discuss and agree with most of the published studies that shows the Bone Morphogenic Protein (BMP), Retinoic Acid (RA) and the implication of TGF-beta/BMP signaling in SAN development. 

The contribution of this study to our understanding on SAN cells is by pinpointing the role of specific signaling pathways and validating the same in vitro. This can lead to the understanding of how subtype specific differentiation of SAN-CMs can be carried out by fine-tuning these key pathways.

Reviewer #2 (Public Review): 

In the manuscript titled "A single cell transcriptional roadmap of human pacemaker cell differentiation," the authors seek to delineate the cell fate decisions that occur during the in vitro differentiation of human pacemaker cells (SANCM) from hiPSCs. The authors first compare marker expression and functional properties of differentiated SANCM and VCM cells, and establish that the SANCM cells have the expected characteristics of pacemaker cells. Single cell RNA sequencing was then used to explore the heterogeneity of the differentiated cells and illustrate the separate clustering of VCM and SANCM cells. The scRNAseq data was used to identify and characterize the different SANCM subtypes generated by the differentiation process. scRNAseq was then used to analyze samples from different stages of reprogramming and highlighted the changes in the transcriptome during the differentiation process. In addition, pseudotime analysis was performed in conjugation with pharmacological manipulation to show how WNT and TGF-beta signaling affect the stepwise progression of hiPSCs into the identified different SANCM subtypes. This study provides evidence for the presence of different SANCM subtypes generated by the SANCM differentiation process as well as illustrates the role of the WNT and TGF-beta in generating these different clusters of SANCM cells. Additional validation of the SANCM heterogeneity during the in vitro differentiation process as well as additional evidence of novel mediators of the acquisition of the unique SANCM subtype identity would strengthen the impact of this manuscript. 

Specific suggestions: 

1. The first scRNAseq experiment highlights the transcriptional differences between VCM and SANCM clusters, however, these differences are to be expected. This data also supports the hypothesis that the SANCM differentiation leads to a heterogeneous population. Additional bioinformatic analyses into the differences between these different clusters may provide more novel insights and could provide molecular targets to explore in vivo during embryonic development. For example, the identification of Vsnl1 and Gnao1 are promising gene candidates that should be further explored during multiple timepoints of heart development and validated with quantification. This data would provide complementary evidence that this differentiation process recapitulates what happens in vivo. Immunofluorescent staining of select markers of different scRNAseq clusters should also be provided to confirm the identified cluster-specific differentially expressed genes. 

2. The final portion of the manuscript further establishes the specific roles of the WNT and TGF-beta components of the differentiation protocol, but requires additional experiments to show that the heterogeneity is affected at the single cell level when these pathways are altered (such as immunofluorescence staining to show that fewer cells are expressing that gene of interest rather than a systemic change seen by qPCR). Being that the significant roles of WNT and TGF-beta are to be expected due to the presence of chemical modulators of those pathways are present in the differentiation protocol, this manuscript would benefit from experiments exploring other signaling pathways that increase or decrease the efficiency in the creation of the different subtypes of SANCMs, or a more detailed evaluation of when the hiPSC based strategy begins to overlap with heart development and a characterization of the role of the newly identified genetics target(s) in SANCM subtypes differentiation in vivo.

Reviewer #1 (Public Review):

The authors took advantage of an existing protein-trap resource in zebrafish to identify genes important for normal pacemaker function in adults. They generated a collection of lines with mutation in genes that expressed at reasonably high levels in the heart and assess their ECG. They identified 3 candidates with increased incidence of sinus arrest and focused on validation of dnajb6b. The dnjb6b mutant fish display other defects including enhanced response to atropine and carbacol and bradycardia. They show that dnajb6b is expressed in a subset of cells in the sinus node in zebrafish. In mouse sinus node, DNAJB6 expressing cells have low expression of TBX3 and its target HCN4. In addition, Dnajb6b+/- mice also display similar phenotypes. Analysis of pacemaker function in ex vivo mouse hearts by high-resolution fluorescent optical mapping of action potentials revealed that the number of leading pacemakers in Dnajb6b+/- hearts is decreased in the sinus node, with a concomitant increase in the auxiliary pacemakers. RNAseq analysis of the right atrial tissues detected expression changes in ion channels and genes involved in Ca2+ handling and Wnt signaling. Overall, the results support the conclusion that DNAJB6 is important for proper sinus node function, thus adding it to the short list of sick sinus syndrome genes. However, the manuscript has several weaknesses.

Weakness<br /> The manuscript does not address the mechanism by which decreased DNAJB6B causes sick sinus syndrome. For example, it is unknown if DNAJB6B functions cell autonomously or non-cell autonomously in the sinus node. The RNAseq analysis identified changes in ion channels in the right atrial tissues of 1-year old mice, cellular electrophysiology of the sinus node cells was not assessed.

The manuscript does not address why the zebrafish homozygous mutants are adult viable while the mouse homozygotes are embryonic lethal. The insertion of the GBT411 disrupt dnajb6b(L) but not dnajb6b(S), while the mouse mutation deletes the entire gene. Does this difference partially explain the difference?

Reviewer #2 (Public Review):

In this manuscript, the authors expand upon previous work describing development of a protein trap library made with the gene-break transposon. This library was screened to identify lines displaying gene trap expression in the heart (zebrafish insertional cardiac mutant collection). A pilot screen of these lines using adult ECG phenotypes identifies dnajb6b as a new gene important for cardiac rhythm. Using the GBT/dnajb6b zebrafish line, Ding et al. find a proportion of aged homozygous mutant fish (1.5-2 years) present sinus arrest episodes and reduced heart rate. Treating GBT411/dnajb6b mutant adults with compounds revealed aberrant responses to autonomic stimuli, and sinus arrest episodes were induced following verapamil exposure, providing evidence that GBT411/dnajb6b as an arrhythmia mutant. This conclusion could be better supported by presenting specific ECG parameters to characterize the conduction defect more thoroughly. The authors then report that Dnajb6+/- adult mice recapitulate some of the phenotypes observed in zebrafish, including sinus arrest and AV blocks, as well as impaired (although different) responses to autonomic stimuli. The authors describe that these are features of sick sinus syndrome in the absence of cardiomyopathy phenotypes in either the zebrafish or mouse lines. However, overall cardiac morphology is not well described for either the GBT411/dnajb6b or Dnajb6+/- models.

To further support a role for Dnajb6 in sinoatrial node dysfunction, the authors performed optical mapping of action potentials from isolated mouse atrial tissue. These data reveal that Dnajb6+/- cultures exhibit ectopic pacemakers outside of the sinoatrial node, including within the atrial wall and inter-atrial septum. These data also show prolongation of SAN recovery time at baseline and following autonomic stimulation, further suggesting SAN dysfunction. RNA-sequencing experiments of DNAjb6+/- adult right atrial tissue showed differentially expressed genes encoding Ca2+ handling related proteins, ion channels, and WNT pathway related proteins. As these genes are involved in the cardiac conduction system, the authors suggest these pathways as molecular mechanisms underlying SSS phenotypes in Dnajb6 models.

Sick sinus syndrome is a relatively rare arrhythmia most commonly found in older populations. Therefore, it has been challenging to establish clinically relevant models and there is a limited understanding of mechanisms of SSS pathogenesis. One particular strength of this manuscript is the ECG phenotype-based forward screen of the gene-breaking transposon (GBT)-based gene trap library in aged animals. This pilot study provides proof-of-concept that this screening approach is well suited to identify regulators of cardiac function in adults and genes linked to adult diseases like SSS.

Reviewer #3 (Public Review):

Sick Sinus Syndrome (SSS) is a heart rhythm disorder that often occurs in the older population. The underpinning mechanism of SSS is largely unknown. The Xu lab has previously reported the zebrafish insertion cardiac (ZIC) mutant collection that consists of 35 gene trap lines with cardiac expression. In this manuscript, the authors employed electrocardiography to screen the ZIC collection and found that loss of function of cyth3a, vapal and dnajb6b led to cardiac defects resembling SSS. They then performed more in-depth analyses to examine how dnajb6 loss would impact the heart in both zebrafish and mouse models. The authors made several interesting observations. The authors showed that cardiac cells with high HCN4 and Tbx3 expression have relatively low dnajb6 expression, suggesting differential transcriptional regulations of these genes in the heart. Electrophysiology and optical mapping analyses revealed potential defects in pacemaker activities in the absence of dnajb6 and bulk RNA-seq analysis detected altered expression of multiple ion channels and wnt signaling genes. While these data support a link between dnajb6 and SSS, the manuscript would be greatly strengthened with additional quantitative measurements and mechanistic studies.

Reviewer #1 (Public Review): 

This study aims to examine how the COVID-19 pandemic has impacted cancer screening services, more specifically breast cancer screening in Spain using a number of key program performance indicators. They show that some performance indicators (screening participation, number of screen-detected cancers) were impacted, but that many others appear to be unchanged (false positive rates, cancer detection rates per participant, cancer stage distribution). Overall, this study adds important data to examine the question of how the pandemic has impacted cancer services. 

The major strengths of this study include its large representative sample size, the use of multiple rounds of screening in the pre-COVID-19 era to establish a pre-pandemic baseline, and the ability to adjust for several demographic and socioeconomic indicators that could confound results. 

Overall, the results support the study's conclusions that the COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers, but that other indicators such as false-positives rates, cancer detection rates per participant did not change. I think it is possible there is even evidence the recall rate is lower in the post-COVID-19 era; this analysis did not achieve statistical significance in stratified analyses, but I think that if the authors were to do an overall analysis of all participants they would find a significantly lower recall rate in the post-COVID-19 era. I think that the analysis of the changes of distributions of characteristics of participants in the post-COVID-19 era (Table 2) is not as informative as it could be, as participation rates by socioeconomic characteristics are influenced by invitation rates, and the invitation rates are shown to have varied over time. It is therefore possible that changes in the sociodemographic characteristics of participants in the post-COVID-19 era represent changes in eligibility to the program rather than changes in participation rates by socioeconomic status. I would have liked to see an analysis of participation rates (participants/invitations) by socioeconomic variables to better support the authors' conclusions. 

This data and analysis will be useful for other countries with breast screening programs who will be looking to compare the impact of the pandemic has had on their own screening programs.

Reviewer #2 (Public Review): 

The paper presents a description of the changes of the screening performance indicators during the period March 2020 to March 2021 compared to the period 2021-2019. The authors found a decrease in screening attendance, particularly in women who previously participated and in newcomers. On the other hand, the indicators focusing on the accuracy of the screening test (cancer detection, recall and false positives) showed small differences, if any. 

The data are interesting, but a more detailed analysis of the mechanisms underlying the changes would be much more informative and useful: what was the flow of invitations? Did reduced participation occur in delayed invitations? Can you estimate the delay in mammography? Is there an association between delay in invitation and attendance? 

The paper is very well presented with a robust set of indicators. Interpretation of the results is sound. 

The analyses could be improved by trying to understand the mechanisms that caused the decrease in attendance.

Reviewer #3 (Public Review): 

The authors studied the effect of the COVID-19 pandemic on some performance indicators in the population-based breast cancer screening programme of Barcelona, Spain. Towards this goal, they conducted a before and after analysis comparing the performance of the screening indicators before and after the pandemic and controlling for some characteristics of the screening population such as type of breast cancer screening round (prevalent, incidence), socioeconomic index, family history of breast cancer. The authors highlighted a reduction in participation in the post COVID-19 period especially in women invited for the first time or in those who had already participated in screening in previous years. The analysis did not reveal significant differences in other performance parameters (recall rate, detection rate, false positives, stage of tumors). The study has public health merit in starting to evaluate (with real numbers) the impact that such a disastrous event as the COVID-19 pandemic has had on screening activities. And, above all, to begin to evaluate the impact in order to implement countermeasures and strategies to resolve the critical issues that have unequivocally occurred as a consequence of the interruption/slowdown of breast cancer screening activities.

Reviewer #1 (Public Review):

This manuscript by Serrero et al reports on a very clever series of experiments that identified the dynamin-like GTPase resistance protein B (MxB) as an interferon-inducible protein that interacts with and disassembles herpesvirus capsids. The herpesvirus virion is complex consisting of viral structural proteins in hundreds of copies that make up the capsid and an additional tegument layer consisting of proteins that interact with the capsid and link it with the viral envelope. In these studies, extracts prepared from human macrophages were mixed with various forms of HSV capsids and the capsid-host proteins complexes were characterized by quantitative mass spectrometry (MS), immunoblot, and electron microscopy analysis. Using this novel assay the authors identified MxB as an interferon-inducible protein that had the remarkable property to bind and dissemble capsids resulting in the release of the viral genome. Interestingly, capsid assembly did not require proteases but was dependent on the ability of MxB to hydrolyze GTP and dimerize. Studies with capsids stripped of various tegument proteins indicated that MxB binding is localized to the capsid vertices and likely requires the capsid vertex specific proteins for this interaction.

This is an excellent study. I found all the experiments, including the supplemental data, to be complete and convincingly interpreted. The paper is well written, very concisely presented considering the large amount of data, and will be important to those studying the antiviral mechanisms of interferon-induced proteins. The many experiments all contribute to the detailed analysis of MxB's role in the antiviral innate immune response to herpesviruses. The conclusions of this paper are well supported by data. One of the bonuses of these experiments is that the MS studies identified many interferon-induced proteins that will need further characterization to determine their antiviral mechanism.

Reviewer #2 (Public Review):

Serrero et al. set out to identify the interactions between herpes simplex virus I (HSV-1) and host proteins by conducting proteomics analyses of cellular factors that bind to cell-free capsids. They prepared the capsids under various salt conditions and after trypsin digestion treatment to mimic potentially different states that might occur during viral entry or exit. They used cellular proteins found in control or interferon-treated macrophages. Following incubation of the capsids and cellular factors, they pelleted the capsids and identified many capsid-binding proteins by mass spectrometry. They reproduced the results by repeating the experiment several times and a few of the proteins have been previously reported to bind to viral capsid or tegument, but for the most part, the authors did not independently validate the results, nor did they explore the significance of the interactions. However, these proteomics data could prove to be useful as a reference for future studies.

Because the authors detected the host restriction factor MxB as one of the capsid-interacting factors and because it has been reported to restrict herpesviruses, they then used their binding assays along with quantitative electron microscopy (EM) to investigate the mechanism by which MxB inhibits HSV-1. Most interestingly, they find that MxB destroys HSV-1 capsids, seemingly by punching holes at the vertices. Expression of MxB by interferon treatment or, more convincingly, by transgene expression, results in a greater number of 'punched' capsids. MxB mutants lacking the N-terminus or deficient in GTP binding or hydrolysis are less able or unable to damage the capsids. The concordance of these results with prior studies of MxB restriction of HSV-1 replication supports the idea that the way MxB acts is by damaging capsids. Binding of these mutants to capsids seems to be necessary but is not sufficient for damaging the capsids. They also show that the effect of MxB on capsids is generalizable to other alphaherpesviruses (HSV-2 and VZV).

Perhaps the most intriguing result is that MxB acts most efficiently on naked capsids; its binding to and destruction of capsids is inhibited under conditions where more viral tegument proteins should be associated with capsids and may shield the capsids from targeting by MxB. The authors also show that MxB damage to capsid leads to viral DNA leakage and they hypothesize, but do not test, that the released DNA might trigger of DNA sensors and promote immune responses. Overall, this work reveals useful insights into the MxB anti-herpesviral mechanism and provides an original model of how viruses might evade capsid-targeting host defenses.

Reviewer #1 (Public Review):

This interesting manuscript provides in vitro and in vivo evidence that a bacterial factor (IncV) requires phosphorylation by host kinase(s) to interact with VAP and establish a contact site between the ER and the bacterial inclusion membrane.

Three different phosphorylation events are required. First CK2 is recruited to and phoshphorylates the c-terminus of IncV. Second, this leads to further phosphorylation of residues surrounding two FFAT motifs, strengthening the interaction with VAP. Third, one of the FFAT motifs is a phospho-FFAT and requires phosphorylation of a specific threonine by an unknown kinase.

The story is interesting and the experiments carefully executed.

The phosphorylation of IncV by CK2 and its effect on VAP binding are clearly demonstrated using phosphonull and phosphomimic mutants.

Clarification is nonetheless required concerning the chain of phosphorylation events required for VAP binding, and whether they are successive or unrelated but converging on changing affinity for VAP.

Reviewer #2 (Public Review):

This study investigates the membrane contact sites (MSCs) between the C. trachomatis inclusion and the host endoplasmic reticulum (ER). The MCS is mediated by the interaction between the pathogen factor IncV (localising to the C. trachomatis inclusion) and the ER host factor VAP. The manuscript offers new insights into the biology of IncV and VAP interaction and, in addition, identifies a novel key factor critical for host ER association with the C. trachomatis inclusion.

The manuscript presents its scientific findings in three major parts.

First, the authors provide in vitro data indicating that the C. trachomatis factor IncV is phosphorylated, most likely by an unknown host factor. Based on data available in the literature, the authors hypothesised that the host kinase CK2 phosphorylates IncV.

Second, the study proceeds to investigate the function of the host kinase CK2 in IncV phosphorylation in vitro and during C. trachomatis infection. In vitro binding assays show that phosphorylation of IncV is necessary and sufficient to promote the interaction between IncV and VAP. In addition, in vitro binding assays also suggest that CK2-mediated IncV phosphorylation is necessary and sufficient to promote interaction between IncV and VAP. Subsequently, the study presents experiments during C. trachomatis infection to illustrate the function of CK2 in mediating the interaction between IncV and VAP. Partial siRNA knock-down of host CK2 and inhibition of CK2 with CX4945 suggest IncV phosphorylation via CK2 in the host cell. When CK2 inhibitor CX4945 is applied at different concentrations, a dose-dependent reduction of VAP association to the C. trachomatis inclusion can be observed via IFA.

Lastly, domains and residues of IncV that are phosphorylated and serve as binding domains for the CK2 kinase or VAP are identified. Experiments using IncV mutants identify three serine residues at the C-terminus of IncV to be critical for CK2 binding and IncV phosphorylation. However, in vitro data suggest that phosphorylation of the three serine residues alone is not sufficient to mediate IncV-VAP interaction. Indeed, the phosphorylation of serine tracts upstream of the IncV FFAT motifs appear to mediate the IncV-VAP interaction. Preventing phosphorylation of these serine tracts by substituting the endogenous serine residues with alanine abolished VAP recruitment to the C. trachomatis inclusion in the host cell, but not recruitment of CK2.

Overall, I find the conclusions of this manuscript are mostly well supported by the presented data. Some aspects of the paper, however, would benefit from further experiments and clarification.

Strengths of the manuscript:

The manuscript is well written and the authors present their scientific reasoning in a clear manner. The experimental data presented here are put into the context of previous findings regarding IncV (Stanhope et al., 2017), making it easy for the reader to follow the path of scientific discovery.

The in vitro binding and phosphorylation assays clearly define the requirements for the interaction between IncV and VAP. The need for CK2-dependent phosphorylation of IncV for VAP recruitment to the inclusion is convincingly demonstrated. Overall, the in vitro experiments are thoroughly executed and support the author's conclusions.<br /> It remains a constant question in the field of trans-kingdom MCS how proteins from the pathogen are able to interact with host factors. Murray and colleagues put forward a very relevant finding by providing data that would indicate pathogen mimicry of host protein features to enable host organelle recruitment. All in all, this paper significantly contributes to our understanding of trans-kingdom MCS between the pathogen and the host.

Weaknesses of the manuscript:

Although immunofluorescence combined with confocal microscopy represents one of major experimental tools to analyse the association of IncV, CK2 and VAP to the C. trachomatis inclusion, the methodology is not depicted in a comprehensible manner. The procedure itself is described in the Material and Methods section of the paper. However, it remains unclear how the authors conducted the analysis of their immunofluorescence data. A representative schematic demonstrating the complexity of the procedure, including the generation of 3D objects and the normalization of fluorescence intensity, would create more clarity about the methodology used in this study.

The data for CK2 during C. trachomatis infection of a host cell is not entirely convincing. One, the knockdown of CK2 via siRNAs was not complete. Despite rigorous analysis, the conclusions drawn from these data are not very strong. Second, the inhibition of CK2 with CX4945 has an inherent weakness since secondary effects on other host cell processes cannot be excluded. Nonetheless, the entirety of the data provides logical indications for the function of CK2 during C. trachomatis infection, despite the weaknesses of the individual experimental set-ups.

The manuscript lacks clarity regarding the details of CK2 function and IncV phosphorylation. The provided in vitro data can be interpreted such that CK2 is sufficient to cause IncV phosphorylation and to mediate interaction with VAP. However, in the discussion section, the authors argue that other kinases must be involved in the phosphorylation of the serine tracts upstream of the FFAT domain since phospho-FFAT is not a CK2 target (lines 354-355). However, no reference is provided to support this statement and no further insight into this reasoning is given. This makes it difficult for the reader to understand the final conclusion about CK2 phosphorylation.<br /> The final model proposes a sequential binding of CK2 and VAP to IncV during C. trachomatis infection. CK2 binds to IncV first to mediate IncV phosphorylation, thus promoting VAP binding. While in vitro data could be interpreted this way, data obtained from host cells infected with C. trachomatis does not strengthen the subsequential nature of the model. It would support the model to show an scenario during the infection with C. trachomatis in which VAP is absent from the C. trachomatis inclusion despite the presence of CK2. If the model stands true, this could be achieved with a CK2 variant unable to phosphorylate IncV.

Interestingly, the manuscript offers an experimental set up that could show the above scenario. The paper presents an IncV S/A variant in which the serines from the serine-rich tracts upstream of IncV FFAT motifs are substituted with alanine, an amino acid that cannot be phosphorylated. When expressing the IncVS/A variant in C. trachomatis, CK2 still localises to the inclusion while VAP is absent. However, since the authors argue that CK2 cannot phosphorylate the serine-rich tracts upstream of IncV FFAT motifs, this observation is not suitable to support the model that the authors are proposing.

Overall, the author's conclusions regarding the details of CK2-dependent phosphorylation of CK2 during C. trachomatis infection are difficult to follow in the current manuscript.

Reviewer #1 (Public Review):

Gut microbiome variation is relevant to host health. In turn, the environment provided by the host influences gut microbiome community composition. Recent studies suggest that this environment is at least in part shaped by host genetics, making microbial abundances in the gut a heritable class of traits. Here, Doms et al use a powerful crossing design in hybrid mice (Mus musculus musculus x Mus musculus domesticus, derived from a well-studied hybrid zone in Europe) to estimate heritability, map genetic associations with microbial taxon abundance, and link within-species heritability estimates to macroevolutionary patterns of phylosymbiosis (i.e., diversification in gut microbes that mirrors diversification in their hosts).

Strengths of the manuscript include the clever use of a crossing design with mostly inbred hybrid lines as founders, which confers impressive power, and integration of the mouse data with external estimates of co-speciation rates to test for predictors of phylosymbiosis. The latter result, in particular, suggests a potentially generalizable principle for why some microbes are closely associated with host phylogenies, while others are not. The authors also analyze 16S rRNA data from both DNA (the typical approach in 16S studies) and RNA, which generates largely concordant but complementary results. Together, these analyses generate a substantial number of candidate genotype-microbiome phenotype associations, several of which replicate previous findings but many of which are new.

In their current form, however, it is not clear how robust some of these analyses are. Neither the heritability analyses or mapping analyses control for technical or biological covariates/confounders. It is extremely rare that genomic data sets are free of technical or batch effects; housing conditions, experimental timing, or other factors could also influence heritability and/or mapping estimates. Additionally, because the study population includes both recent kin and historically admixed individuals, controlling for relatedness in the mapping analysis may not be sufficient to control for genetic structure. These possibilities should be probed further, and even if they don't affect the results, the supporting analyses should be shown.

Finally, the most interesting results surround the mapping and genetic architecture results, especially the possibility that genetic architecture predicts phylosymbiosis. However, the results section feels asymmetrically focused on the descriptive results of many different enrichment analyses. While these kinds of analyses can provide context, the paper would benefit from sharpening, and potentially shortening, this section, especially where the motivation for a given analysis is unclear.

Reviewer #2 (Public Review):

This study maps the genetic determinants of gut microbiota composition through laboratory crossing experiments using two subspecies of mice: Mus musculus domesticus and Mus musculus musculus.

A major strength of the study is the generation of a large experimental population of mice reared under controlled conditions, providing unprecedented resolution for identifying associations between host genotype and the microbiota. In contrast to previous mouse microbiota QTL mapping studies, this work uses relatively outbred and genetically diverse mouse lines, thereby capturing a higher levels of genetic variation and providing greater power to detect genotype-microbiota associations.

Another strength of the work is its focus on mucosal associated microbiota, as these communities are expected to be most affected by direct interactions with host cells and their products. Previous work in this area has focused only on either fecal or cecal microbiota.

The molecular and statistical methods employed were appropriate to address the questions posed, and the results supported the study's conclusions.

Cumulatively, this study provides a list of mammalian genomic loci that appear to influence the composition of the gut microbiota, including several loci associated with human diseases. Identification of these candidates set the stage for future functional genetics studies that employ gene editing approaches to directly test host genotype-microbiota interactions.

Reviewer #3 (Public Review):

This is an interesting study by Doms et al., reporting on using inbred mouse lines to genetically map loci in the mouse genome that are associated with the composition of the microbiome.

The study has several strengths:: it focuses on the mucosa-associated microbiome, which more directly interacts with host cells, while previous studies used fecal microbiome data. In addition, the correlation between heritability estimates and cospeciation rate estimates is a novel result. The finding that ​​16S rRNA transcript profiling allows for detecting more heritable taxa is also a relevant result that will be interesting for the field.

Although the study is important, there is one major point of concern, relating to the heritability estimates reported in the paper. The heritability results may be a bit surprising considering the current knowledge and literature: the heritability values are very high, with several values around 90% or higher. This is unexpected, and I am not sure how this is reconciled with the expectation that most variation in the microbiome is environmental rather than genetic. Although some potential reasons are given in the Discussion (mice raised in a controlled environment, using cecal content, etc), these values are substantially higher than can be expected.

Reviewer #1 (Public Review):

A clear strength of the present manuscript is its scientific rigor. The authors put a lot of emphasis on transparent reporting and pre-registered their hypotheses. The within-person experimental design is well constructed and deals upfront with several potential confounds. All in all, the experimental design allowed a replication and extension of findings related to evoked neural responses due to auditory presentation during sleep.

Nevertheless, the exact neural mechanisms that should drive sleep-dependent learning gains due to reactivation remain elusive. In part this is due to analytical choices - especially with regard to the phase-amplitude coupling analyses. For example, it remains to be established that there is a reliable coupling of SOs and SPs before any condition specific analyses appear appropriate.

Reviewer #2 (Public Review):

The work by Nicolas et al. investigates neurophysiological processes in response to sound cues delivered during sleep. Importantly, the presented sound cues were previously associated with a motor sequence participants had to practice. By presenting the sound cues during sleep, performance in pressing the motor sequence was increased (targeted memory reactivation, TMR). At the neural level, presenting sound cues associated with a motor sequence resulted in a higher amplitude (of the evoked response as well as of spontaneous slow waves) than presenting sound cues without any association. Further, the precise interplay between slow and sigma oscillations correlated with the behavioural TMR benefit.

This finding is of high interest. However, some aspects of the analyses have to be clarified and the interpretation of sigma oscillations protecting motor memory (by being nested in the trough of the slow oscillation peak) has to be more substantiated by further results.

Strengths:

The study is elegantly designed (within-subjects design) and allows for testing the proposed hypotheses. The study as a sleep study is well controlled for example by incorporating a habituation nap, by using actigraphy during three nights before the learning nap and by measuring vigilance objectively as well as subjectively.

One of the biggest strengths of the study is its pre-registration. The authors did not just pre-registered the study but moreover highlight and justify any deviation from the pre-registration and state whether an analysis was planned or exploratory. Thus, the whole research process is very transparent and plausible.

Weaknesses:

(1) The interpretation of sigma oscillations protecting motor memories (i.e., sigma power towards unassociated sound cues is increased in the trough of an evoked potential) is not very well substantiated by the results.

(2) The motivation for some analysis decisions is not always clear. To highlight one example, it is unclear why the authors average the data across channels. Previous findings demonstrate that slow oscillations and sleep spindles vary across the scalp (Klinzing et al. (2016), Cox et al. (2017)). Thus, averaging across all channels potentially introduces more noise.

(3) The description of some methods has to be more precise (for example the detection of slow waves and sleep spindles and specifically the phase coupling).

Reviewer #3 (Public Review):

Nicolas et al. performed a nap study in healthy humans to examine the temporal dynamics of sleep oscillations during procedural memory consolidation. To this end, the authors used targeted memory reactivation (TMR) to re-expose participants during a nap to a sound cue previously associated with a finger tapping sequence. As control conditions serve (i) a second encoded sequence with a sound that is not played during sleep, (ii) a novel control cue not heard during prior wakefulness and (iii) so-called rest-periods during which no cueing was performed. Behaviorally, the authors confirm the beneficial effect of TMR as participants perform better (faster) on the reactivated sequence in comparison to the not-reactivated sequence after their nap and even after an additional night spent at home.

Electroencephalography recordings acquired during the nap then revealed that TMR cues evoked stronger responses than control cues hinting a distinct processing of familiar and memory-related cues. This is supported by a general analysis 0.5 to 2 Hz slow waves, one fundamental sleep oscillation linked to memory consolidation, which showed higher densities during intervals of real-cueing. Interestingly, the density of 12-16 Hz sleep spindles was not influenced, however, their frequency decreased and amplitude increased. Finally, the authors assessed the coupling between slow waves and sleep spindles, which rather counter-intuitively showed an increased coupling during intervals cued with control sounds. Moreover, the stronger this coupling the higher the TMR benefit.

Altogether, this data revealed an interesting slow wave-spindle dynamic underlying the processing of familiar and unfamiliar auditory cues and scrutinizes how these brain rhythms mediate memory consolidation

Overall, this is a very well-designed experiment and I salute that it has been pre-registered and how transparent everything has been reported. Moreover, the utilization of a control sound during sleep is currently rarely taken advantage of during TMR study, while they can add important insights. While the analysis pipeline is appropriate and well-rounded, some aspects need to be clarified and extended.

Response to control sounds:

It is very surprising that the response to control sounds is, apart from an early evoked component around 100 ms, almost nonexistent. Auditory stimuli are overall known to normally evoke K-complexes and strong spindle responses. Could it be that for some reason control sounds were lower in volume or do they lead to a stronger habituation? Control analysis might help to ensure that there is really no confusion. For example, ERP at the beginning and end of each stimulation interval could be contrasted. Moreover, the authors state that sound cues were balanced across subjects. However, they also state that the volume was adapted for each sound individually. Additional data or statistics on these volume, randomization and cued slow wave phase might be very helpful.

Discrete slow wave analysis:

It is reported that the offline detection of slow waves yielded identical numbers across conditions, but this contradicts the later reported differences in densities. If this is true, it implies that the total time during which real cues and control cues were presented as well as the cueing paused (i.e., the rest intervals) differs within subjects. It needs to be ensured that effective stimulation times are comparable between subjects and are not confounded by unfair comparisons

Statistical results:

Consistently across all cluster-based statistics, significant clusters somehow do not reflect the underlying colormaps. One would expect that significances are driven by clusters of greatest difference (Figure 6B and C). That something might be amiss, is reflected in the statement that a contrast of TFRs for real and control cues revealed no significant cluster, although this contrast shown in Figure 7a clear depicts two cluster with strong power differences (before 500 ms around 8 Hz, and after 500 ms around 20 Hz).

Moreover, follow-up analysis revolving around sleep spindles are based on inconsistent frequency ranges. For one analysis a prior significant cluster is used (Figure 8) while for the other it is limited to 12- 16 Hz and a much shorter time window than the overall cluster (Figure 7), even in the pre-registered 12-16 Hz window. Overall, these analyses should be checked and streamlined.

Reviewer #1 (Public Review):

The manuscript "Crotamiton derivative JM03 extends lifespan and improves oxidative and hypertonic stress resistance in Caenorhabditis elegans via inhibiting OSM" by Bao et al. details a drug screen and optimization of a lead compound. Overall I am positive about this manuscript. The screen is of substantial size and appears well conducted. The n-number per condition is relatively small, but this mainly means that the screen will have missed some hits as false positives would be caught by subsequent confirmation studies. The second part of the manuscript then details validation and optimization of one hit of the screen, crotamiton. The authors carry out confirmation, some validation of a likely target and some medicinal chemistry / drug optimization. While there are some limitations to this part of the study, the study is valuable, both in terms of the specific drug investigated and as a template for future studies.

Reviewer #2 (Public Review):

Bao and colleagues present a chemical genetics study to identify novel compounds extending lifespan in C. elegans and investigate the mechanisms of action of their most potent compound JM03 derived from their primary hit crotamiton. Among to strong parts of the paper are the reasonable size of the screen of over 1000 compounds. The screen covers a substantial sector of pharmacological activity. Following the screen, they conducted structure-activity relationship studies to improve the drug's potency and succeed in that attempt. Few anti-aging compound screens in the literature have followed a screen with a structure-activity relationship study to optimize the primary hit. The follow-up and improvement of the primary hit by medicinal chemistry are one of the stronger points of the paper. Their main compound, JM03, extends lifespan and improves health span, pharyngeal pumping, locomotion, and does not seem to affect brood size, all signs of a drug increasing health span. Because the target for the original drug crotamiton is known (TRPV4), they investigate the C.elegans homologs osm-9 and ocr-2. They find osm-9 mutants to be resistant to the longevity effect of JM03. This finding makes osm-9 a likely mechanistic target of JM03. However, because JM03 is a compound that was optimized based on lifespan and because the original drug crotamiton has not been shown to bind osm-9 (only TRPV4), the evidence is not yet sufficient to claim osm-9 to be the mechanistic target of JM03. Any experiment that would show that JM03 directly interacts with osm-9 or modulates the activity in vitro would make this paper much stronger and allow the authors to claim having identified the mechanistic target of JM03. The lack of an experiment that demonstrates a direct interaction is not a weakness in the paper but more a missed opportunity to add real strength to the paper, given that all the evidence they have pointed to osm-9 as a target.

There are a few weaknesses too. The cohort size of 15 animals/drugs during the screen suggests that there must have been a substantial amount of false negatives. That cohort size only detects 50% of all drugs that extend lifespan by 20% and miss roughly 80% of the drugs that extend lifespan by 10%, the cut-off criteria for hits. There is nothing wrong with this strategy, but the text should clearly state that not having found the effect of a drug in a screen is not evidence for the absence of an effect. Similarly, the effect of the JM03 is relatively small, making it more difficult to show that there is no effect in a given strain. To show the absence of an effect in osm-9, the authors use cohorts of roughly 150 animals in each arm to ensure that they can detect a longevity effect if it is present. The source data show that they used enough animals for figure 3 (10 x15 animals) and should detect a longevity effect of JM03 if there were one in osm-9. However, all the animals combined amounts to essentially one experiment, and a second repeat of that size is necessary for a firm conclusion in the paper. A final potential weakness may be in the RNAseq data. From the cluster analysis shown in Fig. 4i, it seems that the three replicates of treated and untreated samples are not very similar to each other. A principal component (PCA) plot that shows that the three control and 3 JM03 treated samples cluster would strengthen the confidence in the data and provide more substantial support for the conclusions in Figure 4.

Overall, the authors aim to identify new anti-aging compounds as well as the underlying mechanism of action. They largely succeed in these aims. The relatively small effect of the lifespan extension makes testing and validating the underlying mechanisms of action more difficult as the ~15% increase requires them to test large cohorts, but overall this is done well. This paper is one of the few in which the authors conduct medicinal chemistry to improve upon the longevity effect of their primary hit one aspect that makes notable compared to other, similar papers.

Compounds targeting TRPV channels like JM03 to slow aging is an interesting concept, particularly since Riera et al. (Cell 2014) have shown that lowering signaling by TRPV channels can also extend lifespan in mice. Identifying a compound that achieves the same, found in an unbiased chemical screen, suggests that TRPV channels may make a druggable target for aging that is evolutionarily conserved.

Reviewer #1 (Public Review):

Wang et al. investigated the roles of over-expressed microRNAs (miRs) in a Drosophila tumor model caused by concomitant clonal gain of RasV12 and clonal loss of Discs large in developing epithelia. They identified miR-306 and miR-79 from the same miR cluster as able to reduce tumor growth significantly when over-expressed in the tumor cells. These miRs were shown to target the 3'UTR of the ubiquitin ligase Rnf146, causing Rnf146 protein downregulation. It has already been established in the field that Rnf146 interacts with poly-ADP-ribose polymerases called Tankyrases (TNKs) to target proteins for degradation and that TNKs activate JNK signaling. The authors find that over-expressed Rnf146 can downregulate TNKs and JNK signaling in cultured S2 cells and in Drosophila tumors. The authors propose that miR-306 and -79 directly target Rnf146, which results in elevated TNK and this induces JNK signaling and causes the death of tumors.

The novelty of this study is identifying Rnf146 as a target of miR-306 and miR-79. The connections between Rnf146-TNK and TNK-JNK were already known from the work of others. A main conclusion of the paper - that these miRs could be used as cancer therapeutics - is not strongly supported by the data because in some experiments over-expression of these miRs negatively affected WT cells, and this undermines the authors' conclusion that miR over-expression does not affect the growth of WT cells. Strengths of the paper are: the use of powerful clonal techniques to make, monitor and measure tumors, and the proper analysis and quantification of some of the results. However, some of the data analyses need to be clarified and extended.

Reviewer #2 (Public Review):

This is a very straightforward manuscript by the laboratory of Tatsushi Igaki in Kyoto, Japan. The authors identify a number of miRNAs whose expression in RasV12/dlg- tumors suppresses tumor growth. They also show that several of these miRNAs suppress RasV12/lgl- tumor growth. They focus on two of these miRNAs, miR-79 and miR-306, and worked out the mechanism by which these miRNAs act as tumor suppressors. First, they show that expression of these miRNAs induces apoptosis in RasV12/dlg- tumor and RasV12/lgl- clones. They then show that miR-79 and mi-306 increase JNK signaling in these tumor clones. Inhibition of JNK by bskDN restores tumor growth, suggesting that the tumor suppressive function of these miRNAs goes through JNK signaling. Interestingly also, the tumor suppressive function of these miRNA is dependent on the dlg- component and not on RasV12. They then show that other tumor types which are associated with increased JNK signaling (PVR, Src64B) can also be suppressed by expression of these miRNAs. Using bioinformatics, they identified 11 potential mRNA targets of these miRNAs. Only one of them, encoding the Ringfinger protein dRNF146, accounts for the increased JNK activation and the authors show that dRNF146 is a direct target of these miRNAs. It was previously shown that dRNF146 can target the poly-ADP-ribose polymerase Tankyrase for degradation. Tankyrase can promote JNK phosphorylation and activation in a non-canonical manner. The authors performed a number of elegant experiments and essentially confirmed that Tankyrase degradation is blocked in these tumor clones when miR-79 and -306 were overexpressed.

Overall, this is a very nice and straightforward manuscript. It presents a tumor suppressor mechanism which exploits tumor-promoting JNK activity in tumor cells by overactivating it so that the tumor cells die by JNK-induced apoptosis. The mechanism in this manuscript is very well worked out. A large number of controls were done. The data are very convincing, very well quantified and well presented. The manuscript is also very well written and very easy to read. I did not detect any significant weakness.

Reviewer #3 (Public Review):

In this M, Wang and cols use the Drosophila Ras-Dlg tumor model to search for miRNAs with a tumor suppressive role. The authors identify two miRNAs - namely miR-306 and miR-79, as elements that reduce oncogenic growth but do not affect normal growth. After, the authors try to identify the mechanisms by which these miRNAs limit tumor growth. The authors claim that the axis dNRF146-Tnks enhances JNK activity inducing apoptosis in tumor cells. The authors propose an exciting synthetic lethality interaction between the tumor background and these miRNAs. However, the conclusions obtained are not well-supported by the results presented here.

The authors claim that miR-306/79 over-expression and dRNF146 downregulation enhances JNK activation in tumor cells. This is based on different correlations but changes in JNK activity in those genetic contexts are not shown.

The results suggesting that dRNF146 is a miR-306/79 target gene with physiological relevance are very poor.

This work is based in the comparison between many very complex genetic backgrounds. However, most of those experiments lack the control experiments that will allow to compare those conditions properly.

Finally, the connection between dRNF146, Tnks, and JNK has been previously established and it is not novel.

Reviewer #1 (Public Review):

This paper compares output signals from the mouse retina in three conditions: awake mice, anaesthetized mice, and isolated retinas. The paper reports substantial differences, particularly between awake and either of the other conditions. Retinal signaling has been well studied using ex vivo preparations, with an assumption that the findings from those studies can be carried over to how the retina operates in vivo. The results from this paper at a minimum indicate a need to be cautious about that assumption. There are several technical issues that need testing or further explanation, and several issues about the presentation that could be clarified.

Spike sorting<br /> The paper does not describe any control analyses that test for contamination in spike sorting. These are needed to evaluate the work.

Light levels<br /> The paper argues that differences in light level cannot account for the results. According to the methods, light levels were about two-fold higher at the retina in array recordings as compared to the front of the eye for in vivo recordings. The main text indicates that they differ less, it's not clear why the numbers in the main text and methods are different. Aside from this issue, this comparison does not consider the loss of light between the front of the eye and the retina. It is crucial that the paper provide a more detailed description of light levels. This should include converting those light levels to units that include the spectral output of the light source used (e.g. to isomerizations per rod or cone per second).

Comparison with other work<br /> The authors accurately point out that there is not much prior work on retinal outputs in awake animals. The paper, however, minimally describes the work that does exist. The Hong et al. (2018) paper, in particular, should be discussed. There are several differences between the results of that paper and the present paper. These include the fraction of recorded cells that are DS cells, and the maintained firing rates (though this does not appear to be studied systematically in Hong et al.).<br /> A related issue is that there are a few comparisons of ex vivo RGC responses with behavioral sensitivity. Smeds et al. (2019) is one example. More generally, the long-standing observation that dark-adapted sensitivity approaches limits set by Poisson fluctuations in photon absorption, and that prior RGC measurements are consistent with this result, is hard to explain if the RGCs are firing at high spontaneous rates under these conditions. RGC responses will certainly change with light level, but this merits discussion in the paper.

Sampling bias<br /> The paper argues that sampling bias is not likely to contribute substantially to the results because of the wide variety of cell types recorded (line 431). This does not seem like a particularly strong argument, especially given the large degree of overlap in the distributions of most quantities across preparations. The argument about many cell types could be made more strongly if the distributions were completely separated, but that is not the case.

Sensitivity<br /> The firing rates in response to 10% contrast sinusoids are quite low, as are the maximal firing rates for high contrast sinusoids. Relatedly, the modulation produced by the noise stimuli, particularly for the array recordings, is weak. This raises concerns about the health of some of the preparations.

Efficient coding<br /> Sparse firing is not a universal property of retinal ganglion cell responses. Primate midget RGCs, for example, have pretty high maintained firing rates as shown in many past studies. Mouse RGCs have also been reported to operate in a mode similar to the high firing rate On cells reported here (Ke et al. 2014). A more balanced discussion of this past work is needed.

Role of eye movements<br /> Could eye movements be at least partially responsible for the differences in response properties? Specifically, small fixational eye movements might produce a constantly varying input that could modulate firing.

Reviewer #2 (Public Review):

The technical achievements presented in the manuscript represent a tour de force, as optical tract recordings in awake mice have only rarely been done before. The substantial number of neurons recorded in both awake and anaesthetized conditions form a precious and world-wide unique dataset. However, since the recordings represent a non-standard approach, it would be, in my view, highly beneficial to show more details about the success of the method. How did the authors post-hoc identify electrode contacts located in the optical tract, how did the spike waveforms look like, what were the metrics of spike sorting quality, etc.

The authors go a long way in characterising the functional response properties of the recorded neurons and relating them to previous ex-vivo recordings. Based on the responses they find, the authors claim that they identified "... a new response type [which] likely emerged due to high baseline firing in awake mice". Regarding this claim, how do the authors rule out that it corresponds to any of the previously described cell types? For instance, the very sharp transient or brief modulations by the contrast part of the stimulus might have been missed in previous classifications based on calcium responses (e.g. Baden et al. 2016), where a number of cell types seem to respond equally strong to grey and white and have an elevated response throughout the sinusoidal modulation of contrast. I acknowledge that the authors touch upon the possibility that the newly described OFF-suppressive ON cells correspond to a known cell type in the discussion, but I would recommend changing the phrasing of the results to avoid potential misunderstandings.

The manuscript makes the interesting suggestion that "the retinal output characteristics [...] observed in vivo, [...] provide a completely different view on the retinal code". Given that this conclusion would change the way we should think about and do retinal neuroscience, in my view, the authors should take a few more steps to quantitatively demonstrate the implications of their findings on retinal coding, e.g. how much lower is the information transmitted per spike, how much does a temporal code based on spike timing suffer with the latencies observed in vivo. If the authors could quantify through computational modelling approaches the consequences of the observed differences, they might also be able to revise their title / main message, i.e. that "Awake responses suggest inefficient dense coding in the mouse retina".

Reviewer #3 (Public Review):

The manuscript by Boissonnet, Tripodi, and Asari compares retinal ganglion cell (RGC) light responses in awake mice (recorded in the optic nerve) with those under two forms for anaesthesia and previously attained ex vivo recordings. This is a well motivated study looking at a question that is really critical to the field.

The presentation is generally clear and compelling. My suggestions are relatively minor and aimed at improving an already very strong article.

1. More cells in the awake condition would help strengthen the conclusions. Only 51 cells are reported, and mouse RGCs comprise more than 40 different types. The authors are well aware of the possible confound of sampling bias, and the best way to mitigate this issue in this experimental paradigm is simply to record more cells. The anesthsia conditions each have about 100 cells, which is better.

2. It took me longer than it should have (had to look up the previous paper cited) to figure out that the ex vivo comparison data were recorded at 37{degree sign}C. This is an important detail since most ex vivo recordings are at 32{degree sign}C. The authors should make this clear in the text and perhaps say something in the Discussion about comparisons to the larger body of literature of ex vivo studies at 32{degree sign}.

3. Direction and orientation selectivity should be separated in Fig. 2 and not combined into the confusing term "motion sensitive." Motion sensitivity has another meaning in the literature for RGCs that respond preferentially to moving over static stimuli without direction or orientation preference (Kuo et al., 2016; Manookin et al., 2018)

4. While I am certainly sympathetic to the argument that the RGC spike code is "inefficient" in the sense that it does not conform to efficient coding theory (ETC), I think it's oversimplified to claim that the present data is a key argument against ETC. Plenty of ex vivo data has already shown ETC to be incomplete at best, and misguided at worst, since it includes the implicit assumption that image reconstruction is the retina's objective function (or even that the experimenter has any idea what that objective function is). For example, OFF sustained alpha (OFF delta in guinea pig) RGCs are not quite sparse feature detectors even ex vivo, and they seem to be optimized to transmit contrast with high SNR (Homann and Freed, 2017). In general, the enormous coverage factor of the RGC population seems to make ETC untenable to begin with, as discussed in (Schwartz, 2021) and elsewhere. I realize that there are still people attached to simplistic forms of ETC as a key principle of retinal computation, so I am not asking for the authors to completely remove this angle. Rather, a more nuanced treatment of the issue both in the introduction and the discussion is warranted.

References<br /> Homann, J., and Freed, M.A. (2017). A mammalian retinal ganglion cell implements a neuronal computation that maximizes the SNR of its postsynaptic currents. Journal of Neuroscience 37, 1468-1478.<br /> Kuo, S.P., Schwartz, G.W., and Rieke, F. (2016). Nonlinear Spatiotemporal Integration by Electrical and Chemical Synapses in the Retina. Neuron 90, 320-332.<br /> Manookin, M.B., Patterson, S.S., and Linehan, C.M. (2018). Neural Mechanisms Mediating Motion Sensitivity in Parasol Ganglion Cells of the Primate Retina. Neuron 97, 1327-1340.e4.<br /> Schwartz, G.W. (2021). Retinal Computation (Academic Press).

Reviewer #1 (Public Review):

In this paper, Romero-Becerra et al report their findings on MKK6 deficiency in the heart. They show that global deletion of MKK6 reduces life span in mice. They also show that young mice have cardiac hypertrophy and that it progresses to cardiac dilatation and fibrosis as they age. Their mechanistic studies demonstrate that MKK6 deletion leads to reduced p38a activation but at the same time causes MKK3-p38g/d hyperphosphorylation and increased mTOR signaling. The activation of this pathway then results in cardiac hypertrophy. To confirm the role of this pathway, they show that cardiac hypertrophy in Mkk6-/- mice is reversed with deletion of either p38g or p38d, or with rapamycin treatment. They also demonstrate similar findings in cardiac specific MKK6 KO mice. They conclude that they have identified "a key role for the MKK3/6-p38g/d pathway in the development of cardiac hypertrophy, which has important implications for the clinical use of p38a inhibitors in the long-term treatment since they might result in cardiotoxicity".

This paper is interesting and the experiments are conducted carefully. However, a lot is already known about MKK proteins and their downstream targets P38 proteins. For example, Martindale et al in 2005 showed that overexpression of MKK6 in the heart proteins protects against MI (J Biol Chem. 2005 Jan 7;280(1):669-76). This paper is not even referenced in the manuscript. Additionally, a lot is known about the effects of MKK6 on P38 proteins, but the authors fail to highlight the novelty of their paper over previously published papers. Additionally, some of the experiments are not carefully conducted or interpreted and additional experiments or explanation is needed for those figures.

Reviewer #2 (Public Review):

In this manuscript, Romero-Becerra et al. utilize molecular biology techniques to fill a key gap in the field - how different p38 MAPK isoforms are regulated, as well as the contributions of MKK3 and MKK6 to cardiac hypertrophy. The strengths of the paper include the generation and characterization of multiple novel mouse models for in vivo modulation the MKK3/6-p38 signaling pathway. The work has implications for the clinical use of p38a inhibitors and is likely to be highly impactful in the field of cardiovascular mTOR biology.

Reviewer #3 (Public Review):

This study demonstrates that 9-week-old mice with systemic MKK6 gene deletion exhibit cardiac hypertrophy with preserved cardiac function. Similar results were observed in mice with cardiomyocyte-restricted MKK6 gene deletion. On the other hand, aged MKK6 -/- mice progressively develop cardiac dysfunction and fibrosis. Deletion of the MKK6 gene leads to decreased p38α phosphorylation and increased MKK3/p38γ/δ pathway activation. The latter is associated with mTOR overactivation and protein synthesis. Concomitant deletion of p38γ or p38δ, as well as inhibition of mTOR with rapamycin, rescue hypertrophy in 9-week-old MKK6 -/- mice.

In general, this paper is interesting. The demonstration of a crosstalk between MKK6 and 3 involving p38 isoforms and mTOR is intriguing. However, there are some important issues that need to be addressed. In some cases, data are associative and additional experiments are needed to better dissect the molecular mechanisms underlying the cardiac effects of MKK6 gene deletion. In particular, it is not clear whether MKK6 restrains cardiac growth by MKK3 inhibition or p38α activation. Additional experiments are needed to clarify the molecular mechanisms through which p38γ/δ and mTOR are activated in MKK6 -/- mice. Cause of death in MKK6 -/- mice should also be studied.

Reviewer #1 (Public Review):

Jo et al. use a combination of micropatterned differentiation, single cell RNA sequencing and pharmacological treatments to study primordial germ cell (PGC) differentiation starting from human pluripotent stem cells. Geometrical confinement in conjunction with a pre-differentiation step allowed the authors to reach remarkable differentiation efficiencies. While Minn et al. already reported the presence of PGC-like cells in micropatterned differentiating human cultures by scRNA-Seq (as acknowledged by the authors), the careful characterization of the PGC-like population using immunostainings and scRNA-Seq is a strength of the manuscript. The attempt at mechanistically dissecting the signaling pathways required for PGC fate specification is somehow weaker. The authors do not present sufficient evidence supporting the ability to specify PGC fate in the absence of Wnt signaling and the importance of the relative signaling levels of BMP to Nodal pathways; the wording of the text should be amended to better reflect the presented evidence or the authors should perform additional experiments to support these claims. The molecular characterization of why colonies confined to small areas differentiate much better would greatly increase the biological significance of the manuscript (the technical achievement of reaching such efficiency is impressive on its own).

The authors propose a mathematical model based on BMP and Nodal signaling that qualitatively recapitulate their experimental data. While the authors should be commended for providing examples of other simple models that do not fully recapitulate their data, it would have been nice to see an attempt at challenging quantitatively the model. In particular, the authors do not take advantage of the ability to explore in a more systematic manner the BMP/Nodal phase space with their system.

The authors' claim that PGCLC formation can be rescued by exogenous Activin when blocking endogenous Wnt production is surprising given the literature. The authors only show that they can restore a TFAP2C+SOX17+ population but do not actually stain for an established germ cell marker. It appears essential to perform a PRDM1 staining in these conditions (Figure 4A) to unambiguously identify this population.

The authors only provide weak evidence that the fates depend on the relative signaling levels of BMP and Nodal. Indeed, fewer cells acquire a fate the lower BMP concentration they use, including the fates marked by Sox17 expression. It would more convincing to show the assay of Figure 4F for a range of BMP concentrations at which the overall differentiation works sufficiently well.

Reviewer #2 (Public Review):

This manuscript uses a micropatterned differentiation system to explore the mechanism of human primordial germ cell-like cell (hPGCLC) specification and proposes a previously un-recognized role of NODAL signaling operating downstream of BMP signaling. The strength of the manuscript is the development of a simple in vitro system that is potentially suitable for exploring the mechanism of human primordial germ cell-like cell (hPGCLC) specification. The weakness of the manuscript is the lack of rigorous validation of the identity of the hPGCLCs appeared in the micropatterned differentiation system and the lack of the discussion relevant to the in vivo developmental mechanisms.

Reviewer #1 (Public Review): 

This study reports on the inference of the evolutionary trajectory of two specialist species that evolved from one generalist species. The process of speciation is explained as an adaptive process and the changing genetic architecture of the process is analyzed in great detail. The genomic dataset is big and the inference from it solid. The authors reach the conclusion that introgression and de novo mutations, but not standing genetic variation, are the main players in this adaptive process. 

I would avoid the term adaptive radiation for the group of fish studied here. It is misleading. It is generally accepted to use the term adaptive radiation when a fairly large number of new species originate from a common ancestor (cichlids in big African lakes, gammarids in Lake Baikal, etc). Here are only 2 new lines that evolved from a common ancestor. Furthermore, I do not see much parallel between the ideas and concepts used when people study real adaptive radiations and one studied here. I actually believe that the term adaptive radiation even distracts from the beauty of the current study. 

The "Result and discussion" section has rather little discussion. There is not much about other systems or studies, neither in concepts nor in biology. The results are not linked to the bigger questions and the larger field. The same is true for the conclusion, which is very strongly centered on the here reported study. What can we learn from this study for other systems? Is there a generalizable take-home message? How do the findings relate to commonly held ideas/theory on how adaptive speciation works? Without this, it reads like a report of a case study, disconnected from the larger field. To achieve this aim, it may be good to split the main section into a result and a discussion section, but this is only a suggestion.

Reviewer #2 (Public Review): 

This is a really interesting and challenging question the authors are addressing here. I enjoyed reading the manuscript and a few comments below: 

One major concern I have concerns the analysis of the two treatments (low and high density, l411). I believe that the two treatments should analyzed separately as the authors are estimating two different fitness landscapes. When conducting their analysis, experiment is treated as a single factor. Yet, in Martin and Wainwrigth (2013), it was established that the fitness landscapes were quite different between the two treatments (Figure S7 of said paper), meaning that different phenotypes (and therefore genotypes) were affected differently. I do not think that the complex effect described there can be capture by a single factor as done here. 

A second major concern I have is in the use of the Admixture software (Figure 1 and l152.) The generalist type is assumed to be the ancestral type. Yet, a unique group was not assigned to it. This is a known problem for Admixture (Lawson et al. 2018). Groups that are under-sampled are far more likely to be consider a mixture of different ancestry groups even when this is impossible (Rasmussen et al 2010, Skolung et al 2012). While this in itself is not problematic, I am concerned about the use the authors are making of these ancestry proportions (l 156-165). The authors analyzed how ancestry of scale eater or molluscivore affect survival probability, growth, or the hybrid composite fitness. However, the ancestries values are partly generated due to an artefact, so I wonder how modelling the ancestral type as a group, and therefore acknowledging some amount of share ancestry between the three species may further affect this analysis. <br /> I understand the need to use subsets of a network, due to impossibly large dimension size of the network in the first place. However, subsetting said network may give the wrong impression of the whole network (Fragata et al 2019). I wish this point was further discussed here. 

L 294-295: I wonder whether the results here could be used to discuss the geometry of the different fitness peaks. The small number of steps within molluscivores suggest a rather narrow peak, while the rather large ones within the generalist suggest a rather flat fitness peak. The shape of the peak can be linked to the amount of genetic variation that can be maintained within populations, as well as the mutational load of said populations. 

L74-75 I would suggest to more cautious in the phrasing here. While this is true within Fisher geometric model, where population are assumed monomorphic and infinite, this is not true in general. Deleterious mutations can fix within populations, especially when drift is non negligible. Crossing fitness valleys has been quite widely investigated (see Weissman et al 2010 for example). Even the authors themselves mention it later (l 108). 

Lastly, I would be more cautious about the conclusion. Line 373-374, the authors mentioned that "de novo mutations may enable the crossing of a large fitness valley". Given that the authors focus only on adaptive walk (fitness always has to increase between each mutational step), there is no crossing of fitness valleys. Switching from one fitness peak to another is simply a matter of walking along a (very) narrow ridge.

Reviewer #3 (Public Review): 

This paper uses sophisticated regression methods and numerical experiments to produce a genotype-fitness relationship for three closely related sympatric pupfish species, forming an adaptive radiation. In addition to providing insights into the genetic targets of selection, this paper goes further in attempting to tease out what types of genetic variation were most likely to have played key roles in this radiation. 

Strengths: 

The idea behind this study is excellent, and clearly a large amount of thought and effort went into collecting the underlying data. The attention paid to linking evolutionary dynamics with the fitness results is laudable. The system is extremely exciting and I think an experiment and analysis of this sort could potentially be interesting to a broad audience within evolutionary biology. 

Weaknesses: 

The claim that this is the first genotypic fitness network in a vertebrate needs additional qualifiers: as far as I can tell, the claim to novelty is based on the inclusion of multiple species, the number of alleles, and measuring fitness in the field. I can't fully assess this claim but I would urge the authors to avoid staking a stronger claim to priority than is really needed, as it might be a lightening rod for criticism and hair-splitting that would distract from the contents of the paper. 

One of my major questions while reading this was whether these three species were better or worse adapted to subenvironments within the lakes. This is partially answered in a few places in the manuscript, but I think that resolving this point more precisely would help interpret if positioning all three species on the same fitness landscape is fair. 

I find it a little hard to follow the construction of the landscapes in Fig. 2 B and C. I am not clear why the landscapes don't cover the location of the molluscivore population. I think the fitnesses predicted for the main bulk of the generalists and scale-eaters are the same across the two landscapes (as I expect they would be), but this is obscured by the differing fitness ranges of the two landscapes. I would suggest using a single color-fitness relationship for the two panels to aid cross-comparison. Also, two salient features of the landscape-the major peak at the top center and the deep pit at the bottom center-seem to be supported by few fish in each case. I would imagine that something like boot-strapping could be done for fitness landscapes, where the support for each feature of the landscape could be judged by how often it appears in subsets of the data (or in inferred models with nearly as high support as the best model), but I acknowledge that might be very hard to do. Still, I think some statement of uncertainty should be prominently included. 

More generally, the landscapes reconstructed in Fig. 2 do not show very clear evidence that the M or S types are separated by valleys from the G type. Close inspection of the figure suggests a very shallow valley might be present between G and M, but the overall trend is declining fitness; between G and S, fitness appears to simply decline. While peaks may occur within the landscapes composed of limited sets of loci, the overall pattern seen in Fig. 2 doesn't seem conducive to analyzing how adaptive evolution in generalists crossed valleys to reach the putatively higher peaks of the two specialists. As such, I find the connection between these phenotypic-fitness landscapes and the later genotypic fitness landscapes quite confusing. 

I also had trouble understanding the role of fitness in the analysis of mutational distances in a subset of loci between the three species (lines 282-296). While the illustration in Fig. 3C uses directed edges to capture fitness data, this framework doesn't seem to be applied in Fig. 3d or the resulting analyses in 3e. As such, I don't see how this section is about genotypic fitness landscapes at all. 

The final part of the conclusion sketches a story in which de novo and introgressed alleles reduce the accessibility of reverse evolution, back to a generalist. I think this is conceptually confusing because we don't expect evolution to favor paths toward lower fitness, even if those paths do not pass through a valley. Again, the framing here-that generalists are less fit than either specialist-is hard to square with the facts that generalists seem to be coexisting with the specialists, and much closer to the hypothesized fitness peak than is either specialist. 

This is a complicated and ambitious paper, on an exciting system and aiming at important questions. I think the main results about genotypic-fitness networks are hard to relate back to the other major analyses in the paper due to the points raised above. Moreover, using fitness measurements of three coexisting species to infer how they evolved faces a major obstacle: if fitnesses are frequency-dependent, then the actual trajectory of an initially rare variant will be completely obscured post-invasion. This possibility, as well as the potential issue that data on reproductive success might change these findings, need to be discussed, especially in light of the puzzling fact that the specialists appear less fit than their ancestor in at least one of the paper's major analyses.

Reviewer #1 (Public Review):

Bacteria growth laws are a very interesting field of research with lots of recent activity in trying to understand the older results including that the fraction of a cell that is ribosomes increases linearly with the cell growth rate (regardless of the carbon source). Interestingly, the line doesn't cross the origin at zero growth rate, but has a non-zero offset. This paper aims to address why this is the case and proposes it arises because of the need to devote a pool of ribosomes to maintaining the proteome and compensating for protein degradation, which becomes more important for more slowly growing cells. Yet, while plausible, the data are quite sparse and it is unclear to me how a bacterial cell would have a distinct inactive pool of ribosomes.

The main proposal is that the offset arises because of protein degradation. The hypothesis is that the rate of protein degradation becomes increasingly important at slower growth rates so that to maintain the proteome a larger and larger fraction of ribosomes is engaged in maintenance rather than growth duties. Initially, the degradation rate is considered fixed, but the data gathered from the literature seems to indicate that degradation rates increase at slower growth (Fig. 3). This is pretty interesting as my intuition would have thought that the speed of protein degradation would increase with the cell growth rates since the rates of most processes do. Here, they report the opposite although the data on yeast are pretty sparse.

I'm left wondering about the following major points though:

1. Why don't the authors use the fitted degradation rates as a function of growth rate from Fig 3 for their analysis?

2. I don't understand the notion of an inactive pool of ribosomes (eq 12). What evidence is there for the distinction of two separate pools. I could guess that all the ribosomes are infrequently translating protein so that each spends more time unengaged and there appears 'inactive', but it isn't really a separate pool. This assumption seems to me the least compelling, and more data or discussion needs to be brought to bear to justify it.

Reviewer #2 (Public Review):

Bacterial growth laws have enabled considerable progress in our quantitative understanding of cell physiology. The most important growth law describes the dependence of ribosome concentration on growth rate in exponential growth, which is linear with a y-axis offset. In this work, the authors address the origin of this y-axis offset, which is an important conceptual problem. They show that a theoretical model that takes into account both protein degradation and a fraction of inactive ribosomes can explain the empirically observed offset better than the conventional approach, which neglects protein degradation.

Explaining the origin of the y-axis offset in the first growth law would be an important advance with a major impact on the field. The theoretical analysis in this work is carefully performed and the results are clearly presented and easily accessible for a broader audience. However, the experimental support for some key assumptions of the model needs to be clarified and there may be a major conceptual problem with the interpretation of quantities measured at or near growth rate zero.

Specific issues:

1. The limit of zero growth rate, which is the focus of this work, is problematic as key quantities entering the growth laws are not clearly defined in this limit. The authors present an extension of the model first set up by Scott et al. (2010). The original model was designed for cells in steady state exponential growth. At zero growth rate, it is not clear what the steady state is. In exponential growth, this steady state is reached after sufficiently many generations at constant growth rate under constant conditions; however, at zero growth rate, key quantities that are measured will depend on how long the cells were kept at zero growth before the measurement is done (the relaxation time scale of the system becomes infinite in this limit). Very low growth rates with doubling times as long as 10 hours are also hard to detect experimentally and would in practice be treated as zero growth. It should be explained how the measurements at zero growth (from the literature) were performed and how we can be sure that they are as reproducible and clearly defined as those at finite growth rate.

2. The authors assume nonspecific degradation in their model. Here, it would be useful to clarify to what extent this assumption holds. I thought that only a small minority of proteins are specifically targeted for degradation in E. coli. A short summary on what is currently known about the common molecular mechanisms of protein degradation in E. coli and S. cerevisiae would be helpful.

3. Different ranges for protein half-lives are mentioned throughout the paper. The authors acknowledge that degradation time scales between 10 and 100 hours (as mentioned in Goldberg and Dice, 1974; Maurizi, 1992) are negligible (lines 44-46). Later on a simple estimate (lines 90-92) gives degradation time scales of 1-10 hours. However, along with data from Scott et al. (2010) and Metzl-Raz et al. (2017), the authors use their own model to calculate these time scales, more specifically using the assumption that the offset of the ribosomal mass fraction is caused by protein degradation. It needs to be clarified if the degradation time scales needed to explain the offset are consistent with plausible values based on literature knowledge.

4. Figure 3 shows results from the final model which includes protein degradation and the distinction between active and inactive ribosomes. In panel b, experimental data for degradation rates is presented and a fit is performed, which is later used to calculate the data points in panel c. The fit for the right plot in panel b includes only three data points and therefore seems arbitrary, especially in the range of 0.4 to 0.6. This is unfortunate as this fit is used for data points that give the crucial comparison between experimental data and the model predictions in panel c. Figure 3c is quite important for this work, as it captures not only the performance of the model in comparison to the (estimated) data but also the difference between the old model and the new model. The agreement of the lower bound from the model (which corresponds to the case without degradation) appears quite good, especially considering that it has one less free parameter. Here, it would be useful to perform a quantitative comparison of the agreement of the two models with the experimental data to support the relevance of the new model. Additionally, in the legend white symbols are mentioned that are not visible in the plots.

5. Figure 2 - Supplement 2, which shows the degradation rate measured at different growth rates, is crucial for this work and should be a main figure. A discussion of the methods used to measure the degradation rate and an estimate of experimental errors would be helpful. Further, several references for data on degradation rates are given. However, in this figure and throughout the paper only one of these data sets (Pine, 1973) is used for the calculations. Including data of at least one other reference would help to further corroborate the model; it should also be clarified if the different datasets of degradation rates are consistent with each other. It is notable that all references for the degradation rate data are 40-50 years old. The authors mention the methods used for the measurement of these data but it seems necessary to further discuss if these methods are still state of the art.

6. In Figure 3 - Supplement 1 experimental data is shown to support the constant-ratio ansatz that is used in the paper. This plot should be corroborated by a quantitative analysis to support the constant behavior of the ratio. For the S. cerevisiae data, it seems from the plot that the ratio is decreasing with increasing growth rate, as the values decrease almost by a factor of five (from ~0.25 to ~0.05). For example, calculating the correlation coefficient and its significance for these data would help to support that they are constant.

Reviewer #1 (Public Review):

In this study, the authors set out to clarify the relationship between brain oscillations and different levels of speech (syllables, words, phrases) using MEG. They presented word lists and sentences and used task instructions to attempt to focus listeners' attention on different levels of linguistic analysis (syllables, words, phrases).

I came away with mixed feelings about the task design: following each stimulus (sentence or word list), participants were asked to (a) press a button (i.e. nothing related to what they heard, (b) indicate which of two syllables was heard, (c) indicate which of two words was heard, (d) indicate which pair of words was present in the correct order. This task is the critical manipulation in the study, as it is intended to encourage (or in the authors' words, "require") participants to focus on different timescales of speech (syllable, word, and phrase, respectively). I very much like the idea of keeping the physical stimuli unchanged, and manipulating attention through task demands - an elegant and effective approach. At the same time, I have reservations about the degree to which these task instructions altered attention during listening. My intuition is that, if I were a participant, I would just listen attentively, and then answer the question about the specific level. For example, I don't know that knowing I would be doing a "word pair" task, I would be attending at a slower rate than a "word" task, as in both cases I would be motivated to understand all of the words in the sentence. I fully acknowledge my introspection (n=1) may be flawed here, but nevertheless, any additional support validating the effect of these instructions would help the interpretation of the MEG results.

The analysis steps generally seem sensible and well-suited to answering the main claims of the study. Controlling for power differences between conditions through matching was a nice feature.

I had a concern about accuracy differences (as seen in Figure 1) across stimulus materials and tasks. In particular, for the phrase task, participants were more accurate for sentence stimuli than word list stimuli. I think this makes a lot of sense, as a coherent sentence will be easier to remember in order than a list of words. But, I did not see accuracy taken into account in any of the analyses. These behavioral differences raise the possibility that the MEG results related to the sentence > word list contrast in phrases (which seems one of the most interesting findings in IFG) simply reflect differences in accuracy.

With the caveat of the concern regarding accuracy differences, the research goals were clear and the conclusions were generally supported by the analyses.

Reviewer #2 (Public Review):

In a MEG study, the authors investigate as their main question whether neural tracking at the phrasal time scale reflects linguistic structure building (testing different conditions: sentences vs. word-lists) or an attentional focus on the phrasal time scale (testing different tasks, passive listening, syllable task, word task, word combination/phrasal scale task). They perform the following analyses at brain areas (ROIs: STG, IFG, MTG) of the language network: (1) Mutual information (MI) between the acoustic envelope and the delta band neuronal signals is analyzed. (2) Power in the delta band is analyzed. (3) Connectivity is analyzed using debiased WPLI. For all analyses, linear mixed-models are separately conducted for each ROI. The main finding is that the sentence compared to the word-list condition is more strongly tracked at the phrasal scale (MI). In STG the effect was task-independent; in MTG the effect only occurred for active tasks; and in IFG additionally, the word-combining/phrasal scale task resulted in higher tracking compared to all other tasks. The authors conclude that phrasal scale neural tracking reflects linguistic processing which takes place automatically, while task-related attention contributes additionally at IFG (interpreted as combinatorial hub involved in language and non-language processing). The findings are stable when power differences are controlled. The connectivity analysis showed increased connectivity in the delta band (phrasal time scale) between IFG-STG in the phrasal-scale compared to the passive task (adding to the IFG MI findings). (Additionally, they separately analyze neural tracking at the syllabic and word time scale, which however is not in the main focus).

Major strength/weaknesses of the methods and results:<br /> A major strength of the results is that part of them replicate the authors' earlier findings (i.e. higher tracking at the phrasal time scale for sentences compared to word-lists; Kaufeld et al., 2020), while they complement this earlier work by showing that the effects are due to linguistic processing and not to an attentional focus on the phrasal time scale due to the task (at least in STG and MTG; while the task plays a role for the IFG tracking). Another strength is that a power control analysis is applied, which allows excluding spurious results due to condition differences in power. A weakness of the method is that analyses were applied separately per ROI, and combined across correct/incorrect trials (if I understood correctly), no trial-based analysis was conducted (which is related to how MI is computed). Furthermore, several methodological details could be clarified in the manuscript.

The authors achieved their aims by providing evidence that neuronal tracking at the phrasal time scale in STG and MTG depends on the presence of linguistic information at this scale rather than indicating an attentional focus on this time scale due to a specific task. Their results support the conclusion. Results would be strengthened by showing that these effects are not impacted by different amounts of correct/incorrect trials across conditions (if I understood that correctly).

The findings are an important contribution to the ongoing debate in the field whether neuronal tracking at the phrasal time scale indicates linguistic structure processing or more general processes (e.g. chunking).

Reviewer #3 (Public Review):

This manuscript presents a MEG study aiming to investigate whether neural tracking of phrasal timescales depends on automatic language processing or specific tasks related to temporal attention. The authors collected MEG data of 20 participants as they listened to naturally spoken sentences or word lists during four different tasks (passive listening vs. syllable task vs. word tasks vs. phrase task). Based on mutual information and Connectivity analysis, the authors found that (1) neural tracking at the phrasal band (0.8-1.1 Hz) was significantly stronger for the sentence condition compared to the word list condition across the classical language network, i.e., STG, MTG, and IFG; (2) neural tracking at the phrasal band was (at least tend significantly) stronger for phrase task than other tasks in the IFG; (3) the IFG-STG connectivity was increased in the delta-band for the phrase task. Ultimately, the authors concluded that neural tracking of phrasal timescales relied on both automatic language processing and specific tasks.

Overall, this study is trying to tackle an interesting question related to the contributing factors for neural tracking of linguistic structures. The study procedure and analyses are well executed, and the conclusions of this paper are mostly well supported by data. However, I do have several major concerns.

1. The title of the manuscript uses the description "tracking of hierarchical linguistic structure". In general, hierarchical linguistic structures involve multiple linguistic units with different timescales, such as syllables, words, phrases, and sentences. In this study, however, the main analysis only focused on the phrasal band (0.8-1.1 Hz). It seemed that there was no significant stimulus- or task-effect on the word band or syllabic band (supplementary figures). Therefore, it is highly recommended that the authors modify the related descriptions, or explain why neural tracking of phrases can represent neural tracking of hierarchical linguistic structures in the current study.

2. In Methods, the authors employed MI analyses on three frequency bands: 0.8-1.1 Hz for the phrasal band, 1.9-2.8 Hz for the word band, and 3.5-5.0 Hz for the syllabic band (line 191-192). As the timescales of linguistic units are various and overlapped in natural speech, I wonder how the authors define the boundaries of these frequency bands, and whether these bands are proper for the naturally spoken stimuli in the current study. These important details should be clarified.

3. What is missing in the manuscript are the explanations of the correlation between behavioral performance and neural tracking. In Results, the behavioral performance shows significant differences across the active tasks (Figure 1), but the MI differences across the tasks are relatively weak in IFG (Figure 3). In addition, the behavioral performance only shows significant differences between the sentence and word list conditions during the phrasal task, but the MI differences between the conditions are significant in MTG during the syllabic, word, and phrasal tasks. Explanations for these inconsistent results are expected.

4. Since the behavioral performance of these active tasks is likely related to the temporal attention to relevant timescales of different linguistic units, I wonder whether there exist underlying neural correlates of behavioral performance (e.g., significant correlation between performance and mutual information). If so, it may be interesting and bring a new bright spot for the current study.

Reviewer #1 (Public Review):

The paper by Chen et al studies inter-individual differences in the left-right asymmetry of the shape of the cerebral cortex. The authors introduce a novel shape asymmetry measure based on a spectral analysis of cortical geometry, reporting that relatively coarse scales of shape asymmetry are highly specific to individual study participants. Shape asymmetry (SAS) is shown to have associations with cognition and biological sex, but not handedness. Result suggest that shape asymmetry is not highly heritable, and that it is driven primarily by environmental rather than genetic influences.

The paper has many strengths. The problem of investigating directional versus fluctuating asymmetry is clearly stated and biologically important. SAS is based on a sophisticated methodological approach and rigorously applied. The use of three datasets increases the generalizability of the results, and the comparison to fMRI measures provides important context. Weaknesses include the interpretability of the measure and some specific methodological issues that could be further addressed as discussed below.

1. The lack of higher identifiability of fine-grained SAS is hard to understand. Given that secondary and tertiary sulci are not likely to change between time point 1 and time point 2, and that it is known that secondary and tertiary sulci vary more than primary sulci between people, this suggests that higher measurement error at finer scales may limit the comparisons between fine and coarse made in the paper.

2. From a neuroanatomical perspective, it is not clear what individuals with different asymmetries of shape at different scales actually look like, which limits the interpretability of the measure.

3. The possibility that image quality could affect measures of shape asymmetry is not addressed.

4. The paper does not address that different way of measuring of handedness could theoretically have different associations with asymmetry measures.

Reviewer #2 (Public Review):

Being a paleoanthropologist, I am not a real specialist of the neuroscientific field. For this reason, my understanding of the methods, and particularly of the mathematics behind, may be partial. However, I am used to studies of bilateral variation of the brain. For these reasons, my comments mostly concern the theorical framework of the study, the way the data are analysed and exploited and the interpretations. The authors propose with this paper a new approach to characterize the main asymmetries of the whole cortical shape. This new tool is interesting and provides an original perspective on a longstanding question. Thanks to this approach, the authors identify interesting individual characteristics as individual's shape asymmetry appear to be a good parameter to identify each individual. I have more concerns about the application of this new tool in the context of earlier studies of human brain asymmetries, particularly when the authors contextualise their own researcher and results within the existing knowledge on the topic. From a methodological point of view, I would be interest in having more information about the identified bilateral variation for individuals and samples and a clearer characterization of different parameters for bilateral variation.

Reviewer #1 (Public Review):

Krasniewski et al. investigated the varying populations of mouse skeletal muscle resident macrophages with age using single-cell transcriptomics. They find that mouse SKM macrophages can be divided into two subgroups, anti-inflammatory LYVE+ and proinflammatory LYVE- macrophages. They further classify these macrophages into LYVE1+/MHCII-lo (similar to classical M2 activation), LYVE1-/MHCII-hi (similar to classical M1 activation), LYVE1+/MHCII-hi, and LYVE1-/MHCII-lo, with LYVE1+/MHCII-hi macrophages expressing traits of both the classical M1 and M2 macrophages, and LYVE1-/MHCII-lo macrophages being enriched with mRNAs encoding cytotoxicity proteins. Using a phagocytosis assay, they show that LYVE1-/MHCII-lo macrophages have a reduced % of phagocytosing cells, notably while having a higher gMFI. Interestingly, the data also indicate that commonly used polarization markers CD206 and CD86 are widely and simultaneously expressed, suggesting they are not best suited to represent polarization. By performing an unsupervised classification of macrophage clusters, the authors find smaller macrophage subpopulations that suggest increased expression of inflammatory and cell-cycle related mRNAs in old SKM. These data expand and enhance what the field uses as markers for macrophage polarization and suggests and age-dependent change in macrophage populations, with older SKM containing a higher percentage of proinflammatory M1-like macrophages.

The manuscript presents interesting findings and provides an important resource to better understand innate immune shifts with aging as well as their functional consequences. Although most conclusions are well supported by data, clarifications are needed to fully support the study and improve its long-term reproducibility.

Since the study is performed exclusively on male animals and aging is extremely sex-dimorphic, it would be important for the authors to contextualize the findings in terms of how they may be affected as a function of sex.

Reviewer #2 (Public Review):

The manuscript by Krasniewski et al., utilizes single cell RNA seq analysis to investigate skeletal muscle macrophage populations in healthy young and old mice. Utilizing transcriptomic analysis and further validation via immune-staining and flow cytometry, the authors show that multiple sub-populations of macrophage subsets exist in healthy skeletal muscle, and are characterized by differential expression of Lyve and MHCII. Additionally, utilizing further analysis comparing skeletal muscle macrophage subpopulations in young vs old mice, the authors show that during aging these macrophage subpopulations skew from an M2-like state to a pro-inflammatory M1-like state. Lastly, unsupervised classification of old vs young macrophages revealed novel subsets of macrophages that increase during aging, suggesting a role for skeletal muscle macrophages in aging related muscle pathophysiology.

The study overall is an interesting and timely investigation of skeletal muscle macrophage populations and transcriptomics in both healthy young and old mice, and would be a valuable resource to the inflammaging and muscle biology field. However, the manuscript is largely descriptive and does not provide any mechanistic or functional insight or test what role these macrophage subsets play in muscle physiology of young or old mice.

Reviewer #3 (Public Review):

In this article, the authors sought to dissect the heterogeneity of skeletal muscle macrophages and catalogue the changes occurring with age. To do so, they performed a scRNAseq of CD11b+ cells in skeletal muscles in 3 and 23 mo old male mice. They describe four different subsets defined by MHC-II and Lyve1 expression displaying distinct transcriptional profiles. They confirm the existence of these subsets using flow cytometry and immunofluorescence imaging of skeletal muscle tissue. They show that these subsets display different phagocytic capacity, notably in accordance with GO annotation suggesting enriched expression of phagocytic genes in LnHl. Comparisons of macrophage subsets between young and old animals revealed a decrease of Lyve1+ and increase of Lyve1- macrophages in old. Analysis of differentially expressed genes revealed an overall increase of pro-inflammatory genes in old macrophages. Finally, the authors performed an unbiased analysis to confirm the subsets described with the supervised analysis. In general, and as presented scRNA analyses are superficial that provide scant new insights into macrophage biology and aging.

Reviewer #1 (Public Review):

Ching et al investigate the long-range migration and maturation of cilia-forming centrioles in multiciliated OSNs of the adult mouse. They develop techniques to perform expansion microscopy of the tissue, as well as explant culture and live imaging. Images obtained from expansion microscopy in this tissue are just spectacular, and provide suborganelle details of centriole organization as they traverse the OSN dendritic projections and eventually dock and form cilia. Although the study is predominantly descriptive and observational, the increased resolution gained by expansion microscopy allow them to do things like count the exact number of centrioles in progenitors and mature OSNs, and describe the sub-organelle organization of centrioles as they migrate, mature and build cilia.

Key findings include the observation that centrioles migrate in clusters, though it is unclear what molecularly connects the clusters. Using makers of centriole maturation they show that immature centrioles migrate and subsequently lose those markers when they reach the apical surface where ciliogenesis will occur. PCM factors associated with MT nucleation remain associated with centrioles throughout the migration and maturation process where they presumably retain their MT nucleation capacity. Distal and subdistal appendages are present only in a signal centriole in immature OSNs, presumably the parent centriole, and that these markers only associate with the rest of the centrioles once they have docked at the apical surface. Stabilizing MTs using taxol in an ALI culture system leads to decreased migration of OSN centrioles suggesting a role for dynamic microtubules in their movement. Overall the data are very high quality. The study raises more questions than answers - how do centrioles cluster, how do they migrate, what controls their maturation in both space and time. The paper lays the groundwork for tackling these questions and provides some intriguing hypotheses to guide those future studies.

Reviewer #2 (Public Review):

Olfactory sensory neurons (OSN) are a unique type of multi-ciliated cell that have a distinct and dynamic morphology. These cells have numerous centrioles that will generate their numerous cilia that project off the end of their dendrite. The Ching et al. manuscript addresses the question of where these centrioles are generated and how they are transported to the dendritic knobs. The authors use expansion microscopy to quantify centriole number and to characterize centriole maturation including localization of a wide range of centriolar proteins. They develop both an ex vivo culture system and an explant based ALI culture system to visualize centriole migration towards the dendritic knob. Finally they show that microtubule (MT) stabilization with Taxol leads to a defect in the centriole movements.

Overall, there is a lot of beautiful data in this paper and the claims are generally supported by the data. While OSNs have been fairly well characterized at the EM level, it is certainly a worthwhile endeavor to revisit some of this description with newer technologies and with live imaging. To that end this manuscript is largely descriptive and while that is often used negatively, here I think it is an important addition to the field. In particular the development of novel culture systems promises to bring new insights to the field. However, certain aspects of these culture systems require further validation / description. Additionally, while the authors attempt to bring some mechanism into their analysis via MT manipulation, the results are preliminary and in my opinion would require deeper analysis to support their claims.

Reviewer #3 (Public Review):

Analyzing the long-distance migration of centrioles at the dendrite tip of olfactory neurons in adult mice, Ching et al. first show that centrioles migrate along with dendrite extension, forming multiple clusters of centrioles distributed along a single dendrite. Interestingly, the maturation of centrioles occurs during their migration. Indeed, some of the migrating centrioles still contain the STIL and SAS-6 markers, while all centrioles in mature OSNs are devoid of these proteins. The authors show that immature OSNs carry only one cilium, organized from the mother centriole, the only one that has appendages at this stage. Maturation of the other centrioles, which allows them to acquire distal appendages, therefore occurs near the apical membrane. The mother centriole also has subdistal appendages, while the other centrioles acquire a single basal foot, as in multiciliated cells bearing motile cilia. The authors then show that treatment with paclitaxel, a drug that stabilizes microtubules, leads to an increase in the number of centrioles in the subapical region of the epithelium, suggesting a defect in centriole migration. Overall, this is an interesting work that sheds light on a cell type whose ciliogenesis is poorly characterized. Various protocols are developed for this study, including a protocol for explant culture. However, this study would be strengthened by further analysis of the different stages of centriole assembly and maturation, as well as the mechanisms underlying centriole migration.

Reviewer #2 (Public Review):

This is an excellent report describing a new functionality for FHF sodium channel-binding proteins. Certain combinations of FHF and sodium channel isoforms enable the generation of resurgent current. Specifically, TTX-resistant sodium channels (Nav1.8 and Nav1.9) in conjunction with A-type FHFs result in a resurgent current. The mechanism involves an open-channel block analogous to the way A-type FHFs induce long-term inactivation of TTX-sensitive sodium channels. The researchers also employ FHF4 knockdown to show that endogenous A-type FHF underlies resurgent current in DRG neurons and enhanced excitability.

Reviewer #3 (Public Review):

This is an extremely exciting and important study that constitutes a major (and long-awaited) advance in the molecular understanding of resurgent Na current. Reproducing resurgent current by expression of two proteins has never been done before: All studies that have tried to work their way toward the molecular mechanism have relied on peptides from candidate blocking proteins which mimic resurgent current, and co-expression of those candidate proteins with Na channels has been unsuccessful. Here, the authors have accomplished three things:

(1) They have for the first time successfully molecularly reconstituted Na channels that produce resurgent Na current by expressing the FHF4A protein with NaV1.8 or 1.9.<br /> (2) They have also reconstituted resurgent currents by coexpressing FHF2A with NaV1.5 or 1.7.<br /> (3) They have identified a key residue that regulates the sensitivity of NaV alpha subunits to resurgent-current mimicking open-channel block by the NaVbeta4 peptide.

Not only do these experiments satisfactorily and convincingly address a long-standing question (and give an idea of the wealth of molecular combinations that may generate resurgent current), they also open the door to molecular manipulation of this current, which will be highly informative and potentially of significant practical use, given the proposed role of the current in several disorders and disease states, including pain (as shown by these authors). The work is convincingly done and clearly presented.

Reviewer #1 (Public Review):

The work by Mazal et al. demonstrates the possibility to reconstruct information from proteins structure at an angstrom resolution, using key elements in super-resolution microscopy: working at low temperature to accumulate an important number of photons per molecule (thus increasing localization precision), and discriminating different labels, positioned at precise locations of the proteins oriented in 3D, with the use of their polarization emission behavior. This approach is elaborated based on previous works by the authors, and is applied here for the first time to protein complexes in 3D. This is achieved thanks to additional steps of data processing and more advanced analysis algorithms, to (1) extract, out of step-wise time dependencies, the presence of molecule's identified by their different orientations and (2) use supervised particle classification for the reconstruction of the final structure information.<br /> This work is a step forward in the use of optical super-resolution for ultra-high resolution analyses that come in close complementarity to electron-microscopy, and can be applied to proteins structures that are delicate to crystallize. While it shows that it can reproduce information from a structure as complex as a hexameric geometry, it is however not clear how this approach will be applied to unknown protein structures. The approach seems robust but is also still limited to a very specific framework of low-level labeling, immobilized and low-concentration proteins, therefore not yet likely to apply to dynamic studies as mentioned in the manuscript.

Some points need to be addressed to clarify the findings, the conclusions, and the broader claims.

It is known that point spread functions from 3D-oriented dipoles, as found in the present study, are not symmetric Gaussians but rather deformed shapes that might lead to significant localization inaccuracies as compared to the localization precision reached here. The effect of this bias needs to be discussed. Related to this point, the authors should address and consider the possibility to directly measure the 3D orientation of fluorophores, which might be very relevant for the discrimination method developed in this work.

The method assumes that there is no possible rotational flexibility of the dipoles attached to the studied protein. Even though the measurements are performed at low temperature, it does not prevent different probable orientations to be explored for each fluorophore.

The limitations of the method, in particular, the number of possibly discriminated orientations, required time dynamics of the photophysics of the fluorophores, required signal to noise level, required number of measurements given the very low yield of used molecules, should be clarified, in particular giving elements for possible improvements.

The applicability of the method to a larger framework is not entirely clear. Its application to unknown or dynamic proteins structures should be addressed, in particular with respect to the used supervised classification procedure.

Reviewer #2 (Public Review):

The authors present polarCOLD, an extension of their recently presented technique of optical localization microscopy at cryogenic temperatures (COLD). They point out that the main limitation of COLD as being dependent on intensity fluctuations to separate individual emitters, which can then be localized. Such intensity fluctuations depend on the local environment and quantum efficiency of the fluorophore, which was previously shown to allow discrimination of up to four sites (Weissenburger, 2017). Recording the emission polarization as an additional parameter was recently presented by the authors (Böning, 2021) and shown to support fluorophore discrimination.

In the present manuscript, the authors now use polarCOLD in combination with partial labeling and particle classification to characterize more complex proteins with up to 6 binding sites. While DNA structures were used previously, the authors now demonstrate their technique by reconstructing binding sites in two multimeric proteins at Angstrom resolution. The new approach readily allows the discrimination of 5 fluorophores. By using a 3D particle reconstruction algorithm, they achieve a remarkable resolution of 4.9 Å for the simple trimeric protein PCNA. Towards more complex proteins, the authors exploit partial labeling together with particle classification to overcome the limitation of the number of fluorophores. They use a 50% labeled hexameric protein to accurately localize the remaining three fluorophores, which are then translated into a 3D structure using a combination of simulations, classification and template matching.

The authors extend their recently developed polarCOLD technique to the reconstruction of multimeric proteins, which was not shown previously. A major strength of cryogenic localization microscopy is that it can achieve Angstrom resolution. Although currently limited to purified proteins, which in principle makes the sample also compatible with cryoEM, COLD indeed allows discriminating binding sites within a complex which might not be readily possible with cryoEM. Still, both techniques operate in the same resolution regime and it will be interesting to explore the possibilities towards non-symmetric complexes or mixed biological samples.

Reviewer #3 (Public Review):

The paper by Mazal, Wieser and Sandoghdar presents a method to image small molecular complexes with light microscopy, but obtain resolutions/localization uncertainties of fluorescent labels that have been limited to cryo-EM.

This submission by Mazal, Wieser and Sandoghdar builds upon earlier work from the same group (Weisenburger, Nature Methods, 2017 and Boning, ACS Photonics, 2021). The polarisation detection does not increase the sparsity compared to Weisenburger, but on the detection side they can identify different emitters based on their fixed dipole emission as shown in Boning. They further improve the sparsity, by explicit underlabeling, which later is compensated by particle registration and averaging. Compared to Boning the submission adds 3D reconstructions of two molecular complexes from 2D underlabeled structures. The polarisation and localization method is improved technically, but the concept was already there.

Reviewer #1 (Public Review):

Apicomplexan parasites, including the malaria parasite Plasmodium, possess a characteristic inner membrane complex (IMC), which plays an essential role in maintaining the parasite shape and regulating motility. In this interesting study, Qian and colleagues determine the IMC proteome of erythrocytic stages in the rodent malaria parasite Plasmodium yoelii, and identify the palmitoyl-acyl-transferase DHHC2 as a key enzyme that regulates the localization of IMC proteins through palmitoylation. The authors used a proximity biotinylation strategy based on TurboID to identify by mass spectrometry 300 proteins associated with the IMC. Using genetic tagging they could confirm IMC localization of 19 out of 22 selected candidate proteins. This analysis revealed that many of the IMC proteins are predicted to undergo palmitoylation, a modification that is known to play a role in protein localization to the IMC. The authors identified 3 candidate IMC palmitoyl-acyl-transferase, including DHHC2, which was most highly expressed and predicted to interact with many of the identified IMC proteins. Using conditional protein depletion based on the auxin degron system, the authors demonstrate that DHHC2 is essential for blood stage growth, schizont segmentation and merozoite invasion, and show that DHHC2 palmitoylates GAP45 and CDPK1, two essential IMC proteins. Altogether this study provides a comprehensive view of the IMC proteome and the role of palmitoylation in Plasmodium erythrocytic stages.

Strengths:

-This study provides a comprehensive view of the IMC proteome and identifies new IMC proteins<br /> -The work is robust and involves cutting-edge approaches such as TurboID (used for the first time in Plasmodium), auxin degron system, CRISPR-Cas9 targeted mutagenesis of DHHC2 substrates.<br /> -This study convincingly demonstrates the role of DHHC2 in the palmitoylation of IMC proteins in Plasmodium blood stages, providing potential targets for the development of novel anti-malarial strategies.

Limitations:

-The screen identified a large number of candidate IMC proteins, raising the possibility that some are false positives.<br /> -There could be alternative explanations for the observed depletion of GAP45 and CDPK1 from the IMC upon mutagenesis, DHHC2 depletion or 2BP treatment, including lower expression or disruption of the IMC.

Reviewer #2 (Public Review):

In this research article, Quian et al. investigate the composition of the inner membrane complex (IMC) of Plasmodiun yoelii schizonts by proximity labelling and identify 11 new proteins in the pellicle of the parasite attesting for the robustness of the enrichment. They also dissect the role of DHHC2, an IMC-resident protein acyl-transferase by generating an inducible knock-down of this enzyme. By doing so, they convincingly demonstrate the essential role of DHHC2 for the survival of the parasite in the mouse model and show that it is required for the intraerythrocytic development of the parasites and more specifically for the segmentation of the schizonts. In addition, the authors demonstrate that GAP45 and CDPK1 are palmitoylated proteins that are not found associated to the membrane in DHHC2 depleted parasites.

Finally, point mutations have been generated in these two proteins to determine the cysteine(s) that might be palmitoylated by DHHC2.

Overall the article is well written, the experiment are well conducted, well controlled and analyzed and the role of DHHC2 in the parasite development is nicely illustrated. However, the dissection of GAP45 and CDPK1 needs further analysis and discussion, respectively. Indeed, on one hand, the GAP45 construct used to assess the IMC targeting palmitoylation sites might be already altered by the C-terminal tagging while on the other hand, CDPK1 is described in the literature as a plasma membrane protein like its orthologue TgCDPK3.

The data presented in this study are of high quality. Some immunofluorescence needs to be improved in their brightness to better determine where are localized the proteins of interest and some inconsistencies of MSP1 staining between the figures need to be discussed (likely resulting from different timing of auxin and 2-bromopalmitate exposure).

Reviewer #3 (Public Review):

In this manuscript, the authors use TurboID proximity labeling to identify novel components of the Plasmodium inner membrane complex. They then verify many of the identified candidate proteins, demonstrating the utility of the approach. They build on this by identifying the major palmitoylacyltransferase involved in tethering IMC proteins to the membranes of the organelles and directly test the importance of palmitoylation in the trafficking and function of several key IMC proteins. The experiments are supported by extensive controls throughout the paper. Overall, this is a robust paper that provides an important addition to the field. Specific comments are below.

1. line 149 and S2A. The authors use the term "signal peptide" for the N-terminal 20 amino acids of ISP1 that target TurboID to the IMC<br /> a. "signal peptide" is likely to be confused with a secretory signal peptide for entrance into the lumen of the ER/golgi. There is no predicted signal peptide on ISP1 (Signal P Prediction), instead ISP1 is likely both myristoylated and palmitoylated as previously shown in T. gondii. This tethers the protein to the cytoplasmic face of the IMC (and potentially to vesicles targeting to the IMC).

b. Line 565-573 This becomes more confusing in the discussion when the authors claim that the "signal peptide" directs the fusion through the ER/Golgi secretory pathway.

Together, this would be better stated as an "IMC targeting peptide" to avoid confusion with this well-established nomenclature (and modify the discussion accordingly)

2. Regarding predicted acylation of TurboID identified IMC protein candidates<br /> a) It would be useful to state how many of the proteins are predicted to be palmitoylated and add this to table S1.<br /> b) Since myristoylation also plays a role in IMC trafficking, it would also be useful to state how many of the proteins are predicted to be myristoylated (also add to S1).

Reviewer #1 (Public Review):

The present manuscript investigates an essential aspect of multicellularity, coordination between gene regulatory networks (GRNs), presented as grouped in so-called teams, and their deregulations in cancer, leading in particular in cancer to epithelial-mesenchymal plasticity (EMP), the propension of plastic cancer cells to go towards an epithelial (MET) or a mesenchymal (EMT) phenotype, according to the needs of the cancer cell population in a given ecosystem.

The authors have a long experience in molecular systems biology studies and publications in EMP (EMT/MET) and they are well aware of publications in the worldwide community on this topic. The present study proposes a structure of GRNs in 'teams' that may be 'strong', yielding stable phenotypes, or 'weak', yielding unstable phenotypes prone to plasticity.

The ideas presented in this manuscript, taking advantage of a well-set methodological analysis of gGRNs and their coordination, include fixation on given physiological phenotypes and their stability by such teams, hybrid states, and plastic transitions between states, all based on their newly introduced concept of teams, which might be an illuminating one to understand normal coordination between tissues in multicellular organisms and its deregulation in cancer.

Reviewer #2 (Public Review):

In this paper, the authors identify topological metrics in gene-regulatory networks that have the potential to predict the sub-types of phenotypic stead states that the network can lead to. The results hold great value for the field of Theoretical Systems Biology.

The paper becomes too technical too quickly and assumes a lot of knowledge from the reader. Equations and theoretical concepts are not always well defined. In general, I would recommend connecting the results from the simulations/topology metrics to EMP biology earlier in the paper. Alternatively, rather than investigating 5 networks related to EMP, the generalization of the statements could become stronger if the authors explore the trends of the theoretical analysis in networks modeling other biological processes (such as SCLC).

One of the main findings of the paper is that the distance between the matrix of correlation values between nodes in all steady states obtained from simulation and influence matrix indicates that the mean group strength is a good quantity to identify teams of nodes in the network. However, it remains unclear how to identify groups/teams in the networks based on influence: is it unsupervised (hierarchical?) clustering? How do the authors identify the number of teams of nodes in randomized?

The authors also explore whether team structure correlates with the stability of relevant biological phenotypes. To characterize stability, they define static (e.g., frustration and stead state frequency) and dynamic network metrics (e.g., coherence and higher-order perturbations), and correlate them to the mean group strength in both WT and randomized networks. Results are promising: team structure and group mean strength show interesting correlative trends with both the static and dynamic metrics. However, everything relies on the mean group strength, which as mentioned before is not convincingly defined in randomized networks.

Taken together, the conclusions of this paper would be better supported if a better explanation of team identification in gene-regulatory networks would be provided, and if networks related to other biological processes would be investigated.

Reviewer #1 (Public Review):

This is an interesting manuscript providing important new information on the mechanism of action of EROS in the generation of superoxide by the NADPH oxidase of neutrophils. The authors have shown in previous publications that EROS deficiency results in defective NOX2 activity and thus represents a hitherto unrecognised, rare form of chronic granulomatous disease. They now show how EROS is involved in oligosaccharide transfer during the maturation of gp91phox and also extend what is known about the role for EROS in regulating expression of the P2x7 ion channel.

The results presented in the manuscript are supported by findings from a variety of techniques and for the most part, are convincing and well presented. However, I do have queries about certain aspects of the manuscript.

1. Figure 1<br /> The much lower EROS expression when gp91phox is expressed warrants a comment.<br /> Fig 1 G. Please explain what fold change represents. From F, zero time expression appears much more than the 1.5 fold higher shown in G for the EROS-expressing cells. This needs explaining. With the very high error bars (presumably for the EROS sample although this is not clear) overlapping zero I find it hard to conclude anything from this figure.

2. P 9 line 9 states that Fig 1H shows that cycloheximide increases expression. Yet it appears from the legend that cycloheximide is present in all samples and it is EROS that increases expression. Please clarify.

3. Fig 3A&B and p12 1st para. The identification of OST as a binding partner is interesting and a significant novel finding. However, the presentation of this information appears to me to be unduly complex and more information is required. Not all the readers will be familiar with the details of SAINTexpress methodology and more explanation of what is being shown would be helpful. At the least, a supplementary Table of the 59 identified proteins would be helpful, plus information on controls to establish selective pull down by EROS and on how the blue spots in A relate to the proteins. Also please make it clearer which of the proteins in B were identified and the relevance of showing all the steps in the pathway.

4. Figure 6. This contains a large amount of information. Although interesting, I am concerned that the authors may be trying to include too much at the expense of the necessary detail for some of the experiments. For example, the EROS -/- +ATP scattergram on the left of Fig 6E does not seem to agree with the right hand graph. I would also like to see the mean values for the 5 experiments in Fig 6G shown. Most importantly, insufficient information is given for Fig 6H. I don't think I missed it but I could find no details about the experiment in the Methods section. We need to know more about exactly how many animals in were in each group (death of 1 animal appears to equate to 5% of total - how does this relate to >10 in total), how signs of illness were monitored and related to death, and generally more about the conditions of the experiment. Alternatively, this may be better left to a more detailed study.

Reviewer #2 (Public Review):

Randzavola et al. investigated the role of EROS (Essential for reactive oxygen species) in the early maturation stages of the Nox2 enzyme responsible for ROS production. They find that EROS in a similar manner supports assembly and stability of purinergic membrane receptors such as P2X7, linking Nox2 and inflammasome activation.

Moreover, they show that inhibition of EROS by affecting ROS and inflammasome activation might ameliorate pathology during influenza A virus infection and has the potential to tune antiviral immune responses in general.

These data add in an interesting way to previous work on the function of EROS in mice and humans and provide further mechanistic insight into EROS interaction with Nox2 and P2X7 receptor. The conclusions of this paper are mostly well supported by data, but some details on the in vivo influenza A virus infection experiment need to be clarified.

Reviewer #3 (Public Review):

The study by Randzavola and colleagues provides a follow-up of their previous publication (Thomas DC et al, J Exp Med 2017) describing EROS (Essential for Reactive Oxygen Species or C17Orf62) as a novel chaperone essentially required to support the phagocyte Nox NADPH Oxidase respiratory burst and bacterial killing. Here, the authors extend the investigation of the mechanism underlying EROS effect and show its very early binding in the endoplasmic reticulum and interaction with immature partially glycosylated forms of gp91phox (the catalytic subunit of the Nox complex), allowing the incorporation of heme and subsequent binding of p22phox, which later follows the usual steps for complex maturation. A novel finding was the association of EROS with the OST component of the N-glycosylation machinery. An extended proteome analysis confirmed that EROS is quite specific for the gp91phox/p22phox complex and also for the purinergic P2X7 receptor, which also interacts with EROS (as also shown previously by the authors and further investigated by Ryoden et al. J Immunol 2020). The authors further validate EROS binding to P2X7 and provide evidence that EROS loss-of-function impairs P2X7-associated functions. Particularly, mice with genetically ablated EROS show improved survival to influenza infection.

A major strength of this line of investigation is the clear functional importance of EROS in the regulation of the protein expression of the Nox complex components. Previous work has clearly shown that human EROS deficiency associated with the severe immunodeficiency Chronic Granulomatous Disease, which is usually caused by genetic deficiency of the Nox complex components. Indeed, the loss of gain of functions of EROS are very clearly associated with major changes in the expression of those components, indicating EROS functional relevance. Moreover, the interplay between the P2X7 receptor and EROS is also relevant, given that this receptor mediates an important arm of innate immunity, namely the nucleotide-driven inflammasome activation. Thus, the authors are likely dealing with some undoubtedly important novel information which may be of broad impact to understand several aspects of the adaptive and even adaptive immunity.

Enthusiasm for this article, however, is somewhat decreased by some aspects, as follows:<br /> 1) While there is a substantial amount of new data, the corresponding progress in depth of mechanistic insights has not been commensurate, bearing in mind the author's previous work. The novel findings are the more clear documentation of EROS/gp91phox interaction and its time-course during nascent gp91phox protein processing in the ER. Also, their interplay with the OST complex. The extended list of proteins associating with EROS essentially confirms previous findings. Also, the work with P2X7 mostly confirms previous findings, while the novel and interesting experiment with EROS-silenced mice and viral infection needs further work, as commented below.<br /> 2) Some aspects of these results are less than clearcut. The association between gp91phox and EROS is generally convincing, but for many experiments the authors make wide use of transfections of tagged protein constructs. One can clearly understand that this is possibly the only feasible approach at this time, however these constructs carry the intrinsic problem of possible protein misfolding, which would make them a potentially artificial target of any endoplasmic reticulum chaperone-like protein such as EROS. This would impact exactly on the very mechanism the authors are proposing for EROS effects, i.e., early protein processing.<br /> 3) The same consideration applies to the experiments in Figure 3 with the OST complex STT3A. The co-localizations shown by the authors are technically acceptable, but their meaning is unclear, given it is expected that the proteins EROS and OST occupy the same compartment, being ER-located proteins, especially if transfected as constructs (tagged or not).<br /> 4) It would be important to assess whether cells receiving such constructs depict markers of endoplasmic reticulum stress and/or show impaired survival.<br /> 5) The experiments with co-transfection in HEK293 cells of EROS, Nox1 and Nox4 provide results at variance with the author's data in their previous work, in which endogenous Nox1 (intestine) and Nox4 (kidney) had no changes in expression in genetically silenced EROS mice.<br /> 6) The article is conceptually divided into two parts. However, there is no clear cross-fertilization between them and they essentially do not integrate.<br /> 7) While the authors claim that "the loss of both ROS and P2X7 signalling leads to resistance to influenza infection", this was not in fact shown in this work. It is known that P2X7 deficiency protects against influenza infection. Thus, it follows naturally that EROS deficiency, which essentially eliminates the expression of P2X7, would have the same effect. However, the role of ROS and gp91phox, i.e. whether or not they add to this equation, remains unclear.

Reviewer #1 (Public Review):

This manuscript presents results of a study in young adult male subjects of the effect of muscle length on force potentiation of human quadriceps muscle under very carefully controlled conditions that attempt to ensure that force measurements are not influenced by position of the femur and tibia relative to the axis of rotation of the dynamometer used to directly record leg extension forces. Direct measurements of knee torques are compared to an indirect measure of force based on patellar tendon shear waves. Inferences about muscle length based on knee angles at the time of contraction are independently confirmed by evaluation of muscle fascicle length using ultrasound techniques to further control conditions across subjects. Force potentiation is measured at three joint angles providing three different muscle lengths for study. Voluntary contractions were performed using EMG activity to provide a target for subject effort. Young healthy male subjects were studied. Strengths of the study include a very careful and systematic approach to measuring muscle force generation at three different muscle lengths. Challenges to applying patellar tendon shear wave speed as a measure of tendon load were identified. The data add to the weight of evidence that muscle length determines force potentiation of the quadriceps muscle in human subjects.

Reviewer #2 (Public Review):

The authors made a careful and critical series of measurements using human dynamometry. In particular they were careful to derive the best estimate of quadriceps muscle force that they could, correcting the torque measured by the dynamometer with detailed dynamic estimates of the moment arm during knee extension movements. Figure 6 shows how much knee angle changes without any change in position of the external dynamometer arm. They used the root mean squared emg signal to signal to the subject what level of muscle activation was required. Quadriceps muscle force was also estimated by a technique established by others to measure the speed of a mechanical impulse within the patellar tendon. The squared velocity of this impulse is claimed to correlate with the transmitted force.

The authors need to make this clearer in their presentation and to make clearer when they refer to the speed of the wave, and when they refer to the squared speed that is supposed to correlate with force.

Reviewer #1 (Public Review):

Until recently EEG/MEG research has been primarily focused on the analysis of neural oscillations and evoked responses. A noise component i.e. 1/f or aperiodic part of the spectrum was mostly considered as a nuisance. Recently, however, this aperiodic part was recognized as an important and neurophysiologically meaningful form of neural activity reflecting a balance between excitation and inhibition. Yet estimation of such aperiodic component has been performed for relatively long recordings. Recognizing that brain states are dynamic and that both periodic and aperiodic components can change quickly in time, the authors introduced an approach (SPRiNT) allowing estimation of these components in a time-resolved manner, which provides parameters for consecutive time segments. This study includes a large number of simulations and analyses of real data including EEG recordings from a large number of healthy participants and LFP recordings from rats. In the case of EEG recordings, the authors show how parameters extracted with SPRiNT differ between young and elderly participants and between eyes-closed and eyes-open conditions. In LFP recordings neural activity is used to define periods of rest from the motor activity. In general, the study is performed on a good technical level, contains adequate statistical treatment of the data and the obtained results are interpreted in agreement with the current neurophysiological understanding of the periodic and aperiodic parts of electrophysiological signals. The method will be important for the analysis of neural data where transient neural states are likely to be present, for instance during different sensory, motor and cognitive tasks.

Reviewer #2 (Public Review):

This paper describes a new tool for decomposing neural data into periodic and aperiodic spectral components. Traditionally the aperiodic (1/f) component has been viewed as noise that is static over time, but recently it has become clear that it is physiologically meaningful and variable. Ignoring its parameters and temporal variation thereof can lead to misinterpretation of the periodic components. The authors build on a recent parameterisation approach (Donoghue et al., 2020) to make it temporally resolved, and more robust to transient periodic components.

Using this new method, the authors show that SPRiNT outperforms the original static method based on realistic simulations, and further show that its performance in detecting periodic components is generally high, though it struggles to detect low-frequency components (e.g. delta activity), and it underestimates the number of periodic components when more than two were simulated. Using SPRiNT in empirical data, the authors show that changes in periodic and aperiodic parameters correlate with participants' age and behaviour in humans and that aperiodic dynamics are related to movement in rodents. Because this method gives a richer and more accurate description of neural dynamics, it has the potential to be widely adopted by the field.

Strengths:<br /> By transforming the static parameterisation method into a time-resolved one, the authors break down the assumption of temporal stationarity of a/periodic components, an assumption that is challenged by empirical data. The authors use a rigorous set of simulations to support this claim, and moreover, they show that their method gives a richer description of empirical data than what is traditionally used in the field.<br /> Furthermore, the proposed method is simple in use and computationally efficient. The source code is readily available in Brainstorm and as MATLAB standalone function and has the potential to be widely used.<br /> The results presented by the authors are transparent and the conclusions are supported by multiple pieces of evidence, e.g. both frequentist statistics and a post hoc Bayes factor analysis are presented, and the supplemental material presents additional evidence.

Weaknesses:<br /> While the simulations in this paper support the claim that the presented method can parameterise time-varying a/periodic components, the simulations are not exhaustive. The periodic components of the simulated power did not overlap as is often seen in empirical data, they were confined to 1-40 Hz (e.g. no gamma activity was simulated), and the simulations did not include a knee in the aperiodic component. This means that it Is unclear whether SPRiNT would work as well in more complex or excessively noisy datasets. The non-sinusoidal waveform shape of the periodic component in the rodent data reiterates this concern. Furthermore, the SPRiNT and specparam parameters were fixed and arbitrary, and it is unclear how robust the current results are with respect to changes in these parameters.

Reviewer #3 (Public Review):

The authors developed a novel method (Spectral Parametrization Resolved in Time, SPRiNT) intended for conducting time-resolved parametrization of both periodic and aperiodic neural activity. The method builds largely on the specparam/fooof-toolbox (fitting oscillations & one over f) and extends it by implementing a short-time Fourier transform (STFT) based approach for estimating time-resolved periodograms which are followed by the parametrization of neural activity via specparam and elimination of outlier spectral peaks. SPRiNT is then tested using simulated data against an alternative wavelet-based approach for conducting time-resolved parametrization of aperiodic and periodic activity as well applied to both resting-state human EEG data and intracranial data from rodents to evaluate the value of inspecting spectral parametrization in a dynamic manner. The question addressed by the study is very timely as there is an increasing interest in the role of aperiodic neural activity as well as detailed aspects of oscillatory components across a wide range of neuroscientific questions that have so far been primarily approached via static estimates of the spectral components. Based on the simulations, SPRiNT appears to be very efficient and superior at least compared to the one alternative method, opening the possibility for other researchers to investigate the role of aperiodic and periodic neural activity in a time-resolved manner. The method is applied to two sets of real recorded data, a resting-state EEG data collected from adults of different age groups (20-40 and 55-80 years) and intracranial data from two rodents during resting and movement conditions. The analyses on real data show that the slope of aperiodic activity varies across tasks/states and that the variability of the frequency of alpha oscillations dissociates individuals based on their age group. The analyses on real data thus show that at least for periodic data it is important to consider the fluctuations of the oscillatory parameters within extended periods of individual tasks. However, for aperiodic components, the evidence for this is not very strong. The work shows that the slope of aperiodic components changes at the transition from movement to resting condition but based on the reported findings it is not clear whether this represents more than just a gradual change in the amount of movement of the rodents. As for the comparison of SPRiNT to alternative approaches, the conducted testing against alternative methods does not unambiguously demonstrate its value in examining time-resolved properties of periodic and aperiodic components. This holds both for using SFTM vs. wavelets, using specparam based parametrization vs. direct estimates from STFT analyses, and using SPRiNT vs. basing the parametrization on a single spectral estimate across the whole duration of a task/state. The work thus 1) presents a novel approach for enhancing the study of a timely neuroscientific question that aims to facilitate the investigation of a broad range of related questions within the field, 2) shows that the dynamic properties of cortical oscillations within a uniform task can be a relevant marker of neural activity for dissociating different subject groups, and 3) yields added evidence on the importance of investigating the task- and state-dependence of aperiodic activity. However, the present level of testing of SPRiNT and evaluation of the observations do not fully allow one to evaluate the impact of the method and to determine the importance of investigating the different neural components (periodic vs. aperiodic) in a time-resolved manner.

In my opinion, the study could be improved particularly by extending the comparison of SPRiNT to alternative approaches as well by a more thorough discussion of the observations, especially as regards the value of time-resolved analysis of aperiodic vs periodic neural activity.

Specific comments

1. Based on the simulated data, SPRiNT seems to be very efficient and robust, and it is also superior to the wavelet-specparam approach. However, while the simulations are very extensive, I find that they are constructed in a manner that may induce biases as the comparison is conducted between SPRiNT and a single, fixed wavelet-based approach. Like any spectral analysis technique, wavelets possess their own trade-off between temporal and frequency resolutions. As the wavelet analyses are conducted using a fixed set of parameters, it may be that some of the differences between the methods stem from how well they are suited for detecting the simulated activity that is constructed using a certain standard deviation of their oscillatory frequencies. It would be valuable to evaluate whether changing the wavelet-analysis parameters or the width of the simulated oscillations would change how the alternative methods compare. It is of course clear that the STFT based approach would remain computationally superior, but it would be interesting to see whether the other differences would remain as robust after the above more detailed evaluation of the methods. Related to the method comparison, it also appears that the outlier removal within SPRiNT markedly improves the quantification of the periodic components. This matter could be discussed more within the manuscript.

2. As for the investigation of real data, there are a few aspects that in my opinion could be investigated more thoroughly. Based on the findings it appears that the fine-grained time-resolved parametrization yields added value, especially in eyes-open rest where the fluctuation of alpha center frequency dissociates the different age groups, whereas the other time-resolved findings are not as unambiguously supportive of the need for fine-grained time-resolved analysis. Regarding the first point (fluctuation of alpha center frequency), the finding that the amount of fluctuation within the alpha frequency is distinct across age groups is very interesting. On the methodological, an open question is whether SPRiNT is required for making this observation. That is, is this effect observed only when applying the specparam-based parametrization (and outlier removal) after STFT or would the same observation have been made simply by estimating the fluctuations directly from the STFT based spectral estimates? As for using SPRiNT to determine the properties of aperiodic activity, presently it is not clear whether the approach yields added value compared to the more direct use of specparam. That is, the present findings show that the mean aperiodic slope dissociates both different age groups and resting-state conditions (eyes-open vs. -closed). It would be appropriate to test whether the same observation would be made by using specparam in the more standard way by first obtaining one spectral estimate across the whole one-minute time windows and then parametrizing this estimate. This type of testing would yield insights into whether there is a difference between SPRiNT that builds on dynamic but noisier spectral estimates and that allows the outlier removal and the standard approach benefiting from more stable spectral estimates for the present data and possibly for other questions. As for the rodent movement data, the evidence is clear that the aperiodic exponent differs between resting and movement state. However, the fundamental meaning of the change of the exponent at transition points is not explored. Does this change simply reflect the speed of the animal/amount of movement that changes across the time period prior and post rest and movement onsets? That is, does the transition curve align with the movement curve or does it represent something more complex? This aspect could be evaluated and discussed more extensively. Together, the above additional evaluations would be beneficial for determining whether there is value in looking at aperiodic activity in a time-resolved manner and whether a fine-grained analysis is needed or would a more static analysis fact takes into account the tasks/states fare equally or even in a superior manner.

Reviewer #1 (Public Review):

This manuscript reports a new genetically encoded neuronal silencer BoNT-C. They show that it fully blocks neurotransmission in two classes of Drosophila motor neurons (Is and 1b; tonic and phasic, respectively). They also update a GCaMP postsynaptic reporter SynapGCaMP to express GCaMP8f instead of 6f. They selectively silence 1b or 1s neurons to disambiguate the neurotransmission properties of each neuron. Finally, they show that silencing either 1b or 1s neurons does not induce heterosynaptic structural or functional plasticity (only neuron ablation triggers plasticity). The data are convincing. The new silencing tool will be widely used.

Reviewer #2 (Public Review):

In this manuscript, Han et al. investigate the intrinsic and heterosynaptic plasticity in motor neurons with emphasis on both structure and function of neuromuscular junctions (NMJs) in fruit fly larvae. The larval NMJs have been extensively used by multiple labs as a model to study both the structure and function of synapses, shedding light on mechanisms of heterosynaptic plasticity. The body wall larval muscles in Drosophila are coinnervated by two types of glutamatergic excitatory motor neurons: Ib and Is. Ib MNs establish big synaptic buttons and exhibit a tonic firing pattern, while Is MNs make smaller synaptic buttons and have a phasic firing pattern.

First, the authors develop a new genetic tool (BoNT-C) to selectively suppress neurotransmission in either Ib or Is synapses without affecting the intrinsic structure of the pre and post-synaptic components of the NMJs. Compared to previously used methods (e.g. using Kir2.1, TNT, or apoptotic ablation), this is a significant advance in the field. Then, the authors take advantage of this tool to study how BoNT-C mediated silencing of Is inputs affects the structure/function of Ib inputs and vice versa. In parallel with using BoNT-C, the authors perform similar experiments in animals where Is or Ib NMJs are being perturbed by TNT or apoptotic ablation, enabling them to accomplish a nice comparative analysis of data collected from different animal groups. The authors make two significant conclusions as below:

1) Synaptic assembly, composition, and growth of Drosophila NMJs (both pre and post-synapse components) are not dependent on neurotransmitter release or firing patterns of motor neurons (phasic vs tonic).

2) Heterosynaptic structural or functional plasticity is induced only when MN-Is or MN-Ib innervation is physically absent. Such Heterosynaptic plasticity is not observed when they use BoNT-C to functionally silence (but not structurally perturb) MN-Is or MN-Ib motor neurons.

The conclusions of this paper are properly supported by the provided data. Overall this work opens a new window to examine novel aspects of heterosynaptic structural and functional plasticity.

Reviewer #3 (Public Review):

The strength of the manuscript by Han et al. is the comprehensive characterization of BoNT-C, showing that it truly abolishes all evoked and mini responses without structural alteration of the NMJ. Based on this, the authors then show that ablation of all neurotransmission in either Ib or Is does not cause any compensatory changes (neither functional nor structural) in the 'other' (i.e. looking at Is when silencing Ib or looking at Ib when silencing Is).

The weakness of the manuscript lies in the modest gain over the previous work. Specifically, Aponte-Santiago had already shown that many parameters are not changed (in Ib when Is is perturbed, or in Is when Ib is perturbed), including that 'the Is terminal failed to show functional or structural changes following loss of the coinnervating Ib input' (quote from 2020 paper). Hence, the only major difference is that Han et al now show that Ib also does not really change when Is is silenced. Aponte-Santiago also clearly showed a ~50% EJP reduction when Is or Ib are perturbed alone, and adding these two equals wild type. The highly emphasized finding of Han et al. that (quote) ' composite values of Is and Ib neurotransmission can be fully recapitulated by isolated physiology from each input' quite obviously follows from the one key finding that one does not affect the other, as mentioned above in the strengths. The wording is a bit odd, but really adding Is (with Ib perturbed) and Ib (with Is perturbed) inputs is really not adding much over either the main finding nor the previous work. On a different but somewhat similar topic, UAS-BoNT-C is not a new tool. I am a bit put off by the wording ' We have developed a botulinum neurotoxin, BoNT-C...'. More on this and the way the previous BoNT-C paper (Backhaus et al., 2016) is cited in the detail comments below in the recommendations for the authors. Additionally, the manuscript does not really dive into an analysis of phasic versus tonic functions (that's just a correlation with the Is and Ib dominant modes of function). Finally, since the authors show that loss of Is or Ib function does not cause any change in the other, we are left to wonder what actually DOES cause heterosynaptic plasticity. TNT or rpr DO cause some heterosynaptic plasticity and they also DO cause some structural changes - but whether the structural changes themselves are important here remains unclear. Substantial progress would have been to take the starting point that BoNT-C does not cause heterosynaptic plasticity, and then identify the signal that does (is is morphology? or signaling between Is and Ib? Or with the muscle?).

Overall, while an initial reading of the manuscript sounded rather exciting, a deeper analysis of the work in context of the literature of the last few years diminishes my enthusiasm for the novelty and progress provided.

Reviewer #1 (Public Review):

This study puts forward a novel mechanistic model of neurotransmitter vesicle fusion (vesicle exocytosis) which is relatively simple but significantly more detailed than the widely used phenomenological models of calcium-dependent fast exocytosis. The main goal of the Authors is to account more fully and holistically for the known properties of neurotransmitter release, namely: (1) the highly nonlinear dependence of neurotransmitter release rate and latency on calcium ion (Ca2+) concentration, based on the published recordings obtained from the giant calyx of Held auditory synaptic terminals, (2) the low intrinsic Ca2+ affinity of the main sensor for Ca2+ triggered exocytosis, synaptotagmin (Syt); (3) evidence that synaptotagmin's Ca2+ affinity is greatly increased after is binds to PIP2 phospholipids that are concentrated at the interface between the vesicle and synaptic membranes.

The main conclusions of this study is that the increase in Syt sensor's affinity to Ca2+ upon allosteric binding to PIP2 phospholipids is sufficient to account for the observed high sensitivity of neurotransmitter release rate and latency to Ca2+ elevations, and that the best fit to experimental data is achieved if about 15 Syt molecules are positioned along the surface of the vesicle, with three (on average) Syt molecules binding to PIP2 and Ca2+ before vesicle fusion is triggered. Thus, the study provides an explanatory framework for predicting the synaptotagmin copy number distribution per vesicle.

STRENGTHS

The proposed model occupies a "sweet spot" in terms of level of detail, going beyond widely used phenomenological models that are too simple to provide descriptive insight into the molecular interactions underlying observed Ca2+ dependence of vesicle fusion rate and latency, but staying away from highly detailed molecular models that cannot be fully constrained using existing experimental data, and which may not be needed to account for the main features of fast calcium-triggered exocytosis.

The advantage of the proposed model is that it holistically ties together within a single, relatively simple framework the main features of neurotransmitter release at central synapses, namely: (1) the high order (4th or 5th order) cooperativity in Ca2+ binding, despite the fact that only two Ca2+ ions bind to the relevant C2B domain of any single Syt molecule during fast calcium-triggered vesicle fusion; (2) the increase in Syt affinity to Ca2+ upon PIPs binding; (3) Syt copy number distribution per vesicle.

An appealing feature of the model is that it naturally leads to (and therefore explains in more depth) the phenomenological model of vesicle fusion put forward previously by Lou, Scheuss and Schneggenburger (2005), whereby vesicle fusion can proceed in several stages with increasing rate, which the proposed model explains in terms of the increase in fusion probability with increasing number of Syt-PIP2 "bridges" formed between the vesicle and synaptic membrane upon Syt binding to Ca2+ and PIP2. I think this model can also be viewed as a more detailed extension of the "excess binding site" model of Stephen D. Meriney and colleagues.

Another strength of this work is that it carefully examines and solves a fully stochastic model of vesicle fusion, rather than a simplified mass-action representation that would not be adequate given the small copy number of Syt1 and Syt-PIP2 "bridges" proposed in this model. For the case of constant Ca2+ pulses, the Authors take advantage of the exact solution of the underlying Markov process, and perform stochastic simulation for a transient Ca2+ signal that mimics an incoming action potential.

Finally, parameter values were constrained very systematically, using an automated optimization algorithm that allows an unbiased estimate for modeling parameters achieving the best fit with experimental data. Quite appropriately, a derivative-free optimization approach was used, since optimization methods based on gradient descent would not perform well if the objective/cost function calculation involves numerical integration and is susceptible to other sources of numerical noise.

Given the relative simplicity of the model, it can readily be used in computational studies that rely on accurate representation of calcium-triggered vesicle fusion that goes beyond simple mass-action schemes, but does not require molecular-level precision and resolution in modeling the underlying processes.

Importantly, the simulation source code is included, allowing to reproduce the results of the model.

Finally, I would like to note that despite the technical nature of the model, the manuscript is written in an accessible way, and figure are well designed, making it easy to follow the logic of this work.

WEAKNESSES

Given the Authors' choice of modeling detail level, and the overall scope of the study, I do not detect significant weaknesses in the approach or results. The only potential weakness I can see is that the assumption of simultaneous binding of two calcium ions, rather than a sequence of two binding events, may affect the estimation of vesicle release latency examined in this study.

Of course, the simplified model proposed here cannot fully account for all molecular interactions involved in fast non-constitutive vesicle fusion, and in particular, the interaction of synaptotagmin molecules with the SNARE machinery is only represented as the height of the barrier to vesicle fusion, but a full model may not be needed for a descriptive understanding of this phenomenon.

More minor suggestions for improvement are conveyed in a separate recommendation for the Authors.

Reviewer #2 (Public Review):

Vesicular synaptotagmins are the undisputed Ca2+ sensors for synchronous neurotransmitter release. However, despite intense study it remains unclear exactly how the binding of 5 Ca2+ ions to Synaptotagmin's two C2 domains leads to the observed Ca2+ dependence of vesicle fusion. Moreover, it is unclear how many Syts bind Ca2+ to initiate fusion. This is a fascinating question. For decades, the 4-5 power dependence of exocytosis on Ca2+ was attributed to cooperative binding of 5 Ca ions to Syt1. This study convincingly proposes an alternative scenario, where cooperative Ca/PIP2 binding and multiple Syt1 molecules can explain the Ca dependence of release. The authors make interesting and testable predictions about the molecular mechanism by which the C2B domain initiates fusion, and about the number of Syts required for synchronous release. To improve the readability and impact of this study, the authors should highlight what is novel about the predictions of their model, and put them in context with previous studies and interpretations.

Reviewer #3 (Public Review):

In this paper by Kobbersmed et al., the authors used mathematical analysis to investigate the role played by the interaction of Ca2+, PIP2, and synaptotagmin in shaping the kinetics of neurotransmitter release. Published data from in vitro analysis of the affinities of synaptotagmin1 for Ca2+ and PIP2 and the copy numbers of synaptotagmin molecules per vesicle are used in the model. Applying the model predictions to published data at a specific synapse (calyx of Held), the authors show that conformational stabilization of a crosslinking synaptotagmin/Ca2+/PIP2 complex plays a role in extending the dwell time needed to allow multiple crosslinking. These crosslinks are assumed to lower the energy barrier for vesicle fusion. An assumed strong cooperativity of Ca2+ and PIP2 binding to synaptotagmin can solve the problem that the Ca2+ affinity of synaptotagmin measured in vitro (Kd in the range of 200 µM) is much lower that the estimated Ca2+ affinity of the Ca2+ sensor for vesicle fusion measured at the calyx of Held (Kd in the range of 5 µM). A minimum of three crosslinked synaptogamins per vesicle was enough to account for physiological data obtained at the calyx of Held, nevertheless higher copy number of synaptogamins ensured a higher probability of interaction of synaptotagmin with Ca2+ and PIP2. The approach is innovative because the author aim to explain synaptic parameters with simulations of single synaptotagmin molecule. The main concern is that the validity of the conclusions is difficult to judge as the study relies only on modeling. Some of the assumptions of the modeling could be wrong and there is no attempt for experimental validation of the model.

Reviewer #1 (Public Review):

The paper by Ichiyama et al. characterizes how CRH-expressing neurons of the paraventricular nucleus of hypothalamus (PVN) alter their firing characteristics during an acutely stressful experience. The authors first use in vivo single-unit extracellular recordings from optogenetically identified CRH neurons in PVN, before and during noxious stimulation of the sciatic nerve. CRH neurons fire in bursts during basal conditions that included long interburst non-spiking periods. During the stressful stimulus, instead, these cells stopped bursting, became tonically active and had increased overall firing rates. An in silico network model simulated the PVn network and used realistic synaptic currents injected into CRH cells. This model illustrated how simple recurrent inhibition can act as a switch changing the cells from one firing pattern to the other.

The experiments are carried out with care and the data are of high quality. This manuscript represents the first time to my knowledge that electrophysiological recordings have been used in vivo to track the firing of individual CRH neurons before and during acute stress. The authors then created a network model to test the idea that synaptic currents may shift the firing patterns of these cells from a bursting to a tonic firing state, and present evidence that a drop in GABAergic inhibition coupled with an increase in spike-triggered adaptation mimicked the effects seen in vivo after stress. Taking this information back to neurons in brain slices, the authors use their model to drive similar changes in spike patterns by altering relevant synaptic and intrinsic currents.

There is some concern that previous work examining the role of other intrinsic currents in burst behavior as well as in vitro data from CRH neurons in slices after stress are not discussed or considered.

Reviewer #2 (Public Review):

Ichiyama et al. revealed the neural mechanism of state-dependent change by recording from corticotropin-releasing hormone (CRH) neurons in the paraventricular nucleus (PVN) and by in silico remodeling. The firing pattern in CRHPVN neurons is rhythmic brief burst (RB) and continuous single spike (SS). The authors revealed that recurrent inhibition is involved in the activity state switch between RB and SS. In silico remodeling will help to understand changing of the firing pattern in the peptidergic neurons in the hypothalamus and the neural regulatory mechanism of stress response by CRHPVN neurons.

Reviewer #3 (Public Review):

This manuscript by Ichiyama et al examines the firing properties of identified CRH neurons in the paraventricular nucleus of the hypothalamus in anaesthetized mice. They make a rather surprising observation that CRH neurons show high frequency, albeit brief, rhythmic bursts in unstressed mice only. A brief stressor converts cell activity into a more sustained, single spike firing mode. The authors support their observations with a computational model that suggests feedback inhibition may regulate the activity patterns of CRH neurons in distinct states.

As the authors correctly note, this is the first electrophysiological study showing spike activity in CRH neurons. Although there have been other studies using Ca imaging, none have shown spike activity. Part of the challenge is obtaining high-quality recordings from a deep structure like the PVN; the other is identifying individual cells with high confidence when they are surrounded by other, non-CRH cells.

This is an important contribution that furthers our understanding of CRH activity in vivo. It is also an unexpected observation that uncovers interesting neural dynamics that will provide the impetus for new studies exploring firing characteristics in discrete physiological and emotional states. The work will be influential. It is critical, therefore, that the authors are certain about the identity of the neurons.

Reviewer #1 (Public Review):

Aldonza MB, et. al. aim to understand how fucosylation of the cancer cell secretome affects the response to therapies. To begin, the authors analyze publicly available cell-based expression and drug sensitivity data, and conclude that high expression of FUT8, a fucosylation gene, results in resistance to specific therapies, including RTKs, EGFRi, and MAPK/ERK pathway inhibitors. The authors explore this further through the generation of 16 drug resistant cell lines, using inhibitors of EGFR, HER2, BRAF, MET, and ALK. The authors identify that fucosylated proteins, between 40-60kD are upregulated in drug resistant CM and patient serum, which the authors identify as PON1, a protein with paraoxonase enzymatic activity and component of HDL. The authors show that PON1 fucosylation, at N253, resulted in increased stability and secretion of the protein. Blocking PON1 fucosylation, through knockdown of PON3 or expression of PON1-N253G, blocked the outgrowth of resistant cells. Exploration into the mechanism of how PON1 was contributing to therapy resistance, lead the authors to explore the UPR and ATF6 as potential downstream targets of PON1. Finally, the authors use transcriptomics to also look for potential downstream effectors of fucosylation. These data are interesting and show a potential mechanism of resistance to EGFR/MAPK pathway inhibitors via secreted factors.

While the conclusions of the paper are mostly well supported, the manuscript is dense and sometimes difficult to follow. Some additional clarification is needed.

1. The authors use analysis of many publicly available datasets to set up and frame their story of how fucosylation contributes to widespread therapy resistance. However, the data in these figures (1A, 1C, and 1D) in fact show that expression of FUT genes are correlated with a range of therapeutic response, not widespread resistance to all therapy which the authors claim. However, the depth in which the authors explore EGFR and MAPK pathway inhibition is a strength, and the authors show a potential mechanism to how fucosylation is contributing to resistance to these therapeutics.

2. The authors use extensive cell models to test their hypotheses, however, they do not perform any in vivo experiments. It would be important for the authors to test their mechanism (modulation of FUT8 or PON1 through shRNA or overexpression) in vivo to determine if modulation of these factors changed tumor growth inhibition or the time to development of resistance.

3. As stated above, FUT8 expression was correlated with resistance to specific therapies, including RTKs, EGFRi, and MAPK/ERK pathway inhibitors. How does treatment with these inhibitors increase PON1 fucosylation? This is an important question that remains unanswered. Discussion of why fucosylation of PON1 is contributing specifically to the resistance of these inhibitors would be of interest to readers and should at least be commented on in the discussion.

Reviewer #2 (Public Review):

In this study, the authors study therapy-induced fucosylated secretome signatures at a pan-cancer level. The authors initially profiled therapy-associated changes in fucosylation-related genes and their methylation statuses by querying a number of online datasets including CCLE and GDSC. They found that fucosylation-related gene expression is correlated with various therapies. Further, they identified fucosyltransferase 8 (FUT8) as a key therapy-associated fucosylation gene, the expression of which correlated with reduced responsiveness. In vitro, the authors demonstrated that targeted kinase inhibitors distinctively induced core fucosylation of secreted proteins <60 kDa. They further established that the fucosylation of these secreted proteins is regulated by the fucose salvage SLC35C1-FUT8 pathway and is enriched in the Golgi prior to secretion. The authors further demonstrated that the upregulation of core fucosylation of the secreted proteins correlated with drug resistance in a patient cohort and drug resistance clones. By the label-free proteomics of N65 glycoproteomes the authors discovered antioxidant PON1 as a critical component of the therapy-induced secretome. The authors showed that the core fucosylation at N253 is required for PON1 stability and secretion, and further that PON1 fucosylation is mediated by PON3 in the Golgi, which establishes the Golgi redox homeostasis. The transcriptomic analysis demonstrated that genes negatively regulating the response to stimulus and cell communication act as modulators upon inhibition of secretome PON1 fucosylation.

General Comments:

This is a novel study where the authors study the fucosylated secretome that is induced during therapy, which promotes resistance. The authors conducted a detailed in-vitro study by generating the resistance clones and comprehensively analyzing PON1 fucosylation. Although the authors have delineated the effects of fucosylation on the stability and secretion of PON1, how fucosylated PON1 promotes therapeutic resistance, remains unclear. Moreover, the study would have benefitted from in vivo validation of the author's findings to delineate the contribution of fucosylated PON1 to the development of therapeutic resistance (and perhaps other tumorigenic capacities not observed in the in vitro assays). Nonetheless, this study highlights novel contributions of fucosylation specifically to therapeutic-stress induced adaptations that promote resistance. Further, the findings reported herein lay the foundation for subsequent assessment of fucosylation/fucosylated secretome-related novel therapeutic targets and biomarkers that are predictive of therapeutic responsiveness.

Reviewer #3 (Public Review):

This is a data rich manuscript that provides a novel basis for drug resistance. The authors show an increased fucosylation of secreted proteins is a hallmark of drug resistance to multiple targeted therapies. Through unbiased approaches the authors demonstrate that fucosylated PON1 is secreted and is degradation resistant. Furthermore, PON1 is essential in driving drug resistance through decreasing tumor inflammation and oxidative stress. This is a robust and rigorous study that provides a novel and druggable mechanism for drug resistance in cancer.

Reviewer #1 (Public Review):

It is thought that gene duplications are a major factor driving the emergence and expansion of paralogous proteins. But how redundant proteins evolve to acquire new interactions specificities is poorly understood.

Here the authors focused on understanding how specificity evolves in signaling pathways involving two-component systems. In bacteria two-component systems contain a sensor histidine kinase (HK) and cognate response regulator (RR), usually encoded in the same operon. Upon signal recognition by the kinase, signal transduction is activated resulting in the phosphorylation of the response regulator. Most bacteria have dozens of these systems, however cross-talk between different response regulators and non-cognate response regulators is usually minimal. This specificity was shown to be explained by a small number of amino acids residues involved in the interaction between the histidine kinase and the response regulator responsible for preventing cross-talk between non-cognate proteins.

How does this specificity evolves to prevent cross-talk between recently duplicated pairs, is the question the authors address here. They assume that for novel signaling pathways to occur newly insulated pathways need to be established following a duplication event. They asked how many mutations, and in how many of the proteins in each pair would need to acquire mutations to obtain insulated pathways with absence or minimal cross-talk between non-cognate proteins.

They used a bio-informatics approach (ancestral protein reconstruction) to infer the sequence of ancestral histidine kinase (ancHK) and ancestral response regulator (ancRR) existing prior duplication events, and to infer two pairs of ancestral paralogous post-duplication. They cloned and expressed this proteins, and measured the specificity of all these reconstructed proteins. They observed that each kinase showed slower transfer (thus lower specificity) to the non-cognate partner. Similarly, to the currently occurring counterparts in Calaubacter crescentus.<br /> Then they identified and tested mutations predicted to be involved in specificity. They identify three residues involved in preventing cross-talk between non-cognate pairs of two pairs of paralogous proteins, and propose that these residues were sufficient for the establishment of specificity following the duplication event. Moreover, they propose that these 3 mutations would be enough to establish insulation of two signaling pathways. Interestingly, these mutations affect only one protein from each of the two-component system studied. Showing that specificity and insulation of pathways can be achieved without the need of mutations in all the proteins involved. This was surprising as initially expectations were that to obtain insulated pathways after a duplication event all the four proteins involved would have to acquire mutations in the two protein-protein interfaces involved. These finding highlight the importance of acquisition of mutation that prevent interactions with non-cognate proteins in insulation and in the emergence of novel signaling pathways.

To understand how general these findings are additional work with other paralogous interacting proteins would be needed.

In summary, here the authors observed that the inferred duplicated paralogous gained specificity towards their cognate pairs in comparison with the inferred ancestral proteins. They used a clever approach to identify residues involved in preventing cross-talk between non-cognate protein paralogous and they propose that these residues were responsible for driving insulation of paralogous pathways post-duplication.

The manuscript is well written and technically sound.

Reviewer #2 (Public Review):

Nocedal and Laub used ancestral sequence reconstruction to study how protein interaction specificity evolves following a gene duplication event. They considered the EnvZ-OmpR two component signaling system. This histidine kinase-response regulator pair underwent a duplication event in alpha-proteobacteria to yield the paralogous EnvZ1-OmpR1 and EnvZ2-OmpR2 systems in Caulobacter crescentus. The authors used ancestral sequence reconstruction to design maximum likelihood EnvZ-OmpR sequences immediately prior to this gene duplication and just after the gene duplication event. They then characterized these ancestral sequences in vitro, and compared their interaction specificities to those of the extant, native EnvZ-OmpR systems. They found that three mutations introduced soon after gene duplication are sufficient to rewire signaling specificity. Interestingly, the mutations are not isolated to one of the duplicated pairs, but instead are spread across the histidine kinase of one pair and the response regulator of the other. This is consistent with a model in which signaling cross-talk is avoided through sub-functionalization of both protein pairs, rather than neofunctionalization of only one. The experiments appear very well done, the data are presented logically, and the results strongly support their conclusions.

These experiments nicely add to a growing body of work from the Laub lab that shows how a small number of mutations can lead to new specificity and prevention of cross-talk. Prior work from the same lab has already established that a small number of mutations can rewire specificity in the context of rationally engineered sequences (e.g. Capra 2010, McClune 2019, and Skerker 2008, as cited by the authors), here this is demonstrated using ancestral sequence reconstruction. More generally, we know that protein interfaces are marginally stable, and that interface stability is typically the result of a small number of thermodynamically favorable interactions (classically: Clackson and Wells (1995) Science v.267(383)). Given prior work from the Laub lab, as well as engineering studies from other groups on different model proteins (e.g: Kapp et al (2012) PNAS v.109:5277), it is well-expected only a small number of mutations are necessary to rewire specificity. Thus, the results are not particularly surprising, though the use of ancestral sequence reconstruction brings an interesting new dimension to exploring protein interaction specificity. While the data imply a model for evolution of protein-protein interaction specificity through sub-functionalization rather than neofunctionalization for this particular protein pair, it is unclear that this finding should generalize to other protein pairs (or even that a general strategy for evolving specificity post gene duplication should exist at all).

Reviewer #3 (Public Review):

The authors set out to understand how proteins arising from gene duplication evolve to avoid cross-talk. The used ancestral sequence reconstruction to infer ancestral sequences for two paralogs of bacterial histidine kinases (HK) and their downstream response regulators (RR). They focused on three ancestral pairs of proteins: the preduplicate ancestor (ancHK/ancRR), the paralog 1 ancestor (ancHK1/ancRR1), and the paralog 2 ancestor (ancHK2/ancRR2). They found that ancHK and ancRR were compatible with each other and their descendants. Post duplication, each HK/RR pair gained specificity: ancHK1 prefers ancRR1 to ancRR2; ancHK2 prefers ancRR2 to ancRR1. They traced these differences in specificity to sequence changes in ancHK2 and ancRR1. ancHK2 acquired two mutations that excluded interaction with ancRR1. ancRR1 acquired a mutation that both disrupted its interaction with ancHK2 and increased its interaction with ancHK1. This reveals two different mechanisms for decreased cross-talk: exclude interaction with a non-cognate partner (mutations that disrupt ancHK2/ancRR1 interaction) or promote interaction with the cognate partner (mutation that improves ancHK1/ancRR1 interaction).

Strengths:

The story the authors present is clear, well-written, and intriguing. I find it particularly fascinating that the two lineages disrupted cross-talk by different mechanisms, and that this involved changes to either the HK or the RR, but not both on the same lineage. The phylogenetic and experimental results are mostly clear and convincing. Such work dissecting the evolutionary biochemical mechanisms by which signaling pathways diverge is important for a number of reasons. 1) It can reveal hidden mechanisms of specificity not obvious from simple structural analyses (for example, the mutations this study revealed that allow separation of paralog 1 and paralog 2 signaling.); 2) It helps us understand how prima facie complex evolutionary problems can be readily resolved with only a few mutations; and 3) It shows the "design principles" of these signaling pathways, namely that avoiding cross-talk can likely be achieved by relatively small changes to kinetics of the interactions between non-cognate and cognate proteins.

Weaknesses:

1. The authors reconstruct a single phylogenetic tree for both the HK and RR components, concatenating the sequences together and then performing a single analysis. This could be problematic. First, if horizontal gene transfer occurred for one, but not the other, partner, the gene trees for the HK and RR components could be discordant. In this scenario, the reconstructed sequences would be incorrect because they were done on an a prior concordant tree. Second, there was insufficient detail in the methods to know how the matched pairs of HK/RR sequences were generated. If the authors inadvertently mixed up paralogs (e.g. generating incorrect HK1-RR2 or HK2-RR1 concatenations) this could lead to a poor phylogenetic inference. A simple way to check for both problems would be to generate phylogenetic trees for HK and RR separately and check for tree concordance. If the separate trees are concordant, the concatenated sequences are justified. If the separate trees are discordant, the authors would have to determine whether independent reconstructions would alter their reconstructed sequences.

2. The authors use a simple in vitro phosphorylation assay as their assay for the ability of HK to phosphorylate RR. There were, however, two aspects of the assay that were not clear in the text.

2A: First, the authors built their quantification around tracking the depletion of phosphorylated HK. There were a number of variants that showed much slower HK dephosphorylation than others, with barely detectable RR phosphorylation. A sceptical reviewer might wonder if this is slow activity represents specific dephosphorylation or instead spontaneous dephosphorylation to inorganic phosphate. (If the latter, the reconstructed protein is not really functional at all). An appropriate negative control would be tracking the rate of dephosphorylation of HK with no RR added.

2B: Second, the authors used this assay to compare relative catalytic efficiencies (kcat/KM) of their variants. It was unclear how they extracted this information from the data as presented, which consist of a single velocity curve determined at a fixed concentration of HK and RR. In most contexts, obtaining kcat/KM requires measuring V0 vs. 0. More information on what precisely is being reported is necessary. (I should note that their qualitative results, looking at the gels, won't be affected by this; just statements like a 28-fold preference of ancHK2 for ancRR2 vs. ancRR1).

3. There are a number of places where existing work in the field could be cited more appropriately. The authors argue in a couple of places that ASR has not been used to reconstruct historical protein-protein interactions; however, this is not true. Examples include: Holinksi Proteins 2016 https://doi.org/10.1002/prot.25225; Wheeler et al 2018 Biochemistry https://doi.org/10.1021/acs.biochem.7b01086; Lauren et al. MBE 2020. https://doi.org/10.1093/molbev/msaa198; and Wheeler et al MBE 2021. https://doi.org/10.1093/molbev/msab019. Further, on p. 17, the authors cite Field and Matz MBE 2010 as an example of a study looking at the evolution of protein/small-molecule interactions. This is not true: that study looked at the evolution of GFP-like protein color.

4. The authors suggest in a few places that the deepest ancestor (ancHK/ancRR) was not optimized for phosphate transfer because this activity improves for later ancestors. An alternative interpretation is that these deepest ancestors are relatively poorly reconstructed, and thus that overall activity is lower. Indeed the alternate reconstruction of ancHK-alt/ancRR-alt barely showed detectable activity. As such, I think the poor reconstruction hypothesis is much more likely than a suboptimal ancestral function that was subsequently optimized.

Reviewer #1 (Public Review):

This work provides new insights into the contribution of Native American ancestry to skin pigmentation in the absence of European ancestry. To investigate potential skin-lightening alleles associated with Native American ancestry, the authors turn to the Kalinago, an admixed population on the Caribbean island of Dominica with predominantly Native American and African ancestry. Additionally, this paper provides an interesting analysis of previously reported albinism alleles, which paints a more complex picture of the genetic architecture of pigmentation.

Strengths:<br /> This article presents new data on a population with an understudied ancestry composition. Many Native American populations have considerable European admixture. Genetic variance of Native American origin that contributes to decreased skin pigmentation may be hard to distinguish in the presence of European ancestry. Therefore, finding an admixed population with primarily African and Native American ancestry should provide a unique opportunity to explore skin pigmentation-related variation without the overwhelming signal of European alleles. Moreover, this study contributes to the diversification of populations included in genomic research.

This work provides an intriguing exploration of three Kalinago individuals with albinism, and it reports a novel variant associated with albinism in this population. The authors initially looked at 28 mutations previously reported to be associated with albinism in African and Native American populations. But none of these variants were present in their three Kalinago participants with albinism. They then decided to carry out whole-exome sequencing of one of the albino individuals and one of their parents to search for what specific variants may be associated with albinism in this particular population.

The authors report 12 candidate variants across seven oculocutaneous albinism (OCA) genes that were heterozygous in the parents and homozygous derived in the albino individual (a criterion for a recessive condition). Of those candidates, they focus on two missense mutations in OCA2: R305W and NW273KV. One of those variants, NW273KV, was previously reported in a compound heterozygote African American individual with albinism.

This novel variant was homozygous derived in all three Kalinago individuals with albinism. Moreover, the authors were able to ascertain a hypopigmentary effect in heterozygous individuals.

The genome-wide association study described in this paper provided effect sizes for several variants associated with pigmentation in the Kalinago. However, the predicted effects (based on an additive model) could not explain the measured phenotype in the three albino individuals. This provided concrete quantitative evidence that these pigmentation variants (and likely, others) do not work in a simple additive manner. Overall, this paper contributes significantly to the pigmentation genetics literature and provides further incentive for exploring the genetic architecture of pigmentation in diverse populations.

Weaknesses:<br /> My main criticism of this paper is that it only considers the possibility for Native American-derived pigmentation alleles to contribute by decreasing pigmentation. The paper frames Native American and East Asian ancestry as necessarily tied to lighter pigmentation. However, this does not consider that there have been previous reports of Native American-European populations where Native American ancestry has been associated with darker skin.

Along this line, it is unclear why the authors bring up shared ancestry between East Asians and Native Americans. If they are looking for derived variants in Native American populations that would have arisen after the split from a common ancestor with East Asians, it is unclear why they expect that those variants would have a depigmenting effect, as opposed to increasing pigmentation.

The exclusive consideration of the adaptive nature of light pigmentation is evident in this paper's discussion of the vitamin D hypothesis, but the omission of the corresponding folate-protection hypothesis, which posits that darker skin would provide critical adaptive benefits in high UV environments. The authors themselves note that the Kalinago would have migrated relatively recently from the northern part of South America (a high UV area). So presumably, if there had been any recent selection relating to pigmentation in this Native American population, the expectation should be that it would have been in the direction of darker skin.

This criticism does not affect the conclusions of the paper. However, I believe the paper would be stronger if it offered a justification of the search for depigmentation alleles only.

Reviewer #2 (Public Review):

This paper investigates the genetic structure and genetic basis of skin pigmentation in the Kalinago population in the Commonwealth of Dominica. The paper makes three main claims.

1. Kalinago individuals have recent ancestry from Native American, African and European sources.<br /> 2. The identification of a coding variant in OCA2 (likely from the African source population) with a large effect on pigmentation and that causes albinism in heterozygous form.<br /> 3. That a negative correlation between Native American ancestry and skin pigmentation indicates the presence of unknown derived alleles associated with skin pigmentation in that population.

I think that claim 1 is likely true although the ADMXITURE analysis presented in the paper is less quantitative than presented. This claim could be further tested by local ancestry analysis. Claim 2 is supported. Claim 3 is likely true although I not surprising given the observed differences in pigmentation between Native American and West African populations.

Reviewer #3 (Public Review):

This pigmentation study focuses on a community from Kalinago Territory from the Caribbean islands that on average possess high percentages of Indigenous American ancestry, and broadens the effort of quantifying the genetic effects on skin pigmentation in humans. It is appreciable that the authors intended to explore the trait in understudied populations.

The manuscript has a cohesive and detailed introduction to the population history of the Kalinago Territory community and guided the readers to understand the anthropological background and the formation of the populations' ancestry composition. The layout and logic of the result section is easy for readers to follow. The authors also had an efficient analysis design to narrow down candidate albinism alleles from exome data with three albino individuals in their samples. However, limitation exists on the scope of the study, where the authors characterized variants' effect from only three known genes in Europeans (SLC24A5, SLC45A2, OCA2), whilst a lot more have been documented (e.g. KITLG, TYRP1). It is also surprising that the authors claimed no previous establishment on pigmentation genetics in Native Americans and East Asians while there have been quite a few, and did not provide sufficient discussion or comparison of their results and these studies.

I also have some remaining concerns about the validity of the major scientific conclusions being supported by the current evidence. Based on the overall study design and very sparse methods description, it is unavoidable for readers to speculate each analysis. For example, the existing methods did not indicate that the authors used the correct statistical model for association analyses to estimate the effect sizes, in presence of close relatedness in their samples; The conclusions on ancestry contribution are ambiguous with regard to the resolution of ancestry decomposition being used in the downstream linear models and association tests; There are technical concerns whether several key methods, including ancestry inference and linear models, have been performed correctly; No replication cohort is used for the novel estimate of population-wide effect size on OCA2NW273KV.

Reviewer #1 (Public Review):

This paper describes a straightforward method to produce graphene-coated cryo-EM grids, which does not require complicated machines or techniques. Thereby it has the potential to make these powerful types of grids more widely accessible to researchers. Besides a description of the method, the authors also present a structure soluble methane monooxydase hydroxylase (sMMOH) from Methylococcus capsulatus, as determined using both conventional Au Quantifoil grids and their graphene-coated grids. I am not entirely convinced of the comparison between the Au Quantifoil grids and the graphene-coated ones, nor of the differences between the EM and Xray structures (also see below), but these parts of the paper seem to be less important than the description of the new method.

Reviewer #2 (Public Review):

This manuscript describes an easily made grid holder (3D printed transfer tool), shown in Figure S1, which is used to transfer commercially available graphene from pads, as provided, onto EM grids. In addition, a baking protocol (24 hr at 200 {degree sign}C in air) is used to remove most of the PMMA that remains on the transferred graphene, after washing with acetone. The use of these graphene-coated grids is demonstrated by preparing cryo-EM samples of soluble Methane Monoxoginase (sMMOH), a ~250 kDa particle, resulting in a high-resolution (2.4 Å} structure.

While using a transfer tool is a good idea, it represents a rather minor, incremental advance.

I am far less enthusiastic about the use of high-temperature oxidation, in air, as a way to remove residues of PMMA that remain after washing with acetone. There is already extensive literature that shows that oxidation of the graphene is difficult to prevent when conditions are pushed far enough to remove all of the contamination. Indeed, Figure S2 C confirms that the surface of graphene remains contaminated over much or possibly all of the area of a hole in the supporting Quantifoil grid. A higher magnification image would have made this even more apparent.

In short, nothing new is presented that makes me believe that these grids will be more successful than those used in previous publications, whether used "as is", after glow discharge treatment, or when functionalized in other ways. If, on the other hand, a way could be found to remove all of the polymerized, amorphous residue, it might be possible that existing methods that have been tried to passivate or functionalize the graphene might have a better chance of success. I caution, however, that many have tried to achieve this goal (making atomically clean graphene on EM grids), without success.

Reviewer #3 (Public Review):

The most interesting and novel part of the manuscript is the process for removing PMMA from the graphene after the transfer of the PMMA/graphene pad to electron microscopy grids. The authors use incubation in acetone followed by baking overnight at 200 Celsius. If this proves to be reproducible with easily obtained sources of commercial graphene, it will be a major aid in allowing more labs to generate electron microscopy grids with graphene. To further clarify the efficacy of this process and aid the reproducibility of the method, we ask the authors to improve the characterisation of the suspended graphene on the grids and add more detail in the description of the transfer and cleaning procedures.

In particular, in order to unambiguously demonstrate removal of the PMMA, Fig. 2 should include selected area electron diffraction (SAED) data where only the graphene layer suspended over the holes (no supporting foil) contributes to the diffraction pattern. This is easily achieved with a selected area aperture of the correct size. Patterns should be shown at each step of the process after the transfer. The authors should also clearly indicate in the TEM images the area of the sample that is illuminated to generate the SAED pattern. The SAED pattern as a function of tilt could also be examined to confirm a single graphene layer is present over the hole.

Reviewer #1 (Public Review):

Clauw et al combine large-scale phenotyping, trait-environment correlation analyses, transcriptome profiling, GWAS, and tests of adaptive differentiation to examine the potential for local adaptation in growth among >200 accessions of A. thaliana sampled from a wide range of locations. They show accessions from northern latitudes produced larger seedlings yet slower growth given exposure to colder temperatures compared to accessions from southern latitudes. They provide clear evidence that growth is polygenic and exhibits rather large broad-sense heritabilities, identify candidate loci underlying plant growth, and provide evidence for adaptive differentiation in initial size and growth rate at one of the temperatures examined.

There are a number of strengths and a few weaknesses of this work. Strong points are the depth of data generated - the authors take size twice per day using 7k plants (5 replicates of 249 accessions, 2 temperature treatments across 3 repeated experiments). They model growth with a power-law function, noting that growth slows with increasing size, and then use these estimates of growth (initial size, growth rate at two temperatures, and response to changes in temperature) to assess correlations to climate (exclusively focusing on mean temperature during the coldest quarter). Another strength is the combination of this dense phenotypic analysis with metabolome, transcriptome, and GWAS analyses to examine the functional genetic basis underlying the potential growth differences between northern and southern populations. They likewise perform a test of adaptive differentiation.

This work, while extensive, has a few areas that need improvement. Of major concern is that in its current form, it lacks important and useful evolutionary/ecological framing and hypotheses - why is an assessment of local adaptation for growth useful, interesting, and what specific question is this work tackling? Most people likely assume growth is locally adapted. Without broader framing, it is difficult to understand the novelty or importance of the work. There is a rich literature that the authors could tap into (e.g. growth is a key part of life history and trade-offs between growth and survival or reproduction, given environmental cues, is certainly adaptive, yet this has not been considered at such a broad and multi-level analysis before), which would make the relevance of the current manuscript more broadly appreciated. The overall arching hypothesis of the study should be more easily identified in the introduction.

Next, most take-homes from the phenotypic work are shown from simple regressions yet the methods state that more developed statistical models were employed. We need to see the results of the analyses that drive the assertions. Additionally, more rigorous analyses should be provided: it appears from the regressions that populations located predominantly in Asia (the populations that experience the coldest winter temperatures) are driving the correlations between growth and climate, and even potentially responsible for the adaptive differentiation result. Digging into this further will be important. Further, the wide range of growth plasticity (ie growth rate temperature response) in North Sweden populations call into question some of the simple conclusions drawn in the text. This too should be examined more closely.

Reviewer #2 (Public Review):

The manuscript's main claim is that there is local adaptation for growth rate response to cold. Specifically, the growth rate of accessions from cold regions is less reduced by cold than the growth rate of accessions from warmer regions (Fig. 4). Additionally, the results of a Qst-Fst-like test suggest that the difference in growth rate response is adaptive. The manuscript hypothesizes that northern accessions actively inhibit their growth because slow growth may be beneficial in cold climates.

The manuscript has an impressive phenotyping dataset demonstrating variation in initial growth, growth in each treatment, and temperature growth response. The manuscript also clearly demonstrates that these phenotypes are correlated to winter temperature and that the variation in these responses is larger than expected due to drift, consistent with local adaptation. We see these findings as the strongest aspects of the paper.

A major weakness of the paper is the gene expression analysis. As presented here (Figure 5), it is not clear how these results support the conclusion of adaptation. Furthermore, the methods and results are not clearly described. However, we did find the analysis of how gene cluster expression changed across treatments in accessions from different climates (Figure S5) more interesting. There is promise for these results if they are more clearly presented and discussed, to contribute to the overall argument of the paper by comparing how plastic expression changes relate to evolved expression changes.

An additional weakness of the paper is the current framing. The introduction immediately begins with a reference to A. thaliana life history and does not link these results to broader questions about the evolution of plasticity that would be interesting to more readers. The manuscript would be improved by connecting growth rate response to temperature with ideas about the evolution of plasticity in the introduction and discussion. For example, active and passive plasticity are defined in the introduction but not returned to later in the discussion, despite the fact that the careful phenotyping done in this paper is a good example of how to distinguish between active and passive plasticity. Similarly, throughout the paper, there could be clearer links between specific results, like the heritability estimates and the GWAS results, and the main argument about plasticity.

Reviewer #3 (Public Review):

The study reports on a large experiment using a powerful design and thorough control of variation. I am particularly impressed with the full triplication, which makes for an exemplary design. Controlling the amount of soil and thus its density is also very relevant here. The modelling and the characterisation of trait variation are thorough and mostly clear although figures 2 and 3 are not very informative.

Unfortunately implementing a GWAS and RNA-seq analysis did not yield much insight, with no gene or locus to single out. The study does not provide novel molecular insights and instead places a focus on the different levels of plasticity found across population. This calls for the refocusing of the paper on the trait variation and how the treatment response differs across populations and locations of origin.

- Issue with the conceptual framework<br /> Whilst the modelling is thorough, I have some reservations about the conceptual framework and its biological interpretation.<br /> The plants are first grown for 15 days at 22°C before the treatment (6°C vs. 16°C) starts. The size reached after these 15 days, inferred as the intercept of the power curve is interpreted as an absolute measure of early growth.<br /> In my mind, M_0 confounds early growth with growth at a warm, near-optimal temperature. The authors need to justify that this is not another measure of plasticity for growth under warmer conditions (ie. that growth during the first 15 days is constant and not/less temperature-dependent). Then there is a high correlation between r's at 6°C, 16°C and their reaction norms. This is quite trivial.

- Lack of clarity in the presentation of the data<br /> The authors mention metabolomic data (eg. line 148) that are nowhere to be found in the manuscript. There is no clear disclosure of which eight accessions were retained for RNA-seq. I gather I could use the x-axis label on fig. 5, but this is too much work-out to be clear.<br /> The authors have tested two modelling frameworks and retained a power-law model. This is justified based on goodness-of-fit of these models but there is too much information about the model that is not being used in the results. It would be better to show the one, best model in the results and keep the alternative model and the justification for not using it in the methods.

- Some heuristics need further justification or explanation<br /> A fair bit of the introduction is spent on presenting cold acclimation molecular mechanism but the lowest temperature tested here is 6°C. This is above growth cessation and per se requires a justification for how this temperature is expected to induce cold acclimation response in A. thaliana.<br /> It is unclear what were the 241 cold-acclimation genes selected and how was enrichment tested? Give the degrees of freedom of the test.<br /> The testing of adaptive differentiation presents in Fig. 7 the values along PC5&6, I assume that PC1 to 4 were not as visual, but that is also a heuristic that needs to be made explicit.<br /> Finally, most analyses take into account population stratification using a "correction for structure". It is unclear how the K matrix was computed (how the SNP were selected and what kind of relatedness calculation was implemented). Was it always the same K matrix across analysis (I suspect those used for the GWAS and for the adaptive differentiation test are not the same).

Reviewer #1 (Public Review):

In this manuscript, Sehring et al. investigate the process of osteoblast migration and dedifferentiation during zebrafish fin regeneration after amputation. In a previous study the authors explored the process of osteoblast dedifferentiation and identified NF-kappaB signaling/retinoid acid as negative regulators of osteoblast dedifferentiation. In the first part of this study, the authors studied osteoblast migration in this model, and show, using approaches combining live imaging, pharmacological inhibition and genetic strategies, that osteoblast dedifferentiation and migration can be uncoupled. While NFkappaB/RA regulates dedifferentiation without affecting migration, migration involves the complement system that is part of the innate immune system, and actomyosin dynamics. In the second part of the study, the authors established a trauma model by removing two fin ray segments on each side of a segment. They show that regenerative bone formation occurs only distally while the generic injury response (i.e. dedifferentiation and migration) occurs proximally and distally.

Strengths:

The data throughout the manuscript is of high quality and the conclusions are in general well supported by the results. The authors built on their previous work that demonstrated the role of NF-KappaB and retinoic acid in osteoblast dedifferentiation in regenerating zebrafish fins. Similar approaches and imaging techniques are employed in this study to describe changes in osteoblast morphology and migration after fin amputation, and to interfere with actomyosin dynamics using inhibitor treatment. Methods used in the previous study to reveal the role of NF-kappaB and RA in osteoblast dedifferentiation are used again here to show that this pathway does not affect migration. The novelty of this study is also to address the role of the complement system in osteoblast cell shape change in migration after amputation.

The authors describe a new model of hemiray removal to further emphasise their analyses on the process of polarized bone growth distally to the remaining fin segments, and to reveal that the initial steps of cell shape change, and migration occurs symmetrically on both distal and proximal ends of fin segments, independently from the bone regenerative response.

Weaknesses:

The data presented in the first part of the study are convincing. However, it is unclear whether each step of cell elongation and alignment, cell migration, cell dedifferentiation and regenerative response, is required for fin regeneration following amputation. As indicated in the discussion, the authors cannot provide evidence for the requirement of migration or dedifferentiation for the overall success of fin regeneration. Such limitations should be more clearly stated.

In the second part of the study, the term trauma needs to be clarified or reconsidered. A trauma model would imply that healing is impaired. Evidence for a non-healing phenotype is lacking and is expected in support of a trauma model.

The authors describe the process of fin regeneration that may share common features with bone regeneration in other species. In the absence of direct evidence of common mechanisms between fin regeneration and bone regeneration in other systems, the authors should remain focused on "fin regeneration" in their conclusions rather than referring to "bone regeneration" and "bone formation" in more general terms.