Reviewer #1 (Public Review):

Gu et al. examine how activity in the substantia nigra pars reticulata (SNr) contributes to proactive inhibition - the suppression of upcoming actions - by recording SNr activity in rats performing a task requiring them to be prepared to cancel a planned movement. This task was developed in a previous study by the same authors in which they examined how globus pallidus pars externa (GPe) activity depends on proactive inhibition (Gu et al., 2020), which motivated the present focus on SNr. The task is rich and the complementary analyses of how the neural activity relates to the behavior, at the level of individual neurons and populations, are appropriate and illuminating. Overall, this study is well done and has the potential to be a nice contribution to our understanding of how the SNr, and therefore the basal ganglia, mediate behavioral inhibition. Addressing a few questions, however, would improve the paper.

- It is not obvious why the presence or absence of proactive inhibition should be determined on a session-by-session basis. It seems quite possible that proactive inhibition is not an all-or-none phenomenon, and also that it might be exhibited to a greater or lesser extent across a session (e.g., due to changes in motivational drive). It would therefore strengthen the paper to better explain the rationale for comparing neural activity across entire sessions "with" and "without" proactive inhibition. Within-session variation in proactive inhibition could be quite advantageous, allowing for within-neuron comparisons. It is even possible that the differences in neural activity that the authors report here using session-by-session analysis are an underestimate of the true effect of proactive inhibition.

- It is difficult to rule out alternative explanations for the observed differences in SNr activity. While the authors acknowledge this point in the 3rd paragraph of the discussion, they only discuss one potential alternative - reward expectation. Another difference between maybe-stop and no-stop trials is the likelihood that a particular target should be selected, which has also been shown to modulate SNr activity (Basso & Wurtz, 2002). As is often the case with complex behavioral tasks, there may be many other differences between trial types that may contribute to differences in neural activity. It would be helpful for the authors to more fully explain how their results relate to contextual modulation of SNr activity, and why the dependence of SNr activity on proactive inhibition may be a novel finding.

- A natural question arising from this study, as with most studies of neural recordings during behavior, is the causal nature of the neural activity. It would be non-trivial and beyond the scope of the current study to perform the sort of perturbations that could determine whether population variability causally relates to preparation to suppress actions. But it would be useful to discuss future experiments that might be able to test causality.

Reviewer #2 (Public Review):

The authors have recorded the activity of neurons in the rat substancia nigra pars reticulata (SNr) while animals performed a version of a stop-signal task. The goal of this study is to investigate and describe the contribution of SNr in proactive inhibitory control. By examining single-cell responses as well as population activity, the authors show that increasing the probability of stop signal trials induces several changes in SNr responses. First, specific populations of SNr neurons increase their activity during proactive, direction-specific inhibition. At the population level, neurons are biased away from the side of the movement that has to be potentially inhibited. Second, during proactive inhibition, neuron activity is more variable, both at the single-cell and population levels. Finally, the authors show that animals' outcome history influences both firing rates and variability of neuron responses in the current trial. Especially, neural variability is increased following a failure to inhibit a movement.

Strengths<br /> The manuscript provides an interesting and timely insight into the role of the basal ganglia output nucleus in movement initiation control. The paper is often clearly and concisely written (although see one issue related to this below). One of the main strengths of the work is to allow an interesting comparison with recent work by the same team, aimed at investigating the responses of another basal ganglia nucleus (GPe) in the same task, using similar analyses (this comparison is not extensively exploited in the discussion section though). Another potential strength is the use of different analysis scales. The authors investigated single-unit responses as well as population "trajectories" in the neural state space. This is an interesting option that could have been better motivated, given that the two approaches assume quite different brain operations.

Weaknesses<br /> The analyses and results sometimes lack clarity and details. For instance, and unless I missed the information, it is not clearly stated whether "maybe-stop" trial analyses only include Go trials or if (failed) Stop trials are also considered. Moreover, quite complicated figures are often described very briefly in the main text. Methods are also often too succinctly described, and sometimes refer to a previous publication (Gu et al., 2020) that readers did not necessarily read.<br /> There are some points that the authors might need to discuss more. Especially, a global picture of the role of the different basal ganglia nuclei during movement control would have been appreciated. Also, the authors monitored the activity of the rat basal ganglia output. We would have appreciated more information regarding the impact of this output activity on SNr target areas, as compared to their previous work that focused on GPe for instance. Another example concerns the observation that SNr activity is elevated during active inhibition regardless of the firing rate pattern before movement (increase or decrease). As noted by the authors themselves, this is inconsistent with the classical role assigned to the basal ganglia output nucleus (i.e. a decrease in activity promotes movement). Despite that this observation is of potential interest to readers working on the basal ganglia, it is not discussed.

https://www.explainpaper.com/

Another in a growing line of research tools for processing and making sense of research literature including Research Rabbit, Connected Papers, Semantic Scholar, etc.

Functionality includes the ability to highlight sections of research papers with natural language processing to explain what those sections mean. There's also a "chat" that allows you to ask questions about the paper which will attempt to return reasonable answers, which is an artificial intelligence sort of means of having an artificial "conversation with the text".

cc: @dwhly @remikalir @jeremydean

Reviewer #1 (Public Review):

Einarsson et al have produced CAGE data from EBV-immortalised lymphoblastoid cells from more than a hundred individuals from two genetically diverse African populations (YRI and LWK), and used it to study how sequence variation affects the activity of promoters at the level of expression variability and at the level of transcription start site usage within promoters across individuals.

The dataset is very exciting, and the analyses were performed carefully and described well. The results show that promoters in the genome vary a lot with respect to their expression variability across individuals and that their level of variability is closely associated with their biological function and their sequence and architectural features. These results are often confirmatory - it is well established that promoters have different architectures associated with different sequence elements, different types of gene regulation and even differences across individual cells. In general, the multifarious observations boil down to one key distinction:

- Regulated genes have promoters that look and act differently from those of housekeeping genes.

While this is unsurprising, the authors then proceed to analyse other underlying differences between low variability (mostly housekeeping) and high variability (overwhelmingly regulated) promoters. Several observations have alternative and sometimes more elegant explanations if some of the previously worked out properties of housekeeping vs regulated promoters are taken into consideration:

- The authors are keen to interpret the architectural features of ubiquitously expressed (housekeeping) promoters as selected for robustness against mutations in ensuring stable and steady expression levels. However, there are some known facts about both housekeeping and regulated promoters that make alternative interpretations plausible.

- When discussing broad promoters, the authors disregard the well known fact that the most commonly used transcription start positions are those with YR sequence at (-1,+1) position. Any mutation within the span of broad promoter cluster that removes an existing YR or introduces a new one has the capacity to change both the TSS distribution pattern and overall level of expression of that promoter - but only slightly. This way, broad promoters can be viewed as adaptation not for robustness but for ability to take many mutations with small effect size that will drive any _positive_ selection smoothly across a changing fitness landscape.<br /> - Indeed, the main property of low variability promoters is that there isn't a single nucleotide change (either substitution or indel) that can substantially change their activity. (In that they are clearly different from e.g. TATA-dependent promoters, where one change can abolish TBP binding or deprive the promoter of a YR dinucleotide at a suitable distance from the TATA box.) This is achieved by their dependence on broad and weak sequence signatures such as GC composition and nucleosome positioning signal. However, most such genes are not known to have a strict requirement for dosage control. On the contrary, dosage seems to be much more critical for the functional classes that in the authors' analysis show variable expression.<br /> - Whether it is a removal of YR dinucleotide, introduction of a new one, or the change of nucleosome positioning, it seems that the transcription level from housekeeping, low variability promoters is unaffected, or at least affected mildly enough that it is not within the statistical power of the CAGE data across different individuals to detect the difference. Rather than robustness, it can be interpreted as competition - the architecture recruits preinitiation complex at a fairly constant rate, and it is the different YR positions that "compete" for serving as transcription initiation position, with the CAGE signal reflecting the relative effectiveness of each position in that competition. If one of the YR dinucleotides is removed, often the other, neighbouring ones will be used instead. The same might happen for potential multiple nucleosome positioning signals - if one becomes less efficient at stopping a nucleosome, another will be used more often.<br /> - The fact that decomposed parts of housekeeping promoters add up to approximately the same expression level across individuals even when they are uncorrelated point that they might actually be anticorrelated - indeed, the UFSP2 plot in Figure 4E looks like the two decomposed promoters are anticorrelated. That would argue against the independence of the decomposed promoters - indeed it may again point to "competition" where the decrease in use of one will simply shift most initiation events to the other.<br /> - In general, not everything is a result of direct evolutionary selection, and that is what should have clear landmarks of purifying selection. On the contrary, promoters, especially housekeeping promoters, have vastly different nucleotide and dinucleotide compositions across Metazoa, both at large and at relatively short distances, which means they can undergo concerted evolution as a group, which means they should be "robust" to mutations in a way that allows them to change much more and more rapidly than some other promoter architectures - especially TATA-dependent architectures whose key elements and spacing between them haven't substantially changed for more than a billion years, and possibly longer.

- While housekeeping promoters are broad but mostly not among the broadest, regulated promoters can be either broad or narrow. This is also known - while narrow promoters are overrepresented for tissue-specific and non-CGI promoters, promoters of Polycomb-bound developmental genes are often broad and have large CpG islands; the latter may account for some of the broadest CAGE clusters observed in the data. It would be an interesting finding if both TATA-dependent and developmental promoters were found to be variable across individuals in a non-trivial way (the trivial way being the variability due to larger dynamic range of their expression - e.g. the expression of SIX3 in many cell types is basically zero, while the dynamic range of RPL26L1 is very limited) - this should be checked by analysing them separately.

- While broad promoters can be decomposed into subclusters with differential expression across individuals, the authors do not seem to allow for the decomposition of intertwined TSS positions within the cluster, but rather postulate hard boundaries between subclusters. This is different from e.g. overlapping maternal and zygotic promoter use (Haberle et al Nature 2014), where the distribution of the used TSS positions is different but the clusters can overlap.

- Both Dreos et al (PLOS Comp Biol 2016) and Haberle et al. (2014) show that one stable element of a broad promoter is the positioning signal of its first downstream nucleosome. As seen very convincingly in both Drosophila and zebrafish, the dominant TSS position of the broad promoter is highly predictive of the position of first downstream nucleosome and its underlying positioning sequence, and the most plausible interpretation is that there is an "optimal" distance from nucleosome for transcriptional initiation, resulting in the dominant (i.e. most often used) TSS position. In mammals, broad promoters are even broader than in those two species and might have multiple nucleosome positioning signals they can use. In such cases, mutations in one of the nucleosome positioning signals, or indels changing the spacing between the nucleosome and the part of sequence that contains TSS, might lead to differential use of one nucleosome signal vs other. This would be compatible with the authors' observations in low variability promoters that decomposed promoters are used to different extends in different individuals.

- If we were to look for sources of difference other than the actual sequence architecture, some differences between regulated and unregulated promoters can be explained by the key difference: the regulation of regulated genes comes from outside the core promoter; the regulation of housekeeping genes is largely dependent on the intrinsic activity of the core promoter itself. This way, for example, in the absence of a causative variant in the promoter itself, the observed variability in the SIX3 promoter might not be encoded in the promoter itself - instead, enhancer responsiveness might be encoded in the promoter, and the variability itself could be due an enhancer that can be hundreds of kilobases away. Such a scenario combined with broad promoter would likely result in decomposed promoters that are highly correlated across individuals - because they are both externally controlled by the same regulatory inputs.

Reviewer #2 (Public Review):

This manuscript by Einarsson and colleagues in the Andersson lab examined how genetic variability across a population impacts both gene expression and promoter architecture in a human population. The authors generate new CAGE data in 108 lymphoblastoid cell lines (LCLs). The authors' analysis is focused on defining how DNA sequence and promoter architecture correlate with population-variation in expression across this cohort. In general, there is a lot that I like about this manuscript: The dataset will be an extremely valuable resource for the genomics community. Furthermore, the biological findings are often thoughtful and potentially interesting and significant for the community. The analysis is generally very strong and is clearly conducted by a lab that has a lot of expertise in this area. My main concerns are centered around the often unwarranted implication that DNA sequence or promoter features cause differences in variation at different genes.

Reviewer #1 (Public Review):

This work characterizes at the mechanistic level the relationship between ER stress and the lack of glycosylation of two seipin mutants observed in seipinopathy, N152S and S154L (nomenclature of the long form of seipin). In short, the authors find that lack of glycosylation (ngSeipin) decreases ER calcium levels, and that it does so in an aggregation-dependent way, with no effect at low protein expression (or when oligomerization is impeded) and a significant effect (also leading to apoptosis) when high amounts of non-glycosylated seipin are expressed in the cell. The authors show that this causes ER stress, using BiP, XBP1 and CHOP as markers, and that this is attenuated when SERCA2b is overexpressed. They also identify the C-terminus of seipin as the region directly interacting with SERCA2b.

The work is carefully described, with extensive controls, and the conclusions are supported by the data presented. In addition, the results have important consequences in several fields. First, they clarify the relationship between ER stress and nerurodegenerative diseases in general, and seipinopathy in particular. Second, by identifying the mechanism through which seipin and SERCA2b interact, they raise interesting mechanistic considerations about the relationship between lipid accumulation and calcium homeostasis; third, they hint at potential therapeutic approaches for ER-stress associated neurodegenerative diseases.

Weaknesses

The major weakness of this work is that it lacks an assessment of the relevance of the findings in vivo. This originates from two issues. First, the phenotype observed depends on the amount of non-glycosylated protein, and the investigation of the amount of protein in different cell types (especially neurons) is beyond the scope of this work. Also, the use of a double mutant (N152S, S154L) rather than of two single mutants (that are clinically relevant) makes a direct comparison with the pathological scenario quite difficult.

In addition, the authors describe that in glycosylated seipin, deletion of the N-terminus and modification of the TM helices has a very large effect on ER calcium levels (Figure 6C), but no mechanistic explanation for this observation is provided.

Reviewer #2 (Public Review):

The authors used a cell based system to investigate how expression of disease-associated Seipin glycosylation mutants (ngSeipin) impact on endoplasmic reticulum (ER) homeostasis. In particular, they focus their attention on SERCA, previously shown to interact genetically and biochemically with Seipin. They show that endogenous SERCA interacts with both overexpressed WT and ngSeipin. Using reporters monitoring calcium levels in the cytosol and ER lumen, it is shown that overexpression of ngSeipin (but not WT seipin) results in lower ER calcium levels, increase ER stress and eventually apoptosis. Based on the analysis of several Seipin mutants, the authors conclude that the toxicity of ngSeipin requires oligomerization (via the luminal domain) and the presence of its C-terminal domain. It is proposed that low ER calcium resulting from inhibition of SERCA by ngSeipin is a key event in Seipinopathies.

Despite the large amount of data presented, these not always lay support to the main conclusions of the study. Critical flaws are:

1- All conclusions are based on experiments where Seipin is overexpressed to levels are are unlikely to be physiological, even in the disease context. Importantly, as shown at several points (for example Figure 3), the effects of ngSeipin are drastically different depending of the expression levels.

2- The conclusions about ngSeipin aggregation are unjustified. The PLA assay is not suitable to assess protein aggregation or to distinguish between aggregation and oligomerization.

3- The effects of ngSeipin on UPR activation or calcium levels are modest, in particular considering that the levels to which it is overexpressed in relation to endogenous Seipin (see for example Figure 1Ec or 3Ac).

Reviewer #3 (Public Review):

Here, Saito et al. studied the mechanism underlying Seipinopathy, a dominant motor neuron neurodegenerative disease, showing that non-glycosylated Seipin dominantly inactivates ER calcium pump SERCA2b and subsequently causes ER stress and apoptosis. Seipin is a key regulator of lipid metabolism and involves in the biogenesis of lipid droplets. This manuscript provides valuable insights into the role of non-glycosylated Seipin in ER calcium homeostasis and ER stress-induced apoptosis, which is important for a better understanding of the pathogenesis of Seipinopathy and the role of ER calcium in neurodegenerative diseases.

1. The biochemical and genetic evidence from HCT116 cells showed in this manuscript strongly supports the function of non-glycosylated Seipin in ER stress and cell apoptosis by disrupting ER calcium homeostasis. However, a concern about this study is the colorectal carcinoma cell line HCT116 used. Neuron cell expresses a much higher level of Seipin than HCT116 cells. Although a higher level of non-glycosylated Seipin was expressed in HCT116 Seipin knockout cells to mimic the physiological level in neuron cells, whether non-glycosylated Seipin exhibits the same mechanism in neuron cells is still unclear. Further studies in neurons or cell lines with comparable Seipin level will help to understand its actual role in neurodegenerative disease.<br /> 2. A higher level of non-glycosylated Seipin expression causes aggregates/clusters of Seipin on ER, as shown in Figure 1C. Since non-glycosylated Seipin physically interacts with SERCA2, it is important to know whether non-glycosylated Seipin expression changes the localization of calcium pump SERCA2b on ER.

Reviewer #1 (Public Review):

Dingus J et al investigated an important technical issue with the use of single domain antibodies (nanobodies) as intracellularly expressed proteins to probe cellular biology. Over the past decade, the relative simplicity and stability of nanobodies compared to conventional antibodies has led to many interesting uses of these molecules as either sensors or means to perturb intracellular protein function. Many have generally assumed that the increased stability of nanobodies enables them to be expressed in a functional form within the reducing environment of the cytoplasm. With an observation that many nanobodies are actually not stable within the cytoplasm, the authors aimed to determine the sequence determinants of what drives stability/instability, and then devised strategies to rescue folding of unstable nanobodies in the cytosol. They first looked at 75 nanobodies and use a fluorescence based metric to determine which nanobodies are stable and unstable. This revealed a set of residues that are enriched in either category. With a further strategy to determine consensus changes for stability, the authors rescued the stability of a large fraction of unstable nanobodies. Further analysis allowed the authors to whittle down to a few mutations that are important for stability, with some structural considerations in mind. In further important experiments, the authors show that these rescuing mutations generally do not destroy antigen binding. Importantly, they clearly highlight a few examples where the stability rescue strategy impairs antigen binding. Finally, experiments in retinal cells and bacteria support the success of this strategy.

The overall manuscript is well presented with clear data and appropriate caveats included throughout the work.

Reviewer #2 (Public Review):

This study investigated a substantial set of camelid nanobodies for their characteristics when expressed in mammalian cells as intrabodies. Intrabodies have a variety of important research, diagnostic and therapeutic uses, and nanobodies have several inherent characteristics that make them amenable for use as intrabodies. While a substantial number of nanobodies have been developed that are effective as intrabodies, a systematic study of the suitability of a set of otherwise unrelated nanobodies for this purpose has not been performed. As such, the molecular characteristics of what may make an nanobody suitable for use as an intrabody have not been defined. This study addresses this gap in knowledge by FP-tagging a set of 75 nanobodies selected from among those whose structure has been solved. The study uses live cell imaging to evaluate expression of these nanobodies when expressed in mammalian cells. These results are used in bioinformatics analyses to define key amino acids positions in the nanobodies that distinguish those that have high level expression in diffuse cytoplasmic pattern that is consistent with expression in a stable, soluble form. These analyses inform mutagenesis to phenoconvert poorly expressed nanobodies into those with improved expression. The outcome is a set of rules that can be used by investigators to predict the likely characteristics of a nanobody with a given sequence when expressed in cells as an intrabody. The strengths of the study is the elegant and rational manner it is pursued by the iterative application of bioinformatics analyses of nanobody sequences, cell biological assays of expression as intrabodies and mutagenesis. This study has great value to the field as nanobodies gain increased use as intrabodies. The weakness is the lack of a quantitative analysis of expression levels and solubility, with all of the results based on a subjective visual determination of the appearance of the FP-tagged nanobody in expressing cells. Moreover, steady-state appearance is used to infer active processes of aggregation and clearance. Another weakness is that the study presumes that the steady-state expression levels of FP-tagged nanobodies are determined solely by posttranslational stability/solubility, and not by differences in transfection levels, transcription, and translation. Lastly, the study implies that the set studied here is representative of nanobodies in general and the results are transferable across all nanobodies. While the study still has substantial value in spite of these weaknesses, the manuscript would be greatly improved by explicitly stating these limitations of the study.

Reviewer #3 (Public Review):

Dingus et al. have developed an innovative and powerful approach for improving the intracellular stability of nanobodies. Nanobodies are single chain antibodies that are typically generated in select species such as llamas or alpacas. Because nanobodies are secreted and are present in general in the extracellular environment, they often become unstable when expressed in the reduced intracellular environment. Dingus et al. investigated 75 nanobodies from the Protein Data Bank and found that 42 were unstable when expressed intracellularly. In order to improve stability of these nanobodies, they first determined consensus residues that were present within the framework region, which does not include the CDR regions, in over 80% of the stable nanobodies. Mutating residues within the framework of unstable nanobodies to match consensus residues in the stable nanobodies stabilized 26 of 42 nanobodies. Mutating consensus unstable residues stabilized another 11. Thus 37/42 unstable nanobodies were stabilized using this mutational approach. Further experiments provided evidence that some of the stabilized nanobodies still had some affinity for their targets. Furthermore, one stabilized nanobody was stable when expressed in the retina in vivo and 3 of 5 were stable when expressed in bacteria.

1. This study provides a straightforward approach to improving the intracellular stability of nanobodies that could prove to be very useful for solving a common and vexing problem.

2. From the data provided, it was difficult to determine whether the binding affinity of the mutated nanobodies had been diminished by the mutations that increased stability, and if so, by how much. Furthermore, target binding affinity was assessed for just 5 nanobodies, which calls into question whether this strategy will be useful.

3. Ultimately, the goal of expressing most nanobodies intracellularly is to bind to endogenous targets. It is difficult to assess how useful the stabilization strategy will be since it was not determined whether any of the stabilized nanobodies could bind their endogenous targets intracellularly.

Reviewer #1 (Public Review):

This paper describes the structure of an N-terminus OB-fold of the 70kD subunit of human replication protein A (RPA70N) bound to a peptide from five different proteins; HELB, ATRIP, BLM (two peptides), RMI1, and WRN, which are involved in various DNA transactions. This study of X-ray crystallography revealed a structural basis of RPA70N OB-fold for weak interactions with Kd of 10-18 uM. Importantly, distinct binding modes of RPA70N to different substrates indicate the flexible nature of this domain in the recognition of binding partners. In addition, the authors characterized the role of a critical hydrophobic residue in the peptides on the interactions to RPA70N by Isothermal titration calorimetry (ITC). The structural analysis of RPA70N with 6 different binding peptides is impressive and the results described in the paper support the main conclusion. Understanding the structural flexibility of the RPA70N domain is important to know the molecular mechanisms of how RPA regulates distinct DNA transaction pathways. On the other hand, the authors need some in vivo functional assays to support their conclusion.

Reviewer #2 (Public Review):

RPA is a ssDNA binding protein that functions as a hub protein to recruit more than three dozen enzyme onto DNA to coordinate almost all DNA metabolic roles. There are two specific protein interaction domain OB-F and the wh domain. NMR and crystallographic studies have solved the structure of OB-F bound to peptides from various target interactors. Nevertheless, these cognate binding sequences are not conserved. To decipher if there are unique binding modes during such interactions, Wu et. al., use a strategy to tether these target peptides to OB-F using a flexible linker and have solved the structure of complexes with peptides from HelB, ATRIP, RMI1, WRN and BLM. The high-resolution structures presented by Wu et. al. showcase key interactions between RPA70N and peptides of binding partners. These findings add to similar knowledge from several other such structures that have been previously reported. The authors also suggest multivalency where multiple OB-F domains can be bound by a single peptide or a cluster of peptides. This leads to a model where such an interaction can stabilize RPA nucleoprotein filaments and better recruit interacting partners. However, such a model assumes that OB-F is floating around freely accessible to interact with other proteins. This assumption is incorrect as in most of these cases (like in Rad52-RPA interaction) there are other inter and intra protein interactions that need to be accounted for and are ignored here. Ideally, interaction studies with full length proteins provide better mechanistic understanding of interactions between proteins.

Reviewer #3 (Public Review):

The authors have obtained beautiful structures of the OB-fold of RPA70 and peptides of interacting partners. This is accompanied by biochemical assays to show binding.

What is absent is a clear comparison of the binding sites, peptide orientations (in schematic format) and implications for regulation of ssDNA binding (by RPA70 and partner) as well as regulation of activity.

The impact of the paper in its current format is limited and can do with significant improvement.

Reviewer #1 (Public Review):

Kohler and Murray present high-throughput image-based measurements of how low-copy F plasmids move (segregate) inside E. coli cell. This active segregation ensures that each daughter cell inherit equal share of the plasmids. Previous work by different labs has shown that faithful F-plasmid segregation (as well as segregation of many other low-copy plasmids, segregation of chromosomes in many bacterial species and segregation of come supramolecular complexes) require ParA and ParB proteins (or proteins similar to them) and is achieved by an active transport mechanism. ParB is known to bind to the cargo (plasmid) and ParA forms a dimer upon ATP binding that binds to DNA (chromosome) non-specifically and also can bind to ParB (associated with cargo). After ATP hydrolysis (stimulated by the interaction with ParB), ParA dimer dissociates to monomers and from ParB and the chromosome. While different mechanisms of the ParA-dependent active transport had been proposed, recently two mechanisms become most popular - one based on the elastic dynamics of the chromatin (Lim et al. eLife 2014, Surovtsev PNAS 2016, Hu et al Biophys.J 2017, Schumaher Dev.Cell 2017) and the other based on a theoretically-derived "chemophoretic" force (Sugawara & Kaneko Biophysics 2011, Walter et al. Phys.Rev.Lett. 2017).

The authors start by following motion of F plasmid with one or two plasmids per cell and by analyzing plasmid spatial distribution, plasmid displacement (referred to as velocity) as a function of their relative position, and autocorrelations of the position and the displacement. They concluded that these metrics are consistent with 'true positioning' (i.e. average displacement is biased toward the target position - center for one plasmid and 1/4 and 3/4 positions for two plasmids ) but not with 'approximate positioning' (i.e. when plasmid moves around target position, for example, in near-oscillatory fashion). This 'true positioning' can be described as a particle moving on the over-dampened spring. They reproduce this behavior by expanding the previous model for 'DNA-relay' mechanism (Lim et al. eLife 2014, Surovtsev PNAS 2016), in which plasmid is actively moved by the elastic force from the chromosome and ParA serves to transmit this force from the chromosome to the plasmid. Now, the authors explicitly consider in the model that the chromosome-bound ParA can diffuse (which the authors refer as 'hopping') and this allows the model to achieve 'true plasmid positioning' for some combination of model parameters in addition to oscillatory dynamics reported in the original paper (Surovtsev PNAS 2016).

Based on their computational model, the authors proposed that two parameters, diffusion scale of ParA = 2(2Dh/kd)1/2/L (typical length diffused by ParA before dissociation) and ratio of ParB-dependent and independent hydrolysis rates = kh/kd are key control parameters defining what qualitative behavior is observed - random diffusion, near-oscillatory behavior, or overdamped spring ('true positioning'). They vary this two parameters ~30- fold and ~200-fold range by changing Dh and kh respectively, to illustrate how dynamics of the system changes between these 3 modes of motion. While these parameters clearly play important role, the drawback is that the authors did not put either theoretical reasoning why these parameters are truly governing or showed it by varying other model parameters (kh, number of ParA NParA, spring constant of chromosome k, diffusion coefficient of the plasmid Dp) to show that only these combinations define the type of the system behavior. The authors qualitative analysis on importance of relies on the steady state solution for the diffusion equation for ParA. It is really unfortunate that no ParA distribution was measured simultaneously with the plasmid motion, as this would allow to compare experimental ParA profiles to expected quasi-steady-state solutions.

The authors also show by simulations that overdamped spring dynamics can transition into oscillatory behavior when decreases, for example by cell growth. Indeed, they observed more oscillatory behavior when they compared single-plasmid dynamics in the longer cells compared to the shorter cells. This was not the case in double-plasmid cells, in eprfect agreement with their analysis. They also calculated ATP consumption in the model and concluded that the system operates close but below (perhaps, "above" should be used as it refers to bigger) the threshold to oscillatory regime which minimize ATP consumption. While ATP consumption analysis is very intriguing, this statement (Abstract Ln24-25) seems at odds with the authors own analysis that another ParA-dependent plasmid system, pB171, operates mostly in oscillatory regime, and it is actually for this regime the authors' analysis suggest minimal ATP-consumption (Fig. 8).

I think the real strength of the paper is that it can potentially to show that if one considers that the intracellular cargo can be moved by the fluctuating chromosome via ParA-mediated attachments, then various dynamics can be achieved depending on combinations of several control parameters (plasmid diffusion coefficient, ParA diffusion coefficient, rate of hydrolysis and so on) including previously reported 'oscillations' (Surovtsev PNAS 2016), 'local excursions' (Hu et al Biophys.J 2017) and 'true positioning' (Schumaher Dev.Cell 2017). The main drawback (in this reviewer opinion) that this is obscured by the current presentation and discussion of this work and previous modelling work on ParA-dependent systems. For example, instead of using "unifying" potential of the presented model, yet another name 'relay and hopping' is used in addition to previously used 'DNA-relay', 'Brownian ratchet', 'Flux-based positioning', and it appears that the presented model is an alternative to these previously published work. And only in model description (in Methods section) one can find that the "... model is an extension of the previous DNA-relay model (Surovtsev et al., 2016a) that incorporates hopping and basal hydrolysis of ParA and uses analytic expressions for the fluctuations rather than a second order approximation"(p.17, ln15-17). While it is of course the authors right to decide how to name their model, it should be explicitly clear to the reader what is a real conceptual difference between presented and previous models from the abstract, introduction and discussion section of the paper, not from the "fine-print" details in the supplementary materials. This would allow to avoid unnecessary confusion (especially for the readers not directly involved into the modelling of ParA/B system) and clarify that all these models rely on the elastic behavior of fluctuating chromosome to drive active transport of the cargo. This reviewer believes that more explicit discussion on the models (one from the authors and previously published) differences and similarities will help with our understanding of how ParA-dependent system operate. This discussion should also include works on PomXYZ system, in which it was shown that similar dynamic system can lead to specific positioning within the cell (Schumaher Dev.Cell 2017, Kober et al. Biophys.J 2019). This will may it explicit that the models results have direct impact beyond the ParA-dependent plasmid segregation.

I think that expanded parameter analysis, and explicit model comparison/discussion will make the contribution of this work to the field more clear and with the potential to advance our general understanding of how the same underlying mechanism can lead to various modes of intracellular dynamics and patterning depending on parameters combination.

Reviewer #2 (Public Review):

The work presented in this manuscript details an analysis of the partitioning of low copy plasmids under the control of the ParABS system in bacteria. Using a high throughput imaging set up they were able to track the dynamics of the partition complex of one to a few plasmids over many cell cycles. The work provides an impressive amount of quantitative data for this chemo-mechanical system. Using this data, the paper sought to clarify whether the dynamics of plasmids is due to regular positioning or noisy oscillations around a mean position. They supplement their experimental work with an intuitive model that combines elements of previous modelling efforts. Their model relies on diffusion of the ParA substrate on the nucleoid with the dynamics of the ParB partition complex being driven by the underlying elastic force due to the nucleoid on which the substrate is tethered. Their model dynamics depend on two parameters, the ratio of the length over which the substrate can explore to the characteristic length of the space and the ratio of stimulated to non-stimulated hydrolysis rates of the substrate. If the length ratio is large, ParA can fully explore the space before interacting with the ParB complex leading to balanced fluxes and regular positioning. If it gets reduced, for example by lengthening the cell, oscillations can emerge as fluxes of substrates become imbalanced and a net force can pull the partition complex.

Strengths:<br /> Given the large amount of data, the observations unambiguously show that one particular ParABS system under the conditions studied is carrying out regular positioning of plasmids. The model synthesizes prior work into a nice intuitive picture. These model parameters can be fit to the data leading to estimates of molecular kinetic parameters that are reasonable and in line with other observations. Lining up the experimental observations with the phase space of the model suggests that the system is poised on the edge of oscillations, allowing for the system to have regular positioning with low resource consumption.

Weaknesses:

However, despite the correspondence of the simulated results with the experimental findings, other explanations are not completely ruled out. The paper emphasizes that ParA diffusion/hopping on the nucleoid is essential for the establishment of regular positioning and that without it, only oscillations were possible. Prior simulation efforts, that the paper cites, which include ParA diffusion and mixing in the cytosol but no diffusion on the nucleoid have shown that regular positioning is possible and that oscillations could get triggered as the system lengthened. Thus ParA hopping is not a necessity for regular positioning (as claimed in the paper), but very well might be needed for the given kinetic parameters of the system studied here.

The paper also presents experimental results for a second ParABS system (pB171) that is more likely to show oscillations. They attribute the greater likelihood of oscillations for pB1717 being due to ParA exploring a smaller space than the F plasmid system that showed regular positioning. This is pure conjecture and the paper does not provide any evidence that this is the reason. Thus it is hard to conclude if oscillations may not be due to other factors.

Reviewer #1 (Public Review):

In this manuscript by Ramaprasad et al., the authors report on the functional characterization of the P. falciparum glycerophosphodiesterase to assess its role in phospholipid biosynthesis and development of asexual stages of the parasite. The authors utilized loxP strategy to conditionally knock-out the target gene, they also carried out complementation assays to show recovery of the knock-out parasites. They further show that Choline supplementation is also able to rescue the knock-out phenotype. Quantitative lipidomic analyses show effect on majority of membrane phospholipids. In vitro activity assays and metabolic labelling assays shows role of GDPD in metabolism of exogenous lysoPC for PC synthesis. The manuscript deciphers the functional role of an important component of lipid metabolism and phospholipid synthesis in the parasite, which are crucial metabolic pathways required for replication of the parasite in the host cell.

Reviewer #2 (Public Review):

The authors use a conditional Lox/Cre knock-out system to test and confirm the essentiality of glycerophosphodiester phosphodiesterase (GDPD) for blood-stage parasites and a key role in mobilizing choline from precursor lysophosphocholine (LPC) for parasite phospholipid synthesis. Prior works had identified serum LPC as the key choline source for parasites, localized this enzyme in parasites, and suggested an essential function in releasing choline, but this key function had remained untested in parasites. This manuscript critically advances mechanistic understanding of parasite phospholipid metabolism and its essentiality for blood-stage Plasmodium and identifies a potential new drug target.

Overall, this study is well constructed and rigorously performed, and the data provide strong support for the central conclusions about GDPD essentiality and functional contribution to parasite phosphocholine metabolism. The observation that exogenous choline largely rescues parasites from lethal deletion of GDPD is especially compelling evidence for a critical and dominant role in choline mobilization. A few aspects of the paper, however, are not fully supported by the current data and/or need clarification.

1. GDPD localization<br /> a) The authors conclude that GDPD is localized to the parasitophorous vacuole (PV) and parasite cytoplasm (lines 114-115), which is consistent with the prior 2012 Klemba paper. However, the data in the present paper (Figures 2A and 2E) only seem to support cytoplasmic localization but don't obviously suggest a population in the PV, in part because no co-staining with a PV marker is shown. The legend for Fig. 2E indicates staining with the PV marker, SERA5, but such co-stain is not shown in the figures or figure supplements. This data should ideally be included and described.

b) How do the authors explain cytoplasmic localization for GDPD? This protein contains an N-terminal signal peptide, which can account for secretion to the PV but would contradict a cytoplasmic population. The 2012 Klemba paper suggested that internal Met19 might provide an alternate site for translation initiation without a signal peptide and thus result in cytoplasmic localization. Some discussion of this ambiguity, its relation to understanding GDPD function, and a possible path to resolve experimentally seem necessary, especially as the authors suggest from data in Fig. 7 that this enzyme may have functions beyond choline mobilization, which may relate to distinct forms in different sub-cellular compartments.

2. The phenotypes depicted by representative microscopy images in panel 4E (especially for choline rescue) should be supported by population-level analysis by flow cytometry or microscopy of many parasites to establish generality.

3. The analysis in the last results section (starting on line 296) seems preliminary.<br /> a) For panel 7B, a population analysis of many parasites, with appropriate statistics, is important to establish a generalizable defect beyond the single image currently provided.

b) The data here would seem to be equally explained by an alternative model that GDPD∆ parasites are competent to form gametocytes but their developmental stall (due to choline deficiency) prevents progression to gametocytogenesis. The authors speculate that GDPD may play other roles in phospholipid metabolism beyond choline mobilization that are essential for gametocytogenesis. Their model, if correct, predicts that a GDPD deletion clone from +RAP treatment that is rescued by exogenous choline should not form gametocytes. Testing this prediction would be important to strongly support the conclusion of broader roles for GDPD in sexual development beyond choline mobilization.

Reviewer #3 (Public Review):

In this work, Ramaprasad et al. aimed to investigate the roles of a glycerophosphodiesterase (PfGDPD) in blood stage malaria parasites. to determine its role, they generated a conditional disruption parasites line of PfGDPD using the DiCre system. RAP-induced DiCre-mediated excision results in removal of the catalytic domain of this protein. Loss of this domain leads to a significant reduction of parasite survival, specifically affecting trophozoite stages. They suggest that there is an invasion defect when this protein domain is deleted. They additionally show the introduction of an episomal expression of PfGDPD can rescue the activity of the protein and restore parasite development. Interestingly, exogenous choline can rescue the effects of the loss of PfGPDP. Lipidomic analyses with labelled LPC show that choline release from LPC is severely reduced upon protein ablation and in turn prevents de novo PC synthesis. These experiments also show increase in DAG levels suggesting a defect in the Kennedy pathway. The authors purified PfGDPD and enzymatically show that this protein facilitates the release of choline from GPC. Additionally, the paper also briefly looks at the effects of the protein during sexual blood stages and show this is unlikely to be involved in sexual differentiation.

This paper is of interest to the community since the breakthrough paper of Brancucci et al. (2017), which showed us that decreased LPC levels induce sexual differentiation. This work brings novel insight into a GDPD responsible for the release of choline from GPC which actual seems more relevant to asexual stages and not sexual stage parasites. The authors have been extremely thorough in their experimentations on parasite viability and the exact role of this protein.

Reviewer #1 (Public Review):

This work sheds light on the adverse effects of Bacillus thuringiensis, a strong pathogenic bacteria used as a microbial pesticide to kill lepidopteran larvae that threaten crops, on gut homeostasis of non-susceptible organisms. By using the Drosophila melanogaster as a non-susceptible organism model, this paper reveals the mechanisms by which the bacteria disrupt gut homeostasis. Authors combined the use of different genetic tools and Western blot experiments to successfully demonstrate that bacterial protoxins are released and activated throughout the fly gut after ingestion and influence intestinal stem cell proliferation and intestinal cell differentiation. This phenomenon relies on the interaction of activated protoxins with specific components of adherens junctions within the intestinal epithelium. Due to conserved mechanisms governing intestinal cell differentiation, this work could be the starting point for further studies in mammals.

The conclusions proposed by the authors are in general well supported by the data. However, some improvements in data representation, as well as additional key control experiments, would be needed to further reinforce some key points of the paper.

1) Figure 1 and others: Several graphs in the manuscript show the number of cells/20000µm2.<br /> How is the shape of the gut in the different conditions studied in this manuscript?<br /> The gut shape (shrunk gut versus normal gut for example) could influence the number of cells seen in a small area. For example, the number of total cells quantified in a small area (here 20000µm2) of a shrunk gut can be increased while their size decrease. As a result, the quantification of a specific cell type in a small region (here 20000µm2) can be biased and not represent the real number of cells present in the whole posterior part of the R4 region. Would it make sense to calculate a ratio "number of X cells/number of DAPI positive cells per 20000µm2"?

2) Figure 4: Is it possible that Arm staining is less intense between ISC and progenitors after ingestion of the bacteria due to the fact there is a high rate of stem cell proliferation? Could it be an indirect effect of stem cell proliferation rather than the binding of the toxins to Cadherins?<br /> Could the authors use the ReDDM system to distinguish between "old" and newly formed cells? This could be a good control to make sure that the signal is quantified in similar cells between the control and the different conditions.

Figure 4E' and 4G': Arm staining seems more intense when looking at the whole membrane levels of cells compared to control. Is it possible that the measured ratio contact intensity/membrane intensity presented in Figure 4I could be impacted and not reflect the real contact intensity between ISC and progenitor cells?<br /> What is the hypothesis of the authors about the decrease of Arm or DE-Cad seen after bacterial/crystal ingestion? Does the interaction between the toxins and DE-Cad induce a relocation of DE-Cad?

The authors should add more details about the way to quantify in the Material and methods section. How many cells have been quantified per intestine? How did they choose the cells where they quantified the contact intensity?..etc

Figure 4B, D, F and H: How did the authors recognize the ISCs? Could the authors do quantifications of DE-Cad signal? Like Arm staining, the staining seems stronger at the whole membrane level in F and H compared to the control.

3) Figure 5: How is the stem cell proliferation upon overexpression of DE-Cad in control or upon bacteria/crystals ingestion? Do the authors think that the decrease of Pros+RFP+ new cells upon overexpression of DE-Cad could result from a decrease of stem cell proliferation?<br /> Did the authors quantify the % of new ECs in the context of overexpression of DE-Cad?<br /> Figure 5F: As asked before, did the authors distinguish the signal between newly born cells and the signal between older cells?

The same experiments (stem cell proliferation + quantification of the % of new ECs) could be also done when authors overexpress of the Connectin, supplemental figure 5. This would be another control to conclude that the effects on cell differentiation are specific due to the interaction between DE-Cad and the toxins.

In the "crystals" condition, the overexpression of Connection seems to partially rescue the increase % of new Pros+RFP+ new cells observed in Figure 3F (Figure S5I compared to Figure 3F).

Reviewer #2 (Public Review):

The authors have used well-characterized Drosophila intestinal epithelium as a model to investigate the potentially harmful effect of Btk Cry toxins on organisms that are not susceptible to the toxins. The experiments are well-designed, precisely performed, and appropriately assessed. Therefore, the presented results are in support of the authors' claims and conclusions. Additionally, the manuscript is written well to convey the message to a wide audience.

Reviewer #3 (Public Review):

The described work is about assessing Drosophila midgut histopathology upon consumption of an entomopathogenic strain of B. thuringiensis and its Cry1A toxins, which are lethal to lepidoptera, but non-lethal to Drosophila. Thus, Drosophila is characterized a non-susceptible organism. The authors tested if this "non-susceptible host" is nevertheless histopathologically susceptible. They convincingly show that it is, because the mechanism of action of the Cry1A toxins on progenitor cell E-Cadherin is functionally (but not biochemically) revealed in flies and in Drosophila S2 cells.

Strengths: The thorough cell fate analysis based on reporter genes and the alternative methods tested e.g. the wild type vs. mutant bacterial strains and purified active and inactive versions of Cry toxins.

Weakness: The heavy reliance on reporter transgenes, instead of staining of endogenous proteins and the lack of clonal analysis. Despite this the main conclusions are sufficiently supported.

Reviewer #1 (Public Review):

Modular E3 ligase complexes play important roles in controlling cell proliferation and differentiation. As had been illustrated by Cullin-RING-ligase complexes that are associated at specific stages of neuronal differentiation, regulated formation of E3 ligase complexes can strongly impact cell fate specification, but only very few examples of such regulation have been reported. Whether E3 ligase composition impacts the global proteome is not known. Providing additional examples of E3 ligase complexes, whose composition is regulated during differentiation processes, would be an important contribution to our understanding of how the ubiquitin system controls cell fate.

In this manuscript, Sherpa and coworkers used quantitative proteomics in in vitro models of erythrocyte differentiation to discover changes in the composition of the CTLH E3 ligase. Rather than finding altered association of substrate adaptors, including GID4, the authors noted the exchange of the scaffold subunits RanBP9 and RanBP10. Structural analyses suggested that this exchange does not have major impacts on CTHL conformation, but may lead to a reduction in E3 ligase activity towards a model substrate. The authors also deleted the enzymatic CTLH subunit MAEA and the E2 UBE2H from cell lines that served as in vitro models of erythrocyte differentiation. They found that loss of MAEA caused a strong decrease in UBE2H, which interestingly required the catalytic activity of CTLH. This observation suggested that CTLH complex composition is actively regulated. The loss of CTLH activity led to an increase protein abundance of hemoglobin subunits and accelerated erythrocyte differentiation, suggesting that CTLH might restrict cell fate specification until proper signals have been received by precursor cells.

While the observation of altered CTLH composition during differentiation is interesting, this study does not establish whether it is functionally important. The authors should assess whether deletion of RanBP9 or RanBP10 has functional consequences onto erythrocyte differentiation, which would indicate that the observations made here are significant in the context of this differentiation program. Furthermore, how MAEA loss causes a depletion in UBE2H has not been addressed beyond a simple rescue experiment using a single MAEA mutant, and the specificity and importance of this regulatory circuit therefore remains somewhat unclear. I do believe that especially the first issue needs to be addressed by the authors in order to establish the importance of the findings reported in this manuscript.

Reviewer #2 (Public Review):

In this study, the authors investigate the ubiquitin-mediated mechanisms underlying erythroid maturation. They first investigated proteome changes of CD34+ cells and HUDEP2 cells (an immortalized CD34+-derived line) which can be induced to undergo differentiation into different erythroblast stages. They identified that protein members of the E3 ubiquitin ligase complex called CTLH complex were globally increased during differentiation. They also found that the expression of several E2 enzymes including UBE2H, which partners with the CTLH complex, increase in later stages of erythroid maturation. Interestingly, they found that the 2 subunits of the CTLH complex, RanBP9 and RanBP10 which are structurally very similar, display opposite changes of expression, with RanBP9 decreasing and RanBP10 increasing during differentiation. They then show that both RanBP9 and RanBP10 can support complex formation in vitro and result in ubiquitin transfer competent complexes using ubiquitination with a model substrate peptide in vitro.

In the second part of the study, they created CRISPR-Cas9 knock out of UBE2H and the CTLH complex subunit MAEA in HUDEP2 cells to investigate the effect on proteome changes and erythroid cell differentiation. They found that both UBE2H and MAEA knockout cells display pronounced proteome-wide changes in erythroid-specific factors. They also show that the knockout of UBE2H and MAEA cause aberrant differentiation, with accelerated maturation, altogether suggesting that these 2 factors are required to maintain cells in progenitor state. Finally, they identify that MAEA expression is required to maintain UBE2H expression and that this regulation occurs at the post-translational level.

The authors clearly demonstrate that the CTLH complex and its associated E2 enzyme play important roles in erythroid differentiation. They also generated a wealth of data that document erythroid differentiation and point out very interesting co-regulatory mechanisms regarding ubiquitin machineries underlying this process. Notably, the authors identify an intriguing regulation of two CTLH complex members, RanBP9 and RanBP10 during erythroid maturation that correlates with, and suggests that the replacement of RanBP9 and RanBP10 during the process may be involved in regulating pathways that lead to erythroid maturation.

Unfortunately, while the above-mentioned regulation of the two CTLH complex members, RanBP9 and RanBP10 is suggested to play a role in erythroid maturation, it is not investigated further. It is genuinely surprising that the authors did not investigate the proteome of the RanBP9 and RanBP10 knockout HUDEP2 cells they generated, to figure out the effect the differential expression of these factors on erythrocyte development.

Instead, the study changes direction to focus on another CTLH complex subunit, MAEA, and how that subunit may function to regulate the expression of UBE2H, the E2 enzyme associated with the CTLH complex, in a manner seemingly independent of the other complex members. Overall, the work is interesting and advance our knowledge of the erythroid differentiation process, but there are some main issues including over-interpretation of data and experimental issues limiting data interpretation that would need to be addressed or the authors would need to revise their conclusions since as it stands now, some of the conclusions are not supported by the data.

Reviewer #3 (Public Review):

Sherpa, Müller et al. utilize temporal global proteome analysis of human erythropoiesis models to identify dynamic differential expression of RANBP9 and RANBP10, two homologous subunits of the multi-subunit ubiquitin E3 ligase CTLH. Through elegant biochemical and structural approaches, the authors provide compelling evidence that RANBP9 and RANBP10 form distinct, but structurally similar, catalytically competent CTLH E3 ligase complexes, that are differentially enriched in different stages of erythrocyte differentiation. Using CRISPR/Cas mediated knock outs, the authors inactivate the catalytic subunit of the CTLH E3 ligase, MAEA, or its cognate E2 enzyme UBE2H and show that this leads to spontaneous differentiation in erythrocyte progenitors under maintenance conditions and provide evidence that loss of these two proteins also accelerates differentiation. Interestingly, in these experiments the authors find that loss of MAEA leads to proteasomal degradation of UBE2H, which can be rescued by wildtype, but not catalytically inactive MAEA, demonstrating that UBE2H stability is coupled to cognate E3 ligase activity.

Strength:<br /> This study confirms previously known transcriptional regulation and functions of UBE2H and CTHL E3 ligase components during erythrocyte differentiation and identifies a previously unrecognized role for CTHL E3s during erythrocyte progenitor maintenance. In addition, the authors identify two new regulatory mechanisms impinging on the UBE2H-CTLH E3 that might be important for erythrocyte differentiation: differentiation stage-specific assembly of RANBP9-CTHL and RANBP10-CTHL complexes and coupling of UBE2H stability to catalytic activity of the CTLH E3 ligase.

Weaknesses:<br /> While the newly identified regulatory mechanisms are interesting, the major weakness of the study is that there is no evidence that these regulatory processes are functionally relevant for erythrocyte differentiation. In addition, the described phenotypes of UBE2H and MAEA deletion on erythrocyte differentiation could be analyzed in more detail, in particular addressing whether the accelerated differentiation reported is yielding functional progeny. Also the study could be strengthened by more quantitative assessment of the differentiation stage-dependent RANBP9-CTLH and RANBP9-CTLH E3 ligase complexes.

Reviewer #1 (Public Review):

Shade et al. describe the endocast and semicircular canal of multiple individuals and ontogenetic stages belonging to the taxon Europasaurus. Investigation of these traits lead the authors to suggest that this dwarfed sauropod was precocial and potentially capable to communicate with other individuals of the same species.

Overall, I enjoyed the manuscript, because of the importance of the taxon and the gap in our knowledge that this study fills. The anatomical descriptions of the endocast and semicircular canal are well done and detailed. That being said, the manuscript can be improved in terms of comparative framework: in the current version, the manuscript only covers anatomical comparisons in the discussion. I would suggest the authors include a final figure showing multiple endocasts of other sauropodomorphs to better show the evolutionary morphological transitions affecting the endocast and semicircular canal in this clade. It would also be useful to have tables with measurements comparing hearing frequencies among non-avian dinosaurs with Europasaurus: is this taxon peculiar in this? Or is it in the range of other taxa? Finally, the fact that vocalization was possible in this taxon does not imply gregarious behavior: this should be specified better in the manuscript.

Reviewer #2 (Public Review):

The authors aim to analyze and describe the neuroanatomy of the Late Jurassic sauropod Europasaurus holgeri. This is done by scanning with microCT both adult and juvenile specimens.

The authors successfully report in detail the overall anatomy of the Europasaurus braincase, as well as morphological characteristics so far undescribed in this taxon. Precociality in juveniles is suggested and also well-supported. Comparisons made with other sauropods are considered appropriate and clear.

Aspects of reproductive and social behavior in this taxon are deduced from the estimated auditory capabilities. They are not investigated in detail and more details regarding these aspects would be welcomed in the discussion.

Images in the manuscript are well-presented and clear, supporting adequately the description. Slicing of the CT data is sufficiently clear although a "polishing" of the final renders in some cases would be appreciated. Again, it is not necessary, since images are clear enough, but only suggested.

Reviewer #4 (Public Review):

This manuscript reports combining recently developed and described in the accompanying paper nanobodies against Sallimus and Projectin with DNA-Paint technology that allows super-resolution imaging. Presented data prove that such a combination provides a powerful system for imaging at a nano-scale the large and protein-dense structures such as Drosophila flight muscle. The main outcome is the observation that in flight muscle sarcomeres Salimus and Projectin overlap at the I/A band border. This was elegantly achieved using double color DNA-Paint with Sls and Projectin nanobodies.

Overall, as it stands, this manuscript even if of high technological value, remains entirely descriptive and short in providing new insights into muscle structure and architecture.<br /> The main finding, an overlap between short Sls isoform and Proj in flight muscle sarcomeres, is redundant with the author's observation (described in the companion paper "A nanobody toolbox to investigate localisation and dynamics of Drosophila titins") that in larval muscles expressing a long Sls isoform, Sls and Proj overlap as well.<br /> Alternatively, combination of Sls and Proj nanobodies with DNA-Paint represents an interesting example of technological development that could strengthen the accompanying nanobodies toolkit manuscript.

Reviewer #1 (Public Review):

The authors use the nanobody tools generated in the companion manuscript and have combined them with DNA-Paint oligonucleotide labeling to generate super-resolution images of indirect flight muscles. Using this approach, they could map the precise organization of the different domains from the two giant titin-like fly homologs called Sallimus and Projectin against which the nanobodies had been raised with a precision ranging from 1 nm to 4 nm, depending on the distance between them. They show that in indirect flight muscles the N-ter of Sallimus is located within 50 nm of the Z-disc, and that its C-ter reaches the A-band roughly 100 nm away from the Z-disc. Likewise, they show that the N-ter of Projectin colocalizes with the C-ter of Sallimus at the edge of the A-band, whereas its C-ter is located about 250 nm away in the A-band and 350 nm from the Z-disc. It overall suggests a staggered and linear organization of both proteins with a potential area of overlap spanning 10-12 nm, that Sallimus could bridge the Z-disc to the A-band acting as a ruler, while Projectin should only overlap with 15% of the A-band and possibly a 10 nm of the I-band.

The value of this work comes from its use of advanced technologies (DNA-Paint + super-resolution). The biological conclusions confirm and refine earlier and recent papers, especially EM papers and the impressive and very comprehensive JCB paper by Szikora et al in 2020, although the conclusions of the present work differ somewhat from those of Szikora who had predicted that Sallimus does not reach the A-band. That aspect could have been better discussed.

Reviewer #2 (Public Review):

Taking advantage of the high molecular order of the Drosophila flight muscle, Schueder, Mangeol et al. leverage small (<4 nm) original nanobodies, tailored coupling to fluorophores, and DNA-PAINT resolution capabilities, to map the nanoarchitecture of two titin homologs, Sallismus and Projectin.

Using a toolkit of nanobodies designed to bind to specific domains of the two proteins (described in the companion article "A nanobody toolbox to investigate localisation and dynamics of Drosophila titins" ), Schueder, Mangeol et al position these domains within the sarcomere with <5nm resolution, and demonstrate that the N-ter of Sallismus overlaps with the C-ter of Projectin at the A-band/I-band interface. They propose this architecture may help to anchor Sallismus to the muscle, thus supporting flight muscle function while ensuring muscle integrity.

This study nicely extends previous work by Szikora et al, and precisely dissect the the sarcomeric geography of Sallismus and Projectin. From these results, the authors formulate specific functional hypotheses regarding the organization of flight muscles and how these are tuned to the mechanical constraints they undergo.

Although they remain descriptive in essence, the conclusions of the paper are well supported by the experimental results.

Reviewer #3 (Public Review):

This manuscript by Schueder et al. provides new insight into an important question in muscle biology: how can the smaller titin-like molecules of the much larger sarcomeres of invertebrate muscle perform the same function as the larger titin of vertebrate muscles which have smaller sarcomeres? These functions include the assembly, stability and elasticity of the sarcomere. Using two state of the art methods--nanobodies and DNA-PAINT super-resolution microscopy, the authors definitively show that in the highly ordered indirect flight muscle of Drosophila, the elongated proteins Sallimus and Projectin are arranged such that the N-terminus of Sallimus is embedded in the Z-disk, and the C-terminus is embedded in the outer portion of the A-band, and that in this outer portion of the A-band is also embedded the C-terminus of Projectin; thus, if the C-terminus of Sallimus can bind to thick filaments, and/or these overlapping portions of Sallimus and Projectin interact, there would be a linkage of the Z-disk and/or thin filament to the thick filaments to help determine the length and stability of the sarcomere.

The strengths of this paper include the implementation of nanobody and DNA-PAINT super-resolution microscopy for the first time for muscle. The extraordinary 5-10 nm resolution of this method allows imaging for definitive localization of the termini of these elongated proteins in the Drosophila flight muscle sarcomere. In addition, the manuscript is well written with sufficient background information and rationale presented, is easy to read, complex new methods are well-described, the figures are of high quality, and the conclusions are well-justified. A minor weakness is that despite the authors demonstrating that the C-terminus of Sallimus is located at the outer edge of the A-band, and that the N-terminus of Projectin is located also in the outer edge of the A-band, the authors provide no data to show whether, for example, these portions of these titin-like molecules interact, or whether Sallimus might interact with thick filaments. Such data would be required to prove their model. However, I can understand that this would require extensive additional study, and the authors have already provided a tremendous amount of data for this first step in supporting the model. Nevertheless, the authors should cite a relevant previous study on the Sallimus homolog in C. elegans called TTN-1, which is also a 2 MDa polypeptide of similar domain organization to at least the large isoforms of Salliums found in fly synchronous muscles. In the study by Forbes et al. (2010), immunostaining, albeit not to the impressive resolution achieved in the present paper, showed that TTN-1 was also localized to the I-band with extension into the outer edge of the A-band. More importantly, that study also showed that "fragment 11/12", Ig38-40, which is located fairly close to the C-terminus of TTN-1 binds to myosin with nanomolar affinity (Kd= 1.5 nM), making plausible the idea that TTN-1 may bind to the thick filament in vivo.

Reviewer #1 (Public Review):

Hepatitis C virus (HCV) infection continues to be an enormous global public health problem with over 70 million infected. The advent of all-oral direct-acting antivirals (DAAs) has transformed the landscape of HCV therapy and paved the path to the ambitious World Health Organization (WHO) goal of viral hepatitis elimination by 2030. Research to establish an algorithm to shorten DAA therapy duration while maintaining high cure rates would impact both treatment access and achieving HCV elimination. The current clinical study aimed to examine a response-guided therapy (RGT) algorithm to shorten the standard 12-week sofosbuvir and daclatasvir therapy based on measuring hepatitis C viral load level at day 2 of treatment. The authors managed to complete this study despite severe COVID-19-related restrictions. While the RGT algorithm failed to reach acceptable cure rates under the 4-week treatment arm, the study provides valuable kinetic data to test other RGT approaches. Also, this paper is novel since data on HCV RNA genotype 6 kinetics is lacking.

Reviewer #2 (Public Review):

This clinical trial is conducted to pursue short course DAA therapy. For an ultra-short course to work, it has to be simple, equally efficacious to established treatments, and requires no additional workup (like genotyping, IL28B, HCV VL determination, etc after initiation of therapy as shown in Liu et al.). This is because our aim is to simplify therapy to treat most people, especially those who are not engaged in care.<br /> This work struggles to achieve these goals, as the to the SVR for short-course therapy is unacceptably low. The authors' conclusion that treat short first and then you can treat those who fail again does not appear to achieve these goals, as realistically, it is difficult to re-engage marginalized population from an elimination perspective. The ideal is to treat them in one attempt.

Reviewer #3 (Public Review):

This prospective study evaluated the utility of D2 VL determination for response-guided ultra-short (4w) sofosbuvir + daclatasvir treatment of chronic HCV patients (with mild disease) with G1+6. Shortening therapy duration reduces DAA use with a cure rate of 75% overall upon first-line treatment and 100% among retreated patients. In contrast to a previous report in G1b patients that showed a 100% success rate with D2-based 3-week triple therapy, the present study fails to show a good enough yield for a 4w sofosbuvir + daclatasvir regimen among G1+6 patients. Given the small number of patients, additional studies should determine whether a different time point and/or a different viral threshold could be more appropriate indicators to allow a 4-week duration of dual therapy (without a protease inhibitor).

Strengths:<br /> A. An important study that is a nice addition to previous reports evaluating the utility of response-guided therapy for shortening the duration of HCV treatment. Given the disease burden and the high costs of treatment, especially in low-income countries, this is a major goal that was also advocated by the WHO.<br /> B. This study investigates an ultra-short protease-inhibitor-free regimen and therefore complements a previous (positive) RGT study of a 3-week triple regimen.<br /> C. This study is prospective with careful analyses of ample data, including the evaluation of RAS by gene sequencing. The follow-up was long enough and analyses of viral kinetics were performed. In addition, a detailed analysis of re-treatment outcomes and viral mutations in this population was performed<br /> D. Although the main objective (shortening therapy to 4 weeks) was not adequately achieved (<90% success rate), the study's results may suggest that re-treatment in case of failure is safe and efficient, although further studies with a higher number of patients are needed for confirmation.

Limitations:<br /> A. Relatively small study cohort. Overall, only 34 patients were treated with a 4-week regimen. However, given the results, it seems that this number of patients who achieved only a 75% cure rate, is enough to exclude the use of a D2 RGUT, at least in G1+6 patients treated with sofosbuvir + daclatasvir. On the other hand, even 100% of success rate on 8-week treatment among 17 patients is not really enough to draw firm conclusions on the adequacy of this short regimen among this group of patients. A higher number of patients could better validate this positive result.<br /> B. The values chosen for the RGT are arbitrary. The relatively small number of patients could not allow for a more detailed analysis of more appropriate time points and/or viral load thresholds to determine the adequacy of a 4-week of therapy in individual patients. The D2 500IU/ML threshold is based on a small previous phase 2 study on G1b patients treated with a triple-drug regimen, which does not necessarily imply dual therapy (w/o a protease inhibitor) involving patients with a different subtype of the virus. In this context, a control group treated with triple combination therapy (with a protease inhibitor) could be very helpful to the study.<br /> C. Is there a particular pattern of viral kinetics to 4w cured patients Vs. failures? Fig 1 (Appendix 1) only shows the means of viral load and the general kinetics for the whole population, but individual plots of viral kinetics are not presented although could potentially be useful. Also, according to the presented data, day 7 VL D. According to Table 3, no significant differences in the host or viral factors were detected between cured or failures of the 4w regimen. However, the low number of patients makes it very difficult to interpret these data and might miss potential differences between these two groups of patients, emphasizing again the difficulty in drawing firm conclusions from this study. In this context, I wonder whether a regression analysis would better define either viral (subtype, RAS) or host factors that are implicated in a 4w duration success.

Reviewer #1 (Public Review):

Using multiple mouse models with varying levels of H19 and Igf2 expression, the authors dissect the role of H19 and Igf2 in cardiac and placental development. Severe cardiac defects and placental anomalies were found to be correlated with the extent of H19/Igf2 dysregulation. Transcriptomic analysis revealed that H19/Igf2 dysregulation disrupts pathways related to extracellular matrix (ECM) and proliferation of endothelial cells. This work links the heart and placenta through regulation by H19 and Igf2, demonstrating that an accurate dosage of both H19 and Igf2 is critical for normal embryonic development, especially related to the cardiac-placental axis. The topic is of significance and the data are of high quality.

Reviewer #2 (Public Review):

Despite the fact that Igf2 and H19 are the two best-studied imprinted genes in (mouse) development, substantial gaps in knowledge continue to exist as to their independent functions in normal and pathological situations, including in the imprinting disorders BWS and SRS to which they are linked. Here, using three established mouse models in a clever way, the authors are able to dissect the impact of overexpression or depletion of Igf2 and H19 independently of each other. This sophisticated use of mouse genetic models is a major achievement in trying to discern the precise impact of these genes on the development of particular cell types and tissues.

The authors report the placenta and heart as the two most severely affected organs in these mouse models. What remains unclear is if these phenotypes are causally linked, such that - for example - endothelial cell dysfunction causes the placental phenotypes or, conversely, trophoblast dysfunction causes the heart phenotypes. The "placenta-heart axis" is repeatedly referred to; however, unlike in the use of the term in the current manuscript, this term is more commonly used to describe situations where the placenta is causative of heart phenotypes, as first established in the Pparg mutation. Along these lines, it would be instrumental to establish in at least one of the mouse models under investigation here, if any of the heart or placental defects are secondary to gene function in a cell type outside of the affected organ itself.

The transcriptomic analysis of E12.5 endocardial cushion cells in the various mouse models is informative in the extraction of Igf2- and H19-specific gene functions. This analysis raises a few questions: In Fig. 6D, a huge sex effect is obvious with many more DEGs in female embryos compared to males. How can this be explained given that Igf2/H19 reside on Chr7 and do not primarily affect gene expression on the X chromosome? Is any chromosomal bias observed in the genomic distribution of DEGs? A separate issue is raised by Fig. 6E that shows a most dramatic dysregulation of a single gene in the delta3.8/hIC1 "rescue" model. Interestingly, this gene is Shh. Hence, these embryos should exhibit some dramatic skeletal abnormalities or other defects linked to sonic hedgehog function.

The placental analysis needs to be strengthened. Placentas should be consistently positioned with the decidua facing up, and the chorionic plate down. The placentas in Fig. 3F are sectioned at an angle and the chorionic plate is missing. These images must be replaced with better histological sections. The CD34 staining has not worked and does not show any fetal vasculature, in particular not in the WT sample. The "thrombi" highlighted in Fig. 4E are well within the normal range, to make the point that these are persistent abnormalities more thorough measurements would need to be performed (number, size, etc).

The statement that H19 is disproportionately contributing to the labyrinth phenotype (lines 154/155) is not warranted as Igf2 expression is reduced to virtually nothing in these mice. Even though there is more H19 in the labyrinth than in the junctional zone, the phenotype may still be driven by a loss of Igf2.<br /> Given the quasi Igf2-null situation in +/hIC1 mice, is the glycogen cell type phenotype recapitulated in these mice, and how do glycogen numbers compare in the other mouse models?

How do delta3.8/+ and delta3.8/hIC1 mice with a VSD survive? Is it resolved some time after birth such that heart function is compatible with postnatal viability? And more importantly, do H19 expression levels correlate with phenotype severity on an individual basis?

Reviewer #3 (Public Review):

The study conducted by Chang and colleagues elegantly describes the significance of appropriate H19 and Igf2 gene expression control in the formation of the fetal heart and placenta. They used established and newly developed genetic models in mice, histological analyses, and transcriptomic assessments to assess the contribution of H19 and Igf2 to the defects observed. On a whole the paper is very well written, the experimental design is sound, the results compelling, and the conclusions supported. I only have minor suggested edits/comments.

Reviewer #1 (Public Review):

The work is largely based on metabolic flux assays of cultured cells, using a combination of metabolite concentration assessments, stable isotope-labeled substrates coupled with mass spectrometry, mathematical modeling, and cell proliferation analysis. The work finds a significant and unexpected phenotype in lung fibroblasts and smooth muscle cells of decreased lactate production in hypoxia which is important in the field of pulmonary hypertension. The evidence is strong and could be assisted with further orthogonal studies.

Reviewer #2 (Public Review):

Copeland et al. set out to assess the impact of HIF1 activation - either through glycolysis or pharmacological inhibition of prolyl hydroxylase (PHD) - in primary fibroblasts and smooth muscle cells. The goal was to compare the metabolic responses between these two states, and with the scores of papers studying metabolic responses to hypoxia in cancer cells. Using a combination of metabolomics, metabolic flux analysis, and gene expression studies, they surprisingly find that hypoxia induces the expected activation of glycolytic genes, but fails to induce some of the classical metabolic responses reported in cancer cells, including glucose uptake and lactate secretion. Lactate secretion is enhanced by PHD expression, but this is reversed by hypoxia. The authors further find that hypoxia induces the expression of MYC, and they use gain and loss of function experiments to show that MYC is involved in the reduction of lactate secretion by hypoxia. The paper's strengths are the detailed and quantitative analysis of metabolic responses in two different models of non-transformed cell proliferation, as well as the combination of gain- and loss-of-function analyses of MYC. Relative limitations include the use of a single chemical compound to activate HIF-1 in normoxia, and the lack of an explanation for why MYC is induced in hypoxia but not in normoxic HIF activation, or why MYC's effects are so different here than what is usually observed in cancer cells. If validated, the findings of the paper would add complexity to the mechanisms by which cells respond to hypoxia; to date, these responses have mostly been studied in cancer cells, and the new data suggest that non-transformed cells respond quite differently. The findings also suggest that MYC's effects on metabolism are determined in part by the cell state, as a large amount of existing data indicates that MYC drives lactate secretion in cancer cells.

Reviewer #3 (Public Review):

Via a study of metabolic flux of proliferating human primary cells (lung fibroblasts and PASMCs) in vitro, the authors primarily find that MYC uncouples an increase in HIF-dependent glycolytic gene transcription from the glycolytic flux in hypoxia. This finding is surprising and significant, given that prior work in cancer cell lines has indicated that glycolysis is uniformly increased under hypoxic stress. Strengths of the study include the comprehensive rigor of the approach to reach this conclusion, the accounting of multiple confounding variables, and the well-written presentation of the findings. These findings will be of use to the general scientific community, particularly the atlas of molecular alterations seen with their flux analyses. The surprising findings will set the stage for additional work on MYC's role in primary vs. transformed cells, the mode of regulation of MYC in primary cells, and the relevance of this mechanism in in vivo contexts of health and disease. A weakness of the study that can be improved upon in future work includes confirmation of findings in more physiologically relevant contexts of primary tissue in the body.

Peer review report

Title: Crossref as a source of open bibliographic metadata

version: 2

Referee: Simon Porter

Institution: Digital Science

email: s.porter@digital-science.com

ORCID iD: https://orcid.org/0000-0002-6151-8423

General assessment

This is a clear paper that outlines a motivation (assess the metadata completeness of the Crossref record for the purposes of scientometric analysis,) along with providing a set of useful metrics to assess the completeness of each metadata field.

Essential revisions that are required to verify the manuscript

No essential revisions identified

Other suggestions to improve the manuscript

Minor suggestions: Figures in the interactive version of the preprint do not have headings or captions, or a link back to the paper.

On data availability, In the context of the paper, making the code used to process the Crossref’s XML Metadata Plus Snapshot would be a useful contribution enabling scientometric analysis of the Crossref dataset.

The following are offered as suggestions that could be added to the paper at the authors discression, but do not effect the content or the conclusions of the peer review

The authors have chosen to frame metadata completeness of Crossref records as a ‘good in itself,’ leaning on Waltman, L. (2020b) to do the work of setting this up.

Within this framework, the analysis is offered as a set of observations to help publishers understand where they need to do better. It might be the case that Publishers do not intrinsically understand why making certain metadata types available is valuable to the community.

On the question of how Crossref can be used in scientometric analysis, readers are left to make up their own minds on what Crossref can be used for today, vs what it might be capable of providing in the future based on the evidence presented. It would be a stronger conclusion to highlight the types of scientometric analysis that are now possible with Crossref, (for instance bibliometric coupling,) and those that require limits or caveats (analysis by affiliation, abstract.) As this analysis lends itself to being rerun in the future, it would be useful to trace advances (hopefully!) not just in terms of the number of things, but also in terms of how sceintometric analysis capability is progressing because of it.

Decision

Verified manuscript: The content is scientifically sound, only minor amendments (if any) are suggested.

Reviewer #1 (Public Review):

This excellent manuscript challenged the premise that NF-kappaB and its upstream kinase IKKbeta play a role in muscle atrophy following tenotomy. Two animal models were used - one leading to enhanced muscle-specific NF-kappaB activation and the other a muscle-specific deletion. In both models, there was no significant relationship to observed muscle changes following tenotomy. Overall this work is significant in that it challenges the existing dogma that NF-kappaB plays a crucial role in muscle atrophy.

Surprisingly the authors noted that there were basal differences observed in the phenotypes of their models that were sex-dependent. They note that male mice lose more muscle mass after tenotomy and specifically type 2b fiber loss.

Overall this is an outstanding study that challenges the notion that NF-kappaB inhibitors are likely to improve muscle outcomes following injuries such as rotator cuff tears. Its main weakness is that there were no pharmacological arms of investigation; this fails to definitively exclude the hypothesis that inhibition may exert some effect in healing, perhaps in surrounding non-muscle matrix tissue that in turn may assist in healing.

Reviewer #2 (Public Review):

The purpose of this study was to evaluate the transcription factor NF-KB, a common transcription factor that is thought to mediate muscle atrophy, in the setting of a rotator cuff injury. Unlike many other models of atrophy such as hind limb suspension, aging, and neurologic injury, the tenotomy model represents a unique mechanical change where the muscle is acutely unloaded from the bone, which is relevant for rotator cuff injuries as well as achilles tendon ruptures.

The premise of the study was that NF-kB, a known central regulator of muscle atrophy, would be a central mediator of this process in a tenotomy model as well. The study hypothesized that NF-kB inhibition would reduce atrophy in a rotator cuff model through atrogene-independent mechanisms, a hypothesis that is well supported by literature in other models.

Using gain of function and loss of function NF-kB inhibitors, the IKKB family, to evaluate this pathway after a tenotomy model. The results were rigorously approached with appropriate timelines and controls, and the analyses were well done. Surprisingly, the study found that NF-kB did not appear to be an important regulator of tenotomy-induced atrophy, which they did an excellent job of exploring in detail with their gain/loss of function mice, and by looking at cellular changes, protein changes, and architectural changes after rotator cuff injury. They did find that autophagy, which was more pronounced in male mice, was a sex-dependent mechanism that seemed to regulate atrophy.

The primary strength of this paper is a rigorous approach to 'negative' data. Did the authors definitively prove that NF-kB has no role in the tenotomy-induced atrophy? Probably not entirely, since there are limitations of the mouse model and the knockdown mice. There cannot be complete elimination of load since mice heal with some scar tissue, and the knockdown is not complete elimination. However, even with these limitations, this presents important findings that tenotomy, which induces mechanical unloading of the muscle-tendon unit, provides a unique biomechanical environment for the muscle to undergo atrophy, which warrants a more in-depth look given that these injuries are unique and extremely common. It must be mentioned that the results are entirely supported by their data and that even though the model is not 'perfect' it truly supports that NF-kB has a limited role in atrophy. The sex-mediated differences based on autophagy are a secondary hypothesis and are interesting but possibly less clinically relevant based on the differences shown.

The important next step for this group and others is to evaluate the 'how and why' of tenotomy atrophy if not through NF-kB. Is it that there are many redundant processes that the muscle may have to circumnavigate the NF-kB pathway given that it is so ubiquitous that the authors didn't see a difference? Could it be differences in axial vs appendicular muscle? Or should there be a closer look at the mechanosensors in the muscle cells to determine if there are other key drivers of atrophy? Regardless, this paper shows that tenotomy-induced muscle atrophy is unique, and supports the conclusion that muscle has many ways to atrophy based on the injury it undergoes.

Reviewer #3 (Public Review):

This study is designed to test the mechanistic role of NF-kB signaling in muscle atrophy following rotator cuff injury. The authors utilized a genetic gain-of-function and loss-of-function model to manipulate NF-kB activation and how this alters muscle plasticity following rotator cuff tendon transection.

The authors provided thorough analyses of muscle morphology, biochemistry, and function, which is a major strength of the study. However, there are some key confounding variables authors failed to address. For example, the difference in the estrous cycle in female animals was not controlled. The study could have been significantly improved by controlling sex hormone levels or at least testing differences in response to injury. Furthermore, more data are needed to link NFkB signaling and autophagy to make any kind of conclusions.

Overall, in the current form of the manuscript, the presented data seem underdeveloped, and the addition of more supporting data could significantly improve the quality of the manuscript and enhance our understanding of NFkB signaling and muscle wasting in rotator cuff injury.

Reviewer #1 (Public Review):

This paper makes two major contributions. First, the authors provide a large synthetic dataset of human arm trajectories tracing the alphabet in 3D space. They also model the musculoskeletal system and the muscle spindles during tracing. This dataset would be very valuable for later studies. I thank the authors for making the effort.

Second, the authors train various neural networks on two tasks, a character trajectory-decoding task and an action recognition task, from spindle outputs and find that artificial neural network representations from the action-recognition task better explain what is known about the proprioceptive system. This is potentially an important finding, because, the authors claim that trajectory decoding is the canonical hypothesis for proprioception's role.

The authors are very systematic in the methodology with which they did their machine learning and representational analysis. I don't have any major comments on that.

I have concerns about the main finding though. While it is true that state estimation is thought to be a major function of proprioception, this state estimation is part of a control loop. If the goal is to refute the canonical hypothesis for proprioception, the authors should actually simulate/train a full control loop. This is likely to change their conclusions because authors interpret state prediction as the prediction of end effector coordinates at each time step. However, to run a control system one may need to predict other state variables - like effector velocities and accelerations, muscle configurations, etc. - as well, and these may change the intermediate level representations.

Reviewer #2 (Public Review):

Does our proprioceptive system try to recognize our own actions?

Proprioception is our sense of the motion and posture of our own body. This sixth sense uses signals from receptors in the joints, tendons, muscles, and skin that measure forces and degrees of extension. These receptors enable us to sense, for example, the posture of our body as we wake from sleep. They also provide feedback signals that help us precisely control our limbs, for example during handwriting.

Feedback is thought to be essential to motor control, enabling the controller in our brains to rapidly adapt to the unexpected. The unexpected may include changes in the environment (like something pushing our hand that we didn't see coming), changes in our bodies (such as muscle fatigue or injury), and shortcomings of the motor program (such as a lack of precision or a badly planned limb trajectory). Feedback can come from vision and even audition, but proprioception provides an essential additional feedback path that informs us directly about the motion and posture of our limbs, and any forces on them.

How does feedback control work in the human motor system? I want to write a 'k', but there are forces on my limbs resulting from the friction of chalk on this particular blackboard. Also, my muscles are recovering from tennis practice this morning, and I haven't used chalk on a blackboard in years.

If the goal is to write a 'k', I have some flexibility. I am committed, not to a precise trajectory, but to a more abstractly defined objective: to write a legible 'k'. This suggests that feedback processing should evaluate to what extent I am succeeding at the action, not at tracing out a particular trajectory. Does what I'm actually doing look like writing a 'k'?

In a new paper, Sandbrink et al. (pp2022) report on simulations of the human musculoskeletal system and neural network models that suggest that the tuning properties of neurons in the somatosensory cortex (S1) can be explained by assuming that the objective of the proprioceptive system is to recognize the action being performed.

They used recorded traces of a person writing lower-case letters to simulate the responses of muscle spindles sensing the lengths and velocities of muscles in the human arm as would be present if the hand was moved passively along these trajectories. The physical simulation uses a 3D model of the human arm with two parameters for the direction of the upper arm and two more for the direction of the lower arm. These four parameters are inferred by inverse kinematics from the hand trajectories tracing each letter in a variety of vertical and horizontal planes. A 3D muscle model then enables the authors to compute the expected spindle responses that reflect the lengths and velocities of 25 relevant upper arm muscles.

The authors then trained neural network models of proprioceptive processing that took the simulated muscle spindle signals as input. The neural net architectures included one that first integrates information over the muscle spindles and then across time ("spatial-temporal"), one that integrated across muscle spindles and time simultaneously ("spatiotemporal") and a recurrent long-short-term-memory model.<br /> Each architecture was trained on two objectives: to decode the trajectory (i.e. the position of the hand tracing a letter as a function of time) or to recognize the action (i.e. the letter being traced). The two objectives correspond to two hypotheses about the function of proprioceptive processing: To inform the feedback controller about either the current position of the hand or the letter being drawn.

The models trained to recognize the action developed tuning more consistent with what is known about the tuning of neurons in the primary somatosensory cortex in primates. In particular, direction tuning with roughly equal numbers of units preferring each direction emerged in the middle layers of the neural network models trained to recognize the action, similar to what has been observed in primate neural recordings. Direction tuning is already present in the muscle-spindle signals, but the spindle signals do not uniformly represent the directions.

The task-optimization approach to neural network modeling is inspired by work in vision, where neural networks trained on the task of image classification explained responses to novel images in populations of neurons in the inferior temporal cortex. This result suggested a tentative answer to the why question: Why do inferior temporal neurons exhibit the response profiles and representational geometry they exhibit? Because their function (or one of their functions) is to recognize the objects in the images. Here, similarly, the authors address a why question with task-optimized neural network models: Why do somatosensory cortical neurons exhibit the types of tuning that have been reported in the literature?

The function of proprioception, of course, is not for the brain to recognize which letter it is trying to write. It already knows that. The function is to sense how the current trajectory - the actual, not the intended one - differs from, say, a legible "k" (if that was the intention), and to map from that difference to a modification vector that will improve the outcome.<br /> Why is action decoding relevant for performing the action? A key reason may be that the goal is not to produce a fixed trajectory, but to produce a legible 'k'. A legible 'k' is not a single trajectory, but a class of trajectories containing an infinity of viable solutions. If someone nudged my arm while writing, adaptive feedback control should not attempt to return me to the originally intended trajectory, but to a new trajectory that traces the most legible 'k' that is still in the cards, which may be a different style of 'k' than I originally intended.

The paper contributes a useful data set for training models and a qualitative comparison of models to real neurons in terms of tuning properties. It would be good, in follow-up studies, to directly test to what extent each of the models can quantitatively predict either single-neuron responses or population representational geometries, as has been done in vision, and to perform statistical comparisons between models.

Importantly, this paper develops the idea of combining simulations body and brain, of the musculoskeletal system, and the processing of control-related signals in the nervous system, which provides a very exciting direction for future research.

Strengths

• The paper introduces a highly original research program that marries simulation of the musculoskeletal system and neural network modelling to predict neural representations in the proprioceptive pathway.<br /> • The authors performed an architecture search and trained multiple instances of different neural network architectures with each of the two objectives.<br /> • The paper includes comprehensive analyses of the proprioceptive representations from the simulated muscle-spindle signals through the layers of the models. These analyses characterize unit tuning, linear decodability, and representational similarity.<br /> • The results suggest an explanation for the direction tuning with a roughly uniform distribution of the units' direction preferences that has been reported previously for neurons in the primate primary somatosensory (S1) cortex.<br /> • If the simulated muscle-spindle data set, models and analysis code were shared along with the published paper, this work could form the basis for quantitative model evaluation and further model development.

Weaknesses

• The models are qualitatively evaluated by comparison of model unit tuning to what is known about the tuning of neurons in the somatosensory cortex. Follow-up studies should quantitatively evaluate the models by inferential analyses of their ability to predict measured responses.<br /> • The two training objectives differ in multiple respects, making it difficult to assess what the necessary requirements are for the emergence of representations similar to primate S1. Decoding the hand position may be too simple, but what about decoding velocity, or trajectory descriptors such as curvature? There may be a middle ground between trajectory decoding and action recognition that also leads to the emergence of tuning properties as found in primate S1.

Reviewer #1 (Public Review):

In this well-written manuscript, Afshar et al demonstrated the significant transcriptional and proteomic differences between cultured human umbilical vein endothelial cells (HUVECs) and those freshly isolated from the cords. They showed that TGFbeta and BMP signaling target genes were enriched in cord cells compared to those in culture. Extracellular matrix (ECM) and cell cycle-related genes were also different between the two conditions. Because master regulators of EC shear stress response genes, KLF2 and KLF4, were downregulated in culture, the authors sought to restore the in vivo transcriptional profile with the application of shear stress in an orbital shaker and dextran-containing media for various time periods. They showed that after 48 hours of shear stress the transcriptional profile of sheared cells correlated with in vivo transcriptional profile more significantly than static cultures. They also showed, using single cell RNAseq, that EC-smooth muscle cell cocultures resulted in changes in TGFbeta and NOTCH signaling pathways and rescued 9% of the in vivo transcriptional signatures.

This is an important study that was elegantly executed. The authors should also be commended for making their data public; thereby, creating a valuable resource for vascular biologists.

Reviewer #2 (Public Review):

The authors profiled the transcriptome and proteome of human umbilical vein endothelial cells freshly isolated from in vivo and compared that with the same cells exposed to in vitro culture under different conditions, including static culture, flow, and co-culture with smooth muscle cells. The experiments were properly designed and performed. The authors also provided a reasonable and sound interpretation of their findings. This study provides valuable insights into how the culturing conditions impact on gene expression, encouraging the field to select their in vitro work setting appropriately. Overall, the manuscript is well-written and easy to follow.

Several notable strengths include:

1. Parallel transcriptome- and proteome-wide profiling of endothelial cells enabling the unbiased interrogation of gene expression and a genome-wide view of the impact of in vitro culture on endothelial transcriptome.<br /> 2. The innovative experimental design and comparisons were done with genetically identical ECs (from the same donors) in vivo and in vitro.<br /> 3. The analyses were robust and provided novel information on flow-dependent and cell context-dependent gene regulation, with the native freshly isolated cells as a baseline.<br /> 5. The donor samples used in this study were diverse including Asian, White, Black, Latino, and American Indian samples which reduce racial background bias.

Some points that can strengthen the study:

A clear description of experimental and analytical details (e.g. how the comparisons were made) and more in-depth interpretation and discussion of the results, e.g. the complete genes that are rescued by flow and co-culture and potential synergy of these factors.

Reviewer #3 (Public Review):

Afshar et al. performed RNA-seq and LC-MS of in vivo and in vitro HUVECs to identify the role of culture conditions on gene expression. Given the widespread use of HUVECs to study EC biology, these findings are interesting and can help design better in vitro experiments. There have been previous papers that compared in vivo and in vitro HUVECs, however, the depth of sequencing and analysis in this manuscript identifies some novel effects which should be accounted for in future in vitro experiments using ECs.

Strengths:<br /> 1. Major findings of distinct pathways affected by cell culture are novel and interesting. The authors identify major effects on TGFb and ECM gene expression. They also corroborate previous findings of flow response pathways, namely KLF2/4 and Notch pathway regulation.<br /> 2. Use of multiple genomic methods to profile effects of culture conditions. The LC-MS data showed a significant correlation with RNA-seq, however, the data were not as strong so not used for subsequent analyses.<br /> 3. Use of scRNA-seq to show the dynamic effects of co-culture and shear stress on ECs is very novel. However, the heterogeneity in the EC populations is not discussed in this manuscript.

Weaknesses:<br /> 1. The physiological relevance of these changes in gene expression is not demonstrated in the manuscript. The authors claim the significance of their data is to improve in vitro culture to better represent in vivo biology. Is this the case with orbital shear stress? Do they rescue some functional effects in ECs with long-term shear stress? An angiogenesis, barrier function, or migration assay for HUVECs exposed to different conditions would help answer this question. A similar assay for cells after EC-VSMC co-culture would validate the importance of these stimuli.<br /> 2. One explanation for the increased expression of ECM genes in vivo is that these cells are contaminated with VSMCs/fibroblasts. This could be very likely given that cells were not sorted or purified upon isolation. Expression of other VSMC or fibroblast-specific markers (i.e. CNN1, MYH11, SMTN, DCN, FBLN1) would help determine if there is some level of non-EC contamination.<br /> 3. The use of scRNA-seq in Figure 4 is interesting. There appear to be 2 distinct EC populations in the co-cultured ECs. What are the marker genes for the 2 populations?<br /> 4. The modest shifts in gene expression with shear stress and co-culture could be attributed to the batch effect. The authors describe 1 batch correction method (ComBat) in the bulk RNA-seq, but no mention of batch correction was noted in the scRNA-seq methods. The authors should ensure that batch effect correction in all data is adequate, and these results should be added to the manuscript.<br /> 5. Table 1 shows ATAC-seq was done, however, no data from these experiments are provided in the manuscript.<br /> 6. Shear stress was achieved with an orbital shaker, which the accompanying citation states introduces significant heterogeneity in the ECs. This is based on the location of the culture dish. Was this heterogeneity seen in the scRNA-seq data?<br /> 7. It would be important to know whether the authors reproduce the findings from other papers that CD34 expression is reduced in cultured HUVECs:

Muller AM, Cronen C, Muller KM, Kirkpatrick CJ: Comparative analysis of the reactivity of human umbilical vein endothelial cells in organ and monolayer culture. Pathobiology 1999;67:99-107.

Delia D, Lampugnani MG, Resnati M, Dejana E, Aiello A, Fontanella E, Soligo D, Pierotti MA, Greaves MF: Cd34 expression is regulated reciprocally with adhesion molecules in vascular endothelial cells in vitro. Blood 1993;81:1001-1008.

Reviewer #1 (Public Review):

The authors seek to quantify SARS-CoV-2 viral kinetics and address the question of whether this varies with variant, vaccination status, previous exposure, symptom status or age. The results are supported by two independent analyses. A first analysis based on a logistic regression that models the probability of having a cycle threshold (Ct) value <= 30 on each day post-detection. A second analysis that uses a semi-mechanistic model that describes viral proliferation and clearance (using Ct value as a proxy) with a 2-piece linear function.

The authors find small, but clear differences in SARS-CoV-2 clearance times related to several factors. They show that for Omicron infections, boosted individuals have longer clearance times than non-boosted individuals. When further stratifying by pre-booster antibody titer, they found that boosted individuals with low antibody titers had a slowest clearance, and non-boosted individuals with high antibody titers had a quickest clearance. These results are slightly confounded by age, given that boosted individuals were generally older than non-boosted ones, and younger Omicron-infected individuals had higher antibody titers than older Omicron-infected individuals, but the trends were consistent in the sensitivity and subgroup analysis. Overall, the conclusions are supported by the data analysis.

Given the changing epidemiology of SARS-CoV-2, it is important to continue to estimate viral kinetics and clearance times to adapt isolation policies accordingly. I agree with the claim of the authors that these results may support a change from time-based policies of isolation to test-based ones.

The strengths of the manuscript are the quality of the data, with a high sampling frequency, the choice of the statistical models, and the sensitivity analysis conducted. An inevitable weakness is that the population is not representative of the whole population (acknowledged in the manuscript). In this regard, a bit more information about the population of the study in the introduction would be appreciated.

I very much liked the results for the viral kinetics model. The viral kinetics model allows to differentiate the duration of the two phases (proliferation and clearance) as well as the peak viral RNA, thus giving a more precise picture of the attributes of the viral trajectory that vary as a function of different factors. I found the procedure and the results for this model easier to interpret than the results from the logistic regression.

Reviewer #2 (Public Review):

This manuscript provides a detailed and useful account of post-infection viral trajectories during the early SARS-CoV-2 Omicron era. Data in these analyses come from a unique cohort individuals from the National Basketball Association including players who, while they may not be representative of the general population, were sampled densely throughout the pandemic. The authors describe the duration of (presumptive) infectiousness, using CT values as a proxy, and explore how time to non-infectiousness differs by immune history and demographics. The authors used logistic regression models to estimate the probability of having a Ct value < 30 by day since detection and various other factors including lineage, age, post-primary vaccination antibody levels and exposure history. They then used previously published semi-mechanistic models to post infection kinetics, allowing for variability in kinetics by similar factors.

The authors make several important observations:

1. That most people continue to have a Ct value < 30 on the 5th day post detection. While not a novel observation, even for Omicron infections, it further adds to the importance of isolation strategies that include a testing component.

2. That rebounds do happen but even with relaxed definitions it is usually less than 1% (as high as perhaps 3%). If these are indeed in individuals that did not take anti-virals, these data are important for quantifying changes in the risk of rebound infections after antiviral treatment.

3. That boosted individuals were less likely to have an Omicron infection but among those that were infected, they were more likely to have a longer period with an elevated viral load. While this may be partly due to an age effect (and other factors), the authors suggest that even after controlling for age, this difference persists. Through looking at post-primary vaccination antibody levels (to the prototypical SARS-CoV-2) in a subset of the cohort, the authors show that this booster effect may be due to the fact that breakthrough infections in boosted individuals tended to occur in those who had a lower initial antibody response.

The authors do a great job of trying to disentangle lineage, age and exposure history, in primary and sensitivity analyses but there is no way to do this perfectly. I believe the conclusions are well justified by the results of the analyses and the authors sufficiently discuss the limitations of the data and results.

Reviewer #1 (Public Review):

The authors studied the dynamics of dynamic multicellular response and the cell-cell interaction networks after PNS injury. This is the first longitudinal study that has been carried out in such detail. It also includes a comparative analysis between circulating immune cells in peripheral blood, and in the injured nerve. They performed a follow-up using flow cytometry, ELISA, in situ hybridization, and immunofluorescence labeling of nerve sections. In addition, they compared the role of Wallerian degeneration in this process by using the Sarm1-/- mutant mice. The authors show how immune cells get metabolically reprogrammed after nerve injury, how the distal and proximal compartments react differentially, and how the cell interactions change during injury and resolution. The authors show great biological knowledge in the analyses of their data. This is a great resource for scientists working on the PNS or regeneration in general. To facilitate excess to their data the authors provided a web tool.

Reviewer #2 (Public Review):

In this manuscript, Zhou et al carried out a very thorough spatial and temporal transcriptomic analysis of various cellular responses in the injured sciatic nerve using single-cell RNAseq. As such, it provides a wealth of new information on how cells in the nerve respond to a crush injury, both at the injury site and distally, during the first-week post-crush. The data are technically sound and the authors validated many of the observed expression changes in specific cells using a variety of approaches such as FACS, RNAscope, and immunostaining. They also created a searchable, publicly available tool, iSNAT, that allows the exploration of changes in gene expression in the injured nerve, which will be very valuable for the research community. The authors focus particularly on immune cells in the nerve and reveal a number of interesting findings. For example, they demonstrate that monocytes and macrophages are recruited to the nerve and undergo reprogramming, initially to pro-inflammatory cells relying on glycolysis, then to inflammation-resolving cells that rely on oxidative phosphorylation. In addition, they use sarm1-/- mice, which have very delayed Wallerian degeneration, to demonstrate that independent of Wallerian degeneration, immune cells are recruited to the injury site, but minimally in the distal region. However, they find an increase in monocytes distally, suggesting that these cells fail to differentiate into macrophages in the absence of WD.

Overall, this is a very comprehensive analysis that provides a very useful resource for the field and reveals a number of interesting new insights into the immune response in the injured peripheral nerve. These results have important implications for understanding nerve regeneration and neuropathic pain.

As with any such study, the results are limited by the number of cells that can be analyzed and the number of sequencing reads. The authors were able to obtain a large number of most cells for analysis; however, the number of myelinating Schwann cells was fairly small, due to the need to remove myelin debris. A similar limitation has been encountered by others and does limit the ability to deeply investigate changes in Schwann cells after injury. This is particularly relevant because, as the authors bring up in their discussion, there is considerable evidence indicating that Schwann cells are involved in recruiting immune cells to the injured nerve. Thus, it was somewhat surprising that some of the signaling detected in Fig. 5 was not from Schwann cells, but this may be due to these cells being underrepresented. The authors should consider specifically examining changes in the Schwann cell profiles to determine if there is an increase in the expression of any of the known chemokines.

Among the interesting findings that came out of their analysis was an increase in monocytes in the distal nerve of the sarm1-/- mice, suggesting that these cells are recruited prior to Wallerian degeneration (WD) but in the absence of WD, they fail to differentiate into macrophages. This finding indicates that some aspect of WD promotes the differentiation of these cells. However, the authors should confirm the increase in monocytes prior to WD in the wild-type nerve, for example at 1-day post crush. This could be done by immunostaining or FACS.

The metabolic reprogramming observed after the injury, to a more glycolytic phenotype, is consistent with what has been observed by others for macrophages that are pro-inflammatory. However, the metabolic changes were only noted in the whole nerve at 3 dpc (Fig. 3). The authors should similarly comment on, and provide evidence for, the metabolic phenotype of the macrophages specifically in the distal nerve (Fig. 8). Are these initially pro-inflammatory and then inflammation resolving or are they always largely anti-inflammatory?

Reviewer 3 (Public Review):

The authors are to be commended on their clear presentation of the animals and time points (in table 1), their validation with ELISA, and the insightful follow-up experiments and validation. This is an important study that will be of broad interest to the field.

However, there are key issues that must be addressed, mostly relating to a lack of basic explorative analyses on the core scRNAseq datasets found in the paper.

Reviewer #1 (Public Review):

In this paper, the authors first examined how the spontaneous bursts of activity in the optic tectum of zebrafish arise from the excitatory and inhibitory connectivity patterns between tectal neurons. Toward this goal, they recorded spontaneous activity patterns of tectal neurons using large-scale calcium imaging and fitted a simple model to the data to estimate parameters of hypothetical connectivities. They claim that a uniform distribution of fast, short-range excitatory connections and slow, long-range inhibitory connections across tectal populations are sufficient to replicate several aspects of spontaneous burst dynamics.

Based on this finding, the authors further examined the role of model-estimated network states in sensory perceptions and eye convergence behavior for prey capture. Their series of experiments show that the proposed slow, long-range inhibitory connections may underlie sensory habituations for spatially specific visual stimuli and resulting eye convergence behavior for prey capture. Their experiments also show that spontaneous dynamics drive spontaneous eye convergence behavior. Based on these results, the authors propose underlying mechanisms of spontaneous activity bursts in the optic tectum and their behavioral significance.

The major strength of the paper is that it found a critical role of inhibitory connectivities between tectal neurons in sensory adaptation and its behavioral consequences based on both statistical modeling and experiments. The model-driven estimation of neural connectivity is rigorous and will likely set the standard for future works in optic tectum research. The major weakness of the paper is its organization of messages in the abstract and the discussion. It would be challenging for readers to understand what is the main take-home message. There are also claims in the discussion that went beyond what their results can support and may result in unnecessary drawbacks from peers in the field. I advise the authors to revise these sections so that the reader can better understand the significance of the paper and how it contributes to the progress in the research field.

The authors' experiments and analyses convincingly support their main claims. Their findings will likely contribute to a better understanding of how excitatory and inhibitory connectivities develop in the optic tectum of zebrafish and how such connectivities play critical roles in sensory perception and behaviors.

This work sits on insights from the recent studies that described the emergence of spontaneous neural assemblies in the optic tectum and the visual habituation behavior of zebrafish. The optic tectum is one of the most studied regions in the zebrafish brain and is an excellent model for understanding these universal neural phenomena observed across animal taxa. I am convinced that the insights from this paper will further stimulate community efforts.

Reviewer #2 (Public Review):

Zylbertal and Bianco propose a new model of trial-to-trial neuronal variability that incorporates the spatial distance between neurons. The 7-parameter model is attractive because of its simplicity: A neuron's activity is a function of stimulus drive, neighboring neurons, and global inhibition. A neuroscientist studying almost any brain area in any model organism could make use of this model, provided that they have access to 1) simultaneously-recorded neurons and 2) the spatial locations of those neurons. I could foresee this model being the de-facto model to compare to all future models, as it is easy to code up and interpret. The paper explores the effectiveness of this distance model by modeling neural activity in the zebrafish optic tectum. They find that this distance-based model can capture 1) bursting found in spontaneous activity, 2) ongoing co-fluctuations during stimulus-evoked activity, and 3) adaptation effects during prey-catching behavior.

Strengths:

The main strength of the paper is the interpretability of the distance-based model. This model is agnostic to the brain area from which the population of neurons is recorded, making the model broadly applicable to many neuroscientists. I would certainly use this model for any baseline comparisons of trial-to-trial variability.

The model is assessed in three different contexts, including spontaneous activity and behavior. That the model provides some prediction in all three contexts is a strong indicator that this model will be useful in other contexts, including other model organisms. The model could reasonably be extended to other cognitive states (e.g., spatial attention) or accounting for other neuron properties (such as feature tuning, as mentioned in the manuscript).

The analyses and intuition to show how the distance-based model explains adaptation were insightful and concise.

Weaknesses:

Model evaluation and comparison: The paper does not fully evaluate the model or its assumptions; here, I note details in which evaluation is needed. A key assumption of the model - that correlations fall off in a gaussian manner (Fig. 1C-E - is not supported by Fig. 1C, which appears to have an exponential fall-off. Functions other than gaussian may provide better fits. Furthermore, it is not clear whether the r^2s in Fig. 1E are computed in a held-out manner (more details about what goes into computing r^2 are needed). Assessing the model based on peak location alone (Fig. 1E) is not sufficient, as other smooth monotonically-decreasing functions may perform similarly. Simulating from the model greatly improves the reader's understanding (Fig. 2D), but no explanation is given for why the simulations (Fig. 2D) have almost no background spikes and much fewer, non-co-occurring bursts than those of real data (Fig. 2E). A key assumption of the distance model (Fig. 2A) is that each neuron has the same gaussian fall-off (i.e., sigma_excitation and sigma_inhibition), but it is unclear if the data support this assumption. Although an excitatory and inhibitory gain is assumed (Fig. 2A), it is not clear from the data (Fig. 1C) that an inhibitory gain is needed (no negative correlations are observed in Fig. 1C-D). After optimization (Fig. 3), the model is evaluated on predicting burst properties but not evaluated on predicting held-out responses (R^2s or likelihoods), and no other model (e.g., fitting a GLM or a model with only an excitatory gain) is considered. In particular, one may consider a model in which "assemblies" do exist - does such an assembly model lead to better held-out prediction performance? It is unclear why a genetic algorithm (Fig. 1A-C) is necessary versus a grid search; it appears that solutions in Generation 2 (Fig. 3C, leftmost plot, points close to the origin) are as good as solutions in Generation 30 and that the spreads of points across generations do not shrink (as one would expect from better mutations). Given the small number of parameters (7), a grid search is reasonable, computationally tractable, and easier to understand for all readers (Fig. 3A). It is unclear why the excitatory and inhibitory gains of the temporal profiles (Fig. 3I) appear to be gaussian but are formulated as exponential (formula for I_ij^X in Methods). Overall, comparing this model to other possible (similar) models and reporting held-out prediction performance will support the claim that the distance model is a good explanation for trial-to-trial variability.

Data results: Data results were clear and straightforward. However, the explanation was not given for certain results. For example, the relationship between pre-stimulus linear drive and delta R was weak; the examples in Fig. 4C do not appear to be representative of the other sessions. The example sessions in Fig. 4C have R^2=0.17 and 0.19, the two outliers in the R^2 histogram (Fig. 4D). The black trace in Fig. 4D has large variations (e.g., a linear drive of 25 and 30 have a change in delta R of ~0.1 - greater than the overall change of the dashed line at both ends, ~0.08) but the SEMs are very tight. This suggests that either this last fluctuation is real and a major effect of the data (although not present in Fig. 4C) or the SEM is not conservative enough. No null distribution or statistics were computed on the R^2 distribution (Fig. 4C, blue distribution) to confirm the R^2s are statistically significant and not due to random fluctuations. The absence of any background activity in Fig. 6B (e.g., during the rest blocks) is confusing, given that in spontaneous activity many bursts and background activity are present (Fig. 2E). Finally, it appears that the anterior optic tectum contributes to convergent saccades (CS) (Fig. 7E) but no post-saccadic activity is shown to assess how activity changes after the saccade (e.g., plotting activity from 0 to 60). No explanation is given why activity drops ~30 seconds before a convergent saccade (Fig. 7E). No statistical test is performed on the R^2 distribution (Fig. 7H) to confirm the R^2s (with a mean close to R^2=0.01) are meaningful and not due to random fluctuations.

Presentation: A disjointed part of the paper is that for the first part (Figs. 1-3), the focus is on capturing burst activity, but for the second part (Figs. 4-7), the focus is on trial-to-trial variability with no mention of bursts. It is unclear how the reader should relate the two and if bursts serve a purpose for stimulus-evoked activity.

Citations: The manuscript may cite other relevant studies in electrophysiology that have investigated noise correlations, such as:<br /> - Luczak et al., Neuron 2009 (comparing spontaneous and evoked activity).<br /> - Cohen and Kohn, Nat Neuro 2011 (review on noise correlations).<br /> - Smith and Kohn, JNeurosci 2008 (looking at correlations over distance).<br /> - Lin et al., Neuron 2015 (modeling shared variability).<br /> - Goris et al., Nat Neuro 2014 (check out Fig. 4).<br /> - Umakantha et al., Neuron 2021 (links noise correlation and dim reduction; includes other recent references to noise correlations).

Reviewer #1 (Public Review):

This manuscript by McCafferty et al. presents the integrative computational structural modelling of the IFT-A complex, which is important to proper cilium organelle formation in eukaryotic cells. Recent advances in protein structure prediction (AlphaFold) allowed the authors to model the structures of the 6 individual subunits of the IFT-A complex. Interactions between IFT-A proteins were experimentally investigated by purifying Tetrahymena cilia, isolating IFT complexes, and utilizing chemical crosslinking and mass spectrometry (MS). In addition, the authors present a somewhat improved 23Å cryo-electron tomography (cryo-ET) map of the IFT-A complex (previously determined cryo-ET structures of IFT trains have resolutions of 24-40Å). Integrative modelling using the predicted structures of the 6 IFT-A proteins and the experimental data as restraints allows the authors to present a structural model for the entire IFT-A complex. This model is analysed in the context of the polymeric IFT train structure, interactions with the IFT-B complex, and the structural position of ciliopathy disease variants.

This is in principle a timely and interesting study that attempts to push the limits of structural modelling of large protein complexes using structure prediction in combination with experimental data. Unfortunately, the study has several shortcomings and the data providing restraints for the integrative modelling are not optimal.

1) Chemical crosslinking and MS were used to obtain both intra-molecular crosslinks used to validate the structural models of the individual IFT-A proteins as well as inter-molecular crosslinks used as restraints in the structural modelling of the hexameric IFT-A complex. It is mentioned on p. 4, line 9, that IFT-A complexes were enriched from the flagellar lysate M+M fractions using SEC and that fractions from SEC containing IFT-A complexes were crosslinked for MS analysis. However, the authors do not show the data for this sample, neither SEC profiles, SDS-PAGE nor data of the cross-linked samples. On p. 7 the authors write that their SEC profile corresponds to monomeric IFT-A, but this is not shown anywhere in the manuscript. The reason this is so important is that the IFT-A complex assembles into linear polymeric structures together with the IFT-B complex as so-called IFT trains in cilia. Data obtained from isolated IFT trains would thus have additional crosslinks between subunits in neighbouring IFT-A complexes that, if used to restrain the position of subunits within a hexameric IFT-A complex, would likely result in a wrong architecture. The fact that the authors also observe crosslinks between IFT-A and IFT-B proteins strongly suggests that they indeed carried out the crosslinking experiment on polymeric rather than monomeric IFT complexes.

2) Given that the crosslink/MS data are unlikely to provide sufficient restraints for IFT-A structure assembly (and may even be misleading), the cryo-ET data become increasingly important. Unfortunately, the 23Å cryo-ET map does not provide sufficient detail to unambiguously fit domains of the IFT-A subunits as several of these have similar architectures consisting of WD-repeats followed by TPRs.

3) Two preprints of the IFT-A structure appeared over the last few weeks. Hesketh et al., (https://www.biorxiv.org/content/10.1101/2022.08.09.503213v1) have obtained a single particle cryo-EM structure of the human IFT-A complex at 3.5Å resolution for the IFT121/122/139 part of the complex providing amino acids side-chain information. In addition, Lacey et al. (https://www.biorxiv.org/content/10.1101/2022.08.01.502329v1) provide a 10-18Å resolution cryo-ET structure of the Chlamydomonas IFT trains containing both IFT-A and IFT-B. It is noteworthy that the model outlined in the current manuscript is very different from the IFT-A models of Hesketh et al., and Lacey et al. (the Lacey et al. manuscript by the way shares an author with the McCafferty et al., manuscript). In both Hesketh et al., and Lacey et al. the IFT121 and IFT122 subunits interact via the N-terminal WD-repeats and the C-terminal TPRs with the beta-propellers (WD-repeats) positioned parallel and in close contact. In the model proposed by McCafferty, the beta-propellers of IFT121 and IFT122 are positioned far away from each other (>50Å) and are perpendicular to each other. Several other large discrepancies are found in the relative positions of IFT-A subunits. This suggests serious problems with the structural model of IFT-A proposed by McCafferty and needs to be addressed with great care.

4) The authors observe crosslinks between the IFT-A proteins (IFT122 and IFT140) and IFT-B proteins (IFT70, IFT88, and IFT172) as discussed on pg. 6 and shown in figure 5A. To accommodate these crosslinks into the structural model of the IFT train shown in Figure 5A, the authors place the IFT-B subunits IFT70 and IFT88 far apart in the IFT-B complex. However, these subunits are known to interact directly (Taschner et al. JCB 2014) and indeed sit in proximity to the IFT train structure as observed by Lacey et al. While the crosslinking data may well be correct, the incorrect structural model of IFT-A likely forces an incorrect positioning of IFT-B proteins to fulfill the crosslinking data.

Reviewer #2 (Public Review):

The authors use XL-MS and AlphaFold to predict the structure and interactions of the six individual IFT-A proteins of Tetrahymena. As this data set still allows for numerous possible 3D structures of the hexameric complex, the authors fitted their models to the low-resolution 3D structure of the IFT-A densities of Chlamydomonas IFT trains in situ obtain by cryo-EM and image averaging. While not optimal, this cross-species approach is possible as IFT proteins are highly conserved and the identified crosslinks fit the Tetrahymena and Chlamydomonas AlphaFold structures almost equally well. The result is a best-fitting model, which was further "validated" by accounting for previously established interactions between IFT-A proteins (and IFT-A to -B interactions). The manuscript also provides a scholarly comparison of the IFT-A particle and protein structure with other cellular protein of similar domain structure and observe that many such proteins participate in intracellular transport.

The structure of the IFT-A complex presented here is modeled rather than based on direct imaging. In as much, this is probably an intermediate step. However, because the fine structure of the IFT-A particle remains unknown, this indirect approach appears useful and appropriate. The model presented here fits the available data and likely can be tested further in future experiments. Probably, the approach could be also used to predict the structure of other multiprotein complexes. The work elegantly demonstrates how the structures of single proteins provided by AlphaFold can drive structure predictions of protein complexes.

Reviewer #1 (Public Review):

It is a very interesting study that provides a clear and sophisticated description of the dynamic changes that take place at a calvaria defect site in terms of blood vessels, osteoblastic cells, and gradient of O2. It uses cutting-edge techniques. It is likely to become a critical reference for the scientific community.

It is a descriptive paper, but the data are solid.

Reviewer #2 (Public Review):

This study was built on the authors' previous publications to visualize angiogenesis and osteogenesis processes at subcritical-sized mouse calvarial defects using multiphoton microscopy. This provides, for the first time, the visible imaging of bone healing and vascularization within the defect after different time points of injury, although the physiological progression of calvarial bone healing was already known. More interestingly, the study used microscopy to visualize the oxygen distribution and energy metabolism within the defects at different time points during the process of bone healing. This allows one to understand the pathophysiological progressions of bone diseases and regeneration. It will also provide critical information to optimize the therapeutic bone healing and regeneration approach for different clinical situations.

Reviewer #3 (Public Review):

In this manuscript, authors present very exciting findings on the cranial bone defect repair using cutting-edge multiphoton imaging to study the role of different vessel subtypes and related oxygen and metabolic microenvironments. The authors used transgenic reporter mouse models to label and track blood vessel subtypes at the site of repair. They demonstrate the role of capillary subtypes at the repair sites in skull bone and provide evidence for the existence of specialized metabolic environments for coupling angiogenesis and osteogenesis. The study provides important insights into the dynamics and role of blood vessel subtypes in cranial bone defect repair.

Reviewer #1 (Public Review):

In this paper by Moller et al. the authors investigate the basic cell biological processes by which microglia phagocytose apoptotic neurons. This is an important concept to investigate because it is well known that neural debris is produced and that microglia clear it, but little is known about how molecular mechanisms of how microglia phagocytose that debris. These authors utilize the strength of the zebrafish system to identify the microtubule dynamics are critical during a specific type of microglia phagocytosis. Then, the paper describes the molecular components that contribute to this microtubule-mediated process. The paper is excellent, with exceptional imaging and molecular manipulations that support an overall mechanistic pathway. It will be an important contribution to the microglia field and cited in future studies that investigate microglia efferocytosis.

Reviewer #2 (Public Review):

Möller and colleagues describe a crucial role for the centrosome in tissue resident macrophages in the brain, termed microglia, in limiting the rate of efferocytosis. They undertake a live cell imaging approach in zebrafish to demonstrate that microglia remove dying neurons mainly by extending long cellular branches - a process, which depends on an intact microtubule cytoskeleton. They further establish a relationship between centrosome movement into microglial branches and successful neuronal engulfment. Artificial doubling of centrosome numbers led to enhanced engulfment and simultaneous removal of two cells, while cells with only one centrosome preferentially phagocytose one neuron at a time. Thus, they propose that centrosome polarization is a critical parameter in regulating the rate of microglial efferocytosis.

This is a very interesting manuscript. The conclusions of the work are well supported by the data. The imaging is beautiful.

Reviewer #3 (Public Review):

In this manuscript Moller et al., perform a lovely characterization of how centrosome movements synchronize with phagocytic cup formation during microglial efferocytosis of neuronal corpses in the larval zebrafish. Using a combination of elegant imaging and reporters tools the authors characterize two modes of phagosome formation, one involving process formation. They describe movements of the actin cytoskeleton, microtubules, and the centrosome in this process, and find that targeted migration of the centrosome into one branch is predictive of 'successful' engulfment, and increasing the number of centrosomes increases microglial engulfment capacity, suggesting it is a rate limiting factor. Finally, they use pharmacology to link this to DAG signaling. Although as the authors note, this process has been previously linked to phagocytosis in other cell types and the molecular regulators are well known, the beautiful imaging and the focus on microglia makes this a welcome addition to the field. I have no major concerns.

Reviewer #1 (Public Review):

The manuscript by Himmel et al is an interesting study representing a topic of substantial interest to the somatosensory neurobiology community. Here, the authors use CIII peripheral neurons to investigate polymodality of sensory neurons. From vertebrates to invertebrates, this is a long-standing question in the field: how is it that the same class of sensory neurons that express receptors for myriad sensory modalities encode different behavioral responses. This system in Drosophila seems to be an intriguing system to study this question, making use of the genetic toolkit in the fly and ease of behavioral assays. In this study, the authors identify a number of channels that are important for cold nociception, and they showed that some of these do not appear to also encode mechanosensation. Despite my initial enthusiasm for this paper, halfway through, it felt as if I were reading two different papers that were loosely tied together. This lack of cohesion significantly reduced my enthusiasm for this work. Below are some of my criticisms:

1. The first half of the paper is about a role for Anoctamins in cold nociception, but the second half switched somewhat abruptly to ncc69 and kcc. I assumed the authors would connect these genes in a genetic pathway, performing some kind of epistatic genetic interaction studies or even biochemical assays, and that this was the reason to switch the focus of the paper midway through. But this was not the case. Moreover, they performed a different constellation of experiments for the genes in the first half vs the second half of the paper (eg. Showed a role in cold nociception vs mechanosensation or showing phenotype from overexpression). This lack of cohesion made it difficult to follow the work.

2. In Fig1B,C how does one confirm a CIII neuron is being analyzed. It might help the reader if there were at least some zoomed out photos where all the cell types are labeled and potentially compared to a schematic. Moreover, is there a CIII specific marker to use to co-stain for confirmation of neuron type?

3. As this paper is predicated on detecting differences by behavioral phenotype, the scoring analysis is not as robust as it could be, especially considering the wealth of tools in Drosophila for mapping behaviors. The "CT" phenotype is begging for a richer behavioral quantification. This critique becomes relevant here when considering the optogenetic induced CT behavior in Fig5. If the authors were to use unbiased quantitative metrics to measure behavior, they could show how similar the opto behavior is to the natural cold evoked behavior. Perhaps the two are not the same, although loosely fitting under the umbrella of "CT".

4. Following on from the last comment, the touch assays in Fig3 have a different measurement system from the other figures. Perhaps touch deficits would be identified with richer behavioral quantification. Moreover, do these RNAi larvae show any responses to noxious mechanical stimulation?

Reviewer #2 (Public Review):

Himmel and colleagues study how individual sensory neurons can be tuned to detect noxious vs. gentle touch stimuli. Functional studies of Drosophila class III dendritic arborization neurons characterized roles in gentle touch and identified a receptor, NompC, and other factors that mediate these responses. Subsequent work primarily from the authors of the current study focused on roles for the same sensory neurons in cold nociception. The two proposed sensory inputs lead to quite distinct sets of behaviors, with touch leading to halting, head turning and reverse peristalsis, and noxious cold leading to whole body contraction. How activity of one type of sensory neuron could lead to such different responses remains an outstanding question, both at the levels of reception and circuitry.

The cIII responses to noxious cold and innocuous touch raises questions that the authors address here, proposing that studies of this system could advance the understanding of chronic neuropathic pain. A candidate approach inspired by studies in vertebrate nociceptors led the authors to study anoctamin/TMEM16 channels subdued, and CG15270, termed wwk by the authors. The authors focus on a pathway for gentle touch vs. cold nociception discrimination through anoctamins. Several of the experiments in this manuscript are well done, in particular, the electrophysiological recordings provide a substantial advance. However, the genetic and expression analysis has several gaps and should be strengthened. The data also do not provide strong support for some key aspects of the proposed model, namely the importance of relative levels of Cl co-transporters.

Major comments:

1) Knockout studies are accomplished using two MiMIC insertions whose effects on subdued or CG15270/wwk are not characterized by the authors. This needs to be established. The MiMIC system is also not well explained in the text for readers.

2) Subdued expression is inferred by a Gal4 enhancer trap. This can be a hazardous way of determining expression patterns given the uncertain relevance of the local enhancers driving the expression. According to microarray analysis subdued is strongly expressed in cIII neurons, but c240-Gal4 is barely present compared to nearby neurons, raising questions about whether this line reflects the expression pattern, including levels, even though the authors suggest that the line is previously validated (line 95; it is unclear what previously validated means). Figure 1B should not be labeled "subdued > GFP" since it is not clear that this is the case. Another more direct method of assessing expression in cIII is necessary. Confidence is higher for wwk using a T2A-Gal4 line, however, Figure 1C might be misleading to readers and indicate that wwk-T2A-Gal4 is cIII specific whereas in supplemental data the authors show how it is much more broadly expressed. The expression pattern in the supplemental figures should be moved to the main figures.

3) In figure 8 the authors propose a model in which the relative levels of K-Cl cotransporters Kcc (outward) and Ncc69 (inward) in cIII neurons determine high intracellular Cl- levels and a Cl- dependent depolarizing current in cIII neurons. They test this model using overexpression and loss of function data, but the results do not support their model since for most of the overexpression and LOF of kcc and ncc69 do not significantly affect cold nociception, the exception being ncc69 RNAi. The authors suggest that this could be due to Cl homeostasis regulated by other cotransporters. Nonetheless, it leaves a significant unexplained gap in the model that needs to be addressed.

4) Related to the #3, the authors should verify the microarray data that form the basis for their differential expression model.

Reviewer #3 (Public Review):

1. The described studies seek to test a plausible hypothesis having important biological implications: that Ca2+ coming through TRP channels and/or from intracellular stores during cold stimulation activates anoctamin Cl- channels, which further depolarize the CIII neuron via inward Cl- current (outward Cl- diffusion) resulting from high intracellular Cl- concentration caused by high expression of the outwardly directed Cl- transporter ncc69, thereby driving the intense electrical activity in CIII neurons needed to trigger cold-specific behavioral responses.

2. Elegant phylogenetic analysis is provided to show that Drosophila subdued and white walker are orthologous to human TMEM16/anoctamins ANO1/2 and ANO8, respectively, to go along with ncc69 already known to be orthologous to human NKCC1.

3. Strong genetic and behavioral evidence shows that knocking down the expression of subdued or white walker globally or selectively in CIII neurons reduces the incidence and magnitude of a cold-specific contraction response ("CT") to 5 degree C stimulation but not responses to gentle touch.

4. These knock-downs also reduce electrical activity recorded in cell bodies of CIII neurons induced by cooling to 15 or 10 degrees C in a semi-intact ("fillet") preparation.

5. CIII-specific knock-down of ncc69 reduces CT responses while overexpression of kcc (which should have the opposite effect on intracellular Cl- concentration) also tends to reduce these responses, indicating that the balance of Cl- pump activity in these neurons favors excitation when Cl- channels are opened (e.g., during cold stimulation).

6. Optogenetic activation of an exogenously expressed Cl- channel (Aurora) in CIII neurons evokes CT responses, showing that Cl- currents are sufficient to produce these responses, presumably by strongly activating the CIII neurons.

7. Reducing extracellular Cl- enhances ongoing electrical activity of CIII neurons, strengthening the conclusion that opening Cl- channels excites these neurons.

8. Overexpressing ncc69 in CIII neurons enhances basal and evoked electrical activity, and sensitizes larvae CT responses to cooling to 10 degrees C, further strengthening the conclusion that opening Cl- channels excites CIII neurons and suggesting that this specific genetic manipulation could provide a model in Drosophila for detailed investigations into a potentially general mechanism contributing to neuropathic sensitization and pain.

9. The authors integrate findings from the present study with those from their recent cold acclimation paper to make the speculative but interesting suggestion that mechanisms selected during evolution to enable cold acclimation might also be recruited in neuropathic contexts to produce maladaptive sensitization.

There are also several modest weaknesses in the paper:

1. A notable gap remains in the evidence for the hypothesized mechanisms that enhance electrical activity during cold stimulation and the proposed role of anoctamins (Fig. 8) - the lack of evidence for Ca2+-dependent activation of Cl- current. The recording methods used in the fillet preparation should enable direct tests of this important part of the model.

2. The behavioral and electrophysiological consequences of knocking down either of the two anoctamins are incomplete (Fig.2), raising the significant question of whether combined knock-down of both anoctamins in the CIII neurons would largely eliminate the cold-specific responses.

3. Blind procedures were not used to minimize unconscious bias in the analyses of video-recorded behavior, although some of the analyses were partially automated.

4. The term "hypersensitization" is confusing. Pain physiologists typically use "sensitization" when behavioral or neural responses are increased from normal. In the case of increased neuronal sensitivity, if the mechanism involves an increase in responsiveness to depolarizing inputs or an increased probability of spontaneous discharge, the term "hyperexcitability" is appropriate. Hypersensitization connotes an extreme sensitization state compared to a known normal sensitization state (which already signifies increased sensitivity). In contrast, the effects of ncc69 overexpression in this manuscript are best described simply as sensitization (increased reflexive and neuronal sensitivity to cooling) and hyperexcitability (expressed as increased spontaneous activity at room temperature).

Reviewer #1 (Public Review):

This study characterizes interesting behavioral differences between the pest Drosophila Suzuki, and the well-studied fruit fly Drosophila melanogaster. D. Suzuki display a weaker preference for sugar-rich foods, and also prefer harder food substrates. The manuscript then investigates changes in electrophysiological responses to sugars, finding that some but not all sweet-sensing sensilla are lost. The authors also show reduced expression of several sweet-sensing gustatory receptors and increased expression of several mechanoreceptors in D. Suzuki. Additional studies are needed to determine whether physiological and molecular changes account for observed behavioral changes.

Reviewer #2 (Public Review):

Drosophila suzukii prefers to lay eggs on ripe, intact fruit, which contrasts with Drosophila melanogaster, which lays eggs primarily on overripe fruit. The goal of the work by Wang et al. is to decipher the basis for this difference. Part of the explanation is that D. suzukii have a lower preference for sugars, compared to D. melanogaster. Based on electrophysiological recordings, the lower sugar preference in D. suzukii could be due in part to reduced sugar responsiveness of their gustatory receptor neurons in the labella.

The authors then performed transcriptome analyses to analyze the differential expression genes in the tarsi and labella of D. melanogaster and D. suzukii. They found that multiple sugar Grs were reduced in expression in D. suzukii, potentially accounting for the lower sugar responsiveness of D. suzukii.

Ripe fruit is harder than overripe fruit. Therefore, the authors considered whether the differential preferences for D. suzukii and D. melanogaster to lay eggs on ripe and overripe food respectively might be due in part to distinct biases for substrates of different hardness. Indeed, D. suzukii and D. melanogaster preferred harder and softer food, respectively. Moreover, several mechanosensory genes, most notably nompC, were expressed at higher levels in D. suzukii.

The authors also examined combinations of different concentrations of sugars and different levels of food hardness. The results support the conclusion that both food hardness and sugar levels contribute to the distinct preferences for oviposition sites for D. suzukii and D. melanogaster.

This work does an excellent job of employing a diverse combination of approaches (behavioral, electrophysiological and transcriptomics) to interrogate the basis for the differences in oviposition preferences in the two Drosophila species. Moreover, this study raises many new questions concerning the mechanisms contributing to the distinct preferences for ripe and overripe fruit exhibited by D. suzukii and D. melanogaster.

Reviewer #3 (Public Review):

This paper focuses on characterizing differences between D. suzukii and D. melanogaster preferences for laying eggs on substrates of varying sugar content and stiffness. The authors demonstrate that D. suzukii show a weaker preference for multiple sugars in oviposition choice assays, that D. suzukii show a loss of sugar responsiveness in some labellar sensilla, and that some GR-encoding genes are expressed at much lower levels compared to. D. melanogaster in the legs and labellum. Intriguingly, a number of mechanosensory channel genes are upregulated In D. suzukii legs and labellum. The authors show that D. suzukii females prefer stiffer oviposition substrates compared to D. melanogaster and the balance of sweetness/texture preference differs between the two species. This is consistent with their ecological niches, with D. suzukii generally preferring to lay eggs in ripe fruit and D. melanogaster generally preferring overripe fruit.

This paper builds on previous work from this group (Dweck et al., 2021) and others (Karageorgi et al., 2017 and others) that previously demonstrated that D. suzukii prefer to lay eggs on stiffer substrates compared to D. melanogaster, will tolerate more bitter substrates and show reduced expression of several bitter GR genes. This manuscript appropriately acknowledges this work and the findings are consistent with these studies.

The manuscript is well-written, the experiments are well-controlled, the figures clearly convey the experimental findings, the data support the authors conclusions, and the statistical analysis is appropriate.

The weakest point of the paper is the lack of connection drawn between the sequencing, electrophysiological, and behavioral data. For example, the electrophysiological responses to glucose appear to be the same in both species in Figure 3 but the behavioral responses in Figure 2 are different between the two species. The authors do not provide any speculation as to what could account for this seeming discrepancy. Additionally, although Gr64d transcript is almost completely absent in D. suzukii leg RNA seq data in Figure 4B, there are no differences in the electrophysiological responses in leg sensilla in Figure 3. This seems to imply that, although there are differences gene expression of some Grs that this does not necessarily lead to a functional difference.

The authors identify mechanosensory genes that are upregulated in D. suzukii compared to D. melanogaster and suggest that these changes underlie the difference in substrate stiffness. However, it is not immediately clear that high levels of these mechanosensors would impart a new oviposition preference. Although the authors acknowledge that there are likely circuit-level differences between the two species, they do not directly test the role of any of these mechanosensors in oviposition preference in either species.

In Figure 3 there are clear differences in some of labellar responses but the leg responses look similar overall. This suggests that the labellum is playing a special role in oviposition evaluation. The paper would be strengthened by providing more insight into which tissues (labellum, legs, wings, ovipositor, etc...) are likely used to sample potential egg laying substrates.

Reviewer #1 (Public Review):

The goal of this study was to investigate the mechanisms that lead to the release of photosynthetically fixed carbon from symbiotic dinoflagellate alga to their coral host. The experimental approach involved culturing free-living Brevolium sp dinoflagellates under "Normal" and "Low pH" conditions (respective target pH of 7.8 and 5.50) and measuring the following parameters: (Fig.1) cell growth rate over ~28 days, photosynthetic activity, glucose and galactose secretion at day 1; (Fig. 2) Cell clustering, external morphology (using SEM), and internal morphology (using TEM) after 3 weeks; (Fig. 3) Transcriptomic analyses at days 0 and 1; and (Fig. 4) glucose and galactose concentration in Normal culturing medium after 24h incubation with a putative cellulase inhibitor (PSG).

The paper reports decreased growth at Low pH coupled with decreased photosynthetic rates and increased glucose and galactose release in 1-day Breviolum sp. cultures. At this same time point, genes related to cellulase were upregulated, and after 3 weeks morphological changes on the cell wall were reported. The addition of the cellulase inhibitor PSG to cells in pH 7.8 media decreased the release of glucose and galactose.

The paper concludes that acidic conditions mimicking those reported for the coral symbiosome -the intracellular organelle that hosts the symbiotic algae- upregulate algal cellulases, which in turn degrade the algal cell wall releasing glucose and galactose that can be used as a source of food by the coral host. However, there are some methodological issues that hamper the interpretation of results and conclusions.

Reviewer #2 (Public Review):

Ishii and colleagues investigated the process of monosaccharide release from algae in low-pH environmental conditions, mimicking the acidic lysosomal-like intracellular compartment where the algae reside symbiotically and transfer nutrients to their hosts, namely corals and other animals. Upon exposure of cultured algae to low pH, subsequent physiological changes as well as the increased presence of glucose and galactose were measured in the surrounding media. Concurrently, photosynthetic activity was decreased, and further experiments employing the photosynthetic inhibitor DCMU to cultures also replicated the increased monosaccharide release. Transcriptomic comparison of algae in low pH to controls showed differential expression in glycolytic pathways and, interestingly, a strong upregulation of signal-peptide-containing isoforms of cellulases. Finally, the elegant use of a cellulase inhibitor on the cultured algae revealed a decrease in monosaccharides in the media. This led the authors to propose a pathway of sugar release in which acidic conditions trigger a cellulase-driven cascade of cell wall degradation in the algae and their consequent release of monosaccharides. These results have interesting implications on the molecular mechanisms of coral-algae symbiosis, contributing to the understanding of how these important symbioses function on the cellular level.

Overall the conclusions of this manuscript are supported by the data presented, but clarification and elaboration are needed to fully justify the proposed mechanisms and better situate the results in a broader context of the field.

Reviewer #1 (Public Review):

Oberin, Petautschnig et. al investigated the developmental phenotypes that resulted from oocyte-specific loss of the EED (Embryonic Ectoderm Development) gene - a core component of the Polycomb repressive complex 2 (PRC2), which possess histone methyltransferase activity and catalyses trimethylation of histone H3 at lysine 27 (H3K27). The PRC2 complex plays essential roles in regulating chromatin structure, being an important regulator of cellular differentiation and development during embryogenesis. As novel findings, the authors find that PRC2-dependent programming in the oocyte, via loss of the core component EE2, causes placental hyperplasia and propose that the increase of placental transplacental flux of nutrients leads to fetal and postnatal overgrowth. At the mechanistic level, they show altered expression of genes previously implicated in placental hyperplasia phenotypes. They also establish interesting parallelism with the placental hyperplasia phenotype that is frequently observed in cloned mice.

Strengths:

The mouse breeding experiments are very well designed and are powerful to exclude potential confounding genetic effects on the developmental phenotypes that resulted from the loss of EED in oocytes. Another major strength is the developmental profiling across gestation, from pre-implantation to late gestation.

Weaknesses:

The evidence for 'oocyte' programming is restricted to phenotypic and gene expression analysis, without measurements of epigenetic dysregulation. It would be an added value if the authors could show evidence for altered H3K27me3 or DNA methylation in the placenta, for example.

The claim that placental hyperplasia drives offspring catch-up growth is not supported by current experimental data. The authors do not address if transplacental flux is increased in the hyperplastic placentae, measure amino acids and glucose in fetal/maternal plasma, or perform tetraploid rescue experiments to ascertain the contribution of the placenta to growth phenotypes. Furthermore, it is unclear, from the current data, if the surface area for nutrient transport is actually increased in the hyperplastic placenta and the extent to which other cell populations (i.e. spongiotrophoblasts) are affected in addition to glycogen cells. In addition, one of the supporting conclusions that the placenta is a key contributor to fetal overgrowth is based on a very crude measurement - placenta efficiency - which the authors claim is increased in the homozygous mutants compared to controls. After analysing the data carefully, I find evidence for decreased placental efficiency instead. I believe that the authors mistakenly present the data as placenta to fetal weight ratios, which led to the misinterpretation of the 'efficiency' concept.

The authors do not mention alternative explanations for the observed fetal catch-up and postnatal overgrowth. Why would oocyte epigenetic programming effects be restricted to the placenta, and not include fetal organs?

Reviewer #2 (Public Review):

Consistent fetal growth trajectories are vital for survival and later life health. The authors utilise an elegant and novel animal model to tease apart the role of Eed protein in the female germline from the role of somatic Eed. The authors were able to experimentally attribute placental overgrowth - particularly of the endocrine region of the placenta - to the function of Eed protein in the oocyte. Loss of Eed protein in the oocyte was also associated with dynamic changes in fetal growth and prolonged gestation. It was not determined whether the reported catch-up growth apparent on the day of birth was due to enhanced fetal growth very late in gestation, a longer gestational time ie the P0 pups are effectively one day "older" compared to the controls, or the pups catching up after birth when consuming maternal milk.

Reviewer #3 (Public Review):

My understanding of the main claims of the paper, and how they are justified by the data are discussed below:<br /> Overall, loss of PRC2 function in the developing oocyte and early embryo causes:

1) Growth restriction from at least the blastocyst stage with low cell counts and midgestational developmental delay.

Strengths:

• Live embryo imaging added an important dimension to this study. The authors were able to confirm an unquantified finding from a previous lab (reduced time to 2-cell stage in oocyte-deletion Eed offspring, Inoue 2018, PMID: 30463900) as well as identify developmental delay and mortality at the blastocyst-hatching transition.<br /> • For the weight and morphological analysis the authors are careful to provide isogenic controls for most of the experiments presented. This means that any phenotypes can be attributed to the oocyte genotype rather than any confounding effects of maternal or paternal genotype.<br /> • Overall, there is good evidence that oocyte deletion of Eed results in early embryonic growth restriction, consistent with previous observations (Inoue 2018, PMID: 30463900).

Weaknesses:

Gaps in the reporting of specific features of the methodology make it difficult to interpret/understand some of the results.

2) Placental hyperplasia with disproportionate overgrowth of the junctional trophoblast especially the glycogen trophoblast (GlyT) cells.

Strengths:

• The authors provide a comprehensive description of how placental and embryo weight is affected by the oocyte-Eed deletion through mid-to-late gestation development. The case for placentomegaly is clear.<br /> Weaknesses:<br /> • The placental efficiency data presented in Figure 3G-I is incorrect. Placental efficiency is calculated as embryo mass/placental mass, and it increases over the late gestation period. For e14.5 for example (Fig3G), WT-wt embryo mass = ~0.3g, placenta mass = 0.11g (from Fig 3D) = placental efficiency 2.7; HET-hom = 0.25/0.12 = 2.1. The paper gives values: WT-wt 0.5, HET-hom 0.7. Have the authors perhaps divided placenta weight by embryo mass? This would explain why the E17.5 efficiencies are so low (WT-wt 0.11 rather than a more usual figure of 8.88. If this is the case then the authors' conclusion that placental efficiency is improved by oocyte deletion of Eed is wrong - in fact, placental efficiency is severely compromised.<br /> • The authors have performed cell type counting on histological sections obtained from placentas to discover which cells are contributing to the placentomegaly. This data is presented as %cell type area in the main figure, though the untransformed cross-sectional area for each cell type is shown in the supplementary data. This presentation of the data, as well as the description of it, is misleading because, while it emphasises the proportional increase in the endocrine compartment of the placenta it downplays the fact that the exchange area of the mutant placentas is vastly expanded. This is important for two reasons. Firstly, the whole placenta is increased in size suggesting that the mechanism is not placental lineage-specific and instead acting on the whole organ. Secondly in relation to embryonic growth, generally speaking, genetic manipulations that modify labyrinthine volume tend to have a positive correlation with fetal mass whereas the relationship between junctional zone volume and embryonic mass is more complex (discussed in Watson PMID: 15888575, for example). The authors should reconsider how they present this data in light of the previous point.<br /> • Again, some of the methods are not clearly reported making interpretation difficult - especially how they have estimated their GlyT number.

3) Perinatal embryonic/pup overgrowth.

Strengths:

• The overgrowth exhibited by the oocyte-Eed-deleted pups is striking and confirms the previous work by this group (Prokopuk, 2018). This is an important finding, especially in the context of understanding how PRC2-group gene mutations in humans cause overgrowth syndromes. It is also intriguing because it indicates that genetic/environmental insults in the mother that affect her gamete development can have long-term consequences on offspring physiology.

Weaknesses:

• Is the overgrowth intrauterine or is it caused by the increase in gestation length? The way the data is reported makes it impossible to work this out. The authors show that gestation time is consistently lengthened for mothers incubating oocyte-Eed-deleted pups by 1-2 days. In the supplementary material, the mutant embryos are not larger than WT at e19.5, the usual day of birth. Postnatal data is presented as day post-parturition. It would probably be clearer to present the embryonic and postnatal data as days post coitum. In this way, it will be obvious in which period the growth enhancement is taking place. This is information really important to determine whether the increased growth of the mutants is due to a direct effect of the intrauterine environment, or perhaps a more persistent hormonal change in the mother that can continue to promote growth beyond the gestation period.

4) "fetal growth restriction followed by placental hyperplasia, .. drives catch-up growth that ultimately results in perinatal offspring overgrowth".

Here the authors try to link their observations, suggesting that i) the increased perinatal growth rate is a consequence of placentomegaly, and ii) the placentomegaly/increased fetal growth is an adaptive consequence of the early growth restriction. This is an interesting idea and suggests that there is a degree of developmental plasticity that is operating to repair the early consequences of transient loss of Eed function.

Strengths:

• Discrepancies between earlier studies are reconciled. Here the authors show that in oocyte-Eed-deleted embryos growth is initially restricted and then the growth rate increases in late gestation with increased perinatal mass.

Weaknesses:

• Regarding the dependence of fetal growth increase on placental size increase, this link is far from clear since placental efficiency is in fact decreased in the mutants (see above).<br /> • "Catch-up growth" suggests that a higher growth rate is driven by an earlier growth restriction in order to restore homeostasis. There is no direct evidence for such a mechanism here. The loss of Eed expression in the oocyte and early embryo could have an independent impact on more than one phase of development. Firstly, there is growth restriction in the early phase of cell divisions. Potentially this could be due to depression of genes that restrain cell division on autosomes, or suppression of X-linked gene expression (as has been previously reported, Inoue, 2018 PMID: 30463900). The placentomegaly is explained by the misregulation of non-canonically imprinted genes, as the authors report (and in agreement with other studies, e.g. Inoue, 2020. PMID: 32358519).<br /> • Explaining the perinatal phase of growth enhancement is more difficult. I think it is unlikely to be due to placentomegaly. Multiple studies have shown that placentomegaly following somatic cell nuclear transfer (SCNT) is caused by non-canonically imprinted genes, and can be rescued by reducing their expression dosage. However, SCNT causes placentomegaly with normal or reduced embryonic mass (for example -Xie 2022, PMID: 35196486), not growth enhancement. Moreover, since (to my knowledge) single loss of imprinting models of non-canonically imprinted genes do not exist, it is not possible to understand if their increased expression dosage can drive perinatal overgrowth, and if this is preceded by growth restriction and thus constitutes 'catch up growth'.

Reviewer #1 (Public Review):

This work addresses the mechanisms of transmembrane proteins TMEM87A and TMEM87B, which are thought to play a role in protein transport, but have been implicated in other processes as well, such as signaling and acting as mechanosensitive ion channels.

The authors have determined a cryo-EM structure of human TMEM87A, finding that the protein consists of a Golgi-dynamics (GOLD) domain, sitting on top of a membrane spanning seven-transmembrane helical domains. The GOLD domain possesses a large cavity which is open to solution and the membrane. A related structure has been found for a protein Wntless known to promote membrane transport and secretion of the Wnt signaling proteins, and are lipid-modified.

Based on this similarity, the authors propose TMEM87A and other GOLD domain proteins are involved in transport of other membrane-associated proteins, such as ghrelin and several cytokines. This is in contrast to the proposed roles of TMEM87 as a signaling or ion channel molecule. The authors report on no evidence of channel activity in reconstituted liposomes carrying the TMEM 87 protein. However, no target molecule has been identified.

The work is based on a combination of Cryo-EM experiments and use of Alpha-fold-based prediction. It is competently done and the results are of interest to structural biologists. However, in the absence of a known target molecule of TMEM87A, a protein whose transport depends on TMEM87A, the results are of limited interest to a wider audience.

Reviewer #2 (Public Review):

In this report, Hoel and colleagues present evidence that the TMEM87 proteins are members of a larger family of GOLD domain seven-transmembrane helix proteins that consist of a 7 transmembrane helix containing membrane domain and an extracellular / luminal Golgi-dynamics (GOLD) domain. Combining AlphaFold2 modelling with a low-resolution (~4.7) cryo-EM map, the authors were able to build a model of human TMEM87A. Comparisons revealed that TMEM87A is most structurally related to Wntless, including a large membrane accessible cavity on the extracellular / luminal side of the 7 TM domain. A non-protein density was resolved in this cavity in TMEM87A that may correspond to a lipid molecule.

This study represents an important advance of the understanding of this poorly characterized family of proteins. While the structure is of low resolution, it is well interpreted, and authors take good advantage of AlphaFold2 to gain insights into potential function.

Reviewer #3 (Public Review):

In this well-written manuscript, Hoel et al., determine the 4.7 Å cryo-EM structure of TMEM87A - a protein of unknown function but proposed to have roles in protein transport to and from the Golgi, mechanosensitive ion channels, and in developmental signaling. The team perform an electrophysiological assay to demonstrate that under their experimental conditions the protein is not a mechanosensitive channel, and compare their structures to other structures and Alphafold models to place this protein in a newly defined protein family which they suggest may have roles in trafficking membrane-associated cargo.

Given that the only data provided in this manuscript (aside from a single electrophysiological assay) is a low resolution cryo-EM map this manuscript has really on reached the hypothesis generating stage. No experiments to demonstrate what the role of this protein is have been performed.

Reviewer #4 (Public Review):

This study revealed the structure of TMEM87A for the first time. Unexpectedly, the authors found that TMEM87A shared high structural similarity with WLS that mediates Wnt secretion and trafficking. Particularly, these two proteins share a similar extracellular GOLD domain and a large cavity that is accessible from both the extracellular side and the membrane. Through structural comparison, the authors have also identified a few other membrane proteins that share similar architecture with TMEM87A/WLS. These findings define a new membrane protein family that may play important roles in membrane-associated protein trafficking.

The authors also provided structural analyses and functional characterizations that suggest TMEM87A might function differently from GPCRs or ion channels. This proposal is reasonable. More experimental evidence is needed in either this study or future studies.

Overall, the findings from this study are highly interesting. This work provides a molecular framework for future elucidation of TMEM87A's functional roles and provides important and novel insights into this newly defined family of membrane proteins, and more broadly protein trafficking process.

Reviewer #1 (Public Review):

This paper described in considerable detail the extension of the FIB milling technique to incorporate an in-chamber fluorescent light microscope that is coincident with the FIB and SEM beams. Existing instruments either rely on an external FLM system (requiring a specimen transfer step that may result in additional contamination) or an integral FLM that required cumbersome and inaccurate movement of the stage inside the SEM chamber. Coincident beams would thus be very welcome to all practitioners of the challenging art of making cryo lamella. While not novel in concept the authors had to develop several innovations inside the chamber to make all this work.

Reviewer #2 (Public Review):

The authors report here on the development of an integrated, on-axis fluorescent module as an upgrade to existing FIB-SEMs. The optical axis of the new fluorescent module is designed to be coincident with both SEM and FIB beams, thus allowing imaging of the same spot of the specimen with three beams (i-beam, e-beam, and light beam), all within the chamber of a FIB-SEM and without any stage movement. The authors show a detailed design of the FLM module, together with the complete redesign of the specimen-holding stage. A new specimen stage is needed to accommodate the objective lens of the FLM that must be positioned within a few millimeters from the sample and would not fit into the already crowded upper part of most FIB-SEM chambers. In such a setup, the sample is observed from the top with i-beam and e-beam and with a light beam from underneath.

The design of the piezo positioning stage is well presented together with the results of the stage performance. It has very low repositioning error and resistance to mechanical vibrations. With five degrees of freedom, the sample at this stage can be accurately positioned for specific milling geometry. It is unclear what are the stage limits and if, for example, 90 degrees (orthogonal) FIB-milling is achievable with this stage.

The second part of the paper showcases two results utilizing the coincident beam setup for fluorescence-guided lamellae preparation. The authors describe the successful preparation of several lamellae while guided by the fluorescent signal from the area of thinning. Subsequent TEM data acquisition showed that a) the target of interest was present in the lamella after the final thinning; b) lamellae were sufficiently thin for tomographic data acquisition; c) ice remained vitreous and with minor contamination.

Advantages:<br /> In the described setup, all three beams inside the FIB-SEM chamber are coincident and can be centered on the same area of the specimen given the correct Z-height. This greatly simplifies and accelerates the acquisition of the fluorescent signal that is currently done in either a) an external fluorescent microscope, which involves additional time-consuming sample transfer steps prone to contamination; or b) integrated off-axis FLM, which involves large stage movements with limited precision. Additionally, since there is no need for stage movement, fluorescent data can be acquired without interrupting the milling process, enabling real-time monitoring of the presence of the fluorescent label. Reported Z-resolution for the light microscope module, coupled with the precision of the piezo stage enables accurate positioning of the sample for the targeted milling with 100 nm accuracy in Z using the specimen's fluorescent signal without the need for additional fiducials.<br /> The proposed setup comes as a complete solution: FLM module + custom cryo-cooled piezo stage + modified Quorum sample shuttle transfer + Odemis imaging software to control the microscope as well as all custom components. This setup has the potential to modernize older FIB-SEMs that don't have a cryo stage at all, lack integrated FLM, have stage issues, or run outdated software. However, it is unclear how compatible this system is FIB-SEM manufacturers other than TFS.

Limitations:<br /> The described stage is designed from the ground up to work with the standard TEM AutoGrids, thus limiting the type of the compatible sample to the prepared on-the-grid (i.e. plunge-frozen grids or grids prepared following the waffle method). It looks like the standard SEM stub cannot be used in this system, however, a 3 mm standard HPF type-B can potentially be accommodated (perhaps additional modification is needed). Even if 3 mm HPF hats can be used, positioning of the FLM objective below the specimen makes fluorescent imaging impossible, thus lift-out will rely on external fluorescence imaging.<br /> Another concern is the possibility of automated FIB-milling using Odemis software. Modern proprietary software, such as TFS AutoTEM, Zeiss' SmartFIB, or open-source Autoscript-based solutions such as SerialFIB, offer the GUI-based user-friendly automated milling setup suitable for unsupervised overnight lamellae preparation. It is unclear whether Odemis software would allow a similar level of automation.

Reviewer #1 (Public Review):

This paper has many strengths that support its conclusions. Specifically, the use of natively expressed Piezo1 engineered to carry the HA tag allowed the authors to explore the distribution of the protein from primary cells isolated from a mouse at native expression levels. Thus, over-expression effects could be avoided. The super-resolution imaging is nicely controlled and convicting in its analysis of the distribution of the channel in 3D. The supporting EM data also supports the findings from fluorescence. Likewise, the theory is convincing in proving a mechanistic reason why the channel distributes into this region of the cell. While the data are quite nice and well analyzed, the paper is lacking in an exploration of what function this distribution of the channel would provide to the cell. Likewise, if this distribution was disturbed, would the red blood cell's behavior change? For example, would calcium signals in response to an osmotic challenge or squeezing change if the channel was not concentrated in the dimple? As it stands now, the paper presents a structural view of the distribution of piezo1 in a primary cell plasma membrane but lacks direct experimental evidence for the mechanism of this concentration or mechanistic insight into the effects of this spatial distribution on red blood cell physiology.

Reviewer #2 (Public Review):

The manuscript by Vaisey et al investigates the organization of Piezo1 on the surface of mouse red blood cells. The authors found that Piezo1 prefers to distribute within the concave dimple as compared to the convex rim regions of the RBC. Additionally, Piezo1s form individual trimers that do not show an apparent tendency to cluster or interact with cytoskeletal components.

The manuscript addresses a timely topic regarding the mechanisms underlying the subcellular distribution of Piezo1, a major mammalian mechanosensitive ion channel. The findings regarding the behavior (curvature sensing, lack of clustering) of Piezo1 in live cells potentially have broad implications in biophysics, mechanobiology, and physiology. Overall, I found the manuscript well written. The experimental data collected with super-resolution microscopy and electron microscopy are compelling and of high quality. However, important details of the modeling aspects are unclear and several key control experiments are missing.

Reviewer #3 (Public Review):

Vaisey et al., 2022 utilize super-resolution and electron microscopy techniques to characterize the distribution of Piezo1 ion channels in red blood cells. Prior theoretical research has proposed that the highly curved Piezo1 conformation may bias the channel localization in cell membranes through a mechanism of curvature coupling (Haselwandter and Mackinnon, 2018). Vaisey et al., 2022 find that Piezo1 channels diffuse in the membrane, are not clustered and that their localization is biased to the highly curved RBC dimple, thus matching the hypothesis of curvature coupling. The findings in this paper advance our understanding of how Piezo1 channel conformation affects its localization. With some exceptions the experiments and analyses are performed carefully and rigorously, and the numbers of biological replicates are sufficient. I find this manuscript exciting.

Reviewer #1 (Public Review):

This manuscript by Borssato et al describes atomic-level structural details of the central core domain of nonstructural protein 1 (Nsp1) of SARS-CoV-2, the virus responsible for the ongoing COVID-19 pandemic. Authors combined X-ray crystallography, fragment screening, computational modeling, and molecular dynamics simulation approaches to characterize potentially druggable pockets in Nsp1 core (aa 10-126). This study presents several notable strengths. For example, authors screened and tested 60 fragments from the Maybridge Ro3 library and solved a co-crystal structure of Nsp1 core with one such fragment 2E10 (N-(2,3-dihydro-1H-inden-5-yl)acetamide) to 1.1Å resolution. The molecular dynamics simulation and other computational experiments were performed rigorously.

Nsp1 blocks the path of mRNA in ribosomes to modulate protein synthesis in the host cell. Nsp1 also binds the first stem-loop (SL1) of SARS-CoV-2 mRNA. The authors used a molecular docking program (HADDOCK) to build models of the Nsp1/RNA complex and predicted two modes of Nsp1 binding to SL1 RNA. A comparative structural analysis of Nsp1/2E10 experimental structure with Nsp1/SL1 (model) reveals that small molecule compounds occupying this site may block RNA binding of Nsp1. Given the established role of this interface in modulating the host and viral gene expression programs, this finding provides an important framework for designing the small molecules capable of completely blocking this interface.

A weakness of this study is the lack of experimental validation of the two modes of Nsp1 binding to SL1 RNA.

Reviewer #2 (Public Review):

In this manuscript, the authors have identified cryptic pockets in the Nsp1 protein of the SARS-CoV-2 virus. The authors used computational methods to identify these pockets and demonstrate drug binding via simulation studies. The authors also show that such cryptic pockets exist in other beta-coronaviruses as well.

The authors carried out fragment-based screening using macromolecular crystallography and confirmed the presence of drug bound in one of the pockets identified. However, the binding assays showed a weak binding with high error. Further, the authors perform Nsp1-mRNA simulation studies to identify how Nsp1 binds to the 5'UTR of SARS-CoV-2 mRNA and mention that targeting the identified pocket in Nsp1-N could disrupt the SARS-CoV-2 Nsp1-mRNA complex. However, there are conflicting reports on direct binding between the SARS-CoV-2 Nsp1-mRNA (See references 17 & 29).

Nsp1 helps establish viral infection in the host, and hence identifying the druggable site in this protein is important. Therefore, this study is important and exciting.

Reviewer #3 (Public Review):

In this manuscript, Borsatto et. al. have attempted to identify druggable cryptic pockets in the Non-structural protein 1 (Nsp1) of SARS-CoV-2. The authors analyzed analyzed molecular dynamics simulations of Non-structural protein 1 (Nsp1) of SARS-CoV-2 to search for potential drug binding pockets. The authors analyzed potential drug binding pocket volumes in unbiased simulations and utilized a Hamiltonian replica exchange scheme called SWISH to search for additional cryptic binding sites. The authors utilized conformations from their simulations to conduct a computational screen of potential drug fragments, and experimentally tested their predictions by soaking Nsp1 crystals with predicted fragment hits, and found that 1 of 60 predicted hits binds in a predicted pocket with mM binding affinity, and identified crystal packing contacts that may have prevented additional fragment hit binding. Finally, they ran simulations of Nsp1 in complex with RNA which suggest that ligand binding in pocket 1 may hinder RNA complex formation and run simulations of homologous Nsp1 in additional CoV genera to determine if the identified pockets are conserved.

The authors utilized two approaches for identifying potential drug binding pockets: unbiased MD simulations and the SWISH hamiltonian replica exchange that scales water protein interactions to explore the opening of more hydrophobic binding cavities, which can be stabilized by cosolvent benzene molecules. The authors identify 2 potential pockets (pockets 1 and 2) from unbiased simulations, and identify an additional 2-pockets (pockets 3 and 4) from SWISH simulations. Pockets 2-4 are connected by a shallow groove identified on the x-ray structure, but are substantially deeper than this groove. The authors proceed to use the FTDyn and FTMap programs to search for potential fragment binding spots, and identified that pocket 1 contained the largest number binding hotspots (~50%), and that many predicted binding hotspots were found in the cryptic pockets discovered by SWISH.

The authors proceeded to test their predictions by soaking 60 fragment hits obtained by FTMap and FTDyn, identified a single fragment that binds in Fragment 1, and solved the X-ray structure of this bound fragment. They also utilized microscale thermophoresis and thermal shift assays to measure a Kd value of 2.74 + 2.63mM. The authors then proceeded to analyze crystal packing contacts and identify packing contacts that may have prevented additional fragment hit binding. Finally, they ran simulations of Nsp1 in complex with RNA which suggest that ligand binding in pocket 1 may hinder RNA complex formation and run simulations of homologous Nsp1 in additional CoV genera to determine if the identified pockets are conserved.

The authors were successful in identifying an experimentally verifying a druggable pocket in Nsp1. It is unclear to me however, to what extent the features of the this pocket are cryptic, and if the fragment that was found to bind could have been discovered using only the crystal structure, as this ligand appears to bind to a cavity identified by the Fpocket software from a crystal structure. In a sense the authors have computationally identified and experimentally verified a druggable pocket, and have proposed the presence of 3 additional potentially druggable cryptic pockets with strong computational evidence, but have not experimentally verified the druggablity of the proposed cryptic pockets.

This manuscript represents an excellent demonstration of a state-of-the-art MD based computational methods for druggable pocket discovery on an important drug target. The experimental verification fragment binding to one of the identified sites, and the identification of putative additional sites, provide a foundation for future rational drug discovery campaigns of SARS-CoV-2 and other CoVs.

Reviewer #1 (Public Review):

The authors introduced a dual chemical-induced reversible gene knockout method (CIRKO) using a reportable and reversible conditional intronic cassette (ReCOIN). They could use Cre to delete genes, and another recombinase Flp to recover genes. This would provide a means to reversibly control gene expression rather than deletion. Another strength of this system is that GFP is built in to allow investigators to see if the gene is inactivated or activated, thus monitoring gene status by visible fluorescence. The authors have used this method mainly in pig gene manipulation. It would be great if this system could also be tested in mouse genes, as Cre-loxP system for gene deletion is mostly used in mouse. Thus demonstration of this method in mouse gene manipulation would broaden its future application. Overall, this work provides a flexible gene switch system for in vitro and in vivo gene function study.

Reviewer #2 (Public Review):

Shi et al present novel genetic tools to carry out conditional reversible genetics. These allow the Cre-dependent inactivation of a given gene of interest, together with reporter expression, and the posterior Flp-recombinase-dependent deletion of the ReCOIN cassette and reactivation of the full gene expression. The process is based on the alternative splicing of an exon containing the ReCOIN cassette in the default mode, followed by sequential recombination/reversion of this cassette by Cre, leading to the expression of a reporter in the cells having a gene deleted. Subsequently, Flp recombinase can be used to delete the ReCOIN cassette, restoring the wild-type gene. The strategy is largely based on the XTR system (Robles-Oteiza et al, 2015) but with the difference that it also allows the targeting of genes composed by a single exon (without introns), as the construct is not targeted to an intron but instead integrated into one of the first exons of the gene of interest.

The authors also design and generate a single genetic construct (CIRKO), that enables doxycycline-inducible expression of Cre and FlpOERT2, followed by tamoxifen activation of the latter. After doxycycline administration, inversion of the ReCOIN allele truncates the gene and fuses it with a reporter and a polyA cassette, and after tamoxifen induction of FlpOERT2, the ReCOIN cassette is deleted, thus restoring the wildtype gene.<br /> Although the authors provide convincing evidence of the sequential recombination process, several aspects of the data analysis need to be improved and controlled.<br /> 1) Authors did not evaluate whether the integration of the ReCOIN construct in the exon of the gene of interest affects the gene's endogenous expression levels. This needs to be carefully assessed as it may generate loss-of-function or hypomorphic alleles, even in the absence of any other manipulation. Data presented in Fig.1-Sup 5 shows that the Cherry levels are much lower in the unrecombined allele containing the ReCOIN than after full recombination and expression of the native wildtype allele, suggesting that the simple integration of the ReCOIN cassette may decrease gene expression.<br /> 2) One of the main problems of this and previous COIN or XTR systems is that the expression of the reporter after flipping the ReCOIN allele (to produce gene knockout) is often too weak because its expression is driven by the endogenous gene promoter and alternative splicing, which for most genes does not allow the clear separation between mutant (reporter+) and wildtype/reversed cells. Another caveat of this system is that wild-type and reversed (gene-reactivated) cells are indistinguishable.<br /> 3) Although the authors use cell lines to demonstrate the expression of the targeted gene of interest before and after each of the sequential recombination events of the allele by immunofluorescence, there is no quantitative data reflecting the efficiency and reliability of each event in the entire cell population. Data is mainly obtained from a few single cell-derived clones, rather than the entire population of transfected cells.<br /> 4) There is no data showing that their system works as predicted in vivo.

Reviewer #3 (Public Review):

In the research described in this manuscript, Shi and colleagues were attempting to develop a versatile and flexible method for generating conditional and reversible gene knockouts. They wanted their method to be widely applicable and easily adapted to any target gene of interest. In addition, they wanted to demonstrate the use of their new method in several different experimental contexts, reinforcing their conclusions about its value. In pursuit of these goals, the authors modified a method (COIN) in which an artificial intron containing a Cre-dependent gene-trap cassette is inserted into an exon of the target gene. In the modified ReCOIN method, the gene trap cassette is flanked by target sites of Flp recombinase. Cre recombination inverts the gene trap cassette, resulting in the disruption of the targeted gene. Subsequent Flp recombination deletes the gene trap cassette, restoring the expression of the targeted gene. The authors also devised a strategy (CIRKO) to permit rapid, non-invasive control of the ReCOIN system. In general, the authors have achieved their goals. The experiments in the manuscript are well-designed and clearly described, and they highlight the strengths of the strategy. However, a few limitations of the strategy and the experimental analyses are also clear:

1. The ReCoin module retains an antibiotic resistance cassette driven by the PGK promoter, which is a powerful ubiquitous promoter with bidirectional activity. In the original COIN module, the resistance cassette is deleted by Flp recombinase, but this is not possible in ReCOIN where Flp has been co-opted for gene regulation. In a variety of contexts, retained PGK-driven antibiotic cassettes have been shown to have unpredictable effects on the expression of surrounding genes. It would perhaps have been better if the ReCOIN module had been designed so that the resistance cassette was deleted by a third recombinase such as VCre or PhiC31. The possibility of ectopic gene expression or downregulation driven by the PGK promoter should be kept in mind when characterizing new ReCOIN alleles.

2. Somewhat related to point 1, the authors performed an experiment in transiently transfected cells to demonstrate that insertion of the ReCOIN module does not affect the expression levels of an mCherry reporter. However, the metric they reported, % mCherry+ cells, speaks more to transfection efficiency than expression levels. Mean fluorescence intensity might have been more informative.

3. In the section describing Cas9-ReCOIN, the authors mention the need to temporally control Cas9 expression, because persistent Cas9 expression can result in genomic instability. However, it is not clear that ReCOIN offers any advantage over the original COIN module in this context. In experiments where a Cas9 plasmid is transfected, Cre recombination allows the Cas9 to be switched off, but Flp recombination, turning Cas9 back on permanently, would seem to have no experimental value. Alternatively, in a cell line with Cas9 stably integrated into Rosa26 or a similar safe harbor locus, it would be desirable to have Cas9 temporarily turned on (Off-On-Off). Unfortunately, reCOIN seems to offer the ability to temporarily turn Cas9 off (On-Off-On).

4. Although live pigs containing a ReCOIN allele of TP53 were generated, experiments showing recombination of ReCOIN alleles were all performed in cultured cells or pre-implantation embryos. As yet, the ReCOIN/CIRKO strategy has not been fully validated in postnatal animals.

5. The CIRKO strategy allows rapid control of ReCOIN to turn gene expression off and on via dosing with doxycycline and tamoxifen. This non-invasive temporal control of gene expression has obvious value in both cultured cells and model organisms. However, as currently described CIRKO cannot be used for cell type-specific knockouts, because Cre and Flp expression is regulated by ubiquitous (though chemically inducible) promoters.

Reviewer #1 (Public Review):

This is a well-executed study using cutting-edge proteomics analysis to characterize muscle tissue from a genetically diverse mouse population. The use of only females in the study is a serious limitation that the authors acknowledge. The statistical methods, including protein quantification, QTL mapping, and trait correlation analysis are appropriate and include corrections for multiple testing. One concern is that missense variants, if they occur in peptides used to quantify proteins, could lead to false-positive signatures of low abundance (see lines 123-127). The experimental validation and deep dive into UFMylation provide some confidence in the reliability of other associations that can be mined from these data. The authors have provided a web-based tool for exploring the data.

Reviewer #2 (Public Review):

Molendijk et al. have performed muscle proteomics on a large population of genetically-variable mice - 161 mice from 73 different inbred strains out of the HMDP set, typically in duplicate but with a handful of strains with 3 or 4 biological replicates. Proteomics was run by TMT-based DDA, with around ~2000 proteins quantified in the entire cohort and an additional ~2000 quantified in at least 30% of the cohort. They have identified a few dozen of genes of interest that were detected through QTL mapping to be possibly associated with muscle phenotypes, of which a couple of dozen were designed to be targeted with AAVs and checked in vitro. Potentially two - and definitely one - of the knockdowns were successful in cell lines, and the successful one, on the gene UFC1, was tested in mice. The knockdown of UFC1 in mice had a very striking phenotypic effect on muscle function, providing new insight into the physiology and opening new avenues of research for how this mechanism may work.

Reviewer #1 (Public Review):

Overall, Long et al. very nicely show that the peel-1 locus gives a fitness benefit to strains independent of the zeel-1 gene. This famous TA element has been characterized solely for its role as a selfish genetic element, even though the original authors mused that it could have arisen because of a fitness benefit. This manuscript makes a valuable contribution by using both modeling and empirical results to show this point. The results have broad implications for the evolution of TA elements.

Reviewer #2 (Public Review):

In this manuscript, Long and colleagues explore a very fundamental question regarding the origin and evolution of selfish genetic elements. In particular, they focus their study on the paradoxical abundance of toxin-antidote elements in Caenorhabditis species that reproduce largely by selfing. As a model system, they study the C. elegans peel-1/zeel-1 locus, the first TA to be molecularly dissected in eukaryotes.

Major strengths

1. The manuscript is well-written and easy to follow.<br /> 2. It tackles a very interesting question. Toxin-antidote elements are made of two genes, one coding for a toxin and a second one for its cognate antidote. Although these selfish genes seem relatively simple, there are two paradoxes associated with their evolutionary inception. First, what function evolved first? How can a toxin evolve in the absence of an antidote? Why would an antidote evolve in the absence of a toxin? Second, how does gene drive evolve in selfing nematodes? Toxin-antidote elements thrive under conditions that maximize their dispersal, that is, outcrossing. So, why are toxin-antidote elements so common in nematodes that mainly reproduce by selfing? The main finding of Long and colleagues, namely, that the toxin peel-1 increases the fitness of selfing hermaphrodites, has the potential to change how we think about these ubiquitous selfish elements.

Major weaknesses

Although the results presented by the authors are interesting and suggestive, I find the evidence largely insufficient. In particular, a lack of appropriate controls in the following experiments.

1. The main claim of this paper boils down to a single experiment. Figure 3C and 3E. In particular the contrast between N2(marker) worms and N2 (peel-1 null; marker) strains. In essence, the authors show that peel-1 null worms lay 6% fewer embryos than WT and that they are outcompeted by N2 worms when co-cultured. However, I feel this is not properly controlled. Every time one generates a mutant worm by CRISPR (or other means) there is a chance that a secondary non-desired change is introduced. This could be due to the technique itself, for instance, CRISPR gRNA having an off-target or it could be derived from the transgenesis procedure itself. That is, the bottleneck effect associated with injecting worms and picking single progeny to establish mutant lines that could fix random mutations. Since these effects are to some degree unavoidable, careful controls must be provided. First and foremost is the generation of independent alleles. As far as I could tell, the authors only mention and do experiments with a single peel-1 null mutant. There is also no mention of backcrossing strains to the parental strain in the methods section. This is particularly troubling because at the end of the day, the authors based the whole paper on a very modest effect on fitness. Now, such a modest effect, of course, would be sufficient for natural selection to act upon in the wild, but at the same time, it could be perfectly caused by off-targeting or genetic drift of random mutations in the background. If one were to take "N2" reference strains from different labs in the world, I'm pretty sure that we would see differences in fitness, most of them with a larger effect size.

In my opinion, a critical control missing in the study would be a "rescue" experiment by performing CRISPR editing on the peel-1 null mutant line and "fixing" the toxin allele. This should restore the phenotypes back to WT levels and would discard any secondary off-target effects. The authors could claim that the NIL experiment (Figure 2) strengthens their view because they see a similar effect as in the peel-1 null worm. However, as they also point out, these worms have >100kb introgression with multiple genes in there, thus any small effect on fitness could be perfectly due to linkage. For consistency, one would have expected also to make a peel-1 null allele in the NIL background, but that experiment was not provided either.

In summary, there are many trivial ways in which a mutant line will have a slight decrease in fitness and none of these are controlled in this manuscript. Moreover, decreasing fitness is trivial, but increasing it, is not.

2. The authors propose PEEL-1 increases the fitness of hermaphrodites by making them lay more eggs. Now, as far as we know, PEEL-1 is not expressed in the female gonad, only in sperm. Thus, one logical conclusion (or the only simple scenario I can think of) would be that PEEL-1 increases the total number of mature sperm in hermaphrodites. I think that further work characterizing this phenomenon would be fundamental to strengthen the claim made by the authors.

Reviewer #3 (Public Review):

This paper aimed to understand how toxin-antidote (TA) elements are spread and maintained in species, especially in species where outcrossing is infrequent and the selfish gene drive of TA elements is limited. The paper focuses on the possible fitness costs and benefits of the peel-1/zeel-1 element in the nematode C. elegans. A combination of mathematical modeling and experimental tests of fitness are presented. The authors make a surprising finding: the toxin gene peel-1 provides a fitness advantage to the host. This is a very interesting finding that challenges how we think about selfish genetic elements, demonstrating that they may not be wholly "selfish" in order to spread in a population.

Strengths<br /> 1. The authors support results found with a zeel-1 peel-1 introgressed strain by using CRISPR/Cas9 genetic engineering to precise knock-out the genes of interest. They were careful to ensure the loss-of-function of these generated alleles by using genetic crosses.

2. Similarly, the authors are careful with controls, ensuring that genetic markers used in the fitness assays did not affect the fitness of the strain. This ensures that the genes of interest are causative for any source of fitness differences between strains, therefore making the data reliable and easily interpretable.

3. A powerful assay for directly measuring the relative fitness of two strains is used.

4. The authors support relative fitness data with direct measurements of fitness proximal traits such as body size (a proxy for growth rate) and fecundity, providing further support for the conclusion that peel-1 increases fitness.

Weaknesses<br /> 1. One major conclusion is that peel-1 increases fitness independent of zeel-1, but this claim is not well supported by the data. The data presented show that the presence of zeel-1 does not provide a fitness benefit to a peel-1(null) worm. But the experiment does not test whether zeel-1 is required for the increased fitness conferred by the presence of peel-1. Ideally, one would test whether a zeel-1(null);peel-1(+) strain is as fit as a zeel-1(+);peel-1(+) strain, but this experiment may be infeasible since a zeel-1(null);peel-1(+) strain is inviable.

2. The CRISPR-generated peel-1 allele in the N2 background only accounts for 32% of the fitness difference of the introgressed strain. Thus, the effect of peel-1 alone on fitness appears to be rather small. Additionally, this effect of peel-1 shows only weak statistical significance (and see point 5 below). Given that this is the key experiment in the paper, the major conclusion of the paper that the presence of peel-1 provides a fitness benefit is supported only weakly. For example, it is possible that other mutations caused by off-target effects of CRISPR in this strain may contribute to its decreased fitness. It would be valuable to point out the caveats to this conclusion, or back it up more strongly with additional experiments such as rescuing the peel-1(null) fitness defect with a wild-type peel-1 allele or determining if the introduction of wild-type peel-1 into the introgressed strain is sufficient to confer a fitness benefit.

3. The strain that introgresses the zeel-1 peel-1 region from CB4856 into the N2 background was made by a different lab. Given that N2 strains from different labs can vary considerably, it is unclear whether this introgressed strain is indeed isogenic to the N2 strain it is competing against, or whether other background mutations outside the introgressed region may contribute to the observed fitness differences.

4. Though the CRISPR-generated null allele of peel-1 only accounts for 32% of the fitness difference of the zeel-1 peel-1 introgressed strain, these two strains have very similar fecundity and growth rates. Thus, it is unclear why this mutant does not more fully account for the fitness differences.

5. Improper statistical tests are used. All comparisons use a t-test, but this test is inappropriate when multiple comparisons are made. Importantly, correction for multiple comparisons may decrease the already weak statistical significance of the fitness costs of the peel-1 CRISPR allele (Fig 3E), which is the key result in the paper.

6. N2 fecundity and growth rate measurements from Fig 2B&C are reused in Fig 3C&D. This should be explicitly stated. It should also be stated whether all three strains (N2, the zeel-1 peel-1 introgressed strain, and the peel-1 CRISPR mutant) were assayed in parallel as they should be. If so, a statistical test that corrects for multiple comparisons should also be used.

7. It appears that the same data for the controls for the fitness experiments (i.e. N2 vs. marker & N2 vs. introgressed npr-1; glb-5) may be reused in Fig 2A and 3E. If so, this should be stated. It should also be stated whether all the experiments in these panels were performed in parallel. If so, this may affect the statistical significance when correcting for multiple comparisons.

Reviewer #4 (Public Review):

In "A Toxin-Antidote Selfish Element Increases Fitness of its Host", Long et al. attempt to address an outstanding question in the evolution of toxin-antidote (TA) systems in primarily selfing species: How do TA systems escape drift and spread in a primarily selfing species? The authors use simulations to show that at outcrossing rates similar to that observed in C. elegans a TA element, like the peel-1/zeel-1 element, has a high probability of being lost to genetic drift. However, the authors show that the peel-1 gene provides a fitness advantage to strains harboring it, providing evidence for a dual role for this gene and insights into how this element might have escaped being lost to genetic drift.

Strengths:

The experiments in this paper are well-framed. The authors use simulations to show that the observed frequency of the peel-1/zeel-1 TA element in the C. elegans population is highly unlikely given the inferred outcrossing rates of species.

The authors clearly show that the 140-370kb CB4856 introgression into N2 lowers relative fitness, number of eggs laid, and animal size, relative to N2.

The authors generated null alleles of peel-1 and zeel-1 and showed that a truncated version of PEEL-1 confers a detrimental fitness effect when compared to N2. Furthermore, the authors show that the fitness effect associated with peel-1 is independent of the antidote (zeel-1) component of this TA element.

Weaknesses:

1) The reference N2 strain has been cultivated in the lab for decades and many different versions of this strain exist. The different versions of N2, which might have slightly different genomes, are likely to have different fitness in laboratory conditions. It is unclear whether the N2 strain used to construct QX1198 is the same N2 strain used to construct CX12311, PTM229, and PTM377 (and others derived from these). The potential difference in the N2 strain used for the construction of these strains might contribute to the large discrepancy between the relative fitness shown in Figure 2A (~0.25) and Figure 3E-F (~0.07). Alternatively, the other CB4856-specific variants present in the 140-370 kb introgression in the QX1198 strain might cause this large discrepancy.<br /> Regardless of the potential discrepancy among N2 strains used as the genetic background, the claim that the presence of peel-1 confers higher relative fitness is supported by Figure 3E because PTM377/409 were presumably derived from the same N2 strain.

2) For Figures 2B and 3C, the authors report the number of eggs laid per animal. C. elegans strains can lay embryos that do not hatch and therefore fail to develop into reproductive adults. Does the difference between N2 and N2(peel-1(0)) remain when considering the number of reproductively mature progeny? Presumably, eggs laid translate to reproductive adults because a relative fitness increase is observed when peel-1 is present.

3) The authors did not perform whole-genome sequencing of the peel-1 and zeel-1 CRISPR edited strains or mention any backcrossing done to eliminate potential off-target editing events. Therefore it is difficult to conclude whether off-target effects might influence the quantified traits presented in Figure 3. This concern is somewhat alleviated by the reciprocal competition assay presented in Figure 3E (4th boxplot), but a potential off-target editing event that lowers fitness could have segregated with the silent dpy-10 and peel-1 edits.<br /> The same concern is present with the zeel-1-independence experiment, however, this experiment does not have reciprocal competition experiments.

4) In Figure 3C-D, the authors show that a homozygous truncated version of PEEL-1 confers a reduction in eggs laid per animal (proxy for brood size) and animal length (proxy for developmental speed). However, the authors do not show whether a heterozygous truncated PEEL-1 strain (N2 peel-1/peel-1(kah126)) confers the same reduction in eggs laid or animal size. Would the allele frequency dynamics derived from the simulations be affected by a fitness advantage only being conferred by the presence of two copies of peel-1?

5) The authors show a fitness advantage associated with peel-1 in laboratory conditions. It is obviously extremely difficult to extend these observations to the wild, however, the authors do not take their observations that peel-1 confers a fitness advantage in the lab and apply their empirical observations to the simulation framework. If the laboratory fitness advantage of peel-1 did extend to the wild, one might expect the element would fix in the population in the simulation framework.

6) It seems possible that a truncated version of the PEEL-1 protein might have unknown deleterious fitness consequences that are independent of any beneficial effect the full-length protein might have. The same is true for the truncated ZEEL-1 protein, though potentially less concerning because there are only 5 amino acids.

Reviewer #1 (Public Review):

This work by Shen et al. demonstrates a single molecule imaging method that can track the motions of individual protein molecules in dilute and condensed phases of protein solutions in vitro. The authors applied the method to determine the precise locations of individual molecules in 2D condensates, which show heterogeneity inside condensates. Using the time-series data, they could obtain the displacement distributions in both phases, and by assuming a two-state model of trapped and mobile states for the condensed phase, they could extract diffusion behaviors of both states. This approach was then applied to 3D condensate systems, and it was shown that the estimates from the model (i.e., mobile fraction and diffusion coefficients) are useful to quantitatively compare the motions inside condensates. The data can also be used to reconstruct the FRAP curves, which experimentally quantify the mobility of the protein solution.

This work introduces an experimental method to track single molecules in a protein solution and analyzes the data based on a simple model. The simplicity of the model helps a clear understanding of the situation in a test tube, and I think that the model is quite useful in analyzing the condensate behaviors and it will benefit the field greatly. However, the manuscript in its current form fails to situate the work in the right context; many previous works are omitted in this manuscript, exaggerating the novelty of the work. Also, the two-state model is simple and useful, but I am concerned about the limits of the model. They extract the parameters from the experimental data by assuming the model. It is also likely that the molecules have a continuum between fully trapped and fully mobile states, and that this continuum model can also explain the experimental data well.

Reviewer #2 (Public Review):

In this paper, Shen and co-workers report the results of experiments using single particle tracking and FRAP combined with modeling and simulation to study the diffusion of molecules in the dense and dilute phases of various kinds of condensates, including those with strong specific interactions as well as weak specific interactions (IDR-driven). Their central finding is that molecules in the dense phase of condensates with strong specific interactions tend to switch between a confined state with low diffusivity and a mobile state with a diffusivity that is comparable to that of molecules in the dilute phase. In doing so, the study provides experimental evidence for the effect of molecular percolation in biomolecular condensates.

Overall, the experiments are remarkably sophisticated and carefully performed, and the work will certainly be a valuable contribution to the literature. The authors' inquiry into single particle diffusivity is useful for understanding the dynamics and exchange of molecules and how they change when the specific interaction is weak or strong. However, there are several concerns regarding the analysis and interpretation of the results that need to be addressed, and some control experiments that are needed for appropriate interpretation of the results, as detailed further below.

(1) The central finding that the molecules tend to experience transiently confined states in the condensed phase is remarkable and important. This finding is reminiscent of transient "caging"/"trapping" dynamics observed in diverse other crowded and confined systems. Given this, it is very surprising to see the authors interpret the single-molecule motion as being 'normal' diffusion (within the context of a two-state diffusion model), instead of analyzing their data within the context of continuous time random walks or anomalous diffusion, which is generally known to arise from transient trapping in crowded/confined systems. It is not clear that interpreting the results within the context of simple diffusion is appropriate, given their general finding of the two confined and mobile states. Such a process of transient trapping/confinement is known to lead to transient subdiffusion at short times and then diffusive behavior at sufficiently long times. There is a hint of this in the inset of Fig 3, but these data need to be shown on log-log axes to be clearly interpreted. I encourage the authors to think more carefully and critically about the nature of the diffusive model to be used to interpret their results.

Even in the context of the 'normal' two-state diffusion model they present, if they wish to stick with that-although it seems inappropriate to do so-can the authors provide some physical intuition for what exactly sets the diffusivities they extract from their data. (0.17 and 0.013 microns squared per second for the mobile and confined states). Can these be understood using e.g., the Stoke-Einstein or Ogston models somehow?

(2) Equation 1 (and hence equation 2) is concerning. Consider a limit when P_m=1, that is, in the condensed phase, there are no confined particles, then the model becomes a diffusion equation with spatially dependent diffusivity, \partial c /\partial t = \nabla * (D(x) \nabla c). The molecules' diffusivity D(x) is D_d in the dilute phase and D_m in the condensed phase. No matter what values D_d and D_m are, at equilibrium the concentration should always be uniform everywhere. According to Equation 1, the concentration ratio will be D_d/D_m, so if D_d/D_m \neq 1, a concentration gradient is generated spontaneously, which violates the second law of thermodynamics. Can the authors please justify the use of this equation?

Indeed, the derivation of Equation 1 appears to be concerning. The flux J is proportional to D * dc/dx (not k*D*c as in the manuscript). At equilibrium dc/dx = 0 on both sides and c is constant everywhere. Can the authors please comment?

So then another question is, why does the Monte Carlo simulation result agree with Equation 1? I suspect this has to do with the behavior of particles crossing the boundary. Consider another limit where D_m = 0, that is, particles freeze in the condensed phase. If once a particle enters the condensed phase, it cannot escape, then eventually all particles will end up in the condensed phase and EF=infty. The authors likely used this scheme. But as mentioned above this appears to violate the second law.

(3) Despite the above two major concerns described in (1) and (2), the enrichment due to the presence of a "confined state", is reasonable. The equilibrium between "confined" and "mobile" states is determined by its interaction with the other proteins and their ratio at equilibrium corresponds to the equilibrium constant. Therefore EF=1/P_m is reasonable and comes solely from thermodynamics. In fact, the equilibrium partition between the dilute and dense phases should solely be a thermodynamic property, and therefore one may expect that it should not have anything to do with diffusivity. Can the authors please comment on this alternative interpretation?

Reviewer #1 (Public Review):

Kidneys have very high energy needs and they preferentially use lipids as their energy source. Lipid metabolism however poorly understood in the kidney. Lipids accumulate in diseased kidneys, however the mechanism of lipid accumulation is not well understood. The team has studied lipid metabolism in the kidney.

1. The team has first performed some basic lipid accumulation studies in kidneys of healthy mice. Lipid uptake show very significant feeding and fasting differences. It is unclear what stage of the feeding cycle the experiments were performed and whether the team has standardized it.

2. All measurements have been performed using the colorimetric kit, the team should also use mass spec to validate results.

3. The team did not measure lipolysis, fatty acid oxidation or fatty acid synthesis so statements so statements made around these pathways appear to be only speculative. They could measure it or adjust the text.

4. Figure2 is probably the most valuable information in the paper. Lipid accumulation is only measured by staining. The team should also perform Plin stain or other methods to support their statement.

5. The apical vs basal lipid update also seems speculative. I am not sure that we could see these differences. In addition, no quantification is presented to support the findings.

6. For fatty acid uptake the team has analyzed the cd36 KO but not the fatp2 KO mice.

7. The team has analyzed a PT injury model but most proteinuria is the result of glomerular injury. Unclear whether the data is relevant for glomerular disease

8. The human urinary fatty acid quantification would need positive control samples. Clinically we often see lipid droplets in the urine, which is inconsistent with the presented data.

9. No clear conclusion can be drawn from the data

Overall while the project has some interesting elements and the presented data is relatively weak and no clear conclusion can be drawn and the overall message is unclear.

Reviewer #2 (Public Review):

Dr. Kawakami and colleagues investigate that FA is taken up via both apical and basolateral sides of tubular epithelial cells. CD36 is known to be expressed in tubular cells, so it is expected and well known that FA was taken up via CD36 at the basolateral side. However, FA is also taken up at the apical side (primary urinary side) independent of CD36 activity, and albumin reabsorption is an interesting new finding, although the specific mechanism involved in this process is not shown but discussed possible mechanism in a discussion section in the manuscript. Authors provide the evidence of CD36 expression in the basolateral side of tubules, TG contents in kidney tissue, and FA levels in serum and urine utilizing CD36KO mice, PTi (PT specific injury), and megalin KO mice to support the author's hypothesis.

Although it is an interesting study, this study is overall descriptive by performing staining and testing FA levels in serum or urine rather than conducting functional studies in tubule cells. Moreover, the authors exclude the possibility that TG content is associated with TG lipolysis. Cell stores uptake FA as TG in lipid droplets and lipase activity is required to use FA as their energy source especially in tubular cells that are known to use FA as their energy source. Thus, there is a high probability that the balance between FA uptake and TG lipolysis determines TG contents. To exclude the TG lipolysis and ensure the TG contents are highly and solely associated with serum FA, the author should provide lipase activity, level of lipolysis, and TG content in tubular cells in vitro.

Reviewer #3 (Public Review):

The authors of this study were trying to determine the mechanisms of of fatty acid uptake and accumulation in the kidney. Their work identified clear evidence for both basolateral (CD36-dependent) and apical uptake of fatty acids in the kidney. The apical uptake of fatty acids is independent of megalin. Interestingly there is absence of fatty acids in the urine even in subjects with significant proteinuria indicating that fatty acids in the urine are completely taken up by the renal tubules.

Reviewer #1 (Public Review):

Previous work, much of it by some of the authors, has characterized modification of various ion channels by SUMOYLation. However, there has been relatively little work exploring the effects of such modulation on function of neurons. This manuscript begins by showing quite large reciprocal effects of either enhancing or reducing SUMOYLation in layer 5 pyramidal neurons. One of the effects found is a leftward shift of the voltage-dependence of persistent sodium current. The authors then test the hypothesis that these changes result in part from SUMOYLation of Nav1.2 channels, and using a mouse engineered to eliminate Nav1.2 SUMOYLation, nicely show that modulation of Nav1.2 shifts the voltage-dependence of Nav1.2 and speeds back-propagation of action potentials from the AIS into the soma.

The results in the manuscript are interesting, important, and convincing. Besides being important for describing effects of SUMOYLation on overall neuronal function, the selectivity of SUMOYLation for modifying Nav1.2 but not Nav1.6 channels - and the observation of slowing of back-propagation but not forward propagation from the AIS - adds to the previous data on the distinct functional roles of Nav1.2 and Nav1.6 channels in the AIS.

It is puzzling that the authors focused so much on the effects of SUMOYLation on back-propagation and so little on the large effect on the frequency of firing, which seemed quite dramatic and potentially equally or more important for overall neuronal function than speeding back-propagation. In fact, after introducing the idea that the change in the f-I slope might reflect modulation of Na channels, there is little further discussion of the significance of the changes in firing frequency. Evidently, selective modulation of Nav1.2 channels but not Nav1.6 channels greatly affects firing. Is this explained only by the leftward shift of persistent sodium current from Nav1.2 channels? Or does the leftward shift of Nav1.2 channel gating affect spike threshold? Does modeling of selective modulation of Nav1.2 channels capture these changes in firing frequency and the slope of the f-I curve?

Reviewer #2 (Public Review):

In this work, Kotler et al. examine the consequences of SUMOylation in the regulation of cortical pyramidal neurons excitability. The authors take advantage of previous articles from their groups in which they have shown that ion channel activity is regulated by the SUMO pathway. Most of the experiments are whole-cell recordings including purified SUMO1 or SENP peptides in the pipette solution, in order to show the effects of SUMOylation and deSUMOylation, respectively. They study repetitive firing and passive membrane properties of cortical neurons, finding that SUMO1 increases the neuronal excitability and the neuronal gain. Interestingly, deSUMOylation with SENP1 dialysis produces opposite effects, indicating that an endogenous basal level of ion channel SUMOylation is present. Importantly, they generate (using CRISPR/Cas9 technology) a mouse model with a point mutation that renders Nav1.2 channels insensible to SUMOylation (Nav1.2-K38Q). In cortical neurons from this mouse model, SUMOylation affects mainly passive neuronal properties; so, modification of neuronal gain by SUMO1 seems to be mediated by changes in Nav1.2 activity. Next, they make use of voltage-clamp recordings and simultaneous fluorescence imaging of Na+ fluxes to assess changes in the persistent sodium current, one of the main factors that can modify neuronal gain. SUMOylation causes a leftward shift in the activation kinetics of INaP, and that change is not observed in Nav1.2-K38Q mice. Finally, the authors show that SUMOylation of Nav1.2 channels affects EPSPs and, of great relevance, the speed of back-propagating action potentials, without modifying the speed of forward-propagating action potentials.

Overall, the conclusions of this paper are mostly well supported by data, the manuscript is well-written, nicely organized, and breaks new ground in the role of SUMOylation modulating neuronal activity and action potential backpropagation, a key aspect for synaptic plasticity, and should be of broad interest.

However, some aspects need to be clarified.

1) The statistical analysis for the first two figures (lines 156 to 215 in the main text) seems to contain some errors, that could change the interpretation of the results. Or, by the contrary, there are some errors in the data provided (mean +/- S.E., number of replicates). Details on this subject are indicated in "recommendations for the authors". Figure 5b has not included statistical analysis. Mean values plus S.E. and "n" are not indicated in Figure 3 - Figure Supplement 1 and 2, and in Figure 4.

2) The authors mention that the recordings are done in L5 pyramidal neurons, but there are two main classes of these neurons: "thick-tufted" and "slender tufted". These two classes have different morphological and electrophysiological profiles. For example, spiking properties and input resistance can be quite different in both types, as showed by van Aerde & Feldmeyer, 2015 ("Morphological and Physiological Characterization of Pyramidal Neuron Subtypes in Rat Medial Prefrontal Cortex", Cerebral Cortex, 25:788-805). The number of neurons recorded for each condition is around 5-7 for most of the experiments in the article. This number should be increased to avoid bias that could provide differences between different treatments, if the neurons are chosen randomly and not selected by type. The values for input resistance, time constant, etc., should be comparable between conditions just after break-in (before SUMO1 or SENP1 dialysis, and similar to control internal solution). For example, in the case immediately after the break-in, the F-I curves showed in Figure 1 - Figure Supplement 1 should be similar for SUMO1, SENP1 and Control, but they are not.

3) The neurons in the mutant (Nav1.2-Lys38Gln mouse model) are provided with Nav1.2 channels that are constantly deSUMOylated. This condition could likely drive compensatory changes in the expression/activity of different ion channels in the neurons from mutant mice. A more complete characterization of neuronal properties from this mouse model, in control internal solution, should be desirable, and also a comparison with parameters obtained from wild type neurons with SENP1 internal solution (after dialysis).

Reviewer #3 (Public Review):

SUMOylation of sodium channels has been implicated as a substantial modulator of current properties. However, prior studies have been limited as they have not examined the impact of SUMOylation in developed neurons. Here the investigators made a mouse with the key SUMOylation site (K38) in Nav1.2 mutated to prevent SUMOylation (K38Q). They characterize modulation of cortical pyramidal neuron firing while manipulating SUMOylation using recombinant proteins in wild-type and SCN2A-K38Q mouse neurons. SUMOylation modulates sodium currents elicited with ramp depolarizations and alters back-propagation of action potentials and thus impacts excitatory post-synaptic potentials. The K38Q mutation prevents these effects on neuronal sodium currents. The work does indeed suggest that SUMOylation modulates specific ionic currents in neurons and that SUMOylation of Nav1.2 may play a role in synaptic integration.

While the work is interesting, it is limited in several aspects. First, previous studies have reported that SUMOylation modulates the voltage-dependence of Nav1.2 activation and steady-state inactivation. Perhaps because of the difficulties associated with voltage clamping neurons in slice, the current work focuses on ramp currents. While the study states that SUMOylation "exclusively controls InaP generation", this can be misleading as other sodium current properties were not examined in the neurons. Alterations in the voltage-dependence of activation could contribute to the observed changes in ramp currents which are characterized as persistent currents in this study. Second, the study does not examine the impact of the K38Q mutation on behavior. It will be very interesting to see how this mutation impacts learning and memory in the mice.

Reviewer #1 (Public Review):

Aguinagalde et al. investigated alternative treatment options for invasive pneumococcal diseases and considered the use of monoclonal antibodies to promote the killing of bacteria. For this to happen, complement deposition and activation are required to occur on the bacterial surface. The authors discovered that hexamerization of IgG strongly augments the recruitment of C1, and specific mutation of the antibodies can support this process and enable efficient phagocytosis and killing of bacteria by neutrophils. Further, sets of in vivo studies support the idea that passive immunization with these modified antibodies improves survival from pneumococcal pneumonia in mice.

Considering vaccine-escape serotypes, the (sometimes) suboptimal vaccine response together with the increased occurrence of strains resistant to antibiotics, the search for alternative treatments is highly warranted, and this study is an excellent example supporting the use of therapeutic antibodies targeting the capsule.

This study is generally very well performed and very well written. The authors conclusively show the importance of mAb hexamerization to augment complement deposition and activation on the surface of pneumococci, which promotes subsequent phagocytosis by neutrophils. Further experiments prove the importance of hexamerization of mAbs and the importance of this complement in the uptake of bacteria by neutrophils. Subsequent in vivo studies showed the therapeutic usefulness of modified antibodies in preventing mortality and bacteremia in female mice. All these data provide strong evidence for the claims of the authors.

I noticed 2 weaknesses, the first related to the killing assays: considering that WT IgG less efficiently promotes complement-mediated phagocytosis of bacteria, one would assume that the ingested bacteria (to be killed) would be lower in neutrophils exposed to this IgG, to begin with - which is not accounted for in the analyses shown.

A second weakness in my mind pertains to the in vivo experiment: the model used obviously requires a very high number of bacteria (the inoculum), somehow indicating that this specific bacterial strain does not lead to progressive infection (i.e. with replicating bacteria) but mice experience a severe acute inflammatory response followed by the rapid elimination of bacteria. This explains the high mortality - and indicates that mice succumb to acute inflammation, rather than the progressive replication of bacteria. To conclusively prove the therapeutic value of those modified antibodies, a clinically more relevant S. pneumoniae model would be helpful.

A third aspect, which should be addressed in the discussion, unless tested and not shown, is how anti-pneumococcal IgM antibodies compare to hexamerized IgGs. Is there any advantage, or do they perform similarly with regards to complement activation?

Reviewer #2 (Public Review):

In this clearly presented study, the authors are assessing the impact of introducing hexamerisation-associated mutations into human monoclonal antibodies that target the capsule of pneumococcus. The impact of these mutations is assessed in in vitro systems using human sera or neutrophils. The second series of studies use mouse models involving the adoptive transfer of antibody and the subsequent challenge of mice.

The major strengths of the study are that the authors are addressing an important area of unmet need, both in terms of alternative treatments for bacterial infections and also in how antibodies function against bacterial pathogens. This is a neglected area, particularly in the context of understanding how antibodies function after binding to bacterial capsules. The results are intriguing, and one consideration is whether enhancing complement activation is beneficial or harmful for a therapeutic antibody. Based on these results is there the possibility of a natural selection against strong levels of complement activation?

The study clearly shows that the introduction of the hexamerisation mutations affects the ability of the antibodies to bind and activate complement. The studies in Fig 2 examining the role of Fc are particularly elegant. One issue is that it is surprising that the WT IgG1 and IgG3 monoclonals have a minimal capacity to fix and activate complement, despite IgG1/3 to other antigens being efficient isotypes at fixing complement. In the absence of data showing whether IgG1/3 from normal human sera against capsule fixes complement then it is difficult to contextualise these results or to assess if other changes, such as in glycosylation, contribute to the results presented. Related to this, there is reasonable evidence that antibodies induced to capsules can be protective yet the data in Fig 5 suggests that without the mutations then the monoclonals are not effective at all for 6B and only effective at the highest concentration for 19A.

The adoptive transfer experiments demonstrate that the antibodies can moderate bacteraemia. The mechanism of this is not explored and the importance of hexamerisation and complement activation not demonstrated, especially as it is not clear if human antibodies and mouse complement are a productive combination in this context.

Reviewer #1 (Public Review):

Histone peptides have been the primary tools for identification and characterization of histone readers. However, in vivo the real substates of histone readers are nucleosomes, in which histone tails exist in dynamic equilibrium between free, accessible state and DNA-bound, inaccessible states. Therefore, other histone modifications, particularly acetylation, impact the accessibility of histone tails to reader proteins. Using modified nucleosomes and known H3K4me3-binding PHD fingers, the authors show that indeed acetylation on nucleosomes has more profound impact than on histone peptide in terms of binding affinity and specificity, likely through increasing H3K4me3 accessibility. The authors further extend the study to investigate the impact of nucleosomal acetylation on H3K4 methyltransferase MLL1C's activity on nucleosome. Surprisingly, MLL1C shows no or very low level of enzymatic activity toward the unacetylated nucleosome, whereas H3 tr-acetylation strongly enhances H3K4 methylation by MLL1C, likely through increasing the accessibility of H3 tail to the enzyme. Consistent with this in vitro data, MS analysis of MCF-7 cells shows that increasing histone acetylation by HDAC inhibitor increases the global levels of H3K4 methylation, particularly on the histone tails with higher levels of acetylation. Together, these findings suggest a model in which acetylation releases nucleosome-bound H3 tails to available H3K4 methyltransferases for subsequent methylation and provide a molecular basis for the long-standing connection between H3 acetylation and H3K4 methylation.

The effect of histone acetylation on histone tail accessibility to reader proteins have been previously reported by several groups, including studies from some of the authors of the current manuscript. The novelty of this study lies on the findings that tail accessibility also affects the enzymatic activity of H3K4 methyltransferases. However, additional evidence is needed to further strengthen the findings.

Reviewer #2 (Public Review):

In this manuscript, Jian et al. reported their biochemical study demonstrating that histone H3 lysine acetylation facilitates H3K4me3 binding by the PHD finger proteins on nucleosome as compared to peptides, and enhances H3K4 methylation by histone methyltransferase MLL1. Histone lysine acetylation and methylation are well known to play an important role in directing gene transcription in chromatin, but how they work in coordination is much less understood. Therefore, this study provides new insights into how histone H3 lysine acetylation promotes gene transcriptional activation through enhancing writing and reading of histone H3K4 methylation, which is recognized as a histone mark for transcriptional activation. While this is an interesting study, there are a number of questions that the authors should address as described below, which would confirm the functional importance and relevance of their results.

Specific Comments:

1. It has been reported that PHD fingers can bind to DNA in addition to lysine-methylated histone H3. Can the authors address whether or not the enhanced selectivity of PHD-nucleosome interactions over PHD-peptide interactions is due to PHD-DNA binding?

2. What's the binding affinities of PHD-nucleosome interactions and PHD-peptide interactions, respectively?

3. Histone H4K5acK8ac is a well-known site-specific histone acetylation mark for gene transcriptional activation, much more so than histone H3 acetylation. Does H4K5K8 acetylation enhance PHD-H4K3me3 binding in nucleosome?

4. The authors provided the data showing cis histone H3 tail lysine acetylation effects on PHD-H4K3me3 binding. What about trans histone H3 lysine acetylation effects?

Reviewer #1 (Public Review):

This manuscript investigates the role of dopamine (DA) release in the dorsal bed nucleus of the stria terminalis (dBNST) investigating sign and goal tracking behavior, response to systemic fentanyl, and to fentanyl self-administration. The studies are largely well conducted and interesting, and the conclusions are justified by the data. The behavioral experiments are elegant and well-conceived, and good thought has been put into how they fit with current theories of learning and reinforcement. As written, however, it is hard to know how much of this data is novel as compared to what is known about DA release in the nucleus accumbens (NAc) which partially comes from similar sources (ventral tegmental area/VTA) but the BNST also receives DA from divergent sources (periaquaductal gray/PAG). The anatomy of DA innervation in the BNST is somewhat distinct and it is doubtful that the optical fiber has the spatial resolution to distinguish between areas that are innervated more by the VTA, which seems more restricted to the juxtacapsular subnucleus, vs. the PAG which more broadly innervates the dlBNST and the oval subnucleus. Further, the release of DA by these two areas may be differentially governed and that is not considered.

Reviewer #2 (Public Review):

In addition to the nucleus accumbens, the bed nucleus stria terminalis (BNST; part of the extended amygdala) is also a recipient of dopamine release from VTA and other regions. While nucleus accumbens dopamine signaling has been heavily implicated in individual differences in the attribution of incentive salience towards a reward predictive cue and reward learning, it is still unclear whether dopamine signaling in extended amygdala is involved in this process.

Here, Gyawali et al. use GRABDA sensors to record dopamine signaling in the dorsal BNST (dBNST) during Pavlovian and instrumental cue-evoked reward tasks. During a Pavlovian lever autoshaping task, they observed individual differences in dopamine signaling in response to a reward CS, with sign-tracking rats showing heightened dopamine response compared to goal-tracking rats. dBNST dopamine signaling also bidirectionally encoded violations in reward prediction, as well as outcome-specific satiety. Finally, they show that fentanyl self-administration-associated cues also elevate dBNST dopamine signaling.

The manuscript is very well written, includes appropriate controls, use of statistical analyses, and conclusions were generally justified by their results. In some instances, larger group sizes would allow authors to more powerfully assert their claims. Although causal manipulations would further solidify the necessity of cue-evoked dopamine signaling in the BNST, these are a very interesting and thorough set of experiments that importantly highlight the role of endogenous dopamine dynamics in BNST in cue-related reward motivation. Not only are these findings important in defining a role for BNST in appetitive motivation (in addition to its more famous role in aversive motivation), but they are also likely to impact future important work that causally delineates sources of dopamine to BNST.

Reviewer #3 (Public Review):

Gyawali et al. make use of fiber photometry methods with a dopamine biosensor to monitor dopamine signaling in the BNST, where it has received much less attention compared to striatal regions. They use a Pavlovian conditioned approach paradigm to assess the encoding of associative learning, finding that, similar to the striatum, BNST dopamine responds to violations of expectation. Further, BNST dopamine responses to Pavlovian cues and outcomes vary according to individual differences in conditioned approach behaviors. In other studies, they demonstrate that BNST dopamine tracks sensory-specific satiety, and is amplified following fentanyl self-administration. Overall these are interesting and well done studies that make great use of new sensor technology. This work represents a foray into monitoring learning-related dopamine signals in non-striatal areas. A primary critique pertains to the analysis and interpretations of the reward prediction error manipulations, which I do not think bidirectional reward prediction error encoding is definitely demonstrated.

Reviewer #2 (Public Review):

The authors designed this study to identify the direct T3 target genes that underlie the T3 actions in the brown adipose tissue (BAT). The unique model used (dominant negative TRa knock-in and a TRb knock-out) allows for the isolation of BAT-specific actions from other well-known systemic effects on thermogenesis, including the central nervous system. The strengths of the study reside in the novel methodological approach. Previous studies of T3 actions in the BAT used animal models that did not allow for full isolation of BAT-specific effects of T3. A limitation however is the combination of TRa knock-in (which causes permanent suppression of TRa-dependent genes) with the TRb knockout, which only prevents T3 induction of TRb-dependent genes. Nonetheless, the results were impressive with the identification of about 1,500 genes differentially expressed in the BAT, among which UCP1 and PGC1a were the two main ones. Although it has been known that both UCP1 and PGC1a are downstream targets of T3, the work establishes through an ingenious approach the critical direct role played by T3 in BAT thermogenesis. In addition, the genetic approach utilized here is of great value and could be easily expanded to other tissues and systems.

Reviewer #1 (Public Review):

Yanis Zekri et al have addressed an important question of the possible role of thyroid hormone (T3) and its nuclear receptor (TR) on local BAT thermogenesis and energy expenditure. In this well-written manuscript and well-carried work, the authors address the above question by A) by generating the BATKO mice by selectively eliminating TR signaling in BAT by knocking-in a TRα1L400R, a dominant negative version of the TRa1 receptor, and by floxing the ThRb gene. They characterized this mouse thoroughly to show that they totally lacked T3 responsiveness. Using qPCR they evaluated the selective abrogation of Thrb and Hr expression in BAT tissue relative to other tissue sites. B) Using time-course transcriptome analysis they then go on to enlist all the T3/TR direct target genes using well-defined criteria and further linking with their ChipSeq data they identified 639 putative target genes which are under the direct control of T3/TR signaling. Interestingly their gene analysis lead them to some target genes directly involved with UCP1 and PGC1α in addition to genes of many other metabolic processes related to BAT thermogenesis. The experiments on denervated BAT on wild-type PTU-fed was a rather neat experiment to eliminate the influence of noradrenergic terminal BAT target genes. Furthermore, the cold exposure experiments and the high-fat diets feeding with the series of complex analyses led them to the conclusion that BAT KO animals suffered from reduced efficiency of BAT adaptive thermogenesis. By comparing the BAT transcriptome of BATKO and CTRL mice after 24h at 4{degree sign}C, the authors further go on to show how BAT TR signaling controls other subsets of genes, especially a wide variety of metabolic regulations, especially lipolysis/fatty acid oxidation. Finally, EdU injection experiments showed a direct effect of T3 on BAT proliferation.

I think it was well thought and well-designed study for understanding the complex action of cell-autonomous T3 regulation of adaptive thermogenesis. The conclusions of this paper are well supported by the data provided.

Reviewer #3 (Public Review):

This paper details the importance of thyroid hormone signaling in BAT in response to environmental and nutritional stress. The authors utilize a novel genetic model to specifically target BAT and impair thyroid hormone signaling. The physiologic insight is of great interest. The role of the sympathetic nervous system in the BAT response is not fully addressed but it appears that cell-autonomous signaling mediates TH signaling in response to hyperthyroidism. The link cistromically between the TR and PGC1 is also novel and of interest.

Reviewer #1 (Public Review):

This work addresses a long-standing question about how tolerance develops at the presynaptic level. That the number of receptors is unchanged following the treatment of animals with opioids was known since the early work using receptor binding assays. The conclusion was that receptor/effector coupling was disrupted was thought to be the primary mechanism underlying tolerance. This work indicates that the location of receptors is critically important in the development of tolerance. This work is groundbreaking and a game changer in the understanding of tolerance at the cellular level.

Reviewer #2 (Public Review):

Jullie et al addressed the long-standing question of how presynaptic desensitization of opioid receptor signaling can occur on the timescale of hours despite the fact that it does not occur on the timescale of minutes. They also compared the mu and delta opioid receptors in this context and asked whether their desensitization occurs in a homologous or heterologous manner when co-expressed in the same neurons.

A major strength of the work is the use of a relatively high-volume imaging assay of synaptic transmission based on VAMP2-SEP to detect exocytosis of synaptic vesicles and its modulation by heterologously expressed opioid receptors in cultured neurons. This allowed for large data sets to be acquired and analyzed with good statistical power. It also reports on a validated metric of synaptic transmission.

A significant weakness arises from the need to overexpress opioid receptors in cultured striatal neurons in order to conduct the experiments with high reliability. Because the authors did not attempt to address receptor expression levels and relate overexpression to endogenous receptor expression levels in axons, the physiological significance of the findings remains, to some extent, in doubt.

Using heterologously expressed receptors, the primary finding that slow desensitization (of presynaptic suppression of neurotransmission) occurs via endocytosis of membrane-localized opioid receptors, is well supported by multiple lines of evidence. 1) Blocking receptor endocytosis, either via mutation of GRK2/3 phosphorylation sites or pharmacological block with compound 101 prevents slow desensitization of MOR. ) SEP-MOR and SEP-DOR fluorescence (indicative of plasma membrane localization) is reduced by chronic agonist treatment.

The secondary findings that MOR and DOR do not desensitize or undergo endocytosis in a heterologous manner, and that DOR-depletion from the plasma membrane is more facile than MOR and independent of C-terminus phosphorylation, are well supported by the data and analyses.

Despite the reliance on heterologously expressed opioid receptors, the findings are likely to have a high impact on the fields of GPCR trafficking and opioid signaling, as they address a major outstanding question with direct relevance to opioid drug tolerance and may generalize to other GPCRs.

The findings also evoke new questions that will spur further work in the field. For example, just focusing on DOR, by what mechanism does agonist-driven DOR endocytosis occur not via GRK2/3 phosphorylation? By extension, would G protein-biased DOR agonists be expected to produce less tolerance? To be clear these are not to be addressed in this manuscript.

Reviewer #3 (Public Review):

The studies in the manuscript "Endocytic trafficking determines cellular tolerance of presynaptic opioid signaling" use a novel approach to assess the signaling of presynaptic opioid receptors that inhibit the release of neurotransmitters. Historically, studies have used whole-cell patch-clamp electrophysiology studies of spontaneous and evoked neurotransmitter release to measure the presynaptic effects of opioid receptors. Since the recordings were made in postsynaptic cells that expressed receptors for the released neurotransmitter, the electrophysiological measurements are indirect with respect to the presynaptic receptors under study. The technique used in this manuscript is based on a pHlorin-based unquenching assay that is a measure of synaptic vesicle exocytosis. In this case, the super-ecliptic pHluorin (SEP) is a pH-sensitive GFP that increases fluorescence as the synaptic vesicle protein that it is attached to (VAMP2-SEP) relocates from the acidic synaptic vesicle to the plasma membrane. Opioid agonists inhibit this activity with acute administration and this inhibition is reduced with prolonged, or chronic administration (hours), demonstrating tolerance. The SEP protein can also be conjugated to opioid receptors and used to measure the proportion of receptors on the plasma membrane compared to internalized receptors. The studies show that agonist activation of mu-opioid receptors (MORs) induces endocytosis that is dependent on phosphorylation of the C-terminus and that the development of tolerance is correlated with the loss of MORs at the surface. The results are different for the delta-opioid receptor (DOR) which is also internalized with acute agonist administration but that loss of receptors on the membrane occurs more rapidly and is not dependent on phosphorylation of the C-terminus.

The results in the studies are clearly presented and clearly substantiate the prior work using electrophysiology to show the late development of tolerance of presynaptic opioid receptor signaling. The studies extend prior work by showing that endocytosis of both MOR and DOR occurs in presynaptic locations but that the cellular mechanisms underlying the maintenance of these receptors on the plasma membrane differ. The imaging results show convincing effect sizes, even with genetic and pharmacological manipulations, that will allow for even further investigation into the cellular mechanisms underlying the development of tolerance. Since these studies transfected the cultured striatal neurons with both the opioid receptors and the VAMP2-SEP, one question that remains is whether imaging of the VAMP2-SEP has the resolution to detect inhibition of endocytosis by endogenous opioid receptors. Since the authors make the point that this technique has advantages over traditional electrophysiological approaches, it is important that the technique allows for the measurement of endogenous levels of receptors. There are minor questions about the statistics used in some of the graphs, and the utility of the presentation of p values on the right-hand axis but these concerns do not alter the overall significance of the studies, which are high impact.

Reviewer #1 (Public Review):

In this paper, the authors investigate how a large loom-sensitive neuron in grasshoppers becomes sensitive to looming light objects (ON looms) and looming dark objects (OFF looms). They use different visual stimuli, calcium imaging, electrophysiology, and pharmacology to identify how ON and OFF looms each elicit responses in this large neuron.

This topic is important because the segregation of visual signals into ON and OFF channels is fundamental to visual processing, yet these signals must typically be recombined to yield useful visual signals. How and where this happens remains of interest across visual systems. This study finds that, interestingly, ON looms are integrated into the neural response via a pathway that does not retain retinotopic information. The authors suggest potential energetic and functional advantages for the observed arrangement of dendritic integration.

The strength of this paper is in its dissection of the mechanisms of dendritic integration and in its surprising findings. The major weakness in this paper is that when the authors perform detailed modeling of the neural response, they do not provide enough information to evaluate their results. They make some strong arguments about energetic favorability of different synaptic arrangements, which are also not explained in enough detail.

Reviewer #2 (Public Review):

The LGMD for well over 40 years has served as a model for understanding neural computations, and its mechanisms for integrating visual stimuli are thought to be well established (including past work from the authors and other labs). The LGMD has one large dendrite field that renders it selective to dark expanding objects through a combination of retinotopically distributed off inputs and intrinsic conductances. The LGMD has two smaller dendrite fields that receive on (luminance increments) or off (luminance decrements) inhibition. Surprisingly, Dewell et al. find one of the small dendrite fields, previously found to process off inhibition, also responds robustly to expanding white objects (on excitation). Interestingly, its integration strategy differs from how the larger dendrite processes off excitation. Ca2+ activity within this smaller dendrite field shows minimal to no retinotopic arrangement of inputs. Ca2+ responses to white looming stimuli are also maintained as the coherence of the stimulus decreases, suggesting the change in luminance, but not the spatial pattern of change in luminance, underlies the LGMD's response to white expanding objects. Interestingly, the grasshopper takeoff behavior, for which the LGMD is involved, also follows a similar trend. The probability a dark looming stimulus elicits an escape strongly depends on stimulus coherence, while the probability a white looming stimulus elicits an escape does not. Overall, these findings shed light on how feature inputs can be differentially computed within the same neuron and how these computations shape behavioral responses.

Claims:

1. ON excitation occurs on the LGMD dendrite field previously thought to receive only OFF inhibition.<br /> a. The authors provide calcium imaging and local delivery of cholinergic antagonist data to support this claim.

2. ON inputs do not have retinotopic mapping across the dendrite field, unlike OFF inputs dedicated to a different dendritic field<br /> a. Analyzed calcium imaging data support this claim, but analysis methods need to be clarified and relevant anatomy need to be discussed in relation to the columnar structure of the lobula.

3. Lack of retinotopy of ON inputs makes the LGMD insensitive to ON looming stimuli coherence<br /> a. The authors provide calcium imaging data supporting the response within the dendrite receiving ON inputs does not have a strong dependency on the coherence within the looming stimulus.

4. Behavior follows witnessed dendrite integration, with decreasing coherence affecting escapes to dark but not white looms.<br /> a. The provided behavior data support these claims.

5. Limited coherence reduces energetic cost<br /> a. The rationale for this claim and the methods for the modeling experiments that support these claims need to be included/expanded.

Reviewer #3 (Public Review):

This work investigates how looming stimuli that increase in luminance are processed by the lobula giant movement detector (LGMD) neuron in grasshoppers. The manuscript starts by arguing that real life approaching predators are likely to generate a mixture of looming stimuli that increase (ON) and decrease (OFF) in luminance. Previous work has characterised well the behavioural and neurophysiological responses to OFF looms, showing that they efficiently evoke escape responses in grasshoppers and that they are mapped in a retinotopic manner to the A dendritic field for LGMD, a property important for computing that spatial coherence of the stimulus. In this manuscript, behavioural experiments show that ON looms are as efficient as OFF stimuli in eliciting escape, but that surprisingly the behaviour is independent of spatial coherence. Calcium imaging experiments show that in ON stimuli activate the C field of the LGMD neuron, suggesting a strong segregation at the cellular level between the ON and OFF pathways. Further analysis of these data show that in contrast with the OFF pathways, there appears to be no retinotopic organization of the inputs onto the dendritic tree and instead, the distribution is random. Electrophysiological recordings then reveal a progressive increase in firing rate as the ON looming stimulus approaches, with a profile that is independent of the spatial coherence of the stimulus, in agreement with the behaviour. The manuscript ends by demonstrating that mixed ON and OFF looming stimuli activate both the C and A dendritic fields and retain sensitivity to spatial coherence, and a biophysical model is shown to reproduce the experimental findings.

The overall conclusion from this work is that the visual system of the grasshopper is sensitive to ON approaching stimuli, but it is unable to discriminate their spatial coherence because of the random distribution of ON inputs onto the LGMD dendritic tree. The authors further argue that this organization allows grasshoppers to be sensitive to these stimuli while reducing the number of synapses require to reach AP threshold, thereby conserving energy. I think that the experiments are very nicely done, well designed, the data are of great quality and support the main arguments. The greatest strength of this work, and indeed of the model system, is the ability to link behaviour, sensory processing, and cellular physiology with biophysical detail in a single piece of work. I believe that this is a valuable contribution to all these fields. I have a couple of main comments for the authors to consider.

1 - This work focuses exclusively on excitatory input. However, as the authors mention, LGMD neurons also receive inhibitory inputs, and these inputs also appear to segregate to different areas of the dendritic tree depending on the pathway. The contribution of inhibition is mostly ignored throughout the manuscript, but I think that it would be beneficial to discuss how inhibitory inputs fit into the story. For example, if OFF inhibition maps onto the C field, then presumably when there is mixed ON/OFF stimulation there is inhibition of the ON excitation onto the C field? If so, how much excitation of the C field is left? How much does the retainment of spatial coherence sensitivity with mixed stimuli arise from the fact that OFF excitation might dominate because it inhibits the C field? I don't think that additional experiments are needed, but a discussion would be useful. Related, does the model include inhibitory synapses?

2 - The argument that the cellular organization found here is good because it allows grasshoppers to be sensitive to white approaching stimuli while disregarding spatial coherence and saving energy seems plausible. But it's not clear to me why this is 'optimal' (from the title - 'optimizes neuronal computation'). What exactly is being optimized here? And why is it good that grasshoppers can't discriminate the spatial coherence of ON looming stimuli? Is everything that approaches a grasshopper fast and white always a bad thing, but not the case if the approaching thing is black? Some further placement of these findings into an ecological setting might be helpful here.

Reviewer #1 (Public Review):

Abdel-Hag, Reem et al. investigated the beneficial effects of a fiber-rich diet in the pathology of α-synuclein overexpressing (ASO) mice, a preclinical model of Parkinson's disease. They found that a prebiotic intervention attenuates motor deficits and reduces microglial reactivity in the substantia nigra and striatum. They extended these findings by doing scRNA sequencing, and they identified the expansion of a protective disease-associated microglia (DAM), a microglial subset previously described during the early stages of disease in several mouse models. Interestingly, the data indicate that microglia do not influence the behavior of ASO mice in the early stages of disease progression. However, microglia are the key mediators of the protective effects of prebiotic treatment in ASO mice. Overall, the conclusions of this paper are well supported by data, but some aspects should be considered to improve the manuscript.

1) Colony-stimulating factor 1 receptor (CSF1R) inhibition has been widely used as a method for microglia depletion, however, the impact of this approach on peripheral immune cells is controversial. The authors elegantly showed that most gut-associated immune cell populations were unaffected by PLX5622. However, CSF1R signaling has been implicated in the maintenance of gut homeostasis. Could it be possible that PLX5622 treatment affects directly the gut microbiome composition? Are the beneficial changes in the gut microbiome composition of a prebiotic diet still maintained in combination with PLX5622? CSF1R inhibitors with low brain penetration such as PLX73086 and therefore unable to deplete resident microglia (Bellver- Landete, Victor et al., Nat Commun, 2019) would be helpful to rule out peripheral off-target effects.

2) The authors claimed that microglial depletion eliminates the protective effects of the prebiotic diet in ASO mice by showing increased levels of aggregated aSyn in the SN (Fig 5G). However, microglial depletion also has the same effect on WT mice. How do authors interpret this result?

3) What is the rationale for doing a long-term (17 weeks) prebiotic intervention? Have the authors considered doing a short-term intervention? The prebiotic diet should change quickly the gut microbiome composition within a few days or weeks.

Reviewer #2 (Public Review):

The manuscript by Abdel-Haq and colleagues is a descriptive study providing evidence that mice displaying motor impairment related to Parkinson's disease fed with a prebiotic diet show a decrease in the severity of this impairment (some, but not all, of the motor functions tested). Their data indicate that microglial cells are required to mediate the beneficial effect of the prebiotic treatment. Indeed, in the absence of microglial cells, the prebiotic treatment is no longer able to attenuate the motor deficit. This manuscript is of interest to a wide audience as it provides further evidence that links motor impairment related to PD to events occurring in the gut (gut-brain axis). Furthermore, some of the new findings presented in the manuscript highlight the contribution of immune mechanisms as key contributors to the pathophysiological process leading to PD.

This is an interesting study showing for the first time that the beneficial effect of a prebiotic treatment in the context of motor impairment related to PD is mediated by microglial cells. Since these cells are of macrophagic origin, their data support the concept that the immune system plays a role along the gut-brain axis during the pathophysiological process leading to PD. The sequencing data may be of additional value to some. Considering that the authors had a model system where clear beneficial motor impairment was observed, it is surprising that they did not investigate further whether the dopaminergic system in the SN and STR was modified in relation to the prebiotic treatment and microglial depletion.

Reviewer #3 (Public Review):

Abdel-Haq presents a comprehensive analysis of the impact of dietary fiber on the ASO mouse model. They describe diet-induced changes in the gut microbiota, microbial metabolites, host gene expression, microglial activation, and motor deficits. Pharmacological inhibition of microglia highlights the importance of these cells for the impact of prebiotics, raising intriguing hypotheses for future studies.

Strengths include the rigor and reproducibility of these studies, the clarity of the presentation, and the timely focus on microglial interactions with the gut microbiome.

The major weakness is the descriptive nature of these studies and the lack of reduction in the mechanism. Only a single model is used and there is no attempt to test the translational relevance of these findings in humans. The putative pathway (fiber→bacteria→SCFA→microglia) has already been reported, so the data is largely confirmatory in nature.

Despite these concerns, this work adds to the growing literature on the gut-brain axis and will be helpful for motivating continued studies in mice and human cohorts. However, caution should be advised for using these results to motivate specific dietary recommendations to patients.

Reviewer #1 (Public Review):

The software presented in this paper is well documented and represents a significant achievement that breaks new ground in terms of what is possible to render and explore in the web browser. This tool is essential for the exploration of SC2 data, but equally useful for the tree of life and other tree-like data sets.

Reviewer #2 (Public Review):

This manuscript describes a web-based tool (Taxonium) for interactively visualizing large trees that can be annotated with metadata. Having worked on similar problems in the analysis and visualization of enormous SARS-CoV-2 data sets, I am quite impressed with the performance and "look and feel" of the Taxonium-powered cov2tree web interface, particularly its speed at rendering trees (or at least a subgraph of the tree).

The manuscript is written well, although it uses some technical "web 2.0" terminology that may not be accessible to a general scientific readership, e.g., "protobuf" (presumably protocol buffer) and "autoscaling Kubernetes cluster". The latter is like referring to a piece of lab equipment, so the author should provide some sort of reference to the manufacturer, i.e., https://kubernetes.io/. In other respects, the manuscript lacks some methodological details, such as exactly how the tree is "sparsified" to reduce the number of branches being displayed for a given range of coordinates. Some statements are inaccurate or not supported by current knowledge in the field. For instance, it is not true that the phylogeny "closely approximates" the transmission tree for RNA viruses. Mutations are not associated with a "point in the phylogeny", but rather the branch that is associated with that internal node.

A major limitation of displaying a single phylogenetic tree (albeit an enormous one) is that the uncertainty in reconstructing specific branches is not readily communicated to the user. This problem is exacerbated for large trees where the number of observations far exceeds the amount of data (alignment length). Hence, it would be very helpful to have some means of annotating the tree display with levels of uncertainty, e.g., "we actually have no idea if this is the correct subtree". DensiTree endeavours to do this by drawing a joint representation of a posterior sample of trees, but it would be onerous to map a user interface to this display. I'm raising this point as something for the developers to consider as a feature addition, and not a required revision for this manuscript.

The authors make multiple claims of novelty - e.g., "[...] existing web-based tools [...] do not scale to the size of data sets now available for SARS-CoV-2" and "Taxonium is the only tool that readily displays the number of independent times a given mutation has occurred [...]" - that are not entirely accurate. For example, RASCL (https://observablehq.com/@aglucaci/rascl) allows users to annotate phylogenies to examine the repeated occurrence of specific mutations.<br /> Our own system, CoVizu, also enables users to visualize and explore the evolutionary relationships among millions of SARS-CoV-2 genomes, although it takes a very different approach from Taxonium. Taxonium is an excellent and innovative tool, and it should not be necessary to claim priority.

Although the source code (largely JavaScript with some Python) is quite clean and has a consistent style, there is a surprising lack of documentation in the code. This makes me concerned about whether Taxonium can be a maintainable and extensible open-source project since this complex system has been almost entirely written by a single developer. For example, `usher_to_taxonium.py` has a single inline comment (a command-line example) and no docstring for the main function. `JBrowsePanel.jsx` has a single inline comment for 293 lines of code. There is some external documentation (e.g., `DEVELOPMENT.md`) that provides instructions for installing a development build, but it would be very helpful to extend this documentation to describe the relationships among the different files and their specific roles. Again, this is something for the developers to consider for future work and not the current manuscript.

Reviewer #3 (Public Review):

The paper succinctly provides an overview of the current approaches to generating and displaying super-large phylogenies (>10,000 tips). The results presented here provide a comprehensive set of tools to address the display and exploration of such phylogenies. The tools are well-described and comprehensive, and additional online documentation is welcome.

The technical work to display such large datasets in a responsive fashion is impressive and this is aptly described in the paper. The author rightly decides that displaying large phylogenies is not simply a matter of rendering "more nodes", and so in my eyes, the major advancement is the approach used to downsample trees on-the-fly so that the number of nodes displayed at one time is manageable. This is detailed only briefly (Results section, 1st paragraph, 2 sentences). I would like to see more discussion about the details of this approach. Examples that came up while exploring the tool: the (well implemented) search functionality reports results from the entire tree (e.g. in Figure 4, the number of red circles is not a function of zoom level), how does this interact with a tree showing only a subset of nodes? How is the node order chosen with regards to "nodes that would be hidden by other nodes are excluded" and could this affect interpretations depending on the colouring used?

Taxonium takes the approach of displaying all available data (sparsification of nodes notwithstanding). Biases in the generation of sequences, especially geographical, will therefore be present (especially so in the two main datasets discussed here - SARS-CoV-2 and monkeypox). This caveat should be made explicit. Has the author considered choosing which nodes to exclude for sparsified trees in such a way as to minimise known sampling biases?

Interoperability between different software tools is discussed in a technical sense but not as it pertains to discovering the questions to ask of the data. As an example, spotting the specific mutations shown in figure 3 + 4 is not feasible by checking every position iteratively; instead, the ability to have mutations flagged elsewhere and then seamlessly explore them in Taxonium is a much more powerful workflow. This kind of interoperability (which Taxonium supports) enhances the claim of "providing insights into the evolution of the virus".

Taxonium has been a fantastic resource for the analysis of SARS-CoV-2 and this paper fluently presents the tool in the context of the wider ecosystem of bioinformatic tools in use today, with the interoperability of the different pieces being a welcome direction.

Reviewer #1 (Public Review):

The paper by Gomez et al. describes investigations employing extracellular recordings of neural spiking in rat pups across different sleep states in primary (M1) and secondary (M2) cortices as well as in the prefrontal cortex (PFC) in response to spontaneous motor activity and tactile stimulation. The authors demonstrate activity across these areas that are associated with active sleep (AS) and identify responses in each region to internally generated movements and external stimuli. Because these results contradict earlier findings in the same areas under anesthesia, they also perform similar recordings in urethane anesthetized animals and show that similar responses are not observed under these conditions. Based on findings from anesthetized and unanesthetized recordings, the authors conclude that early responses associated with AS occur in higher cortical areas, a novel observation for the brain regions studied which had been missed in previous studies because they are absent under anesthesia. Finally, in their discussion, the authors consider the potential roles of state dependent activity in development and contend that differences in activity patterns between motor cortical areas and PFC reflect the diversity or heterogeneity of the inputs they respond to.

The finding presented, particularly the observation of state specific activity in the PFC similar to that observed in more sensory linked areas of the motor cortex, are novel and of interest for their potential relevance to development. However, analysis of the recordings presented in the current manuscript are largely descriptive and do not convey much functional insight beyond simple observation of the phenomenon. In addition, some of the claims made, particularly those related to the differences between PFC and motor cortex, are not clearly supported by the data as currently presented. For these reasons, the study should be revised to including by incorporating additional analysis and potentially further experiments. In addition, clarification of the text and figures is needed to allow the findings to be clearly understood. Resolution of these issues would be important to improve the quality of the manuscript.

Reviewer #2 (Public Review):

The way a child sleeps is much different than the way an adolescent or an adult sleeps. One difference concerns the time spent in active sleep (AS, also called paradoxical or REM sleep), which is very high in early stages of development and thought to favor brain plasticity that is relevant for circuit development. This study is a step forward to understand the neuronal activity patterns by which REMS promotes this plasticity.

The study addresses this question in particular for higher-order cortical areas. It finds that activity in M2 and mPFC is greater for AS than for wakefulness. Within AS, activity is further elevated in relation to spontaneous limb movements that are characteristic for this state. At P8 but less so at P12, both M2 and mPFC also respond to external sensory stimulation. Therefore, the authors have identified the time window over which these higher cortical areas are sensory responsive yet decline to do so over a period of four days. Through contrasting their results with naturally sleeping with the ones of urethane-anesthetized pups, they further support the unique status of AS in the regulation of neuronal activity and sensory responsiveness that is critical for development. This will enable precise further manipulation to study the anatomo-functional basis of this sensory responsiveness and its role for the development of the sensorimotor system.

Reviewer #1 (Public Review):

Multiple myeloma (MM) is a common often incurable plasma cell disease. Fatty acid binding proteins (FABPs) represent biomarkers for aggressive disease in MM, and pharmacologically inhibiting FABPs kill tumor cells and induce cell cycle arrest. This work demonstrates that targeting FABP5 holds great therapeutic potential for killing diseased cells, with few negative off-target effects on healthy cells.

The authors first found their FABP target by utilizing the Broad Institute's Cancer Dependency Map (DepMap), where only FABP5 exhibited a score in all 20 MM cell lines that demonstrated a strong reliance on FABP5 for survival. To test the effects of FABP5 in MM cell lines they created knock outs, however, the efficacy was relatively low with expression down only 84%. The results demonstrated a reduced proliferation and subsequently, the authors sought to use chemical FABP inhibitors. To understand how FABP5 inhibition could lead to reduced MM cell proliferation, RNAseq was performed. The results analysis demonstrated that MYC, a known oncogene, was found as a central downregulated node. MYC's importance was further confirmed with proteomic analysis.

To help put these findings into clinical context, they investigated the combination of FABP inhibition (FABPi) with dexamethasone, a common therapy for MM patients, where they found that FABPi enhanced dexamethasone's efficacy. Overall, this is an outstanding manuscript that should help advance the overall understanding of MM. The major weakness relates to an unclear mechanism of action (MOA) for FABP5 in MM cells.

Reviewer #2 (Public Review):

Farrell et al. investigated the effect of FABP5 inhibition in myeloma, demonstrating a reduction in tumour burden. They present extensive data to demonstrate that FABP5 inhibition, either by CRISPR-Cas9 or pharmacologically, reduces myeloma cell growth. Transcriptomic and proteomic profiling reveals a wealth of gene and protein sets that are altered in response to FABP5 inhibition, the most notable of which are the UPR and MYC. Two preclinical murine models of myeloma are employed, with a significant reduction in tumour burden and increase in survival observed in response to FABP5 inhibition, providing strong support for the translational potential of this approach in myeloma. Supporting in silico analysis of patient datasets demonstrates associations between FABP5 expression and myeloma survival, providing a strong clinical correlate. The conclusions of the paper are well supported by the data.

Strengths

To the best of my knowledge, this is a novel finding in myeloma, revealing a new therapeutic approach which appears to be highly effective in reducing tumour burden. The work is comprehensive, using a panel of myeloma cell lines and a multitude of in vitro approaches to determine response to FABP inhibition.

Weaknesses

FABP inhibition is known to be effective in other cancers, therefore it is not surprising that it is also effective in myeloma. Mechanism is eluded to following the transcriptomic and proteomic analysis, however, this is not explored in a conclusive manner. Myeloma is a cancer of the bone marrow associated with osteolysis, however, no analysis of the effect of FABP inhibition on myeloma bone disease is presented.

Reviewer #3 (Public Review):

In this manuscript, Farrell and colleagues investigated the role of FABP genes in multiple myeloma progression using a combination of in vitro, in vivo, and in silico approaches, as well as genetic and pharmacologic interventions. They report that FABP genes are expressed in myeloma cells and show that genetic inhibition of FABP5 or pharmacologic inhibition of several FABP genes decreases myeloma cell number in vitro and in vivo. The decrease in cell number correlates with cell cycle arrest and a modest increase in apoptosis. By performing a comprehensive transcriptomic, proteomic, and metabolomic analysis, the authors find that inhibition of FABP genes reduces MYC gene expression and UPR genes, and decreases mitochondrial respiration, and blocks. Consistent with their in vitro and in vivo data, the authors show that FAPB5 expression in patients negatively correlates with survival. Overall, the data is interesting and provides new therapeutic targets to combat the growth of myeloma cells in the bone marrow. The conclusions are mostly supported by the data; however some mechanistic aspects of the studies need to be clarified and extended.

Strengths:<br /> 1) The use of genetic (CRISPR) and pharmacologic (BMS309403 and SBFI-26) and in vitro and in vivo models adds scientific rigor to the findings presented and increase their clinical relevance.<br /> 2) The authors perform a highly comprehensive analysis of the consequences of FABP inhibition in myeloma cells using transcriptomic, proteomic or metabolic analysis. The bioinformatic analysis of these data is well done and rendered additional potential targets (genes or pathways) mediating FABP effects on myeloma cells.<br /> 3) The addition of in silico analysis of patient databases adds translational value to their findings.

Weaknesses:<br /> 1) Despite the comprehensive bioinformatic analysis performed by the authors, the mechanisms by which inhibition of members of the FABP family decreases tumor progression are not investigated. Several potential mechanisms are inferred (i.e., MYC, DNA methylation, UPR genes, mitochondrial respiration) but no experiments are performed to demonstrate their involvement in the response to FABP inhibitors.<br /> 2) The authors indicate FABP inhibitors are safe, but their toxicity analysis is limited to body weight, which might not be a good indicator of toxicities.<br /> 3) FABP inhibitors have systemic effects that could contribute to the decreased tumor burden. This is not considered in the interpretation of the in vivo results.

Reviewer #1 (Public Review):

Mutations in Doublecortin (DCX), which is a microtubule-binding protein cause lissencephaly. This manuscript by Rao et al. demonstrates the mechanism by which DCX affects retrograde transport in the neurons. Authors show that DCX functions to affect dynein transport in the axon via two different mechanisms - 1. By regulating dynein-microtubule interaction and 2. By regulating the interaction of JIP3 to the dynein motor complex. Interestingly, they have also shown the formation of the dynein-dynactin-JIP3 complex and reconstituted its motility in vitro. Authors demonstrate DCX regulation by affecting the recruitment of the second dynein in the dynein-dynactin-JIP3 complex to affect dynein velocity. Because DCX also regulates Kinesin-3 mediated transport, this work uncovers the role of DCX in regulating opposite polarity motors during neuronal growth. Overall the manuscript is well written, the work is original, experiments are performed carefully and most of the findings justify the conclusions drawn by the authors.

Reviewer #2 (Public Review):

The authors have tried to provide a molecular mechanism for the observation that the lack of DCX increases run lengths of retrogradely moving cargo. The authors show a direct interaction of DCX with Dynein and that this direct interaction is the key means by which to regulate dynein-dependent retrograde run lengths of cargo. DCX seems to have a dual role - on microtubules where it appears to prevent attachment of dynein to microtubules. DCX also appears to reduce JIP3 binding to dynein.

A major strength is that they have used a combination of approaches including in vitro motility assays to support their arguments.

Reviewer #1 (Public Review):

In this manuscript by Kim et al., the authors use live-cell imaging of transcription in the Drosophila blastoderm to motivate quantitative models of gene regulation. Specifically, they focus on the role of repressors and use a 'thermodynamic' model as the conceptual framework for understanding the addition and placement of the repressor Runt, i.e. synthetic insertion of Runt repressor sites into the Bicoid-activated hunchback P2 enhancer. Coupled with kinetic modeling and live-cell imaging, this study is a sort of mathematical enhancer bashing experiment. The overarching theme is measuring the input/output relationship between an activator (bicoid), repressor (runt), and mRNA synthesis. Transcriptional repression is understudied in my opinion. One finding is that the inclusion of cooperativity between trans-acting factors is necessary for understanding transcriptional regulation. Most, if not all, of the tools used in this paper have been published elsewhere, but the real contribution is a deep, quantitative dissection of transcriptional regulation during development. As such, the only real questions for this referee are whether the modeling was done rigorously to produce some general biological conclusions. By and large, I think the answer is yes.

Comments:

Fig. 6 was the most striking figure for this referee, specifically that different placements of Runt molecules on the enhancer lead to distinct higher order interactions. I am wondering if the middle data column in Fig. 6 represents a real difference from the other two, and if so, it seems that the positioning - as opposed to simply the stoichiometry - is essential in cooperativity. This conclusion implies that transcriptional regulation is more precise than what some claim is just a mushy ball of factors close to a promoter. In other words, orientation may matter. Proximity may matter. Interactions in trans matter.

There needs to be at least one prediction which is validated at the level of smFISH / mRNA in the embryo. Without detracting from the effort the authors have expended in looking directly at transcription, if the effects can't be felt by the blastoderm at the level of mRNA/cell, it become difficult to argue for the relevance to development. Also, I feel there is little chance that these measurements can be quantitatively replicated unless translated to the level of total protein or mRNA. Such a measurement (orthogonal quantitative confirmation of the repressor cooperativity result) would also assuage my concern about the time averaging as shown in Fig. S3.

Reviewer #2 (Public Review):

In this paper, eGFP: LlamaTag-Runt was inserted into Drosophila embryo cells by CRISPR-Cas9 technology, and quantitative gene expression and time-lapse measurements were performed. The molecular mechanism was modeled and analyzed by thermodynamic model, the experimental data were fitted by MCMC, and the necessity of cooperation was given.

Reviewer #3 (Public Review):

The authors have presented results from carefully planned and executed experiments that probe enhancer-drive expression patterns in varying cellular conditions (of the early Drosophila embryo) and test whether standard models of cis-regulatory encoding suffice to explain the data. They show that this is not the case, and propose a mechanistic aspect (higher order cooperativity) that ought to be explored more carefully in future studies. The presentation (especially the figures and schematics) are excellent, and the narrative is crisp and well organized. The work is significant because it challenges our current understanding of how enhancers encode the combinatorial action of multiple transcription factors through multiple binding sites. The work will motivate additional modeling of the presented data, and experimental follow-up studies to explore the proposed mechanisms of higher order cooperativity. The work is an excellent example of iterative experimentation and quantitative modeling in the context of cis-regulatory grammar. At the same time, the work as it stands currently raises some doubts regarding the statistical interpretation of results and modeling, as outlined below.

The results presented in Figure 5 are used to claim that the data support (i) an unchanging K_R regardless of the position of the Runt site in the enhancer and (ii) an \omega_RP that decreases as the site goes further away from the promoter, as might be expected from a direct repression model. This claim is based on only testing the specific model that the authors hypothesize and no alternative model is compared. For instance, are the fits significantly worse if \omega_RP is kept constant and the K_R allowed to vary across the three sites. If different placements of the Runt site can result in puzzling differences in RNAP-promoter interaction, it seems entirely possible that the different site placements might result in different K_R, perhaps due to unmodeled interference from bicoid binding. Due to these considerations, it is not clear if the data indeed argue for a fixed K_R and distance-dependent \omega_RP.

Results presented in Figure 6 make the case that higher order cooperativity involving two DNA-bound molecules of Runt and the RNAP is sufficient to explain the data. The trained values of such cooperativity in the three tested enhancers appear orders of magnitude different. As a result, it is hard to assess the evidence (from model fits) in a statistical sense. Indeed, if all of the assumptions of the model are correct, then using the high-order cooperativity is better than not using it. To some extent, this sounds statistically uninteresting (one additional parameter, better fits). It is not the case that the new parameter explains the data perfectly, so some form of statistical assessment is essential. Moreover, it is not the case that the model structure being tested is the only obvious biophysics-driven choice: since this is the first time that such higher order effects are being tested, one has to be careful about testing alternative model structures, e.g., repression models that go beyond direct repression and pairwise cooperativity that goes beyond the traditional approach of a single (pseudo)energy term.

The general theme seen in Figure 6 is seen again in Figure 7, when a 3-site construct is tested: model complexities inferred from all of the previous analyses are insufficient at explaining the new data, and new parameters have to be trained to explain the results. The authors do not seem to claim that the higher order cooperativity terms (two parameters) explain the data, rather that such terms may be useful.

Reviewer #2 (Public Review):

This is an interesting study investigating the effects of sensory conflict on rhythmic behaviour and gene expression in the sea anemone Nematostella vectensis. Sensory conflict can arise when two environmental inputs (Zeitgeber) that usually act cooperatively to synchronize circadian clocks and behaviour, are presented out of phase. The clock system then needs to somehow cope with this challenge, for example by prioritising one cue and ignoring the other. While the daily light dark cycle is usually considered the more reliable and potent Zeitgeber, under some conditions, daily temperature cycles appear to be more prominent, and a certain offset between light and temperature cycles can even lead to a breakdown of the circadian clock and normal daily behavioural rhythms. Understanding the weighting and integration of different environmental cues is important for proper synchronization to daily environmental cycles, because organisms need to distinguish between 'environmental noise' (e.g., cloudy weather and/or sudden, within day/night temperature changes) and regular daily changes of light and temperature. In this study, a systematic analysis of different offsets between light and temperature cycles on behavioural activity was conducted. The results indicated that several degrees of chronic offset results in the disruption of rhythmic behaviour. In the 2nd part of the study the authors determine the effect of sensory conflict (12 hr offset that leads to robust disruption of rhythmic behaviour) on overall gene expression rhythms. They observe substantial differences between aligned and offset conditions and conclude a major role for temperature cycles in setting transcriptional phase. While the study is thoroughly conducted and represents and impressive amount of experimental and analytical work, there are several issues, which I think question the main conclusions. The main issue being that temperature cycles by themselves do not seem to fulfil the criteria for being considered a true Zeitgeber for the circadian clock of Nematostella.

Major points:

Line 53: 'However, many of these studies did not compare more than two possible phase relationships.....'. Harper et al. (2016) did perform a comprehensive comparison of different phase relationships between light and temperature Zeitgebers (1 hr steps between 2 and 10 hr offsets), similar to the one conducted here. I think this previous study is highly relevant for the current manuscript and -- although cited -- should be discussed in more detail. For example, Harper et al. show that during smaller offsets temperature is the dominant Zeitgeber, and during larger sensory conflict light becomes the dominant Zeitgeber for behavioural synchronization. Only during a small offset window (5-7 hr) behavioural synchronization becomes highly aberrant, presumably because of a near breakdown of the molecular clock, caused by sensory conflict. Do the authors see something similar in Nematostella? Figure 3 suggests otherwise, at least under entrainment conditions, where behaviour becomes desynchronized only at 10 and 12 hr offset conditions. But in free-run conditions behaviour appears largely AR already at 6 hr offset, but not so much at 4 and 8 hr offsets (Table 2). So there seems to be at least some similarity to the situation in Drosophila during sensory conflict, which I think is worth mentioning and discussing.

Line 111: The authors state that 14-26C temperature cycle is 'well within the daily temperature range experienced by the source population'. Too me this is surprising, as I was not expecting that water temperature changes that much on a daily basis. Is this because Nematostella live near the water surface, and/or do they show vertical daily migration? Also, I do not understand what is meant by '...range of in situ diel variation (of temperature)'. I think a few explanatory words would be helpful here for the reader not familiar with this organism.

Lines 114-117: I was surprised that clock genes can basically not be synchronized by temperature cycles alone. Only cry2 cycled during temperature cycles but not in free-run, so the cry2 cycling during temperature cycles could just be masking (response to temperature). Later the authors show robust molecular cycling during combined LD and temperature cycles (both aligned and out of phase), indicating that LD cycles are required to synchronize the molecular clock. Moreover, a previous study has demonstrated that LD cycles alone (i.e., at constant temperature) are able to induce rhythmic molecular clock gene expression (Oren et al. 2015). Similarly, the free running behaviour after temperature cycles does not look rhythmic to me. In Figure 2A, 14-26C there is at best one peak visible on the first day of DD, and even that shows a ~6 phase delay compared to the entrained condition. After the larger amplitude temperature cycle (8:32C) behaviour looks completely AR and peak activity phases in free-run appear desynchronized as well (Fig. 2B). Overall, I think the authors present data demonstrating that temperature cycles alone are not sufficient to synchronize the circadian clock of Nematostella. One way to proof if the clock can be entrained is to perform T-cycle experiments, so changing the thermoperiod away from 24 hr (e.g., 10 h warm : 10 h cold). If in a series of different T-cycles the peak activity always matches the transition from warm to cold (as in 12:12 T-cycles shown in Fig. 1A) this would speak against entrainment and vice versa.

Lines 210-226: As mentioned above, I think it is not clear that temperature alone can synchronize the Nematostella clock and it is therefore problematic to call it a Zeitgeber. Nevertheless, Figure 3A, B, D show that certain offsets of the temperature cycle relative to the LD cycle do influence rhythmicity and phase in constant conditions. This is most likely due to a direct effect of temperature cycles on the endogenous circadian clock, which only becomes visible (measureable) when the animals are also exposed to certain offset LD cycles. My interpretation of the combined results would be that temperature cycles play only are very minor role in synchronizing the Nematostella clock (after all, LD and temperature cycles are not offset in nature), perhaps mainly supporting entrainment by the prominent LD cycles.

Gene expression part: The authors performed an extensive temporal transcriptomic analysis and comparison of gene expression between animals kept in aligned LD and temperature cycles and those maintained in a 12 hr offset. While this was a tremendous amount of experimental work that was followed by sophisticated mathematical analysis, I think that the conclusions that can be drawn from the data are rather limited. First of all, it is known from other organisms that temperature cycles alone have drastic effects on overall gene expression and importantly in a clock independent manner (e.g., Boothroyd et al. 2007). Temperature therefore seems to have a substantially larger effect on gene expression levels compared to light (Boothroyd et al. 2007). In the current study, except for a few clock gene candidates (Figure 2C), the effects of temperature cycles alone on overall gene expression have not been determined. Instead the authors analysed gene expression during aligned and 12 h offset conditions making it difficult to judge which of the observed differences are due to clock independent and clock dependent temperature effects on gene expression. This is further complicated by the lack of expression data in constant conditions. I think the authors need to address these limitations of their study and tone down their interpretations of 'temperature being the most important driver of rhythmic gene expression' (e.g., line 401). At least they need to acknowledge that they cannot distinguish between clock independent, driven gene expression and potential influences of temperature on clock-dependent gene expression rhythms. Moreover, in their comparison between their own data and LD data obtained at constant temperature (taken from Oren et al. 2015), they show that temperature has only a very limited effect (if any) on core clock gene expression, further questioning the role of temperature cycles in synchronising the Nematostella clock. Nevertheless, I noted in Table 3 that there is a 1.5 to 3 hr delay when comparing the phase of eight potential key clock genes between the current study (temperature and LD cycles aligned) and LD constant temperature (determined by Oren et al.). To me, this is the strongest argument that temperature cycles at least affect the phase of clock gene expression, but the authors do not comment on this phase difference.

Network analysis: This last section of the results was very difficult to read and follow (at least for me). For example, do the colours in Figure 6A correspond to those in Figure 6B, C? A legend for each colour, i.e., which GO terms are included in each colour would perhaps be helpful. As mentioned above, I also do not think we can learn a lot from this analysis, since we do not know the effects of temperature cycles alone and we have no free-run data to judge potential influence on clock controlled gene expression. Under aligned conditions genes are expressed at a certain phase during the daily cycle (either morning to midday, or evening to midnight), which interestingly, is very similar to temperature cycle-only driven genes in Drosophila (Boothroyd et al. 2007). Inverting the temperature cycle has drastic effects on the peak phases of gene expression, but not so much on overall rhythmicity. But since no free-run data are available, we do not know to what extend these (expected) phase changes reflect temperature-driven responses, or are a result of alterations in the endogenous circadian clock.

Reviewer #1 (Public Review):

The sea anemone Nematostella has been previously shown by the authors to exhibit diurnal patterns of movement around their culture dishes -- essentially they move around in darkness and not when in the light. This behaviour is entrained and continues to cycle when animals are kept in constant darkness. In this manuscript the authors test whether temperature cycles can substitute for light cycles in entraining this locomotory behaviour, and it turns out it can. They then test the effects of the two different entraining factors, light and temperature, when applied in phase (aligned exposure cycles) or out of phase (misaligned exposure cycles). The condition the authors call aligned (somewhat arbitrarily) is for the minimal temperature occurring at the beginning of the light cycle. They shift this alignment by 2, 4, 6, 8, 10 and 12 hours; so for example the first altered set has lights on 2 hours after the minimal temperature, and the second set four hours after the minimal temperature. Animals are conditioned to these new entraining cycles for 'at least 2 weeks', then tests applied. The tests are either the behaviour of the animals at a constant temperature in constant darkness, or gene expression under one example of these altered out-of-phase conditions.

The authors view all data within a framework called 'sensory conflict' -- it is even the first two words of the title. This phrase is used in other papers to describe what seems to me an over-simplistic way to view the interactions between different entraining factors. Why is this 'conflict'? If they are two different environmental entraining signals and the cycle of one is shifted relative to the other you are simply changing the alignment of the cycles. By attempting to view the simple change in alignment within the formal framework of 'sensory conflict' the authors are limiting their (and the readers') ability to understand their results; all they see is different levels of conflict, which I would argue are not supported in any way by the results. If you were to shift the alignment of any two in-phase cycles so their peaks were then in anti-phase, you would wipe out any times in which neither of the two cycles was in the negative phase. It would not be 'sensory conflict' if in the anti-phase scenario no clear peak of the behaviour was evident. It would simply be the absence of peaks and troughs of conditions driving the behaviour. The framework used to discuss the data make it difficult to understand.

After exploring impacts on shifting the alignment of light and temperature cycles the authors also examine changes in gene expression patterns in animals entrained to the new regimen. This is a powerful approach as changes in gene expression underlie most of the changes to cellular responses to the environment. The very detailed analysis finds complex changes in transcription patterns. A number of genes associated with biological clocks, or daily cycles of light, have previously been identified in other animals, and a small field has explored them in cnidarians including Nematostella and their relatives, the corals. These cycling genes are found in the results, but temperature was in general a stronger influencer on changes in gene expression. In terms of light, the PAR-bZIP genes once again show up as major responders, and this is strongly supported by the authors' examination of regulatory regions near differentially expressed genes, which are enriched in PAR-bZIP binding sites.

Perhaps the most interesting set of genes identified are those that are only weakly rhythmic when the two entraining factor cycles are aligned, but become sharply rhythmic when they are in antiphase. The new sharp rhythms have an approximately 24 hour periodicity. As mentioned, temperature dominates changes in expression over light. Three core clock genes, Helt, PAR-bZIPa and Clock resist the shift to temperature and maintain their light driven cycles. The clear conclusion is that shifting the two entraining cycles results in large scale shifts in the underlying transcriptome for most rhythmic genes, with temperature dominating light except for core elements of the light responsive clock, and the major shifts are in metabolic processes.

The authors provide a gene level examination of the cellular response to shifting the alignment of two different entraining factors that allows us to view, if not completely understand, how interactions between environmental signals are integrated.

Reviewer #3 (Public Review):

This article reflects a significant effort by the authors and the results are interesting.

For the third set of experiments, are temperature and light really out of synch? While peak in temperature no longer occurs along with lights on, we do still have two 24 hour cycles where changes in the environmental cues still occur simultaneously (lights on with peak in temperature, lights off with min in temperature). I wonder what would happen if light remained at a 24 hour cycle and temperature became either sporadic (randomly changing cycles) or was placed on a longer cycle altogether (temperature taking 20 hours to increase from min to max, and then another 20 hours to go from max to min).

An area that could significantly benefit a broader readership would be to improve overall clarity of figures and rethink if all the results are necessary to convert the key findings of the paper. As written, the results sections is somewhat confusing.

Reviewer #1 (Public Review):

Generally, the strength of this work is the submolecular resolution provided by the MD simulations, while at the same time the weakness is that the results of such simulations are only as good as the force fields used to describe the interactions between gasdermin-D subunits within an assembly and between these subunits and the lipids in the membrane. These simulations yield several interesting results, while also raising various questions, as follows.

The MD simulations are consistent with previous results (e.g., Ding et al., 2016 and Mulvihill et al., 2018, cited in manuscript that gasdermins preferentially bind to anionic lipids, which is not new, but the results are novel here in identifying these interactions at submolecular scale. However, by only showing results for interactions with PI(4,5)P2, without any results for other lipids (if only as a negative control), it remains hard for a reader to assess the relevance and strength of these interactions.

The next result is that the 33-mer "prepore" gasdermin assembly deforms the membrane by just binding - and not inserting into - the membrane. It may seem surprising that such an effect of the membrane may occur without membrane insertion, but it is consistent with previous (experimental) observations for prepore assemblies of the cholesterol dependent cytolysins pneumolysin (Tilley et al., 2005; Faraj et al., Sci Rep 2020) and suilysin (Leung et al., 2014, cited in manuscript). The authors also present data on the 33-mer ring-shaped pore confirmation, not surprisingly finding this pore to be stable.

The more novel results emerge when considering monomers and smaller oligomers. To assess their potential role in pore formation, MD simulations are shown that demonstrate stability of inserted monomers, dimers, etc. of gasdermin-D. Although, as noted by the authors, arc-shaped pores are a common feature for pore forming proteins, it is quite remarkable that a monomer is enough to provide a stable membrane-inserted configuration. The unanswered question, however, is if such smaller gasdermin assemblies will be able to insert into the membrane, presuming that there may be an activation barrier to overcome between prepore (membrane-bound) and pore (membrane-inserted) configuration. That is, while the MD results how that such small oligomers can adopt stable membrane-inserted configurations, they do not justify the authors' claim that such oligomers "create" membrane pores.

The final main and valuable result is about the fate of the lipids in arc-shaped gasdermin assemblies, although the comparison with the ring-shaped pore is lacking (e.g., by initiating the pore assembly with lipids still embedded within the ring). For the arc-shaped pores, the lipids are shown to recede from the inside of the arcs, providing new insight into how the membrane is locally removed. Most intriguingly, the line tension of the lipids appear to "crack" the 16-mer assembly, resulting in a smaller-aperture slit-shaped pores (as have observed by AFM previously). One weakness here is that only a single such cracking event (N=1) is shown to result in the slit-shaped pore.

Another question is how this observation relates to previous MD simulations (by the same lab, Vogele et al, 2019) of pneumolysin pores. Based on MD results and structural details, how do gasdermin-D and pneumolysin compare when viewed through the lens of MD?

Finally, the authors conclude that there are two distinct pathways of membrane pore formation by gasdermin-D (Fig. 5), but do not explain why they exclude formation of larger arc-shaped "adhered prepores" as a pathway of pore formation. Why would larger adhered prepores only insert into the membrane as full rings and not as larger arc-shaped assemblies? That conclusion does not seem justified by the data.

Reviewer #2 (Public Review):

Schaefer and Hummer have performed all-atom molecular dynamics (MD) simulations to study the mechanism of GSDMDNT assembly in membranes closely resembling human plasma membranes. Poses of GSDMDNT-lipid interaction were analyzed. Comparing the assemblies of different GSDMDNT oligomeric states reveals key steps in the membrane pore formation by GSDMDNT, resulting in a model with two GSDMDNT concentration-dependent pathways. That is, low concentration favors monomer insertion followed by assembly in the membranes, whereas high concentration promotes prepore formation at the membrane surface followed by membrane insertion to mature into pore. This model is valuable since it reconciles different experiments that cast doubt on the exact order and mechanism with which GSDMDNT binds the plasma membranes. With comparisons against the existing studies, this paper has provided a better understanding of how various factors such as GSDMDNT concentration and, in particular, the membrane composition may influence the process. The study was well carried out. Given the system size, complexity of the membrane composition, and abundance of cholesterol, the simulations were conducted with strong physical rigor (e.g., long all-atom equilibration with tensionless membranes and with cholesterol flip-flop in equilibrium). The paper was well-organized and nicely written.

Reviewer #1 (Public Review):

Xu et al show that mutants in three DNA replication proteins, Mcm2, Pole3, and Pole4 have defects in differentiation in a mouse embryonic stem cell (ESC) model. The Mcm2 mutant (called Mcm2-2A), which specifically blocks the interaction of Mcm2 with histones, has defects in multilineage differentiation and neural differentiation, despite having minimal effect on ESC proliferation or gene expression. Mcm2-2A fails to fully silence ESC genes and activate appropriate differentiation genes. Chromatin profiling analyses show Mcm2 binds many promoters. During differentiation, the Mcm2-2 mutant retains K3K27me3 at differentiation gene promoters and reduced accessibility, consistent with the observed defects in gene expression.

The findings that Mcm2-2A has minimal effect on proliferation and gene expression in ESCs, but impairs differentiation are interesting, particularly since this mutant seems to separate the histone binding roles of Mcm2 and its roles in DNA replication. Furthermore, the fact the histone binding function is only necessary when cells exit the pluripotent state is of interest. The studies were reasonably thorough and generally support the conclusions that Mcm2 is important for reshaping histone modifications during differentiation, although the details by which this occurs are not clear. Although the authors used two different strategies for identifying the direct binding sites of Mcm2 on chromatin, Mcm2 enrichment at individual loci was relatively weak, suggesting Mcm2 may localize somewhat diffusely. This somewhat weakens the conclusions about the direct vs indirect effects of Mcm2 on chromatin structure and gene expression.

Overall, this paper reports an interesting set of findings that have a few caveats/limitations regarding how Mcm2 mediates these effects on chromatin during ESC differentiation.

My biggest question is about the Mcm2 CUT&RUN data, which appears to have low signal-to-noise. The authors appear to be aware of this issue, as they also used an Mcm2-FLAG line for CUT&RUN studies, with similarly low signal to noise. To be clear, this may be due to the binding properties of Mcm2, which may bind chromatin relatively broadly, causing few highly enriched peaks to be observed (similar to cohesin complex in the absence of CTCF). However, it makes the Mcm2 binding data difficult to interpret. First, most Mcm2 peaks seem to be near promoters. Promoters often have a small amount of signal in negative control (IgG or irrelevant antibody) CUT&RUN experiments, presumably due to their MNase accessibility. It is not clear to what extent Mcm2 peaks exceed background because no negative control CUT&RUN was performed. The high correlation of FLAG and Mcm2 CUT&RUN libraries might still be evident if some of this signal is due to background at TSSs. Second, the authors call 13,742 peaks, but browser tracks of some example peaks at the Pax6 and Nanog promoters show minimal enrichment relative to surrounding regions (Fig. 5I, 5S1B). I have concerns that some of these peaks called statistically significant are not biologically meaningful.

Reviewer #2 (Public Review):

It is established that different histone chaperones not only facilitate the assembly of DNA into nucleosomes following DNA replication and transcription but also are essential to stem cell maintenance and differentiation. Here the authors Xiaowei Xu et al. propose a novel role for Mcm2 DNA helicase, a subunit of the origin licensing complex Mcm2-7 in stem cell differentiation in addition to or in connection to maintaining genomic integrity in DNA replication. This study is a continuation of the authors' previously published work implicating Mcm2-Ctf4-Polα axis in the parental histone H3-H4 transfer to lagging strands. The present study is elegantly executed with a systemic analysis of the role of Mcm2 in the ES differentiation to neuronal lineage.

Major questions<br /> 1. Mouse ES cells with a mutation at the histone binding motif of Mcm2 (Mcm2-2A) grew normally, but exhibited defects in differentiation. Also, the Mcm2-2A mutation linked global changes in gene expression, chromatin accessibility and histone modifications were not apparent to the similar degree in mouse ES cells compared to NPCs.<br /> The authors suggest that the excessive amount of Mcm2 in ES cells, similar to DNA replication, safeguards the chromatin accessibility and gene expression in mouse ES cells resulting in Mcm2-2A mutant ES cells being able to restore the symmetric distribution of parental histones before cell division.<br /> What is underlying the mechanism of this difference since overabundant Mcm2 is present in both ES cells and NPCs?

2. CAF-1, Asf1a, and Mcm2 partake in similar or redundant chromatin regulation during differentiation with silencing of pluripotent genes and induction of lineage-specific genes. These processes were found commonly dysregulated in both Mcm2-2A cells and Asf1a KO ES cells, albeit with varying degrees.<br /> How can authors exclude the possibility of Mcm2 affecting the differentiation via Asf1 with which it forms a complex, as a potentially redundant mechanism in the deposition of newly synthesized or recycled histones?<br /> Can authors test potential redundancy between Mcm2 and other histone chaperones and modifiers? Can the authors rescue the NPC phenotype induced by Mcm2 -2A mutant? Can the authors rescue the Mcm2-2A phenotype by overexpression of another histone chaperone or modifier?

3. Authors argue that Mcm2 may regulate the deposition of newly synthesized or recycled histones via the ability to recycle 1. parental H3.1 and H3.3, 2. via binding directly H3-H4, and/or via 3. Pol II transcription. Which of these mechanisms may be more unique to Mcm2 compared to the other histone chaperones and modifiers?

4. Authors observed that in the ES cells the majority of Mcm2 CUT&RUN peaks were enriched with H3K4me3 CUT&RUN signals and ATAC-seq peaks and a small fraction of Mcm2 CUT&RUN peaks were engaged at the bivalent chromatin domains (H3K4me3+ and H3K27me3+). In contrast, in wild-type NPCs all the Mcm2 peaks co-localized with H3K4me3 and ATAC-seq peaks (H3K4me3+, H3K27me3-). The authors thus argued that Mcm2 binding to chromatin is rewired during differentiation citing this differential engagement of Mcm2 with the bivalent chromatin domains in ES and NPCs. What is the mechanism of Mcm2 differential engagement with the bivalent chromatin domains?

5. Authors indicated that in mouse ES cells Mcm2 CUT&RUN peaks exhibited low densities at the origins. DNA replication origins are licensed by the MCM2-7 complexes, with most of them remaining dormant. Dormant origins rescue replication fork stalling in S phase and ensure genome integrity. It is reported that ESs contain more dormant origins than progenitor cells such as NPCs and that may prevent the replication stress. Also, partial depletion of dormant origins does not affect ECs self-renewal but impairs their differentiation, including toward the neural lineage. Moreover, reduction of dormant origins in NPCs impairs their self-renewal due to accumulation of DNA damage and apoptosis.<br /> Can authors exclude the role of reduced dormant origins reflected in the reduced density of Mcm2 at the origins in the differentiation to neuronal lineages?

Reviewer #1 (Public Review):

Here, Servello et al explore the role of temperature and the temperature-sensing neuron AFD in promoting protection against peroxide damage. Unlike many other environmental threats, peroxide toxicity is expected to be temperature-dependent, since its chemical reactivity should be enhanced by higher temperatures. The authors convincingly and rigorously show that transient exposure to 25C, a condition of mild heat stress in C. elegans, activates animals' defenses against peroxides but potentially not other agents. Interestingly, this response requires the temperature-sensing AFD neurons, though whether temperature-dependent AFD activity is itself involved in this regulation is not explored. Further, the authors find that temperature regulates AFD's expression of the insulin ins-39 and provide evidence supporting the idea that repression of ins-39 at 25C contributes to enhanced peroxide defense. The authors use transcriptomic approaches to explore gene expression changes in animals in which AFD neurons are ablated, providing evidence that the FoxO-family transcription factor DAF-16 potentiates AFD signaling. However, because AFD ablation triggers effects broader than transient 25C exposure, the significance of these findings for temperature-dependent peroxide defense is somewhat unclear. Additionally, the possibility that DAF-16 (as well as another protective factor, SKN-1) function in parallel to temperature stress is consistent with many of the results shown but is not as thoroughly considered. Together, these studies identify a fascinating example of pre-emptive threat response triggered by the detection of a potentiator of that threat, a phenomenon they term "enhancer sensing." While some predictions of the specificity of this phenomenon remain untested, the paper provides intriguing insight into the potential mechanisms by which it may occur.

Major issues:

The dependence of the enhancer-sensing phenomenon on AFD leads the authors to conclude that the 25C stimulus is sensed by AFD itself, but this needs to be directly tested. To do this, they could ask whether tax-4 function is required in AFD, or use mutants in which AFD's thermosensory function is compromised.

The enhancer-sensing model is fascinating, but as it stands it is somewhat oversold. The authors could tone down the writing, indicating that this model is suggested rather than shown. Alternatively, they could more carefully test some of its predictions - for example by exploring the response to other threats (e.g. some of the toxicants described in Fig. S5) at 20C and 25C in WT and AFD-ablated animals.

The role of ins-39 remains somewhat speculative. Fig 4F shows that ins-39 mutants have a reduced induction of peroxide defense, but it seems that this could be the result of a ceiling effect. The authors' model predicts that overexpression of ins-39, particularly at 25C, should sensitize animals to peroxide damage, a prediction that should be tested directly. Further, the authors seem to assume that AFD is the relevant site of ins-39 function, but this needs to be better supported.

Most of the daf-16 and skn-1 experiments are carried out in AFD-ablated animals, making the relevance of these findings for the 25C-dependent induction of peroxide defense somewhat unclear. As the authors show, AFD ablation causes much more extensive changes than transient 25C exposure, clearly seen in slope of the line in 3C. Further, unlike 25C exposure, AFD ablation is a chronic and non-physiological state. It would be useful for the authors to be cautious in their interpretation of these findings and to be clearer about how strongly they can connect them to the "enhancer sensing" phenomenon. Along these lines, the potentiation idea could be toned down a bit. Much of the data is consistent with parallel function for daf-16 (and skn-1) - for example, Fig 5C indicates additive effects of daf-16 and 25C exposure; 6C shows that AFD ablation still has a clear effect on peroxide sensitivity in the absence of both daf-16 and skn-1; and Fig S8a shows that much of the transcriptional response to AFD ablation (along PC1) is intact in daf-16 animals.

Reviewer #2 (Public Review):

In this study, Servello and the colleagues characterize how a temperature sensing neuron AFD regulates increased resistance to hydrogen peroxide in worms cultivated at a higher temperature. They show that loss of AFD and the insulin-like peptide INS-39 produced by AFD increase H2O2 resistance similarly as high temperature growth. To understand the molecular basis, they use mRNA-seq and analysis of gene expression at the whole-genome scale and transgenic lines to show that AFD ablation and high cultivation temperature generate overlapping changes in gene expression via the function of the FOXO transcription factor DAF-16 in the intestine.

This study is built on their previous work that established C. elegans as a model to study mechanisms for sensing and resistance of H2O2, an important environmental chemical threat for living organisms. Here, the authors uncover the neuronal and molecular basis for H2O2 resistance induced by high cultivation temperature. The authors use multiple approaches, including genetics, transgenics, whole-genome gene expression analysis, to characterize "enhancer sensing" that they discovered in this study. The experiments are well designed with appropriate controls. The data analysis is comprehensive and revealing. The findings are novel and explain a common and interesting phenomenon. The new understanding generated in this study will appeal to the readers in the fields of sensory biology, signaling transduction and physiology. The implications or conclusions of a few results presented here could be further discussed or clarified in the context of several previous studies.

Reviewer #3 (Public Review):

This paper offers novel mechanistic insights into how pre-exposure to warm temperature increases the resistance of C. elegans to peroxides, which are more toxic at warmer temperature. The temperature range tested in this study lies within the animal's living conditions and is much lower than that of heat shock. Therefore, this study expands our understanding of how past thermosensory experience shapes physiological fitness under chemical stress. The paper is technically sound with most experiments or analyses carried out rigorously, and therefore the conclusions are solid. However, it challenges our current understanding of the role of the C. elegans thermosensory system in coping with stress. The traditional view is that the AFD thermosensory neuron is activated upon sensing temperature rise, and that temperature sensation through AFD positively regulates systemic heat shock response and promotes longevity in C. elegans. Thus, it is quite unexpected that AFD ablation activates DAF-16 and improves peroxide resistance. It also appears counterintuitive that genes upregulated at 25 degrees overlap extensively with those upregulated by AFD ablation at 20 degrees. I feel that it is premature to coin the term "enhancer sensing" for such a phenomenon, as their work does not rule out the possibility that AFD ablation increases resistance to other stresses that are independent of temperature regarding their toxicity or magnitude of hazard. Additional work is necessary to clarify these issues.

1. Whether the role of AFD in inhibiting peroxide resistance is related to AFD activity needs further clarification. AFD activity depends on the animal's thermosensory experience. As animals in this study are maintained at 20 degrees unless indicated specifically, the AFD displays activities starting around 17 degrees and peaks around 20 degrees. Under such condition, the AFD displays little or no activity to thermal stimuli around 15 degrees. It will be important to test whether cultivation of animals at 20 degrees improves peroxide resistance at 15 degrees, compared to 15 degrees-cultivation/15 degrees peroxide testing. The authors should also test whether AFD ablation further improves survival under peroxides at 15 degrees for animals grown at 20 degrees, whose AFD should show little or no activities at 15 degrees.

2. The importance of the thermosensory function of AFD should be verified. In the current study, the tax-4 mutation was used to infer AFD activity, but tax-4 is expressed in sensory neurons other than AFD. In addition to AFD, AWC can sense temperature and it also expresses tax-4. Therefore, influence on AFD from other tax-4-expressing neurons cannot be excluded. On the other hand, ablation of AFD removes all AFD functions, including those that are constitutive and temperature-independent. Therefore, the authors should test the gcy-18 gcy-8 gcy-23 triple mutant, in which the AFD neurons are fully differentiated but completely insensitive to thermal stimuli. These three thermosensor genes are exclusively expressed in AFD. Compared to the tax-4 mutant that is broadly defective in multiple sensory modalities, this triple gcy mutant shows defects specifically in thermosensation. They should see whether results obtained from the AFD ablated animals could be reproduced by experiments using the gcy-18 gcy-8 gcy-23 triple mutant. The authors are also recommended to investigate ins-39 expression in AFD and profile gene expression patterns in the gcy-18 gcy-8 gcy-23 triple mutant.

3. The literature suggests that AFD promotes longevity likely in part through daf-16 (Chen at al., 2016) or independent of daf-16 (Lee & Kenyon, 2009). Whatever it is, various studies show that activation of AFD and daf-16 promote a normal lifespan at higher temperature, and AFD ablation shortens lifespan at either 20 or 25 degrees. Therefore, the finding that DAF-16-upregulated genes overlap extensively with those upregulated by AFD ablation is quite unexpected (Figure 5B). The authors should perform further gene ontology (GO) analysis to identify subsets of genes co-regulated by DAF-16 and AFD ablation, whether these genes are reported to be involved in longevity regulation, immunity, stress response, etc.

4. I feel that "enhancer sensing" is an overstatement, or at least a premature term that is not sufficiently supported without further investigations. The authors should explore whether AFD ablation or pre-exposure to warm temperature specifically enhances resistance to a stressor the toxicity of which is increased at higher temperature, but does not affect the resistance to other temperature-insensitive threats.

Reviewer #1 (Public Review):

This manuscript investigates the gene regulatory mechanisms that are involved in the development and evolution of motor neurons, utilizing cross-species comparison of RNA-sequencing and ATAC-sequencing data from little skate, chick and mouse. The authors suggest that both conserved and divergent mechanisms contribute to motor neuron specification in each species. They also claim that more complex regulatory mechanisms have evolved in tetrapods to accommodate sophisticated motor behaviors. While this is strongly suggested by the authors' ATAC-seq data, some additional validation would be required to thoroughly support this claim.

Strengths of the manuscript:

1) The manuscript provides a valuable resource to the field by generating an assembly of the little skate genome, containing precise gene annotations that can now be utilized to perform gene expression and epigenetic analyses. The authors take advantage of this novel resource to identify novel gene expression programs and regulatory modules in little skate motor neurons.

2) Cross-species RNA-seq and ATAC-seq data comparisons are combined in a powerful approach to identify novel mechanisms that control motor neuron development and evolution.

Weaknesses:

1) It is surprising that the analysis of RNA-seq datasets between mouse, chick, and little skate only identified 5 genes that are common between the 3 species, especially given the authors' previous work identifying highly conserved molecular programs between little skate and mouse motor neurons, including core transcription factors (Isl1, Hb9, Lhx3), Hox genes and cholinergic transmission genes. This raises some questions about the robustness of the sequencing data and whether the genes identified represent the full transcriptome of these motor neurons.

2) The authors suggest based on analysis of binding motifs in their ATAC-seq data that the greater number of putative binding sites in the mouse MNs allows for a higher complexity of regulation and specialization of putative motor pools. This could certainly be true in theory but needs to be further validated. The authors show FoxP1 as an example, which seems to be more heavily regulated in the mouse, but there is no evidence that FoxP1 expression profile is different between mouse and skate. It is suggested in Fig.5 that FoxP1 might be differentially regulated by SnaiI in mouse and skate but the expression of SnaiI in MNs in either species is not shown.

3) In their discussion section the authors state that they found both conserved and divergent molecular markers across multiple species but they do not validate the expression of novel markers in either category beyond RNA-seq, for example by in situ or antibody staining.

Reviewer #2 (Public Review):

The cartilaginous fish Leucoraja erinacea (little skate) exhibits core features of tetrapod locomotion, thus it is a key species to study conserved principles of tetrapod motor neuron development. Baek et al. provide a new and improved version of the little skate genome, which will be of great interest to the field of comparative genomics and evolutionary biology. In addition, the manuscript uses already published RNA-seq data from skate, mouse and chicken, as well as newly generated ATAC-seq data in little skate to try to reach a better understanding of the regulatory networks underlying motor neuron specification in these different species. While the question is of key importance, the bioinformatics comparisons followed by the authors seem inadequate and deeply biased. All comparative analyses are performed with lists of genes that for each species are selected following different criteria or compared with different neuronal populations, introducing important biases that will later limit the conclusions driven by the authors. Moreover, additional key aspects of evolution, such as paralog substitution or expression of species-specific genes should also be studied. Finally, the lack of experimental validations also reduces the impact of the conclusions, which at this point are highly speculative.

Reviewer #3 (Public Review):

Yoo et al. present a greatly improved assembly and annotation of the little skate genome. Using this new assembly and annotation, the authors re-analyze previously published gene expression data from little skate motor neurons, which were initially analyzed using instead zebrafish gene models. New in this paper is the ATAC-seq showing regions of chromatin accessibility, which was made possible by the improved assembly. Finally, the authors search for predicted transcription factor binding motifs in the vicinity of little skate motor neuron-specific genes to arrive at a model for gene regulatory networks operating in this species. They compare this gene expression and accessibility data and predicted network connections to those observed or predicted in other vertebrates (i.e. tetrapods).

The improved assembly and reanalysis of gene expression are of great use for the study of vertebrate motor neuron development and evolution. The ATAC-seq data are new and highly valuable. The thorough analysis of predicted binding sites is impressive and hints at differences in gene regulatory network architecture between cartilaginous fish and tetrapods.

A major weakness of this paper is the fact that the transcription factor binding site analysis is entirely dependent on bioinformatic predictions, as pointed out by the paper's limitations statement. The authors recognize that there is no actual binding site data obtained using little skate proteins, cells, or DNA (e.g. no ChIP-seq, no knockdowns, no cis-regulatory DNA reporters or mutations, etc). Unfortunately, this results in several unsubstantiated claims made throughout the paper, in which the presence of predicted binding sites is taken as a regulatory connection between genes.

Reviewer #1 (Public Review):

Switching between epithelial and mesenchymal populations is an important stage for cancer growth and metastasis but difficult to study as the cells in this transition are rare. In this study Xu et al investigate changes the splicing regulator environment and changes in specific splice events by monitoring colon cancer cell populations that have epithelial and mesenchymal properties (so are potentially in transition) compared their epithelial partners. Using these potentially transitioning cells should reveal new insights into the causative changes occurring during EMT, a key life threatening step in colon cancer progression, and other cancers too.

The authors were trying to establish if changes in the splicing environment occurred between epithelial and quasi-mesenchymal cells and to what extent this is important for colon cancer in establishing gene expression programmes and cell behaviour related to metastasis. The take home message is that these more "plastic" mesenchymal cells are expressing the mesenchymal transcription factor ZEB1 and reducing expression of the epithelial splicing factor ESRP1 (as well as some other RBPs). The FACS analysis showing that over-expression of ESRP1 alone can switch cell population ratios is very clear and indicates that reduction of this RBP plays a key role in making cells more metastatic. The lentiviral overexpression of CD44s and NUMB2/4 had very dramatic effects on increasing metastatic cellular properties. The clinical stratification analysis of splice isoforms and ZEB1/ESRP1 expression was very informative for understanding what is happening in actual tumours. The methods used and results from these studies are likely to have an impact on understanding the gene expression changes that take place during EMT.

Strengths. The authors have used cell lines that model switching cells between epithelial and quasi-mesenchymal, based on expression of the markers Epcam (epithelial cell adhesion molecule expressed in epithelial cells) and CD44. The study utilises shRNA-mediated knockdown and lentiviral overexpression of ESRP1 and splice isoforms, and monitors endogenous mRNA splice isoforms by RNAseq and qRTPCR, protein isoforms by western, cell surface expression of EpCAM and CD44 using FACS and metastatic potential using a mouse model, and patient gene expression data from TCGA.

Weaknesses: Some of the data here might be novel for colon cancer, but the roles of these RNA binding proteins and ESRP1 target exons are better known in other cancers. Both CD44 and NUMB are known ESRP1 targets already in cells undergoing plasticity (e.g. PMID: 30692202). RBM47 is already known to be downregulated in EMT and quaking upregulated (PMID: 28680090; PMID: 27044866). There is also a lot of literature on ESRP1 expression in cancer and EMT. This should be better discussed.

Reviewer #2 (Public Review):

In the submitted article, Xu and co-workers have explored the alternative splicing of CD44 and NUMB isoforms responsible for promoting epithelial-to-mesenchymal transition in quasi-mesenchymal and highly metastatic subtype of colon cancer. In this regard, the authors have performed numerous RNA-seq and Gene Ontology analyses to identify differentially expressed RNA binding proteins and their associated pathways to understand the related alternative splicing events. CD44s and NUMB2/4 spliced isoforms have been identified as promoting the invasive and metastatic properties while negatively affecting the proliferation of the HCT116 and SW480 cells in Zeb1-ESPR1-dependent manner. Unfortunately, there exists discrepancy and inconsistency at a large extent in the experimental data, along with lack of novel findings as CD44 and NUMB alternative splicing is well investigated in other types of cancers.

Reviewer #1 (Public Review):

Detecting a small object is challenging, particularly when the animal is moving. This is because self-generated visual motion interferes with visual perception. Turner et al. established a new method to record neural activity simultaneously from multiple populations of local visual feature detecting neurons (or lobula columnar projection neurons (LCs)) by improving conventional calcium imaging with a new pre-synapse restricted fast calcium indicator and careful image alignment. They found that LCs can be categorized into four types depending on their visual feature selectivity. By simultaneously recording from multi-type LCs, the authors found, for the first time, that several LC types covary their activities, which improves visual feature encoding. Then, the authors performed calcium imaging from walking flies and found that the visual responses are generally suppressed during walking, particularly in small object-detecting populations. Some portion of shared activity among LC populations was explained by the walking-related modulation. Similarly, global visual motion, which is expected from naturalistic fly's walking, suppressed responses to local visual features in a motion coherence-dependent manner. The suppressive effect was prominent when the visual motion was fast and contained low spatial frequency components. Finally, visual and walking-related signals independently suppressed neural responses during saccadic events. These enormous pieces of evidence nicely fit the idea that the fly engages in visual feature processing only during straight walks while the visual inputs are effectively shut down during sharp turns when contamination by self-generated visual motion is non-negligible. On the other hand, responses to important visual stimuli, such as looming produced by predators, are maintained in any conditions. The authors provided a comprehensive view of how a visual circuit operates in a natural condition and further strengthened the growing idea shared across species that sensory perception is dynamically structured during movement.

Reviewer #2 (Public Review):

This study examines the encoding of distinct visual features during self-motion and reveals distinct mechanisms that contribute to the suppression of features that may be corrupted during self-motion - one based on motor output and one based on the resulting visual input. The authors develop an imaging approach to measure neural activity across many glomeruli, which enables analysis in terms of population codes. They first demonstrate that even though movement strongly alters the response in individual glomeruli, a population-based readout is still able to decode stimulus identity. They then demonstrate that this modulation is primarily suppression of glomeruli that respond to local features, while global features (i.e. looming) are unaltered. Finally, through a combination of visual stimulus manipulations that mimic the effect of movement and analysis of responses relative to behavioral epochs, they show that both the visual input and a motor signal contribute to this suppression.

Together, this provides an elegant explanation of how different signals combine to adapt sensory processing to ongoing behavior. The experiments are cleverly designed and the results are clearly presented, with few technical concerns. The only significant concern entails how well their imaging isolated the visual projection neurons they were targeting.

This study is likely to have a significant impact as it provides a new view on a timely question in visual neuroscience. The study also opens up clear future directions to determine how these two signals are generated and integrated into visual processing, at the neural circuit level. Finally, it provides intriguing parallels to the impact of eye movements on the mammalian visual system.

Reviewer #3 (Public Review):

This manuscript presents a nice approach for performing population recordings from the optic glomeruli of Drosophila, allowing for explorations of how visual stimuli are encoded at a population level. The authors use a combination of behavioral recordings and visual perturbations to identify two mechanisms that contribute to the suppression of visual responses during body saccades: one motor-related and one visual. Overall this study presents a nice combination of imaging and analysis to determine mechanisms by which the visual system tunes out signals associated with self-movement to produce a reliable encoding of the visual world. I do have some concerns about the sources of the gain modulation that they describe across the population, and was confused by some aspects of the framing in terms of self-motion and visual feature decoding.

Joint Public Review:

This manuscript by Harris and Dunn investigates the neurophysiology underlying the optokinetic reflex (OKR), by which image motion on the retina triggers a compensatory eye movement. The strength of the OKR varies with direction of motion, and the present study looks for the origins of that asymmetry in neural signals emerging from the retina, specifically the responses of On-direction-selective retinal ganglion cells (oDSGCs). The authors found that compared to oDSGCs in the inferior retina, superior oDSGCs exhibit higher firing rate and broader tuning width under both high and low contrast conditions. Using whole-cell patch clamp recording, imaging and modeling, they found that the enhanced excitation of superior oDSGCs not only accounts for the higher firing rate of these cells but also broadens their spike tuning curves through spike thresholding. To link these retinal signal to behavior, they used the difference in spike rate between superior and inferior oDSGCs to predict vertical optokinetic responses and show matching results.

This is the first study that systematically compares spiking, synaptic and dendritic properties between superior and inferior oDSGCs. The functional differences between two cell types are interesting and significant, and provide a plausible explanation of OKR. This study also raises the important point that E/I balance is often insufficient to account for the spiking behavior. The data presented are of high quality and comprehensive. Suggestions for revision include clarification of technical issues, and consideration of alternative interpretations. Furthermore, the paper could improve from a better focus on the core results.

Reviewer #1 (Public Review):

The authors sought to establish canine tissue-specific organoids for propagation, storage and potential use in biomedical and translational medicine.

Strengths - The project is ambitious in aim, seeking to raise 6 tissue-specific, stem cell-derived organoid lines.

Weaknesses -

1. While the manuscript refers to stem cell lines, no evidence of progressive organoid morphogenesis has been shown from undifferentiated single stem cells or stem cell clusters. This omission makes it difficult to distinguish true organoids from surviving pieces of parental tissue that the authors actually include within their cultures. The authors infer that high order tissue complexity can be generated within in short term 3D cultures. For example, their kidney organoids contained glomeruli, renal tubules and a Bowman's'capsule. These remarkable findings contrast with a previous study by Chen et al 2019 that showed kidney organoids had restricted morphogenic capacity, forming only simple epithelial dome-like structures (Chen et al 2019). Although the Chen study was cited, the major differences in study findings were not discussed. In the current study, no compelling evidence is provided for the integrated assembly of the glomerular microvascular capillary network, the glomerular epithelial capsule and complex tubular epithelial collecting ducts, during organoid growth.

2. The potential of the organoids for freezing, storage and re-culture is unclear from the data presented.

3. Organoid capacity for regenerative growth in xenograft models has not been tested.

4. Figure 4 lacks appropriate positive and negative tissue controls.

5. Gene expression differences between tissues and organoids are inadequately explained.

6. Methodological detail is sparse. It is not clear how tissue biopsies are obtained, what size they are and how they are processed for organoid preparation.

7. The manuscript as a whole is poorly focussed and difficult to follow. The introduction is repetitive with only weak relevance to the main experiments.

Appraisal - The lack of morphogenesis and xenograft data undermines confidence that the authors have achieved their aims. The above concerns are also likely to hamper utility of the methods for the scientific community.

Reviewer #2 (Public Review):

Zydryski et al. develop a comprehensive toolbox of organ-specific canine organoids. Building on previous work on kidney, urinary bladder, and liver organoids, they now report on lung, endometrium, and pancreatic organoids; all six organoid lines are derived from two canines. The authors attempt to benchmark these organoids via histological, transcriptomic, and immunofluorescence characterization to their cognate organs. These efforts are a welcome development for the organoid field, broaden the scope of use to studies with canine models, and seek to establish robust standards. The organ specific RNAseq dataset is also likely to be useful to other researchers working with the canine model.

A key methodological advance would appear to be that the authors culture these organ-specific organoids using a common cell culture media. This is not the typical protocol in the organoid field; however, the authors do not provide enough information in the manuscript to evaluate if this is a good choice. Furthermore, it is likely that the authors were successful because they included additional tissue components in the co-culture for the organoids which might have provided the necessary tissue specific cues, but the methodological details to reproduce this and the technical evaluation of this approach are missing.

The authors also directly compare the transcriptional responses of the organoids with the organs, but this is a challenging enterprise given that the organoid models do not incorporate resident immune cells and typically are composed only of epithelial cells. This lack of an 'apples to apples' comparison might explain why in many cases the organoids and organs are highly divergent; however, it could also be that the common cell culture media did not lead to specific maturation of cell types.

Reviewer #3 (Public Review):

Zydrski et al. describe the generation and characterization of multiple adult tissues from canines. While canine derived organoids could potentially be advantageous over murine and human organoids, the novelty of generation and characterization is limited, as organoid systems are now being rapidly genetically editing using CRISPR technologies and modeled within immunocompetent environments. Certain points limit my enthusiasm.

First, the authors do not support the use of serum (FBS) in their media and why they include the same growth and differentiation factors across all tissue types.

Second, while bulk RNA sequencing data shows similarity per certain genes to the corresponding tissue, there is a lack of detailed characterization of what passage these organoids were harvested and how they change over time. Do they become more stem like and are they genetically stable?

Third, it would be important to demonstrate that these organoids can be genetically manipulated or be exposed to drugs and how they might be beneficial over murine and human organoids.

Fourth, the organoid complexity is not clear and cannot be ascertained from bulk RNA sequencing- for example, do kidney organoids recapitulate canonical markers at the protein level of proximal tubules, distal convoluted tubules, etc. Are different lung cells represented (AT1/AT2/club) and what is the composition of these cells? Why are these cells selected for?

Fifth, as the authors note, methodically these canine organoids have been developed before from other tissues. For these reasons, my enthusiasm is diminished and unfortunately many of the necessary experiments for further consideration appear out of the scope of the study.

Reviewer #1 (Public Review):

Voltage-clamp fluorometry combines electrophysiology, reporting on channel opening, with a fluorescence signal reporting on local conformational changes. Classically, fluorescence changes are reported by an organic fluoropohore tethered to the receptor thanks to the cysteine chemistry. However, this classical approach does not allow fluorescent labeling of solvent-inaccessible regions or cytoplasmic regions. Incorporation of the fluorescent unnatural amino acid ANAP directly in the sequence of the protein allows counteracting these limitations. However, expression of ANAP-containing receptors is usually weak, leading to very small ANAP-related fluorescence changes (ΔFs).

In this paper, the authors developed an improved method for expression of full-length, ANAP-mutated proteins in Xenopus oocytes. In particular, they managed to increase the ratio of full-length over truncated proteins for C-terminal ANAP incorporation sites. Since C-terminally truncated P2X receptors are usually functional, it is important to maximize the full-length over truncated protein ratio to have a good correspondence between the observed current and fluorescence. Using their improved strategy, they screened for ANAP incorporation sites and ATP-mediated ANAP ΔFs along the whole structure of the P2X7 receptor: extracellular ligand binding domain (head domain), M2 transmembrane segment (gate), as well as a large extracellular domain specific for the P2X7 subtype, the "ballast" domain. The functional role of this domain and its motions following ATP application are indeed unknown. Monitoring ANAP fluorescence changes in this region following ATP binding provides a unique way to study those questions. By analyzing ATP-induced ΔFs from different parts of the receptors, the authors conclude that the ATP-binding domain mainly follows gating, while intracellular "ballast" motions are largely decoupled from ATP-binding

Strengths of the paper:<br /> This paper provides an improved method for efficient unnatural amino acid incorporation in Xenopus oocytes. Thanks to this technique, they managed to enhance membrane expression of ANAP-mutated P2X7 receptors and observed strong fluorescent changes upon ATP application. The paper furthermore describes an impressive screen of ANAP-incorporation sites along the whole protein sequence, which allows them to monitor conformational changes of solvent-inaccessible regions (transmembrane domains) and cytoplasmic regions that were not accessible to cysteine-reactive fluorophores. This screen was performed in a very thorough manner, each ANAP mutant being characterized biochemically for membrane expression, as well as in term of fluorescence changes. The limitations of the approach -small ΔF upon ATP application on wt receptors, problem of baseline fluorescence variations in presence of calcium- are well explained. Overall, this study should thus not only serve as a guide to anyone willing to perform VCF on P2X7 receptors but it should be useful to the whole community of researchers using unnatural amino acids. Thanks to orthogonal labeling with TMRM and ANAP, the authors managed to simultaneously monitor the motions of the extracellular and intracellular domains of P2X7. Finally, they propose methods to simultaneously monitor intracellular domain motion and downstream signaling.

Weaknesses:<br /> Although the fluorescence screen is impressive and well conducted, the biological conclusions remain superficial at this stage. The paper furthermore lacks quantitative analysis. Finally, the title only reflects a minor part of the paper and is therefore not representative of the paper content.

Reviewer #2 (Public Review):

The authors aimed to elucidate the structural rearrangements and activation mechanisms of P2X7 upon ATP application by voltage clamp fluorometry (VCF) using fluorescent unnatural amino acid (fUAA) and other fluorophores. They improved the fUAA methodology and detected ATP binding evoked changes in the ATP binding region and other regions. They also observed facilitation of fluorescence (F) changes by repeated application of ATP associated with gating. The F change in the cytoplasmic ballast region was minor, and with their experimental data, they discussed this region is involved in activation by other cytoplasmic factors, such as Ca2+.

The strengths of the study are as follows.<br /> (1) fUAA methodology was improved to enable experiments by one time injection to oocytes (Figs. 1 and Suppl).<br /> (2) They performed intensive mutagenesis study of as many as 61 mutants (Figs. 3, 4, 5).<br /> (3) A careful evaluation of the successful Anap incorporation and formation of full length proteins was performed by western blot analysis (Fig. 2).<br /> (4) By three wave lengths F recording, they obtained better information, i.e. they classified the interpretation of F changes to, quenching, dequenching, increase in polarity and decrease in polarity (Fig. 3E).<br /> (5) They detected F changes upon ATP application in various regions of P2X7, but not many in the ballast region, showing that the ballast region is not well involved in the ATP evoked gating.<br /> (6) They analyzed the kinetics of F and current and their changes upon repeated ATP application to approach the known facilitation mechanisms. The data are very interesting. They concluded that it is intrinsic to the P2X7 molecule and that it is associated not with the ATP binding but with the gating process (Figs. 3F, 4D, 6A).<br /> (7) They performed interesting analysis to clarify the mechanisms of activation by cytoplasmic factors, especially Ca2+ entered via P2X7 (Fig. 6).

The weaknesses of the study are as follows.<br /> (1) As both structures of P2X in the open and closed states are already solved, and the ATP binding evoked structural rearrangements from the ATP binding site to the gate are already known in detail. The structural rearrangements detected in the extracellular region (Fig. 3) and TM region (Fig. 4) upon ATP application are just as expected. The impact and scientific merits of this part are rather limited.<br /> (2) The facilitation mechanism is of high interest. The authors showed it is intrinsic to P2X2 and associated with the gating rather than ATP binding. However, this reviewer cannot have better understanding about the actual mechanism. (a) What is the mechanistic trigger of facilitation? Possibilities are discussed, but it appears there is no clear answer with experimental evidences yet. (b) How is the memory of the 1st ATP application stored in the molecule, i.e. how does the P2X7 structure just before the 1st application differ from that just before the 2nd application of ATP?<br /> (3) The structural rearrangement of the CaM-M13 region (Fig. 6B, C) attached at the C-terminus by Ca2+ influx through P2X7 upon ATP application is natural due course and not very surprising. Also, it is not accepted as an evidence proving that Ca2+ is the mediator of facilitation.<br /> (4) As to the ballast region, data showed its limited involvement in the ATP-induced structural rearrangements. The function of the ballast region is not clear yet. A possible involvement in GDP binding and/ or metabolism is discussed, but there is no clear experimental evidence.

Reviewer #3 (Public Review):

This research contributes to optimizing the amber stop-codon suppression protocol for voltage-clamp fluorometry (VCF) experiments using Xenopus oocyte heterologous expression system. By in vitro RNA synthesizing the tRNA and tRNA synthetases, combined with the dominant-negative release factor initially developed by Jason Chin's lab, L-Anap can be site-specifically labeled to proteins by a single microinjection of a mixture of molecular components into the cytoplasm of oocytes. Although it avoids nuclear microinjection to oocytes, it adds more RNA synthesis steps. This strategy of using eRF dominant negative variant (eRF1-E55D), was previously applied to the Anap incorporation system using mammalian cell lines and model proteins (Gordon et al, eLife, 2018). In this previous 2018 paper, with eRF1-E55D, the percentage of full-length protein expression increased substantially. Using oocytes in this paper, this percentage apparently did not increase significantly as shown in Fig. 1D, different from the previous paper. Nevertheless, the overall expression level increased successfully by this method, which could facilitate macroscopic fluorescence measurements, especially considering that L-Anap is relatively dim as a fluorophore.

Anap fluorescence change was measured mostly using its environmental sensitivity, which has limited information in interpreting structural changes. The structural mechanisms proposed could be potentially strengthened and the conclusions could be further validated by combining FRET or other distance ruler experiments with the VCF method. The engineered CaM-M13 FRET experiments mostly report the calcium entry, not measuring the rearrangements of P2X7 directly. In addition, results of ATP dose-response relationship for channel activation correlated with ATP dose-dependent Anap fluorescence change, especially for sites showing a large percentage of ATP-induced change in fluorescence, would provide more insights regarding the allosteric mechanism of the channel.

Reviewer #1 (Public Review):

This study presents a series of experiments that investigate maternal control over egg size in honey bees (Apis mellifera). Honey bees are social insects in which a single reproductive female (the queen) lays all the eggs in the colony. The first set of experiments presented here explore how queens change their egg size in response to changes in colony size. Specifically, they show that queens have relatively larger eggs in smaller colonies, and that egg size changes when queens are transplanted into colonies of a different size (i.e. confirming that egg size is a plastic trait in honey bee queens). The second set of experiments investigates candidate genes involved in egg size determination. Specifically, it shows that Rho1 plays a role in determining egg size in honey bee queens.

A strength of the study is that it combines both manipulative field (apiary) experiments and molecular studies, and therefore attempts to consider broadly the mechanisms of plasticity in egg size. The link between these two types of dataset in the manuscript, however, is not strong. While the two parts are related, the molecular experiments do not follow from the conclusions of the field experiments but rather run in parallel (both using the same initial treatments of queens from large v small colonies).

Another strength of the study is the focus on social cues for egg size control in a social insect. Particularly interesting is data showing that queens suddenly exposed to the cues of a larger colony (even where egg-laying opportunities did not actually increase) will decrease their egg size, in the same way as queens genuinely transplanted to larger colonies. That honey bee queens can control their egg sizes in response to cues in the colony is not unexpected, given that queens are known to vary egg size based on the cell type they are laying into (queen, drone or worker cell). Nevertheless, it is interesting to show that worker egg sizes over time are also mediated by social cues.

A weakness of the study is that the consequence of egg size on egg development and survival in honey bees is not made clear. The assumption is that larger egg size compensates for smaller colonies in some way. Do smaller eggs (i.e. those laid in large colonies) fare worse in smaller colonies than they do in large colonies? Showing that the variation in egg size is biologically relevant to fitness is an important piece of the puzzle.

Also, the relationship between egg number and egg size in honey bees remains rather murky. Does egg size depend at least in part on daily egg laying rate (which is sure to be greater in larger colonies)? The study makes an effort to explore this by preventing queens from laying for two weeks and then comparing their egg size when they resume to those that did not have a pause in laying. Although egg size did not vary between the groups in this case, it is unclear whether the same effect would be seen if queens had simply been restricted from laying at such high rates (e.g. if available empty brood cells had been reduced rather than removed entirely).

Overall this study makes new contributions to our understanding of maternal control over egg size in honey bees. It provides stepping stones for further investigation of the molecular basis for egg size plasticity in insects.

Reviewer #2 (Public Review):

This paper builds on recent work showing that honeybee queens can change the size of the eggs they lay over the course of their life. Here the authors identified an environmental condition that reversibly causes queens to change their egg sizes: namely, being in a relatively small or large colony context. Recently published work demonstrated the existence of this egg size plasticity, but it was completely unknown what signaled to the queen. In a series of simple and elegant experiments they confirmed the existence of this egg size plasticity, and narrowed down the set of environmental inputs to the queen that could be responsible for signaling the change in the environment. They also began the work of identifying genes and proteins that might be involved in controlling egg size. They did a comparative proteomic analysis between small-egg-laying ovaries and large-egg-laying ovaries, and then selected one candidate gene (Rho1). They showed that it is expressed during oogenesis, and that when it is knocked down, eggs get smaller.

The experiments on honeybee colonies are well-designed, and they provide fairly strong evidence that the queens are reversibly changing egg size and that it is (at least some component of) their perception of colony size that is the signal. One minor but unavoidable weakness is that experiments on honeybees are necessarily done with small sample sizes. The authors were clear about this, however, and it was very effective that they showed all individual data points. Alongside the previous work on which this paper builds, I found their core results to be rather convincing and important.

I found the parts of the paper on oogenesis to be useful, but overall less informative in answering the questions that the authors set out for those sections. On balance, I think the best way to interpret the oogenesis results is as "suggestive and exploratory". For instance, the experiment aimed at understanding the relationship between egg-laying rate and egg size does not include a direct measurement of egg-laying rate, but instead puts queens in a place with no suitable oviposition sites. The proteomic analysis was fine, but since they were using whole ovaries, with tissue pooled across all stages of oogenesis including mature oocytes, I would be cautious in interpreting the results to mean that they had identified proteins involved in making larger eggs. These proteins might just as easily be the proteins that are put into larger eggs. In fact, for the one candidate gene that is examined, its transcripts seem as though they are predominantly in the oocyte cell itself rather than in the supporting cells that actually control the egg size (although it is hard to tell from the micrographs without a label for cell interfaces).

On that note, with the caveat that the sample sizes are quite small, I agree that there is some evidence that Rho1 is involved in honeybee oogenesis. If this was the only gene they knocked down, and given that it results in a small size change with such a small sample size, it strikes me as a bit of a stretch to say that these results are evidence that Rho1 plays an important role in egg size determination. It is essential to know if this is a generic result of inhibiting cytoskeletal function or a specific function of Rho1. That is beyond the scope of this study, but until those experiments are done, it is hard to know how to interpret these results. For context, in Drosophila, there are lots and lots of genes such that if you knock them down, you get a smaller or differently shaped egg, including genes involved in planar polarity, cytoskeleton, basement membrane, protrusion/motility, septate junctions, intercellular signaling and their signal transduction components, muscle functions, insect hormones, vitellogenesis, etc. This is helpful, perhaps, for thinking about how to interpret the knockdown of just one gene.

Overall, I found the results to be technically sound, and there are several clever manipulations on honeybee colonies that will doubtless be repeated and elaborated in the future to great effect. The core result-that queens can change the size of their eggs quickly and reversibly, in response to some perceived signal-was honestly pretty astonishing to me, and it reveals that there are non-nutritive plastic mechanisms in insect oogenesis that we had no idea existed. I look forward to follow-up studies with interest.

Joint Public Review:

This article reports the results of an observational study in 312 cancer patients to assess post-acute sequelae of SARS-CoV-2 infection (PASC). The descriptive results provide the type of persistant symptoms and their frequency among 188 patients. This information is of interest and adds on to the existing literature.

Strengths:

-The topic is of interest.<br /> -The study has a long-term follow up.<br /> -Data came from both PROs and patients' electronic medical records.

Weaknesses:

-Information about patients' consent and regulatory approval is not provided.<br /> -The relation between the disease stage or anticancer therapy and long covid is missing.<br /> -The impact of long covid on cancer outcome is not shown.

The article describes the main symptoms associated with long covid. However, despite the longitudinal follow-up, a more detailed analysis of the median duration of each symptom is not shown.

Reviewer #1 (Public Review):

The manuscript by Eliazer et al. identifies the Notch ligand Dll4 as a myofiber-derived regulator of muscle stem cells (satellite cells, SCs). The amount of Dll4 surrounding individual SCs on single fiber preparations correlates with the level of Pax7 protein in those cells. Genetic removal of Dll4 from fibers results in: 1) a distribution of Pax7 levels in remaining SCs that skews towards the lower end; and 2) a phenotype similar to, but weaker than, that previously published for removal of the essential Notch pathway transcriptional regulator RBP-J from SCs (including propensity of SCs to spontaneously enter the differentiation program and a deficient regenerative response). Genetic removal of Mib1 from fibers led to loss of Dll4 clustering at SCs and a phenotype similar to loss of Dll4. The authors conclude that Dll4 maintains a continuum of diverse SC states during quiescence, perhaps contributing to which SCs are prone to self-renewal vs. differentiation.

It is accepted that the myofiber is a key niche cell for SCs, but the number of known myofiber-derived niche factors is very small and mechanisms are not well characterized. Furthermore, it is established that Notch signaling in SCs is critical to maintenance of SC quiescence, yet the source and identify of the relevant Notch ligands is not clear. Therefore, the elegant genetic identification of Dll4 as a myofiber niche factor is of high significance. The conclusion about SC states may be somewhat premature, and I have questions about how some of the experiments were performed, but overall this is a very useful paper for the field.

Reviewer #2 (Public Review):

The work by Eliazer et al investigates the role of Dll4 spatial heterogeneity on myofibers in maintaining MuSC diversity. The authors show on isolated myofibers that individual MuSC exhibit different intensities, by immunofluorescence analysis, of Pax7 and Ddx6, expressed in quiescent MuSC, and that there is a positive correlation between the intensities of the two quiescence markers. They further isolated MuSC high, medium and low Pax7 from the Pax7-nGFP transgenic mouse and validated in vitro that that the Pax7 high are slower in entering the cell cycle and expressing myogenin. To understand whether diversity of factor on myofibers could regulate this spatial diversity, the authors focused on Notch signaling. By comparing by microarray data Notch ligands during postnatal muscle growth, they show that Dll4 showed the most enrichment as cells transition to quiescence. By immunofluorescence on isolated myofibers, the authors show heterogeneity of Dll4 localization across the myofiber, with enriched clusters around MuSC. The authors monitored along individual myofibers the distribution of Dll4 and found no correlation with the distance from the NMJ. Upon myofiber specific deletion of Dll4, the authors show that MuSC exhibit downregulation of Pax7 and Ddx6, as well as a reduced number of MuSC in tissues and increased expression of MyoD and myogenin. Upon injury, mice in which Dll4 was deleted in myofibers exhibited reduced myofiber cross-sectional area, indicating a defect in the repair process. By using mice in which Mib1, an activator of Notch signaling, is deleted in myofibers, the authors show reduced Dll4 intensity and reduced diversity of Pax7 expression in MuSC as well as impaired regeneration. Understanding how the microenvironment regulate MuSC diversity is relevant to dissect their heterogeneity. The findings are interesting and novel and the manuscript is well written. However, while the authors report diversity of Dll4 and Mib1 in myofibers, the approach of genetic deletion complete ablates gene expression, and it does not necessarily modulate spatial distribution. Thus, additional experiments are required in order to fully support the authors' interpretation.

Reviewer #3 (Public Review):

In the submitted manuscript, Eliazer et. al. conclude that Dll4 and Mib present on myofibers maintain a continuum of SC fates providing SCs capable of regenerating muscle and repopulatin the SC niche. The data provide new insights into the maintenance of SCs, demonstrating niche-derived factors are responsible for regulating SC behavior. Loss of either Dll4 or Mib from the myofiber reduces SC numbers and impairs muscle regeneration. Overall the data provide compelling evidence that niche-derived Dll4 and Mib regulate SC fate, however, whether the interaction maintains a continuum of SC fates as concluded by the authors is insufficiently supported by the data provided.

One significant issue with the manuscript is the "discovery" of an SC continuum related to the relative levels of Pax7 expression. A similar continuum was established nearly a decade ago by Zammit et al., 2004 and Olguin et al., 2004 and thus, is not new. The authors need to reference the work and discuss the prior published data with regard to the observations in the current manuscript. The data establishing a continuum of SCs and the relationship to Pax7 protein levels can largely be eliminated and referenced by the two former manuscripts. For example, these manuscripts establish that elevated Pax7 levels drive quiescence and low Pax7 levels correlate with differentiation. The data from these manuscripts establish that SCs with modest Pax7 protein levels can acquire quiescence accompanied by increases in Pax7 protein

The data relating the level of Pax7 expression with Dll4a and Mib are intriguing but the authors do not establish a direct relationship, demonstrating that Dll4 or Mib regulate Pax7 levels. An alternative explanation is that Dll4 and Mib inhibit differentiation and thus promote SC quiescence indirectly. This is a critical distinction, as the authors could be correct and Dll4 via Mib regulate SC fate.<br /> It is unclear that the loss of Dll4 or Mib reduce diversity of SCs. If these repress differentiation then their loss would be expected to enhance differentiation and reduce SC numbers, which is what the data demonstrate. No direct experiments demonstrate that Dll4 regulates the levels of Pax7 protein, the data provided show a correlation of higher Pax7 protein if Dll4 is present.

Finally, the injury data provided are for 4d post injury and thus, the data may represent a delay in regeneration as opposed to a failure to regenerate. At 30 d post injury regeneration is typically considered complete. How do wild type and Dll null as well as Mib null muscle compare at 30d post injury.

In summary, the data are intruiguing and suggest that Dll4 regulates satellite cell fate and maintains quiescence of satellite cells or inhibits their differentiation. Some additional data will resolve which of these outcomes is likely.

Reviewer #1 (Public Review):

In this study, Sims et al. evaluate how system-level brain functional connectivity is associated with cognitive abilities in a sample of older adults aged > 85 years old. Because the study sample of 146 normal older adults has lived into advanced years of age, the novelty here is the opportunity to validate brain-behavioral associations in aging with a reduced concern of the potential influence of undetected incipient neuropsychological pathology. The participants afforded resting-state functional magnetic resonance imaging (rs-fMRI) data as well as behavioral neuropsychological test assessments of various cognitive abilities. Exploratory factor analysis was applied on the behavioral cognitive assessments to arrive at summary measures of participant ability in five cognitive domains including processing speed, executive functioning, episodic memory, working memory, and language. rsfMRI data were submitted to a graph-theoretic approach that derived underlying functional nodes in brain activity, the membership of these nodes in brain network systems, and indices characterizing the organizational properties of these brain networks. The study applies the classification of the various brain networks into a sensory/motor system of networks and an association system of network, with further sub-systems in the latter that includes the frontoparietal network (FPN), the default-mode network (DMN), the cingulo-opercular network (CON), and the dorsal (DA) and ventral (VA) attention networks. Amongst other graph metrics, the study focused on the extent to which networks in these brain systems were segregated (i.e., separable network communities as opposed to a more singular large community network). Evaluation of the brain network segregation indices and cognitive performance metrics showed that in general higher network functional segregation corresponds with higher cognitive performance ability. In particular, this association was seen between the general association system with overall cognition, and the FPN with overall cognition, and processing speed.

The results worthy of highlighting include the documentation of oldest-old individuals with detectable brain neural network segregration at the level of the association system and its FPN sub-system and the association of this brain functional state notably with general cognition and processing speed and less so with the other specific cognitive domains (such as memory). This finding suggests that (a) apparently better cognitive aging might stem from a specific level of neural network functional segregation, and (b) this linkage applies more specifically to the FPN and processing speed. These specific findings inform the broader conceptual perspective of how human brain aging that is normative vs. that which is pathological might be distinguished.

To show the above result, this study defined functional networks that were driven more by the sample data as opposed to a pre-existing generic template. This approach involves a watershed algorithm to obtain functional connectivity boundary maps in which the boundary brain image voxels separate functionally related voxels from unrelated voxels by virtue of their functional covariance as measured in the immediate data. This is also a notable objective and data-driven approach towards defining functional brain regions-of-interest (ROIs), nodes, and networks that are age-appropriate and configured for a given dataset as opposed to using network definitions based on other datasets used as a generic template.

The sample size of 146 for this age group is generally sufficient.

For the analyses considering the significance of the effect of the brain network metrics on the cognitive variables, the usage of heirarchical regression to evaluate whether the additional variables (in the full model) significantly change the model fit relative to the reduced model with covariates-only (data collection site, cortical thickness), while a possible approach, might be problematic, particularly when the full model uses many more regressors than the reduced model. In general, adding more variables to regression models reduces the residual variance. As such, it is possible that adding more regressors in a full model and comparing that to a reduced model with much fewer regressors would yield significant changes in the R^2 fit index, even if the added regressors are not meaningfully modulating the dependent variable. This may not be an issue for the finding on the FPN segregation effect on overall cognition, but it may be important in interpreting the finding on the association system metrics on overall cognition.

Critically, we should note that the correlation effect sizes (justified by the 0.23 value based on the reported power analyses) were all rather small in size. The largest key brain-behavior correlation effect was 0.273 (between DMN segregation and Processing Speed). In the broader perspective, such effects sizes generally suggest that the contribution of this factor is minimal and one should be careful that the results should be understood in this context.

Overall, the findings based on hierarchical regressions that evaluate the network segregation indices in accounting for cognition and the small correlation magnitudes are basically in line with the notion that more segregated neural networks in the oldest-old support better cognitive performance (particularly processing speed). However, the level of positive support for the notion based on these findings is somewhat moderate and requires further study.

Reviewer #2 (Public Review):

The authors capitalised on the opportunity to obtain functional brain imaging data and cognitive performance from a group of oldest old with normative cognitive ability and no severe neurophysiological disorders, arguing that these individuals would be most qualified as having accomplished 'healthy ageing'. Combined with the derivation of a cohort-specific brain parcellation atlas, the authors demonstrated the importance of maintaining brain network segregation for normative cognition ability, especially processing speed, even at such late stage of life. In particular, segregation of the frontoparietal network (FPN) was found to be the key network property.

These results bolstered the findings from studies using younger old participants and are in agreement with the current understanding of the connectomme-cognition relationship. The inclusion of a modest sample size, power analysis, cohort-specific atlas, and a pretty comprehension neuropsychological assessment battery provides optimism that the observed importance of FPN segregation would be a robust and generalisable finding at least in future cross-sectional studies. The fact that FPN segregation is relatively more important to cognition than other associative networks also provides novel insight about the possible 'hierarchy' between age-related neural and cognitive changes, regardless of what mechanisms lead to such segregation at such an advanced age. it is also interesting that processing speed remains to be the 'hallmark' metric of age-related cognitive changes, indirectly speaking to its long assumption fundamental impact on overall cognition.

As laid out by the authors, if network differentiation is key to normative cognitive ability at old age, intervention and stimulation programs that could maintain or boost network segregation would have high translational value. With advent in mobile self-administrable devices that target behavioural and neural modifications, this potential would have increasing appeal.

However, I feel that a few things have prevented the manuscript to be a simple yet impactful submission<br /> 1) Interpretation and the major theme of discussion. While the authors attempted to discuss their findings with respect to both the compensatory and network dedifferentiation hypotheses, the results and their interpretation do not readily provide any resolution or reconciliation between the two, a common challenge in many ageing research. The authors did not further elaborate how the special cohort they had may provide further insights to this.

While the results certainly are in line with the dedifferentiation hypothesis, why 'this finding does not exclude the compensation hypothesis' (Discussion) was not elaborated enough. In particular, the authors seemed to suggest that maintained network specialisation may be in such a role, but the results and interpretations regarding network specialisation were not particularly focused on throughout the manuscript. In addition, both up regulation within a network and cross-network recruitment can both be potential compensatory strategies (Cabeza et al 2018, Rev Nat Neurosci). Without longitudinal data or other designs (e.g. task) it is quite difficult to evaluate the involvement of compensation. For instance, as rightly suggested by the authors, the two phenomena may not be mutually exclusive (e.g., maintenance of the FPN differentiation at such old age could be a result of 'compensation' that started when the participants were younger).

2) Some further clarity about the data and statistical analyses would be desirable. First, since scan length determines the stability of functional connectivity, how long was the resting-state scan? Second, what is the purpose of using both hierarchical regression and partial correlation? While they do consider different variances in the dataset, they are quite similar and the decision looks quite redundant to me as not much further insights have been gained.

Reviewer #1 (Public Review):

Zukin and colleagues present a high-resolution cryo-EM structure of the yeast histone acetyltransferase complex NuA4, which acetylates histones H4 and H2A. The structural data is of very high quality and was obtained using state-of-the-art methodology. The resulting structural model comprises the rigid "Hub" of the NuA4 complex, consisting of a core module and the Tra1 subunit, while the functional TINTIN and HAT modules remain unresolved, likely due to high flexibility. Nevertheless, the structure provides detailed insights into the architecture of the NuA4 complex and reveals how the subunits in the Hub interact. The authors supplement the structural data with functional characterization of the binding of reconstituted TINTIN and HAT modules to modified nucleosomes, which reveals different specificities of the two. In combination, these data lead to a model for chromatin binding and modification by the NuA4 complex.

Notably, the structural model presented by the authors here differs from a previous structure of the NuA4 core in several key details, including the assignment of densities to subunits (Wang et al., Nat Comm 2018). This is supported by two key lines of evidence. First, the structural data presented here is of higher resolution. Second, the new model presented here is in good agreement with available cross-linking data. Therefore, the revised model presented here is very likely to be more accurate than previous structural models.

One "downside" (if one wishes) of the structural data is the lack of defined density for the HAT and TINTIN modules. However, this is not a shortcoming of the experimental approach employed here but is caused by the inherently flexible nature of this complex. Thus, this is not something that could easily be improved. Indeed, as the authors point out by comparison to the SAGA complex, flexible tethering of the functional modules appears to be common among chromatin-modifying complexes. This issue is elegantly addressed by the authors through a detailed analysis of AlphaFold predicted structures of subcomplexes of the HAT and TINTIN modules, which are in good agreement with previous cross-linking data. This analysis supports the assumption that the poorly defined density observed by the authors originates from these modules.

Taken together, this is a very well-executed study that provides important insights into the molecular basis of chromatin modification. The conclusions drawn by the authors are supported by the structural data. The model for the mechanism of histone acetylation derived by the authors is very plausible based on the available data but remains somewhat speculative in the absence of experimental structural data for the HAT and TINTIN domains in complex with their substrates as well as functional data for the complete NuA4 complex. However, these data provide an important milestone towards a mechanistic understanding of chromatin acetylation and will serve as a framework for addressing the open questions in the future.

Reviewer #2 (Public Review):

Zhukin et al., present the structure of the central scaffold component of the NuA4 complex. They hypothesise how the nucleosome interacting modules not present in the structure could be arranged, based on Alphafold modelling, and comparison of their structure to other complexes that use the same subunits. They show some interesting -albeit fairly preliminary - biochemistry on the binding of the flexible modules, suggesting a role for acetylation affecting H3K4me3 reading.

While the work builds upon previous structural studies on the Tra1 subunit in isolation and a previous 4.7A resolution structure from another group, there are clear differences and novel findings in this study. The data is presented beautifully and nicely annotated figures make following the many subunits and interactions therein simple. What could have been a very complex manuscript is easy to digest. Some of the figures could do with a couple of additional labels and detailed figure legends to make things a little clearer.

Overall, a nice study and a wonderfully detailed structure of a large multi-subunit assembly but we would recommend some further experimentation validation to bolster their findings.

Major comments

1) All 13 subunits of NuA4 are present by mass spec, however, based on the SDS-page gel (Fig1-1) components of the TINTIN sub-complex seem less than stoichiometric, with Eaf7 and Eaf3 certainly much weaker stained. This is particularly important with reference to Figure 3 and the discussion in the text which assumes the nucleosome interacting modules are all present equally, but too flexible to be observed in the structure.

Simple peptide numbers from mass spec cannot be used as a measure of protein abundance as this is sensitive to multiple confounding factors.

2) A major novel biological finding and conclusion from the abstract concerns the binding to modified nucleosomes. However, this seemed somewhat preliminary, especially considering the discussion around the role of acetylation affecting binding to H3K4me3 nucleosomes based solely on the dCypher screen used.

The discussion on the role of HAT module binding preferential to acetylated and methylated tails concludes that the acetylation liberates the H3 tail from DNA interaction, making H3K4me3 more available for binding by the PHD domain. This is an interesting hypothesis but is stated as fact with very little evidence to make this assertion.

Whilst others have seen similar results (cited in the paper), no data is presented to disregard an alternative hypothesis that there is some additional acetyl-binding activity in the complex. Indeed, in one of the references they cite the authors do show a direct reading of acetylation as well as methylation.

TINTIN binding is subject to high background and a fairly minor effect. The biological relevance to these observations while intriguing needs to be proved further.

3) There is a large focus on the cross-linking mass spec study from another group and the previously published structure of the NuA4 complex. The authors are fairly aggressive in suggesting the other structure from Wang et al., is incorrect. It is very nice that their built structure shows a better interpretation of previous XL-MS data, but still many of the crosslinks are outside of the modelled density. One possibility that should be entertained is that the two studies are comparing different structures/states of NuA4. The authors of the Wang et al., paper indeed comment that Swc4 and Yaf9 are missing from their purified complex. It is of course possible that both structures are correct as they appear to be biochemically different, with the crosslinking in the Setiaputra paper better reflecting the complex presented here.

Reviewer #1 (Public Review):

The authors present a very nice and timely study detailing how single Pseudomonas aeruginosa cells develop into microcolonies. They demonstrate that motility differences from changes in substrate stiffness are likely responsible for differences in microcolony morphology exhibited at different stiffnesses. The authors further conclude based on modeling data that these motility changes are not due to physiological changes resulting from surface sensing, but rather that mechanical properties of the substrate are responsible for modulating motility differences. However, this conclusion is derived partly from the use of a chpA mutant, which the authors' data demonstrate does not exhibit differences in motility compared to WT. These data are very surprising given that several published studies demonstrate a defect in both pilus synthesis and twitching motility in PilChp mutants (including chpA). It is unclear what the differences are between the presented study and the published literature leading to the disparity in these results.

Major strengths of the manuscript include the detailed analysis of differences in phenotypes on substrates with different rigidities and a link back to changes in motility at the single cell level that could describe these differences.

A weakness of the manuscript is the difference between reported motility phenotypes here and what has been previously published in the literature.

Should the above confounding results be clarified, this work will have a broad impact on the field of microbiology and those studying complex microbial communities as it connects relevant phenotypic differences at the single cell level to mechanical perturbations and multicellular morphologies.

Reviewer #2 (Public Review):

In this manuscript, Gomez et al. study the role of substrate stiffness in the first steps of biofilm formation of the versatile pathogen Pseudomonas aeruginosa. In a very thorough experimental set-up, the authors demonstrate that the early colonization of surfaces by Pseudomonas aeruginosa depends on the surface stiffness, irrespective of the chemical nature of the surface. At low stiffness, the bacteria form dense microcolonies, move slowly, do not explore most of the surface, and excrete minimal amounts of extracellular matrix. On the other hand, at high stiffness, the bacteria cover most of the available surface more uniformly, move rapidly, and excrete large amounts of extracellular matrix polymers. The surface stiffness doesn't affect the division time, but the residence time of bacteria in the constant flow configuration used in the paper is longer on stiffer substrates. Ultimately, the substrate stiffness differences lead to differences in gene expression. The carefully executed experiments are interpreted in the light of interesting simple models that help illuminate the wealth of information presented. The overall subject of the role of rigidity in bacterial physiology is topical and should be of interest to many scientists. The fact that a model without any explicit mechanosensing via Type IV pili can still account for the substrate stiffness phenotypic differences in colonization is a superb addition to the field and is fully supported by the data presented. Yet, some additional explanations will help even strengthen the work.

1) One of the difficulties in navigating the paper as it stands is the definition of many parameters in a global manner as fits from derived equations whose assumptions are not always fully validated. For instance, Equation (1) assumes no new addition because of the flushing of the channel with the clean medium. Yet the first peak of residence time on 2.7 kPa gels is around 5 minutes per Fig. S7 whereas the calculation of Vg is done over 100 minutes which should leave plenty of time for detachment and reattachment of bacteria upstream of the recording field of view, no? Similarly, the definition of Vcm is not easy to follow or apprehend. Is it that the general averages of the velocities are too noisy?

2) While the simple kinetic model presented does encapsulate many of the aspects of the data in an understandable way, some of the assumptions should be discussed further. Nowhere is it more important than in the assumption that pili only binds with its tips. While this assumption allows many simplifications in the model, type IV pili can potentially bind throughout their length, and as they can be microns in length, so can the binding region. The Koch et al 2021b does go over the reasoning but having a small discussion earlier in the paper would be great.

3) One of the very interesting characteristics of the models put forth is that they do not rely on direct mechanosensing from the bacterial side but rather are an indirect consequence of substrate rigidity and pili dynamics. The authors mention that the Pil-Chp and Wsp systems are the only ones found so far in Pseudomonas, but this doesn't mean that there is not another system in place. Making clear that they do not fully rule out the possibility of mechanosensing would be interesting.

Reviewer #1 (Public Review):

Sukumar et al. examine the orientation selectivity of individual peripheral tactile afferents in humans at the limits of perceptual resolvability. They report that spike rates and similar measures were only moderately informative, while the temporal profile of the spiking responses was highly informative, an effect that was most likely driven by complex sub-field structure of the receptive field itself. Once temporal responses were corrected for scanning speeds, different orientations could be discriminated across a wide range of different scanning speeds.

Strengths: The paper tackles an open question and will inform future research, both electrophysiological and psychophysical. The study is built on high-quality data and the analysis is well described and rigorous.

Weaknesses: The link with the existing psychophysical literature is rather weak, for example there is no discussion on the effects of scanning speeds or other factors that have been described in that literature and that would appear relevant here.

Reviewer #2 (Public Review):

This study tests the capacity of single glabrous skin human tactile afferent to discriminate the orientation of edges scanned over their receptive fields (RF) at different speeds spanning 2.5 to 180 mm/s. Raised bars of different orientations (-10,-5,5,10 degrees) were glued on a rotating drum that contacted the skin and rotated at different speeds. Afferent recordings were obtained using microneurography. Both the intensity of the response (i.e. firing rate) and the response profile (precise spike timing) were used as input for discrimination. Indeed, tactile RFs have multiple sensitive zones or hotspots, and different edge orientations will activate those hotspots with a slightly different sequence.

It is found that using intensity measures, discrimination is possible within but not across speeds. Discrimination performance is, as expected, better using the temporal spiking profile, and is also possible across speed, if the spike trains are represented in the spatial domain, that is if the spike trains are compressed or expanded according to the scanning speed. Furthermore, it is found that filtering the spike trains with a spatial Gaussian of approx. 60-70 um SD optimizes discrimination performance. Contrary to previous reports, it is found the FA-I afferent have better discrimination performance than SA-I afferents.

This study is mainly a follow-up of a previous report (Pruszynski et al., 2014) that showed the capacity of tactile afferents to signal orientation thanks to their complex RF profiles. It uses the same procedures and analyses but tests smaller orientation differences and a much wider range of different speeds. The dataset is rich and unique, the analyses are straightforward but rigorously carried out and the conclusions are well supported but the results.

Reviewer #3 (Public Review):

In this manuscript, the authors describe experiments that were performed to investigate the peripheral neural mechanism of geometric feature extraction in human glabrous skin. The cutaneous sensory space of fast-adapting type 1 (FA-1) and slow-adapting type 1 (SA-1) afferents comprises multiple sensitive zones (subfields) spanning several fingerprint ridges, and the authors had earlier shown that subfield layout and edge orientation sensitivity are linked. In that study, the authors used edges with large orientation differences. Here they examine the signaling mechanism for fine edge orientation differences and the role of the scanning speed. They find that the same mechanism extends to the signaling of fine edge orientation differences and that it is maintained across a broad range of scanning speeds. Both FA-1 and SA-1 afferents perform well, albeit the former better than the latter, in signaling fine edge orientation differences when the sequential structure of their spiking response is considered. Further, the edge orientation sensitivity is tuned to natural scanning speeds with both afferent types showing speed-invariant orientation signaling when spike trains are represented in the spatial domain. These findings advance the idea that the subfield layout/terminal organization of primary tactile afferents in human glabrous skin is important for the early processing of geometric features.

Reviewer #1 (Public Review):

Overall this is an interesting and comprehensive examination of gene expression in Hutchinson-Gilford Progeria using a mix of pre-collected and de novo fibroblast cell lines. Comparisons in expression are made between age groups of Hutchinson-Gilford Progeria patients and with chronological age-matched and "aging" matched normal controls. This work is then extended to explore the impact of the accumulation of progerin on chromosome compartment use and lamina-associated domain distribution. The focus of the remainder of the paper is on the impact of the Hutchinson-Gilford Progeria mutation on signatures reflective of the three cell types that arise from mesenchymal progenitors, namely osteoblasts, chondrocytes, and adipocytes.

Strengths:

This work expands greatly on previous work in this area. Batch smoothing and increased number of cell lines allowed for more power for discovery and for better resolution of the analysis. This powerful data set represents a treasure mine of information that will be of high use to the field.

Weaknesses:

This work is entirely based on fibroblasts. While this weakness is acknowledged by the authors, the validity of the conclusions is not validated in any way to demonstrate that the fibroblast is sufficient in this instance. Rather the authors rely on a series of references from other biological systems. Comparisons are made between a parent and affected offspring, but this is restricted to one pair of samples.

Reviewer #2 (Public Review):

San Martin et al utilize an extensive set of genomic and bioinformatics tools to perform a comprehensive analysis of the transcriptional status of HGPS fibroblast cell lines, which suggests dysregulation of pathways critical for the development and maintenance of mesenchymal tissues affected in this disorder. The authors conclude, based on transcriptional profiling of these cells, that mesenchymal stem cell depletion exacerbated by defective tissue repair responses results in the HGPS bone phenotype. An important strength of this manuscript is the comparison of HGPS cells not only to age-matched controls but to healthy old adults as well, leading this reviewer to question the validity of describing HGPS as a premature aging disorder. A major shortcoming of this work is the drawing of conclusions on pathomechanisms of HGPS in multiple mesenchyme-derived tissues based on fibroblast transcriptional and epigenetic profiles which are, however, acknowledged by the authors.

Reviewer #1 (Public Review):

This works makes an important contribution to the study of the cell cycle and the attempt to infer mechanism by studying correlations in division timing between single cells.

Given the importance of circadian rhythms to the ultimate conclusions of the study, I think it would be helpful to clarify the connection between possible oscillatory regulatory mechanisms and the formalism developed in e.g. Equation 3. The treatment appears to be a leading order expansion in stochastic fluctuations of the cell cycle regulators about the mean, but if an oscillatory process is involved, the fluctuations will be correlated in time and need not be small.

Reviewer #2 (Public Review):

This paper is of broad interest to scientists in the fields of cell growth, cell division, and cell-cycle control. Its main contribution is to provide a method to restrict the space of potential cell-cycle models using observed correlations in inter-division times of cells across their lineage tree. This method is validated on several data sets of bacterial and mammalian cells and is used to determine what additional measurements are required to distinguish the set of competing models consistent with a given correlation pattern.

The patterns of correlations in the division times of cells within their lineage tree contain information about the inheritable factors controlling cell cycles. In general, it is difficult to extract such information without a detailed model of cell cycle control. In this manuscript, the authors have provided a Bayesian inference framework to determine what classes of models are consistent with a given set of observations of division time correlations, and what additional observations are needed to distinguish between such models. This method is applied to data sets of division times for various types of bacterial and mammalian cells including cells known to exhibit circadian oscillations.

The manuscript is well-written, the analyses are thorough, and the authors have provided beautiful visualizations of how alternative models can be consistent with a finite set of observed correlations, and where and how extra measurements can distinguish between such models. Known models of growth rate correlations, cell-size regulation, and cell cycle control are analyzed within this framework in the Supplemental Information. A major advantage of the proposed method is that it provides a non-invasive framework to study the mechanism of cell-cycle control.

Reviewer #1 (Public Review):

In this manuscript the authors describe an approach for controlling cellular membrane potential using engineered gene circuits via ion channel expression. Specifically, the authors use microfluidics to track S. cerevisiae gene expression and plasma membrane potential (PMP) in single cells over time. They first establish a small engineered gene circuit capable of producing excitable gene expression dynamics through the combination of positive and negative feedback, tracking expression using GFP (Figure 1). Though not especially novel or complex, the data quality is high in Figure 1 and the results are convincing. Note that the circuit is excitable and not oscillatory; it is being driven periodically by a chemical inducer. I think the authors could have done a better job justifying the use of an excitable engineered gene circuit system, since you could get a similar result by just driving a promoter with the equivalent time course of inducer. The authors then use a similar approach to produce excitable expression of the bacterial ion channel KcsA, tracking membrane voltage using the voltage-sensitive dye ThT rather than GFP fluorescence (Figure 2). The experimental results in this figure are more novel as the authors are now using the expression of a heterologous ion channel to dynamically control plasma membrane potential. While fairly convincing, I think there are a few experimental controls that would make these results even more convincing. It is also unclear why the authors are now using power spectra to display observed frequencies compared to the much more intuitive histograms used in Figure 1. Finally, the authors move on to use a similar excitable engineered gene circuit approach to produce inducible control of the K1 toxin which influences the native potassium channel TOK1 rather than the heterologous ion channel KcsA (Figure 3). I have a similar reaction to this figure as with Figure 2: the results are novel and interesting but would benefit from more experimental controls. Additionally, the image data shown in Figure 3b is very unclear and could be expanded and improved.

Overall, in my opinion the claims in the abstract and title are a bit strong. I would de-emphasize global coordination and "synchronous electrical signaling" since the authors are driving a global inducer. To make the claim of synchronous signaling I would want to see spatial data for cells near vs. far from K1 toxin producing cells in Figure 3 along with estimates of inducer/flow timescale vs. expression/diffusion of K1 toxin. As I read the manuscript, I see that most of the synchronicity comes from the fact that all cells are experiencing a global inducer concentration.

Reviewer #2 (Public Review):

The authors present a novel method to induce electrical signaling through an artificial chemical circuit in yeast which is an unconventional approach that could enable extremely interesting, future experiments. I appreciate that the authors created a computer model that mathematically predicts how the relationship between their two chemical stimulants interact with their two chosen receptors, IacR/MarR, could produce such effects. Their experimental validations clearly demonstrated control over phase that is directly related to the chemical stimulation. In addition, in the three scenarios in which they tested their circuit showed clear promise as the phase difference between spatially distant yeast communities was ~10%. Interestingly, indirect TOK1 expression through K1 toxin gives a nice example of inter-strain coupling, although the synchronization was weaker than in the other cases. Overall, the method is sound as a way to chemically stimulate yeast cultures to produce synchronous electrical activity. However, it is important to point out that this synchronicity is not produced by colony-colony communication (i.e., self-organized), but by a global chemical drive of the constructed gene-expression circuit.

The greatest limitation of the study lies in the presentation (not the science). There are two significant examples of this. First, the authors state this study 'provides a robust synthetic transcriptional toolbox' towards chemo-electrical coupling. In order to be a toolbox, more effort needs to be put into helping others use this approach. However little detail is given about methodological choices, circuit mechanisms in relation to the rest of the cell, nor how this method would be used outside of the demonstrated use case. Second, the authors stress that this method is 'non-invasive', but I fail to see how the presented methodology could be considered non-invasive, in in-vivo applications, as gene circuits are edited and a reliable way to chemically stimulate a large population of cells would be needed. It may be that I misunderstood their claim as the presentation of method and data were not done in a way that led to easy comprehension, but this needs to be addressed specifically and described.

In terms of classifying the synchronicity, while phase difference among communities was the key indicator of synchronization, there were little data exploring other aspects of coupled waveforms, nor a discussion into potential drawbacks. For example, phase may be aligned while other properties such as amplitude and typical wave-shape measures may differ. As this is presented as a method meant for adoption in other labs, a more rigorous analytical approach was expected.

Reviewer #3 (Public Review):

We are enthusiastic about this paper. It demonstrates controlled expression of ion channels, which itself is impressive. Going a step further, the authors show that through their control over ion channel expression, they can dynamically manipulate membrane potential in yeast. This chemical to electrophysiological conversion opens up new opportunities for synthetic biology, for example development of synthetic signaling systems or biological electrochemical interfaces. We believe that control of ion channel expression and hence membrane potential through external stimuli can be emphasized more strongly in the report. The experimental time-lapse data were also high quality. We have two major critiques on the paper, which we will discuss below.

First, we do not believe the analyses used supports the authors' claims that chemical or electrical signals are propagating from cell-to-cell. The text makes this claim indirectly and directly. For example, in lines 139-141, the authors describe the observed membrane potential dynamics as "indicative of the effective communication of electrical messages within the populations". There are similar remarks in lines 144 and 154-156. The claim of electrical communication is further established by Figure 2 supplement 3, which is a spatial signal propagation model. As far as we can tell, this model describes a system different from the one implemented in the paper.

Second, it is not clear why the excitable dynamics of the circuit are so important or if the circuit constructed does in fact exhibit excitable dynamics. Certainly, the mathematical model has excitable dynamics. However, not enough data demonstrates that the biological implementation is in an excitable regime. For example, where in the parameter space of Figure 1 supplement 1 does the biological circuit lie? If the circuit has excitable dynamics, then the authors should observe something like Figure 1 supplement 1B in response to a non-oscillating input. Do they observe that? Do they observe a refractory period? Even if the circuit as constructed is not excitable, we don't think that's a major problem because it is not central to what we believe is the most important part of this work - controlling ion channel expression and hence membrane potential with external chemical stimuli.

Reviewer #1 (Public Review):

In this study, Barnes et al. use chronic two-photon imaging of spine calcium in awake mice to examine the functional response types of synapses that undergo homeostatic spine plasticity elicited by sensory deprivation. Spine plasticity is monitored in apical tuft spines of L5 pyramidal cells in the visual or the retrosplenial cortex, following enucleation/visual deprivation or visual and auditory deprivation, respectively. The authors find that spines that convey sensory stimuli, at least those used for testing, do not change but spines whose activity is correlated to intrinsic network activity undergo compensatory strengthening. The experiments are carefully performed, and the writing is clear and concise. The main findings are important in shedding light on the cellular basis by which a network of neurons compensates for the loss of sensory input activity, specifically suggesting a key role of intrinsic network activity. The study is of significant interest to a broad neuroscience readership. Some of the conclusions are not strongly supported by the data as presented, however, and further considerations involving reanalysis of data and/or presentation are warranted.

Reviewer #2 (Public Review):

Barnes et al. follow individual spines on L5 PC distal tufts in mouse V1 before and after contralateral enucleation. At baseline, some spines show activity driven by visual simulation, others are correlated with network activity (average Ca signal in all other spines). After sensory deprivation (12 h), strongly 'visual' spines had smaller Ca transients while previously weakly 'visual' spines had larger transients, indicating homeostatic boosting. These boosted spines are the ones that were correlated with network activity at baseline. Similar results were obtained in the retrosplenial cortex 48 h after auditory or visual deprivation. As previously described for homeostatic plasticity, a block of TNF-a blocked deprivation-induced boosting of spine responses. Somewhat paradoxically, dendritic sensory-evoked responses did increase after sensory deprivation.

The study is well designed and provides exciting new insights into the plasticity of intracortical connections, (over-)compensating for the partial loss of thalamic inputs. To optically resolve the activity of single synapses in vivo during sensory stimulation is technically very challenging. It would be helpful to know whether the recordings were made in the binocular or monocular region of V1. The results argue against a generalized multiplicative upscaling of all inputs and suggest selective boosting of synapses that are part of sensory-driven subnetworks. However, it is not clear whether homeostatic plasticity occurred at the observed spines themselves or on the level of presynaptic neurons, which could then e.g. fire more bursts, leading to larger postsynaptic Ca transients. The possibility that thalamic inputs from the intact eye in layer 4 could be potentiated should be discussed. It would probably help to explain to the reader the layer-specific connectivity of V1 in the introduction, and why thalamic input synapses themselves were not optically monitored (may require adaptive optics). Technical limitations are a main reason why the conclusions are somewhat vague at this point ("... regulation of global responses"), this could be spelled out better.

Reviewer #3 (Public Review):

In this work, the authors address the question of whether sensory deprivation drives homeostatic responses in all dendritic spines (the standard model/status quo) or is restricted to a functional subset of spines. The key claims of the manuscript are well supported by the data, the writing is clear, and the conclusions are both thoughtful and restrained. The contrast/comparison of the current results to prior work, specifically the difference between homeostatic responses in adult versus critical period animals, should be presented early and often.

Strengths:<br /> This manuscript builds on prior work from the authors that seek to understand compensatory plasticity in cortical circuits in the intact animal. Here, the authors present clear evidence that, instead of a global homeostatic response, circuit rebalancing may be the result of a selective strengthening of intra-network connections. Crucially, this rebalancing via network tuning does not involve homeostatic adjustment of sensory-related spines. More specifically, by tracking the same spines over 3 d, the authors reveal a functional separation between those spines that faithfully respond to sensory input and those spines that are network-correlated. The amplitude of calcium transients in network-correlated spines is increased following enucleation, which the authors suggest forms the basis of the global (network-wide) sensory-evoked responses. This is quite interesting as it is somewhat counterintuitive; absent these data, it would be reasonable to assume that increased network responses are reflective of homeostatic processes in the sensory-related spines and synapses. To reach these conclusions, the authors employ GCaMP6s-based calcium imaging of L5 pyramidal neurons in visual and retrosplenial cortices prior to and during sensory deprivation (enucleation or ear-plugging).<br /> This manuscript is well written. It is clear and not overstated. The work is presented in a linear and approachable style that should be accessible to readers outside of the field. These findings are a meaningful advance for the field and raise foundational questions about the neurobiology of the cortex. Specifically, homeostatic regulation of neuronal activity may be constrained to a subset of processes, or alternatively, adult sensory processes are somehow shielded from the impact of homeostatic change.

Weaknesses:<br /> Weaknesses are largely restricted to suggested changes to the writing - specifically, there are additional explanations of the data whose discussion may strengthen the long-term impact of the manuscript.<br /> 1. Most importantly, the hypothesis at the heart of this work (subset versus global processes) is framed as orthogonal to the status quo model of homeostatic processes (global). I suspect that adherents to the global argument would quickly point out that the current work is conducted in adult animals, and the majority of the homeostatic plasticity research (which forms the basis of the global model) is conducted in juvenile animals. This is an important distinction because the visual system is enriched in plasticity mechanisms during the ocular dominance critical period. Since Hubel and Wiesel at least, there is extensive evidence to suggest that sensory systems take advantage of critical periods to set themselves up in accordance with the statistics of the world in which they are embedded. The flip side of this is that sensory systems are far less readily influenced by experience once the critical period is closed (Vital-Durand et al., 1978, LeVay et al., 1980; Daw et al., 1992, Antonini et al., 1999, Guire et al., 1999, Lehmann and Lowel, 2008). Through this lens, one might predict that a key feature of the adult cortex is that sensory spines could benefit by being selectively protected from what would otherwise be global homeostatic processes. Either way, the manuscript can be read as if it is framing a show-down between the classical model and a newer, higher-resolution model. I worry that this will be interpreted as misleading without careful presentation/contextualization of the role of development in the introduction and a thorough dissection in the discussion. Currently, the first occurrence of the word, "adult", occurs in the methods, on page 27, line 512. "Juvenile" and "critical period" are not in the manuscript. The age of the animals in this study isn't mentioned until the methods (between P88 and P148 at the time of imaging).<br /> 2. Goel and Lee (2007) seem quite pertinent here: they show that L2/3 neurons give rise to homeostatic regulation of mEPSCs in both juvenile and adult animals, but that the process is no longer multiplicative in nature once the animal is post-critical period. Multiplicity has been the basis of the argument for global change since Turrigiano 1998. Thus, the Goel and Lee finding seems to really bolster the current findings - and also perhaps reconcile the likelihood of a mechanistic difference between CP and adult homeostatic plasticity.

Reviewer #1 (Public Review):

In this manuscript, the authors explore the mechanisms through which hormone receptors act on their targets to either repress or activate transcription. To do this, they employ a new transgenic tool, a transgenic construct that contains only the ligand binding domain for the ecdysone receptor, EcRLBD, that acts as a sponge for both the steroid hormone ecdysone and for EcR-binding partners. They find that their EcRLBD elicits many of the same phenotypes as other tools used to manipulate the EcR function, suggesting that it acts as a dominant negative. However, it does not elicit all of the same phenotypes as EcR RNAi or overexpression of other dominant negative EcR transgenes (EcRF645A). For example, it interferes with fat body mobilization into the pupal head but does not affect the disintegration of the larval fat body sheets as do the EcR RNAi or EcRF645A.

The authors proceed to provide extensive evidence that the EcRLBD affects both the repression and activation functions of EcR, using EcRE lacz and EcRE GFP transgenes in the developing wing disc. Modifying 20E uptake or metabolism does not affect the ability of EcRLBD to induce precocious de-repression. This is perhaps unsurprising as EcRLBD is proposed to be sponging co-repressors which would be necessary for unliganded EcR repression. However, reducing 20E metabolism does rescue some of the effects of EcRLBD on the activation of gene expression.

The EcRLBD can also induce precocious de-repression of key ecdysone response genes Broad and E93. However, neither of these genes appear to require EcR activation as the later-stage expression is not reduced in EcRLBD larvae. Finally, they demonstrate that the effects they observe when overexpressing EcRLBD in a variety of tissues depend on the ability to bind to a co-repressor Smarter.

There is an impressive amount of work in this manuscript, and the data appears to be of high quality. The experiments are appropriate to the authors' aims, and I feel they will be of broad interest to all those working on developmental physiology and receptor/hormone interactions. Their new transgenic tool is sure to be used by a number of researchers interested in identifying binding partners for EcR across developmental timescales.

I think the most significant weakness of this work is none of the data has been quantified and so it's difficult to judge the extent of variation in samples. Quantification is important, as many of the arguments are based on relative levels of expression. While I feel that the study design supports the authors' aims, the lack of quantitative analysis limits the extent to which the data supports their conclusions.

Reviewer #2 (Public Review):

In this work, the authors analyze the mechanism through which the fluctuations of the Ecdysone hormone modulate the passage from a third instar larva to a pupa, during the process of metamorphosis. They focus on the imaginal wing disc in which initially the levels of Ecdysone fluctuate and in the later phase when the levels of this hormone increase significantly. This entire process depends on the Ecdysone hormone receptor (EcR) and the interaction it has with co-repressors and co-activators. Using as a tool a dominant negative form that does not have the receptor DNA binding site, but does have the hormone binding site as well as regions with which the receptor interacts with co-repressors and co-activators, they show that genes which are repressed early in the wing disc, are de-repressed if this dominant negative is present. Even more, they manage to demonstrate that at the genetic level, one of the co-repressors that acts together with the EcR in the repression of these genes is Smrter/NCoR1. The strategy used is based on the use of genetic tools that are unique to Drosophila, which allows them to carry out a very precise analysis of the expression of the reporter and endogenous genes in a very fine way and allows them to obtain very robust in vivo results. On the other hand, the work can be reinforced using biochemical techniques that may allow showing the direct interactions of the different players studied in this work. Nuclear receptors that respond to steroid hormones are present in all metazoa. Therefore, this work is useful not only to understand the mechanisms of how nuclear receptors modulate gene expression in flies but also in mammals.

Reviewer #1 (Public Review):

Dystroglycan, composed of subunits alpha- and beta, is one of the most important non-integrin cellular adhesion complexes, fundamental to establishing a connection between the extracellular matrix and the cytoskeleton in skeletal muscle and in a wide variety of tissues. For a protein that is produced through the ER-Golgi and then trafficked and targeted through exocytosis at the plasma membrane, unraveling the molecular aspects of every step underlining its maturation must be considered to be of utmost importance.

The authors show how the lack of the N-terminal domain of alpha-dystroglycan (aDGN), achieved specifically in the skeletal muscle of model mice, is partially disrupting the decoration with sugars of the central "mucin-like" region of alpha-dystroglycan own central 'mucin like' region. Specifically, it would impact one of the most crucial steps in such a process, i.e. the LARGE1 directed synthesis of matriglycan, with deleterious consequences for dystroglycan function. This is an important work representing another step to drawing a full picture of dystroglycan maturation, with interesting implications for our understanding of dystroglycan biology and pathology.

Strengths:

Arising in part from previous knowledge acquired on the dystroglycan domain organization, a role for the N-terminal of alpha-dystroglycan in the maturation of the full-length subunit could be envisaged. The authors have set a series of experiments whose overall outcome is not in contrast with the hypothesis made (i.e. that of a possible role played by aDGN in matriglycan elongation or modification).

The presence of a link between the molecular structure of matriglycan and the genesis of muscular dystrophy has been further demonstrated.

Weaknesses:

Some of the data, for example, those on the overexpressed aDGN, need to be re-assessed or re-interpreted providing more controls, if possible.

More data should be reported on the histology and biochemistry of different types of muscle from a wider age range of mice. The degree and severeness of the observed muscular dystrophy phenotype remain a bit unclear. Especially, it should be better compared to the one observed in myd mice.

The work does not show how the reaction mediated by LARGE (i.e. the synthesis of matriglycan) would ultimately take place through (or chaperoned by) aDGN, and no clarification is given on whether a direct interaction between aDGN and LARGE1 occurs.