Reviewer #1 (Public Review):

The manuscript by Chen et al. investigated the interaction between CHI3L1, a chitinase-like protein in the 18 glycosyl hydrolase family, and gut bacteria in the mucosal layers. The authors provided evidence to document the direct interaction between CHI3L1 and peptidoglycan, a major component of bacterial cell walls. In doing so, Chi3l1 produced by gut epithelial cells regulates the balance of the gut microbiome and diminishes DSS-induced colitis, potentially through the colonization of protective gram-positive bacteria such as lactobacillus.

The study is the first to systemically document the interactions between Chi3L1 and microbiome. Convincing data were shown to characterize the imbalance of gram-positive bacteria in the newly generated gut epithelial-specific Chi3L1 deficient mice. Comprehensive FMT experiments were performed to demonstrate the contributions of gut microbiome using the mouse colitis model. However, the manuscript could've been strengthened by additional mechanistic studies concerning the binding between Chi3l1 and peptidoglycan, and how this interaction could facilitate the colonization of gram-positive bacteria. Additionally, the conclusion by the authors that disordered intestinal bacteria in gut epithelial-specific Chi3L1 deficient mice, rather than an effect by host cells, contributes to exacerbated colitis, needs further validation. In fact, the fact that FMT did not completely rescue the phenotype may point to the role of host cells in the processes. On the contrary, there is an existing body of literature demonstrating the detrimental roles of Chi3l1 in the mouse IBD model, conflicting with the current study. The differences in study design and approaches in these studies that lead to controversial findings will need to be discussed.

Specifically,<br /> 1) In Figure 1, it is curious that the authors only chose E.coli and staphytlococcus sciuri to test the induction of Chi3l1. What about other bacteria? Why does only E.coli but not staphytlococcus sciuri induce chi3l1 production? It does not prove that the gut microbiome induces the expression of Chi3l1. If it is the effect of LPS, does it trigger a cell death response or inflammatory responses that are known to induce chi3l1 production? What is the role of peptidoglycan in this experiment? Also, it is recommended to change WT to SPF in the figure and text, as no genetic manipulation was involved in this figure.

2) In Figure 2, the binding between Chi3l1 and PGN needs better characterization, regarding the affinity and how it compares with the binding between Chi3l1 and chitin. More importantly, it is unclear how this interaction could facilitate the colonization of gram-positive bacteria.

3) In Figure 3, the abundance of furmicutes and other gram-positive species is lower in the knockout mice. What is the rationale for choosing lactobacillus in the following transfer experiments?

4) FDAA-labeled E. faecalis colonization is decreased in the knockouts. Is it specific for E. faecalis, or it is generally true for all gram-positive bacteria? What about the colonization of gram-negative bacteria?

5) In Figure 5, the fact that FMT did not completely rescue the phenotype may point to the role of host cells in the processes. The reason that lactobacillus transfer did completely rescue the phenotypes could be due to the overwhelming protective role of lactobacillus itself, as the experiments were missing villin-cre mice transferred with lactobacillus.

6) Conflicting literature demonstrating the detrimental roles of Chi3l1 in mouse IBD model needs to be acknowledged and discussed.

Reviewer #2 (Public Review):

Chen et al. investigated the regulatory mechanism of bacterial colonization in the intestinal mucus layer in mice and its implications for intestinal diseases. They demonstrated that Chi3l1 is a protein produced and secreted by intestinal epithelial cells into the mucus layer upon response to the gut microbiota, which has a turnover effect on facilitating the colonization of gram-positive bacteria in the mucosa. The data also indicate that Chi3l1 interacts with the peptidoglycan of the bacteria cell wall, supporting the colonization of beneficial bacteria strains such as Lactobacillus, and that deficiency in Chi3l1 predisposes mice to colitis. The inclusion of a small but pertinent piece of human data added to solidify their findings in mice.

Overall, the experiments performed were appropriate and well executed, but the data analysis is incomplete and needs to be extended. Also, additional experiments are necessary for clarification and stronger support for their conclusions.

1) Images are of great quality but lack proper quantification and statistical analysis. Statements such as "substantial increase of Chi3l1 expression in SPF mice" (Fig.1A), "reduced levels of Firmicutes in the colon lumen of IECChil1" (Fig.3F), "Chil1-/- had much lower colonization of E.faecalis" (Fig.4G), or "deletion of Chi3l1 significantly reduced mucus layer thickness" (Supplemental Figure 3A-B) are subjective. Since many conclusions were based on imaging data, the authors must provide reliable measures for comparison between conditions, as long as possible, such as fluorescence intensity, area, density, etc, as well as plots and statistical analysis.

2) In the fecal/Lactobacillus transplantation experiments, oral gavage of Lactobacillus to IECChil1 mice ameliorated the colitis phenotype, by preventing colon length reduction, weight loss, and colon inflammation. These findings seem to go against the notion that Chi3l1 is necessary for the colonization of Lactobacillus in the intestinal mucosa. The authors could speculate on how Lactobacillus administration is still beneficial in the absence of Chi3l1. Perhaps, additional data showing the localization of the orally administered bacteria in the gut of Chi3l1 deficient mice would clarify whether Lactobacillus are more successfully colonizing other regions of the gut, but not the mucus layer. Alternatively, later time points of 2% DSS challenge, after Lactobacillus transplantation, would suggest whether the gut colonization by Lactobacillus and therefore the milder colitis phenotype, is sustained for longer periods in the absence of Chi3l1.

Reviewer #3 (Public Review):

Summary:<br /> Chen et al. are addressing a fundamental question in mammalian gut biology, namely how the host controls a mutualistic host-microbiota symbiosis. The authors focus on a protein called Chitinase 3-like protein 1 (Ch3l1) and its interaction with the protective colonic mucus layer. The rationale for the study comes from previous work showing that microbial-associated molecular patterns (MAMPs) can induce Ch3l1 in vitro, but its biological functions in the colon are unknown. In this study, the authors provide evidence supporting the claim that the gut microbiota induces the expression of Ch3l1 in vivo, mainly in mucus-producing goblet cells. Insightfully, the authors note that Ch3l1, although it lacks enzyme (chitinase) activity, still binds Chitin, a glycan that has structural similarity to bacterial cell wall peptidoglycan. This leads the authors to hypothesize that Ch3l1 binds microbial cell walls, particularly those of peptidoglycan-rich Gram-positive probiotic bacteria within the mucus, to promote their retention in the colon. Using a combination of in vivo work with mice conditionally lacking Ch3l1 in gut epithelium (IEC Ch3l1 KO); microbiota profiling; imaging of host-microbiota interactions with labeled microbes; and fecal transplants, the authors provide compelling evidence that Ch3l1 is secreted into the gut mucus layer and that the presence of Ch3l1 is associated with increased levels of beneficial Gram+ bacteria, including Lactobacillus spp. In turn, using a well-characterized colitis model, the authors show that Ch3l1 is associated with protection from intestinal injury caused by Dextran Sodium Sulfate. While these studies are novel and informative, there are several issues that undermine the authors' conclusions.

Strengths:<br /> The authors nicely link microbial induction of Ch3l1 to mucosal protection from intestinal injury. This is done through the use of germ-free and ex-germ-free studies and by comparing Ch3l1 expression in situ between them; microbial sequencing between Control and IEC Ch3l1 KO mice, and clinical and histological injury metrics between these strains. The authors convincingly demonstrate the presence of Ch3l1 in the gut mucus through imaging, and that the deletion of this protein in mice alters the microbiota by reducing the relative abundance of Gram-positive species.

The study employs a technically diverse set of analyses to address their hypothesis, including fluorescent labelling of microbial species for add-back studies, fecal transplants to distinguish the role(s) of the microbiota vs. host in the IEC Ch3l1 KO phenotypes in the intestinal challenge models.

Weaknesses:<br /> The claim that mucus-associated Ch3l1 controls colonization of beneficial Gram-positive species within the mucus is not conclusive. The study should take into account recent discoveries on the nature of mucus in the colon, namely its mobile fecal association and complex structure based on two distinct mucus barrier layers coming from proximal and distal parts of the colon (PMID: ). This impacts the interpretation of how and where Ch3l1 is expressed and gets into the mucus to promote colonization. It also impacts their conclusions because the authors compare fecal vs. tissue mucus, but most of the mucus would be attached to the feces. Of the mucus that was claimed to be isolated from the WT and IEC Ch3l1 KO, this was not biochemically verified. Such verification (e.g. through Western blot) would increase confidence in the data presented. Further, the study relies upon relative microbial profiling, which can mask absolute numbers, making the claim of reduced overall Gram-positive species in mice lacking Ch3l1 unproven. It would be beneficial to show more quantitative approaches (e.g. Quantitative Microbial Profiling, QMP) to provide more definitive conclusions on the impact of Ch3l1 loss on Gram+ microbes.

Other weaknesses lie in the execution of the aims, leaving many claims incompletely substantiated. For example, much of the imaging data is challenging for the reader to interpret due to it being unfocused, too low of magnification, not including the correct control, and not comparing the same regions of tissues among different in vivo study groups. Statistical rigor could be better demonstrated, particularly when making claims based on imaging data. These are often presented as single images without any statistics (i.e. analysis of multiple images and biological replicates). These images include the LTA signal differences, FISH images, Enterococcus colonization, and mucus thickness.

Joint Public Review:

Summary:<br /> Identifying dietary biomarkers, in particular, has become a main focus of nutrition research in the drive to develop personalized nutrition.

The aim of this study was to determine the accuracy of using food composition databases to assess the association between dietary intake and health outcomes. The authors found that using food composition data to assess dietary intake of specific bioactives and the impact consumption has on systolic blood pressure provided vastly different outcomes depending on the method used. These findings demonstrate the difficulty in elucidating the relationship between diet and health outcomes and the need for more stringent research in the development of dietary biomarkers.

Strengths:<br /> The primary strength of the study is the use of a large cohort in which dietary data and the measurement of three specific bioactives and blood pressure were collected on the same day. The bioactives selected have been extensively researched for their health effects. Another strength is that the authors controlled for as many variables as possible when running the simulations to get a more accurate account of how the variability in food composition can impact research findings that associate the intake of certain food components with health outcomes.

Weaknesses:<br /> The authors address the large variability when using food composition data, e.g. the range of tea and apple intake needed to meet recommendations depending on using the mean food composition data or using the lowest reported food content, however, there is no discussion on the intake needed if the biomarker is used. So how many cups of tea are needed to reach the suggested 200 mg/day of flavan-3-ols when using biomarker data instead of the food composition data? More information should be added on the effect of using biomarker data on dietary recommendations and risk assessment.

Reviewer #1 (Public Review):

Summary:<br /> Ye et al. identified a novel tumour microenvironment (TME) signature that can help to prognosticate DLBCL. They first interrogated a publicly available dataset to identify tumour purity-related genes (TPGs) and found these TPGs were associated with extracellular matrix organisation and immune response. Protein-protein interaction analysis identified hub genes that were associated with prognosis, and 3 genes (VCAN, CD3G, C1QB) were selected to construct a prognosis model. The authors attempted to validate the findings on immunohistochemistry (IHC) and showed prognostication using an IHC assay. Finally, they showed a possible prediction of drug sensitivity using the novel signature in DLBCL.

Strengths:<br /> This study investigated both immune and non-immune TME related to tumour purity. Tumour purity has not been thoroughly investigated in DLBCL. Hence, the prognostic significance of tumour purity demonstrated in this paper brought into light another potential area of research in DLBCL. Similarly, the investigation into non-immune TME was novel and thought-provoking, as most research in DLBCL TME has mostly been in the immune microenvironment.

The bioinformatics approach in identifying the key TPGs was well conducted, such as the GO and KEGG enrichment analysis which supported the role of these TPGs in the modulation of the microenvironment. The findings were also validated in another dataset, which increased the confidence in this model. However, it was not clear to me why the authors chose VCAN, CD3G, and C1QB out of the 9 intersection genes that they found. It would perhaps be useful to show the statistical justification in the Supplementary Results section.

The possible translation of these findings into clinical practice by immunohistochemistry (IHC) was a useful tool to make the findings applicable in the clinical setting. However, as stated by the authors, the real-life clinical application of these findings may be more challenging as these antigens seemed to be expressed in a continuum, rather than in a discrete manner. For example, in Figure 5A, even the low VCAN status still demonstrated strong cytoplasmic staining. Similarly, in Figure 5C, it seemed to be difficult to differentiate strong from background staining. This means pre-analytical variables may affect the staining and standardisation among different laboratories may be difficult to achieve without external controls.

Weaknesses:<br /> Though the rationale behind choosing the TPG genes and its correlation with non-immune TME was clear, the justification for investigating CD68+ macrophages, CD4+ T cells, and CD8+ T cells was not as strong. This was done in a subsection that was supposed to investigate the prognostic values of IHC staining in VCAN, CD3G, and C1QB. Hence, the analysis of the immune compartment of the TME was rather superficial. For example, it would be insufficient to correlate CD4+ and CD8T+ T cells without understanding their deeper phenotypes such as regulatory vs memory or exhausted vs activated. An attempt was made to subtype the macrophages by bioinformatics approach but it was not further investigated with IHC.

Similarly, the investigation into drug sensitivity was only done in-silico. This investigation was adequate for hypothesis generation. However, it was not enough to substantiate the claim that TPGs can be used to predict drug sensitivity. This claim requires functional in-vitro experiments to validate the bioinformatics approach, or even correlation with clinical data when the identified drugs were used in DLBCL, for example in the ReMODL-B cohort that used bortezomib.

Reviewer #2 (Public Review):

In this study, Zhenbang Ye and colleagues investigate the links between microenvironment signatures, gene expression profiles, and prognosis in diffuse large B-cell lymphoma (DLBCL). They show that increased tumor purity (ie, a higher proportion of tumor cells relative to surrounding stromal components) is associated with a worse prognosis. They then show that three genes associated with tumor purity (VCAN, CD3G, and C1QB) correlate with patterns of immune cell infiltration and can be used to create a risk-scoring system that predicts prognosis, which can be replicated by immunohistochemistry (IHC), and response to some therapies.

1. The two strengths of the study are its relatively large sample size (n = 190) and the strong prognostic significance of the risk-scoring system. It is worth noting that the validation of this scoring with IHC, a simple technique already routinely used for the diagnosis and classification of DLBCL, increases the potential for clinical translation. However, the correlative nature of the study limits the conclusions that can be drawn in regard to links between the risk scoring system, the tumor microenvironment, and the biology of DLBCL.

2. The tumor microenvironment has been extensively studied in DLBCL and a prognostic implication has already been established (for instance, Steen et al., Cancer Cell, 2021). In addition, associations have already been established in non-Hodgkin lymphoma between prognosis and expression of C1QB (Rapier-Sharman et al., Journal of Bioinformatics and Systems Biology, 2022), VCAN (S. Hu et al., Blood, 2013), and CD3G (Chen et al., Medical Oncology, 2022). Nevertheless, one of the strengths and novelty aspects of the study is the combination of these 3 genes into a risk score that is also valid by immunohistochemistry (IHC), which substantially facilitates a potential clinical translation.

3. Figures 1A-B: tumor purity is calculated using the ESTIMATE (Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data) algorithm (Yoshihara et al., Nature Communications, 2013). The ESTIMATE algorithm is based on two gene signatures ("stromal" and "immune"). It is therefore expected that tumor purity measured by the ESTIMATE algorithm will correlate with the expression of multiple genes. Importantly, C1QB is included in the stromal signature of the ESTIMATE algorithm meaning that, by definition, it will be correlated with tumor purity in that setting.

4. Figure 2A: as established in Figure 1C, high tumor purity is associated with worse prognosis. Later in the manuscript, it is also shown that C1QB expression is associated with a worse prognosis. However, Figure 2A shows that C1QB is associated with decreased tumor purity. It therefore makes it less likely that the prognostic role of C1QB expression is related to its impact on tumor purity. The prognostic impact could be related to different patterns of immune cell infiltration, as shown later. However, the evidence presented in the study is correlative and natural and not sufficient to draw this conclusion.

5. Figure 3G: although there is a strong prognostic implication of the risk score on prognosis, the correlation between the risk score and tumor purity is significant but not very strong (R = 0.376). It is therefore likely that other important biological factors explain the correlation between the risk score and prognosis.

6. Figure 6: the drug sensitivity analysis includes a wide range of established and investigational drugs with varied mechanisms of action. Although the difference in sensitivity between tumors with low and high-risk scores shows statistical significance for certain drugs, the absolute difference appears small in most cases and is of unclear biological significance. In addition, even though the risk score is statistically related to drug sensitivity, there is no direct evidence that the differences in drug sensitivity are directly related to tumor purity.

Reviewer #1 (Public Review):

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

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

I have read the revised version of the manuscript with interest. I agree with the authors that a focus on ecological vs laboratory variables is a good one, although it might have been useful to reflect that in the title.

I am happy to see that the authors included additional analyses using different definitions of FP and DLPFC in the supplementary material. As I said in my earlier review, the precise delineation of the areas will always be an issue of debate in studies like this, so showing the effects of different decisions in vital.

I am sorry the authors are so dismissive of the idea of looking the models where brain size and area size are directly compared in the model, rather preferring to run separate models on brain size and area size. This seems to me a sensible suggestion.

Similarly, the debate about whether area volume and number of neurons can be equated across the regions is an important one, of which they are a bit dismissive.

Nevertheless, I think this is an important study. I am happy that we are using imaging data to answer more wider phylogenetic questions. Combining detailed anatomy, big data, and phylogenetic statistical frameworks is a important approach.

Reviewer #2 (Public Review):

In the manuscript entitled "Linking the evolution of two prefrontal brain regions to social and foraging challenges in primates" the authors measure the volume of the frontal pole (FP, related to metacognition) and the dorsolateral prefrontal cortex (DLPFC, related to working memory) in 16 primate species to evaluate the influence of socio-ecological factors on the size of these cortical regions. The authors select 11 socio-ecological variables and use a phylogenetic generalized least squares (PGLS) approach to evaluate the joint influence of these socio-ecological variables on the neuro-anatomical variability of FP and DLPFC across the 16 selected primate species; in this way, the authors take into account the phylogenetic relations across primate species in their attempt to discover the the influence of socio-ecological variables on FP and DLPF evolution.

The authors run their studies on brains collected from 1920 to 1970 and preserved in formalin solution. Also, they obtained data from the Mussée National d´Histoire Naturelle in Paris and from the Allen Brain Institute in California. The main findings consist in showing that the volume of the FP, the DLPFC, and the Rest of the Brain (ROB) across the 16 selected primate species is related to three socio-ecological variables: body mass, daily traveled distance, and population density. The authors conclude that metacognition and working memory are critical for foraging in primates and that FP volume is more sensitive to social constraints than DLPFC volume.

The topic addressed in the present manuscript is relevant for understanding human brain evolution from the point of view of primate research, which, unfortunately, is a shrinking field in neuroscience. But the experimental design has two major weak points: the absence of lissencephalic primates among the selected species and the delimitation of FP and DLPFC. Also, a general theoretical and experimental frame linking evolution (phylogeny) and development (ontogeny) is lacking.

Reviewer #3 (Public Review):

This is an interesting manuscript that addresses a longstanding debate in evolutionary biology - whether social or ecological factors are primarily responsible for the evolution of the large human brain. To address this, the authors examine the relationship between the size of two prefrontal regions involved in metacognition and working memory (DLPFC and FP) and socioecological variables across 16 primate species. I recommend major revisions to this manuscript due to: 1) a lack of clarity surrounding model construction; and 2) an inappropriate treatment of the relative importance of different predictors (due to a lack of scaling/normalization of predictor variables prior to analysis).

Joint Public Review:

Summary:<br /> Desiderio and colleagues investigated the role of the TALE (three amino acid loop extension) homeodomain transcription factor Meis2 during maturation and target innervation of mechanoreceptors and their sensation to touch. They start with a series of careful in situ hybridizations and immunohistochemical analyses to examine Meis2 transcript expression and protein distribution in mouse and chick DRGs of different embryonic stages. By this approach, they identify Meis2+ neurons as slowly- and rapidly adapting A-beta LTMRs, respectively. Retrograde tracing experiments in newborn mice confirmed that Meis2-expressing sensory neurons project to the skin, while unilateral limb bud ablations in chick embryos in ovo showed that these neurons require target-derived signals for survival. The authors further generated a conditional knock-out (cKO) mouse model in which Meis2 is selectively lost in Islet1-expressing, postmitotic neurons in the DRG (IsletCre/+::Meis2flox/flox, abbreviated below as cKO). WT and Islet1Cre/+ littermates served as controls. cKO mice did not exhibit any obvious alteration in volume or cellular composition of the DRGs but showed significantly reduced sensitivity to touch stimuli and various innervation defects to different end-organ targets. RNA-sequencing experiments of E18.5 DRGs taken from WT, Islet1Cre/+ and cKO mice reveals extensive gene expression differences between cKO cells and the two controls, including synaptic proteins and components of GABAergic- and glutamatergic transmission. Histological analysis and electrophysiological recordings shed light on the physiological defects resulting from the loss of Meis2. By immunohistochemical approaches, the authors describe distinct innervation defects in glabrous and hairy skin (reduced innervation of Merkel cells by SA1-LTMRs in glabrous but not hairy skin, reduced complexity of A-beta RA1-LTMs innervating Meissner's corpuscles in glabrous skin, reduced branching and innervation of A-betA RA1-LTMRs in hairy skin). Electrophysiological recordings from ex vivo skin nerve preparations found that several, but not all of these histological defects are matched by altered responses to external stimuli, indicating that compensation may play a considerable role in this system. This study will be of interest to developmental biologists and neuroscientists, in particular those interested in the sensation of touch.

Strengths:<br /> This is a well-conducted study that combines different experimental approaches to convincingly show that the transcription factor Meis2 plays an important role in the perception of light touch. The authors describe a new mouse model for compromised touch sensation, characterize it by histology and electrophysiological recordings, and identify several genes whose expression depends on Meis2 in mouse DRGs.

Weaknesses:<br /> The authors use different experimental approaches to investigate the role of Meis2 in touch sensation, but the results obtained by these techniques could be better connected. For instance, the authors identify several genes involved in synapse formation, synaptic transmission, neuronal projections, or axon and dendrite maturation that are up- or downregulated upon targeted Meis2 deletion, but it remains to be resolved whether these chances explain the histological, electrophysiological, or behavioral deficits observed in cKO animals.

Reviewer #1 (Public Review):

Summary:<br /> In the current study, Papandreou et al. developed an iPSC-based midbrain dopaminergic neuronal cell model of Beta-Propeller Protein-Associated Neurodegeneration (BPAN), which is caused by mutations in the WDR45 gene and is known to impair autophagy. They also noted defective autophagy and abnormal BPAN-related gene expression signatures. Further, they performed a drug screening and identified five cardiac glycosides. Treatment with these drugs effectively in improved autophagy defects and restored gene expression.

Strengths:<br /> Seeing the autophagy defects and impaired expression of BPAN-related genes adds strength to this study. Importantly, this work shows the value of iPSC-based modeling in studying disease and finding therapeutic strategies for genetic disorders, including BPAN.

Weaknesses:<br /> It is unclear whether these cells show iron metabolism defects and whether treatment with these drugs can ameliorate the iron metabolism phenotypes.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors aim to demonstrate that cardiac glycosides restore autophagy flux in an iPSC-derived mDA neuronal model of WDR45 deficiency. They established a patient-derived induced pluripotent stem cell (iPSC)-based midbrain dopaminergic (mDA) neuronal model and performed a medium-throughput drug screen using high-content imaging-based IF analysis. Several compounds were identified to ameliorate disease-specific phenotypes in vitro.

Strengths:<br /> This manuscript engaged in an important topic and yielded some interesting data.

Weaknesses:<br /> This manuscript failed to provide solid evidence to support the conclusion.

Reviewer #1 (Public Review):

Summary:<br /> Zhang et al., investigated the relationship between monocular and binocular responses of V1 superficial-layer neurons using two-photon calcium imaging. They found a strong relationship in their data: neurons that exhibited a greater preference for one eye or the other (high ocular dominance) were more likely to be suppressed under binocular stimulation, whereas neurons that are more equivalently driven by each other (low ocular dominance) were more likely to be enhanced by binocular stimulation. This result chiefly demonstrates the relationship between ocular dominance and binocular responses in V1, corroborating what has been shown previously using electrophysiological techniques but now with greater spatial resolution (albeit less temporal resolution). The binocular responses were well-fitted by a model that institutes divisive normalization between the eyes that accounts for both the suppression and enhancement phenomena observed in the subpopulation of binocular neurons. In so doing, the authors reify the importance of incorporating ocular dominance in computational models of binocular combination.

The conclusions of this paper are mostly well supported by the data, but there are some limitations of the methodology that need to be clarified, and an expansion of how the results relate to previous work would better contextualize these important findings in the literature.

Strengths:<br /> The two-photon imaging technique used to resolve the activity of individual neurons within intact brain tissue grants a host of advantages. Foremost, two-photon imaging confers considerably high spatial resolution. As a result, the authors were able to sample and analyze the activity from thousands of verified superficial-layer V1 neurons. The animal model used, awake macaques, is also highly relevant for the study of binocular combination. Macaques, like humans, are binocular animals, meaning they have forward-facing eyes that confer overlapping visual fields. Importantly, macaque V1 is organized into cortical columns that process specific visual features from the separate eyes just like in humans. In combination with a powerful imaging technique, this allowed the authors to evaluate the monocular and binocular response profiles of V1 neurons that are situated within neighboring ocular dominance columns, a novel feat. To this aim, the approach was well-executed and should instill further confidence in the notion that V1 neurons combine monocular information in a manner that is dependent on the strength of their ocular dominance.

Weaknesses:<br /> While two-photon imaging provides excellent spatial resolution, its temporal resolution is often lower compared to some other techniques, such as electrophysiology. This limits the ability to study the fast dynamics of neuronal activity, a well-understood trade-off of the method. The issue is more so that the authors draw comparisons to electrophysiological studies without explicit appreciation of the temporal difference between these techniques. In a similar vein, two-photon imaging is limited spatially in terms of cortical depth, preferentially sampling from neurons in layers 2/3. This limitation does not invalidate any of the interpretations but should be considered by readers, especially when making comparisons to previous electrophysiological reports using microelectrode linear arrays that sample from all cortical layers. Indeed, it is likely that a complete picture of early cortical binocular processing will require high spatial resolution (i.e., sampling from neurons in neighboring ocular dominance columns, from pia mater to white matter) at the biophysically relevant timescales (1ms resolution, capturing response dynamics over the full duration of the stimulus presentation, including the transient onset and steady-state periods).

Reviewer #2 (Public Review):

Summary:<br /> This study examines the pattern of responses produced by the combination of left-eye and right-eye signals in V1. For this, they used calcium imaging of neurons in V1 of awake, fixating monkeys. They take advantage of calcium imaging, which yields large populations of neurons in each field of view. With their data set, they observe how response magnitude relates to ocular dominance across the entire population. They analyze carefully how the relationship changed as the visual stimulus switched from contra-eye only, ipsi-eye only, and binocular. As expected, the contra-eye-dominated neurons responded strongly with a contra-eye-only stimulus. The ipsi-eye-dominated neurons responded strongly with an ipsi-eye-only stimulus. The surprise was responses to a binocular stimulus. The responses were similarly weak across the entire population, regardless of each neuron's ocular dominance. They conclude that this pattern of responses could be explained by interocular divisive normalization, followed by binocular summation.

Strengths:<br /> A major strength of this work is that the model-fitting was done on a large population of simultaneously recorded neurons. This approach is an advancement over previous work, which did model-fitting on individual neurons. The fitted model in the manuscript represents the pattern observed across the large population in V1, and washes out any particular property of individual neurons. Given the large neuronal population from which the conclusion was drawn, the authors provide solid evidence supporting their conclusion. They also observed consistency across 5 fields of view.

The experiments were designed and executed appropriately to test their hypothesis. Their data support their conclusion.

Weaknesses:<br /> One weakness of their study is that calcium signals can exaggerate the nonlinear properties of neurons. Calcium imaging renders poor responses poorer and strong responses stronger, compared to single-unit recording. In particular, the dramatic change in the population response between monocular stimulation and binocular stimulation could actually be less pronounced when measured with single-unit recording methods. This means their choice of recording method could have accidentally exaggerated the evidence of their finding.

The implication of their finding is that strong ocular dominance is the result of release from interocular suppression by a monocular stimulus, rather than the lack of binocular combination as many traditional studies have assumed. This could significantly advance our understanding of the binocular combination circuitry of V1. The entire population of neurons could be part of a binocular combination circuitry present in V1.

Reviewer #3 (Public Review):

The authors have made simultaneous recordings of the responses of large numbers of neurons from the primary visual cortex using optical two-photon imaging of calcium signals from the superficial layers of the cortex. Recordings were made to compare the responses of the cortical neurons under normal binocular viewing of a flat screen with both eyes open and monocular viewing of the same screen with one eye's view blocked by a translucent filter. The screen displayed visual stimuli comprising small contrast patches of Gabor function distributions of luminance, a stimulus that is known to excite cortical neurons.

This is an important data set, given the large numbers of neurons recorded. The authors present a simple model to explain the binocular combination of neuronal signals from the right and left eyes.

The limitations of the paper as written are as follows. These points can be addressed with some additional analysis and rewriting of sections of the paper. No new experimental data need to be collected.

1) The authors should acknowledge the fact that these recordings arise from neurons in the superficial layers of the cortex. This limitation arises from the usual constraints on optical imaging in the macaque cortex. This means that the sample of neurons forming this data set is not fully representative of the population of binocular neurons within the visual cortex. This limitation is important in comparing the outcome of these experiments with the results from other studies of binocular combination, which have used single-electrode recording. Electrode recording will result in a sample of neurons that is drawn from many layers of the cortex, rather than just the superficial layers.

2) Single-neuron recording of binocular neurons in the primary visual cortex has shown that these neurons often have some spontaneous activity. Assessment of this spontaneous level of firing is important for accurate model fitting [1]. The paper here should discuss the level of spontaneous neuronal firing and its potential significance.

3) The arrangements for visual stimulation and comparison of binocular and monocular responses mean that the stereoscopic disparity of the binocular stimuli is always at zero or close to zero. The animal's fixation point is in the centre of a single display that is viewed binocularly. The fixation point is, by definition, at zero disparity. The other points on the flat display are also at zero disparity or very close to zero because they lie in the same depth plane. There will be some small deviations from exactly zero because the geometry of the viewing arrangements results in the extremities of the display being at a slightly different distance than the centre. Therefore, the visual stimulation used to test the binocular condition is always at zero disparity, with a slight deviation from zero at the edges of the display, and never changes. [There is a detail that can be ignored. The experimenters tested neurons with visual stimulation at different real distances from the eyes, but this is not relevant here. Provided the animals accurately converged their eyes on the provided binocular fixation point, then the disparity of the visual stimuli will always be at or close to zero, regardless of viewing distance in these circumstances.] However, we already know from earlier work that neurons in the visual cortex exhibit a range of selectivity for binocular disparity. Some neurons have their peak response at non-zero disparities, representing binocular depths nearer than the fixation depth or beyond it. The response of other neurons is maximally suppressed by disparities at the depth of the fixation point (so-called Tuned Inhibitory [TI] neurons). The simple model and analysis presented in the paper for the summation of monocular responses to predict binocular responses will perform adequately for neurons that are tuned to zero disparity, so-called tuned excitatory neurons [TE], but is necessarily compromised when applied to neurons that have other, different tuning profiles. Specifically, when neurons are stimulated binocularly with a non-preferred disparity, the binocular response may be lower than the monocular response[2, 3]. This more realistic view of binocular responses needs to be considered by the authors and integrated into their modelling.

4) The data in the paper show some features that have been reported before but are not captured by the model. Notably for neurons with extreme values of ocular dominance, the binocular response is typically less than the larger of the two monocular responses. This is apparent in the row of plots in Figure 2D from individual animals and in the pooled data in Figure 2E. Responses of this type are characteristic of tuned inhibitory [TI] neurons[2]. It is not immediately clear why this feature of the data does not appear in the summary and analysis in Figure 3. The paper text states that the responses were "first normalized by the median of the binocular responses". This will certainly get rid of this characteristic of the data, but this step needs better justification, or an amendment to the main analysis is needed. In the present form, the model and analysis do not appear to fit the data in Figure 2 as accurately as needed. The authors should address the discrepancy between the data as presented in Figures 2D, E, and Figure 3.

Citations<br /> 1. Prince, S.J.D., Pointon, A.D., Cumming, B.G., and Parker, A.J., (2002). Quantitative analysis of the responses of V1 neurons to horizontal disparity in dynamic random-dot stereograms. Journal of Neurophysiology, 87: 191-208.<br /> 2. Prince, S.J.D., Cumming, B.G., and Parker, A.J., (2002). Range and mechanism of encoding of horizontal disparity in macaque V1. Journal of Neurophysiology, 87: 209-221.<br /> 3. Poggio, G.F. and Fischer, B., (1977). Binocular interaction and depth sensitivity in striate and prestriate cortex of behaving rhesus monkey. Journal of Neurophysiology, 40: 1392-1405 doi 10.1152/jn.1977.40.6.1392.

Reviewer #1 (Public Review):

Summary:<br /> The authors ran an explorative analysis in order to describe how a "tri-partite" brain network model could describe the combination of resting fMRI data and individual characteristics. They utilized previously obtained fMRI data across four scanning runs in 144 individuals. At the end of each run, participants rated their patterns of thinking on 12 statements (short multi-dimensional experience sampling-MDES) using a 0-100% visual analog scale. Also, 71 personality traits were obtained on 21 questionnaires. The authors ran two separate principal component analyses (PCA) to obtain low dimensional summaries of the two individual characteristics (personality traits from questionnaires, and thought patterns from MDES). The dimensionality reduction of the fMRI data was done by means of gradient analysis, which was combined with Neurosynth decoding to visualize the functional axis of the gradients. To test the reliability of thought components across scanning time, intra-class correlation coefficients (ICC) were calculated for the thought patterns, and discriminability indices were calculated for whole gradients. The relationship between individual differences in traits, thoughts, and macro-scale gradients was tested with multivariate regression.

The authors found: a) reliability of thought components across the one hour of scanning, b) Gradient 1 differentiated between visual regions and DMN, Gradient 2 dissociated somatomotor from visual cortices, Gradient 3 differentiated the DMN from the fronto-parietal system, c) the associations between traits/thought patterns and brain gradients revealed significant effects of "introversion" and "specific internal" thought: "Introversion" was associated with variant parcels on the three gradients, with most of parcels belonging to the VAN and then to the DMN; and "Specific internal thought" was associated with variant parcels on the three gradients with most of parcels belonging to the DAN and then the visual. The authors conclude that interactions between attention systems and the DMN are important influences on ongoing thought at rest.

Strengths:<br /> The study's strength lies in its attempt to combine brain activity with individual characteristics using state-of-the-art methodologies.

Weaknesses:<br /> The study protocol in its current form restricts replicability. This is largely due to missing information on the MRI protocol and data preprocessing. The article refers the reader to the work of Mendes et al 2019 which is said to provide this information, but the paper should rather stand alone with all this crucial material mentioned here, as well. Also, effect sizes are provided only for the multiple multivariate regression of the inter-class correlations, which makes it difficult to appreciate the power of the other obtained results.

Reviewer #2 (Public Review):

The authors set out to draw further links between neural patterns observed at "rest" during fMRI, with their related thought content and personality traits. More specifically, they approached this with a "tri-partite network" view in mind, whereby the ventral attention network (VAN), the dorsal attention network (DAN), and the default mode network (DMN) are proposed to play a special role in ongoing conscious thought. They used a gradients approach to determine the low dimensional organisation of these networks. In concert, using PCA they reduced thought patterns captured at four time points during the scan, as well as traits captured from a large battery of questionnaires.

The main findings were that specific thought and trait components were related to variations in the organisation of the tri-partite networks, with respect to cortical gradients.

Strengths of the methods/results: Having a long (1 hr) resting state MRI session, which could be broken down into four separate scanning/sampling components is a strength. Importantly, the authors could show (via intra-class correlation coefficients) the similarity of thoughts and connectivity gradients across the entire session. Not only did this approach increase the richness of the data available to them, it speaks in an interesting way to the stability of these measures. The inclusion of both thought patterns during scanning along with trait-level dispositional factors is most certainly a strength, as many studies will often include either/or of these, rather than trying to reconcile across. Of the two main findings, the finding that detailed self-generated thought was associated with a decoupling of regions of DAN from regions in DMN was particularly compelling, in light of mounting literature from several fields that support this.

Weaknesses of the methods/results: Considering the richness of the thought and personality data, I was a little surprised that only two main findings emerged (i.e., a relationship with trait introversion, and a relationship with the "specific internal" thought pattern). I wondered whether, at least in part and in relation to traits, this might stem from the large and varied set of questionnaires used to discern the traits. These questionnaires mostly comprised personality/mood, but some sampled things that do not fall into that category (e.g., musicality, internet addition, sleep), and some related directly to spontaneous thought properties (e.g., mind wandering, musical imagery). It would be interesting to see what relationships would emerge by being more selective in the traits measured, and in the tools to measure them.

Taken together, the main findings are interesting enough. However, the real significance of this work, and its impact, lie in the richness of the approach: combing across fMRI, spontaneous thought, and trait-level factors. Triangulating these data has important potential for furthering our understanding of brain-behaviour relationship across different levels of organisation.

Reviewer #1 (Public Review):

Summary:<br /> This paper describes a reanalysis of data collected by Gagne et al. (2020), who investigated how human choice behaviour differs in response to changes in environmental volatility. Several studies to date have demonstrated that individuals appear to increase their learning rate in response to greater volatility and that this adjustment is reduced amongst individuals with anxiety and depression. The present authors challenge this view and instead describe a novel Mixture of Strategies (MOS) model, that attributes individual differences in choice behaviour to different weightings of three distinct decision-making strategies. They demonstrate that the MOS model provides a superior fit to the data and that the previously observed differences between patients and healthy controls may be explained by patients opting for a less cognitively demanding, but suboptimal, strategy.

Strengths:<br /> The authors compare several models (including the original winning model in Gagne et al., 2020) that could feasibly fit the data. These are clearly described and are evaluated using a range of model diagnostics. The proposed MOS model appears to provide a superior fit across several tests.

The MOS model output is easy to interpret and has good face validity. This allows for the generation of clear, testable, hypotheses, and the authors have suggested several lines of potential research based on this.

Weaknesses:<br /> The authors justify this reanalysis by arguing that learning rate adjustment (which has previously been used to explain choice behaviour on volatility tasks) is likely to be too computationally expensive and therefore unfeasible. It is unclear how to determine how "expensive" learning rate adjustment is, and how this compares to the proposed MOS model (which also includes learning rate parameters), which combines estimates across three distinct decision-making strategies.

As highlighted by the authors, the model is limited in its explanation of previously observed learning differences based on outcome value. It's currently unclear why there would be a change in learning across positive/negative outcome contexts, based on strategy choice alone.

Reviewer #2 (Public Review):

Summary:<br /> Previous research shows that humans tend to adjust learning in environments where stimulus-outcome contingencies become more volatile. This learning rate adaptation is impaired in some psychiatric disorders, such as depression and anxiety. In this study, the authors reanalyze previously published data on a reversal-learning task with two volatility levels. Through a new model, they provide some evidence for an alternative explanation whereby the learning rate adaptation is driven by different decision-making strategies and not learning deficits. In particular, they propose that adjusting learning can be explained by deviations from the optimal decision-making strategy (based on maximizing expected utility) due to response stickiness or focus on reward magnitude. Furthermore, a factor related to the general psychopathology of individuals with anxiety and depression negatively correlated with the weight on the optimal strategy and response stickiness, while it correlated positively with the magnitude strategy (a strategy that ignores the probability of outcome).

Strengths:<br /> The main strength of the study is a novel and interesting explanation of an otherwise well-established finding in human reinforcement learning. This proposal is supported by rigorously conducted parameter retrieval and the comparison of the novel model to a wide range of previously published models.

Weaknesses:<br /> My main concern is that the winning model (MOS6) does not have an error term (inverse temperature parameter beta is fixed to 8.804).

1) It is not clear why the beta is not estimated and how were the values presented here chosen. It is reported as being an average value but it is not clear from which parameter estimation. Furthermore, with an average value for participants that would have lower values of inverse temperature (more stochastic behaviour) the model is likely overfitting.

2) In the absence of a noise parameter, the model will have to classify behaviour that is not explained by the optimal strategy (where participants simply did not pay attention or were not motivated) as being due to one of the other two strategies.

3) A model comparison among models with inverse temperature and variable subsets of the three strategies (EU + MO, EU + HA) would be interesting to see. Similarly, comparison of the MOS6 model to other models where the inverse temperature parameter is fixed to 8.804).

This is an important limitation because the same simulation as with the MOS model in Figure 3b can be achieved by a more parsimonious (but less interesting) manipulation of the inverse temperature parameter.

Furthermore, the claim that the EU represents an optimal strategy is a bit overstated. The EU strategy is the only one of the three that assumes participants learn about the stimulus-outcomes contingencies. Higher EU strategy utilisation will include participants that are more optimal (in maximum utility maximisation terms), but also those that just learned better and completely ignored the reward magnitude.

Other minor issues that I have are the following:<br /> The mixture strategies model is an interesting proposal, but seems to be a very convoluted way to ask: to what degree are decisions of subjects affected by reward, what they've learned, and response stickiness? It seems to me that the same set of questions could be addressed with a simpler model that would define choice decisions through a softmax with a linear combination of the difference in rewards, the difference in probabilities, and a stickiness parameter.

Learning rate adaptation was also shown with tasks where decision-making strategies play a less important role, such as the Predictive Inference task (see for instance Nassar et al, 2010). When discussing the merit of the findings of this study on learning rate adaptation across volatility blocks, this work would be essential to mention.

Reviewer #3 (Public Review):

Summary:<br /> This paper presents a new formulation of a computational model of adaptive learning amid environmental volatility. Using a behavioral paradigm and data set made available by the authors of an earlier publication (Gagne et al., 2020), the new model is found to fit the data well. The model's structure consists of three weighted controllers that influence decisions on the basis of (1) expected utility, (2) potential outcome magnitude, and (3) habit. The model offers an interpretation of psychopathology-related individual differences in decision-making behavior in terms of differences in the relative weighting of the three controllers.

Strengths:<br /> The newly proposed "mixture of strategies" (MOS) model is evaluated relative to the model presented in the original paper by Gagne et al., 2020 (here called the "flexible learning rate" or FLR model) and two other models. Appropriate and sophisticated methods are used for developing, parameterizing, fitting, and assessing the MOS model, and the MOS model performs well on multiple goodness-of-fit indices. The parameters of the model show decent recoverability and offer a novel interpretation for psychopathology-related individual differences. Most remarkably, the model seems to be able to account for apparent differences in behavioral learning rates between high-volatility and low-volatility conditions even with no true condition-dependent change in the parameters of its learning/decision processes. This finding calls into question a class of existing models that attribute behavioral adaptation to adaptive learning rates.

Weaknesses:<br /> 1. Some aspects of the paper, especially in the methods section, lacked clarity or seemed to assume context that had not been presented. I found it necessary to set the paper down and read Gagne et al., 2020 in order to understand it properly.

2. There is little examination of why the MOS model does so well in terms of model fit indices. What features of the data is it doing a better job of capturing? One thing that makes this puzzling is that the MOS and FLR models seem to have most of the same qualitative components: the FLR model has parameters for additive weighting of magnitude relative to probability (akin to the MOS model's magnitude-only strategy weight) and for an autocorrelative choice kernel (akin to the MOS model's habit strategy weight). So it's not self-evident where the MOS model's advantage is coming from.

3. One of the paper's potentially most noteworthy findings (Figure 5) is that when the FLR model is fit to synthetic data generated by the expected utility (EU) controller with a fixed learning rate, it recovers a spurious difference in learning rate between the volatile and stable environments. Although this is potentially a significant finding, its interpretation seems uncertain for several reasons:

- According to the relevant methods text, the result is based on a simulation of only 5 task blocks for each strategy. It would be better to repeat the simulation and recovery multiple times so that a confidence interval or error bar can be estimated and added to the figure.

- It makes sense that learning rates recovered for the magnitude-oriented (MO) strategy are near zero, since behavior simulated by that strategy would have no reason to show any evidence of learning. But this makes it perplexing why the MO learning rate in the volatile condition is slightly positive and slightly greater than in the stable condition.

- The pure-EU and pure-MO strategies are interpreted as being analogous to the healthy control group and the patient group, respectively. However, the actual difference in estimated EU/MO weighting between the two participant groups was much more moderate. It's unclear whether the same result would be obtained for a more empirically plausible difference in EU/MO weighting.

- The fits of the FLR model to the simulated data "controlled all parameters except for the learning rate parameters across the two strategies" (line 522). If this means that no parameters except learning rate were allowed to differ between the fits to the pure-EU and pure-MO synthetic data sets, the models would have been prevented from fitting the difference in terms of the relative weighting of probability and magnitude, which better corresponds to the true difference between the two strategies. This could have interfered with the estimation of other parameters, such as learning rate.

- If, after addressing all of the above, the FLR model really does recover a spurious difference in learning rate between stable and volatile blocks, it would be worth more examination of why this is happening. For example, is it because there are more opportunities to observe learning in those blocks?

4. Figure 4C shows that the habit-only strategy is able to learn and adapt to changing contingencies, and some of the interpretive discussion emphasizes this. (For instance, line 651 says the habit strategy brings more rewards than the MO strategy.) However, the habit strategy doesn't seem to have any mechanism for learning from outcome feedback. It seems unlikely it would perform better than chance if it were the sole driver of behavior. Is it succeeding in this example because it is learning from previous decisions made by the EU strategy, or perhaps from decisions in the empirical data?

5. For the model recovery analysis (line 567), the stated purpose is to rule out the possibility that the MOS model always wins (line 552), but the only result presented is one in which the MOS model wins. To assess whether the MOS and FLR models can be differentiated, it seems necessary also to show model recovery results for synthetic data generated by the FLR model.

6. To the best of my understanding, the MOS model seems to implement valence-specific learning rates in a qualitatively different way from how they were implemented in Gagne et al., 2020, and other previous literature. Line 246 says there were separate learning rates for upward and downward updates to the outcome probability. That's different from using two learning rates for "better"- and "worse"-than-expected outcomes, which will depend on both the direction of the update and the valence of the outcome (reward or shock). Might this relate to why no evidence for valence-specific learning rates was found even though the original authors found such evidence in the same data set?

7. The discussion (line 649) foregrounds the finding of greater "magnitude-only" weights with greater "general factor" psychopathology scores, concluding it reflects a shift toward simplifying heuristics. However, the picture might not be so straightforward because "habit" weights, which also reflect a simplifying heuristic, correlated negatively with the psychopathology scores.

Reviewer #1 (Public Review):

Nitrogen metabolism is of fundamental importance to biology. However, the metabolism and biochemistry of guanidine and guanidine containing compounds, including arginine and homoarginine, have been understudied over the last few decades. Very few guanidine forming enzymes have been identified. Funck et al define a new type of guanidine forming enzyme. It was previously known that 2-oxogluturate oxygenase catalysis in bacteria can produce guanidine via oxidation of arginine. Interestingly, the same reported enzyme that produces guanidine from arginine also oxidises 2-oxogluturate to give the plant signalling molecule ethylene. Funck et al show that a mechanistically related oxygenase enzyme from plants can also produce guanidine, but instead of using arginine as a substrate, it uses homoarginine and does not produce ethylene. The work will stimulate interest in the cellular roles of homoarginine, a metabolite present in plants and other organisms including humans and, more generally, in the biochemistry and metabolism of guanidine derivatives.

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

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

Overall, I thought this was a very interesting study, comprising biochemical, cellular, and in vivo studies. Of course, more could be done on each of these, and likely will be, but I think the assignment of biochemical function is very strong, across all three approaches. The one new experiment I requested was a demonstration of whether ethylene is produced by the new enzymes - this was clearly shown not to be the case.

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

Summary:<br /> "Phosphorylation, disorder, and phase separation govern the behavior of Frequency in the fungal circadian clock" is a convincing manuscript that delves into the structural and biochemical aspects of FRQ and the FFC under both LLPS and non-LLPS conditions. Circadian clocks serve as adaptations to the daily rhythms of sunlight, providing a reliable internal representation of local time.

All circadian clocks are composed of positive and negative components. The FFC contributes negative feedback to the Neurospora circadian oscillator. It consists of FRQ, CK1, and FRH. The FFC facilitates close interaction between CK1 and the WCC, with CK1-mediated phosphorylation disrupting WCC:c-box interactions necessary for restarting the circadian cycle.

Despite the significance of FRQ and the FFC, challenges associated with purifying and stabilizing FRQ have hindered in vitro studies. Here, researchers successfully developed a protocol for purifying recombinant FRQ expressed in E. coli.

Armed with full-length FRQ, they utilized spin-labeled FRQ, CK1, and FRH to gain structural insights into FRQ and the FFC using ESR. These studies revealed a somewhat ordered core and a disordered periphery in FRQ, consistent with prior investigations using limited proteolysis assays. Additionally, p-FRQ exhibited greater conformational flexibility than np-FRQ, and CK1 and FRH were found in close proximity within the FFC. The study further demonstrated that under LLPS conditions in vitro, FRQ undergoes phase separation, encapsulating FRH and CK1 within LLPS droplets, ultimately diminishing CK1 activity within the FFC. Intriguingly, higher temperatures enhanced LLPS formation, suggesting a potential role of LLPS in the fungal clock's temperature compensation mechanism.

Biological significance was supported by live imaging of Neurospora, revealing FRQ foci at the periphery of nuclei consistent with LLPS. The amino acid sequence of FRQ conferred LLPS properties, and a comparison of clock repressor protein sequences in other eukaryotes indicated that LLPS formation might be a conserved process within the negative arms of these circadian clocks.

In summary, this manuscript represents a valuable advancement with solid evidence in the understanding of a circadian clock system that has proven challenging to characterize structurally due to obstacles linked to FRQ purification and stability. The implications of LLPS formation in the negative arm of other eukaryotic clocks and its role in temperature compensation are highly intriguing.

Reviewer #2 (Public Review):

Summary:<br /> This study presents data from a broad range of methods (biochemical, EPR, SAXS, microscopy, etc.) on the large disordered protein FRQ relevant to circadian clocks and its interaction partners FRH and CK1, providing novel and fundamental insight into oligomerization state, local dynamics, and overall structure as a function of phosphorylation and association. Liquid-liquid phase separation is observed. These findings have bearings on the mechanistic understanding of circadian clocks, and on functional aspects of disordered proteins in general.

Strengths:<br /> This is a thorough work that is well presented. The data are of overall high quality given the difficulty of working with an intrinsically disordered protein, and the conclusions are sufficiently circumspect and qualitative to not overinterpret the mostly low-resolution data.

Weaknesses:<br /> None

Reviewer #3 (Public Review):

Summary:<br /> The manuscript from Tariq and Maurici et al. presents important biochemical and biophysical data linking protein phosphorylation to phase separation behavior in the repressive arm of the Neurospora circadian clock. This is an important topic that contributes to what is likely a conceptual shift in the field.

Joint Public Review:

The authors previously showed that expressing formate dehydrogenase, rubisco, carbonic anhydrase, and phosphoribulokinase in Escherichia coli, followed by experimental evolution, led to the generation of strains that can metabolise CO2. Using two rounds of experimental evolution, the authors identify mutations in three genes - pgi, rpoB, and crp - that allow cells to metabolise CO2 in their engineered strain background. The authors make a strong case that mutations in pgi are loss-of-function mutations that prevent metabolic efflux from the reductive pentose phosphate autocatalytic cycle. The authors also use proteomic analysis to probe the role of the mutations in crp and rpoB. While they do not reach strong conclusions about how these mutations promote autotrophic growth, they provide some clues, leading to valuable speculation.

Comments on revised version:<br /> The authors have thoroughly addressed the reviewers' comments. The major addition to the paper is the proteomic analysis of single and double mutants of crp and rpoB. These new data provide clues as to the role of the crp and rpoB mutations in promoting autotrophic growth, which the authors discuss. The authors acknowledge that it will require additional experiments to determine whether the speculated mechanisms are correct. Nonetheless, the new data provide valuable new insight into the role of the crp and rpoB mutations. The authors have also expanded their description of the crp and rpoB mutations, making it clearer that the effects of these mutations are likely to be distinct, albeit with potential for overlap in function.

Joint Public Review:

The manuscript highlights a mechanistic insight into meiotic initiation in budding yeast. In this study, the authors analyzed the genetic link between the mitotic cell cycle regulator SBF (the Swi4-Swi6 complex) and a meiosis inducing regulator Ime1 in the context of meiotic initiation. The authors' comprehensive analyses with cytology, imaging, RNA-seq using mutant strains lead to the conclusion that Swi4 levels regulates Ime1-Ume6 interaction to activate expression of early meiosis genes for meiotic initiation.

The authors first show a down regulation of Swi4 at the protein level upon meiosis entry and then investigate downstream consequences. This study reveals several regulations: 1) Mutations in CLN1 and 2, which are targets of Swi4, allow rescuing the delay in meiotic entry observed when Swi4 is overexpressed; 2) Ime1 activity is antigonized by Swi4, and more specifically its interaction with Ume6. 3) Expression of SWI4 is regulated by LUTI-based transcription at the SWI4 locus that impedes expression of canonical SWI4 transcripts 4) The expression of SWI4 LUTI is likely negatively regulated by the Ime1-Ume6 complex 5) Whi5 restrict SBF activity during meiotic entry, thereby ensuring Cyclin repression.

The important implication in this paper is that meiotic initiation is regulated by the balance of mitotic cell cycle regulator and meiosis-specific transcription factor.

Joint Public Review:

Summary<br /> Sender et al describe a model to estimate what fraction of DNA becomes cell-free DNA in plasma. This is of great interest to the community, as the amount of DNA from a certain tissue (for example, a tumor) that becomes available for detection in the blood has important implications for disease detection.

Strengths<br /> The question asked by the authors has potentially important implications for disease diagnosis. Understanding how genomic DNA degrades in the human circulation can guide towards ways to enrich for DNA of interest or may lead to unexpected methods of conserving cell-free DNA. Thus, the question "how much genomic DNA becomes cfDNA" is of great interest to the scientific and medical community. I believe this manuscript has the potential to be a widely used resource. As more data is collected on cell-free DNA yields and cellular turnover in the body, this work will only increase in importance.

Appraisal<br /> At this stage of the manuscript (second submission), I think the authors provide important evidence and analysis that aim to answer their research question. Previous concerns about methodology have been addressed.

Impact<br /> This manuscript will be highly impactful on the community. The field of liquid biopsies (non-invasive diagnostics) has the potential to revolutionize the medical field (and has already in certain areas, such as prenatal diagnostics). Yet, there is a lack of basic science questions in the field. This manuscript is an important step forward in asking more "basic science" questions that seek to answer a fundamental biological question.

Reviewer #3 (Public Review):

Summary<br /> Pham, Pahuja, Hagenbeek, et al. have conducted a comprehensive range of assays to biochemically and genetically determine TEAD degradation through RNF146 ubiquitination. Additionally, they designed a PROTAC protein degrader system to regulate the Hippo pathway through TEAD degradation. Overall, the data appears robust. However, the manuscript lacks detailed methodological descriptions, which should be addressed and improved. For instance, the methods used to analyze the K48 ubiquitination site on TEAD and the gene expression analysis of Hippo Signaling are unclear. Furthermore, the multiple proteomics, RNA-seq, and ATAC-seq data must be made publicly available upon publication to ensure reproducibility. Most of the main figures are of low resolution, which needs addressing.

Strengths:<br /> - A broad range of assays was used to robustly determine the role of RNF146 in TEAD degradation.<br /> - Development of novel PROTAC for degrading TEAD.

Weaknesses:<br /> - An orthogonal approach is needed (e.g., PARP1 inhibitor) to demonstrate PARP1's dependency in TEAD ubiquitination.

- The data from Table 2 is unclear in illustrating the association of identified K48 ubiquitination with TEAD4, especially since the experiments were presumably to be conducted on whole cell lysates with KGG enrichment. This raises the possibility that the K48 ubiquitination could originate from other proteins. Alternatively, if the authors performed immunoprecipitation on TEAD followed by mass spectrometry, this should be explicitly described in the text and materials and methods section.

- Figure 2D: The methodology for measuring the Hippo signature is unclear, as is the case for Figures 7E and F regarding the analysis of Hippo target genes.

- Figure S3F requires quantification with additional replicates for validation.

- There is a misleading claim in the discussion stating "TEAD PARylation by PAR-family members (Figure 3)"; however, the demonstration is only for PARP1, which should be corrected.

Reviewer #1 (Public Review):

Summary:<br /> In the first half of this study, Pham et al. investigate the regulation of TEAD via ubiquitination and PARylation, identifying an E3 ubiquitin ligase, RNF146, as a negative regulator of TEAD activity through an siRNA screen of ubiquitin-related genes in MCF7 cells. The study also finds that depletion of PARP1 reduced TEAD4 ubiquitination levels, suggesting a certain relationship between TEAD4 PARylation and ubiquitination which was also explored through an interesting D70A mutation. Pham et al. subsequently tested this regulation in D. melanogaster by introducing Hpo loss-of-function mutations and rescuing the overgrowth phenotype through RNF146 overexpression.

In the second half of this study, Pham et al. designed and assayed several potential TEAD degraders with a heterobifunctional design, which they term TEAD-CIDE. Compounds D and E were found to effectively degrade pan-TEAD, an effect which could be disrupted by treatment with TEAD lipid pocket binders, proteasome inhibitors, or E1 inhibitors, demonstrating that the TEAD-CIDEs operate in a proteasome-dependent manner. These TEAD-CIDEs could reduce cell proliferation in OVCAR-8, a YAP-deficient cell line, but not SK-N-FI, a Hippo pathway independent cell line. Finally, this study also utilizes ATAC-seq on Compound D to identify reductions in chromatin accessibility at the regions enriched for TEAD DNA binding motifs.

Strengths:<br /> The study provides compelling evidence that the E3 ubiquitin ligase RNF146 is a novel negative regulator of TEAD activity. The authors convincingly delineate the mechanism through multiple techniques and approaches. The authors also describe the development of heterobifunctional pan-degraders of TEAD, which could serve as valuable reagents to more deeply study TEAD biology.

Weaknesses:<br /> The scope of this study is extremely broad. The first half of the paper highlights the mechanisms underlying TEAD degradation; however, the connection to the second half of the paper on small molecule degraders of TEAD is jarring, and it seems as though two separate stories were combined into this single massive study. In my opinion, the study would be stronger if it chose to focus on only one of these topics and instead went deeper.

Additionally, the figure clarity needs to be substantially improved, as readability and interpretation were difficult in many panels. Lastly, there are numerous typos and poor grammar throughout the text that need to be addressed.

Reviewer #2 (Public Review):

The paper is made of two parts. One deals with RNF146, the other with the development of compounds that may cause TEAD degradation. The two parts are rather unrelated to each other.

The main limit of this work is the lack of evidence that TEAD factors are in fact regulated by the proteasome and ubiquitylation under endogenous conditions. Also lacking is the demonstration that TEADs are labile proteins to the extent that such quantitative regulation at the level of stability can impact on YAP-TAZ biology. Without these two elements, the relevance and physiological significance of all these data is lacking.

As for the development of new inhibitors of TEAD, this is potentially very interesting but underdeveloped in this manuscript. Irrespectively, if TEAD is stable, these molecules are likely lead compounds of interest. If TEAD is unstable, as entertained in the first part of the paper, then these molecules are likely marginal.

Here are a few other specific observations:

1 The effect of MG is shown in a convoluted way, by MS. What about endogenous TEAD protein stability?

2 The relevance of siRNF on YAP target genes of Fig.2D is not statistically significant.

3 All assays are with protein overexpression and Ub-laddering

4 An inconsistency exists on the only biological validation (only by overexpression) on the fly eye size. RNF gain in Fig4C is doing the opposite of what is expected from what is portrayed here as a YAP/TEAD inhibitor: RNF gain is shown to INCREASE eye size, phenocopying a Hippo loss of function phenotype. According to the model proposed, RNF addition should reduce eye size. The authors stated that " This is in contrast to the anti-growth effect of RNF-146 in the Hpo loss-of-function background and indicates RNF146 may regulate other genes/pathways controlling eye sizes besides its role as a negative regulator of Sd/yki activity". This raises questions on what the authors are really studying: why, according to the authors, these caveats should occur on the controls, and not when they study Hpo mutants?

5 The role of TEAD inactivation on YAP function is already well known. Disappointingly no prior literature is cited. In any case, this is a mere control.

6 The second part of the paper on the Development and Screening of pan-TEAD lipid pocket degraders is interesting but unconnected to the above. The degradation pathway it involves has nothing to do with the enzyme described in the first figures.

7 The role of CIDE on YAP accessibility to Chromatin is superficially executed. Key controls are missing along with the connection with mechanisms and prior knowledge, of TEAD, YAP, chromatin, and other TEAD inhibitors, just to mention a few.

8 The physiological relevance and the mechanistic interpretation of what should be in the ATAC seq in ovcar cells is missing.

Reviewer #1 (Public Review):

Summary:<br /> The current manuscript provides an extensive in vivo analysis of two guidance pathways identifying multiple mechanisms that shape the bifurcation of DRG axons when forming the dorsal funiculus in the DREZ.

Strengths:<br /> Multiple mouse mutant lines were used, together with complementary techniques; the results are very clear and compelling.<br /> The findings are very significant and clearly move forward our understanding of the regulation of axonal development at the DREZ.

Weaknesses:<br /> No major weaknesses were found. As it is I have no recommendations that would increase the clarity or quality of the manuscript.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors conduct a detailed analysis of the molecular cues that control the guidance of bifurcated dorsal root ganglion axons in a key region of the spinal cord called the dorsal funiculus. This is a specific case of axon guidance that occurs in a precise way. The authors knew that Slit was important but many axons still target correctly in Slit knockouts, suggesting a role for other guidance factors. Netrin1 is also expressed in this region, so they looked at netrin mutants. The authors found axons outside the DREZ in the Ntn1 mutants, and they show by single-neuron genetic labeling that many of these come from DRG neurons. Quantified axonal tracing studies in Slit1/2, Ntn1, or triple mutant embryos support the idea that Slit and Ntr1 have distinct functions in guidance and that the effect of their loss is additive. Interestingly none of these knockouts affect bifurcation itself but rather the guidance of one or both of the bifurcated axon terminals. Knockout of the Slit receptors (Robo1/2) or the Netrin 1 receptor (DCC) in embryos causes similar guidance defects to loss of the ligands, providing additional confirmation of the requirement for both guidance pathways.

Strengths:<br /> This study expands understanding of the role of the axon guidance factors Ntr1/DCC and Slit/Robo in a specific axon guidance decision. The strength of the study is the careful axonal labeling and quantification, which allows the authors to establish precise consequences of the loss of each guidance factor or receptor.

Weaknesses:<br /> There are some places in the text where the discussion of these data is compared with other studies and models, but additional details would help clarify the arguments.

Reviewer #3 (Public Review):

Summary:<br /> In this paper, Curran et al investigate the role of Ntn, Slit1, and Slit 2 in the axon patterning of DRG neurons. The paper uses mouse genetics to perturb each guidance molecule and its corresponding receptor. Cre-based approaches and immunostaining of DRG neurons are used to assess the phenotypes. Overall, the study uses the strength of mouse genetics and imaging to reveal new genetic modifiers of DRG axons. The conclusions of the experiments match the presented results. The paper is an important contribution to the field, as evidence that dorsal funiculus formation is impacted by Ntn and Slit signaling. However, there are some potential areas of the manuscript that should be edited to better match the results with the conclusions of the work.

Strengths:<br /> The manuscript uses the advantage of mouse genetics to investigate the axon patterning of DRG neurons. The work does a great job of assessing individual phenotypes in single and double mutants. This reveals an intriguing cooperative and independent function of Ntn, Slit1, and Slit2 in DRG axon patterning. The sophisticated triple mutant analysis is lauded and provides important insight.

Weaknesses:<br /> Overall, the manuscript is sound in technique and analysis. However, the majority of the manuscript is about the dorsal funiculus and not the bifurcation of the axons, as the title would make a reader believe. Further, the manuscript would provide a more scholarly discussion of the current knowledge of DRG axon patterning and how their work fits into that knowledge.

Reviewer #1 (Public Review):

Yu et al. investigated Fusarium oxysporum f. sp. lycopersici SIX effectors structure using experimental and computational approaches, and while doing so, the authors identified several SIX effectors as member of the FOLD family, and expanded the known diversity of the SIX effectors. A very interesting and novel finding is the presence of FOLD putative effectors in other Ascomycetes secretome, sharing structural similarities with SIX effectors Avr1, Avr3 and SIX6.

By performing technically sound predictions and experimental confirmation, the authors also confirmed co-operative interactions between Fol effectors, something that was previously known for different pairs of proteins, expanding this observation for new SIX effectors. In addition, the authors contributed to the understanding of the interaction Fol effectors, specifically FOLD and LARS effectors, - I receptors to suppress immunity by structurally similar effectors.

The conclusions of this paper are supported by data and I think it is a pioneer study analyzing the correspondence between AlphaFold predictions and experimentally derived structures, highlighting that models can answer the scientific questions in some cases but could not be enough in others.

Reviewer #2 (Public Review):

Yu et al. investigated the structural landscape of 'secreted in xylem' (SIX) effector (virulence and avirulence) proteins from the plant-pathogenic fungus, Fusarium oxysporum f. sp. lycopersici (Fol), with the goal of better understanding effector function and recognition by host (tomato) immune receptors. In recent years, several experimental and computational studies have shown that many effector proteins of plant-associated fungi can be assigned to one of a few major structural families. In the study by Yu et al., X-ray crystallography was used to show that two avirulence effectors of Fol, Avr1 (SIX4) and Avr3 (SIX1), which are recognized by the tomato immune receptors I and I-3, respectively, form part of a new structural family, the Fol dual-domain (FOLD) family, found across three fungal divisions. Using AlphaFold2, an ab initio structural prediction tool, the authors then predicted the structures of all proteins within the Fol SIX effector repertoire (and other effector candidates) and provided evidence that two other effectors, SIX6 and SIX13, also belong to this family.

In addition to identifying members of the FOLD family, structural prediction revealed that proteins of the Fol effector repertoire can largely be classified into a reduced set of structural families. Examples included four members of the ToxA-like family (including Avr2 (SIX3) and SIX8), as well as four members of a new family, Family 4 (including SIX5 and PSL1). Given previous studies had demonstrated that Avr2 (ToxA-like) and SIX5 (Family 4) interact and function together, and that the genes encoding these proteins are divergently transcribed, and because homologues of SIX8 (ToxA-like) and PSL1 (Family 4) from another Fusarium pathogen are functionally dependent on each other and, in the case of Fol, are encoded by genes that are next to each other in the genome, the authors hypothesized that SIX8 and PSL1 may also physically interact. In line with this, co-incubation of the SIX8 and PSL1 proteins, followed by size exclusion chromatography (SEC), gave elution and gel migration profiles consistent with interaction in the form of a heterodimer. AlphaFold2-Multimer modelling then suggested that this interaction was mediated through an intermolecular disulfide bond. Such a prediction was subsequently confirmed through mutational analysis of the relevant cysteine residue in each protein in conjunction with SEC.

Finally, using a variant (homologue) of Avr1 from another Fusarium pathogen, as well as chimeric forms of this protein that integrated regions of Avr1 from Fol, Yu et al. determined through co-expression assays in Nicotiana benthamiana with the I immune receptor, as well as subsequent ion leakage assays, that the C-domain of Avr1 is recognized by the I immune receptor. Furthermore, through these assays, the authors were also able to show that surface-exposed residues in the C-domain enable Avr1 to evade recognition by a variant of the I receptor in Moneymaker tomato that does not provide resistance to Fol.

Overall, the manuscript presents a large body of work that is well supported by the data. A key strength of the manuscript is the validation (benchmarking) of protein structures predicted using AlphaFold2, which is a first for large-scale effector structure prediction papers published to date. Another key strength is the use of large-scale effector structure predictions to make hypotheses about functional relationships or interactions that are then tested (i.e. the SIX8-PSL1 protein interaction and recognition of Avr1 by the I immune receptor). This testing again goes above and beyond the large-scale effector structure prediction papers published to date. Taken together, this showcases how experimental and computational experiments can be effectively combined to provide biologically relevant data for the plant protection and molecular plant-microbe interactions fields.

In terms of weaknesses, the manuscript could have validated the SIX8-PSL1 protein interaction with in planta experiments, such as co-immunoprecipitation assays or co-localization experiments in conjunction with confocal microscopy, to provide support for the interaction in a plant setting. However, given what is already known about the Avr2-SIX5 interaction, these additional experiments are not crucial and could instead form part of a follow-up study.

Reviewer #3 (Public Review):

In this work, the authors shed light onto the structures of Fusarium oxysporum f.sp. lycopersici proteins involved in the infection of tomato. They unravelled several new secreted effector protein structures and additionally used computational approaches to structurally classify the remaining effectors known from this pathogen. Through this they uncovered a new and unique structural class of proteins which they found to be present and widely distributed in fungal plant pathogens and plant symbiotic fungi. The authors further predicted structural models for the full SIX effector set revealing that genome-proximal effector pairs share similar structural classes. Building on their Avr1 structure, the authors also define the C-terminal domain and specific amino acid residues that are essential to Avr1 detection by its cognate immune receptor.

A major strength of this work is a portfolio of several (Avr1, Avr3, SIX6, SIX8) new structurally resolved proteins which led to the discovery that several of them fall into the same structural class. These findings are supported by strong results.

The experiments addressing the structure-function relationship of Avr1's avirulence activity are highly relevant to our understanding of disease resistance mechanisms against Fusarium. Additional controls would allow for better support of the conclusions to be drawn. An example is FonSIX4's cell death activity in N.benthamiana leaves and whether FonSIX4 cdll death is indeed dependent on the tomato I receptor. Complementary work in Fusarium mutants lacking Avr1 and expressing chimeric versions would document that the observations from transient expressions in Nicotiana benthamiana are relevant in the biological context of a Fusarium/tomato interaction.

The discovered solvent-exposed residues conditioning Avr1 recognition by the I receptor seem to be positioned in an area of the protein which had previously been highlighted as being highly variable in FOLD proteins of symbiotic fungi but it is not clear from the work whether this is indeed the case or whether Avr1 differs significantly in its structure from FOLD proteins found in other fungi.<br /> It remains to be tested whether the residues conditioning avirulence activity are also crucial for virulence activity in Fusarium.

This work uncovered a new structural class of proteins with critical roles in plant-pathogen interactions. Structure-based predictions and genome-wide comparisons have emerged as a new approach enabling the identification of similar proteins with divergent sequences. The work undertaken by the authors adds to a growing body of work in plant-microbe research, predominantly from pathogenic organisms, and more recently in symbiotic fungi.

Reviewer #1 (Public Review):

The author found the nifuroxazide has the potential to augment the efficacy of radiotherapy in HCC by reducing PD-L1 expression. This effect may be attributed to increased degradation of PD-L1 through the ubiquitination-proteasome pathway. These evidences support the future application of nifuroxazide in the treatment of HCC.

Reviewer #2 (Public Review):

Summary:<br /> Zhao et al. aimed to explore an important question-how to overcome resistance of hepatocellular carcinoma cells to radiotherapy. Given that immune-suppressive microenvironment is a major mechanism underlying resistance to radiotherapy, they reasoned that a drug that blocks PD-1/PD-L1 pathway could improve efficacy of radiation therapy and chose to investigate the effect of Nifuroxazide, an inhibitor of stat3 activation, on radiotherapy efficacy in treating hepatocellular carcinoma cells. From in vitro experiments, they find combination treatment (Nifuroxazide+ radiotherapy) increases apoptosis and reduces proliferation and migration, in comparison to radiotherapy alone. From in vivo experiments, they demonstrate that combined treatment reduces size and weight of tumors in vivo and enhances mice survival. These data indicate a better efficacy of combination therapy compared to radiotherapy alone. Moreover, they also determined the effect of combination therapy on tumor microenvironment as well as peripheral immune response. Specifically, they find that combination therapy increases infiltration of CD4+, CD8+ t cells and NK cells, activates CD8+ t cells, enhances polarization of M1 macrophages and decreases Treg cells in the tumor microenvironment. These changes in tumor microenvironment is consistent with reduced tumor growth by combination therapy. The most intriguing part of the study is the determination of effect of Nifuroxazide on PD-L1 expression in the context of radiotherapy. Considering Nifuroxazide is a stat3 activation inhibitor and stat3 inhibition leads to reduced expression of PD-L1, one would expect Nifuroxazide decreases PD-L1 expression through stat3. However, they find the effect of Nifuroxazide on PD-L1 is dependent on GSK3 mediated Proteasome pathways and independent of stat3, in the given experimental context. To determine the relevance to human hepatocellular carcinoma, they also measured the PD-L1 expression in human tumor tissues of HCC patients pre- and post-radiotherapy. The increased PD-L1 expression level in HCC after radiotherapy is impressive.<br /> Overall, the data are convincing and supportive to the conclusions.

Strengths:<br /> 1) Novel finding: Identified novel mechanism underlying effect of Nifuroxazide on PD-L1 expression in hepatocellular carcinoma cells in the context of radiotherapy.<br /> 2) Comprehensive experimental approaches: using different approaches to prove same finding. For example, Fig4, both IHC and WB were used. Fig5. Both IF and WB were used.<br /> 3) Human disease relevance: Compared observations in mice with human tumor samples.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors investigated the potential of nifuroxazide to enhance responsiveness to radiotherapy, employing both an in vitro cell culture system and an in vivo syngeneic mouse tumor model.

Strengths:<br /> The researchers conducted a series of experiments to elucidate the role of nifuroxazide in facilitating the radiotherapy-induced reduction of proliferation, migration, and invasion of HepG2 cells.

Weaknesses:<br /> The evidence supporting the claim that nifuroxazide contributes to the degradation of radiotherapy-induced upregulation of PD-L1 via the ubiquitin-proteasome pathway is still relatively weak.

Reviewer #1 (Public Review):

Summary:

The authors developed a deep learning method called H3-OPT, which combines the strength of AF2 and PLM to reach better prediction accuracy of antibody CDR-H3 loops than AF2 and IgFold. These improvements will have an impact on antibody structure prediction and design.

Strengths:

The training data are carefully selected and clustered, the network design is simple and effective.

The improvements include smaller average Ca RMSD, backbone RMSD, side chain RMSD, more accurate surface residues and/or SASA, and more accurate H3 loop-antigen contacts.

The performance is validated from multiple angles.

The revised manuscript has cleared my previous concerns.

Reviewer #2 (Public Review):

This work provides a new tool (H3-Opt) for the prediction of antibody and nanobody structures, based on the combination of AlphaFold2 and a pre-trained protein language model, with a focus on predicting the challenging CDR-H3 loops with enhanced accuracy than previously developed approaches. This task is of high value for the development of new therapeutic antibodies. The paper provides an external validation consisting of 131 sequences, with further analysis of the results by segregating the test sets in three subsets of varying difficulty and comparison with other available methods. Furthermore, the approach was validated by comparing three experimentally solved 3D structures of anti-VEGF nanobodies with the H3-Opt predictions

Strengths:

The experimental design to train and validate the new approach has been clearly described, including the dataset compilation and its representative sampling into training, validation and test sets, and structure preparation. The results of the in silico validation are quite convincing and support the authors' conclusions.

The datasets used to train and validate the tool and the code are made available by the authors, which ensures transparency and reproducibiity, and allows future benchmarking exercises with incoming new tools.

Compared to AlphaFold2, the authors' optimization seems to produce better results for the most challenging subsets of the test set.

Weaknesses:

The comparison of affinity predictions derived from AlphaFold2 and H3-opt models, based on molecular dynamics simulations, should have been discussed in depth. In some cases, there are huge differences between the estimations from H3-opt models and those from experimental structures. It seems that the authors obtained average differences of the real delta, instead of average differences of the absolute value of the delta. This can be misleading, because high negative differences might be compensated by high positive differences when computing the mean value. Moreover, it would have been good for the authors to disclose the trajectories from the MD simulations.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript introduces a new computational framework for choosing 'the best method' according to the case for getting the best possible structural prediction for the CDR-H3 loop. The authors show their strategy improves on average the accuracy of the predictions on datasets of increasingly difficulty in comparison to several state-of-the-art methods. They also show the benefits of improving the structural predictions of the CDR-H3 in the evaluation of different properties that may be relevant for drug discovery and therapeutics design.

Strengths:<br /> Authors introduce a novel framework, which can be easily adapted and improved. Authors use a well defined dataset to test their new method. A modest average accuracy gain is obtained in comparison to other state-of-the art methods for the same task, while avoiding for testing different prediction approaches. Although the accuracy gain is mainly ascribed to easy cases, the accuracy and precision for moderate to challenging cases is comparable to the best PLM methods (see Fig. 4b and Extended Data Fig. 2), reflecting the present methodological limit in the field.

Weaknesses:<br /> The proposed method lacks of a confidence score or a warning to help guiding the users in moderate to challenging cases.

Reviewer #1 (Public Review):

Summary:<br /> This study presents a valuable finding on the increased activity of two well-studied signal transduction pathways - STAT-3 and TGF-Beta in a specific subtype of pancreatic cancer. Specifically, SMAD4 deficient tumors (commonly observed in pancreatic cancer) are well differentiated in the presence of STAT3. Yet surprisingly, in the presence of SMAD4 in a STAT-3 deficient pancreatic cancer, the phenotype is poorly differentiated in the background of KRASGD12D. The evidence in the animal models supporting the authors' claims is solid, although including TCGA data and/or a larger number of patients would have strengthened the study. The work will be of interest to medical biologists working on pancreatic cancer and potentially the broader field.

Strengths:<br /> Strengths are the animal models and the lead author's expertise in STAT3 signaling.

Weaknesses:<br /> Weaknesses are the absence of correlation between the results from the animal studies and human pancreatic cancers.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript explores mechanisms by which STAT3 may regulate KRAS mutant cancers.

In the first set of experiments, STAT3 GOF mutants diminished the transformation of p53-null mouse embryonic fibroblasts expressing endogenous mutant KRAS(G12D) (KP MEFs) and this was dependent on direct transcriptional activation induced by phosphorylated STAT3. It appears that this is mediated via a reduction in TGFb signaling such that knockout of either TGFBR2 or SMAD4 can phenocopy the effects of STAT3 GOF mutants in KP MEFs.

In the next part of the paper, the authors used murine pancreatic ductal adenocarcinoma (PDAC)-derived cell lines bearing endogenous KRAS(G12D) and TP53(R172H) mutations (KPC) to determine the extent to which STAT3 may regulate KRAS dependency. They determined that KRAS and STAT3 KO both induced mesenchymal-like phenotypes and that TGFBR2 and SMAD4 KO induced epithelial phenotypes. The loss of STAT3 appeared to correlate with a KRAS-independent signature, and SMAD4/TGFBR2 KO could not induce epithelial phenotypes when STAT 3 was also knocked out.

Strengths:<br /> Overall, this is an interesting paper that highlights the complicated interactions between KRAS, STAT3, and TGF beta signaling. The authors use multiple models and attempt to link data to patient cohorts.

Weaknesses:<br /> While correlations are strong, the study would benefit from additional cause-and-effect type experiments. It would also be beneficial to better tie together the first and second parts of the paper.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript by Chen et al. presents a detailed metabolic characterization of male and female WT and CTRP10 knockout mice. The main finding is that female KO mice become obese on both low-fat and high-fat diets but without evidence of marked insulin resistance, hepatic steatosis, dyslipidemia, or increased inflammatory markers. The authors performed a detailed transcriptomic analysis and identified differentially expressed genes that distinguish high-fat diet-fed CTRP10 KO from WT control mice. They further show that this set of genes exhibits cross-correlation in human tissues, and that this is greater in females than in males. The data indicate that the CTRP10 KO model may be useful to understand how obesity and metabolic dysfunction are coupled to each other, and how this occurs by a sex-biased mechanism.

Strengths:<br /> The work presents a large amount of data, which has been carefully acquired and is convincing. The transcriptomic analysis will further help to define what pathways are associated with obesity, but not necessarily with metabolic dysfunction. The manuscript will be of interest to investigators studying metabolic diseases, and to those studying sex-specific differences in metabolic physiology. The limitations of the study are acknowledged, including that a whole-body knockout was used. The cause of the increased body weight is not entirely clear, despite the careful and detailed analysis that was performed. Notwithstanding these limitations, the phenotype is interesting, and this work will establish a basis for further work to understand the mechanisms that are involved.

Weaknesses:<br /> Genes identified as DEGs in the mouse RNAseq data set were used to identify a set of human orthologous transcripts and the abundances of these transcripts were correlated with each other in Figure 10. This identified a greater correlation ("connectivity") in subQ adipose compared to other tissues, and in females compared to males. The description of how this analysis was done could be clearer. In some cases, the text refers to the software that was used without describing the goal of the analysis. In other instances, specialized terminology was used (e.g. "biweight midcorrelation") without defining what this means.

Reviewer #2 (Public Review):

Summary:<br /> In the current study, the authors investigated the role of loss of CTRP10 results in female obesity with preserved metabolic health. The overall conclusion is supported by the experimental data that CTRP10 negatively regulates body weight in females and that loss of CTRP10 results in benign obesity with largely preserved insulin sensitivity and metabolic health. The authors have shown the role of sex differences in the metabolically healthy obese (MHO) phenotype, which may increase the scope for research in this area.

Strengths:<br /> The study provides a detailed idea of how genes are regulated in a sex-dependent manner.

Weaknesses:<br /> Mechanistic details are missing.

Reviewer #3 (Public Review):

Summary:<br /> This study examines the impact of CTRP10/C1QL2 absence on obesity and metabolic health in mice. Female mice lacking CTRP10 tend to develop obesity, particularly on a high-fat diet. Surprisingly, they do not display the typical metabolic traits associated with obesity, like fatty liver or glucose intolerance. This indicates a disconnection between weight gain and metabolic issues in these female mice. The research underscores the need to understand sex-specific factors in how obesity influences metabolic health.

Strengths:<br /> The study provides compelling evidence regarding Ctrp10's role in female-specific metabolic regulation in mice, shedding light on its potential significance in metabolically healthy obese (MHO) individuals.

Weaknesses:<br /> -The analysis and description of sex-specific human data require more details to highlight the relevance of Ctrp10 mouse data and the analysis of differentially expressed genes in humans.<br /> -There's a lack of analysis regarding secreted Ctrp10 under various dietary conditions.<br /> -The study didn't assess adipose tissue function to evaluate metabolic health.

Reviewer #1 (Public Review):

Summary:

Bartolome et al. report adaptation of proximity labeling using BirA and TurboID fusions to proteasome subunits to identify the proteasome-proximal proteome both in cultured cells and also in a newly developed mouse model. Using this approach, the authors demonstrate identification of many known proteasome-interacting proteins, as well as several new proteins, some of which are validated directly. The authors further evaluate the proteasome-proximal proteome in most mouse organs, and find substantial agreement with the proteome identified from cultured cells, as well as between tissues. This represents one of the first studies of the "proteasome-ome" in vivo, and sets the stage for addressing numerous important future questions regarding how the proteasome's environment changes over time, in response to different stimuli, and in distinct disease conditions.

Strengths:

Generally speaking, the approach provided is rigorous and supported by several complementary lines of evidence, such as demonstration that the interactome is enriched for known proteasome-binding proteins and co-purification or co-elution experiments. Similarly, the high agreement between the outcomes in cultured cells and in the mouse model developed by the authors provides further confidence in the results.

Weaknesses:

The major weakness of the work is arguably the choice of proteasome subunits for tagging with biotinylating enzymes. In most cases, the subunits and termini chosen for tagging are known to either protrude toward functionally important regions (such as the substrate-processing pore of the ATPase component), to have important functional roles likely to be disrupted via tagging, or are subunits known to be substituted by others in some conditions. Thus, the interactome reported may conflate those of normal proteasomes with those harboring tag-induced functional or structural defects. Although the authors made a commendable attempt to demonstrate minimal impacts of tagging, the conclusions would be greatly further strengthened by contrasting the impacts of tagging subunits less likely to cause perturbations and by more rigorously demonstrating normal proteolysis of a broader array of known proteasome substrates.

Reviewer #2 (Public Review):

Summary

In this work, Bartolome and colleagues develop a new approach to identify proteasome interacting proteins and substrates. The approach is based on fusing proteasome subunits with a biotin ligase that will label proteins that come in close physical distance of the ligase. These biotin-labeled proteins (or their resulting tryptic peptides) can be affinity purified using streptavidin and identified by mass spectrometry.

This elegant solution was able to identify a large proportion of known proteasome interactors, as well as multiple potential new interactors. Combining this approach with a proteasome inhibitor allowed also for the enrichment of substrates, due to increased contact time between substrates and the proteasome. Again, the authors were able to identify novel substrates. Finally, the authors implemented this strategy in vivo, providing the hints for potential tissue-specific proteasome interactors.

This novel strategy provides an additional approach to identify new proteasome substrates, which can be particularly powerful for low abundant proteins, e.g., transcription factors. The possibility to implement it in vivo in specific cell types opens the possibility for identifying proteasome interactors in small cell subpopulations or in subpopulations involved in disease.

Strengths:

The authors carefully characterized their genetically engineered proteasome-biotin ligase fusions to ensure that proteasome structure and activity was not altered. This is key to ensure that the proteins identified to interact with the proteasome reflect interactions that occur under physiological conditions.

The authors implemented an algorithm that controls the false positive rate of the identified interactors of the proteasome. This is an important aspect to avoid spending time on the characterization of potential interactors that are just an artifact of the experimental setup.

The addition of a proteasome inhibitor allowed the authors to identify substrates of the proteasome. Although there are other strategies to do this (e.g., affinity purification of Gly-Gly modified peptides, which is a marker for ubiquitination), this additional approach can highlight currently unknown substrates. One example are low abundance proteins, such as transcription factors.

The overall strategy developed by the authors can be implemented in vivo, which opens for the possibility of determining cell type-specific proteasome interactors (and perhaps substrates).

Weaknesses:

There is a small proportion of the PSMA4-biotin ligase fusion that remains unassembled (i.e., not part of the functional proteasome) and that can contribute to a small proportion of false positive interactions.

Reviewer #3 (Public Review):

Summary:

Bartolome et al. present ProteasomeID, a novel method to identify components, interactors, and (potentially) substrates of the proteasome in cell lines and mouse models. As a major protein degradation machine that is highly conserved across eukaryotes, the proteasome has historically been assumed to be relatively homogeneous across biological scales (with few notable exceptions, e.g., immunoproteasomes and thymoproteasomes). However, a growing body of evidence suggests that there is some degree of heterogeneity in the composition of proteasomes across cell tissues, and can be highly dynamic in response to physiologic and pathologic stimuli. This work provides a methodological framework for investigating such sources of variation. The authors start by adapting the increasingly popular biotin ligation strategy for labelling proteins coming into close proximity with one of three different subunits of the proteasome, before proceeding with PSMA4 for further development and analysis based on their preliminary labelling data. In a series of well-constructed and convincing validation experiments, the authors go on to show that the tagged PSMA4 construct can be incorporated into functional proteasomes, and is able to label a broad set of known proteasome components and interacting proteins in HEK293T cells. They also attempt to identify novel proteasomal degradation substrates with ProteasomeID; while this was convincing for known substrates with particularly short half-lives (exemplified by the transcription factor c-myc), follow-up validation experiments with other substrates were less clear. One of the most compelling results was from a similar experiment to confirm proteasomal degradation induced by a BRD-targeting PROTAC, which I think is likely to be of keen interest to the targeted degradation community. Finally, the authors establish a ProteasomeID mouse model, and demonstrate its utility across several tissues.

Strengths:

1) ProteasomeID itself is an important step forward for researchers with an interest in protein turnover across biological scales (e.g., in sub-cellular compartments, in cells, in tissues, and whole organisms). I especially see interest from two communities: those studying fundamental proteostasis in physiological and pathologic processes (e.g., ageing; tissue-specific protein aggregation diseases), and those developing targeted protein degradation modalities (e.g., PROTACs; molecular glues). All the datasets generated and deposited here are likely to provide a rich resource to both. The HEK293T cell line data are a valuable proof-of-concept to allow expansion into more biologically-relevant cell culture settings; however, I envision the greatest innovation here to be the mouse model. For example, in the targeted protein degradation space, two major hurdles in early-stage pre-clinical development are (i) evaluation of degradation efficacy across disease-relevant tissues, and (ii) toxicity and safety implications caused by off-target degradation, e.g., of newly-identified molecular glues and/or in particularly-sensitive tissues. The ProteasomeID mouse allows early in vivo assessment of both these questions. The results of the BRD PROTAC experiment in 293T cells provides an excellent in vitro proof-of-concept for this approach.

2) The mass spectrometry-based proteomics workflows used and presented throughout the manuscript are robust, rigorous, and convincing. For example, the algorithm the authors use for defining enrichment score cut-offs are logical and based on rational models, rather than on arbitrary cut-offs that are common for similar proteomics studies. The construction (and subsequent validation) of both BirA*- and miniTurbo- tagged PSMA4 variants also increases the utility of the method, allowing researchers to choose the variant with the labelling time-scale required for their particular research question.

3) The optimised BioID and TurboID protocol the authors develop (summarised in Fig. S2A) and validate (Fig. S2B-D) is likely to be of broad interest to cell and molecular biologists beyond the protein degradation field, given that proximity labelling is a current gold-standard in global protein:protein interaction profiling.

Limitations:

I think the authors do an excellent job in highlighting the limitations of ProteasomeID throughout the Results and Discussion. I do have some specific comments that might provide additional context for the reader.

1) The authors do a good job in showing that a substantial proportion of PSMA4-BirA* is incorporated into functional proteasome particles; however, it is not immediately clear to me how much background (false-positive IDs) might be contributed by the ~40 % of PSMA4-BirA* that is not incorporated into the mature core particle (based on the BirA* SEC-MS traces in Fig. 2b and S3b, i.e., the large peak ~ fraction 20). Are there any bands lower down in the native gel shown in Fig. 2c, i.e., corresponding to lower molecular weight complexes or monomeric PSMA4-BirA*? The enrichment of proteasome assembly factors in all the ProteasomeID experiments might suggest the presence of assembly intermediates, which might themselves become substrates for proteasomal degradation (as has been shown for other incompletely-assembled protein complexes, e.g., the ribosome, TRiC/CCT).

2) Although the authors attempt to show that BirA* tagging of PSMA4 does not interfere with proteasome activity (Fig. 2e-f), I think the experimental evidence for this is incomplete. They show that the overall chymotrypsin-like activity (attributable to PSMB5) in cells expressing PSMA4-BirA* is not markedly reduced compared with control BirA*-expressing cells. However, they do not show that the activity of the specific proteasome sub-population that contains PSMA4-BirA* is unaffected (e.g., by purifying this sub-population via the Flag tag). The proteasome activity of the sub-population of wild-type proteasome complexes that do not contain the PSMA4-BirA* (~50%, based on the earlier immunoblots) could account for the entire chymotrypsin-like activity-especially in the context of HEK293T cells, where steady-state proteasome levels are unlikely to be limiting. It would also be useful to assess any changes in tryspin- and caspase- like activities, especially as tagging of PSMA4 could conceivably interfere with the activity of some PSMB subunits, but not others.

3) I was left unsure of the general utility of ProteasomeID for identifying novel proteasomal substrates in homeostatic or stressed conditions. The immunoblots for the two candidates the authors follow up in Fig. 4g was not especially clear; the reduction in the bands are modest, at best. Furthermore, classifying candidates based on enrichment following proteasome inhibition with MG-132 have the potential to lead to a high number of false positives. ProteasomeID's utility in identifying potential substrates in more targeted settings (e.g., molecular glues, off-target PROTAC substrates) is far more apparent.

Reviewer #1 (Public Review):

Summary:<br /> Zhang et al. describe novel roles for the centriolar protein CEP44, namely that it is required for centriole engagement (and thus inhibition of centriole reduplication) and that it promotes microtubule stability. While a function of CEP44 in centriole engagement is somehow convincingly shown, the data do not support a role for CEP44 in microtubule stabilization.

Strengths:<br /> The finding that centriole engagement relies on CEP44 is novel and of great interest to the centriole field. Interestingly, the authors correlate reduced CEP44 expression levels with the occurrence of breast carcinoma, which makes this study also very interesting for a broad audience.

Weaknesses:<br /> The paper has important findings, but unfortunately, the main claims are only partially supported.

1) The role of CEP44 in microtubule stability is not clear from the presented data:<br /> - Fig. 7A and S6 A, there is no visible difference in microtubule density/intensity between the different groups of cells. In Fig. 7C, the CEP44 S324A spindle looks even brighter than the WT spindle. The authors need to indicate how many cells were analyzed. This information is actually lacking in all the experiments.

2) Several figure parts are not properly labelled.

3) Several of the experiments (WBs) likely miss proper controls: How did the authors detect proteins that run at very similar sizes: 55 kDa (alpha-tubulin), 44 kDa (Cep44), and 57 kDa (Cep57 and Cep57L)? The loading control needs to be detected in the same lane as the protein of interest. Did the authors strip and reprobe membranes? If so, this needs to be indicated and included in the methods section.

4) It is not clear how such a low CEP44-FLAG expression (Fig. 5A) can rescue a CEP44 KO.

Reviewer #2 (Public Review):

Zhang and Wei, et al. investigated the role of a centrosomal protein, CEP44, in regulating centrosomes and spindle integrity, with a focus on processes that may be dysregulated in breast cancer. The authors found that a breast cancer cell line, MDA-MB-436, lacks CEP44 protein and has amplified centrioles. CEP44 expression is reduced in samples from breast cancer patients. By super-resolution microscopy, the authors localize CEP44 to the proximal inner lumen of centrioles, as has also been previously shown by another group (Atorino et al 2020). Next, the authors investigate the role of CEP44 in centrosome regulation. They found that loss of CEP44 in HeLa cells results in extra puncta of CEP97 or Centrin-3, while ectopic overexpression of CEP44 in MDA-MB-436 cells reduces the number of CEP97 foci. Only one of the excess puncta in a CEP44-depleted HeLa cell recruits CEP164 or ODF2, indicating that extra foci were not the result of cytokinesis failure. In G1, most (~80%) of CEP44-depleted cells have 2 centrin foci, while in G2, a small population (~20%) have more than 4 centrin foci, and gamma-tubulin is recruited in foci in G2. The authors were able to observe centriole disengagement and amplification using live cell imaging. The authors propose that CEP44 acts in regulating centriole engagement by recruiting CEP57 and CEP57L1 to centrioles. The authors made CEP44 knockout cell lines using CRISPR and found that loss of CEP44 results in multipolar spindles, correlated with an increase in centriole amplification. Finally, the authors investigate the role of CEP44 at the mitotic spindle. The authors find that CEP44 localizes to spindles and is phosphorylated by Aurora A at G2/M on Ser324. Phosphorylation of CEP44 is required for its proper distribution between centrosomes and the spindle and microtubule stability within both spindles and interphase microtubules. Together, these studies shed light on the roles of CEP44 within centrosomes and spindles and will be of interest to cell biologists and cancer biologists studying cell division and centrosomes.

The conclusions of this paper are only partially supported. The analyses could be improved to address the concerns about the major conclusions.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Zhang et al. analyzes the function of the centrosomal protein CEP44 in centriole duplication and in the formation of the mitotic spindle. The first part addresses the role of CEP44 at centrioles. Using mostly RNAi-mediated depletion in cell lines and in some cases KO cells, the authors find increased centriole numbers in depleted cells and, based on quantification of centrioles stained with various centriole markers as well as live imaging, conclude that this is due to premature centriole disengagement and overduplication. The second part, which is largely independent of the first, focuses on the role of CEP44 in the mitotic spindle. The authors find that CEP44 is phosphorylated in mitosis in an Aurora A-dependent manner and identify the phosphorylation site, which controls CEP44 spindle localization and functions in maintaining spindle integrity.

Strength:<br /> The manuscript makes the interesting observation that reduced expression of CEP44 is observed in breast cancer and correlated with poor survival in patients.<br /> The analysis of mitotic phosphorylation including the identification of the modified site and its role in spindle recruitment is interesting and useful.

Weakness:<br /> The authors seem to largely ignore previously published work that contrasts with the findings presented in the current study. The previous work found a role of CEP44 in centriole formation and centrosome conversion and observed reduced centriole numbers in depleted cells, whereas the current study claims the opposite, a role in centriole engagement that leads to overduplication and increased centriole number in depleted cells. However, the supporting evidence is not strong enough, especially in light of the previous work. Considering that CEP44 depletion also disrupts mitosis, which could affect centriole numbers by failed segregation/division, a more careful analysis in synchronized cultures would be needed. Also, cell cycle analysis would be required to rule out cell cycle effects in CEP44-depleted cells, which could also explain altered centriole numbers. Moreover, the quality of the imaging is often not sufficient to support the claims.<br /> The second part is largely disconnected from the first and reads as if it was a separate study. There is no attempt to integrate both parts. For example, the second part seems to largely focus on normal bipolar spindles, even though the first part reveals multipolarity as a phenotype after CEP44 knockdown. It remains unclear if the spindle defects are due to centriole defects, defective spindle microtubule stability/organization, or both, and whether the centriole-localized or spindle-localized CEP44 is involved.

Another weak aspect is that neither for RNAi nor for KO cells the authors show that CEP44 is depleted at centrioles and to what extent. This is only shown in cell extract.

Reviewer #1 (Public Review):

Summary:<br /> In their manuscript, Zhou et al. analyze the factors controlling the activation and maintenance of a sustained cell cycle block in response to persistent DNA DSBs. By conditionally depleting components of the DDC using auxin-inducible degrons, the authors verified that some DDC proteins are only required for the activation (e.g., Dun1) or the maintenance (e.g., Chk1) of the DSB-dependent cell cycle arrest, while others such as Ddc2, Rad24, Rad9 or Rad53 are required for both processes. Notably, they further demonstrate that after a prolonged arrest (>24 h) in a strain carrying two DSBs, the DDC becomes dispensable and the mitotic block is then maintained by SAC proteins such as Mad1, Mad2, or the mitotic exit network (MEN) component Bub2.

Strengths:<br /> The manuscript dissects the specific role that different components of the DDC and the SAC have during the induction of a cell cycle arrest induced by DNA damage, as well as their contribution to the short-term and long-term maintenance of a DNA DSB-induced mitotic block. Overall, the experiments are well described and properly executed, and the data in the manuscript are clearly presented. The conclusions drawn are also generally well supported by the experimental data. The observations contribute to drawing a clearer picture of the relative contribution of these factors to the maintenance of genome stability in cells exposed to permanent DNA damage.

Weaknesses:<br /> The main weakness of the study is that it is fundamentally based only on the use of the auxin-inducible degron (AID) strategy to deplete proteins. This is a widely used method that allows a very efficient depletion of proteins. However, the drawback is that a tag is added to the protein, which can affect the functionality of the targeted protein or modify its capacity to interact with others. In fact, three of the proteins that are depleted using the AID systems are shown to be clearly hypomorphic. Verification of at least some of the results using an alternative manner to eliminate the proteins would help to strengthen the conclusions of the manuscript.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript analyzes the genetic requirement for DNA damage-induced cell cycle checkpoint induction and maintenance in budding yeast bearing one or two unrepairable DNA double-strand breaks using auxin-induced degradation (AID) of key DNA damage response (DDR) factors. The study paid particular attention to solving a puzzle regarding how yeast bearing two unrepaired DNA breaks fail to engage in "adaptation" whereas those with a single unrepairable break eventually resume cell cycling after a prolonged (up to 12 h) G2 arrest.

The most novel findings are: 1. The genetic requirement for the entry to DDC and the maintenance are separable. For instance, Dun1 is partially required for the entry but not DDC maintenance whereas Chk1 is only required for maintenance. 2. Cells with two irreparable breaks respond to DDR only up to a certain time (~12 h post damage) and beyond this point, depend on spindle assembly checkpoint (SAC) and mitotic exit network (MEN) to halt cell cycling. 3. The authors also propose an interesting model that the location of DNA breaks and their distance to centromeres can lead to the triggering of SAC/MEN and dictate the duration of cell cycle arrest and their adaptability following DNA damage. The results thus provide the most compelling evidence on the role of SAC/MEN in DNA damage response and cell cycle arrest albeit its impact might be limited to the current experimental set-up or under conditions when DNA repair is severely deficient.

Overall, the conclusion of the study is well supported by the elegant set of genetic experimental data and employed multiple readouts on DDC factor depletion on checkpoint integrity and cell cycle status. However, the study still relies heavily on Rad53 phosphorylation as the primary metric to assess checkpoint status. Since evidence exists the residual DDC still operates even when Rad53 phosphorylation is undetectable, additional readouts for DDC functions might be necessary to strengthen the study's conclusions. These and other concerns that need clarifications or further experimental validations are discussed below.

Reviewer #3 (Public Review):

Summary:<br /> The DNA damage checkpoint (DDC) inhibits the metaphase-anaphase transition to repair various types of DNA damage, including DNA double strand breaks (DSBs). One irreparable DSB can maintain the DDC for 12-15 hours in yeast, after which the cells resume the cell cycle. If there are two DSBs, the DDC is maintained for at least 24 hours. In this study, the authors take advantage of this tighter DDC to investigate whether the best-known proteins involved in establishing the DDC are also responsible for its long-term maintenance during irreparable DSBs. They do this by cleverly degrading such proteins after DSB formation. They show that most, but not all, DDC proteins maintain the cell cycle block. Interestingly, DDC proteins become dispensable after 15 hours and the block is then maintained by spindle assembly checkpoint (SAC) proteins.

Strengths:<br /> The authors have engineered a tight yeast system to study DDC shutdown after irreparable DSBs and used it to address whether checkpoint proteins (DDC and SAC) contribute to the long-term maintenance of DSB-mediated G2/M block. The different roles of Ddc2, Chk1, and Dun1 are interesting, while the fact that SAC overtakes DDC after 15 hours is intriguing and highlights how DSBs near and far from centromeres can have a profound impact on cell adaptation to DSBs.

Weaknesses:<br /> Some of the results they present essentially confirm their own previous findings, albeit with a tighter strain design for long-term arrest. In addition, some conclusions about the role of specific DDC proteins in cell cycle arrest at G2/M need further experimental support. The results with Bfa1/Bub2 are surprising and somewhat unexpected. There is no clear mechanism for how depletion of Bub2, but not Bfa1, can relieve the G2/M (metaphase) block.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript describes the identification and characterization of rice SCC3, including the generation and characterization of plants containing apparently lethal null mutations in SCC3 as well as mutant plants containing a c-terminal frame-shift mutation. The weak scc3 mutants showed both vegetative and reproductive defects. Specifically, mitotic chromosomes appeared to partially separate during prometaphase, while meiotic chromosomes were diffuse during early meiosis and showed alterations in sister chromatid cohesion, homologous chromosome pairing, and recombination. The authors suggest that SCC3 acts as a cohesin subunit in mitosis and meiosis, but also plays more functions other than just cohesion.

Strengths:<br /> The manuscript contains a large amount of generally high-quality data.

Weaknesses:<br /> Several of the conclusions drawn in the manuscript are not supported by the data. There are many examples where the authors either draw conclusions or make statements that are just not justified based on the data presented or present a conclusion as a new finding, which has already been demonstrated in the past by others. For example, they claim that SCC3 functions in the maintenance of replication. From my reading of the manuscript, nowhere did the authors examine DNA replication. Likewise, several of the conclusions drawn are in direct contrast with what is known about SCC3 in other organisms. Therefore, the conclusions are either groundbreaking or incorrect.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript shows detailed evidence of the role of cohesin regulators in rice meiosis and mitosis.

Strengths:<br /> There is a very clear mechanism for its role during replication. The strength of the evidence and its novelty is very high. This paper makes a significant contribution to the body of knowledge on meiotic cohesion in a valuable plant model.

Weaknesses:<br /> The authors did not consider creating heterozygous mutants for the replication fork.<br /> Moderate English language editing may be required.

Reviewer #3 (Public Review):

Summary:<br /> Prior research on SCC3, a cohesin subunit protein, in yeast and Arabidopsis has underscored its vital role in cell division. This study investigated into the specific functions of SCC3 in rice mitosis and meiosis. In a weakened SCC3 mutant, sister chromatids separating was observed in anaphase I, resulting in 24 univalents and subsequent sterility. The authors meticulously documented SCC3's loading and degradation dynamics on chromosomes, noting its impact on DNA replication. Despite the loss of homologous chromosome pairing and synapsis in the mutant, chromosomes retained double-strand breaks without fragmenting. Consequently, the authors inferred that in the scc3 mutant, DNA repair more frequently relies on sister chromatids as templates compared to the wild type.

Strengths:<br /> The study presents exceptionally well-executed research in the field of rice cytogenetics.

Weaknesses:<br /> While the paper's conclusions are generally well-supported, further substantiation is needed for the claim that SCC3 inhibits template choice for sister chromatids. To bolster this conclusion, I recommend that the authors perform whole-genome sequencing on parental and F1 individuals from two rice variants, subsequently calculating the allele frequencies at heterozygous sites in the F1 individuals. If SCC3 indeed inhibits inter-sister chromatid repair in the wild type, we would anticipate a higher frequency of inter-homologous chromosome repair (i.e., gene conversion). This should be manifested as a bias away from the Mendelian inheritance ratio (50:50) in the offspring of the wild type compared to the offspring of the scc3+/- mutant.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript describes a deficiency in nuclear pore complexes (NPCs) to maintain proper compartmentalization between the nucleus and cytoplasm in a mouse model of AD-related Aβ pathology. Experiments demonstrate NPC dysfunction in cultured neurons and mouse tissue as a result of intracellular Aβ, which may cause reduced levels of certain nucleoporins, leading to a reduced number of NPCs, and their dysfunction in nuclear protein import and maintaining nucleocytoplasmic compartmentalization. In addition, the authors also report a potential mechanism for how NPC dysfunction may result in increased vulnerability to inflammation-induced necroptosis, where core components are reportedly activated via phosphorylation through nucleocytoplasmic shutting. Overall, the study is interesting and well conducted and reveals striking NCT defects in a Aβ pathology disease model that may have important implications for our understanding of AD pathology.

Strengths:<br /> Previous studies have found nucleocytoplasmic transport (NCT) defects in other models of age-related neurodegenerative diseases, including Huntington's disease, tauopathy, C9orf72-linked frontotemporal dementia / amyotrophic lateral sclerosis (FTD/ALS), and TDP-43 proteinopathy in FTD/ALS. Typically, NCT defects have been linked mechanistically to aberrant co-aggregation of nucleoporins with e.g. TDP-43 and tau found in disease models and sometimes also human autopsy tissue. This study is novel, in that it describes NCT defects that are caused by Alzheimer's disease (AD) related Aβ pathology, using a human APP knock-in mouse model (AppNL-G-F/NL-G-F) that exhibits robust Aβ pathology in the CNS. The main focus of this study is on the barrier dysfunction of the NPCs leading to compartmentalization defects, while previous publications in the field have focused more on active protein import and RNA export defects. This is of considerable interest since an age-dependent decline in NPC barrier function has been observed in transdifferentiated neurons derived from normal-aged fibroblasts (Mertens et al., 2015). The potential link of NPC dysfunction to an increased vulnerability to inflammation-induced necroptosis may also be relevant to other neurodegenerative disorders with NCT dysfunction. Experiments are largely focused on either dissociated neuronal cultures, or studies using mouse tissue at different stages of disease progression. Experiments are mostly based on immunocytochemistry (ICC) and histochemistry (IHC) of nucleoporins to show morphological NPC defects and fluorescent reporter constructs and dyes of defined MW to show NPC dysfunction. The experiments using an anti-nuclear pore O-linked glycoprotein antibody [RL1], which recognizes multiple metazoan nucleoporins that are modified via post-translational O-GlcNAcylation, show a very striking reduction in staining intensity that is also replicated with antibodies specific for the FG-motif rich Nup98 and the very stable and essential NPC component Nup107. Taken together, the fluorescence microscopy studies convincingly support the claim of NPC dysfunction leading to defective compartmentalization between the nucleus and cytoplasm.

Weaknesses:<br /> However, the molecular mechanisms leading to NPC dysfunction and the cellular consequences of resulting compartmentalization defects are not as thoroughly explored. Results from complementary key experiments using western blot analysis are less impressive than microscopy data and do not show the same level of reduction. The antibodies recognizing multiple nucleoporins (RL1 and Mab414) could have been used to identify specific nucleoporins that are most affected, while the selection of Nup98 and Nup107 is not well explained. There is also no clear hypothesis on how Aβ pathology may affect nucleoporin levels and NPC function. All functional NCT experiments are based on reporters or dyes, although one would expect widespread mislocalization of endogenous proteins, likely affecting many cellular pathways. The second part of this manuscript reports that in App KI neurons, disruption in the permeability barrier and nucleocytoplasmic transport may enhance activation of key components of the necrosome complex that include receptor-interacting kinase 3 (RIPK3) and mixed lineage kinase domain1 like (MLKL) protein, resulting in an increase in TNFα-induced necroptosis. While this is of potential interest, it is not well integrated in the study. This potential disease pathway is not shown in the very simple schematic (Fig. 8) and is barely mentioned in the Discussion section, although it would deserve a more thorough examination.

Reviewer #2 (Public Review):

Summary:<br /> The authors try to establish that there is an Abeta-dependent loss of nuclear pores early in Alzheimer's disease. To do so the authors compared different NUP proteins and assessed their function by analyzing nuclear leakage and resistance to induction of nuclear damage and the associated necroptosis. The authors use a mouse knockin for hAPP with familial Alzheimer's mutations to model amyloidosis related to Alzheimer's disease. Treatment with an inhibitor of beta-amyloid production partially rescued the loss of nuclear pore proteins in young KI neurons, implicating beta-amyloid in Nuclear Pore dysfunction, a mechanism already described in other neurodegenerative diseases but not in Alzheimer's disease.

The conclusions of this paper related to familial AD are well supported by data but are not related to an aging decline in NUP function, where it is required to extend data analysis and one additional experiment.

1. Adding statistics and comparisons between wild-type changes at different times/ages to determine if the nuclear pore changes with time in wild-type neurons. The images show differences in the Nuclear pore in neurons from the wild-type mice, with time in culture and age. However, a rigorous statistical analysis is lacking to address the impact of age/development on NUP function. Although the authors state that nuclear pore transport is reported to be altered in normal brain aging, the authors either did not design their experiments to account for the normal aging mechanisms or overlooked the analysis of their data in this light.

2. Add experiments to assess the contribution of wild-type beta-amyloid accumulation with aging. It was described in 2012 (Guix FX, Wahle T, Vennekens K, Snellinx A, Chávez-Gutiérrez L, Ill-Raga G, Ramos-Fernandez E, Guardia-Laguarta C, Lleó A, Arimon M, Berezovska O, Muñoz FJ, Dotti CG, De Strooper B. 2012. Modification of γ-secretase by nitrosative stress links neuronal ageing to sporadic Alzheimer's disease. EMBO Mol Med 4:660-673, doi:10.1002/emmm.201200243) and 2021 (Burrinha T, Martinsson I, Gomes R, Terrasso AP, Gouras GK, Almeida CG. 2021. Upregulation of APP endocytosis by neuronal aging drives amyloid-dependent synapse loss. J Cell Sci 134. doi:10.1242/jcs.255752), 28 DIV neurons are senescent and accumulate beta-amyloid42. In addition, beta-amyloid 42 accumulates normally in the human brain (Baker-Nigh A, Vahedi S, Davis EG, Weintraub S, Bigio EH, Klein WL, Geula C. 2015. Neuronal amyloid-β accumulation within cholinergic basal forebrain in ageing and Alzheimer's disease. Brain 138:1722-1737. doi:10.1093/brain/awv024), thus, it would be important to determine if it contributes to NUP dysfunction. Unfortunately, the authors tested the Abeta contribution at div14 when wild-type Abeta accumulation was undetected. It would enrich the paper and allow the authors to conclude about normal aging if additional experiments were performed, namely, treating 28Div neurons with DAPT and assessing if NUP is restored.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript reports the novel observation of alterations in the nuclear pore (NUP) components and the function of the nuclear envelope in knock-in models of APP and presenilin mutations. The data show that loss of NUP immunoreactivity (IR) and pore density are observed at times prior to plaque deposition in this model. The loss of NUP IR is correlated with an increase in intraneuronal Abeta IR with two monoclonal antibodies that react with the N-terminus of Abeta. Similar results are observed in cultured neurons from APP-KI and Wt mice where further results with cultured neurons indicate that Abeta "drives" this process: incubation of neurons with oligomeric, but not monomeric or fibrillar Abeta causes loss of NUP IR, incubation with conditioned media from KI cells but not wt cells also causes loss of NUP IR and treatment with the gamma secretase inhibitor, NAPT partially blocks the loss of NUP IR. Further data show that nuclear envelope function is altered in KI cells and KI cells are more sensitive to TNFalpha-induced necroptosis. This is potentially an important and significant report, but how this fits within the larger picture of what is known about amyloid aggregation and accumulation and pathogenesis in neurons needs to be clarified. The results from mouse brains are strong, while the results from cultured cells are in some instances are of a lower magnitude, less convincing, ambiguous, and sometimes over-interpreted.

Strengths:<br /> 1. Loss of NUP expression and activity is a novel observation.<br /> 2. Its association with intraneuronal Abeta immunoreactivity suggests an association with Alzheimer's disease.<br /> 3. The experiments generally appear to be well-controlled.<br /> 4. Multiple approaches are sometimes used to increase the robustness of the data.

Weaknesses:<br /> 1. It does not consider the relationship of the findings here to other published work on the intraneuronal perinuclear and nuclear accumulation of amyloid in other transgenic mouse models and in humans.<br /> 2. It appears to presume that soluble, secreted Abeta is responsible for the effect rather than the insoluble amyloid fibrils.<br /> 3. Most of the critical findings on the association with Abeta and the functional consequences are done in cultured neurons and not in mouse models.<br /> 4. There is no evidence from the human brain that would strengthen the significance.<br /> 5. It is not clear when the alteration in NUP expression begins in the KI mice as there is no time at which there is no difference between NUP expression in KI and Wt and the earliest time shown is 2 months. If NUP expression is decreased from the earliest times at birth, then this makes the significance of the observation of the association with amyloid pathology less clear.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript aimed at elucidating the substrate specificity of two M23 endopeptidase Lysostaphin (LSS) and LytM in S. aureus. Endopeptidases are known to cleave the glycine-bridges of staphylococcal cell wall peptidoglycan (PG). To address this question, various glycine-bridge peptides were synthesized as substrates, the catalytic domain of LSS and LytM were recombinantly expressed and purified, and the reactions were analyzed using solution-state NMR. The major finding is that LytM is not only a Gly-Gly endopeptidase, but also cleaves D-Ala-Gly. Technically, the advantage of using real-time NMR was emphasized in the manuscript. The study explores an interesting aspect of cell wall hydrolases in terms of substrate-level regulation. It potentially identified new enzymatic activity of LytM. However, the biological significance and relevance of the conclusions remain clear, as the results are mostly from synthetic substrates.

Strengths:<br /> The study explores an interesting aspect of cell wall hydrolases in terms of substrate-level regulation. It potentially identified new enzymatic activity of LytM.

Weaknesses:<br /> 1. Significance: while the current study provided a detailed analysis of various substrates, the conclusions are mainly based on synthesized peptides. One experiment used purified muropeptides (Fig. 3H); however, the results were unclear from this figure. The results from synthesized peptides may not necessarily correlate with their biological functions in vivo. Secondly, the study used only the catalytic domain of both proteins. It is known that the substrate specificity of these enzymes is regulated by their substrate-binding domains. There is no mention of other domains in the manuscript and no justification of why only the catalytic domain was studied. In short, the relevance of the results from the current study to the enzymes' actual physiological functions remains to be addressed, which attenuated the significance of the study.

2. Impact and novelty: (1) the current study provided evidence suggesting the novel function of LytM in cleaving D-Ala-Gly. The impact of this finding is unclear. The manuscript discussed Enterococcus faecalis EnpA. But how about other M23 endopeptidases? What is biological relevance? (2) A very similar study published recently showed that the activity of LSS and LytM is regulated by PG cross-linking: LSS cleaves more cross-linked PG and LytM cleaves less cross-linked PG (Razew, A., Laguri, C., Vallet, A., et al. Staphylococcus aureus sacculus mediates activities of M23 hydrolases. Nat Commun 14, 6706 (2023). The results of this paper are different from the current study whereby both LSS and LytM prefer cross-linked substrates (Fig, 2JKL). Moreover, no D-Ala-Gly cleavage was observed by LytM using purified PG substrate from Razew A et al. An explanation of inconsistent results is needed here. In my opinion, the knowledge generated from the current study has not been fully settled. If the results can be validated, the contribution to the field is incremental, but not substantial. (3) The authors emphasized a few times in the text that it is superior to use NMR technology. In my opinion, NMR has certain advantages, such as measuring the efficacy of cleavage, but it is not that superior. It should be complementary to other methods such as mass spectrometry. In addition, more relevant solid-state NMR using intact PG or bacterial cells was not discussed in the study. I am of the opinion that the corresponding text should be revised.

3. The conclusions are not fully supported by the data<br /> As mentioned above, the conclusions from synthesized peptide substrates may not necessarily reveal physiological functions. The conclusions need to be validated by more physiological substrates.

4. There are some issues with the presentation of the figures, text, and formatting.

Reviewer #2 (Public Review):

Summary:<br /> This work investigates the enzymatic properties of lysostaphin (LSS) and LytM, two enzymes produced by Staphylococcus aureus and previously described as glycyl-glycyl endopeptidases. The authors use synthetic peptide substrates mimicking peptidoglycan fragments to determine the substrate specificity of both enzymes and identify the bonds they cleave.

Strengths:<br /> - This work is addressing a real gap in our knowledge since very little information is available about the substrate specificity of peptidoglycan hydrolases.<br /> - The experimental strategy and its implementation are robust and provide a thorough analysis of LSS and LytM enzymatic activities. The results are very convincing and demonstrate that the enzymatic properties of the model enzymes studied need to be revisited.

Weaknesses:<br /> - The manuscript is difficult to read in places and some figures are not always presented in a way that is easy to follow. This being said, the authors have made a good effort to present their experiments in an engaging manner. Some recommendations have been made to improve the current manuscript but these remain minor issues.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript by Dubey et al. examines the function of the acetyltransferase Tip60. The authors show that (auto)acetylation of a lysine residue in Tip60 is important for its nuclear localization and liquid-liquid-phase-separation (LLPS).

The main observations are: (i) Tip60 is localized to the nucleus, where it typically forms punctate foci. (ii) An intrinsically disordered region (IDR) within Tip60 is critical for the normal distribution of Tip60. (iii) Within the IDR the authors show that a lysine residue (K187), that is auto-acetylated, is critical. Mutation of that lysine residue to a non-acetylable arginine abolishes the behavior. (iv) biochemical experiments show that the formation of the punctate foci may be consistent with LLPS.

Strengths:<br /> The experiments are largely convincing and appear to be well executed.

Weaknesses:<br /> The main concern I have is that all in vivo (i.e. in cells) experiments are done with overexpression in Cos-1 cells, in the presence of the endogenous protein. No attempt is made to use e.g. cells that would be KO for Tip60 in order to have a cleaner system or to look at the endogenous protein. It would be reassuring to know that what the authors observe with highly overexpressed proteins also takes place with endogenous proteins.

Also, it is not clear how often the experiments have been repeated and additional quantifications (e.g. of western blots) would be useful.

In addition, regarding the LLPS description (Figure 1), it would be important to show the wetting behavior and the temperature-dependent reversibility of the droplet formation.

On balance, this is an interesting study that describes the role of acetylation of Tip60 in controlling its biochemical behavior as well as its localization and function in cells. The authors mention in their Discussion section other examples showing that acetylation can change the behavior of proteins with respect to LLPS; depending on the specific context, acetylation can promote (as here for Tip60) or impair LLPS.

Reviewer #2 (Public Review):

The manuscript "Autoacetylation-mediated phase separation of TIP60 is critical for its functions" by Dubey S. et al reported that the acetyltransferase TIP60 undergoes phase separation in vitro and cell nuclei. The intrinsically disordered region (IDR) of TIP60, particularly K187 within the IDR, is critical for phase separation and nuclear import. The authors showed that K187 is autoacetylated, which is important for TIP60 nuclear localization and activity on histone H4. The authors did several experiments to examine the function of K187R mutants including chromatin binding, oligomerization, phase separation, and nuclear foci formation. However, the physiological relevance of these experiments is not clear since TIP60 K187R mutants do not get into nuclei. The authors also functionally tested the cancer-derived R188P mutant, which mimics K187R in nuclear localization, disruption of wound healing, and DNA damage repair. However, similar to K187R, the R188P mutant is also deficient in nuclear import, and therefore, its defects cannot be directly attributed to the disruption of the phase separation property of TIP60. The main deficiency of the manuscript is the lack of support for the conclusion that "autoacetylation-mediated phase separation of TIP60 is critical for its functions".

This study offers some intriguing observations. However, the evidence supporting the primary conclusion, specifically regarding the necessity of the intrinsically disordered region (IDR) and K187ac of TIP60 for its phase separation and function in cells, lacks sufficient support and warrants more scrutiny. Additionally, certain aspects of the experimental design are perplexing and lack controls to exclude alternative interpretations. The manuscript can benefit from additional editing and proofreading to improve clarity.

Reviewer #3 (Public Review):

This study presents results arguing that the mammalian acetyltransferase Tip60/KAT5 auto-acetylates itself on one specific lysine residue before the MYST domain, which in turn favors not only nuclear localization but also condensate formation on chromatin through LLPS. The authors further argue that this modification is responsible for the bulk of Tip60 autoacetylation and acetyltransferase activity towards histone H4. Finally, they suggest that it is required for association with txn factors and in vivo function in gene regulation and DNA damage response.

These are very wide and important claims and, while some results are interesting and intriguing, there is not really close to enough work performed/data presented to support them. In addition, some results are redundant between them, lack consistency in the mutants analyzed, and show contradiction between them. The most important shortcoming of the study is the fact that every single experiment in cells was done in over-expressed conditions, from transiently transfected cells. It is well known that these conditions can lead to non-specific mass effects, cellular localization not reflecting native conditions, and disruption of native interactome. On that topic, it is quite striking that the authors completely ignore the fact that Tip60 is exclusively found as part of a stable large multi-subunit complex in vivo, with more than 15 different proteins. Thus, arguing for a single residue acetylation regulating condensate formation and most Tip60 functions while ignoring native conditions (and the fact that Tip60 cannot function outside its native complex) does not allow me to support this study.

Specific points:<br /> -It is known that over-expression after transient transfection can lead to non-specific acetylation of lysines on the proteins, likely in part to protect from proteasome-mediated degradation. It is not clear whether the Kac sites targeted in the experiments are based on published/public data. In that sense, it is surprising that the K327R mutant does not behave like a HAT-dead mutant (which is what exactly?) or the K187R mutant as this site needs to be auto-acetylated to free the catalytic pocket, so essential for acetyltransferase activity like in all MYST-family HATs. In addition, the effect of K187R on the total acetyl-lysine signal of Tip60 is very surprising as this site does not seem to be a dominant one in public databases.

-As the physiological relevance of the results is not clear, the mutants need to be analyzed at the native level of expression to study real functional effects on transcription and localization (ChIP/IF). It is not clear the claim that Tip60 forms nuclear foci/punctate signals at physiological levels is based on what. This is certainly debated because in part of the poor choice of antibodies available for IF analysis. In that sense, it is not clear which Ab is used in the Westerns. Endogenous Tip60 is known to be expressed in multiple isoforms from splice variants, the most dominant one being isoform 2 (PLIP) which lacks a big part (aa96-147) of the so-called IDR domain presented in the study. Does this major isoform behave the same?

-It is extremely strange to show that the K187R mutant fails to get in the nuclei by cell imaging but remains chromatin-bound by fractionation... If K187 is auto-acetylated and required to enter the nucleus, why would a HAT-dead mutant not behave the same?

-If K187 acetylation is key to Tip60 function, it would be most logical (and classical) to test a K187Q acetyl-mimic substitution. In that sense, what happens with the R188Q mutant? That all goes back to the fact that this cluster of basic residues looks quite like an NLS.

-The effect of the mutant on the TIP60 complex itself needs to be analyzed, e.g. for associated subunits like p400, ING3, TRRAP, Brd8...

-The discussion is excessively long without addressing the obvious questions mentioned above.

Reviewer #1 (Public Review):

This study shows that SET7 and LSD1 regulate the dynamic methylation of EZH2 at K20, which is recognized by L3MBTL3 promoting protein degradation via the DCAF5-CRL4 E3 ubiquitin ligase. K20 methylation negatively regulates S21 phosphorylation and vice versa, modulating EZH2 functions. Mice harboring the K20 methylation-deficient mutant (K20R) exhibit hematopoietic defects. Overall, this is an interesting study elucidating a novel mechanism of EZH2 regulation. The methodologies are sound and the conclusions are largely supported by the data provided. However, there are some questions regarding the overall model and some contradictory results.

Reviewer #2 (Public Review):

EZH2 is upregulated in most advanced cancers and has been investigated as a therapeutic target for many years. However, how EZH2 activity is regulated remains to be fully elucidated. In this study, Guo et al. provided a new mechanism for the regulation of EZH2. The authors demonstrated that the protein stability of EZH2 is dynamically regulated by lysine methylation-dependent proteolysis. Specifically, K20 of EZH2 is monomethylated by SET7 methyltransferase and demethylated by LSD1 demethylase. The methylated K20 is recognized by specific methyl-lysine reader L3MBTL3 to promote EZH2 for ubiquitin-dependent proteolysis by the CRL4DCAF5 ubiquitin E3 ligase complex, resulting in the dysregulation of EZH2/PRC2 activity and reduction of H3K27me3. The authors further found a methylation-phosphorylation switch existed in some cancer cells and this switch controls EZH2 stability and hematopoiesis.

Overall, most conclusions of this paper are well-supported by the results presented, only some aspects of Figure 6 need to be extended. This work is of interest to biomedical researchers in the field of cancer epigenetics after minor revision.

Reviewer #3 (Public Review):

In this study, the authors demonstrated a new mechanism by which the protein stability of EZH2 is regulated. This mechanism is multifaceted and yet the authors provided evidence for every step of regulation. EZH2 is monomethylated at K20 by SET7, which can be removed by LSD1 and recognized by L3MBTL3. L3MBTL3 recruits the ubiquitin E3 ligase CRLDCAF5 to EZH2 via methylation of K20, which results in polyubiquitylation and proteasomal degradation of the histone methyltransferase. Additionally, they found that AKT-mediated phosphorylation of EZH2 at S21 blocks monomethylation at K20 and vice versa. Finally, they demonstrated in the K20R GEMM model that stabilization of EZH2 protein leads to reactive hyperplasia and hematopoiesis. In general, this study reveals an interesting and novel mechanism underlying the regulation of the epigenetic mark H3K27me3 and the oncogenic function of EZH2. The authors have considered every aspect of the signaling pathway that regulates the protein stability of EZH2. The data was comprehensive, rigorous, and supportive of the conclusions they made. Their results may help explain some of the conflicting results that previous studies have reported.

However, there are still some issues with the significance of the work and the quality of the data. The major issues are:<br /> 1. The converged effect of EZH2 methylation and phosphorylation on H3K27me3 is unclear.<br /> 2. How the methylation-phosphorylation switch of EZH2 determines the biological phenotypes they observed is not addressed.<br /> 3. Some of the data in the manuscript is conflicting.

Reviewer #1 (Public Review):

The study by Schmehl and colleagues asks an important question, i.e. how are multiple objects/stimuli represented in the visual system despite broad tuning properties of neurons along multiple different dimensions (e.g. space, features). This is a continuation of an impactful and highly significant line of work from the Groh lab and their collaborators. In previous work, they showed that fluctuations in firing patterns may be critical in representing multiple objects and parse them in time. In this particular study, the authors ask three specific questions to extend these observations: (i) Are such fluctuations widespread in the visual system?; (ii) Are they related to the perceptual distinction of objects?; (iii) And how are they related to the functional specialization of neuronal populations along feature dimensions (e.g. faces, motion).

It seems to me that there is ample evidence for the first two questions from previous work by these authors. For (i), fluctuations in firing patterns related to multiple stimuli have been shown in the auditory (e.g. inferior colliculus, Caruso et al., 2018) and multiple areas of the visual system (i.e. V1, V4, and the face patch system; Caruso et al., 2018; Jun et al., 2022). The present study adds data from MT to this increasing evidence. For (ii), Jun et al., 2022 already showed that fluctuations are not related to stimuli perceived as merged, or not distinct. Thus, the main contribution appears to be related to functional specialization. I suggest clarifying the major novelty of the present report and to focus the introduction on it.

The present work analyzed three different data sets acquired in different areas (V1, V4, MT, IT face network), using different feature stimuli (motion, faces), obtained under various attention conditions/states (passive fixation, actively ignored). Many of the results are nice confirmations and minor extensions of previous work. The conceptual advance and novelty of the findings are therefore limited.

There is a growing literature on fluctuating neural firing patterns that is not considered in this report. The scholarship appears a bit impoverished with only 19 references, many of which point to work from this group of collaborators. I suggest that the authors consider the present work in the context of the wider literature more scholarly, even if not all the relations of these different lines of work can be conclusively connected at this point. For a few examples, there is work by Kienitz and colleagues on fluctuating neural patterns in V4 evoked by competing grating stimuli. Also, the work by Engel, Moore, and colleagues on 'on' and 'off' states in the context of selective attention seems relevant, or the work by Fiebelkorn and Kastner on rhythmic perception and attention.

Reviewer #2 (Public Review):

In a beautiful line of work, the authors have proposed the intriguing idea that activity patterns of neurons can fluctuate between representing one of multiple stimuli in its receptive field. This allows for time-multiplexing of information by neural populations. The idea was initially proposed by Caruso et al (2018) and tested for both auditory and visual stimuli and later extended in Jun et al (2022). The current study analyzes additional datasets to further extend the conclusions across multiple areas and different stimulus sets.

Together with the earlier work, the current study provides solid evidence for the hypothesis that fluctuating activity patterns in neurons representing multiple stimuli may be a general phenomenon. This exciting possibility may have implications for the studies of perception, attention, decision-making, and other cognitive functions.

In the current study, the claim that the fluctuating activity patterns may be a general phenomenon is supported by multiple data sets from area MT and face patches MF and AL in IT cortex, using multiple stimulus sets (moving dots and gratings for MT, and face-face and face-object pairs for IT cortex). The major strength of this study is the consistency of the results across these areas and stimulus sets.

The description of the results would benefit from a better explanation of how low spike counts may influence the outcome of the analysis. Due to a smoothing procedure used for visualization, the spike counts for the paired stimuli (AB, black lines) shown in Figure 3a-b and Figure 4a-d go below 0. However, the actual spike count on a trial can not go below 0. The symmetric smoothing procedure may hide an underlying skewed distribution of spike counts that can only be positive. The statistical analysis is not performed on the smoothed distribution but on the actual spike counts, and the validity of the result is therefore not in question. However, the paper would benefit from 1) visualization of the unsmoothed trial counts, and 2) an explanation of how assumptions of symmetric/skewed distributions may affect the outcome.

Overall, the authors have presented an interesting hypothesis that is supported by rigorous analysis, they clearly described the results, and they have given a fair discussion of what we can and cannot conclude from this dataset. This line of work deserves the attention of a broad audience within the field of neuroscience.

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors attempt to reinvestigate an old question in population genetics regarding the age of alleles that have experienced different strengths (and directions) of natural selection. Under simple population genetic models, alleles that are positively selected are expected to change frequency in populations faster than neutral alleles. So the naïve expectation is that if you look at alleles that are the same population frequency, those that have been evolving neutrally should have been segregating in the population longer than those that have been experiencing natural selection. While this is exactly what the authors find for alleles inferred to be experiencing negative selection (i.e. they tend to be younger than alleles inferred to be neutral that are at the same frequency), the authors find the opposite for alleles inferred to be under positive selection: they tend to be older than alleles inferred to be neutral. The authors argue that this pattern can be explained by a model where positively selected mutations experience a phase of balancing selection that can dramatically extend the period of time that these alleles segregate in the population.

Strengths:<br /> The question that the authors address is very interesting and thought provoking. When confronted with a counter-intuitive finding, the authors describe an interesting hypothesis to explain it. The authors investigate a number of interesting sub analyses to corroborate their findings.

Weaknesses:<br /> While there are some intriguing hypotheses in this manuscript, I struggle to be convinced. The main point that the authors argue is that positively selected alleles are older than their neutral counterparts at the same frequency. They argue that this may be because the positively selected alleles are stuck in some form of balancing selection for a long time before they switch to a more classical form of directional selection. The form of balancing selection they argue is one caused by linkage to deleterious alleles, which takes time for the beneficial alleles to recombine onto a more neutral background. I would really like to see some simulations that demonstrate this can actually occur on average. Reading this paper brought back memories of the classic Birky and Walsh (1988; PMCID: PMC281982) paper that argued that linkage amongst selected alleles does not impact the substitution rate of linked neutral alleles, but does reduce the substitution rate among beneficial alleles. Their simple simulations in 1988 illuminated how this works, and they developed a simple mathematical model that helped us understand how it works. In the current paper, it seems the authors are arguing for a similar effect, but rather than focus on beneficial alleles that fix, they are focusing on beneficial alleles that are still segregating. These seem like similar stories, but without simulations or a mathematical model, I struggle to gain any insight into why the observation is the way it is (and not simply due to a number of possible confounding effects noted below).<br /> There are a number of elements to the methods and interpretation that could use clarification.<br /> • Genetic data. One of the biggest weaknesses of this analysis is the choice of genetic data. The authors use the UK10k dataset, and reference the 2015 paper. Looking at that paper, it seems that the data may be composed of low coverage whole genome sequencing data (7x) and high coverage exome sequence data (80x). It appears that these data were integrated into a single VCF file, similar to the 1000 Genomes Project Phase 3 data. If these are the data that was used, then there are substantial differences between the coding and non-coding variants that are compared. However, it is possible that the authors chose to restrict the analysis to the low coverage WGS data and neglected to indicate it in the methods section. I will assume that this is the case for the rest of the review, but the authors should clarify.<br /> • Recombination rates. I believe the authors use an LD-based recombination map. While these maps are correlated at the longer physical distances with pedigree maps, there are substantial differences at shorter physical scales. These differences have been argued to be due to the action of natural selection skewing patterns of LD. If that is the case, then some of the observations in this paper are circular. Please confirm similar findings with a pedigree-based recombination map.<br /> • Recombination rates, pt 2. The authors compare patterns of non-synonymous coding variants to a set of non-coding, non-regulatory SNPs. They argue "these will necessarily have experienced similar mutational and recombinational processes". I don't know that this is true. There are both distinct recombination patterns and mutational patterns in genes vs non-coding regions of the genome. It would be important to more carefully match coding and non-coding variants based on both recombination as well as the type of nucleotide change. There are substantial differences in CpG composition in coding vs non-coding regions for example. While the authors say "Analyses thought to be sensitive to CpG high mutability were limited to SNPs that did not occur as part of a CpG", it is quite unclear what where CpGs were included vs excluded.<br /> • Identifying ancestral vs derived alleles. It is unclear how the authors identified ancestral vs derived alleles (they say "inferred ancestral sequence from Ensembl (1) and a maximum likelihood estimator". Several studies have shown that ancestral misidentification can cause skews in the site frequency spectrum. If the ancestral state of some fraction of alleles were misidentified, then the estimated allele age would be incorrect. Figure 1B shows that the mean frequency of the alleles with the largest delta-EP tend to be very low. This makes me think that ancestral misidentification may have impacted the results.<br /> • Figure 2B and C. I do not understand how the median can be so far outside the mean and error bars. The legend does not specify what the error bars are, but I feel the distribution must be shown if it is so skewed that the mean and any definition of error does not include the median.<br /> • Inferring allele ages. The authors use two methods for estimating allele ages, but focus on GEVA. They use the default parameter of effective population size 10,000. How sensitive is the model to this assumption? It has been shown that different regions of the genome (particularly coding vs neutral non-coding) experience different rates of deleterious mutations, and therefore different rates of background selection. Simple models of background selection would suggest that these regions will therefore have different effective population sizes.<br /> • Fst analysis. The authors look at Fst among 3 populations as a function of delta-EP compared to frequency-matched control SNPs. They find there is no statistical support for different levels of Fst in any pairwise comparison for any delta-EP bin. It seems strange that alleles with large delta-EP would not show increased Fst compared to control SNPs... If they are indeed positively selected, the assumption must be that they are then positively selected in all populations, which seems unlikely. Alternatively, by considering only narrow allele frequency bins, it is possible that Fst is also being controlled, and therefore this analysis is non-informative. A simulation would help understand what the expected pattern is here.<br /> • It would be great to show more figures like 2A. You can place the x-axis on a log-scale so that it is easier to view the lower allele frequencies. This plot clearly shows differences among the 3 categories. I am very surprised at the much shorter error bars for negative delta-EP at high frequency compared to positive delta-EP variants... Shouldn't there be very few negative delta-EP alleles at such high frequency?

Reviewer #2 (Public Review):

The authors provide an analysis showing that the allele ages of putatively advantageous alleles tend to be older than those of neutral alleles. To do this, the authors first classify mutations as either neutral, advantageous or deleterious based on a metric called the 'evolutionary probability' which is correlated to the impact of selection acting on a mutation. Then, the authors quantify the age of the mutations using the GEVA method and they also quantify tc (the time of the ancestral node of the edge carrying the mutation). Interestingly, the authors find that advantageous mutations tend to have an older allele age and an older value of tc compared to neutral mutations. The authors posit some explanations for this result invoking the action of balancing selection.

This is an interesting paper and its results could merit an important change in our conception of how we believe that natural selection is acting on the human genome. I have concerns about some of the analysis presented on this paper that have to do with two main factors: 1) Showing that the estimates of allele ages and tc are robust on the dataset presented (more on this topic here below). 2) Presenting more simulations or analytical theory where the authors can show that the models presented by the authors to explain the results indeed fit the data well. As an example, the authors could perform some simulations (likely using SLiM) under the balancing selection models posited by the authors and then show that they can produce data where the allele ages for deleterious, neutral and advantageous alleles have similar patterns to what is observed on the genomic dataset analyzed.

Major concerns

- What is the impact of multiple mutations on the same site on the estimates of allele ages with GEVA?

- GEVA, which is one of the methods used by the authors, 'overestimates "intermediate" times and underestimates older times' according to Ragsdale and Thornton (2023) MBE. What is the impact of this effect for the analysis performed by the authors? Do RUNTC has any known biases on their estimate of tc?

- Additionally what is the impact of phasing errors on the estimates of allele age presented by the authors?

Reviewer #3 (Public Review):

In their manuscript, Pivirotto et al. make an unexpected observation that a set of candidate beneficial alleles according to the Evolutionary Probability method (EP) have estimated ages thousands of years older than control alleles of similar frequency and outside of functional segments. To explain this unexpectedly older ages, the authors propose a number of interesting evolutionary processes related to balancing selection, including staggered sweeps.

It is important to first mention that the authors do find that as expected, deleterious alleles are younger than controls. This provides evidence that the allele age estimates used by the authors are of sufficient quality to detect age differences between groups of genes. I am also convinced by the fact that EP can be used to focus on a set of alleles substantially enriched in deleterious ones, given the very clear frequency patterns related to EP.

I have a number of concerns about the manuscript, including one rather serious one.

My main concern is that many of the observations made by the authors could be caused by mispolarization of alleles, where either (i) mostly low frequency derived alleles are mischaracterized as ancestral and the other, actually ancestral allele is mischaracterized as a high frequency derived allele, or (ii) mostly low frequency ancestral alleles are mischaracterized as derived. Unfortunately, the authors do not even mention the risk of mispolarization in their manuscript. This is a serious problem for this manuscript because ancestral alleles annotated as derived are by definition going to generate older age estimates than if they were truly derived. It would be very useful to be able to have a look at the full distribution of allele ages rather than just confidence intervals as in Figure 1. I happen to have experience with mispolarization of high frequency ancestral alleles as derived by a maximum likelihood method, different from the one used by the authors (Keightley et al Genetics 2018), where the mispolarization became visible as a very suspicious SFS with a visible excess of high frequency variants, especially those expected to be functional (because of the relatively larger corresponding supply of low frequency deleterious functional variants). Even if the ML method used by the authors is not the same, mispolarization is still a serious risk. Glémin et al. Genome Research 2015 also found that mispolarization is far from being a negligible issue.

Mispolarization of low frequency alleles may be especially prominent in the case of mispolarized deleterious alleles associated with a very negative delta-EP, that then appear as alleles with a very positive delta-EP. Focusing on high delta-EP alleles may then in fact enrich the dataset in mispolarized alleles that then result in older age estimates. Looking at Figure 1B especially, I am worried by the fact that very high delta-EP values seem to go back to the frequencies observed for very negative delta-EP. This is what mispolarization of low frequency alleles might cause as a pattern, in this case especially low frequency ancestral alleles being misidentified as derived?

The authors can address the possible issue of mispolarization in multiple ways. First, they can use simulations of sequences to estimate amounts of mispolarization based on their polarization approach, using substitutions/mutation rates as realistic as possible.<br /> Second, the authors could check if there is suspicious symmetry in the distribution of delta-EP between alleles at frequency f and alleles at frequency 1-f. This pattern could be generated by mispolarization.

My second less serious concern has to do with the use of high delta-EP as evidence that alleles are beneficial. The validation set from the Patel & Kumar 2019 paper is arguably small with 24 known selected variants. It does not follow from the fact that a small set of known selected variants have higher delta-EP, that all variants with high delta-EP tend to be beneficial. This is especially true in the case where beneficial variants tend to be rare, and there are then far more variants expected with high delta-EP than there are beneficial variants. I am willing to change my mind on this if the overall results can be shown to be robust after accounting for allele mispolarization.

Third, I like the idea of staggered sweeps to explain the results, but I am wondering if there is any evidence in the literature of interference between deleterious and advantageous variants that the authors could base their proposed explanation on.

Finally, and I realize that it is a bit of a stretch, I am wondering if the authors could better justify their choices of methods to estimate the age of alleles. What about ARGweaver, Relate or tsdate? How do these methods compare with GEVA? From looking at the literature I could not find a direct comparison of the precision of GEVA compared to these other tools, but it may be worth at least discussing that the results could be further put to the test with other available ARG-based tools to estimate allele ages. Wilder Wohns et al. Science 2022 compare the performance of these different ARG methods with ancient DNA data, and in fact find that GEVA does not perform as well as for example Relate or tsdate.

Reviewer #1 (Public Review):

Summary:<br /> Herein, Blaeser et al. explored the impact of migraine-related cortical spreading depression (CSD) on the calcium dynamics of meningeal afferents that are considered the putative source of migraine-related pain. Critically previous studies have identified widespread activation of these meningeal afferents following CSD; however, most studies of this kind have been performed in anesthetized rodents. By conducting a series of technically challenging and compelling calcium imaging experiments in conscious head fixed mice they find in contrast that a much smaller proportion of meningeal afferents are persistently activated following CSD. Instead, they identify that post-CSD responses are differentially altered across a wide array of afferents, including increased and decreased responses to mechanical meningeal deformations and activation of previously non-responsive afferents following CSD. Given that migraine is characterized by worsening head pain in response to movement, the findings offer a potential mechanism that may explain this clinical phenomenon.

Strengths:<br /> Using head fixed conscious mice overcomes the limitations of anesthetized preps and the potential impact of anaesthesia on meningeal afferent function which facilitated novel results when compared to previous anesthetized studies. Further, the authors used a closed cranial window preparation to maximize normal physiological states during recording, although the introduction of a needle prick to induce CSD will have generated a small opening in the cranial preparation, rendering it not fully closed as suggested. However, technical issues with available AAV's and alternate less invasive triggering methodologies necessitate the current approach.

Weaknesses:<br /> Although this is a well conducted technically challenging study that has added valuable knowledge on the response of meningeal afferents the study would have benefited from the inclusion of more female mice. Migraine is a female dominant condition and an attempt to compare potential sex-differences in afferent responses would undoubtedly have improved the outcome. The authors report potential sex-specific effects on AAV transfection rates between males and females which have contributed to this imbalance.

The authors imply that the current method shows clear differences when compared to older anaesthetized studies; however, many of these were conducted in rats and relied on recording from the trigeminal ganglion. Attempts to address this point have proven difficult due to limited GCaMP signalling in anaesthetised mice, meaning that technical differences cannot be ruled out.

Reviewer #2 (Public Review):

This is an interesting study examining the question of whether CSD sensitizes meningeal afferent sensory neurons leading to spontaneous activity or whether CSD sensitizes these neurons to mechanical stimulation related to locomotion. Using two-photon in vivo calcium imaging based on viral expression of GCaMP6 in the TG, awake mice on a running wheel were imaged following CSD induction by cortical pinprick. The CSD wave evoked a rise in intracellular calcium in many sensory neurons during the propagation of the wave but several patterns of afferent activity developed after the CSD. The minority of recorded neurons (10%) showed spontaneous activity while slightly larger numbers (20%) showed depression of activity, the latter pattern developed earlier than the former. The vast majority of neurons (70%) were unaffected by the CSD. CSD decreased the time spent running and the numbers of bouts per minute but each bout was unaffected by CSD. There also was no influence of CSD on the parameters referred to as meningeal deformation including scale, shear, and Z-shift. Using GLM, the authors then determine that there there is an increase in locomotion/deformation-related afferent activity in 51% of neurons, a decrease in 12% of neurons, and no change in 37%. GLM coefficients were increased for deformation related activity but not locomotion related activity after CSD. There also were an increase in afferents responsive to locomotion/deformation following CSD that were previously silent. This study shows that unlike prior reports, CSD does not lead to spontaneous activity in the majority of sensory neurons but that it increases sensitivity to mechanical deformation of the meninges. This has important implications for headache disorders like migraine where CSD is thought to contribute to the pathology in unclear ways with this new study suggesting that it may lead to increased mechanical sensitivity characteristic of migraine attacks.

Reviewer #3 (Public Review):

Summary: In this manuscript, Blaeser et al. explore the link between CSD and headache pain. How does an electrochemical wave in the brain parenchyma, which lacks nociceptors, result in pain and allodynia in the V1-3 distribution? Prior work had established that CSD increased the firing rate of trigeminal neurons, measured electrophysiologically at the level of the peripheral ganglion. Here, Blaeser et al. focus on the fine afferent processes of the trigeminal neurons, resolving Ca2+ activity of individual fibers within the meninges. To accomplish these experiments, the authors injected AAV encoding the Ca2+ sensitive fluorophore GCamp6s into the trigeminal ganglion, and 8 weeks later imaged fluorescence signals from the afferent terminals within the meninges through a closed cranial window. They captured activity patterns at rest, with locomotion, and in response to CSD. They found that mechanical forces due to meningeal deformations during locomotion (shearing, scaling, and Z-shifts) drove non-spreading Ca2+ signals throughout the imaging field, whereas CSD caused propagating Ca2+ signals in the trigeminal afferent fibers, moving at the expected speed of CSD (3.8 mm/min). Following CSD, there were variable changes in basal GCamp6s signals: these signals were unchanged in the majority of fibers, signals increased (after a ~20 min delay) in 10% of fibers, and signals decreased in 20% of fibers. Bouts of locomotion were less frequent following CSD, but when they did occur, they elicited more robust GCamp6s signals than pre-CSD. These findings advance the field, suggesting that headache pain following CSD can be explained on the basis of peripheral cranial nerve activity, without invoking central sensitization at the brain stem/thalamic level. This insight could open new pathways for targeting the parenchymal-meningeal interface to develop novel abortive or preventive migraine treatments.

Strengths: The manuscript is well-written. The studies are broadly relevant to neuroscientists and physiologists, as well as neurologists, pain clinicians, and patients with migraine with aura and acephalgic migraine. The studies are well-conceived and appear to be technically well-executed.

Weaknesses: In the present study, conclusions are based entirely on fluorescence signals from GCamp6s. Fluorescence experiments should be interpreted cautiously in the context of CSD. GCamp6 fluorophores are strongly pH dependent, with decreased signal at acidic pH values (at matched Ca2+ concentration). CSD induces an impressive acidosis transient in the brain parenchyma, so one wonders whether the suppression of activity reported in the wake of CSD (Figure 2) in fact reflects decreased sensitivity of the GCamp6 reporter, rather than decreased activity in the fibers. If intracellular pH in trigeminal afferent fibers acidifies in the wake of CSD, GCamp6s fluorescence may underestimate the actual neuronal activity.

Reviewer #1 (Public Review):

The evolution of dioecy in angiosperms has significant implications for plant reproductive efficiency, adaptation, evolutionary potential, and resilience to environmental changes. Dioecy allows for the specialization and division of labor between male and female plants, where each sex can focus on specific aspects of reproduction and allocate resources accordingly. This division of labor creates an opportunity for sexual selection to act and can drive the evolution of sexual dimorphism.

In the present study, the authors investigate sex-biased gene expression patterns in juvenile and mature dioecious flowers to gain insights into the molecular basis of sexual dimorphism. They find that a large proportion of the plant transcriptome is differentially regulated between males and females with the number of sex-biased genes in floral buds being approximately 15 times higher than in mature flowers. The functional analysis of sex-biased genes reveals that chemical defense pathways against herbivores are up-regulated in the female buds along with genes involved in the acquisition of resources such as carbon for fruit and seed production, whereas male buds are enriched in genes related to signaling, inflorescence development and senescence of male flowers. Furthermore, the authors implement sophisticated maximum likelihood methods to understand the forces driving the evolution of sex-biased genes. They highlight the influence of positive and relaxed purifying selection on the evolution of male-biased genes, which show significantly higher rates of non-synonymous to synonymous substitutions than female or unbiased genes. This is the first report (to my knowledge) highlighting the occurrence of this pattern in plants. Overall, this study provides important insights into the genetic basis of sexual dimorphism and the evolution of reproductive genes in Cucurbitaceae.

Reviewer #2 (Public Review):

Summary:

This study uses transcriptome sequence from a dioecious plant to compare evolutionary rates between genes with male- and female-biased expression and distinguish between relaxed selection and positive selection as causes for more rapid evolution. These questions have been explored in animals and algae, but few studies have investigated this in dioecious angiosperms, and none have so far identified faster rates of evolution in male-biased genes (though see Hough et al. 2014 https://doi.org/10.1073/pnas.1319227111).

Strengths:

The methods are appropriate to the questions asked. Both the sample size and the depth of sequencing are sufficient, and the methods used to estimate evolutionary rates and the strength of selection are appropriate. The data presented are consistent with faster evolution of genes with male-biased expression, due to both positive and relaxed selection.

This is a useful contribution to understanding the effect of sex-biased expression in genetic evolution in plants. It demonstrates the range of variation in evolutionary rates and selective mechanisms, and provides further context to connect these patterns to potential explanatory factors in plant diversity such as the age of sex chromosomes and the developmental trajectories of male and female flowers.

Weaknesses:

The presence of sex chromosomes is a potential confounding factor, since there are different evolutionary expectations for X-linked, Y-linked, and autosomal genes. Attempting to distinguish transcripts on the sex chromosomes from autosomal transcripts could provide additional insight into the relative contributions of positive and relaxed selection.

Reviewer #3 (Public Review):

The potential for sexual selection and the extent of sexual dimorphism in gene expression have been studied in great detail in animals, but hardly examined in plants so far. In this context, the study by Zhao, Zhou et al. al represents a welcome addition to the literature.

Relative to the previous studies in Angiosperms, the dataset is interesting in that it focuses on reproductive rather than somatic tissues (which makes sense to investigate sexual selection), and includes more than a single developmental stage (buds + mature flowers).

Reviewer #1 (Public Review):

The apicoplast, a non-photosynthetic vestigial chloroplast, is a key metabolic organelle for the synthesis of certain lipids in apicomplexan parasites. Although it is clear metabolite exchange between the parasite cytosol and the apicoplast must occur, very few transporters associated with the apicoplast have been identified. The current study combines data from previous studies with new data from biotin proximity labeling to identify new apicoplast resident proteins including two putative monocarboxylate transporters termed MCT1 and MCT2. The authors conduct a thorough molecular phylogenetic analysis of the newly identified apicoplast proteins and they provide compelling evidence that MCT1 and MCT2 are necessary for normal growth and plaque formation in vitro along with maintenance of the apicoplast itself. They also provide indirect evidence for a possible need for these transporters in isoprenoid biosynthesis and fatty acid biosynthesis within the apicoplast. Finally, mouse infection experiments suggest that MCT1 and MCT2 are required for normal virulence, with MCT2 completely lacking at the administered dose. Overall, this study is generally of high quality, includes extensive quantitative data, and significantly advances the field by identifying several novel apicoplast proteins together with establishing a critical role for two putative transporters in the parasite. The study, however, could be further strengthened by addressing the following aspects:

Main comments:

1. The conclusion that condition depletion of AMT1 and/or AMT2 affects apicoplast synthesis of IPP is only supported by indirect measurements (effects on host GFP uptake or trafficking, possibly due to effects on IPP dependent proteins such as rabs, and mitochondrial membrane potential, possibly due to effects on IPP dependent ubiquinone). This conclusion would be more strongly supported by directly measuring levels of IPP. If their or technical limitations that prevent direct measurement of IPP then the author should note such limitations and acknowledge in the discussion that the conclusion is based on indirect evidence.

2. The conclusion that condition depletion of AMT1 and/or AMT2 affects apicoplast synthesis of fatty acids is also poorly supported by the data. The authors do not distinguish between the lower fatty acid levels being due to reduced synthesis of fatty acids, reduced salvage of host fatty acids, or both. Indeed, the authors provide evidence that parasite endocytosis of GFP is dependent on AMT1 and AMT2. Host GFP likely enters the parasite within a membrane bound vesicle derived from the PVM. The PVM is known to harbor host-derived lipids. Hence, it is possible that some of the decrease in fatty acid levels could be due to reduced lipid salvage from the host. Experiments should be conducted to measure the synthesis and salvage of fatty acids (e.g., by metabolic flux analysis), or the authors should acknowledge that both could be affected.

Reviewer #2 (Public Review):

In this study Hui Dong et al. identified and characterized two transporters of the monocarboxylate family, which they called Apcimplexan monocarboxylate 1 and 2 (AMC1/2) that the authors suggest are involved in the trafficking of metabolites in the non-photosynthetic plastid (apicoplast) of Toxoplasma gondii (the parasitic agent of human toxoplasmosis) to maintain parasite survival. To do so they first identified novel apicoplast transporters by conducting proximity-dependent protein labeling (TurboID), using the sole known apicoplast transporter (TgAPT) as a bait. They chose two out of the three MFS transporters identified by their screen based and protein sequence similarity and confirmed apicoplast localisation. They generated inducible knock down parasite strains for both AMC1 and AMC2, and confirmed that both transporters are essential for parasite intracellular survival, replication, and for the proper activity of key apicoplast pathways requiring pyruvate as carbon sources (FASII and MEP/DOXP). Then they show that deletion of each protein induces a loss of the apicoplast, more marked for AMC2 and affects its morphology both at its four surrounding membranes level and accumulation of material in the apicoplast stroma. The authors attempted to decipher the function of the transporters on metabolic functions of the apicoplast: (a) notably for IPP synthesis through the assessment of vesicle import allowed by IPP-based anchors, which was found to be affected in the mutants, as well as (b) apicoplast fatty acid synthesis by indirect assessment of vesicle import. However, none of them directly concluded on the actual function of the transporters. Furthermore heterologous complementation in bacterial system also failed to demonstrate the transporters' function.

However, this study is very timely, as the apicoplast holds several important metabolic functions (FASII, IPP, LPA, Heme, Fe-S clusters...), which have been revealed and studied in depth but no further respective transporter have been identified thus far. hence, new studies that could reveal how the apicoplast can acquire and deliver all the key metabolites it deals with, will have strong impact for the parasitology community as well as for the plastid evolution communities. The current study is well initiated with appropriate approaches to identify two new putatively important apicoplast transporters, and showing how essential those are for parasite intracellular development and survival. However, in its current state, this is all the study provides at this point (i.e. essential apicoplast transporters disrupting apicoplast integrity, and indirectly its major functions, FASII and IPP, as any essential apicoplast protein disruption does). The study fails to deliver further message or function regarding AMC1 and 2, and thus validate their study. Currently the manuscript just describes how AMC1/2 deletion impacts parasite survival without answering the key question about them: what do they transport. The authors yet have to perform key experiments that would reveal their metabolic function. Ideally the authors would work further and determine the function of AMC1 and 2.

Reviewer #1 (Public Review):

The manuscript addresses a fundamental question about how different types of communication signals differentially affect brain state and neurochemistry. In addition, their manuscript highlights the various processes that modulate brain responses to communication signals, including prior experience, sex, and hormonal status. Overall, the manuscript is well-written and the research is appropriately contextualized.

That being said, it remains important for the authors to think more about their analytical approaches. In particular, the effect of normalization and the explicit outlining and interpretations of statistical models. As mentioned in the original review, the normalization of neurochemical data seems unnecessary given the repeated-measures design of their analysis and by normalizing all data to the baseline data and including this baseline data in the repeated measures analysis, one artificially creates a baseline period with minimal variation that dramatically differs in variance from other periods (akin to heteroscedasticity). If the authors want to analyze how a stimulus changes neurochemical concentrations, they could analyze the raw data but depict normalized data in their figures (similar to other papers). Or they could analyze group differences in the normalized data of the two stimulus periods (i.e., excluding the baseline period used for normalization).

It would also be useful for the authors to provide further discussion of the potential contributions of different types of experiences (mating vs. restraint) to the change in behavior and neurochemical responses to the vocalization playbacks and to try to disentangle sensory and motor contributions to neurochemical changes.

Reviewer #3 (Public Review):

The work by Ghasemahmad et al. has the potential to significantly advance our understanding of how neuromodulators provide internal-state signals to the basolateral amygdala (BLA) while an animal listens to social vocalizations.

Ghasemahmad et al. made changes to the manuscript that have significantly improved the work. In particular, the transparency in showing the underlying levels of Ach, DA, and 5HIAA is excellent. My previous concerns have been adequately addressed.

Reviewer #1 (Public Review):

Summary:<br /> This paper describes a comparison of different statistical methods for model comparison and covariate selection in neural encoding models. It shows in particular that issues arising from temporal autocorrelation and missing variables can lead to statistical tests with substantially higher false positive rates than expected from theory. The paper proposes methods for overcoming these problems, in particular cross-validation with cyclical shift permutation tests. The results are timely, important, and likely to have a broad impact. In particular, the paper shows that cell tuning classification can vary dramatically with the testing procedure, which is an important lesson for the field as a whole.

Strengths:<br /> - Novel and important comparison of different methods for variable selection in nested models.

Weaknesses:<br /> - Does not (yet) examine effect sizes<br /> - Does not motivate/explain key methods clearly enough in the main text.

General Comments:<br /> 1. My first general comment is that the paper in its current form focuses on the "null hypothesis significance testing" (NHST) paradigm. That is, it is focused on binary tests about what variables to include (or not include) in a regression model, and the false-positive rates of such tests. However, the broader statistics community has recently seen a shift away from NHST and towards a statistical reporting paradigm focused on effect sizes. See for example:<br /> - "Scientists rise up against statistical significance". Nature, March 2019.<br /> - Moving to a World Beyond "p < 0.05". RL Wasserstein, AL Schirm, NA Lazar. The American Statistician, 2019.

In light of this shift, I think the paper would be substantially strengthened if the authors could add a description of effect sizes for the statistical procedures they consider. Thus, for example, in cases where a procedure selects the wrong model (e.g., by selecting a variable that should not be included), how large is the inferred regression weight, and/or how large is the improvement in prediction performance (e.g. test log-likelihood) from including the erroneous regressor? How strong is the position tuning ascribed to a MEC cell that is inappropriately classified as having position tuning under one of the sub-optimal procedures? (Figure 7 shows some example place maps, but it would be nice to see a more thorough and rigorous analysis).

My suspicion would be that even when the hypothesis test gives a false positive, the effect sizes tend to remain small... but it is certainly possible that I'm mistaken, or that inferred effect sizes are more accurate for some procedures than others.

2. My only other major criticism relates to clarity and readability: in particular, the various procedures discussed in the paper ("forward selection", "maxT correction", "permutation test with cyclic shifts") are not clearly explained in the main paper, but are relegated to the Methods. Although I think it is useful to keep many of the mathematical details in the methods section, it would benefit the reader to have a general and intuitive explanation of the key methods within the flow of the main paper. The first paragraph of the Results section is particularly underdeveloped and hard to read and could benefit from a substantial revision to introduce and motivate the terms and procedures more clearly. I would recommend moving much of the text from the Methods into the Results section, or at the very least adding a paragraph describing the general idea/motivation for each method in Results.

Reviewer #2 (Public Review):

This paper considers methods for statistical analysis of autocorrelated neural recording time series: an important question for neuroscience, that is underappreciated in the community. The paper makes a valuable contribution to this topic by comparing methods based on cross-validation and cyclic shift on simulated grid-cell data. My main suggestions regard clarity, which would greatly benefit from a more didactic approach: explaining the methods compared to the main text and providing more explanatory figures. But there are also some additional analyses that would strengthen the paper.

There are two ways to build support for the validity of a statistical method: by mathematically proving that it is valid, or by empirically verifying it with simulated data where the correct answer is known. A mathematical proof removes all doubt to validity but empirical validation can still be useful even without proof, as it demonstrates that the method works in at least some circumstances. For empirical validation to be most convincing, it helps to also show some situations where the method doesn't work, ideally by varying a continuous parameter that reliably moves the simulation from a situation where it works to one where it doesn't. If the method works in all but extremely unrealistic cases, this builds confidence that it will work on real data.

The main conclusion of this paper's simulations is that the cyclic shift method most often detects valid correlations, while still not exceeding the false positive rate expected for a valid test. Readers may take this paper as indicating that the circular shift method is safe in all circumstances, but this is not correct. The authors acknowledge that circular shift can sometimes be invalid, and have made modifications to mitigate the problem. But there is neither a mathematical proof that these mitigations work, nor an analysis of the circumstances under which they succeed and fail. I doubt a formal proof is possible since there are likely situations in which even the new methods give false positive results. So the authors should include an empirical test of their modified circular shift method as compared to plain circular shift in various simulations. To gain confidence in the new method it is important to characterize the situations where both methods succeed; where the new method succeeds but traditional cyclic shift gives false positive errors; and situations in which both fail. If situations where the new method fails are so unrealistic that they would never occur in real data, we can have better confidence in the method.

The main contributions of the paper are the modifications to circular shifting and cross-validation that avoid problems of temporal contiguity, but these are only described in the Methods section. But this is a methods paper, so the description of the new methods should be in the main text, including explanatory figures currently in the Methods.

The introduction presents two problems that can occur in neural data: autocorrelation, and omitted variables. However, it is not clear that the current methods help with the problem of omitted variables. In fact, I don't see how any analysis method could solve the problem of omitted variables. If an experimenter observes a correlation between X and Y, there is no way to know this isn't because a third variable Z correlates with X and influences Y, without any effect of X on Y. It is generally impossible to prove causation without making randomized manipulations of one variable; although some methods claim to infer causality by observing all variables that could possibly have a causal effect, this is unlikely to occur in neuroscience. In any case, the problem of omitted variables seems irrelevant to the current study and could be removed.

The list of analysis methods mentioned in the first paragraph of the introduction (eg TDA, LVM) seems irrelevant: it is not clear how the methods evaluated here would be used to assess the significance of those methods. Better to stick to a description of how correlations are difficult to detect in autocorrelated signals, which is what the current methods address.

Reviewer #3 (Public Review):

Summary:<br /> The authors consider various statistical testing frameworks for model selection in the context of neuronal tuning. They consider cross-validation as a baseline scheme, and show various corrections and modifications to existing cross-validation schemes together with the underlying data/sign shuffling procedures for finding null distributions. Through careful simulations, they show that some of these tests are expectedly too conservative or too optimistic, and show that a log-likelihood-based test statistic with a cyclic shift permutation test for obtaining null distribution and Bonferroni correction strikes the right balance between hits and false detection. They further apply these tests to calcium imaging data from the mouse entorhinal cortex to identify grid cells (i.e., cells for which position is selected as a relevant variable).

Strengths:<br /> The paper is very well written, easy to follow, and enjoyable to read. It addresses an important issue in modern neuroscience, which is drawing conclusions based on data with missing or (unaccounted for) auto-correlated covariates.

Weaknesses:<br /> The paper would benefit from including more rigorous theoretical justification on why some of the procedures examined here outperform the others. This could be done in a stylized example with a Gaussian linear model, for which some of the used statistics have well-known distributions.

Comparisons with false discovery rate (FDR) control, as a more appropriate measure of performance when dealing with many comparisons, would benefit the existing comparisons merely based on Bonferroni correction.

Including spiking history in the generalized linear models (GLMs) used in analyzing the mouse data could be beneficial, as existing literature points to the importance of spiking history as a relevant covariate.

Reviewer #1 (Public Review):

Summary:<br /> Zhu et al. set out to better understand the neural mechanisms underlying Drosophila larval escape behavior. The escape behavior is comprised of several sequenced movements, including a lateral roll motion followed by fast crawling. The authors specifically were looking to identify neurons important for the roll-to-crawl transition.

Strengths:<br /> This paper is clearly written. The experiments are logical and complementary. They support the author's main claim that SeIN128 is a type of descending neuron that is both necessary and sufficient to modulate the termination of rolling.

Weaknesses:<br /> -This manuscript is narrowly focused on Drosophila larval escape behavior. It would be more accessible to a broader audience if this work was put into a larger context of descending control.<br /> -In general, the rigor is high. However, a few control experiments are missing.

Reviewer #2 (Public Review):

Summary:<br /> This study discovered a neural mechanism that serves as a switch from rolling to fast crawling behaviors in Drosophila larvae. It addressed important open questions of how neural circuits determine the sequence of locomotor behaviors and how animals switch from one behavior to another. Overall, its results support the conclusions. The experimental approaches should be described more clearly.

The escape behavior of Drosophila larvae includes rolling followed by fast crawling, where the neural mechanism of this sequence is unclear. The authors identified SeIN128, a group of descending neurons that facilitates rolling termination and shortens crawling latency. By investigating the EM connectome of larval CNS, they found that SeIN128 receives inputs from Basin-2 and A00c neurons, which are reported to facilitate rolling. SeIN128 makes reciprocal inhibitory synapses onto Basin-2 and A00c. Gad staining indicates that SeIN128 neurons are GABAergic, and inhibition of SeIN128 caused increased rolling probability and prolonged rolling. RNAi knockdown of GABA receptors in Basins further validated that SeIN128 inhibits Basins via GABAergic inputs. Lastly, the authors found that SeIN128 inhibits rolling induced by two types of Basin neurons, Basin-2 and Basin-4. Overall, SeIN128 forms a feedback inhibition ensemble that terminates rolling and shifts the animal to crawling.

Strengths:<br /> - The question (i.e., the neural circuitry of action selection) addressed by this study is important.<br /> - Larval and adult Drosophila is a powerful model system in neuroscience study, with rich genetic tools, diverse behaviors, and well-studied nervous systems. This study makes good use of them.<br /> - The experiments, analyses, and results are mostly rigorous and support the major claims. This study combined multiple innovative approaches, such as automated, machine-learning-based behavioral assays, EM reconstruction of larval CNS neurons, and genetic manipulation of specific neurons.

Weaknesses:<br /> - The description of methods and quantification for certain analyses are not clear or detailed enough for a comprehensive judgment of rigorousness, or for other scientists to repeat the experiments. This especially applies to the algorithm.<br /> - "Corkscrew-like rolling" is not an accurate term for larval rolling. The neuromuscular basis of rolling was recently studied by Cooney et. al., showing that rolling is the circumferential propagation of muscle activity where all segments contract similarly and synchronously.<br /> - The readability of the manuscript (text and figures) needs improvement, especially in making it understandable for a general audience. The addition of visual representations, simplifying the complex names of neurons, avoiding overall long sentences, and providing sufficient background introduction may help.

Reviewer #3 (Public Review):

Summary: Drosophila larvae exhibit characteristic escape behavior in response to a noxious stimulus. The underlying nociceptive circuit that regulates the temporal dynamics of escape behavior - bending, rolling, and crawling remains unclear. Using behavioral prototypes with optical stimulation and imaging, the authors show the function of descending neurons (SeIN128) in the termination of the rolling and subsequent initiation of the crawling behavior. The study further establishes the functional connectome of SeIN128, Basin-2, and A00c neurons, forming an inhibitory feedback circuit that regulates the rolling-escape sequences.

Strength: The study provides anatomical and functional evidence for temporal dynamics of escape behaviors in Drosophila larvae. Authors convincingly show the function of bilaterally descending neurons (previously identified SeIN128 neurons) in the transition of escape sequences. Based on the previous studies and functional connectome analysis, the study shows that SeIN128 neurons form a GABAergic feedback circuit with Basin-2, a second-order interneuron, and A00c, an ascending neuron downstream of Basin-2. Activation of SeIN128 neurons terminates the rolling by suppressing Basin-2 activity, facilitating subsequent rapid escape crawling. Thus, it establishes the function of feedback inhibition in temporal dynamics of escape behavior and contributes to a mechanistic understanding of the nociceptive circuits.

Weakness: The manuscript is written clearly; however, the presentation of the data needs to be improved for readability. The data and discussion establish the function of SeIN128 and Basin-2 in escape behavior, but the role of A00c neurons needs to be clarified.

Reviewer #1 (Public Review):

This valuable study demonstrates a novel mechanism by which implicit motor adaptation saturates for large visual errors in a principled normative Bayesian manner. Additionally, the study revealed two notable empirical findings: visual uncertainty increases for larger visual errors in the periphery, and proprioceptive shifts/implicit motor adaptation are non-monotonic, rather than ramp-like. This study is highly relevant for researchers in sensory cue integration and motor learning. However, I find some areas where statistical quantification is incomplete, and the contextualization of previous studies to be puzzling.

Issue #1: Contextualization of past studies.

While I agree that previous studies have focused on how sensory errors drive motor adaptation (e.g., Burge et al., 2008; Wei and Kording, 2009), I don't think the PReMo model was contextualized properly. Indeed, while PReMo should have adopted clearer language - given that proprioception (sensory) and kinaesthesia (perception) have been used interchangeably, something we now make clear in our new study (Tsay, Chandy, et al. 2023) - PReMo's central contribution is that a perceptual error drives implicit adaptation (see Abstract): the mismatch between the felt (perceived) and desired hand position. The current paper overlooks this contribution. I encourage the authors to contextualize PReMo's contribution more clearly throughout. Not mentioned in the current study, for example, PReMo accounts for the continuous changes in perceived hand position in Figure 4 (Figure 7 in the PReMo study).

There is no doubt that the current study provides important additional constraints on what determines perceived hand position: Firstly, it offers a normative Bayesian perspective in determining perceived hand position. PReMo suggests that perceived hand position is determined by integrating motor predictions with proprioception, then adding a proprioceptive shift; PEA formulates this as the optimal integration of these three inputs. Secondly, PReMo assumed visual uncertainty to remain constant for different visual errors; PEA suggests that visual uncertainty ought to increase (but see Issue #2).

Issue #2: Failed replication of previous results on the effect of visual uncertainty.

2a. A key finding of this paper is that visual uncertainty linearly increases in the periphery; a constraint crucial for explaining the non-monotonicity in implicit adaptation. One notable methodological deviation from previous studies is the requirement to fixate on the target: Notably, in the current experiments, participants were asked to fixate on the target, a constraint not imposed in previous studies. In a free-viewing environment, visual uncertainty may not attenuate as fast, and hence, implicit adaptation does not attenuate as quickly as that revealed in the current design with larger visual errors. Seems like this current fixation design, while important, needs to be properly contextualized considering how it may not represent most implicit adaptation experiments.

2b. Moreover, the current results - visual uncertainty attenuates implicit adaptation in response to large, but not small, visual errors - deviates from several past studies that have shown that visual uncertainty attenuates implicit adaptation to small, but not large, visual errors (Tsay, Avraham, et al. 2021; Makino, Hayashi, and Nozaki, n.d.; Shyr and Joshi 2023). What do the authors attribute this empirical difference to? Would this free-viewing environment also result in the opposite pattern in the effect of visual uncertainty on implicit adaptation for small and large visual errors?

2c. In the current study, the measure of visual uncertainty might be inflated by brief presentation times of comparison and referent visual stimuli (only 150 ms; our previous study allowed for a 500 ms viewing time to make sure participants see the comparison stimuli). Relatedly, there are some individuals whose visual uncertainty is greater than 20 degrees standard deviation. This seems very large, and less likely in a free-viewing environment.

2d. One important confound between clear and uncertain (blurred) visual conditions is the number of cursors on the screen. The number of cursors may have an attenuating effect on implicit adaptation simply due to task-irrelevant attentional demands (Parvin et al. 2022), rather than that of visual uncertainty. Could the authors provide a figure showing these blurred stimuli (gaussian clouds) in the context of the experimental paradigm? Note that we addressed this confound in the past by comparing participants with and without low vision, where only one visual cursor is provided for both groups (Tsay, Tan, et al. 2023).

Issue #3: More methodological details are needed.

3a. It's unclear why, in Figure 4, PEA predicts an overshoot in terms of perceived hand position from the target. In PReMo, we specified a visual shift in the perceived target position, shifted towards the adapted hand position, which may result in overshooting of the perceived hand position with this target position. This visual shift phenomenon has been discovered in previous studies (e.g., (Simani, McGuire, and Sabes 2007)).

3b. The extent of implicit adaptation in Experiment 2, especially with smaller errors, is unclear. The implicit adaptation function seems to be still increasing, at least by visual inspection. Can the authors comment on this trend, and relatedly, show individual data points that help the reader appreciate the variability inherent to these data?

3c. The same participants were asked to return for multiple days/experiments. Given that the authors acknowledge potential session effects, with attenuation upon re-exposure to the same rotation (Avraham et al. 2021), how does re-exposure affect the current results? Could the authors provide clarity, perhaps a table, to show shared participants between experiments and provide evidence showing how session order may not be impacting results?

3d. The number of trials per experiment should be detailed more clearly in the Methods section (e.g., Exp 4). Moreover, could the authors please provide relevant code on how they implemented their computational models? This would aid in future implementation of these models in future work. I, for one, am enthusiastic to build on PEA.

3f. In addition to predicting a correlation between proprioceptive shift and implicit adaptation on a group level, both PReMo and PEA (but not causal inference) predict a correlation between individual differences in proprioceptive shift and proprioceptive uncertainty with the extent of implicit adaptation (Tsay, Kim, et al. 2021). Interestingly, shift and uncertainty are independent (see Figures 4F and 6C in Tsay et al, 2021). Does PEA also predict independence between shift and uncertainty? It seems like PEA does predict a correlation.

References:

Avraham, Guy, Ryan Morehead, Hyosub E. Kim, and Richard B. Ivry. 2021. "Reexposure to a Sensorimotor Perturbation Produces Opposite Effects on Explicit and Implicit Learning Processes." PLoS Biology 19 (3): e3001147.<br /> Makino, Yuto, Takuji Hayashi, and Daichi Nozaki. n.d. "Divisively Normalized Neuronal Processing of Uncertain Visual Feedback for Visuomotor Learning."<br /> Parvin, Darius E., Kristy V. Dang, Alissa R. Stover, Richard B. Ivry, and J. Ryan Morehead. 2022. "Implicit Adaptation Is Modulated by the Relevance of Feedback." BioRxiv. https://doi.org/10.1101/2022.01.19.476924.<br /> Shyr, Megan C., and Sanjay S. Joshi. 2023. "A Case Study of the Validity of Web-Based Visuomotor Rotation Experiments." Journal of Cognitive Neuroscience, October, 1-24.<br /> Simani, M. C., L. M. M. McGuire, and P. N. Sabes. 2007. "Visual-Shift Adaptation Is Composed of Separable Sensory and Task-Dependent Effects." Journal of Neurophysiology 98 (5): 2827-41.<br /> Tsay, Jonathan S., Guy Avraham, Hyosub E. Kim, Darius E. Parvin, Zixuan Wang, and Richard B. Ivry. 2021. "The Effect of Visual Uncertainty on Implicit Motor Adaptation." Journal of Neurophysiology 125 (1): 12-22.<br /> Tsay, Jonathan S., Anisha M. Chandy, Romeo Chua, R. Chris Miall, Jonathan Cole, Alessandro Farnè, Richard B. Ivry, and Fabrice R. Sarlegna. 2023. "Implicit Motor Adaptation and Perceived Hand Position without Proprioception: A Kinesthetic Error May Be Derived from Efferent Signals." BioRxiv. https://doi.org/10.1101/2023.01.19.524726.<br /> Tsay, Jonathan S., Hyosub E. Kim, Darius E. Parvin, Alissa R. Stover, and Richard B. Ivry. 2021. "Individual Differences in Proprioception Predict the Extent of Implicit Sensorimotor Adaptation." Journal of Neurophysiology, March. https://doi.org/10.1152/jn.00585.2020.<br /> Tsay, Jonathan S., Steven Tan, Marlena Chu, Richard B. Ivry, and Emily A. Cooper. 2023. "Low Vision Impairs Implicit Sensorimotor Adaptation in Response to Small Errors, but Not Large Errors." Journal of Cognitive Neuroscience, January, 1-13.

Reviewer #2 (Public Review):

Summary:<br /> The authors present the Perceptual Error Adaptation (PEA) model, a computational approach offering a unified explanation for behavioral results that are inconsistent with standard state-space models. Beginning with the conventional state-space framework, the paper introduces two innovative concepts. Firstly, errors are calculated based on the perceived hand position, determined through Bayesian integration of visual, proprioceptive, and predictive cues. Secondly, the model accounts for the eccentricity of vision, proposing that the uncertainty of cursor position increases with distance from the fixation point. This elegantly simple model, with minimal free parameters, effectively explains the observed plateau in motor adaptation under the implicit motor adaptation paradigm using the error-clamp method. Furthermore, the authors experimentally manipulate visual cursor uncertainty, a method established in visuomotor studies, to provide causal evidence. Their results show that the adaptation rate correlates with perturbation sizes and visual noise, uniquely explained by the PEA model and not by previous models. Therefore, the study convincingly demonstrates that implicit motor adaptation is a process of Bayesian cue integration

Strengths:<br /> In the past decade, numerous perplexing results in visuomotor rotation tasks have questioned their underlying mechanisms. Prior models have individually addressed aspects like aiming strategies, motor adaptation plateaus, and sensory recalibration effects. However, a unified model encapsulating these phenomena with a simple computational principle was lacking. This paper addresses this gap with a robust Bayesian integration-based model. Its strength lies in two fundamental assumptions: motor adaptation's influence by visual eccentricity, a well-established vision science concept, and sensory estimation through Bayesian integration. By merging these well-founded principles, the authors elucidate previously incongruent and diverse results with an error-based update model. The incorporation of cursor feedback noise manipulation provides causal evidence for their model. The use of eye-tracking in their experimental design, and the analysis of adaptation studies based on estimated eccentricity, are particularly elegant. This paper makes a significant contribution to visuomotor learning research.

Weaknesses:<br /> The paper provides a comprehensive account of visuomotor rotation paradigms, addressing incongruent behavioral results with a solid Bayesian integration model. However, its focus is narrowly confined to visuomotor rotation, leaving its applicability to broader motor learning paradigms, such as force field adaptation, saccadic adaptation, and de novo learning paradigms, uncertain. The paper's impact on the broader fields of neuroscience and cognitive science may be limited due to this specificity. While the paper excellently demonstrates that specific behavioral results in visuomotor rotation can be explained by Bayesian integration, a general computational principle, its contributions to other motor learning paradigms remain to be explored. The paper would benefit from a discussion on the model's generality and its limitations, particularly in relation to the undercompensating effects in other motor learning paradigms.

Reviewer #3 (Public Review):

Summary<br /> In this paper, the authors model motor adaptation as a Bayesian process that combines visual uncertainty about the error feedback, uncertainty about proprioceptive sense of hand position, and uncertainty of predicted (=planned) hand movement with a learning and retention rate as used in state space models. The model is built with results from several experiments presented in the paper and is compared with the PReMo model (Tsay, Kim, et al., 2022) as well as a cue combination model (Wei & Körding, 2009). The model and experiments demonstrate the role of visual uncertainty about error feedback in implicit adaptation.

In the introduction, the authors notice that implicit adaptation (as measured in error-clamp-based paradigms) does not saturate at larger perturbations, but decreases again (e.g. Moorehead et al., 2017 shows no adaptation at 135{degree sign} and 175{degree sign} perturbations). They hypothesized that visual uncertainty about cursor position increases with larger perturbations since the cursor is further from the fixated target. This could decrease the importance assigned to visual feedback which could explain lower asymptotes.

The authors characterize visual uncertainty for 3 rotation sizes in the first experiment, and while this experiment could be improved, it is probably sufficient for the current purposes. Then the authors present a second experiment where adaptation to 7 clamped errors is tested in different groups of participants. The models' visual uncertainty is set using a linear fit to the results from experiment 1, and the remaining 4 parameters are then fit to this second data set. The 4 parameters are 1) proprioceptive uncertainty, 2) uncertainty about the predicted hand position, 3) a learning rate, and 4) a retention rate. The authors' Perceptual Error Adaptation model ("PEA") predicts asymptotic levels of implicit adaptation much better than both the PReMo model (Tsay, Kim et al., 2022), which predicts saturated asymptotes, or a causal inference model (Wei & Körding, 2007) which predicts no adaptation for larger rotations. In a third experiment, the authors test their model's predictions about proprioceptive recalibration, but unfortunately, compare their data with an unsuitable other data set. Finally, the authors conduct a fourth experiment where they put their model to the test. They measure implicit adaptation with increased visual uncertainty, by adding blur to the cursor, and the results are again better in line with their model (predicting overall lower adaptation) than with the PReMo model (predicting equal saturation but at larger perturbations) or a causal inference model (predicting equal peak adaptation, but shifted to larger rotations). In particular, the model fits experiment 2 and the results from experiment 4 show that the core idea of the model has merit: increased visual uncertainty about errors dampens implicit adaptation.

Strengths<br /> In this study, the authors propose a Perceptual Error Adaptation model ("PEA") and the work combines various ideas from the field of cue combination, Bayesian methods, and new data sets, collected in four experiments using various techniques that test very different components of the model. The central component of visual uncertainty is assessed in the first experiment. The model uses 4 other parameters to explain implicit adaptation. These parameters are 1) learning and 2) retention rate, as used in popular state space models, and the uncertainty (variance) of 3) predicted and 4) proprioceptive hand position. In particular, the authors observe that asymptotes for implicit learning do not saturate, as claimed before, but decrease again when rotations are very large and that this may have to do with visual uncertainty (e.g. Tsay et al., 2021, J Neurophysiol 125, 12-22). The final experiment confirms predictions of the fitted model about what happens when visual uncertainty is increased (overall decrease of adaptation). By incorporating visual uncertainty depending on retinal eccentricity, the predictions of the PEA model for very large perturbations are notably different from and better than, the predictions of the two other models it is compared to. That is, the paper provides strong support for the idea that visual uncertainty of errors matters for implicit adaptation.

Weaknesses<br /> Although the authors don't say this, the "concave" function that shows that adaptation does not saturate for larger rotations has been shown before, including in papers cited in this manuscript.

The first experiment, measuring visual uncertainty for several rotation sizes in error-clamped paradigms has several shortcomings, but these might not be so large as to invalidate the model or the findings in the rest of the manuscript. There are two main issues we highlight here. First, the data is not presented in units that allow comparison with vision science literature. Second, the 1 second delay between the movement endpoint and the disappearance of the cursor, and the presentation of the reference marker, may have led to substantial degradation of the visual memory of the cursor endpoint. That is, the experiment could be overestimating the visual uncertainty during implicit adaptation.

The paper's third experiment relies to a large degree on reproducing patterns found in one particular paper, where the reported hand positions - as a measure of proprioceptive sense of hand position - are given and plotted relative to an ever-present visual target, rather than relative to the actual hand position. That is, 1) since participants actively move to a visual target, the reported hand positions do not reflect proprioception, but mostly the remembered position of the target participants were trying to move to, and 2) if the reports are converted to a difference between the real and reported hand position (rather than the difference between the target and the report), those would be on the order of ~20{degree sign} which is roughly two times larger than any previously reported proprioceptive recalibration, and an order of magnitude larger than what the authors themselves find (1-2{degree sign}) and what their model predicts. Experiment 3 is perhaps not crucial to the paper, but it nicely provides support for the idea that proprioceptive recalibration can occur with error-clamped feedback.

Perhaps the largest caveat to the study is that it assumes that people do not look at the only error feedback available to them (and can explicitly suppress learning from it). This was probably true in the experiments used in the manuscript, but unlikely to be the case in most of the cited literature. Ignoring errors and suppressing adaptation would also be a disastrous strategy to use in the real world, such that our brains may not be very good at this. So the question remains to what degree - if any - the ideas behind the model generalize to experiments without fixation control, and more importantly, to real-life situations.

Specific comments:<br /> A small part of the manuscript relies on replicating or modeling the proprioceptive recalibration in a study we think does NOT measure proprioceptive recalibration (Tsay, Parvin & Ivry, JNP, 2020). In this study, participants reached for a visual target with a clamped cursor, and at the end of the reach were asked to indicate where they thought their hand was. The responses fell very close to the visual target both before and after the perturbation was introduced. This means that the difference between the actual hand position, and the reported/felt hand position gets very large as soon as the perturbation is introduced. That is, proprioceptive recalibration would necessarily have roughly the same magnitude as the adaptation displayed by participants. That would be several times larger than those found in studies where proprioceptive recalibration is measured without a visual anchor. The data is plotted in a way that makes it seem like the proprioceptive recalibration is very small, as they plot the responses relative to the visual target, and not the discrepancy between the actual and reported hand position. It seems to us that this study mostly measures short-term visual memory (of the target location). What is astounding about this study is that the responses change over time to begin with, even if only by a tiny amount. Perhaps this indicates some malleability of the visual system, but it is hard to say for sure.

Regardless, the results of that study do not form a solid basis for the current work and they should be removed. We would recommend making use of the dataset from the same authors, who improved their methods for measuring proprioception shifts just a year later (Tsay, Kim, Parvin, Stover, and Ivry, JNP, 2021). Although here the proprioceptive shifts during error-clamp adaptation (Exp 2) were tiny, and not quite significant (p<0.08), the reports are relative to the actual location of the passively placed unseen hand, measured in trials separate from those with reach adaptation and therefore there is no visual target to anchor their estimates to.

Experiment 1 measures visual uncertainty with increased rotation size. The authors cite relevant work on this topic (Levi & Klein etc) which has found a linear increase in uncertainty of the position of more and more eccentrically displayed stimuli.

First, this is a question where the reported stimuli and effects could greatly benefit from comparisons with the literature in vision science, and the results might even inform it. In order for that to happen, the units for the reported stimuli and effects should (also) be degrees of visual angle (dva).

As far as we know, all previous work has investigated static stimuli, where with moving stimuli, position information from several parts of the visual field are likely integrated over time in a final estimate of position at the end of the trajectory (a Kalman filter type process perhaps). As far as we know, there are no studies in vision science on the uncertainty of the endpoint of moving stimuli. So we think that the experiment is necessary for this study, but there are some areas where it could be improved.

Then, the linear fit is done in the space of the rotation size, but not in the space of eccentricity relative to fixation, and these do not necessarily map onto each other linearly. If we assume that the eye-tracker and the screen were at the closest distance the manufacturer reports it to work accurately at (45 cm), we would get the largest distances the endpoints are away from fixation in dva. Based on that assumed distance between the participant and monitor, we converted the rotation angles to distances between fixation and the cursor endpoint in degrees visual angle: 0.88, 3.5, and 13.25 dva (ignoring screen curvature, or the absence of it). The ratio between the perturbation angle and retinal distance to the endpoint is roughly 0.221, 0.221, and 0.207 if the minimum distance is indeed used - which is probably fine in this case. But still, it would be better to do fit in the relevant perceptual coordinate system.

The first distance (4 deg rotation; 0.88 dva offset between fixation and stimulus) is so close to fixation (even at the assumed shortest distance between eye and screen) that it can be considered foveal and falls within the range of noise of eye-trackers + that of the eye for fixating. There should be no uncertainty on or that close to the fovea. The variability in the data is likely just measurement noise. This also means that a linear fit will almost always go through this point, somewhat skewing the results toward linearity. The advantage is that the estimate of the intercept (measurement noise) is going to be very good. Unfortunately, there are only 2 other points measured, which (if used without the closest point) will always support a linear fit. Therefore, the experiment does not seem suitable to test linearity, only to characterize it, which might be sufficient for the current purposes. We'd understand if the effort to do a test of linearity using many more rotations requires too much effort. But then it should be made much clearer that the experiment assumes linearity and only serves to characterize the assumed linearity.

Final comment after the consultation session:<br /> There were a lot of discussions about the actual interpretation of the behavioral data from this paper with regards to past papers (Tsay et al. 2020 or 2021), and how it matches the different variables of the model. The data from Tsay 2020 combined both proprioceptive information (Xp) and prediction about hand position (Xu) because it involves active movements. On the other hand, Tsay et al. 2021 is based on passive movements and could provide a better measure of Xp alone. We would encourage you to clarify how each of the variables used in the model is mapped onto the outcomes of the cited behavioral experiments.

The reviewers discussed this point extensively during the consultation process. The results reported in the Tsay 2020 study reflect both proprioception and prediction. However, having a visual target contributes more than just prediction, it is likely an anchor in the workspace that draws the response to it. Such that the report is dominated by short-term visual memory of the target (which is not part of the model). However, in the current Exp 3, as in most other work investigating proprioception, this is calculated relative to the actual direction.

The solution is fairly simple. In Experiment 3 in the current study, Xp is measured relative to the hand without any visual anchors drawing responses, and this is also consistent with the reference used in the Tsay et al 2021 study and from many studies in the lab of D. Henriques (none of which also have any visual reach target when measuring proprioceptive estimates). So we suggest using a different data set that also measures Xp without any other influences, such as the data from Tsay et al 2021 instead.

These issues with the data are not superficial and can not be solved within the model. Data with correctly measured biases (relative to the hand) that are not dominated by irrelevant visual attractors would actually be informative about the validity of the PEA model. Dr. Tsay has so much other that we recommend using a more to-the-point data set that could actually validate the PEA model.

Reviewer #2 (Public Review):

Summary:<br /> This study seeks to understand the connection between protein sequence and function in disordered regions enriched in polar amino acids (specifically Q, N, S and T). While the authors suggest that specific motifs facilitate protein-enhancing activities, their findings are correlative, and the evidence is incomplete. Similarly, the authors propose that the re-assignment of stop codons to glutamine-encoding codons underlies the greater user of glutamine in a subset of ciliates, but again, the conclusions here are, at best, correlative. The authors perform extensive bioinformatic analysis, with detailed (albeit somewhat ad hoc) discussion on a number of proteins. Overall, the results presented here are interesting but are unable to exclude competing hypotheses.

Strengths:<br /> Following up on previous work, the authors wish to uncover a mechanism associated with poly-Q and SCD motifs explaining proposed protein expression-enhancing activities. They note that these motifs often occur IDRs and hypothesize that structural plasticity could be capitalized upon as a mechanism of diversification in evolution. To investigate this further, they employ bioinformatics to investigate the sequence features of proteomes of 27 eukaryotes. They deepen their sequence space exploration uncovering sub-phylum-specific features associated with species in which a stop-codon substitution has occurred. The authors propose this stop-codon substitution underlies an expansion of ploy-Q repeats and increased glutamine distribution.

Weaknesses:<br /> The authors were provided with a series of suggested changes to improve clarity, and a series of concerns raised. Some of these have been addressed but many have not. At this point, I do not see my role as telling the authors how to re-write their manuscript, but many of the concerns raised in my original review remain, and the authors have done little to allay those concerns in their revisions.

Reviewer #2 (Public Review):

The authors have greatly expanded their helpful hippocampome.org resource for the community regarding hippocampal cell types and their interactions from many perspectives. The many updates from v1.0 to v1.12 are nicely summarized in Table 1.

With v2.0, they now achieve the original vision of their project - to enable data-driven spiking neural network simulations of rodent hippocampal circuits. This work thus moves hippocampome.org from not only being a useful resource but also being able to launch simulations in which the models have direct links to the experimental literature. This will not only be of interest to the vast hippocampal community, but also to the diverse computational neuroscience community as theoretical models can potentially be "experimentally tested" with v2.0 to allow theoretical insights to be more biologically applicable.

Reviewer #3 (Public Review):

Summary:

The authors aim to provide a multidisciplinary resource on the structural and physiological organization of the hippocampal system and make the available experimental data available for further theoretical work, providing tools to do so in a very flexible and user-friendly way. Since this is a new version of an already existing data-resource, the authors certainly reach their aim and fulfil expectations that the reader might have. The content of the database is as good as the original data, collected from the published knowledge-database, sometimes with help of the original authors, and the overall quality depends further on how the data are curated by the team of authors and many others who helped them. That process is briefly described and more details are available in descriptions of previous versions and on the website. The data extraction, examples of how data can be used and the part on attempts to model the hippocampus are exiting and open doors to new and exciting research opportunities.

Strengths:

Excellent description with many outlined opportunities. Nicely illustrated and inviting to explore the online database. The database itself is easy to navigate and to access relevant information, allowing to do further research on the available data.

Weaknesses:

The figures are complex, containing a heavy information load. One needs some general knowlegde of the system in order to grasp the enormous potential of what is provided.

Reviewer #1 (Public Review):

The authors investigate the function of the PTB domain containing adaptor protein Numb in skeletal muscle structure and function. In particular, the effects of reduced Numb expression in aging muscle is proposed as a mechanism for reduced contractile function associated with sarcopenia. Using ex-vivo analysis of conditional Numb and Numblike knockout muscle the authors demonstrate that loss of Numb but not the related Numblike gene expression perturbs muscle force generation. In order to explore the molecular mechanisms involved, Numb interacting proteins were identified in C2C12 cell cultured myotubes by immunoprecipitation and LC-MS/MS. The authors identify Septin 7 as well as Septin 2, 9 and 10 as a Numb binding proteins and demonstrate that loss of Numb/Numblike in myofibers causes changes in Septin 7 subcellular localization. Of note, whether additional septins form a complex or are also disrupted by Numb/Numblike loss remains an interesting area for further investigation. Additional investigation of the specificity and mapping of the Numb-Septin 7 (or another Septin) interaction would be of interest and provide an approach for future studies to demonstrate the biological relevance and specificity of the Numb-Septin 7 interaction in skeletal muscle

Reviewer #2 (Public Review):

Summary:

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

Strengths:

Straight-forward yet elegant design to help determine the important role the Numb has in skeletal muscle.

Weaknesses:

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

Reviewer #1 (Public Review):

In this manuscript, Davidsen and coworkers describe the development of a novel aspartate biosensor jAspSNFR3. This collaborative work supports and complements what was reported in a recent preprint by Hellweg et al., (bioRxiv.; doi: 10.1101/2023.05.04.537313). In both studies, the newly engineered aspartate sensor was developed from the same glutamate biosensor previously developed by the authors of this manuscript. This coincidence is not casual but is the result of the need to find tools capable of measuring aspartate levels in vivo. Therefore, it is undoubtedly a relevant and timely work carried out by groups experienced in aspartate metabolism and in the generation of metabolite biosensors.

Reviewer #2 (Public Review):

Summary: To create a robust and specific fluorescent sensor for aspartate.

Strengths: Good quality characterisation in a range of environments and experimental conditions.

Weaknesses: Sensor basically identical to iGluSnFR3, but nevertheless useful and specific. The results support the conclusions, and the paper is very straightforward. I think the work will be useful to people working on the effects of free aspartate in biology and given it is basically iGluSnFR3, which is widely used, should be very reproducible and reliable.

Other context - it is a good quality study, although seems to be somewhat incremental.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, Davidsen and collaborators introduce jAspSnFR3, a new version of aspartate biosensor derived from iGluSnFR3, that allows to monitor in real-time aspartate levels in cultured cells. A selective amino acids substitution was applied in a key region of the template to switch its specificity from glutamate to aspartate. The jAspSnFR3 does not respond to other tested metabolites and performs well, is not toxic for cultured cells, and is not affected by temperature ensuring the possibility of using this tool in tissues physiologically more relevant. The high affinity for aspartate (KD=50 uM) allowed the authors to measure fluctuations of this amino acid in the physiological range. Different strategies were used to bring aspartate to the minimal level. Finally, the authors used jAspSnFR3 to estimate the intracellular aspartate concentration.

Strengths:<br /> One of the highlights of the manuscript was a treatment with asparagine during glutamine starvation. Although didn`t corroborate the essentiality of asparagine in glutamine depletion, the measurement of aspartate during this supplementation is a glimpse of how useful this sensor can be.

Weaknesses:<br /> Although this is a well-performed study, I have some comments for the authors to address:<br /> 1-A red tag version of the sensor (jAspSnFR3-mRuby3) was generated for normalization purposes, with this the authors plan to correct GFP signal from expression and movement artifacts. I naturally interpret "movement artifacts" as those generated by variations in cell volume and focal plane during time-lapse experiments. However, it was mentioned that jAspSnFR3-mRuby3 included a histidine tag that may induce a non-specific effect (responses to the treatment with some amino acids). This suggests that a version without the tag needs to be generated and that an alternative design needs to be set for normalization purposes. A nuclear-localized RFP was expressed in a second attempt to incorporate RFP as a normalization signal. Here the cell lines that express both signals (sensor and RFP) were generated by independent lentiviral transductions (insertions). Unless the number of insertions for each construct is known, this approach will not ensure an equimolar expression of both proteins (sensor and RFP). In this scenario is not clear how the nuclear expression of RFP will help the correction by expression or monitor changes in cell volume. The authors may be interested in attempting a bicistronic system to express both the sensor and RFP.<br /> 2-The authors were interested in establishing the temporal dynamics of aspartate depletion by genetics and pharmaceutical means. For the inhibition of mitochondrial complex I rotenone and metformin were used. Although the assays are clearly showing aspartate depletion the report of cell viability is missing. Considering that glutamine deprivation induces arrest in cell proliferation, I think will be important to know the conditions of the cell cultures after 60 hours of treatment with such inhibitors.<br /> 3-The pH sensitivity was checked in vitro with jAspSnFR3-mRuby3 and the sensor reported suitable for measurements at physiological pH. It would be an opportunity to revisit the analysis for pH sensitivity in cultured cells using an untagged version of jAspSnFR3 coupled, for example, to a sensor for pH.<br /> 4-While the authors take an interesting approach to measuring intracellular aspartate concentration, it will be highly desirable if a calibration protocol can be designed for this sensor. Clearly, glutamine depletion grants a minimal ("zero") aspartate concentration. However, having a more dynamic way for calibration will facilitate the introduction of this tool for metabolism studies. This may be achieved by incorporating a cultured cell that already expresses the transporter or by ectopic expression in the cells that have already been used.

Reviewer #1 (Public Review):

Summary:

In this work the authors provide evidence to show that an increase in Kv7 channels in hilar mossy cells of Fmr1 knock out mice results in a marked decrease in their excitability. The reduction in excitatory drive onto local hilar interneurons produces an increased excitation/inhibition ratio in granule cells. Inhibiting Kv7 channels can help normalize the excitatory drive in this circuit, suggesting that they may represent a viable target for targeted therapeutics for fragile-x syndrome.

Strengths:

The work is supported by a compelling and thorough set of electrophysiological studies. The authors do an excellent job of analysing their data and present a very complete data set.

Weaknesses:

There are no significant weaknesses in the experimental work, however the complexity of the data presentation and the lack of a schematic showing the organizational framework of this circuit make the data less accessible to non-experts in the field. I highly encourage a graphical abstract and network diagram to help individuals understand the implications of this work.

The work is important as it identifies a unique regional and cell specific abnormality in Fmr1 KO mice, showing how the loss of one gene can result in region specific changes in brain circuits.

Reviewer #2 (Public Review):

Summary:

Deng et al. investigate, for the first time to my knowledge, the role that hippocampal dentate gyrus mossy cells play in Fragile X Syndrome. They provide compelling evidence that, in slice preparations from Fmr1 knockout mice, mossy cells are hypoactive due to increased Kv7 function whereas granule cells are hyperactive compared to slices from wild-type mice. They provide strong evidence that weakness of mossy cell-interneuron connections contribute to granule cell hyperexcitability, despite converse adaptations to mossy cell inputs. The authors show that application of the Kv7 inhibitor XE991 is able to rescue granule cell hyperexcitability back to wild-type baseline, supporting the overall conclusion that inhibition of Kv7 in the dentate may be a potential therapeutic approach for Fragile X Syndrome.

Strengths:

Thorough electrophysiological characterization of mossy cells in Fmr1 knockout mice, a novel finding.

Their electrophysiological approach is quite rigorous: patched different neuron types (GC, MC, INs) one at a time within the dentate gyrus in FMR1 KO and WT, with and without 'circuit blockade' by pharmacologically inhibiting neurotransmission. This allows the most detailed characterization possible of passive membrane/intrinsic cell differences in dentate gyrus of Fmr1 knockout mice.

Provide several examples showing the use of Kv7 inhibitor XE991 is able to rescue excitability of granule cell circuit in Fmr1 knockout mice (AP firing in intact circuit, postsynaptic current recordings, theta-gamma coupling stimulation)

Weaknesses:

Previously identified weaknesses have been addressed.

Reviewer #3 (Public Review):

The first part of the review was prepared after the first submission of the paper. After this, the authors made several changes in the manuscript. These changes are assessed at the end of the review.

First part:

The paper by Deng, Kumar, Cavalli, Klyachko describe that, unlike in other cell types, loss of Fmr1 decreases the excitability of hippocampal mossy cells due to up-regulation of Kv7 currents. They also show evidence that while muting mossy cells appears to be a compensatory mechanism, it contribute to the higher activity of the dentate gyrus, because the removal of mossy cell output alleviate the inhibition of dentate principal cells. This may be important for the patho-mechanism in Fragile X syndrome caused by the loss of Fmr1.

These experiments were carefully designed, and the results are presented ‎in a very logical, insightful and self-explanatory way. Therefore, this paper represents strong evidences for the claims of the authors. In the current state of the manuscript there are only a few points that need additional explanation.

One of the results, that is shown in the supplementary dataset, does not fit to the main conclusions. Changes in the mEPSC frequency suggest that in addition to the proposed network effects, there are additional changes in the synaptic machinery or synapse number that are independent of the actual activity of the neurons. Since the differences of the mEPSC and sEPSC frequencies are similar and because only the latter can signal network effects, while the former is typically interpreted as a presynaptic change, it cannot be claimed that sEPSC frequency changes are due to the hypo-excitability of mossy cells.

An apparent technical issue may imply a second weak point in the interpretation of the results. Because the IPSCs in the PP stimulation experiments (Fig8) start within a few milliseconds, it is unlikely that its first ‎components originate from the PP-GC-MC-IN feedforward inhibitory circuit. The involvement of this circuit and MCs in the Kv7-dependent excitability changes is the main implication of the results of this paper. But this feedforward inhibition requires three consecutive synaptic steps and EPSP-AP couplings, each of them lasting for at least 1ms + 2-5ms. Therefore, the inhibition via the PP-GC-MC-IN circuit can be only seen from 10-20ms after PP stimulation. The earlier components of the cPSCs should originate from other circuit elements that are not related to the rest of the paper. Therefore, more isolated measurements on the cPSC recordings are needed ‎which consider only the later phase of the IPSCs. This can be either a measurement on the decay phase or a pharmacological manipulation that selectively enhance/inhibit a specific component of the proposed circuit.

I suggest refraining from the conclusions saying "‎MCs provide at least ~51% of the excitatory drive onto interneurons in WT and ~41% in KO mice", because too many factors (eg. IN celll types, slice condition, synaptic reliability) are not accounted for these actual numbers, and these values are not necessary for the general observation of the paper.

There are additional minor issues about the presentation of the results that are explained in the private recommendation for the Authors.

Review after the revision:

The authors accepted my suggestions and made changes in the manuscript to address my point about the interpretation of the mEPSC changes.<br /> The second point was related to the interpretation of the stimulation evoked multisynaptic compound responses. Specifically, the IPSC components in the PP stimulation experiments start within a few milliseconds, and I pointed out that it is unlikely that its first ‎components originate from the PP-GC-MC-IN feedforward inhibitory circuit. The authors provided strong arguments for the interpretation of these compound responses in their reply and the conclusions are consistent with these complex results.

Additional minor issues were fully addressed.

I still think that this is a strong paper that provides new insights into the mechanisms of Fragile X syndrome at the level of single neurons and local network. The extensive series of experiments convincingly support the main findings that in addition to contributing to the underlying mechanisms of this disease also highlight how delicately neuronal activity is balanced even in constrained conditions.

Reviewer #1 (Public Review):

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

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

Weakness:<br /> The authors illustrate that all orangutan individuals sampled, modern and fossil, show a considerable amount of isotopic variation between and within their teeth. Some of this variation is clearly associated with isotopic shifts in precipitation, but some will also be linked to the variation in oxygen isotopes within the forest itself and the many plant foods it produces for the orangutan. In the future, the systematic measurement of oxygen isotopes across orangutan food items, forest canopies and precipitation could help differentiate how much of the observed isotopic variation in teeth is indeed related to climatic shifts alone.

Reviewer #2 (Public Review):

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

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

Weaknesses:<br /> The study only examines six modern and six fossil orangutan individuals. Of those, only four modern individuals were samples across multiple molars.

Reviewer #1 (Public Review):

The article offers a comparative study between various methodologies to evaluate the abundance, richness, and diversity of insects from data obtained in a large-scale field experiment. The experiment is impressive in view of the number of locations, its spatial coverage, the number of instruments or methods used, and the data collected appears rich and worthy of multiple publications. The paper focuses on the validation of a novel approach based on optical sensors. These sensors collect the backscattered light from flying insects in their field of view and can retrieve the wingbeat frequency and the body-to-wing backscattering ratios.<br /> Unfortunately, the paper is poorly written and hard to read, with a lack of clear sections, and an overall confusing structure. The methods, metrics, and data analysis are not properly and thoroughly described, making it sometimes difficult to evaluate the validity of the approach.<br /> Most importantly, the methodology to retrieve the richness and diversity from optical sensors seems flawed. While the scope and scale of the experiment is valuable, I do not believe that this article supports the authors' claim. The main criticisms are described in more detail below.

1) The Material and Method section is poorly structured. The article focuses on a series of metrics to evaluate biodiversity from three independent methods: optical sensors, malaise traps, and net sweeping. The authors need to provide a clear and thorough description of what the metrics to be studied are, and how those metrics are evaluated for each method. While it is the main focus of the paper, the term "biodiversity metrics" is never properly defined, it is used in the singular form in both the title and abstract, then in its plural form in the rest of the paper, making the reader further doubt what exactly it means. It is then discussed using the correlation value retrieved when studying richness, so is the biodiversity metric the same as richness? Studying biodiversity remains a complex and sometimes contentious subject and this term, especially when measured by three different methods, is far from obvious. The term "community metrics" is defined as abundance, richness, and diversity; is that the same as biodiversity metrics? In any case, the method section should thoroughly describe how each of those metrics is calculated from the raw data collected by each method. This information is somewhat there, but in a very unorganized way, making it difficult to read. I would recommend organizing this section with multiple and clear sections: 1) describing the metrics that are meant to be studied, 2) the location, dates and time, type of crops, and other general information about the experiment, 3) description and methods around optical sensors, 4) description and methods around malaise traps, 5) description and methods around the sweeping. The last 3 sections should describe how it retrieves the previously defined metrics, potentially using equations.

2) Regarding the calculation of the body-to-wing ratio, sigma is described as a "signal" line 195, then is described as intensity counts in Figure 2; isn't it really the backscattering optical cross-section? It changes significantly over time during the signal, so how is one value of sigma calculated? Is it the average of the whole insect event? The maximum?

3) The "ecosystem services" paragraph is really confusing and needs to be rewritten.

4) Like for the method section, the result section should be structured around the comparison of each metric, abundance, richness, and diversity, or any other properly defined metrics described in the method, so that the result section is consistent with the method section.

5) The abundance is not correlated; interestingly, malaise traps and sweeping are even less correlated which further supports the claims by the authors that new and improved methods are needed. This part of the results could be further developed. A linear fit could be added to Figure 4.

6) Richness and diversity are the most problematic. Again, the method is poorly described, with pieces of explanation spread out throughout the paper, but my understanding is the following: the optical sensor retrieves two features from each insect signal, wbf, and BWR. Clustering is made using DBSCAN which has 2 parameters: minimum number of signals, and merge distance. It is important to note that these two parameters will greatly influence the number of clusters found by DBSCAN. The richness obtained by optical sensors is defined as the number of clusters and the diversity is evaluated from it as well. Hence, both diversity and richness are greatly dependent on the chosen parameters. The DBSCAN parameters are chosen by maximizing the Spearman correlation between richness obtained by the optical sensors and richness by the capture methods. I see a major problem here: if you optimize the parameters, that directly impact the retrieved diversity and richness by optical sensors, to have the best correlation with either the richness or diversity of the other methods, you will automatically create a correlation between the richness and diversity retrieved by the optical sensors and alternative methods. The p-value in Figure 6 does not represent the probability of the correlation hypothesis being false anymore, since the whole process is based on artificially forcing the correlation from the start.

7) In addition, the clustering method provides values higher than 80, which is quite unrealistic with just 2 features, wbf and BWR. It is clear from many studies using optical sensors that the features from optical sensors are subject to variability. Wbf has naturally some variances within the same species, not to mention temperature dependency. Backscattering cross sections will also heavily function on the insect's orientation (facing or sideways) while crossing the cone of light, and, even though it is a ratio, the collection efficiency of the instrument telescope and scattering efficiency of the target will be impacted by the position of the insects within the cone of light, which will also impact the variability on the BWR. While those features can still be used, obtaining 80 clusters from two variables with such statistical fluctuations is simply not credible. Additional features could help, such as the two wavelengths mentioned in the description of the optical sensor but are never mentioned again.

The conclusion then states that the study serves as the first field validation. I disagree; the abundance doesn't correlate, and the richness and diversity evaluations are flawed. While I do think there is great value in the work done by the authors through this impressive field experiment, and in general in their work toward the development of entomological optical sensors, I believe the data analysis and communication of the results do not support the conclusions drawn.

Reviewer #2 (Public Review):

Summary:

The manuscript by Rydhmer et al. proposes a new technology to survey insects. They deployed optical sensors in agricultural landscapes and contrast their results to those in classical malaise and sweep nets survey methodologies. They found the results of optical sensors to be comparable with classical survey methodologies. The authors discuss the pros and cons of their near-infrared sensor.

Strengths:<br /> Contrasting the results of optical sensors with those obtained with classical malaise and sweep nets was a clever idea.

Weaknesses:<br /> Maybe the first most important shortcoming is the lack of a larger question the new technology can help to answer. If the authors could frame their aims not only as a new tool to sample insects but maybe along the lines of a hypothesis to test in their (agricultural) field of research, this could be a more meaningful article.

The second more important shortcoming is the lack of more complex analyses. The authors seem to be so fixed on counts of abundance and species that they miss the opportunity to look for more complex patterns in their data. The addition of a simple analysis like an NMDS (to test composition changes) could improve the manuscript significantly.

The ecosystem process (granivory) assay is currently poorly contextualized and explained across the text; I was surprised to find this part in M&M without previous warning. It seems to me that adding this part could be a nice addition to the manuscript (see my comment above). But this needs to be explained better in all sections of the manuscript.

As I think that addressing my previous points will reshape the manuscript in important ways, I refrain from giving more specific details at this point. But there are some! Maybe only to mention that Figures 4 and 6 would benefit from individual regressions by crop and Figure 5 from adding results from optical sensors.

Reviewer #1 (Public Review):

Summary:<br /> The evolution of transporter specificity is currently unclear. Did solute carrier systems evolve independently in response to a cellular need to transport a specific metabolite in combination with a specific ion or counter metabolite, or did they evolve specificity from an ancestral protein that could transport and counter-transport most metabolites? The present study addresses this question by applying selective pressure to Saccharomyces cerevisiae and studying the mutational landscape of two well-characterised amino acid transporters. The data suggest that AA transporters likely evolved from an ancestral transporter and then specific sub-families evolved specificity depending on specific evolutionary pressure.

Strengths:<br /> The work is based on sound logic and the experimental methodology is well thought through. The data appear accurate, and where ambiguity is observed (as in the case of citruline uptake by AGP1), in vitro transport assays are carried out to verify transport function.

Weaknesses:<br /> Although the data and findings are well described, the study lacked additional contextual information that would support a clear take-home message.

Reviewer #2 (Public Review):

Summary:<br /> This paper describes evolution experiments performed on yeast amino acid transporters aiming at the enlargement of the substrate range of these proteins. Yeast cells lacking 10 endogenous amino acid transporters and thus being strongly impaired to feed on amino acids were again complemented with amino acid transporters from yeast and grown on media with amino acids as the sole nitrogen source.

In the first set of experiments, complementation was done with seven different yeast amino acid transporters, followed by measuring growth rates. Despite most of them have been described before in other experimental contexts, the authors could show that many of them have a broader substrate range than initially thought.

Moving to the evolution experiments, the authors used the OrthoRep system to perform random mutagenesis of the transporter gene while it is actively expressed in yeast. The evolution experiments were conducted such that the medium would allow for poor/slow growth of cells expressing the wt transporters, but much better/faster growth if the amino acid transporter would mutate to efficiently take up a poorly transported (as in the case of citrulline and AGP1) or non-transported (as in case of Asp/Glu and PUT4) amino acid.

This way and using Sanger sequencing of plasmids isolated from faster-growing clones, the authors identified a number of mutations that were repeatedly present in biological replicates. When these mutations were re-introduced into the transporter using site-directed mutagenesis, faster growth on the said amino acids was confirmed. Growth phenotype data were attempted to be confirmed by uptake experiments using radioactive amino acids; however, the radioactive uptake data and growth-dependent analyses do not fully match, hinting at the existence of further parameters than only amino acid uptake alone to impact the growth rates.

When mapped to Alphafold prediction models on the transporters, the mutations mapped to the substrate permeation site, which suggests that the changes allow for more favourable molecular interactions with the newly transported amino acids.

Finally, the authors compared the growth rates of the evolved transporter variants with those of the wt transporter and found that some variants exhibit a somewhat diminished capacity to transport its original range of amino acids, while other variants were as fit as the wt transporter in terms of uptake of its original range of amino acids.

Based on these findings, the authors conclude that transporters can evolve novel substrates through generalist intermediates, either by increasing a weak activity or by establishing a new one.

Strengths:<br /> The study provides evidence in favour of an evolutionary model, wherein a transporter can "learn" to translocate novel substrates without "forgetting" what it used to transport before. This evolutionary concept has been proposed for enzymes before, and this study shows that it also can be applied to transporters. The concept behind the study is easy to understand, i.e. improving growth by uptake of more amino acids as nitrogen source. In addition, the study contains a large and extensive characterization of the transporter variants, including growth assays and radioactive uptake measurements.

Weaknesses:<br /> The authors took a genetic gain-of-function approach based on random mutagenesis of the transporter. While this has worked out for two transporters/substrate combinations, I wonder how comprehensive and general the insights are. In such approaches, it is difficult to know which mutation space is finally covered/tested. And information that can be gained from loss-of-function analyses is missed. The entire conclusions are grounded on a handful of variants analyzed. Accordingly, the outcome is somewhat anecdotal; in some cases, the fitness of the variants was changed and in others not. Highlighting the amino acid changes in the context of the structural models is interesting, but does not fully explain why the variants exhibit changed substrate ranges. Two important technical elements have not been studied in detail by the authors, but may well play a certain role in the interpretation of the results. Firstly, the authors did not quantify the amount of transporter being present on the cell surface; altered surface expression can impact uptake rates and thus growth rates. Secondly, the authors have not assessed whether overexpressing wt versus variant transporters has an impact on the growth rate per se. Overexpressing transporters from plasmids is quite a burden for the cells and often impacts growth rates. Variants may be more or less of a burden, an effect that may (or may also not) go hand in hand with increased/decreased surface production levels.

And finally, I was somewhat missing an evolutionary analysis of these transporters to gain insights into whether the identified substitutions also occurred during natural evolution under real-life conditions.

Reviewer #3 (Public Review):

The goal of the current manuscript is to investigate how changes in transporter substrate specificity emerge through experimental evolution. The authors investigate the APC family of amino acid transporters, a large family with many related transporters that together cover the spectrum of amino acid uptake in yeast.

The authors use a clever approach for their experimental evolutions. By deleting 10 amino acid uptake transporters in yeast, they develop a strain that relies on amino acid import by introducing APC transporters under nitrogen-limiting conditions. They can thus evolve transporters towards the transport of new substrates if no other nitrogen source is available. The main takeaway from the paper is that it is relatively easy for the spectrum of substrates in a particular transporter of this family to shift, as a number of single mutants are identified that modulate substrate specificity. In general, transporters evolved towards gain-of-function mutations (better or new activities) and also confer transport promiscuity, expanding the range of amino acids transported.

The data in the paper support the conclusions, in general, and the outcomes (evolution towards promiscuity) agree with the literature available for soluble enzymes. However, it is also a possibility that the design of these experiments selects for promiscuity among amino acids. The selections were designed such that yeast had access to amino acids that were already transported, with a greater abundance of the amino acid that was the target of selection. Under these conditions, it seems probable that the fittest variants will provide the yeast access to all amino acid substrates in the media, and unlikely that a specificity swap would occur, limiting the yeast to only the new amino acid.

The authors also examine the fitness costs of mutants, but only in the narrow context of growth on a single (original) amino acid under conditions of nitrogen limitation. Amino acid uptake is typically tightly controlled because some amino acids (or their carbon degradation products) are toxic in excess. This paper does not address or discuss whether there might be a fitness cost to promiscuous mutants in conditions where nitrogen is not limiting.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript presents a method to infer causality between two genes (and potentially proteins or other molecules) based on the non-genetic fluctuations among cells using a version of the dual-reporter assay as a causal control, where one half of the dual-reporter pair is causally decoupled, as it is inactive. The authors propose a statistical invariant identity to formalize this idea.

Strengths:<br /> The paper outlines a theoretical formalism, which, if experimentally used, can be useful in causal network inference, which is a great need in the study of biological systems.

Weaknesses:<br /> The practical utility of this method may not be straightforward and potentially be quite difficult to execute. Additionally, further investigations are needed to provide evidence of the broad applicability of the method to naturally occurring systems and its scalability beyond the simple circuit in which it is experimentally demonstrated.

Reviewer #2 (Public Review):

Summary:<br /> This paper describes a new approach to detecting directed causal interactions between two genes without directly perturbing either gene. To check whether gene X influences gene Z, a reporter gene (Y) is engineered into the cell in such a way that (1) Y is under the same transcriptional control as X, and (2) Y does not influence Z. Then, under the null hypothesis that X does not affect Z, the authors derive an equation that describes the relationship between the covariance of X and Z and the covariance of Y and Z. Violation of this relationship can then be used to detect causality.

The authors benchmark their approach experimentally in several synthetic circuits. In four positive control circuits, X is a TetR-YFP fusion protein that represses Z, which is an RFP reporter. The proposed approach detected the repression interaction in two or three of the positive control circuits. The authors constructed sixteen negative control circuit designs in which X was again TetR-YFP, but where Z was either a constitutively expressed reporter or simply the cellular growth rate. The proposed method detected a causal effect in two of the sixteen negative controls, which the authors argue is not a false positive, but due to an unexpected causal effect. Overall, these pilot studies, albeit in simplified scenarios, provide encouraging results.

Strengths:<br /> The idea of a "no-causality control" in the context of detected directed gene interactions is a valuable conceptual advance that could potentially see play in a variety of settings where perturbation-based causality detection experiments are made difficult by practical considerations.

By proving their mathematical result in the context of a continuous-time Markov chain, the authors use a more realistic model of the cell than, for instance, a set of deterministic ordinary differential equations.

Caveats:<br /> The term "causally" is used in the main-text statement of the central theorem (Eq 2) without a definition of this term. This makes it difficult to fully understand the statement of the paper's central theorem without diving into the supplement.

The basic argument of theorem 1 appears to rely on establishing that x(t) and y(t) are independent of their initial conditions. Yet, there appear to be some scenarios where this property breaks down:

(1) Theorem 1 does not seem to hold in the edge case where R=beta=W=0, meaning that the components of interest do not vary with time, or perhaps vary in time only due to measurement noise. In this case x(t), y(t), and z(t) depend on x(0), y(0), and z(0). Since the distributions of x(0), y(0), and z(0) are unspecified, a counterexample to the theorem may be readily constructed by manipulating the covariance matrix of x(0), y(0), and z(0).

(2) A similar problem may occur when transition probabilities decay with time. For example, suppose that again R=0 and X are degraded by a protease (B), but this protease is subject to its own first-order degradation. The deterministic version of this situation can be written, for example, dx/dt=-bx and db/dt=-b. In this system, x(t) approaches x(0)exp(-b(0)) for large t. Thus, as above, x(t) depends on x(0). If similar dynamics apply to the Y and Z genes, we can make all genes depend on their initial conditions, thus producing a pathology analogous to the above example.

The reviewer does not know when such examples may occur in (bio)physical systems. Nevertheless, since one of the advantages of mathematics is the ability to correctly identify the domain of validity for a claim, the present work would be strengthened by "building a fence" around these edge cases, either by identifying the comprehensive set of such edge cases and explicitly prohibiting them in a stated assumption set, or by pointing out how the existing assumptions already exclude them.

Reviewer #1 (Public Review):

Summary:

This manuscript by Bomba-Warczak describes a comprehensive evaluation of long-lived proteins in the ovary using transgenerational radioactive labelled 15N pulse-chase in mice. The transgenerational labeling of proteins (and nucleic acids) with 15N allowed the authors to identify regions enriched in long-lived macromolecules at the 6 and 10-month chase time points. The authors also identify the retained proteins in the ovary and oocyte using MS. Key findings include the relative enrichment in long-lived macromolecules in oocytes, pregranulosa cells, CL, stroma, and surprisingly OSE. Gene ontology analysis of these proteins revealed enrichment for nucleosome, myosin complex, mitochondria, and other matrix-type protein functions. Interestingly, compared to other post-mitotic tissues where such analyses have been previously performed such as the brain and heart, they find a higher fractional abundance of labeled proteins related to the mitochondria and myosin respectively.

Strengths:

A major strength of the study is the combined spatial analyses of LLPs using histological sections with MS analysis to identify retained proteins.

Another major strength is the use of two chase time points allowing assessment of temporal changes in LLPs associated with aging.

The major claims such as an enrichment of LLPs in pregranulosa cells, GCs of primary follicles, CL, stroma, and OSE are soundly supported by the analyses, and the caveat that nucleic acids might differentially contribute to this signal is well presented.

The claims that nucleosomes, myosin complex, and mitochondrial proteins are enriched for LLPs are well supported by GO enrichment analysis and well described within the known body of evidence that these proteins are generally long-lived in other tissues.

Weaknesses:

One small potential weakness is the lack of a mechanistic explanation of if/why turnover may be accelerating at the 6-10 month interval compared to 1-6.

A mild weakness is the open-ended explanation of OSE label retention. This is a very interesting finding, and the claims in the paper are nuanced and perfectly reflect the current understanding of OSE repair. However, if the sections are available and one could look at the spatial distribution of OSE signal across the ovarian surface it would interesting to note if label retention varied by regions such as the CLs or hilum where more/less OSE division may be expected.

Reviewer #2 (Public Review):

Summary:

The manuscript by Bomba-Warczak et al. applied multi-isotope imaging mass spectrometry (MIMS) analysis to identify the long-lived proteins in mouse ovaries during reproductive aging, and found some proteins related to cytoskeletal and mitochondrial dynamics persisting for 10 months.

Strengths:

The manuscript provides a useful dataset about protein turnover during ovarian aging in mice.

Weaknesses:

The study is pretty descriptive and short of further new findings based on the dataset. In addition, some results such as the numbers of follicles and ovulated oocytes in aged mice are not consistent with the published literature, and the method for follicle counting is not accurate. The conclusions are not fully supported by the presented evidence.

Reviewer #3 (Public Review):

Summary:

In this study, Bomba-Warczak et al focused on reproductive aging, and they presented a map for long-lived proteins that were stable during reproductive lifespan. The authors used MIMS to examine and show distinct molecules in different cell types in the ovary and tissue regions in a 6 month mice group, and they also used proteomic analysis to present different LLPs in ovaries between these two timepoints in 6-month and 10-month mice. The authors also examined the LLPs in oocytes in the 6-months mice group and indicated that these were nuclear, cytoskeleton, and mitochondria proteins.

Strengths:

Overall, this study provided basic information or a 'map' of the pattern of long-lived proteins during aging, which will contribute to the understanding of the defects caused by reproductive aging.

Weaknesses:

The 6-month mice were used as an aged model; no validation experiments were performed with proteomics analysis only.

Reviewer #1 (Public Review):

Summary: This study addressed an alternative hypothesis to temporal binding phenomena. In temporal binding, two events that are separated in time are "pulled" towards one another, such that they appear more coincidental. Previous research has shown evidence of temporal binding events in the context of actions and multisensory events. In this context, the author revisits the well-known Libet clock paradigm, in which subjects view a moving clock face, press a button at a time of their choosing to stop the clock, a tone is played (after some delay), and then subjects move the clock dial to the point where the one occurred (or when the action occurred). Classically, the reported clock time is a combination of the action and sound times. The author here suggests that attention can explain this by a mechanism in which the clock dial leads to a roving window of spatiotemporal attention (that is, it extends in both space and time around the dial). To test this, the author conducted a number of experiments where subjects performed the Libet clock experiment, but with a variety of different stimulus combinations. Crucially, a visual detection task was introduced by flashing a disc at different positions along the clock face. The results showed that detection performance was also "pulled" towards the action event or sensory event, depending on the condition. A model of roving spatiotemporal attention replicated these effects, providing further evidence of the attentional window.

The study provides a novel explanation for temporal binding phenomena, with clear and cleverly designed experiments. The results provide a nice fit to the proposed model, and the model itself is able to recapitulate the observed effects.

Reviewer #2 (Public Review):

Summary:<br /> Temporal binding, generally considered a timing illusion, results from actions triggering outcomes after a brief delay, distorting perceived timing. The present study investigates the relationship between attention and the perception of timing by employing a series of tasks involving auditory and visual stimuli. The results highlight the role of attention in event timing and the functional relevance of attention in outcome binding.

Strengths:<br /> - Experimental Design: The manuscript details a well-structured sequence of experiments investigating the attention effect in outcome binding. Thoughtful variations in manipulation conditions and stimuli contribute to a thorough and meaningful investigation of the phenomenon.<br /> - Statistical Analysis: The manuscript employs a diverse set of statistical tests, demonstrating careful selection and execution. This statistical approach enhances the reliability of the reported findings.<br /> - Narrative Clarity: Both in-text descriptions and figures provide clear insights into the experiments and their results, facilitating readers in following the logic of the study.

Weaknesses:<br /> - Conceptual Clarity: The manuscript aims to integrate key concepts in human cognitive functions, including attention, timing perception, and sensorimotor processes. However, before introducing experiments, there's a need for clearer definitions and explanations of these concepts and their known and unknown interrelationships. Given the complexity of attention, a more detailed discussion, including specific types and properties, would enhance reader comprehension.<br /> - Computational Modeling: The manuscript lacks clarity in explaining the model architecture and setup, and it's unclear if control comparisons were conducted. These details are critical for readers to properly interpret attention-related findings in the modeling section. Providing a clearer overview of these aspects will improve the overall understanding of the computational models used.

Reviewer #1 (Public Review):

Summary:

The current study reports a cryo-EM structure of MFS transporter MelB trapped in an inward-facing state by a conformationally selective nanobody. The authors compare this structure to previously-resolved crystal structures of outward-facing MelB. Additionally, the authors report H/D exchange/ mass spec experiments that identify accessible residues in the protein.

Strengths:

The authors overcame very significant technical challenges to solve the first inward-facing structure of the small, model MFS transporter MelB by cryo-EM. The use of conformation-trapping nanobodies (which had been reported previously by this group) is particularly nice.

Weaknesses:

The authors highlight the use of HDX experiments as a measurement of protein conformational dynamics. However, the experiment instead measures the accessibility of different residues. An ideal experiment would trap the transporter in inward- and outward states, but only the inward conformation is trapped here. The outward-facing conformation is instead an ensemble of outward and occluded conformations. It seems obvious that this will be more dynamic than the nanobody-trapped inward state.

Reviewer #3 (Public Review):

Summary:

The manuscript authored by Lan Guan and colleagues reveals the structure of the cytosol-facing conformation of the MelB sodium/Li coupled permease using the nab-Fab approach and cryoEM for structure determination. The study reveals the conformational transitions in the melB transport cycle and allows understanding of the role of sugar and ion specificities within this transporter.

Strengths:

The study employs a very exciting strategy of transferring the CDRS of a conformation specific nano body to the nab-fab system to determine the inward-open structure of MelB. The resolution of the structure is reasonable enough to support the major conclusions of the study. This is a well-executed study.

Reviewer #1 (Public Review):

Summary: The current study reports a cryo-EM structure of MFS transporter MelB trapped in an inward-facing state by a conformationally selective nanobody. The authors compare this structure to previously-resolved crystal structures of outward-facing MelB. Additionally, the authors report H/D exchange/ mass spec experiments that identify accessible residues in the protein.

Strengths:

The authors overcame very significant technical challenges to solve the first inward-facing structure of the small, model MFS transporter MelB by cryo-EM. The use of conformation-trapping nanobodies (which had been reported previously by this group) is particularly nice.

Weaknesses:

Maps and coordinates were not provided by the authors, which presents a gap in this assessment.

The authors highlight the use of HDX experiments as a measurement of protein conformational dynamics. However, this experiment does not measure the conformational dynamics of the transporter, since in these experiments exchange is not initiated by ligand addition or another trigger. The experiment instead measures the accessibility of different residues, and of course, a freely-exchanging sodium bound transporter would have more exchangeable positions than when a conformation-trapping nanobody is bound. It is not clear what new mechanistic information this provides, since this property of the nanobody has already been established.

Based on the evidence presented, it is somewhat speculative that the structure represents the EIIa-bound regulatory state.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Hariharan and colleagues present an elegant study regarding the mechanistic basis of sugar transport by the prototypical Na+-coupled transporter MelB. The authors identified a nanobody (Nb 725) that reduces melibiose binding but not Na+ binding. In vitro (ITC) experiments suggest that the conformation targeted by this nanobody is different from the published outward-open structures. They go on to solve the structure of this other conformational by cryo-EM using the Nanobody grafted with a fiducial marker and enhancer and, as predicted, capture a new conformation of MelB, namely the inward-open conformation. Through MD simulations and ITC measurements, they demonstrate that such state has a reduced affinity for sugar but that Na+ binding is mostly unaffected. A detailed observation and comparison between previously published structures in the outward-open conformation and this new conformational intermediate allows to strengthen and develop the mobile barrier hypothesis underpinning sugar transport. The conformational transition to the inward-facing state leads to the formation of a barrier on the extracellular side that directly affects the amino acid arrangement of the sugar binding site, leading to a decreased affinity that drives the direction of transport. In contrast, the Na+ binding remains the same. This structural data is complemented with dynamic insights from HDX-MS experiments conducted in the presence and absence of the Nb. These measurements highlight the overall protective effect of nanobody binding, consistent with the stabilization of one conformational intermediate.

Strengths:

The experimental strategy to isolate this elusive conformational intermediate is smart and well-executed. The biochemical and biophysical data were obtained in a lipid system (nanodiscs), which allows dismissing questions about detergent induced artefacts. The new conformation observed is of great interest and allows to have a better mechanistic understanding of ion-coupled sugar transport. The comparison between the two structures and the mobile barrier mechanism hypothesis is convincingly depicted and tested.

Weaknesses:

This is excellent experimental work. My recommendations stem mostly from concerns regarding the interpretation of the observed results. In particular, I am somewhat puzzled by the important role the authors give to the regulatory protein EIIa with little structural or biophysical data to back up their claims. The hypothesis that the conformation captured by the Nb is physiologically and functionally equivalent to that caused by EIIa binding is definitely a worthy hypothesis, but it is not an experimental result.

Evidence in support could include a structure with EIIa bound. Since it does not bind at the same location as the Nb, it seems feasible. Or, the authors could have performed HDX-MS in the presence of EIIa to determine if the effect is similar to that of Nb_725 binding. In the absence of these experiments, discussion about EIIa should be limited. Along the same lines, I find it misleading to put in the abstract a sentence such as "It is the first structure of a major facilitator superfamily (MFS) transporter with experimentally determined cation binding, and also a structure mimicking the physiological regulatory state of MelB under the global regulator EIIAGlc of the glucose-specific phosphoenolpyruvate:phosphotransferase system." None of this is supported by the experimental work presented in this article: the Na+ is modelled (with great confidence, but still) and whether this structure mimics the physiological state of MelB bound to EIIa is not known. The results of the paper are strong and interesting enough per se, and there is no need to inflate them with hypothesis that belongs to the discussion section.

I also note that the HDX-MS experiments do not distinguish between two conformational states, but rather an ensemble of states vs one state.

Reviewer #3 (Public Review):

Summary:

The manuscript authored by Lan Guan and colleagues reveals the structure of the cytosol-facing conformation of the MelB sodium/Li coupled permease using the nab-Fab approach and cryoEM for structure determination. The study reveals the conformational transitions in the melB transport cycle and allows understanding the role of sugar and ion specificities within this transporter.

Strengths:

The study employs a very exciting strategy of transferring the CDRS of a conformation specific nano body to the nab-fab system to determine the inward-open structure of MelB. The resolution of the structure is reasonable enough to support the major conclusions of the study. This is overall a well-executed study.

Weaknesses:

The authors seem to have mixed up the exothermic and endothermic aspects of ITC binding in their description. Positive heats correspond to endothermic heat changes in ITC and negative heat changes correspond to exothermic heats. The authors seem to suggest the opposite. This is consistently observed throughout the manuscript.

Reviewer #2 (Public Review):

Yanagihara and colleagues investigated the immune cell composition of bronchoalveolar lavage fluid (BALF) samples in a cohort of patients with malignancy undergoing chemotherapy and with with lung adverse reactions including Pneumocystis jirovecii pneumonia (PCP) and immune-checkpoint inhibitors (ICIs) or cytotoxic drug induced interstitial lung diseases (ILDs). Using mass cytometry, their aim was to characterize the cellular and molecular changes in BAL to improve our understanding of their pathogenesis and identify potential biomarkers and therapeutic targets. In this regard, the authors identify a correlation between CD16 expression in T cells and the severity of PCP and an increased infiltration of CD57+ CD8+ T cells expressing immune checkpoints and FCLR5+ B cells in ICI-ILD patients.

The conclusions of this paper are mostly well supported by data, but some aspects of the data analysis need to be clarified and extended.

1) The authors should elaborate on why different set of markers were selected for each analysis step. E.g., Different set of markers were used for UMAP, CITRUS and viSNE in the T cell and myeloid analysis.

2) The authors should state if a normality test for the distribution of the data was performed. If not, non-parametric tests should be used.

3) The authors should explore the correlation between CD16 intensity and the CTCAE grade in T cell subsets such as EMRA CD8 T cells, effector memory CD4, etc as identified in Figure 1B.

4) The authors could use CITRUS to better assess the B cell compartment.

Reviewer #3 (Public Review):

The authors collected BALF samples from lung cancer patients newly diagnosed with PCP, DI-ILD or ICI-ILD. CyTOF was performed on these samples, using two different panels (T-cell and B-cell/myeloid cell panels). Results were collected, cleaned-up, manually gated and pre-processed prior to visualisation with manifold learning approaches t-SNE (in the form of viSNE) or UMAP, and analysed by CITRUS (hierarchical clustering followed by feature selection and regression) for population identification - all using Cytobank implementation - in an attempt to identify possible biomarkers for these disease states. By comparing cell abundances from CITRUS results and qualitative inspection of a small number of marker expressions, the authors claimed to have identified an expansion of CD16+ T-cell population in PCP cases and an increase in CD57+ CD8+ T-cells, FCRL5+ B-cells and CCR2+ CCR5+ CD14+ monocytes in ICI-ILD cases.

By the authors' own admission, there is an absence of healthy donor samples and, perhaps as a result of retrospective experimental design and practical clinical reasons, also an absence of pre-treatment samples. The entire analysis effectively compares three yet-established disease states with no common baseline - what really constitutes a "biomarker" in such cases? These are very limited comparisons among three, and only these three, states.

By including a new scRNA-Seq analysis using publicly available dataset, the authors addressed this fundamental problem. Though more thorough and numerical analysis would be appreciated for a deeper and more impactful analysis, this is adequate for the intended objectives of the study.

Reviewer #1 (Public Review):

The authors Wang et al. present a study of a mouse model K74R that they claim can extend the life span of mice, and also has some anti-cancer properties in some standrad models of melanoma and hepatocellular carcinoma. Importantly, this mechanism seems to be mediated by the hematopoietic system, and protective effects can be transferred with bone marrow transplantation.

The authors have now adapted their manuscript reflecting the novelties of these studies. Overall, the study is a continuation and also corroboration of previous work, without clinical data yet. The authors have now expanded their work to a second mouse model, which strengthens their data.

Reviewer #2 (Public Review):

The manuscript by Wang et al., follows up on the group's previous publication on KLF1 (EKLF) K47R mice and reduced susceptibility to tumorigenesis and increased life span (Shyu et al., Adv Sci (Weinh). Sep 2022;9(25):e2201409. doi:10.1002/advs.202201409). In the current manuscript, the authors have described these phenotypes in the context of age, gender, genetic background, and hematopoietic transplantation of bone marrow mononuclear cells. Despite the revisions, significant conceptual concerns still remain in the study that make the inferences in the manuscript less convincing. Major concerns are listed below.

Major concerns:

1. The authors mention more than once in the manuscript that KLF1 is expressed in range of blood cells including hematopoietic stem cells, megakaryocytes, T cells and NK cells. In the case of megakaryocytes, studies from multiple labs have shown that while EKLF is expressed megakaryocyte-erythroid progenitors, EKLF is important for the bipotential lineage decision of these progenitors, and its high expression promotes erythropoiesis, while its expression is antagonized during megakaryopoiesis. In the case of HSCs, the authors reference to their previous publication for KLF1's expression in these cells- however, in this study nor in the current study, there is no western blot documented to convincingly show that KLF1 protein is expressed at detectable levels in these cells. For T cells, the authors have referenced a study which is based on ectopic expression of KLF1. For NK cells, the authors reference bioGPS: however, upon inspection, this is also questionable. As part of the revision, the authors have provided western blots in supplemental figure S4. However, these blots are difficult to interpret, since the EKLF bands for NK cells, and T cells are very faint and since the positive control EKLF band from MEL erythroid cell lysates is oversaturated, to interpret the data clearly. Therefore, although a quantification is shown, the representative blot included for EKLF protein levels is not convincing.

2. The current study rests on the premise that KLF1 is expressed in HSCs, NK cells and leukocytes, and the references cited are not sufficient to make this assumption, for the reasons mentioned in the first point. Therefore, the authors were asked to show both KLF1 mRNA and protein levels in these cells, and also compare them to the expression levels seen in KLF1 wild type erythroid cells along with knockout erythroid cells as controls, for context and specificity. The authors have now included western blots and mRNA levels and have compared it to MEL erythroid cells. This data raises additional questions. Overall, the mRNA levels in CD3+ T cells and B220+ B cells are approximately 3000 fold lower than MEL erythroid cells. Based on the information provided, although unclear, the assumption is that the MEL cell extracts are from undifferentiated cells. Therefore, this raises questions on the inference that the healthy aging phenotype is a result of cell intrinsic effects, since EKLF expression in these cells of interest is extremely low. This also allows for the consideration for potential systemic/indirect effects.

3. In the discussion, the authors make broad inferences that go beyond the data shown in the manuscript. For example, they mention that the tumorigenesis resistance and long lifespan is most likely due to changes in transcription regulatory properties and changes in global gene expression profile of the mutant protein relative to WT leukocytes. And based on reduced mRNA levels of Pd-1 Pd-l1 genes in the CD3+ T cells and B220+ B cells from mutant mice, they "assert" that EKLF is an upstream regulator of these genes and regulates the transcriptomes of a diverse range of hematopoietic cells. The authors were asked to perform a ChIP assay to show whether WT EKLF binds on these genes in these cells, and whether this binding is reduced or abolished in the mutant cells, to substantiate the above statements. The authors have now included a ChIP assay in Figure S5. The data on WT EKLF and K74R EKLF on Pd-1 promoter shows that both forms of EKLF bind at similar levels. Therefore, the mechanism remains unclear, and there is insufficient discussion on how their data support cell intrinsic differences in transcriptional regulation between WT and mutant EKLF.

Reviewer #3 (Public Review):

Hung et al provide a well-written manuscript focused on understanding how Eklf mutation confers anticancer and longevity advantages in vivo.

The authors were responsive to the reviewers comments in some aspects. However, the manuscript continues to suffer from significantly overstated claims that are not mitigated in the revision. While additional data has been added, it is unclear how this new data provides clarity to the overall premise of this observational study. Importantly, the authors have added a second model of hepatocellular carcinoma with findings that are consistent with the melanoma model previously reported. In addition, they make more clear that the previously published manuscript on this subject was use of older donors for BMT while now they use younger donors. This is at best incremental. It remains unclear whether Eklf exerts its effect on resistance to malignant progression / metastasis by modulating Pd1 or Pdl1 vs. increasing NK cells as the authors provide evidence of both and do not resolve which mechanism is primarily involved. Finally, there is no evidence that Eklf mutation confers "an anti-disease and anti-aging" effect as at best the data provides evidence of resistance to malignant progression / metastasis in melanoma and hepatoma models.

The work is impactful as it provides evidence of anticancer effect of a specific hematological mutation but the mechanism by which this occurs is not completely elucidated by this work.

Reviewer #1 (Public Review):

Summary:

The authors attempt to fully characterise the immunoglobulin (Ig) heavy (H) chain repertoire of tumor-infiltrating B cells from three different cancer types by identifying the IgH repertoire overlap between these, their corresponding draining lymph nodes (DLNs), and peripheral B cells. The authors claim that B cells from tumors and DLNs have a closer IgH profile than those in peripheral blood and that DLNs are differentially involved with tumor B cells. The claim that tumor-resident B cells are more immature and less specific is made based on the characteristics of the CDR-H3 they express.

Strengths:

The authors show great expertise in developing in-house bioinformatics pipelines, as well as using tools developed by others, to explore the IgH repertoire expressed by B cells as a means of better characterising tumour-associated B cells for the future generation of tumour-reactive antibodies as a therapy.

Weaknesses:

This paper needs major editing, both of the text and the figures, because as it stands it is convoluted and extremely difficult to follow. The conclusions reached are often not obvious from the figures themselves. Sufficient a priori details describing the framework for their analyses are not provided, making the outcome of their results questionable and leaving the reader wondering whether the findings are on solid ground. The authors are encouraged to explain in more detail the premises used in their algorithms, as well as the criteria they follow to define clonotypes, clonal groups, and clonal lineages, which are currently poorly defined and are crucial elements that may influence their results and conclusions. Having excluded the IGHD gene segment from some of their analyses (at least those related to clonal lineage inference and phylogenetic trees), it is not well explained which region of CDR-H3 is responsible for the charge, interaction strength, and Kidera factors, since in some cases the authors mention that the central part of CDR-H3 consists of five amino acids and in others of seven amino acids. How can the authors justify that the threshold for CDR-H3 identity varies according to individual patient data?

Throughout the analyses, the reasons for choosing one type of cancer over another sometimes seem subjective and are not well justified in the text.

Overall, the narrative is fragmented. There is a lack of well-defined conclusions at the end of the results subheadings. The exact same paragraph is repeated twice in the results section. The authors have also failed to synchronise the actual number of main figures with the text, and some panels are included in the main figures that are neither described nor mentioned in the text (Venn diagram Fig. 2A and phylogenetic tree Fig. 5D). Overall, the manuscript appears to have been rushed and not thoroughly read before submission.

Reviewers are forced to wade through, unravel, and validate poorly explained algorithms in order to understand the authors' often bold conclusions.

Reviewer #2 (Public Review):

Summary:

The authors sampled the B cell receptor repertoires of Cancers, their draining lymph nodes, and blood. They characterized the clonal makeup of all B cells sampled and then analyzed these clones to identify clonal overlap between tissues and clonal activation as expressed by their mutation level and CDR3 amino acid characteristics and length. They conclude that B cell clones from the Tumor interact more with their draining lymph node than with the blood and that there is less mutation/expansion/activation of B cell clones in Tumors. These conclusions are interesting but hard to verify due to the under-sampling and short sequencing reads as well as confusion as to when analysis is across all individuals or of select individuals.

Strengths:

The main strength of their analysis is that they take into account multiple characteristics of clonal expansion and activation and their different modes of visualization, especially of clonal expansion and overlap. The triangle plots once one gets used to them are very nice.

Weaknesses:

The data used appears inadequate for the conclusions reached. The authors' sample size of B cells is small and they do not address how it could be sufficient. at such low sampling rates, compounded by the palsmablast bias they mention, it is unclear if the overlap trends they observe show real trends. Analyzing only top clones by size does not solve this issue. As it could be that the top 100 clones of one tissue are much bigger than those of another and that all overlap trends are simply because the clones are bigger in one tissue or the other. i.e there is equal overlap of clones with blood but blood is not sufficiently sampled given its greater diversity and smaller clones. Similarly, the read length (150bp X2) is too short missing FWR1 and CDR1 and often parts of FWR2 if CDR3 is long. As the authors themselves note (and as was shown in (Zhang 2015 - PMC4811607) this makes mutation analysis difficult. It also makes the identification of V genes and thus clonal identification ambiguous. This issue becomes especially egregious when clones are mutated. Finally, it is not completely clear when the analysis is of single individuals or across all individuals. If it is the former the authors did not explain how they chose the individuals analyzed and if the latter then it is not clear from the figures which measurements belong to which individual (i.e they are mixing measurements from different people). For all these reasons while the authors make many interesting suggestions about the potential relationships of B cell repertoires in cancer tissues and their draining lymph nodes and how to characterize and visualize them, it is hard to assess any of their conclusions and specific results.

Reviewer #3 (Public Review):

In multiple cancers, the key roles of B cells are emerging in the tumor microenvironment (TME). The authors of this study appropriately introduce that B cells are relatively under-characterised in the TME and argue correctly that it is not known how the B cell receptor (BCR) repertoires across tumors, lymph nodes, and peripheral blood relate. The authors therefore supply a potentially useful study evaluating the tumor, lymph node, and peripheral blood BCR repertoires and site-to-site as well as intra-site relationships. The authors employ sophisticated analysis techniques, although the description of the methods is incomplete. Among other interesting observations, the authors argue that the tumor BCR repertoire is more closely related to that of draining lymph node (dLN) than the peripheral blood in terms of clonal and isotype composition. Furthermore, the author's findings suggest that tumor-infiltrating B cells (TIL-B) exhibit a less mature and less specific BCR repertoire compared with circulating B cells. Overall, this is a potentially useful work that would be of interest to both medical and computational biologists working across cancer. However, there are aspects of the work that would have benefitted from further analysis and areas of the manuscript that could be written more clearly and proofread in further detail.

Major Strengths:

1. The authors provide a unique analysis of BCR repertoires across tumor, dLN, and peripheral blood. The work provides useful insights into inter- and intra-site BCR repertoire heterogeneity. While patient-to-patient variation is expected, the findings with regard to intra-tumor and intra-dLN heterogeneity with the use of fragments from the same tissue are of importance, contribute to the understanding of the TME, and will inform future study design.

2. A particular strength of the study is the detailed CDR3 physicochemical properties analysis which leads the authors to observations that suggest a less-specific BCR repertoire of TIL-B compared to circulating B cells.

Major Weaknesses:

1. The study would have benefitted from a deeper biological interpretation of the data. While given the low number of patients one can plausibly understand a reluctance to speculate about clinical details, there is limited discussion about what may contribute to observed heterogeneity. For example, for the analysis of three lymph nodes taken per patient which were examined for inter-LN heterogeneity, there is a lack of information regarding these lymph nodes. 'LN3' is deemed as exhibiting the most repertoire overlap with the tumor but there is no discussion as to why this may be the case.

2. At times the manuscript is difficult to follow. In particular, the 'Intra-LN heterogeneity' section follows the 'LN-LN heterogeneity in colorectal cancer' section and compares the overlap of LN fragments (LN11, LN21, LN31) with the tumor in two separate patients (Fig 6A). In the previous section (LN-LN), LN11, LN21, LN31 are names given to separate lymph nodes from the same patient. The fragments are referred to as 'LN2' and the nodes in the previous section are referred to similarly. This conflation of naming for nodes and fragments is confusing.

3. There is a duplicated paragraph in 'Short vs long trees' and the following section 'Productive involvement in hypermutation lineages depends on CDR3 characteristics.

Reviewer #1 (Public Review):

Summary:<br /> This work explored intra and interspecific niche partitioning along spatial, temporal, and dietary niche partitioning between apex carnivores and mesocarnivores in the Qilian Mountain National Park of China, using camera trapping data and DNA metabarcoding sequencing data. They conclude that spatial niche partitioning plays a key role in facilitating the coexistence of apex carnivore species, spatial and temporal niche partitioning facilitate the coexistence of mesocarnivore species, and spatial and dietary niche partitioning facilitate the coexistence between apex and mesocarnivore species. The information presented in this study is important for wildlife conservation and will contribute substantially to the current understanding of carnivore guilds and effective conservation management in fragile alpine ecosystems.

Strengths:<br /> Extensive fieldwork is evident in the study. Aiming to cover a large percentage of the Qilian Mountain National Park, the study area was subdivided into squares, as a geographical reference to distribute the sampling points where the camera traps were placed and the excreta samples were collected.

They were able to obtain many records in their camera traps and collected many samples of excreta. This diversity of data allowed them to conduct robust analyses. The data analyses carried out were adequate to obtain clear and meaningful results that enabled them to answer the research questions posed. The conclusions of this paper are mostly well supported by data.

The study has demonstrated the coexistence of carnivore species in the landscapes of the Qilian Mountains National Park, complementing the findings of previous studies. The information presented in this study is important for wildlife conservation and will contribute substantially to the current understanding of carnivore guilds and effective conservation management in fragile alpine ecosystems.

Weaknesses:<br /> It is necessary to better explain the methodology because it is not clear what is the total sampling effort. In methodology, they only claim to have used 280 camera traps, and in the results, they mention that there are 319 sampling sites. However, the total sampling effort (e.g. total time of active camera traps) carried out in the study and at each site is not specified.

Reviewer #2 (Public Review):

Summary:<br /> The study entitled "Different coexistence patterns between apex carnivores and mesocarnivores based on temporal, spatial, and dietary niche partitioning analysis in Qilian Mountain National Park, China" by Cong et al. addresses the compelling topic of carnivores' coexistence in a biodiversity hotspot in China. The study is interesting given it considers all three components affecting sympatric carnivores' distribution and co-occurrence, namely the temporal, the spatial, and the dietary partition within the carnivore guild. The authors have found that spatial co-occurrence is generally low, which represents the major strategy for coexistence, while there is temporal and dietary overlap. I also appreciated the huge sampling effort carried out for this study by the authors: they were able to deploy 280 camera trapping sites (which became 322 in the result section?) and collect a total of 480 scat samples. However, I have some concerns about the study on the non-consideration of the human dimension and potential anthropogenic disturbance that could affect the spatial and temporal distribution of carnivores, the choice of the statistical model to test co-occurrence, and the lack of clearly stated ecological hypotheses.

Strengths:<br /> The strengths of the study are the investigation of all three major strategies that can mitigate carnivores' coexistence, therefore, the use of multiple monitoring techniques (both camera trapping and DNA metabarcoding) and the big dataset produced that consists of a very large sampled area with a noteworthy number of camera tap stations and many scat samples for each species.

Weaknesses:<br /> I think that some parts of the manuscript should be written better and more clearly. A clear statement of the ecological hypotheses that could affect the partitioning among the carnivore guild is lacking. I think that the human component (thus anthropogenic disturbance) should have been considered more in the spatial analyses given it can influence the use of the environment by some carnivores. Additionally, a multi-species co-occurrence model would have been a more robust approach to test for spatial co-occurrence given it also considers imperfect detection.

Temporal and dietary results are solid and this latter in particular highlights a big predation pressure on some prey species such as the pika. This implies important conservation and management implications for this species, and therefore for the trophic chain, given that i) the pika population should be conserved and ii) a potential poisoning campaign against small mammals could be incredibly dangerous also for mesocarnivores feeding on them due to secondary poisoning.

Reviewer #1 (Public Review):

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

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

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

This revision is a much improved manuscript and I command the authors for many of their edits.

I find the last part of the discussion, starting at "It is generally believed that changes in gene expression patterns are the result of the evolution of CREs", to be confusing.<br /> In this section, I believe the authors sequentially:<br /> - emphasize the role of CRE in morphological evolution (I agree)<br /> - emphasize that TF, and in particular their own CRE, are themselves important mutational targets of evolution (I agree, but the phrasing need to insist the authors are here talking about the CRE found at the TF locus, not the CRE bound by the TF).<br /> - use the stickleback Pel enhancer as an example, which I think is a good case study, but the authors also then make an argument about DNA fragility sites, which is hard to connect with the present study.<br /> - then continue on "DNA fragility" using the peppered moth and butterfly cortex locus. There is no evidence of DNA fragility at these loci, so the connection does not work. "The cortex gene locus is frequently mutated in Lepidoptera", the authors say. But a more accurate picture would be that the cortex locus is repeatedly involved in the generation of color pattern variants. Unlike for Pel fragile enhancer, we don't know if the causal mutations at this locus are repeatedly the same, and the haplotypes that have been described could be collateral rather than causal. Overall, it is important to clarify the idea that mutation bias is a possible factor explaining "genetic hotspots of evolution" (or genetic parallelism sensu 10.1038/nrg3483), but it is also possible that many genetic hotspots are repeated mutational targets because of their "optimal pleiotropy" (e.g. hub position in GRNs, such as mamo might be), or because of particularly modular CRE region that allow fine-tuning. Thus, I find the "fragility" argument misleading here. In fact the finding that "bd" and "bdf" alleles are different in nature is against the idea of a fragility bias (unless the authors can show increased mutation rates at this locus in a wild silkmoth species?). These alleles are also artificially-selected ie. they increased in frequency by breeding rather than natural selection in the wild, so while interesting for our understand of the genotype-phenotype map, they are not necessarily representative of the mutations that may underlie evolution in the wild.<br /> - Curiously, the last paragraph ("Some research suggests that common fragile sites...") elaborate on the idea that some sites of the genome are prone to mutation. The connection with mamo and the current article are extremely thin. There is here an attempt to connect meiotic and mitotic breaks to Bm-mamo, but this is confusing : it seems to propose Bm-mamo as a recruiter of epigenetic modulators that may drive higher mutation rates elsewhere. Not only I am not convinced by this argument without actual data, but this would not explain how the mutations at the Bm-mamo itself evolved.

On a more positive note, I find it fascinating that the authors identified a TF that clearly articulates or orchestrate larval pattern development, and that when it is deleted, can generate healthy individuals. In other words, while it is a TF with many targets, it is not too pleiotropic. This idea, that the genetically causal modulators of developmental evolution are regulatory genes, has been described elsewhere (e.g. Fig 4c in 10.1038/s41576-020-0234-z, and associated refs). To me, the beautiful findings about Bm-mamo make sense in the general, existing framework that developmental processes and regulatory networks "shape" the evolutionary potential and trajectories of organisms. There is a degree of "programmability" in the genomes, because some loci are particularly prone to modulate a given type of trait. Here, Bm-mamo, as a potentially regulator of both CPs and melanin pathway genes, appear to be a potent modulator of epithelial traits. Claiming that there are inherent mutational biases behind this is unwarranted.

Reviewer #1 (Public Review):

In 2019, Wilkinson and colleagues (PMID: 31142833) managed to break the veil on a 20-year open question on how to properly culture and expand Hematopoietic Stem Cells (HSCs). Although this study is revolutionizing the HSC biology field, several questions regarding the mechanisms of expansion remain open. Leveraging on this gap, Zhang et al.; embarked on a much-needed investigation regarding HSC self-renewal in this particular culturing setting.

The authors firstly tacked the known caveat that some HSC membrane markers are altered during in vitro cultures by functionally establishing EPCR (CD201) as a reliable and stable HSC marker (Figure 1), demonstrating that this compartment is also responsible for long-term hematopoietic reconstitution (Figure 3). Next in Figure 2, the authors performed single-cell omics to shed light into the potential mechanisms involved into HSC maintenance, and interestingly it was shown that several hematopoietic populations like monocytes and neutrophils are also present in this culture conditions, which has not been reported. The study goes on to functionally characterize these cultured HSCs (cHSC). The authors elegantly demonstrate using state-of-the-art barcoding strategies that these culturing conditions provoke heterogeneity in the expanding HSC pool (Figure 4). In the last experiment (Figure 5), it was demonstrated that cHSC not only retain their high EPCR expression levels but upon transplantation these cells remain more quiescent than freshly-isolated controls.

Taken together, this study independently validates that the proposed culturing system works and provide new insights into the mechanisms whereby HSC expansion takes place.

Following a first round of comments, the authors provided a comprehensive point-by-point response to the different points raised by reviewers, which significantly helps on better understanding some of the decisions taken by the authors. However, it is surprising that the current manuscript is practically unchanged compared to the previous version. Effectively, all major comments raised by reviewers are address in the response letter rather than incorporated into a truly updated version, which would be of great benefit for readers.

Further comments:<br /> 1. It is highly appreciated that the authors provide a comprehensive and cohesive explanations on i) the rationale for employing SAILERX for single-cell RNA and ATAC-seq, ii) data on HSC signature projected on independent scRNA-seq datasets and iii) further context on the Fgd5 expression limitations. These are important snippets of information which do not only further validate this manuscript's data but also provide context within the HSC biology field.<br /> However, I do not fully agree with the author statement "our primary objective in this study was to highlight the relatively low content of HSCs in cultures" (page 1, response to Reviewers) justifying why single-cell genome-wise approaches were used. As the authors are aware HSCs are defined by functional characterization rather than transcriptional/chromatin accessibility profiles, so it seems odd that this was the rationale to perform omics for this purpose. More importantly, the authors had gone through the lengths of already performing this costly and time-consuming experiment, but miss out on the opportunity to take a deeper dive into the molecular characteristics that could explain divergent behavior between freshly-isolated and cultured HSCs. It would be extremely relevant to the HSC biology community to understand, for example, if these two HSC populations have differences in enhancer accessibility (if the data quality allows), which could provide an upstream explanation for differences in transcription (is also not explored in this manuscript version).

2. It intriguing that the authors acknowledge that there are already more recent versions of this expansion protocol (page 2, response to Reviewers) and provided a convoluted explanation on why these were not included in the original manuscript. Both papers (PMID: 36809781 and PMID: 37385251) have now been published in respected peer-reviewed journals and provide insights which are pertinent for this work. Yet, the authors decided not to discuss these findings. It is understandable that repeating experiments with these updated conditions is outside of the scope of this manuscript, but it would be relevant to discuss how these recent advances in the protocol impact the work presented in this manuscript.

3. Regarding the previous comment on how cultured HSC are related to HSC aging, I highly appreciate both data on serial transplantation and also on scRNA-seq.

Reviewer #2 (Public Review):

Summary:<br /> In this study, Zhang and colleagues characterise the behaviour of mouse hematopoietic stem cells when cultured in PVA conditions, a recently published method for HSC expansion (Wilkinson et al., Nature, 2019), using multiome analysis (scRNA-seq and scATACseq in the same single cell) and extensive transplantation experiments. The latter are performed in several settings including barcoding and avoiding recipient conditioning. Collectively the authors identify several interesting properties of these cultures namely: 1) only very few cells within these cultures have long-term repopulation capacity, many others however have progenitor properties which can rescue mice from lethal myeloablation; 2) single cell characterisation by combined scRNAseq and scATACseq is not sufficient to identify cells with repopulation capacity; 3) expanded HSCs can be engrafted in unconditioned host and return to quiescence.

The authors also confirm previous studies that EPCRhigh HSCs have better reconstitution capability than EPCRlow HSCs when transplanted.

Strengths:<br /> The major strength of this manuscript is that it describes how functional HSCs are expanded in PVA cultures to a deeper extent that what has been done in the original publication. The authors are also mindful of considering the complexities of interpreting transplantation data. As these PVA cultures become more widely used by the HSC community, this manuscript is valuable as it provides a better understanding of the model and its limitations.

Novelty aspects include:<br /> • The authors determined that small numbers of expanded HSCs enable transplantation into non-conditioned syngeneic recipients.<br /> • This is to my knowledge the first report characterising output of PVA cultures by multiome. This could be a very useful resource to the field.<br /> • They are also the first to my knowledge to use barcoding to quantify HSC repopulation capacity at the clonal level after PVA culture.<br /> • It is also useful to report that HSCs isolated from fetal livers do expand less than their adult counterparts in these PVA cultures.

Weaknesses:<br /> • The analysis of the multiome experiment is limited. The authors do not discuss what cell types, other than functional or phenotypic HSCs are present in these cultures (are they mostly progenitors or bona fide mature cells?) and no quantifications are provided. It seems nonetheless that most cells in these cultures do not acquire differentiation markers. In addition, the functional experiments demosntrate very few retain transplantation capacity. Future works will have to investigate the nature of the bulk of the other cells in these cultures.<br /> • Barcoding experiments are technically elegant but do not bring particularly novel insights.<br /> • Number of mice analysed in certain experiments is fairly low (Figure 1 and 5).<br /> • The manuscript remains largely descriptive. While the data can be used to make useful recommendations to future users working with PVA cultures and in general with HSCs, those recommendations could be more clearly spelled out in the discussion.<br /> • The authors could have provided discussion of the other publications/preprints which have used these methods to date. This would have been useful for researchers who have not used this technique.

Overall, the authors succeeded in providing a useful set of experiments to better interpret what type of HSCs are expanded in PVA cultures. More in depth mining of their bioinformatic data (by the authors or other groups) is likely to highlight other interesting/relevant aspects of HSC biology in relation to this expansion methodology.

Reviewer #1 (Public Review):

Summary:<br /> TRAP transporters are an unusual class of secondary active transporters that utilize periplasmic binding proteins to deliver their substrates. This paper contributes a new 3 Å structure of the Haemophilus influenzae TRAP transporter. The structure joins two other recent cryo-EM structures of TRAP transporters, including a lower resolution structure of the same H. influenzae protein (overall 4.7 Å), and a ~3 Å structure of a homologue from P. profundum. In addition to reporting a higher resolution cryo-EM structure, the authors also recapitulate protein activity in a reconstituted system, investigate protein oligomerization using analytic ultracentrifugation, and evaluate interactions and function in "mix and match" configurations with periplasmic subunits from other homologues.

Strengths:<br /> The strength of the paper is that the better resolution cryo-EM data permits sidechain assignment, the identification of bound lipids, and the identification of sodium ions. It is important to get this structure out there, since the resolution passes an important threshold for model building accuracy. The current structure nicely explains a lot of prior mutagenesis data on the H. influenzae TRAP. This is also the first structure of a TRAP protein to be solved without a fiducial, although the overall structure is not very different than those solved with fiducials.

Weaknesses:<br /> The experiments examining the monomer/dimer equilibrium appear somewhat preliminary. The biological or mechanistic importance of oligomerization is not established, so these experiments are inherently of limited scope. Moreover, cryo-EM datasets exhibit both parallel and antiparallel dimers, the latter of which are clearly not biologically relevant. It is probably impossible to distinguish these in the AUC experiments, which makes interpretation of these experiments more difficult.

Similarly, the importance of the lipid binding sites observed in cryo-EM aren't experimentally established (for example by mutating the binding site) and it is thus unknown whether they are important for function (as the authors acknowledge).

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the membrane component of the sialic acid-specific TRAP transporter, SiaQM (HiSiaQM), from H. influenzae, is structurally characterized. TRAP transporters are substrate binding protein (SBP)-dependent secondary-active transporters, and HiSiaQM is the most comprehensively studied member of this family. While all previous work on fused TRAP transporter membrane proteins suggests that they are monomeric (including the previous structural characterization of HiSiaQM by a different group), a surprising finding from this work is the observation that HiSiaQM can form higher oligomers, consistent with it being a dimer. These higher oligomeric states were initially observed after extraction of the protein with LMNG detergent, but were also observed in DDM detergent, amphipol and nanodiscs using analytical ultracentrifugation (AUC). Structural characterization of dimeric HiSiaQM revealed 2 arrangements, a parallel and antiparallel arrangements, the latter of which is unlikely to be physiologically relevant.

The higher resolution of this new structure of HiSiaQM (2.2-2.7 Å compared to 4.7 Å for the previous structure) facilitated the assignment of bound lipids at the dimer interface and a lipid molecule embedded in each of the protomers; allowed for a clearer refinement of the Na+ and putative substrate binding sites, which differ slightly from the previous structure; and produced better modelled side chains for the residues involved in the SBP:HiSiaQM interaction. The authors developed a useful AUC-based assay to determine the affinity for this interaction revealing an affinity of 65 µM. Finally, the authors make the very interesting observation that a sialic acid specific SBP from a different TRAP transporter can utilize HiSiaQM for transport, contrary to previous observations, revealing for the first time that TRAP membrane components can recognize multiple SBPs.

Overall, this is a well written and presented manuscript detailing some interesting new observations about this interesting protein family. One of the main findings, that the protein can form a dimer, is supported by data, but the physiological relevance of this is questionable, and the possibility that this is artefactual has not been ruled out. Conclusions regarding the mechanistic importance of the lipid bindings sites is not currently supported by the data.

Strengths:<br /> The main strength of this work is the increased resolution of HiSiaQM, which allows for much more precise assignment of side chains and their orientation. This will be of importance for subsequent mechanistic studies on the contributions of these residues to Na+ and sialic acid binding and conformational changes.<br /> The observation of the lipids, especially the lipid embedded near the fusion helix, is an intriguing observation, which lays the groundwork for future work to understand the lipid-dependence of these transporters.<br /> The development of the AUC-based approach to measure SBP affinity for the membrane component will likely prove be useful to future studies.

Weaknesses:<br /> One of the main results from this work is the observation that HiSiaQM can form a dimer. Two arrangements were observed, parallel and antiparallel, the latter of which is almost certainly physiologically irrelevant as it would preclude essential interactions with the extracytoplasmic substrate binding protein. As acknowledged by the author, this non-physiological arrangement is likely a consequence of protein preparation (overexpression, extraction, purification, etc.). However, if one dismisses the antiparallel arrangement as non-relevant and an artefact of protein preparation, it is difficult for the parallel arrangement to maintain its credibility, as it was also processed in the same way. This is especially true when one considers that there is only 100 Å2 buried surface area in the parallel arrangement that does not involve any sidechains; it is difficult to envisage this as a specific interaction, e.g. compared to related proteins that have ~2000 Å2 buried surface area. Unless this dimerization is observed in a bacterial membrane at physiological protein concentrations, it is difficult to rule out the possibility that the observed dimerization is merely an artefact caused by the expression, purification and concentration of the protein.

The manuscript contains some excellent structural analysis of this protein, whose higher resolution reveals some new and interesting insight. However, a weakness of the current work is a lack of validation of these observations using other approaches. For example, lipid interactions are observed in the structure that the authors claim is mechanistically important. However, without disrupting these interactions to look at the effect on transport, this conclusion is not supported. Similarly, the authors use their structure to predict residues that are important for the SBP:membrane protein interaction, and they develop an AUC-based binding assay to study this interaction, but they do not test their predictions using this approach.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript reports new molecular characterization of the Haemophilus influenza tripartite ATP-independent periplasmic (TRAP) transporter of N-acetylneuraminate (Neu5Ac). This membrane transporter is important for the virulence of the pathogen. H. influenza lacks Neu5Ac biosynthetic pathway, and utilizes the TRAP transporter to import it. Neu5Ac is used as a nutrient source but also as a protection from human immune response. The transporter is composed of two fused membrane subunits, HiSiaQM, and one soluble, periplasmic subunit HiSiaP. HiSiaP, by binding to the substrate Neu5Ac, changes its conformation, allowing its binding to HiSiaQM, followed by Neu5Ac and Na+ transport to the cytoplasm. The combination of structural, biophysical and biochemical approaches provides a solid basis for describing the functioning of the Haemophilus influenza Neu5Ac TRAP transporter, which is essential for the pathogen virulence.

Strengths:<br /> The paper describes the electron microscopy structure of HiSiaQM, thanks to its solubilization in L-MNG followed by exchange to amphipol or nanodisc. In these conditions, HiSiaQM consists in a mixture of monomers and dimers, as characterized by analytical ultracentrifugation. The cryo-EM analysis shows two types of dimers: one in an antiparallel configuration, which is artifactual, and a parallel one, which may be physiologically relevant. Cryo-EM on the dimers allows high resolution (≈ 3 Å) structure determination. The structure is the first one of a fused SiaQM, and is the first obtained without megabody. The work highlights structural elements (fusion helix, lipids) that could modulate transport. The authors checked the functionality of the purified HiSiaQM, which, after reconstitution in liposome, displays a significantly larger Neu5Ac transport activity compared to the non-fused PpSiaQM homolog. The work identifies Na+ binding sites, and the putative Neu5Ac binding site. From analytical ultracentrifugation using fluorescently labelled HiSiaP, the authors show that HiSiaP is able to interact with HiSiaQM monomer and dimer, with a low but physiologically relevant affinity. HiSiaP interaction with HiSiaQM was modelled using AlphaFold2, and discussed in view of published activity on mutants, and new transport activity assays using SiaQM and SiaP from different organisms. In conclusion, the combination of structural, biophysical and biochemical approaches provides a solid basis for describing the functioning of this TRAP fused transporter.

Weakness: This work evidences in vitro a HiSiaQM dimer, whose in vivo relevance is not ascertained. However, the authors are very careful, they do not to over-interpret their data, and their conclusions regarding the transporter structure and function are valid irrespective of its state of association.

Reviewer #1 (Public Review):

Summary:

The manuscript by Xia et al. investigated the mechanisms underlying Glucocorticoid-induced osteonecrosis of the femoral head (GONFH). The authors observed that abnormal osteogenesis and adipogenesis is associated with decreased β-catenin in the necrotic femoral head of GONFH patients and inhibition of β-catenin signaling leads to abnormal osteogenesis and adipogenesis in GONFH rats. Of interest, deletion of β-catenin in Col2-expressing cells rather than in osx-expressing cells leads to a GONFH-like phenotype in femoral head of mice.

Strengths:

A strength of the study is that it sets up a Col2-expressing cell-specific β-catenin knockout mouse model that mimics full spectrum of osteonecrosis phenotype of GONFH. This is interesting and provides new insights into the understanding of GONFH. Overall, the data are solid and support their conclusions.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors reported a study to uncover that β-catenin inhibition disrupting the homeostasis of osteogenic/adipogenic differentiation contributes to the development of Glucocorticoid-induced osteonecrosis of the femoral head (GONFH). In this study, they first observed abnormal osteogenesis and adipogenesis associated with decreased β-catenin in the necrotic femoral head of GONFH patients, but the exact pathological mechanisms of GONFH remain unknown. They then performed in vivo and in vitro studies to further revealed that glucocorticoid exposure disrupted osteogenic/adipogenic differentiation bone marrow stromal cells (BMSCs) by inhibiting β-catenin signaling in glucocorticoid-induced GONFH rats, and specific deletion of β-catenin in Col2+ cells shifted BMSCs commitment from osteoblasts to adipocytes, leading to a full spectrum of disease phenotype of GONFH in adult mice.

Strengths:

This innovative study provides strong evidence supporting that β-catenin inhibition disrupts the homeostasis of osteogenic/adipogenic differentiation that contributes to the development of GONFH. This study also identifies an ideal genetic modified mouse model of GONFH. Overall, the experiment is logically designed, the figures are clear, and the data generated from humans and animals is abundant supporting their conclusions.

Weaknesses:

Lack of the discussion to explain how the Wnt agonist 1 works. There are several types of Wnt ligands. It is not clear if this agonist only targets Wnt1 or other Wnts as well? Also, why Wnt agonist 1 couldn't rescue the GONFH-like phenotype in β-cateninCol2ER mice needs to be discussed.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors are trying to delineate the mechanism underlying the osteonecrosis of the femoral head.

Strengths:

The authors provided compelling in vivo and in vitro data to demonstrate Col2+ cells and Osx+ cells were differentially expressed in the<br /> the femoral head. Moreover, inducible knockout of β-catenin in Col2+ cells but not<br /> Osx+ cells lead to a GONFH-like phenotype including fat accumulation, subchondral<br /> bone destruction and femoral head collapse, indicating that imbalance of osteogenic/adipogenic differentiation of Col2+ cells play an important role in GONFH pathogenesis. Therefore, this manuscript provided the mechanistic insights of osteonecrosis as well as potential therapeutic target for disease treatment.

Weaknesses: Additional in depth discussion regarding the phenotype observed in mice is highly encouraged.

Reviewer #1 (Public Review):

Summary:<br /> This paper investigates the neural mechanisms underlying the change in perception when viewing ambiguous figures. Each possible percept is related to an attractor-like brain state and a perceptual switch corresponds to a transition between these states. The hypothesis is that these switches are promoted by bursts of noradrenaline that change the gain of neural circuits. The authors present several lines of evidence consistent with this view: pupil diameter changes during the time point of the perceptual change; a gain change in neural network models promotes a state transition; and large-scale fMRI dynamics in a different experiment suggests a lower barrier between brain states at the change point. However, some assumptions of the computational model seem not well justified and the theoretical analysis is incomplete. The paper would also benefit from a more in-depth analysis of the experimental data.

Strengths:<br /> The main strength of the paper is that it attempts to combine experimental measurements - from psychophysics, pupil measurements, and fMRI dynamics - and computational modeling to provide an emerging picture of how a perceptual switch emerges. This integrative approach is highly useful because the model has the potential to make the underlying mechanisms explicit and to make concrete predictions.

Weaknesses:<br /> A general weakness is that the link between the three parts of the paper is not very strong. Pupil and fMRI measurements come from different experiments and additional analysis showing that the two experiments are comparable should be included. Crucially, the assumptions underlying the RNN modeling are unclear and the conclusions drawn from the simulation may depend on those assumptions.

Main points:<br /> Perceptual tasks in pupil and fMRI experiments: how comparable are these two tasks? It seems that the timing is very different, with long stimulus presentations and breaks in the fMRI task and a rapid sequence in the pupil task. Detailed information about the task timing in the pupil task is missing. What evidence is there that the same mechanisms underlie perceptual switches at these different timescales? Quantification of the distributions of switching times/switching points in both tasks is missing. Do the subjects in the fMRI task show the same overall behavior as in the pupil task? More information is needed to clarify these points.

Computational model:<br /> 1. Modeling noradrenalin effects in the RNN: The pupil data suggests phasic bursts of NA would promote perceptual switches. But as I understand, in the RNN neuromodulation is modeled as different levels of gain throughout the trial. Making the neural gain time-dependent would allow investigation of whether a phasic gain change can explain the experimentally observed distribution of switching times.

2. Modeling perceptual switches: in the results, it is described that the networks were trained to output a categorical response, but the firing rates in Fig 2B do not seem categorical but rather seem to follow the input stimulus. The output signals of the network are not shown. If I understand correctly, a trivial network that would just represent the two input signals without any internal computation and relay them to the output would do the task correctly (because "the network's choice at each time point was the maximum of the two-dimensional output", p. 22). This seems like cheating: the very operation that the model should perform is to signal the change, in a categorical manner, not to represent the gradually changing input signals.

3. The mechanism of how increased gain leads to faster switches remains unclear to me. My first intuition was that increasing the gain of excitatory populations (the situation shown in Fig. 2E) in discrete attractor models would lead to deeper attractor wells and this would make it more difficult to switch. That is, a higher gain should lead to slower decisions in this case. However, here the switching time remains constant for a gain between 1 and 1.5. Lowering the gain, on the other hand, leads to slower switching. It is, of course, possible that the RNN behaves differently than classical point attractor models or that my intuition is incorrect (though I believe it is consistent with previous literature, e.g. Niyogi & Wong-Lin 2013 (doi:10.1371/journal.pcbi.1003099) who show higher firing rates - more stable attractors - for increased excitatory gain).

4. From the RNN model it is not clear how changes in excitatory and inhibitory gain lead to slower/faster switching. In order to better understand the role of inhibitory and excitatory gain on switching, I would suggest studying a simple discrete attractor model (a rate model, for example as in Wong and Wang 2006 or Roxin and Ledberg, Plos Comp. Bio 2008) which will allow to study these effects in terms of a very few model parameters. The Roxin paper also shows how to map rate models onto simplified one-dimensional systems such as the one in Fig S3. Setting up the model using this framework would allow for making much stronger, principled statements about how gain changes affect the energy landscape, and under which conditions increased inhibitory gain leads to faster switching.

One possibility is that increasing the excitatory gain in the RNN leads to saturated firing rates. If this is the reason for the different effects of excitatory and inhibitory gain changes, it should be properly explained. Moreover, the biological relevance of this effect should be discussed (assuming that saturation is indeed the explanation).

Alternative mechanisms:<br /> It is mentioned in the introduction that changes in attention could drive perceptual switches. A priori, attention signals originating in the frontal cortex may be plausible mechanisms for perceptual switches, as an alternative to LC-controlled gain modulation. Does the observed fMRI dynamics allow us to distinguish these two hypotheses? In any case, I would suggest including alternative scenarios that may be compatible with the observed findings in the discussion.

Reviewer #2 (Public Review):

Strengths<br /> - the study combines different methods (pupillometry, RNNs, fMRI).<br /> - the study combines different viewpoints and fields of the scientific literature, including neuroscience, psychology, physics, dynamical systems.<br /> - This combination of methods and viewpoints is rarely done, it is thus very useful.<br /> - Overall well-written.

Weaknesses<br /> - The study relies on a report paradigm: participants report when they identify a switch in the item category. The sequence corresponds to the drawing of an object being gradually morphed into another object. Perceptual switches are therefore behaviorally relevant, and it is not clear whether the effect reported correspond to the perceptual switch per se, or the detection of an event that should change behavior (participant press a button indicating the perceived category, and thus switch buttons when they identify a perceptual change). The text mentions that motor actions are controlled for, but this fact only indicates that a motor action is performed on each trial (not only on the switch trial); there is still a motor change confounded with the switch. As a result, it is not clear whether the effect reported in pupil size, brain dynamics, and brain states is related to a perceptual change, or a decision process (to report this change).

- The study presents events that co-occur (perceptual switch, change in pupil size, energy landscape of brain dynamics) but we cannot identify the causes and consequences. Yet, the paper makes several claims about causality (e.g. in the abstract "neuromodulatory tone ... causally mediates perceptual switches", in the results "the system flattening the energy landscape ... facilitated an updating of the content of perception").

- Some effects may reflect the expectation of a perceptual switch, rather than the perceptual switch per se. Given the structure of the task, participants know that there will be a perceptual switch occurring once during a sequence of morphed drawings. This change is expected to occur roughly in the middle of the sequence, making early switches more surprising, and later switches less surprising. Differences in pupil response to early, medium, and late switches could reflect this expectation. The authors interpret this effect very differently ("the speed of a perceptual switch should be dependent on LC activity").

- The RNN is far more complex than needed for the task. It has two input units that indicate the level of evidence for the two categories being morphed, and it is trained to output the dominant category. A (non-recurrent) network with only these two units and an output unit whose activity is a sigmoid transform of the difference in the inputs can solve the task perfectly. The RNN activity is almost 1-dimensional probably for this reason. In addition, the difficult part of the computation done by the human brain in this task is already solved in the input that is provided to the network (the brain is not provided with the evidence level for each category, and in fact, it does not know in advance what the second category will be).

- Basic fMRI results are missing and would be useful, before using elaborate analyses. For instance, what are the regions that are more active when a switch is detected?

- The use of methods from physics may obscure some simple facts and simpler explanations. For instance, does the flatter energy landscape in the higher gain condition reflect a smaller number of states visited in the state space of the RNN because the activity of each unit gets in the saturation range? If correct, then it may be a more straightforward way of explaining the results.

- Some results are not as expected as the authors claim, at least in the current form of the paper. For instance, they show that, when trained to identify which of two inputs u1 and u2 is the largest (with u2=1-u1, starting with u1=1 and gradually decreasing u1), a higher gain results in the RNN reporting a switch in dominance before the true switch (e.g. when u1=0.6 and u2=0.4), and vice et versa with a lower gain. In other words, it seems to correspond to a change in criterion or bias in the RNN's decision. The authors should discuss more specifically how this result is related to previous studies and models on gain modulation. An alternative finding could have been that the network output is a more (or less) deterministic function of its inputs, but this aspect is not reported.

Reviewer #1 (Public Review):

In this manuscript, the authors explore the effects of DNA methylation on the strength of regulatory activity using massively parallel reporter assays in cell lines on a genome-wide level. This is a follow-up of their first paper from 2018 that describes this method for the first time. In addition to adding more in depth information on sequences that are explored by many researchers using two main methods, reduced bisulfite sequencing and sites represented on the Illumina EPIC array, they now show also that DNA methylation can influence changes in regulatory activity following a specific stimulation, even in absence of baseline effects of DNA methylation on activity. In this manuscript, the authors explore the effects of DNA methylation on the response to Interferon alpha (INFA) and a glucocorticoid receptor agonist (dexamethasone). The author validate their baseline findings using additional datasets, including RNAseq data and show convergences across two cell lines. The authors then map the methylation x environmental challenge (IFNA and dex) sequences identified in vitro to explore whether their methylation status is also predictive of regulatory activity in vivo. This is very convincingly shown for INFA response sequences, where baseline methylation is predictive of the transcriptional response to flu infection in human macrophages, an infection that triggers the INF pathways. The extension of the functional validity of the dex-response altering sequences is less convincing. Sequences altering the response to glucocorticoids, however, were not enriched in DNA methylation sites associated with exposure to early adversity which the authors interpret that "they are not links on the causal pathway between early life disadvantage and later life health outcomes, but rather passive biomarkers. However, this approach does not seem an optimal model to explore this relationship in vivo. This is because exposure to early adversity and its consequences is not directly correlated with glucocorticoid release and changes in DNA methylation levels following early adversity could be related to many physiological mechanisms, and overall, large datasets and meta-analyses do not show robust associations of exposure to early adversity and DNA methylation changes. Here other datasets, such as from Cushing patients maybe of more interest.<br /> ***<br /> After revision, the authors have now discussed this issue carefully, so that this point is addressed.<br /> ***<br /> Overall, the authors provide a great resource of DNA methylation sensitive enhancers that can now be used for functional interpretation of large scale datasets (that are widely generated in the research community), given the focus on sites included in RBSS and the Illumina EPIC array. In addition, their data lends support that difference in DNA methylation can alter responses to environmental stimuli and thus of the possibility that environmental exposures that alter DNS methylation can also alter subsequent response to this exposure, in line with the theory of epigenetic embedding of prior stimuli/experiences. The conclusions related to the early adversity data should be reconsidered in light of the comments above.

Reviewer #2 (Public Review):

This work presents a remarkably extensive set of experiments, assaying the interaction between methylation and expression across most CpG positions in the genome in two cell types. To this end, the authors use mSTARR-seq, a high-throughput method, which they have previously developed, where sequences are tested for their regulatory activity in two conditions (methylated and unmethylated) using a reporter gene. The authors use these data to study two aspects of DNA methylation: 1. Its effect on expression, and 2. Its interaction with the environment. Overall, they identify a small number of 600 bp windows that show regulatory potential, and a relatively large fraction of these show an effect of methylation on expression. In addition, the authors find regions exhibiting methylation-dependent response to two environmental stimuli (interferon alpha and glucocorticoid dexamethasone).

The questions the authors address represent some of the most central in functional genomics, and the method utilized is currently the best method to do so. The scope of this study is very impressive and I am certain that these data will become an important resource for the community. The authors are also able to report several important findings, including that pre-existing DNA methylation patterns can influence the response to subsequent environmental exposures.

Reviewer #1 (Public Review):

Summary:<br /> Alonso-Calleja and colleagues explore the role of TGR5 in adult hematopoiesis at both steady state and post-transplantation. The authors utilize two different mouse models including a TGR5-GFP reporter mouse to analyze the expression of TGR5 in various hematopoietic cell subsets. Using germline Tgr5-/- mice it's reported that loss of Tgr5 has no significant impact on steady-state hematopoiesis, with a small decrease in trabecular bone fraction, associated with a reduction in proximal tibia adipose tissue, and an increase in marrow phenotypic adipocytic precursors. The authors further explored the role of stroma TGR5 expression in the hematopoietic recovery upon bone marrow transplantation of wild-type cells, although the studies supporting this claim are weak. Overall, while most of the hematopoietic phenotypes have negative results or small effects, the role of TGR5 in adipose tissue regulation is interesting to the field.

Strengths:<br /> • This is the first time the role of TGR5 has been examined in the bone marrow.<br /> • This paper supports further exploration of the role of bile acids in bone marrow transplantation and possible therapeutic strategies.

Weaknesses:<br /> • The authors fail to describe whether niche stroma cells or adipocyte progenitor cells (APCs) express TGR5.<br /> • Although the authors note a significant reduction in bone marrow adipose tissue in Tgr5-/- mice, they do not address whether this is white or brown adipose tissue especially since BA-TGR5 signaling has been shown to play a role in beiging.<br /> • In Figure 1, the authors explore different progenitor subsets but stop short of describing whether TGR5 is expressed in hematopoietic stem cells (HSCs).<br /> • Are there more CD45+ cells in the BM because hematopoietic cells are proliferating more due to a direct effect of the loss of Tgr5 or is it because there is just more space due to less trabecular bone?<br /> • In Figure 4 no absolute cell counts are provided to support the increase in immunophenotypic APCs (CD45-Ter119-CD31-Sca1+CD24-) in the stroma of Tgr5-/- mice. Accordingly, the absolute number of total stromal cells and other stroma niche cells such as MSCs, ECs are missing.<br /> • There are issues with the reciprocal transplantation design in Fig 4. Why did the authors choose such a low dose (250 000) of BM cells to transplant? If the effect is true and relevant, the early recovery would be observed independently of the setup and a more robust engraftment dataset would be observed without having lethality post-transplant. On the same note, it's surprising that the authors report ~70% lethality post-transplant from wild-type control mice (Fig 4E), according to the literature 200 000 BM cells should ensure the survival of the recipient post-TBI. Overall, the results even in such a stringent setup still show minimal differences and the study lacks further in-depth analyses to support the main claim.<br /> • Mechanistically, how does the loss of Tgr5 impact hematopoietic regeneration following sublethal irradiation?<br /> • Only male mice were used throughout this study. It would be beneficial to know whether female mice show similar results.

Reviewer #2 (Public Review):

Summary: In this manuscript, the authors examined the role of the bile acid receptor TGR5 in the bone marrow under steady-state and stress hematopoiesis. They initially showed the expression of TGR5 in hematopoietic compartments and that loss of TGR5 doesn't impair steady-state hematopoiesis. They further demonstrated that TGR5 knockout significantly decreases BMAT, increases the APC population, and accelerates the recovery upon bone marrow transplantation.

Strengths: The manuscript is well-structured and well-written.

Weaknesses: The mechanism is not clear, and additional studies need to be performed to support the authors' conclusion.

Reviewer #1 (Public Review):

Here, Muronova et al., demonstrate the physiological importance of a centriole and microtubule-associated protein, CCDC146, in sperm flagellar formation and male reproduction. This study identifies novel causal variants to cause male infertility and resolves the pathogenicity by the mutation with characterizing mouse models. Furthermore, the authors' claims are well supported by the biochemical and imaging approaches used in this study.

Reviewer #3 (Public Review):

Male infertility is an important health problem. Among pathologies with multiple morphological abnormalities of the flagellum (MMAF), only 50% of the patients have no identified genetic causes. It is thus primordial to find novel genes that cause the MMAF syndrome. In the current work, the authors follow up the identification of two patients with MMAF carrying a mutation in the CCDC146 gene. To understand how mutations in CCDC146 lead to male infertility, the authors generated two mouse models: a CCDC146-knockout mouse, and a knockin mouse in which the CCDC146 locus is tagged with an HA tag. Male CCDC146-knockout mice are infertile, which proves the causative role of this gene in the observed MMAF cases. Strikingly, animals develop no other obvious pathologies, thus underpinning the specific role of CCDC146 in male fertility. The authors have carefully characterised the subcellular roles of CCDC146 by using a combination of expansion and electron microscopy. They demonstrate that all microtubule-based organelles, such as the sperm manchette, the centrioles, as well as the sperm axonemes are defective when CCDC146 is absent. Their data show that CCDC146 is a microtubule-associated protein, and indicate, but do not prove beyond any doubt, that it could be a microtubule-inner protein (MIP).

This is a solid work that defines CCDC146 as a novel cause of male infertility. The authors have performed comprehensive phenotypic analysis to define the defects in CCDC146 knockout mice. The manuscript text is well written and easy to follow also for non-specialists. The introduction and discussion chapters contain important background information that allow to put the current work into the greater context of fertility research. Overall, this manuscript provides convincing evidence for CCDC146 being essential for male fertility and illustrates this with a large panel of phenotypic observations. Together, the work provides important first insights into the role of a so-far unexplored proteins, CCDC146, in spermatogenesis, thereby broadening the spectrum of genes involved in male infertility.

Reviewer #1 (Public Review):

Summary:<br /> The study by He et al. investigates the relationship of an increased susceptibility of diabetes patients to COVID-19. The paper raises the possibility that hyperglycemia-induced cathepsin L maturation could be one of the driving forces in this pathology, suggesting that an increased activity of CTSL leads to accelerated virus infection rates due to an elevated processing of the SARS-CoV-2 spike protein.

In a clinical case-control study, the team found that the severity of corona infections was higher in diabetic patients, and their CTSL levels correlated well with the progression of the disease. They further showed an increase in CTSL activity in the long term as well as acute hyperglycemia. SARS-CoV-2 increasingly infected cells that were cultured in serum from diabetic patients, the same was observed using high glucose medium. No effect was observed in the medium with increased concentrations of insulin. CTSL knockout abolished the glucose-dependent increase in infection.

Increased glucose levels did not correlate with an increase in CTSL transcription. Rather He et al. could show that high glucose levels led to CTSL translocation from the ER into the lysosome. It was the glucose-dependent processing of the protease to its active form which promoted infection.

Strengths:<br /> It is a complete study starting from a clinical observation and ending on the molecular mechanism. A strength is certainly the wide selection of experiments. The clinical study to investigate the effect of glucose on CTSL concentrations in healthy individuals sets the stage for experiments in cell culture, animal models, and human tissue. The effect of CTSL knockout cell lines on glucose-induced SARS-CoV2 infection rates is convincing. Finally, the team used a combination of Western blots and confocal microscopy to identify the underlying molecular mechanisms. The authors manage to keep the diabetic condition at the center of their study and therefore extend on previous knowledge of glucose-induced CTSL activation and their consequences for COVID-19 infections. By doing so, they create a novel connection between CTSL involvement in SARS-CoV2 infections and diabetes.

Weaknesses:<br /> The authors suggest that hyperglycemia as a symptom of diabetes leads to an increased infection rate in those patients. Throughout their study, the team focuses on two select symptoms of a diabetic condition, hyperglycemia and hyperinsulinemia. The team acknowledges in the discussion that there could be various other reasons. Hyperglycemia can lead to metabolic acidosis and a shift in blood pH. As CTSL activity is highly dependent on pH, it would have been crucial to include this parameter in the study.

The study rarely differentiates between cellular and extracellular CTSL activity. A more detailed explanation for the connection between the intracellular CTSL and serum CTSL in diabetic individuals, presumably via lysosomal exocytosis, could be helpful with regard to the final model to give a more complete picture.

In the early result section, an effect of hyperglycemia on total CTSL concentrations is described, but the data is not very convincing. Over the course of the manuscript, the hypothesis shifts increasingly towards an increase in protease trans-localization and processing to the active form rather than a change in total protease amounts. The overall importance of CTSL concentrations remains questionable.

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors hypothesized that individuals with diabetes have elevated blood CTSL levels, which facilitates SARS-CoV-2 infection. The authors conducted in vitro experiments, revealing that elevated glucose levels promote SARS-CoV-2 infection in wild-type cells. In contrast, CTSL knockout cells show reduced susceptibility to high glucose-promoted effects. Additionally, the authors utilized lung tissue samples obtained from both diabetic and non-diabetic patients, along with db/db diabetic and control mice. Their findings indicate that diabetic conditions lead to an elevation in CTSL activity in both humans and mice.

Strengths:<br /> The authors have effectively met their research objectives, and their conclusions are supported by the data presented. Their findings suggest that high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum to the lysosome, potentially contributing to diabetic comorbidities and complications.

Weaknesses:<br /> 1. In Figure 1e, the authors measured plasma levels of COVID-19 related proteins, including ACE2, CTSL, and CTSB, in both diabetic and non-diabetic COVID-19 patients. Notably, only CTSL levels exhibited a significant increase in diabetic patients compared to non-diabetic patients, and these levels varied throughout the course of COVID-19. Given that the diabetes groups encompass both male and female patients, it is essential to ascertain whether the authors considered the potential impact of gender on CTSL levels. The diabetes groups comprised a higher percentage of male patients (61.3%) compared to the non-diabetes group, where males constituted only 38.7%.

2. Lines 145-149: "The results showed that WT Huh7 cell cultured in high glucose medium exhibited a much higher infective rate than those in low glucose medium. However, CTSL KO Huh7 cells maintained a low infective rate of SARS-CoV-2 regardless of glucose or insulin levels (Fig. 3f-h). Therefore, hyperglycemia enhanced SARS-CoV-2 infection dependent on CTSL." However, this evidence may be insufficient to support the claim that hyperglycemia enhances SARS-CoV-2 infection dependent on CTSL. The human hepatoma cell line Huh7 might not be an ideal model to validate the authors' hypothesis regarding high blood glucose promoting SARS-CoV-2 infection through CTSL.

3. The Abstract and Introduction sections lack effective organization.

Reviewer #1 (Public Review):

Summary:<br /> This important study provides a comprehensive evaluation of skeletal muscle mitochondrial function and remodeling in a genetically engineered mouse model of pancreatic cancer cachexia. The study builds upon and extends previous findings that implicate mitochondrial defects in the pathophysiology of cancer cachexia. The authors demonstrate that while the total quantity of mitochondria from skeletal muscles of mice with pancreatic cancer cachexia is similar to controls, mitochondria were elongated with disorganized cristae, and had reduced oxidative capacity. The mitochondrial dysfunction was not associated with exercise-induced metabolic stress (insufficient ATP production), suggesting compensation by glycolysis or other metabolic pathways. However, mitochondrial dysfunction can lead to increased production of ROS/oxidative stress and would be expected to interfere with carbohydrate and lipid metabolism, events that are linked to cancer-induced muscle loss. The data are convincing and were collected and analyzed using state-of-the-art techniques, with unbiased proteomics and transcriptomics analyses supporting most of their conclusions.

Additional Strengths:<br /> The authors utilize a genetically engineered mouse model of pancreatic cancer which recapitulates key aspects of human PDAC including the development of cachexia, making the model highly appropriate and translational.

The authors perform transcriptomic and proteomics analyses on the same tissue, providing a comprehensive analysis of the transcriptional networks and protein networks changed in the context of PDAC cachexia.

Weaknesses:<br /> The authors refer to skeletal muscle wasting induced by PDAC as sarcopenia. However, the term sarcopenia is typically reserved for the loss of skeletal muscle mass associated with aging.

In Figure 2, the MuRF1 IHC staining appears localized to the extracellular space surrounding blood vessels and myofibers-which causes concern as to the specificity of the antibody staining. MuRF1, as a muscle-specific E3 ubiquitin ligase that degrades myofibrillar proteins, would be expected to be expressed in the cytosol of muscle fibers.

Disruptions to skeletal muscle metabolism in PDAC mice are predicted based on mitochondrial dysfunction and the transcriptomic and proteomics data. The manuscript could therefore be strengthened by additional measures looking at skeletal muscle metabolites, or linking the findings to previous work that has looked at the skeletal muscle metabolome in related models of PDAC cachexia (Neyroud et al., 2023).

Reviewer #2 (Public Review):

The present work analyzed the mitochondrial function and bioenergetics in the context of cancer cachexia induced by pancreatic cancer (PDAC). The authors used the KIC transgenic mice that spontaneously develop PDAC within 9-11 weeks of age. They deeply characterize bioenergetics in living mice by magnetic resonance (MR) and mitochondrial function/morphology mainly by oxygraphy and imaging on ex vivo muscles. By MR they found that phosphocreatine resynthesis and maximal oxidative capacity were reduced in the gastrocnemius muscle of tumor-bearing mice during the recovery phase after 6 minutes of 1 Hz electrical stimulation while pH was reduced in muscle during the stimulation time. By oxygraphy, the authors showed a decrease in basal respiration, proton leak, and maximal respiration in tumor-bearing mice that was associated with the decrease of complex I, II, and IV activity, a reduction of OXPHOS proteins, mitochondrial mass, mtDNA, and to several morphological alterations of mitochondrial shape. The authors performed transcriptomic and proteomic analyses to get insights into mitochondrial defects in the muscles of PDAC mice. By IPA analyses on transcriptomics, they found an increase in the signature of protein degradation, atrophy, and glycolysis and a downregulation of muscle function. Focusing on mitochondria they showed a downregulation mainly in OXPHOS, TCA cycle, and mitochondrial dynamics genes and upregulation of glycolysis, ROS defense, mitophagy, and amino acid metabolism. IPA analysis on proteomics revealed major changes in muscle contraction and metabolic pathways related to lipids, protein, nucleotide, and DNA metabolism. Focusing on mitochondria, the protein changes mainly were related to OXPHOS, TCA cycle, translation, and amino acid metabolism.

The major strength of the paper is the bioenergetics and mitochondrial characterization associated with the transcriptomic and proteomic analyses in PDAC mice that confirmed some published data of mitochondrial dysfunction but underlined some novel metabolic insights such as nucleotide metabolism.

There are minor weaknesses related to some analyses on mitochondrial proteins and to the fact that proteomic and transcriptomic comparison may be problematic in catabolic conditions because some gene expression is required to maintain or re-establish enzymes/proteins that are destroyed by the proteolytic systems (including the autophagy proteins and ubiquitin ligases). The authors should consider the following points.

Point1. The authors used the name sarcopenia as synonymous with muscle atrophy. However, sarcopenia clearly defines the disease state (disease code: ICD-10-CM (M62.84)) of excessive muscle loss and force drop during ageing (Ref: Anker SD et al. J Cachexia Sarcopenia Muscle 2016 Dec;7(5):512-514.). Therefore, the word sarcopenia must be used only when pathological age-related muscle loss is the subject of study. Sarcopenia can be present in cancer patients who also experience cachexia, however since the age of tumor-bearing mice in this study is 7-9 weeks old, the authors should refrain from using sarcopenia and instead replace it with the words muscle atrophy/ muscle wasting/muscle loss.

Point2. Most of the analyses of mitochondrial function are appropriate. However, the methodological approach to determining mitochondrial fusion and fission machinery shown in Fig. 5F is wrong. The correct way is to normalize the OPA1, MFn1/2 on mitochondrial proteins such as VDAC/porin. In fact, by loading the same amount of total protein (see actin in panel 5F) the difference between a normal and a muscle with enhanced protein breakdown is lost. In fact, we should expect a decrease in actin level in tumor-bearing mice with muscle atrophy while the blots clearly show the same level due to the normalization of protein content. Moreover, by loading the same amount of proteins in the gel, the atrophying muscle lysates become enriched in the proteins/organelles that are less affected by the proteolysis resulting in an artefactual increase. The correct way should be to lyse the whole muscle of control and tumor-bearing mice in an identical volume and to load in western blot the same volume between control cachectic muscles. Alternatively, the relative abundance of mitochondrial shaping proteins related to mitochondrial transmembrane or matrix proteins (mito mass) should compensate for the loading normalization. Because the authors showed elongated mitochondria despite mitophagy genes being up, fragmentation may be altered. Moreover, DNM1l gene is suppressed and therefore DRP1 protein must be analyzed. Finally, OPA 1 protein has different isoforms due to the action of proteases like OMA1, and YME1L that elicit different functions being the long one pro-fusion while the short ones do not. The authors must quantify the long and short isoforms of OPA1.

Point3. The comparison of proteomic and transcriptomic profiles to identify concordance or not is problematic when atrophy programs are induced. In fact, most of the transcriptional-dependent upregulation is to preserve/maintain/reestablish enzymes that are consumed during enhanced protein breakdown. For instance, the ubiquitin ligases when activated undergo autoubiquitination and proteasome degradation. The same happens for several autophagy-related genes belonging to the conjugation system (LC3, Gabarap), the cargo recognition pathways (e.g. Ubiquitin, p62/SQSTM1) and the selective autophagy system (e.g. BNIP3, PINK/PARKIN) and metabolic enzymes (e.g. GAPDH, lipin). Finally, in case identical amounts of proteins have been loaded in mass spec the issues rise in point 2 of selective enrichment should be considered. Therefore, when comparing proteomic and transcriptomic these issues should be considered in discussion.

Reviewer #1 (Public Review):

The study is highly interesting and the applied methods are target-oriented. The biophysical characterization of viable N-protein species and several representative N-protein mutants is supported by the data, including polarity, hydrophobicity, thermodynamic stability, CD spectra, particle size, and especially protein self-association. The physicochemical parameters for viable N-protein and related coronavirus are described for comparison in detail. However, the conclusion becomes less convincing that the interaction of peptides or motifs was judged by different biophysical results, with no more direct data about peptide interaction. Additionally, the manuscript could benefit from more results involving peptide interaction to support the author's opinions or make expression more accurate when concerning the interaction of motifs. Although the authors put a lot of effort into the study, there are still some questions to answer.

Reviewer #2 (Public Review):

Summary:<br /> This work focuses on the biochemical features of the SARS-CoV-2 Nucleocapsid (N) protein, which condenses the large viral RNA genome inside the virus and also plays other roles in the infected cell. The N protein of SARS-CoV-2 and other coronaviruses is known to contain two globular RNA-binding domains, the NTD and CTD, flanked by disordered regions. The central disordered linker is particularly well understood: it contains a long SR-rich region that is extensively phosphorylated in infected cells, followed by a leucine-rich helical segment that was shown previously by these authors to promote N protein oligomerization.

In the current work, the authors analyze 5 million viral sequence variants to assess the conservation of specific amino acids and general sequence features in the major regions of the N protein. This analysis shows that disordered regions are particularly variable but that the general hydrophobic and charge character of these regions are conserved, particularly in the SR and leucine-rich regions of the central linker. The authors then construct a series of N proteins bearing the most prevalent mutations seen in the Delta and Omicron variants, and they subject these mutant proteins to a comprehensive array of biophysical analyses (temperature sensitivity, circular dichroism, oligomerization, RNA binding, and phase separation).

Strengths:<br /> The results include a number of novel findings that are worthy of further exploration. Most notable are the analyses of the previously unstudied P31L mutation of the Omicron variant. The authors use ColabFold and sedimentation analysis to suggest that this mutation promotes the self-association of the disordered N-terminal region and stimulates the formation of N protein condensates. Although the affinity of this interaction is low, it seems likely that this mutation enhances viral fitness by promoting N-terminal interactions. The work also addresses the impact of another unstudied mutation, D63G, that is located on the surface of the globular NTD and has no significant effect on the properties analyzed here, raising interesting questions about how this mutation enhances viral fitness. Finally, the paper ends with studies showing that another common mutant, R203K/G204R, disrupts phase separation and might thereby alter N protein function in a way that enhances viral fitness.

Weaknesses:<br /> In general, the results in the paper confirm previous ideas about the role of N protein regions. The key novelty of the paper lies in the identification of point mutations, notably P13L, that suggest previously unsuspected functions of the N-terminal disordered region in protein oligomerization. The paper would benefit from further exploration of these possibilities.

Reviewer #3 (Public Review):

Nguyen, Zhao, et al. used bioinformatic analysis of mutational variants of SARS-CoV-2 Nucleocapsid (N) protein from the large genomic database of SARS-CoV-2 sequences to identify domains and regions of N where mutations are more highly represented and computationally determined the effects of these mutations on the physicochemical properties of the protein. They found that the intrinsically disordered regions (IDRs) of N protein are more highly mutated than structured regions and that these mutations can lead to higher variability in the physical properties of these domains. These computational predictions are compared to in vitro biophysical experiments to assess the effects of identified mutations on the thermodynamic stability, oligomeric state, particle formation, and liquid-liquid phase separation of a few exemplary mutants.

The paper is well-written and easy to follow, and the conclusions drawn are supported by the evidence presented. The analyses and conclusions are interesting and will be of value to virologists, cell biologists, and biophysicists studying SARS-CoV-2 function and assembly. It would be nice if some further extrapolation or comments could be made regarding the effects of the observed mutations on the in vivo behavior and properties of the virus, but I appreciate that this is much higher-order than could be addressed with the approaches employed here.

Reviewer #1 (Public Review):

This study offers valuable insights into host-virus interactions, emphasizing the adaptability of the immune system. Readers should recognize the significance of MDA5 in potentially replacing RIG-I and the adversarial strategy employed by 5'ppp-RNA SCRV in degrading MDA5 mediated by m6A modification in different species, further indicating that m6A is a conservational process in the antiviral immune response.

However, caution is warranted in extrapolating these findings universally, given the dynamic nature of host-virus dynamics. The study provides a snapshot into the complexity of these interactions, but further research is needed to validate and extend these insights, considering potential variations across viral species and environmental contexts.

Reviewer #2 (Public Review):

This manuscript by Geng et al. aims to demonstrate that MDA5 compensates for the loss of RIG-I in certain species, such as teleofish miiuy croacker. The authors use siniperca cheats rhabdovirus (SCRV) and poly(I:C) to demonstrate that these RNA ligands induce an IFN response in an MDA5-dependent manner in m.miiuy derived cells. Furthermore, they show that MDA5 requires its RD domain to directly bind to SCRV RNA and to induce an IFN response. They use in vitro synthesized RNA with a 5'triphosphate (or lacking a 5'triphosphate as a control) to demonstrate that MDA5 can directly bind to 5'-triphosphorylated RNA. The second part of the paper is devoted to m6A modification of MDA5 transcripts by SCRV as an immune evasion strategy. The authors demonstrate that the modification of MDA5 with m6A is increased upon infection and that this causes increased decay of MDA5 and consequently a decreased IFN response.

The key message of this paper, i.e. MDA5 can sense 5'-triphosphorylated RNA and thereby compensate for the loss of RIG-I, is novel and interesting, yet there is insufficient evidence provided to prove this hypothesis. Most importantly, it is crucial to test the capacity of in vitro synthesized 5'-triphosphorylated RNA to induce an IFN response in MDA5-sufficient and -deficient cells. In addition, a number of important controls are missing, as detailed below. The authors describe an interaction between MDA5 and STING which, if true, is very interesting. However, the functional implications of this interaction are not further investigated in the manuscript. Is STING required to relay signalling downstream of MDA5? The second part of the paper is quite distinct from the first part. The fact that MDA5 is an interferon-stimulated gene is not mentioned and complicates the analyses (i.e. is there truly more m6A modification of MDA5 on a per molecule basis, or is there simply more total MDA5 and therefore more total m6A modification of MDA5).

Finally, it should be pointed out that several figures require additional labels, markings, or information in the figure itself or in the accompanying legend to increase the overall clarity of the manuscript. There are frequently details missing from figures that make them difficult to interpret and not self-explanatory. These details are sometimes not even found in the legend, only in the materials and methods section. The manuscript also requires extensive language editing by the editorial team or the authors.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors investigated the interaction between the pattern recognition receptor MDA5 and 5'ppp-RNA in a teleost fish called Miiuy croaker. They claimed that MDA5 can replace RIG-I in sensing 5'ppp-RNA of Siniperca cheats rhabdovirus (SCRV) in the absence of RIG-I in Miiuy croaker. The recognition of MDA5 to 5'ppp-RNA was also observed in the chicken (Gallus gallus), a bird species that lacks RIG-I. Additionally, they reported that the function of MDA5 can be impaired through m6A-mediated methylation and degradation of MDA5 mRNA by the METTL3/14-YTHDF2/3 regulatory network in Miiuy croaker under SCRV infection. This impairment weakens the innate antiviral immunity of fish and promotes the immune evasion of SCRV.

Strengths:<br /> These findings provide insights into the adaptation and functional diversity of innate antiviral activity in vertebrates.

Weaknesses:<br /> However, there are some major and minor concerns that need to be further addressed. Addressing these concerns will help the authors improve the quality of their manuscript.

One significant issue with the manuscript is that the authors claim to be investigating the role of MDA5 as a substitute for RIG-I in recognizing 5'ppp-RNA, but their study extends beyond this specific scenario. Based on my understanding, it appears that sections 2.2, 2.3, 2.5, 2.6, and 2.7 do not strictly adhere to this particular scenario. Instead, these sections tend to investigate the functional involvement of Miiuy croaker MDA5 in the innate immune response to viral infection. Furthermore, the majority of the data is focused on Miiuy croaker MDA5, with only a limited and insufficient study on chicken MDA5. Consequently, the authors cannot make broad claims that their research represents events in all RIG-I deficient species, considering the limited scope of the species studied.

The current title of the article does not align well with its actual content. It is recommended that the focus of the research be redirected to the recognition function and molecular mechanism of MDA5 in the absence of RIG-I concerning 5'ppp-RNA. This can be achieved through bolstering experimental analysis in the fields of biochemistry and molecular biology, as well as enhancing theoretical research on the molecular evolution of MDA5. It is advisable to decrease or eliminate content related to m6A modification.

Additionally, the main body of the writing contains several aspects that lack rigor and tend to exaggerate, necessitating significant improvement.

Joint Public Review

The present study focuses on the structure and function of human PURA, a regulator of gene transcription and mRNA transport and translation whose mutation causes the neurodevelopmental PURA syndrome, characterized by developmental delay, intellectual disability, hypotonia, epileptic seizures, a.o. deficits. The authors combined structural biology, molecular dynamics simulation, and various cell biological assays to study the effects of disease-causing PURA mutations on protein structure and function. The corresponding data reveal a highly dynamic PURA structure and show that disease-related mutations in PURA cause complex defects in folding, DNA-unwinding activity, RNA binding, dimerization, and partitioning into processing bodies. These findings provide first insights into how very diverse PURA mutations can cause penetrant molecular, cellular, and clinical defects. This will be of substantial interest to cell biologists, neurogeneticists, and neurologists alike.

A particular strength of the present study is the structural characterization of human PURA, which is a challenging target for structural biology approaches. The molecular dynamics simulations are state-of-the-art, allowing a statistically meaningful assessment of the differences between wild-type and mutant proteins. The functional consequences of PURA mutations at the cellular level are fascinating, particularly the differential compartmentalization of wild-type and mutant PURA variants into certain subcellular condensates.

Weaknesses that warrant rectification relate to (i) the interpretation of statistically non-significant effects seen in the molecular dynamics simulations, (ii) the statistical analysis of the differential compartmentalization of PURA variants into processing bodies vs. stress granules, and (iii) the documentation of protein expression levels and knock-down efficiencies.

Reviewer #1 (Public Review):

Summary:<br /> Tian et al. describe how TIPE regulates melanoma progression, stemness, and glycolysis. The authors link high TIPE expression to increased melanoma cell proliferation and tumor growth. TIPE causes dimerization of PKM2, as well as translocation of PKM2 to the nucleus, thereby activating HIF-1alpha. TIPE promotes the phosphorylation of S37 on PKM2 in an ERK-dependent manner. TIPE is shown to increase stem-like phenotype markers. The expression of TIPE is positively correlated with the levels of PKM2 Ser37 phosphorylation in murine and clinical tissue samples. Taken together, the authors demonstrate how TIPE impacts melanoma progression, stemness, and glycolysis through dimeric PKM2 and HIF-1alpha crosstalk.

Strengths:<br /> The authors manipulated TIPE expression using both shRNA and overexpression approaches throughout the manuscript. Using these models, they provide strong evidence of the involvement of TIPE in mediating PKM2 Ser37 phosphorylation and dimerization. The authors also used mutants of PKM2 at S37A to block its interaction with TIPE and HIF-1alpha. In addition, an ERK inhibitor (U0126) was used to block the phosphorylation of Ser37 on PKM2. The authors show how dimerization of PKM2 by TIPE causes nuclear import of PKM2 and activation of HIF-1alpha and target genes. Pyridoxine was used to induce PKM2 dimer formation, while TEPP-46 was used to suppress PKM2 dimer formation. TIPE maintains stem cell phenotypes by increasing the expression of stem-like markers. Furthermore, the relationship between TIPE and Ser37 PKM2 was demonstrated in murine and clinical tissue samples.

Weaknesses:<br /> The evaluation of how TIPE causes metabolic reprogramming can be better assessed using isotope tracing experiments and improved bioenergetic analysis.

Reviewer #2 (Public Review):

In this article, Tian et al present a convincing analysis of the molecular mechanisms underpinning TIPE-mediated regulation of glycolysis and tumor growth in melanoma. The authors begin by confirming TIPE expression in melanoma cell lines and identify "high" and "low" expressing models for functional analysis. They show that TIPE depletion slows tumour growth in vivo, and using both knockdown and over-expression approaches, show that this is associated with changes in glycolysis in vitro. Compelling data using multiple independent approaches is presented to support an interaction between TIPE and the glycolysis regulator PKM2, and the over-expression of TIPE-promoted nuclear translocation of PKM2 dimers. Mechanistically, the authors also demonstrate that PKM2 is required for TIPE-mediated activation of HIF1a transcriptional activity, as assessed using an HRE-promoter reporter assay, and that TIPE-mediated PKM2 dimerization is p-ERK dependent. Finally, the dependence of TIPE activity on PKM2 dimerization was demonstrated on tumor growth in vivo and in the regulation of glycolysis in vitro, and ectopic expression of HIF1a could rescue the inhibition of PKM2 dimerization in TIPE overexpressing cells and reduced induction of general cancer stem cell markers, showing a clear role for HIF1a in this pathway. The main conclusions of this paper are well supported by data, but some aspects of the experiments need clarification and some data panels are difficult to read and interpret as currently presented.

The detailed mechanistic analysis of TIPE-mediated regulation of PKM2 to control aerobic glycolysis and tumor growth is a major strength of the study and provides new insights into the molecular mechanisms that underpin the Warburg effect in cancer cells. However, despite these strengths, some weaknesses were noted, which if addressed will further strengthen the study.

1. The analysis of patient samples should be expanded to more directly measure the relationship between TIPE levels and melanoma patient outcome and progression (primary vs metastasis), to build on the association between TIPE levels and proliferation (Ki67) and hypoxia gene sets that are currently shown.

2. The duration of the in vivo experiments was not clearly defined in the figures, however, it was clear from the tumor volume measurements that they ended well before standard ethical endpoints in some of the experiments. A rationale for this should be provided because longer-duration experiments might significantly change the interpretation of the data. For example, does TIPE depletion transiently reduce or lead to sustained reductions in tumor growth?

3. The analysis of general cancer stem cell markers is solid and interesting, however inclusion of neural crest stem cell markers that are more relevant to melanoma biology would greatly strengthen this aspect of the study.

4. The authors should take care that all data panels are clearly readable in the figures to facilitate appropriate interpretation by the reader.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript ``Self-inhibiting percolation and viral spreading in epithelial tissue' describes a model based on 5-state cellular automata of development of an infection. The model is motivated and qualitatively justified by time-resolved measurements of expression levels of viral, interferon-producing, and antiviral genes. The model is set up in such a way that the crucial difference in outcomes (infection spreading vs. confinement) depends on the initial fraction of special virus-sensing cells. Those cells (denoted as 'type a') cannot be infected and do not support the propagation of infection, but rather inhibit it in a somewhat autocatalytic way. Presumably, such feedback makes the transition between two outcomes very sharp: a minor variation in concentration of ``a' cells results in qualitative change from one outcome to another. As in any percolation-like system, the transition between propagation and inhibition of infection goes through a critical state with all its attributes. A power-law distribution of the cluster size (corresponding to the fraction of infected cells) with a fairly universal exponent and a cutoff at the upper limit of this distribution.

Strengths:<br /> The proposed model suggests an explanation for the apparent diversity of outcomes of viral infections such as COVID.

Weaknesses:<br /> Those are not real points of weakness, though I think addressing them would substantially improve the manuscript.

The key point in the manuscript is the reduction of actual biochemical processes to the NOVAa rules. I think more could be said about it, be it referring to a set of well-known connections between expression states of cells and their reaction to infection or justifying it as an educated guess.

Another aspect where the manuscript could be improved would be to look a little beyond the strange and 'not-so-relevant for a biomedical audience' focus on the percolation critical state. While the presented calculation of the precise percolation threshold and the critical exponent confirm the numerical skills of the authors, the probability that an actual infected tissue is right at the threshold is negligible. So in addition to the critical properties, it would be interesting to learn about the system not exactly at the threshold: For example, how the speed of propagation of infection depends on subcritical p_a and what is the cluster size distribution for supercritical p_a.

Reviewer #2 (Public Review):

Xu et al. introduce a cellular automaton model to investigate the spatiotemporal spreading of viral infection. In this study, the author first analyzes the single-cell RNA sequencing data from experiments and identifies four clusters of cells at 48 hours post-viral infection, including susceptible cells (O), infected cells (V), IFN-secreting cells (N), and antiviral cells (A). Next, a cellular automaton model (NOVAa model) is introduced by assuming the existence of a transient pre-antiviral state (a). The model consists of an LxL lattice; each site represents one cell. The cells change their state following the rules depending on the interaction of neighboring cells. The model introduces a key parameter, p_a, representing the fraction of pre-antiviral state cells. Cell apoptosis is omitted in the model. Model simulations show a threshold-like behavior of the final attack rate of the virus when p_a changes continuously. There is a critical value p_c, so that when p_a < p_c, infections typically spread to the entire system, while at a higher p_a > p_c, the propagation of the infected state is inhibited. Moreover, the radius R that quantifies the diffusion range of N cells may affect the critical value p_c; a larger R yields a smaller value of the critical value p_c. The structure of clusters is different for different values of R; greater R leads to a different microscopic structure with fewer A and N cells in the final state. Compared with the single-cell RNA seq data, which implies a low fraction of IFN-positive cells - around 1.7% - the model simulation suggests R=5. The authors also explored a simplified version of the model, the OVA model, with only three states. The OVA model also has an outbreak size. The OVA model shows dynamics similar to the NOVAa model. However, the change in microstructure as a function of the IFN range R observed in the NOVAa model is not observed in the OVA model.

Data and model simulation mainly support the conclusions of this paper, but some weaknesses should be considered or clarified.

1) In the automaton model, the authors introduce a parameter p_a, representing the fraction of pre-antiviral state cells. The authors wrote: ``The parameter p_a can also be understood as the probability that an O cell will switch to the N or A state when exposed to the virus of IFNs, respectively.' Nevertheless, biologically, the fraction of pre-antiviral state cells does not mean the same value as the probability that an O cell switches to the N or A state. Moreover, in the numerical scheme, the cell state changes according to the deterministic role N(O)=a and N(a)=A. Hence, the probability p_a did not apply to the model simulation. It may need to clarify the exact meaning of the parameter p_a.

2) The current model is deterministic. However, biologically, considering the probabilistic model may be more realistic. Are the results valid when the probability update strategy is considered? By the probability model, the cells change their state randomly to the state of the neighbor cells. The probability of cell state changes may be relevant for the threshold of p_a. It is interesting to know how the random response of cells may affect the main results and the critical value of p_a.

3) Figure 2 shows a critical value p_c = 27.8% following a simulation on a lattice with dimension L = 1000. However, it is unclear if dimension changes may affect the critical value.

Reviewer #3 (Public Review):

Summary:<br /> This study considers how to model distinct host cell states that correspond to different stages of a viral infection: from naïve and susceptible cells to infected cells and a minority of important interferon-secreting cells that are the first line of defense against viral spread. The study first considers the distinct host cell states by analyzing previously published single-cell RNAseq data. Then an agent-based model on a square lattice is used to probe the dependence of the system on various parameters. Finally, a simplified version of the model is explored, and shown to have some similarity with the more complex model, yet lacks the dependence on the interferon range. By exploring these models one gains an intuitive understanding of the system, and the model may be used to generate hypotheses that could be tested experimentally, telling us "when to be surprised" if the biological system deviates from the model predictions.

Strengths:<br /> - Clear presentation of the experimental findings and a clear logical progression from these experimental findings to the modeling.<br /> - The modeling results are easy to understand, revealing interesting behavior and percolation-like features.<br /> - The scaling results presented span several decades and are therefore compelling.<br /> - The results presented suggest several interesting directions for theoretical follow-up work, as well as possible experiments to probe the system (e.g. by stimulating or blocking IFN secretion).

Weaknesses:<br /> - Since the "range" of IFN is an important parameter, it makes sense to consider lattice geometries other than the square lattice, which is somewhat pathological. Perhaps a hexagonal lattice would generalize better.

- Tissues are typically three-dimensional, not two-dimensional. (Epithelium is an exception). It would be interesting to see how the modeling translates to the three-dimensional case. Percolation transitions are known to be very sensitive to the dimensionality of the system.

- The fixed time-step of the agent-based modeling may introduce biases. I would consider simulating the system with Gillespie dynamics where the reaction rates depend on the ambient system parameters.

- Single-cell RNAseq data typically involves data imputation due to the high sparsity of the measured gene expression. More information could be provided on this crucial data processing step since it may significantly alter the experimental findings.

Justification of claims and conclusions:<br /> The claims and conclusions are well justified.

Reviewer #1 (Public Review):

This manuscript from Zaman et al., investigates the role of cKit and Kit ligand in inhibitory synapse function at molecular layer interneuron (MLI) synapses onto cerebellar Purkinje cells (PC). cKit is a receptor tyrosine kinase expressed in multiple tissues, including select populations of neurons in the CNS. cKIt is activated by Kit ligand, a transmembrane protein typically expressed at the membrane of connected cells. A strength of this paper is the use of cell-specific knockouts of cKit and Kit ligand, in MLIs and PCs, respectively. In both cases, the frequency of spontaneous or miniature (in the presence of TTX) IPSCs was reduced. This suggests either a reduction in the number of functional inhibitory release sites or reduced release probability. IPSCs evoked by electrical stimulation in the molecular layer showed no change in paired-pulse ratio, indicating release probability is not changed in the cKit KO, and favoring a reduction in the number of release sites. Changes in IPSC amplitude were more subtle, with some analyses showing a decrease and others not. These data suggest that disruption of the cKit-Kit ligand complex reduces the number of functional synapses with only minor changes in synapse strength.

Reviewer #2 (Public Review):

In their study, Zaman et al. demonstrate that deletion of either the receptor tyrosine kinase Kit from cerebellar interneurons or the kit ligand (KL) from Purkinje cells reduces the inhibition of Purkinje cells. They delete Kit or KL at different developmental time points, illustrating that Kit-KL interactions are not only required for developmental synapse formation but also for synapse maintenance in adult animals. The study is interesting as it highlights a molecular mechanism for the formation of inhibitory synapses onto Purkinje cells.

The tools generated, such as the floxed Kit mouse line and the virus for Kit overexpression, may have broader applications in neuroscience and beyond.

One general weakness is that Kit expression is not limited to molecular layer interneurons but also extends to the Purkinje layer and Golgi interneurons. But this expression does not conflict with the principal conclusions, as Purkinje layer interneurons form few or no synapses onto Purkinje cells.

In summary, the data support the hypothesis that the interaction between Kit and KL between cerebellar Molecular Layer Interneurons and Purkinje Cells plays a crucial role in promoting the formation and maintenance of inhibitory synapses onto PCs. This study provides valuable insights that could inform future investigations on how this mechanism contributes to the dynamic regulation of Purkinje cell inhibition across development and its impact on mouse behavior.

Reviewer #3 (Public Review):

Summary: Bidirectional transsynaptic signaling via cell adhesion molecules and cell surface receptors contributes to the remarkable specificity of synaptic connectivity in the brain. Zaman et al., investigates how the receptor tyrosine kinase Kit and its trans-cellular kit ligand regulate molecular layer interneuron (MLI)- Purkinje cell (PC) connectivity in the cerebellum. Presynaptic Kit is specific for MLIs, and forms a trans-synaptic complex with Kit ligand in postsynaptic PC cells. The authors begin by generating Kit cKOs via an EUCOMM allele to enable cell-type specific Kit deletion. They cross this Kit cKO to the MLI-specific driver Pax2-Cre and conduct validation via Kit IHC and immunoblotting. Using this system to examine the functional consequences of presynaptic MLI Kit deletion onto postsynaptic PC cells, they record spontaneous and miniature synaptic currents from PC cells and find a selective reduction in IPSC frequency. Deletion of Kit ligand from postsynaptic PC cells also results in reduced IPSC frequency, together supporting that this trans-synaptic complex regulates GABAergic synaptic formation or maturation. The authors then show that sparse Kit ligand overexpression in PCs decreases neighboring uninfected control sIPSCs in a potential competitive manner.

Strengths: Overall, the study addresses an important open question, the data largely supports the authors conclusions, the experiments appear well-performed, and the manuscript is well-written. I just have a few suggestions to help shore up the author's interpretations and improve the study.

Weaknesses:

The strong decrease in sIPSC frequency and amplitude in control uninfected cells in Figure 4 is surprising and puzzling. The competition model proposed is one possibility, and I think the authors need to do additional experiments to help support or refute this model. The authors can conduct similar synaptic staining experiments as in Fig S4 but in their sparse infection paradigm, comparing synapses on infected and uninfected cells. Additional electrophysiological parameters in the sparse injection paradigm, such as mIPSCs or evoked IPSCs, would also help support their conclusions.

The authors should validate KL overexpression and increased cell surface levels using their virus to support their overexpression conclusions.

Reviewer #1 (Public Review):

Summary:

The main goal of the authors was to study the testis-specific role of the protein FBXO24 in the formation and function of the ribonucleoprotein granules (membraneless electron-dense structures rich in RNAs and proteins).

Strengths:

The wide variety of methods used to support their conclusions (including transgenic models)

Weaknesses:

The lack of specific antibodies against FBXO24. Some of the experiments showing a specific phenotype are descriptive and lack of logical explanation about the possible mechanism (i.e. AR or the tail structure).

Questions:

The paper is excellent and employs a wide variety of methods to substantiate the conclusions. I have very few questions to ask:

1) KO mice cannot undergo acrosome reaction (AR) even spontaneously. How do you account for this, given that no visible defects were observed in the acrosome?

2) KO sperm are unable to migrate in the female tract, and, more intriguingly, they do not pass through the utero-tubal junction (UTJ). The levels of ADAM3 are normal, suggesting that the phenotype is influenced by other factors. The authors should investigate the levels of Ly6K since mice also exhibit the same phenotype but with normal levels of ADAM3.

3) In Figure 4A, the authors assert that "RBGS Tg mice revealed that mitochondria were abnormally segmented in Fbxo24 KO spermatozoa." I am unable to discern this from the picture shown in that panel. Could you please provide a more detailed explanation or display the information more explicitly?

Reviewer #2 (Public Review):

Summary:

The manuscript by Kaneda et al "FBXO24 ensures male fertility by preventing abnormal accumulation 2 of membraneless granules in sperm flagella" is a significant paper on the role of FBXO24 in murine male germ cell development and sperm ultrastructure and function. The body of experimental evidence that the authors present is extraordinarily strong in both breadth and depth. The authors investigate the protein's functions in male germ cells and sperm using a wide variety of approaches but focusing predominantly on their novel mouse model featuring deletion of the Fbxo24 gene and its product. Using this mouse, and a cross of it with another model that expresses reporters in the head and midpiece, they logically build from one experiment to the next. Together, their data show that this protein is involved in the regulation of membraneless electron-dense structures; loss of FBXO24 led to an accumulation of these materials and defects in the sperm flagellum and fertilizing ability. Interestingly, the authors found that several of the best-known components of electron-dense ribonucleoprotein granules that are found in the intermitochondrial cement and chromatoid body were not disrupted in the Fbxo24 knockout, suggesting that the electron-dense material and these structures are not all the same, and the biology is more complicated than some might have thought. They found evidence for the most changes in IPO5 and KPNB1, and biochemical evidence that FBXO24 and IPO5 could interact.

Strengths:

The authors are to be commended for the thoroughness of their experimental approaches and the extent to which they investigated impacts on sperm function and potential biochemical mechanisms. Very briefly, they start by showing that the Fbxo24 message is present in spermatids and that the protein can interact with SKP1, in a way that is dependent on its F-box domain. This points toward a potential function in protein degradation. To test this, they next made the knockout mouse, validated it, and found the males to be sterile, although capable of plugging a female. Looking at the sperm, they identified a number of ultrastructural and morphological abnormalities, which they looked at in high resolution using TEM. They also cross their model with RBGS mice so that they have reporters in both the acrosome and mitochondria. The authors test a variety of sperm functions, including motility parameters, ability to fertilize by IVF, cumulus-free IVF, zona-free-IVF, and ICSI. They found that ICSI could rescue the knockout but not other assisted reproductive technologies. Defects in male fertility likely resulted from motility disruption and failure to get through the utero-tubal junction but defects in acrosome exocytosis also were noted. The authors performed thorough investigations including both targeted and unbiased approaches such as mass spectrometry. These enabled them to show that although the loss of the FBXO24 protein led to more RNA and elevated levels of some proteins, it did not change others that were previously identified in the electron-dense RNP material.

The manuscript will be highly significant in the field because the exact functions of the electron-dense RNP materials have remained somewhat elusive for decades. Much progress has been made in the past 15 years but this work shows that the situation is more complex than previously recognized. The results show critical impacts of protein degradation in the differentiation process that enables sperm to change from non-descript round cells into highly polarized and compartmentalized mature sperm, with an equally highly compartmentalized flagellum. This manuscript also sets a high bar for the field in terms of how thorough it is, which reveals wide-ranging impacts on processes such as mitochondrial compaction and arrangement in the midpiece, the correct building of the major cytoskeletal elements in the flagellum, etc.

Weaknesses:

There are no real weaknesses in the manuscript that result from anything in the control of the authors. They attempted to rescue the knockout by expressing a FLAG-tagged Fbxo24 transgene, but that did not rescue the phenotype, either because of inappropriate levels/timing/location of expression, or because of interference by the tag. They also could not make anti-FBXO24 that worked for co-immunoprecipitation experiments, so relied on the FLAG epitope, an approach that successfully showed co-IP with IPO5 and SKP1.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors found that FBXO24, a testis-enriched F-box protein, is indispensable for male fertility. Fbxo24 KO mice exhibited malformed sperm flagellar and compromised sperm motility.

Strengths:

The phenotype of Fbxo24 KO spermatozoa was well analyzed.

Weaknesses:

The authors observed numerous membraneless electron-dense granules in the Fbxo24 KO spermatozoa. They also showed abnormal accumulation of two importins, IPO5 and KPNB1, in the Fbxo24 KO spermatozoa. However, the data presented in the manuscript do not support the conclusion that FBXO24 ensures male fertility by preventing the abnormal accumulation of membraneless granules in sperm flagella, as indicated in the manuscript title.

Reviewer #1 (Public Review):

Summary:<br /> This study used a unique acute HIV-1 infection cohort, RV217, to study the evolution of transmitted founder viral Envelope sequences under nascent immune pressure. The striking feature of the RV217 cohort is the ability to detect viremia in the first week of infection, which can be followed at discrete Fiebig stages over long time intervals. This study evaluated Env sequences at 1 week, 4 weeks, and 24 weeks to provide a picture of viral and immunological co-evolution from Fiebig Stage I (1 week), Fiebig Stages IV (4 weeks), and Fiebig Stage VI (>24 weeks). This study design enabled lineage tracing of viral variants from a single transmitted founder (T/F) over the Fiebig Stages I, IV, and VI under nascent immune pressure generated in response to the T/F virus and its subsequent mutants.

Strengths:<br /> As expected, there were temporal differences in the appearance of virus quasispecies among the individuals, which were located predominantly in solvent-exposed residues of Env, which is consistent with prior literature. Interestingly, two waves of antibody reactivity were observed for variants with mutations in the V2 region that harbors V2i and V2p epitopes correlated with protection in the RV144 clinical trial. Two waves of antibody response, detected by SPR, were observed, with the first wave being predominated by antibodies specific for the T/F07 V2 epitope associated with H173 located on the C β-strand in the V2 region. The second wave was dominated by antibodies specific for an H to Y mutation at 173 that emerged due to antibody-mediated pressure to the original H173 virus. This is a remarkable finding in three ways.

First, the mutation is in the C β-strand, an unlikely paratope contact residue, as this region of the V2 loop is shielded by glycans in Env trimer structures with full glycan representation (see PDB:5t3x). The structure used for modeling in the current study was an earlier structure, PDB:4TVP, that had many truncated glycans. This does not detract from the finding that the H173Y mutation likely causes a conformational shift from a more rigid helical/coil conformation to a more dynamic conformation with a β-stranded and β-sheet core preference as indicated by the literature and by the MD simulations carried out by the authors. This observation suggests that using V2 scaffolds with both the H173 and H173Y variants will increase the breadth of potentially protective antibody responses to HIV-1, as indicated in reference 42, cited by the authors. Interestingly, the H173Y mutation abrogates reactivity to mAb CH58 and attenuates reactivity to mAb CH59 isolated from RV144 volunteers. These mAbs recognize conformationally distinct V2 epitopes, adding further credence to the conclusion that the H173Y mutation results in a conformational switch of the V2 region.

Second, the H173Y mutation affects the conformation of V2 epitopes recognized by mAbs that do not neutralize T/F HIV-1 while mediating potent ADCC. The ADCC data in the manuscript provides strong support for this hypothesis and augers for further exploration of the V2 epitopes as HIV-1 vaccine targets.<br /> Third, it is striking that immunogens based on the H173Y mutation successfully recapitulated the observed human antibody responses in wild-type Balb/c mice. The investigators used their extensive knowledge of V2 structures and scaffold-immunogens to create the library of constructs used for this study. In this case, the ΔDSV mutation increased the breadth and magnitude of the murine antibody responses.

Weaknesses:<br /> 1. V2 epitopes exhibit properties of CD4i epitopes in that they are largely absent from the native Env surface, probably by glycan-occlusion, but become more exposed upon CD4 binding. Although the V2-scaffolds were produced in GnTi- cells to produce high-mannose proteins, it appears that no systematic analysis of glycan content or structure was carried out save for enzymatic deglycosylation of the constructs to sharpen bands on SDS-PAGE gels. It would be helpful if the authors could comment on how the lack of this information might impact their conclusions.

2. Similarly, the MD simulations appear to be performed without taking glycan structure/occupancy.

Reviewer #2 (Public Review):

Summary:<br /> In this study, researchers aimed to understand how a transmitted/founder (T/F) HIV virus escapes host immune pressure during early infection. They focused on the V1V2 domain of the HIV-1 envelope protein, a key determinant of virus escape. The study involved four participants from the RV217 Early Capture HIV Cohort (ECHO) project, which allowed tracking HIV infection from just days after infection.

The study identified a significant H173Y escape mutation in the V2 domain of a T/F virus from one participant. This mutation, located in the relatively conserved "C" β-strand, was linked to viral escape against host immune pressure. The study further investigated the epitope specificity of antibodies in the participant's plasma, revealing that the H173Y mutation played a crucial role in epitope switching during virus escape. Monoclonal antibodies from the RV144 vaccine trial, CH58, and CH59, showed reduced binding to the V1V2-Y173 escape variant. Additionally, the study examined antibody-dependent cellular cytotoxicity (ADCC) responses and found resistance to killing in the Y173 mutants. The H173Y mutation was identified as the key variant selected against the host's immune pressure directed at the V2 domain.

The researchers hypothesized that the H173Y mutation caused a structural/conformational change in the C β-strand epitope, leading to viral escape. This was supported by molecular dynamics simulations and structural modeling analyses. They then designed combinatorial V2 immunogen libraries based on natural HIV-1 sequence diversity, aiming to broaden antibody responses. Mouse immunizations with these libraries demonstrated enhanced recognition of diverse Env antigens, suggesting a potential strategy for developing a more effective HIV vaccine.

In summary, the study provides insights into the early evolution of HIV-1 during infection, highlighting the importance of the V1V2 domain and identifying key escape mutations. The findings suggest a novel approach for designing HIV vaccine candidates that consider the diversity of escape mutations to induce broader and more effective immune responses.

Strengths:<br /> The article presents several strengths:

1. The experimental design is well-structured, involving multiple stages from phylogenetic analyses to mouse model testing, providing a comprehensive approach to studying virus escape mutations.

2. The study utilizes a unique dataset from the RV217 Early Capture HIV Cohort (ECHO) project, allowing for the tracking of HIV infection from the very early stages in the absence of antiretroviral therapy. This provides valuable insights into the evolution of the virus.

3. The use of advanced techniques such as phylogenetic analyses, nanoscaffold technology, controlled mutagenesis, and monoclonal antibody evaluations demonstrates the application of cutting-edge methodologies in the study.

4. The research goes beyond genetic analysis and provides an in-depth characterization of the escape mutation's impact, including structural analyses through Molecular Dynamics simulations, antibody responses, and functional implications for virus survival.

5. The study provides insights into the immune responses triggered by the escape mutation, including the specificity of antibodies and their ability to recognize diverse HIV-1 Env antigens.

7. The exploration of combinatorial immunogen libraries is a strength, as it offers a novel approach to broaden antibody responses, providing a potential avenue for future vaccine design.

8. The research is highly relevant to vaccine development, as it sheds light on the dynamics of HIV escape mutations and their interaction with the host immune system. This information is crucial for designing effective vaccines that can preemptively interfere with viral acquisition.

9. The study integrates findings from virology, immunology, structural biology, and bioinformatics, showcasing an interdisciplinary approach that enhances the depth and breadth of the research.

10. The article is well-written, with a clear presentation of methods, results, and implications, making it accessible to both specialists and a broader scientific audience.

Weaknesses:<br /> While the article presents several strengths, it's important to consider potential weaknesses as well:

1. While the exploration of combinatorial immunogen libraries is innovative, the complexity of this approach may pose challenges in terms of practical implementation, scalability, and cost-effectiveness in large-scale vaccine development.

2. The article will benefit from a more explicit discussion of the limitations and potential drawbacks of the methodologies employed. For example, structural analyses, such as Molecular Dynamics simulations, involve complex computational models. The accuracy and reliability of these simulations may vary, and uncertainties in the interpretation of structural data should be acknowledged.

The following concepts are used before they're explained. - DESYNC_FACTOR - REGEN_ADVANCE

Reviewer #1 (Public Review):

Mignerot et al. performed a Herculean effort to measure and describe natural variation in C. elegans egg-laying behavior and egg retention. The paper is well written and organized. The authors show wild strains vary in egg retention with some extremes that appear phenotypically similar to species with viviparity (or live birth / internal hatching of offspring). They previously published a rare variant in the gene kcnl-1 that plays a role in egg retention but identify common variants in this study. They classify wild strains based on egg-retention to separate out the extremely different isolates. Egg laying has been extensively studied in the laboratory strain N2, but rarely addressed in natural strains. The authors investigate egg-laying behaviors using standard assays and find that their classified egg-laying groups have differences in sub-behaviors suggesting diverse roles in the ultimate egg-laying output. Then, they turn to the egg-laying circuit using both exogenous serotonin (5-HT), 5-HT modulatory drugs (e.g. SSRIs), and even genome editing to test epistasis with the mod-5 5-HT reuptake. The effects of 5-HT modulation and mutants are not predictive based on the basal behaviors and egg-retention phenotypes with the most extreme egg-retention strains differing in their responses. Interestingly, strains with more egg retention have decreased fitness (in their laboratory) measures but also provide a protective environment for offspring when exposed to common "natural" stressors. Their final conclusion that egg retention could be a trade-off between antagonistic effects of maternal vs. offspring fitness is supported well and sets the stage for future mechanistic studies across Caenorhabditis.

Reviewer #2 (Public Review):

Mignerot et al. study variations in egg retention in a large set of wild C. elegans strains use detailed analysis of a subset of these strains to those that these variations in egg retention appear to arise from variations in egg-laying behavior. The authors then take advantage of the advanced genetic technology available in C. elegans, and the fact that the cellular and molecular mechanisms that drive egg-laying behavior in the N2 laboratory strain of C. elegans have been studied intensely for decades. Thus, they demonstrate that variations multiple genetic loci appear to drive variations in egg laying across species, although they are unable to identify the specific genes that vary other than a potassium channel already identified in a previous study from some of these same authors (Vigne et al., 2021). Mignerot et al. also present evidence that variations in response of the egg-laying system to the neuromodulator serotonin appear to underlie variations in egg-laying behavior across species. Finally, the authors present a series of studies examining how the retention of eggs in utero affects the fertility and survival of mothers versus the survival of their progeny in a variety of adverse conditions, including limiting food, and the presence of acute environmental insults such as alcohol or acid. The results suggest that variations in egg-laying behavior evolved as a response to adverse environmental conditions that impose a trade-off between survival of the mothers versus their progeny.

Strengths:

The analysis of variations in egg laying by a large set of wild species significantly extends the previous work of Vigne et al. (2021), who focused on just one wild variant strain. Mignerot find that variations in egg laying are widespread across C. elegans strains and result from changes in multiple genetic loci.

To determine why various strains vary in their egg-laying behavior, the authors take advantage the genetic tractability of C. elegans and the huge body of previous studies on the cellular and molecular basis of egg-laying behavior in the laboratory N2 strain. Since serotonin is one signal that induces egg laying, the authors subject various strains to serotonin and to drugs thought to alter serotonin signaling, and they also use CRISPR induced gene editing to mutate a serotonin reuptake transporter in some strains. The results are largely consistent with the idea that variations across strains alter how the egg-laying system responds to serotonin.

The final figures in the paper presents a far more detailed analysis than did Vigne et al. (2021) of how variations in egg retention across species can affect fitness under various environmental stresses. Thus, Mignerot et al. look at competition under conditions of limiting food, and response to acute environmental insults, and compare the ability of adults, in utero eggs, and ex vivo eggs to survive. The results lead to an interesting discussion of how variations in behavior result in a trade-off in survival of mothers versus their progeny. The authors in their Discussion do a good job describing the challenges in interpreting the relevance of these laboratory results to the poorly-understood environmental conditions that C. elegans may experience in the wild. The Discussion also had an excellent section about how the ability of a single species to strongly regulate egg-laying behavior in response to its environment, and how this ability could be adaptive. Overall, these were the strongest and most interesting aspects of Mignerot et al.

Weaknesses<br /> The specific potassium channel variation studied by Vigne et al. (2021) has by far the strongest effect on egg laying seen in the Mignerot et al. study and remains the only genetic variation that has been molecularly identified. So, Mignerot et al. were not able to identify any additional specific genes that vary across species to cause changes in egg laying, and this limited their ability to generate new insights into the specific cellular and molecular mechanisms that have changed across species to result in changes in egg laying behavior.

The authors' use of drug treatments and CRISPR to alter serotonin signaling yielded some insights into mechanistic variations in how the egg-laying system functions across strains, but these experiments only allow very indirect inferences into what is going on. The analysis in Figures 4 and 5 generates a complex set of results that are not easy to interpret. The clearest result seems to be that strains carrying the KCNL-1 point mutation lay eggs poorly and exogenous serotonin inhibits rather than stimulates egg laying in these strains. This basic result was to a large extent reported previously in Vigne et al. 2021.

The analysis of how differences between strains mechanistically result in changes in egg-laying behavior and egg retention, while excellent in concept, is only modestly successful. The analysis of the temporal pattern egg-laying behavior in Figure 3B-3F is relatively weak. Whereas the state of the art in analyzing this behavior is to take videos of animals and track exactly when they lay eggs, analyzing 40 or more hours of behavior per strain, the authors used a lower-tech method of just examining how many eggs were laid within 5-minute intervals over a period of just three hours per strain. While this analysis was sufficient to demonstrate some statistically significant differences in the pattern of egg laying in some strains, it is unclear to what extent these differences could be sufficient to explain the differences in accumulation of unlaid eggs between these strains. In contrast, the variations in age of the onset of egg-laying behavior in Fig 3G and 3H between strains were very strong and may be more likely to reflect mechanistic differences in how egg laying is controlled that could result in the differences in retention of unlaid eggs seen among the strains tested. In the Discussion, the authors extensively write about the work of the Collins lab showing that retained eggs stretch the uterus to produce a signal that activates egg-laying muscles. Could it be that really this mechanism is the main one that varies between strains, leading to the observed variations in time to laying the first egg as well as variations in the number of retained eggs throughout adulthood?

Reviewer #1 (Public Review):

Koumoundourou et al., identify a pathway downstream of Bcl11b that controls synapse morphology and plasticity of hippocampal mossy fiber synapses. Using an elegant combination of in vivo, ex vivo, and in vitro approaches, the authors build on their previous work that indicated C1ql2 as a functional target of Bcl11b (De Bruyckere et al., 2018). Here, they examine the functional implications of C1ql2 at MF synapses in Bcl11b cKO mice and following C1ql2 shRNA. The authors find that Bcl11b KO and shRNA against C1ql2 significantly reduces the recruitment of synaptic vesicles and impairs LTP at MF synapses. Importantly, the authors test a role for the previously identified C1ql2 binding partner, exon 25b-containing Nrxn3 (Matsuda et al., 2016), as relevant at MF synapses to maintain synaptic vesicle recruitment. To test this, the authors developed a K262E C1ql2 mutant that disrupts binding to Nrxn3. Curiously, while Bcl11b KO and C1ql2 KD largely phenocopy (reduced vesicle recruitment and impaired LTP), only vesicle recruitment is dependent on C1ql2-Nrxn3 interactions. These findings provide new insight into the functional role of C1ql2 at MF synapses. The authors utilize a multidisciplinary approach to convincingly demonstrate a role for C1ql2-Nrxn3(25b+) interactions for vesicle recruitment and a Nrxn3(25b+)-independent role for C1ql2 in LTP, The authors establish an important signaling pathway that offers insight into how disruptions of Bcl11b contribute to synapse dysfunction and provide a much needed advance toward understanding the functional consequences of neurexin alternative splicing.

Reviewer #2 (Public Review):

This manuscript describes experiments that further investigate the actions of the transcription factor Bcl11b in regulating mossy fiber (MF) synapses in the hippocampus. Prior work from the same group had demonstrated that loss of Bcl11b results in loss of MF synapses as well as a decrease in LTP. Here the authors focus on a target of Bcl11b a secreted synaptic organizer C1ql2 which is almost completed lost in Bcl11b KO. Viral reintroduction of C1ql2 rescues the synaptic phenotypes, whereas direct KD of C1ql2 recapitulates the Bcl1 phenotype. C1ql2 itself interacts directly with Nrxn3 and replacement with a binding deficient mutant C1q was not able to rescue the Bcl11b KO phenotype. Overall there are some interesting observations in the study, however there are also some concerns about the measures and interpretation of data.

The authors state they used a differential transcriptomic analysis to screen for candidate targets of Bcl11b, yet they do not present any details of this screen. This should be included and at the very least a table of all DE genes included. It is likely that many other genes are also regulated by Bcl11b so it would be important to the reader to see the rationale for focusing attention on C1ql2 in this study.

All viral mediated expression uses AAVs which are known to ablate neurogenesis in the DG (Johnston DOI: 10.7554/eLife.59291) through the ITR regions and leads to hyperexcitability of the dentate. While it is not clear how this would impact the measurements the authors make in MF-CA3 synapses, this should be acknowledged as a potential caveat in this study.

The authors claim that the viral re-introduction "restored C1ql2 protein expression to control levels. This is misleading given that the mean of the data is 2.5x the control (Figure 1d and also see Figure 6c). The low n and large variance are a problem for these data. Moreover, they are marked ns but the authors should report p values for these. At the least this likely large overexpression and variability should be acknowledged. In addition, the use of clipped bands on Western blots should be avoided. Please show the complete protein gel in primary figures of supplemental information.

Measurement of EM micrographs: As prior work suggested that MF synapse structure is disrupted the authors should report active zone length as this may itself affect "synapse score" defined by the number of vesicles docked. More concerning is that the example KO micrographs seem to have lost all the densely clustered synaptic vesicles that are away from the AZ in normal MF synapses e.g. compare control and KO terminals in Fig 2a or 6f or 7f. These terminals look aberrant and suggest that the important measure is not what is docked but what is present in the terminal cytoplasm that normally makes up the reserve pool. This needs to be addressed with further analysis and modifications to the manuscript.

The study also presents correlated changes in MF LTP in Bcl11b KO which are rescued by C1ql2 expression. It is not clear whether the structural and functional deficits are causally linked and this should be made clearer in the manuscript. It is also not apparent why this functional measure was chosen as it is unlikely that C1ql2 plays a direct role in presynaptic plasticity mechanisms that are through a cAMP/ PKA pathway and likely disrupted LTP is due to dysfunctional synapses rather than a specific LTP effect. The authors should consider measures that might support the role of Bcl11b targets in SV recruitment during depletion of synapses or measurements of the readily releasable pool size that would complement their finding in structural studies.

Bcl11b KO reduces the number of synapses, yet the I-O curve reported in Supp Fig 2 is not changed. How is that possible? This should be explained.

Matsuda et al DOI: 10.1016/j.neuron.2016.04.001 previously reported that C1ql2 organizes MF synapses by aligning postsynaptic kainate receptors with presynaptic elements. As this may have consequences for the functional properties of MF synapses including their plasticity, the authors should report whether they see deficient postsynaptic glutamate receptor signaling in the Bcl11b KO and rescue in the C1ql2 re-expression.

These are all addressed in the revised version.