Reviewer #1 (Public Review):

The first synapses of the pain pathway are concentrated in the superficial spinal cord dorsal horn. Here peripheral inputs are processed by local interneuron circuitry before ascending to the brain. The spinal dorsal horn is organized into lamina with the resident interneurons differentiated by their anatomy, physiological and molecular properties. Over the past decade, the restricted expression of select genes has been used to assign potential function to dorsal horn neuron "cell types". This type of work has relied on the genesis of Cre-reporter mouse strains and intersectional tools to generate mice where select sets of neurons can be activated, inhibited, or ablated. The picture that has emerged from these types of experiments is murky but favors the model where there exist genetically defined cell-types play distinct roles in the detection of painful, itchy, thermal, and mechanical stimuli under normal and pathological situations. The current work by Boyle and colleagues concerns itself with the dorsal horn neurons expressing the neuropeptide NPY. This study is directly related to previously published work that demonstrated that ablating spinal cord neurons that express Npy, including those who express this gene transiently during development, resulted in mice that had heightened touch-evoked itch that seemed different from the canonical chemical itch pathways previously identified. A major conclusion from this previous work was that other modalities were unaffected. Subsequent work built on these findings to identify the potential touch inputs and spinal neuron expressing the Npy receptor as part of a mechanical itch circuit.

This current work by Boyle and colleagues challenge challenges this view by providing evidence that in adult mice, the dorsal horn neurons expressing Npy function to broadly inhibit pain and itch. The authors use direct injection of viral vectors, chemogenetics and synaptic silencing to probe the behavioral effects of stimulating or silencing Npy-expressing dorsal horn neurons in a variety of assays under normal and pathological conditions known to produce allodynia and hyperalgesia. Overall, this is a rather carefully conducted study with the appropriate controls. The data are clear, the effect sizes robust and the presentation easy to follow. These findings challenge the conclusion that these neurons are involved selectively in mechanical itch and instead reveal a potentially clinical important group of neurons for pain.

Reviewer #2 (Public Review):

Whether and how molecularly defined neuronal groups in the spinal cord process distinct modalities are of great interest. In this study, Boyle et al. characterized roles of inhibitory neurons expressing NPY in adult mice. By using chemogenetic, electrophysiological tools and behavioral measurements, the authors discovered that activating NPY+ interneurons strongly reduced pruritogen-evoked itch and reflexive behaviors (acute nociception or under inflammation / neuropathic pain states). Silencing NPY+ spinal interneurons enhanced spontaneous and chemical itch in a GRPR+ neurons dependent manner. The authors concluded that, unlike previous findings suggesting that these neurons are selective for mechanical itch, adult NPY+ interneurons play dual roles in gating various types of itch and pain.

Strengths:

The authors performed careful characterization and comparisons between development lineage and adult spinal neurons expressing NPY. This lays the foundation of the current study. The behavioral measurements were also well designed with proper controls.

Weaknesses:

There is inadequate discussion about previous studies of NPY interneurons. Specifically, the authors should address why a more restricted subset of these neurons (this study) have broader effects than seen previously.

I cannot see the reason for including results from manipulation of Dyn+ interneurons in this paper. First, the title does not reflect roles of spinal Dyn+ population. In addition, without further experiments characterizing relationships between NPY and Dyn interneurons in modulating itch and/or nociception, Dyn datasets seem to deviate from the main theme.

While the authors provided convincing evidence that GRPR+ neurons serve as a downstream effector of NPY+ neuron evoked itch, the relationship between GRPR and NPY neurons in modulating pain is not examined. Therefore, Fig. 7B is pure speculation and should be removed.

Reviewer #3 (Public Review):

In the present study by Boyle et al., the function of NPY expressing spinal neurons in pain and itch perception is studied. While the function of these neurons has been addressed previously, the difference to previous studies is the combinatorial use of AAV encoded effectors and cre transgenic mice whereas previous studies relied on cre transgenic mice and reporter mice encoding the effector or only viruses. Boyle at al. demonstrate that their strategy enabled them to restrict the analysis to only those neurons expressing NPY in the adult mouse compared to a more heterogenous population that had been studied before. By using a combination of morphology, electrophysiology and behavioral paradigms they convincingly show that NPY neurons impact pruritoception via inhibiting GRPR neurons. Furthermore, they indicate a role of NPY neurons also in nociception as activation attenuates not only responses to acute nociceptive stimuli but also blocks inflammation or nerve injury induced mechanical and heat hypersensitivity. Selectively activating NPY neurons in vivo may therefore be a promising strategy to treat neuropathic pain.

The result of this study extends and partially contrasts previous studies. The authors argue that contrasting results may be due to the different experimental strategies (e.g. only neurons expressing NPY adult in the present study versus a more heterogeneous population before).

Overall, the experiments are convincing, and the quality of the data/figures is exceptionally high.

Reviewer #1 (Public Review):

Huang C-K. and colleagues in this work address the understudied role of environmental conditions and external forces in cell extrusion as a fundamental part of epithelial homeostasis. They suggest that hydrostatic stress plays a significant role in counteracting cell extrusion forces through the indirect regulation of the focal adhesion kinase (FAK) - protein kinase B (AKT) survival pathway. The team nicely exploits their expertise in fabricating cell culture substrates to control hydrostatic stress on a common epithelial cell model from the kidney (i.e., MDCK). This was done by creating waving surfaces with different lengths from 50µm to 200 µm, thus creating a heterogenous distribution of monolayer forces towards the substrate. Finally, using a specific inhibitor for FAK, they suggest that the survivor pathway FAK-AKT is involved in the observed phenomenon.

In conclusion, the presented data underline the importance of considering external forces and tissue geometry in regulating epithelial homeostasis and the selective transport of water and solutes. These results may have a significant impact on understanding the basic mechanisms of epithelial physiology and pathology, such as in the kidney, intestine, or retina.

Reviewer #2 (Public Review):

The paper by Huan, Yong, et al. studies epithelial cell extrusion in MDCK monolayers grown on sinusoidally wavy surfaces in varying media osmolarities, finding that both curvature and osmolarity-mediated basal hydraulic stress spatially regulate extrusion events. The authors fabricated wavy substrates of varying periods and amplitude out of PDMS (and PA hydrogels) and monitored monolayer evolution and cell extrusion over time, by combining live-cell imaging with a convolutional network-based algorithm for automatic detection of extrusions.

In general, the study has been elegantly designed, starting with convincing evidence for enhanced extrusion rates in concave valleys with respect to convex hills. Next, the authors showed that hyper-osmotic medium reduced cell extrusion rate, which was demonstrated in a variety of different media compositions (e.g. with sucrose, DMSO, or NaCl), while hypo-osmotic medium increased cell extrusion rate. Additionally, the authors applied reflection interference contrast microscopy to reveal fluid spaces between the substrate and the basal side of the monolayer, which were found to grow when media composition was altered from hyper-osmotic to normal osmotic conditions. Using a 3D traction force microscopy approach, the authors demonstrated that cells on convex regions apply a downward pointing force on the substrate, opposite to cells on the concave regions. This was linked to a larger basal separation on the concave valleys as opposed to the convex hills. Finally, the authors focussed on the FAK-Akt pathway to explore the hypothesis that basal hydraulic stress interferes with focal adhesions, leading to differences in cell extrusion rates in media of different osmolarity and on convex or concave surfaces.

Despite the host of relevant experiments and the interesting data acquired with a variety of techniques, some aspects of the manuscript would need to be strengthened or explained in more detail to better support the claims and to provide more convincing evidence.

1) The sinusoidal wavy substrate that the authors use in their investigation is interesting and relevant, but it is important to realise that this is a single-curved surface (also known as a developable surface). This means that the Gaussian curvature is zero and that monolayers need to undergo (almost) no stretching to conform to the curvature. The authors should at least discuss other curved surfaces as an option for future research, and highlight how the observations might change. Convex and concave hemispherical surfaces, for example, might induce stronger differences than observed on the sinusoidal substrates, due to potentially higher vertical resultant forces that the monolayer would experience. The authors could discuss this geometry aspect more in their manuscript and potentially link it to some other papers exploring cell-curvature interactions in more complex environments (e.g. non-zero Gaussian curvature).

2) The discussion of the experiments on PAM gels is rather limited. The authors describe that cells on the PAM gels experience fewer extrusions than on the PDMS substrates, but this is not discussed in sufficient detail (e.g. why is this the case). Additionally, the description of the 3D traction force microscopy and its validation is quite limited and should be extended to provide more convincing evidence that the measured force differences are not an artefact of the undulations of the surface.

3) The authors show nuclear deformation on the hills and use this as evidence for a resultant downward-pointing force vector. This has, indeed, also been observed in other works referenced by the authors (e.g. Werner et al.), and could be interesting evidence to support the current observations, provided the authors also show a nuclear shape on the concave and flat regions. The authors could potentially also characterise this shape change better using higher-resolution data.

4) The U-net for extrusion detection is a central tool used within this study, though the explanation and particularly validation of the tool are somewhat lacking. More clarity in the explanation and more examples of good (or bad) detections would help establish this tool as a more robust component of the data collection (on all geometries).

5) The authors study the involvement of FAK in the observed curvature-dependent and hydraulic stress-dependent spatial regulation of cell extrusion. In one of the experiments, the authors supplement the cell medium with FAK inhibitors, though only in a hyper-osmotic medium. They show that FAK inhibition counteracts the extrusion-suppressing effect of a hyper-osmotic medium. However, no data is shown on the effect of FAK inhibitors within the control medium. Would the extrusion rates be even higher then?

Reviewer #3 (Public Review):

The authors study monolayers of MDCK cells on curved surfaces. These surfaces consist of hemicylindrical valleys and hills obtained through microfabrication involving glass rods and repeated molding steps. They find higher apoptotic extrusion rates in valleys compared to hills for patterns with 25 and 50 µm curvature radii, but not in valleys of 100 µm curvature radius. By using osmotic shocks and reflection interference contrast microscopy, they identify hydraulic stress to drive cell extrusion. 3D force microscopy reveals that cytoskeletal forces point towards the substrate on hills and away from the substrate in valleys. From these observations, the authors conclude that hydraulic stress-induced cell extrusion is assisted by cytoskeletal forces in the valleys and opposed on the hills. Finally, they link the hydraulic stress to the activity of focal adhesion kinase, which in turn affects cell survival through Akt signaling.

Strengths:

This work combines a new microfabrication method with state of the art 3d force microscopy that allows the authors to study curvature-dependent cell extrusion. The application of various osmotic shocks to the system clearly identifies the role of hydraulic stress in cell extrusion. The decoupling of the main driver of cell extrusion (hydraulic stress) from its curvature-dependent modulation through cytoskeletal forces, together with the mechanical activation of apoptosis is an important new finding that significantly advances our understanding of epithelial cell extrusion and could be important during developmental processes and for maintaining intact epithelia in adult organisms.

Weaknesses:

The main weakness of this work is a lack of quantification of the hydraulic stress. Furthermore, the authors do not present data on other cell types such that the phenomenon studied in this work might be specific to MDCK cells. Finally, The authors do not modify cytoskeleton contractility to check how this parameter affects the threshold curvature below which cell extrusion is no longer curvature dependent.

Reviewer #1 (Public Review): 

How morphogens spread within tissues remains an important question in developmental biology. Here the authors revisit the role of glypicans in the formation of the Dpp gradient in wing imaginal discs of Drosophila. They first use sophisticated genome engineering to demonstrate that the two glypicans of Drosophila are not equivalent despite being redundant for viability. They show that Dally is the relevant glypican for Dpp gradient formation. They then provide genetic evidence that, surprisingly, the core domain of Dally suffices to trap Dpp at the cell surface (suggesting a minor role for GAGs). They conclude with a model that Dally modulates the range of Dpp signaling by interfering with Dpp's degradation by Tkv. These are important conclusions, but more independent (biochemical/cell biological) evidence is needed.

As indicated above, the genetic evidence for the predominant role of Dally in Dpp protein/signalling gradient formation is strong. In passing, the authors could discuss why overexpressed Dlp has a negative effect on signaling, especially in the anterior compartment. The authors then move on to determine the role of GAG (=HS) chains of Dally. They find that in an overexpression assay, Dally lacking GAGs traps Dpp at the cell surface and, counterintuitively, suppresses signaling (fig 4 C, F). Both findings are unexpected and therefore require further validation and clarification, as outlined in a and b below. 

a) In loss of function experiments (dallyDeltaHS replacing endogenous dally), Dpp protein is markedly reduced (fig 4R), as much as in the KO (panel Q), suggesting that GAG chains do contribute to trapping Dpp at the cell surface. This is all the more significant that, according to the overexpression essays, DallyDeltaHS seems more stable than WT Dally (by the way, this difference should also be assessed in the knock-ins, which is possible since they are YFP-tagged). The authors acknowledge that HS chains of Dally are critical for Dpp distribution (and signaling) under physiological conditions. If this is true, one can wonder why overexpressed dally core 'binds' Dpp and whether this is a physiologically relevant activity. 

b) Although the authors' inference that dallycore (at least if overexpressed) can bind Dpp. This assertion needs independent validation by a biochemical assay, ideally with surface plasmon resonance or similar so that an affinity can be estimated. I understand that this will require a method that is outside the authors' core expertise but there is no reason why they could not approach a collaborator for such a common technique. In vitro binding data is, in my view, essential. 

In a subsequent set of experiments, the authors assess the activity of a form of Dpp that is expected not to bind GAGs (DppDeltaN). Overexpression assays show that this protein is trapped by DallyWT but not dallyDeltaHS. This is a good first step validation of the deltaN mutation, although, as before, an invitro binding assay would be preferable. Nevertheless, the authors show that DppDeltaN is surprisingly active in a knock-in strain. At face value (assuming that DeltaN fully abrogates binding to GAGs), this suggests that interaction of Dpp with the GAG chains of Dally is not required for signaling activity. This leads to authors to suggest (as shown in their final model) that GAG chains could be involved in mediating the interactions of Dally with Tkv (and not with Dpp. This is an interesting idea, which would need to be reconciled with the observation that the distribution of Dpp is affected in dallyDeltaHS knock-ins (item a above). It would also be strengthened by biochemical data (although more technically challenging than the experiments suggested above). 

In an attempt to determine the role of Dally (GAGs in particular) in the signaling gradient, the paper next addresses its relation to Tkv. They first show that reducing Tkv leads to Dpp accumulation at the cell surface, a clear indication that Tkv normally contributes to the degradation of Dpp. From this they suggest that Tkv could be required for Dpp internalisation although this is not shown directly. The authors then show that a Dpp gradient still forms upon double knockdown (Dally and Tkv). This intriguing observation shows that Dally is not strictly required for the spread of Dpp, an important conclusion that is compatible with early work by Lander suggesting that Dpp spreads by free diffusion. These result show that Dally is required for gradient formation only when Tkv is present. They suggest therefore that Dally prevents Tkv-mediated internalisation of Dpp. Although this is a reasonable inference, internalisation assays (e.g. with anti-Ollas or anti-HA Ab) would strengthen the authors' conclusions especially because they contradict a recent paper from the Gonzalez-Gaitan lab. 

The paper ends with a model suggesting that HS chains have a dual function of suppressing Tkv internalisation and stimulating signaling. This constitutes a novel view of a glypican's mode of action and possibly an important contribution of this paper. As indicated above, further experiments could considerably strengthen the conclusion. Speculation on how the authors imagine that GAG chains have these activities would also be warranted.

Reviewer #2 (Public Review): 

The authors are trying to distinguish between four models of the role of glypicans (HSPGs) on the Dpp/BMP gradient in the Drosophila wing, schematized in Fig. 1: (1) "Restricted diffusion" (HSPGs transport Dpp via repetitive interaction of HS chains with Dpp); (2) "Hindered diffusion" (HSPGs hinder Dpp spreading via reversible interaction of HS chains with Dpp); (3) "Stabilization" (HSPGs stabilize Dpp on the cell surface via reversible interaction of HS chains with Dpp that antagonizes Tkv-mediated Dpp internalization); and (4) "Recycling" (HSPGs internalize and recycle Dpp). 

To distinguish between these models, the authors generate new alleles for the glypicans Dally and Dally-like protein (Dlp) and for Dpp: a Dally knock-out allele, a Dally YFP-tagged allele, a Dally knock-out allele with 3HA-Dlp, a Dlp knock-out allele, a Dlp allele containing 3-HA tags, and a Dpp lacking the HS-interacting domain. Additionally, they use an OLLAS-tag Dpp (OLLAS being an epitope tag against which extremely high affinity antibodies exist). They examine OLLAS-Dpp or HA-Dpp distribution, phospho-Mad staining, adult wing size. 

They find that over-expressed Dally - but not Dlp - expands Dpp distribution in the larval wing disc. They find that the Dally[KO] allele behaves like a Dally strong hypomorph Dally[MH32]. The Dally[KO] - but not the Dlp[KO] - caused reduced pMad in both anterior and posterior domains and reduced adult wing size (particularly in the Anterior-Posterior axis). These defects can be substantially corrected by supplying an endogenously tagged YFP-tagged Dally. By contrast, they were not rescued when a 3xHA Dlp was inserted in the Dally locus. These results support their conclusion that Dpp interacts with Dally but not Dlp. 

They next wanted to determine the relative contributions of the Dally core or the HS chains to the Dpp distribution. To test this, they over-expressed UAS-Dally or UAS-Dally[deltaHS] (lacking the HS chains) in the dorsal wing. Dally[deltaHS] over-expression increased the distribution of OLLAS-Dpp but caused a reduction in pMad. Then they write that after they normalize for expression levels, they find that Dally[deltaHS] only mildly reduces pMad and this result indicates a major contribution of the Dally core protein to Dpp stability. The "normalization" is a key part of this model and is not mentioned how the normalization was done. When they do the critical experiment, making the Dally[deltaHS] allele, they find that loss of the HS chains is nearly as severe as total loss of Dally (i.e., Dally[KO]). Additionally, experimental approaches are needed here to prove the role of the Dally core.

Prior work has shown that a stretch of 7 amino acids in the Dpp N-terminal domain is required to interact with heparin but not with Dpp receptors (Akiyama, 2008). The authors generated an HA-tagged Dpp allele lacking these residues (HA-dpp[deltaN]). It is an embryonic lethal allele, but they can get some animals to survive to larval stages if they also supply a transgene called “JAX” containing dpp regulatory sequences. In the JAX; HA-dpp[deltaN] mutant background, they find that the distribution and signaling of this Dpp molecule is largely normal. While over-expressed Dally can increase the distribution of HA-dpp[deltaN], over-expression of Dally[deltaHS] cannot. These latter results support the model that the HS chains in Dally are required for Dpp function but not because of a direct interaction with Dpp. 

In the last part of the results, they attempt to determine if the Dpp receptor Thickveins (Tkv) is required for Dally-HS chains interaction. The 2008 (Akiyama) model posits that Tkv activates pMad downstream of Dpp and also internalizes and degrades Dpp. A 2022 (Romanova-Michaelides) model proposes that Dally (not Tkv) internalizes Dpp.  

To distinguish between these models, the authors deplete Tkv from the dorsal compartment of the wing disc and found that extracellular Dpp increased and expanded in that domain. These results support the model that Tkv is required to internalize Dpp. They then tested the model that Dally antagonizes Tkv-mediated Dpp internalization by determining whether the defective extracellular Dpp distribution in Dally[KO] mutants could be rescued by depleting Tkv. Extracellular Dpp did increase in the D vs V compartment, potentially providing some support for their model. However, there are no statistics performed, which is needed for full confidence in the results. The lack of statistics is particularly problematic (1) when they state that extracellular Dpp does not rise in ap>tkv RNAi vs ap>tkv RNAi, dally[KO] wing discs (Fig. 6E) or (2) when they state that extracellular Dpp gradient expanded in the dorsal compartment when tkv was dorsally depleted in dally[deltaHS] mutants (Fig. 6I). These last two experiments are important for their model but the differences are assessed only visually. In fact, extracellular Dpp in ap>tkv RNAi, dally[KO] (Fig. 6B) appears to be lower than extracellular Dpp in ap>tkv RNAi (Fig. 6A) and the histogram of Dpp in ap>tkv RNAi, dally[KO] is actually a bit lower than Dpp in ap>tkv RNAi, But the author claim that there is no difference between the two. Their conclusion would be strengthened by statistical analyses of the two lines. 

Strengths: 

1. New genomically-engineered alleles

A considerable strength of the study is the generation and characterization of new Dally, Dlp and Dpp alleles. These reagents will be of great use to the field.

2. Surveying multiple phenotypes

The authors survey numerous parameters (Dpp distribution, Dpp signaling (pMad) and adult wing phenotypes) which provides many points of analysis.

Weaknesses: 

1. Confusing discussion regarding the Dally core vs HS in Dpp stability. They don't provide any measurements or information on how they "normalize" for the level of Dally vs Dally[deltaHS]? This is important part of their model that currently is not supported by any measurements.

2. Lacking quantifications and statistical analyses: 

a. Why are statistical significance for histograms (pMad and Dpp distribution) not supplied? These histograms provide the key results supporting the authors' conclusions but no statistical tests/results are presented. This is a pervasive shortcoming in the current study. 

b. dpp[deltaN] with JAX transgene - it would strengthen the study to supply quantitative data on the percent survival/lethal stage of dpp[deltaN] mutants with or without the JAK transgene <br /> c. The graphs on wing size etc should start at zero. <br /> d. The sizes of histograms and graphs in each figure should be increased so that the reader can properly assess them. Currently, they are very small. 

The authors' model is that Dally (not Dlp) is required for Dpp distribution and signaling but that this is not due to a direct interaction with Dpp. Rather, they posit that Dally-HS antagonize Tkv-mediated Dpp internalization. Currently the results of the experiments could be considered consistent with their model, but as noted above, the lack of statistical analyses of some parameters is a weakness. One problematic part of their result for me is the role of the Dally core protein (Fig. 7B). There is a mis-match between the over-expression results and Dally allele lacking HS (but containing the core). Finally, their results support the idea that one or more as-yet unidentified proteins interact with Dally-HS chains to control Dpp distribution and signaling in the wing disc. 

There is much debate and controversy in the Dpp morphogen field. The generation of new, high quality alleles in this study will be useful to Drosophila community, and the results of this study support the concept that Tkv but not Dally regulate Dpp internalization. Thus the work could be impactful and fuel new debates among morphogen researchers. <br />

The manuscript is currently written in a manner that really is only accessible to researchers who work on the Dpp gradient. It would be very helpful for the authors to re-write the manuscript and carefully explain in each section of the results (1) the exact question that will be asked, (2) the prior work on the topic, (3) the precise experiment that will be done, and (4) the predicted results. This would make the study more accessible to developmental biologists outside of the morphogen gradient and Drosophila communities.

Reviewer #1 (Public Review):

This study by Cao et al. demonstrates role of Neutrophil in clearing apoptotic hepatocytes by directly burrowing into the apoptotic hepatocytes and ingesting the effete cells from inside without causing inflammation. The authors applied intravital microscopy, Immunostaining and electron microscopy to visualize perforocytosis of neutrophil in hepatocytes. They also found that neutrophil depletion impairs the clearance of apoptotic hepatocytes causing impaired liver function and generation of autoantibodies, implying a role of defective neutrophil- mediated clearance of apoptotic cells in Autoimmune Liver disease. The experiments were well designed and conducted, the results were reasonably interpreted, and the manuscript was clearly written with logical inputs.

One weak point is that the signals/mechanisms that determine why neutrophil specifically target apoptotic hepatocytes in liver and no other organs or cells is not clearly understood.

Reviewer #2 (Public Review):

Neutrophils are the most abundant circulating leukocytes in human. They play important roles in innate immune responses to infections and tissue injuries. Although they are dept in phagocytosis of microbes, neutrophils are not known to normally conduct efferocytosis or phagocytose host cells including apoptotic cells and play a significant role in apoptotic cell removal. In this report the authors provide evidence to suggest that neutrophils are involved in removal of apoptotic hepatocytes with certain specificity (i.e., they do not remove HEK293 or HUVEC endothelial cells). Moreover, the authors also show that neutrophils can burrow into the target cells and possibly ingest the target cells from the inside. The authors thus term this neutrophil-mediated efferocytosis process as "perforocytosis". Furthermore, evidence is provided to suggest that this neutrophil-mediated efferocytosis process keeps the number of apoptotic cells low in the livers and that defects in the processes may associate with autoimmune liver (AIL) disease phenotypes. Therefore, many of these findings are novel and the study is of important implications in our understanding of the role of neutrophils in autoimmune disease.

By examination of HE-stained, noncancerous liver tissue sections from patients with hepatocellular carcinoma and hepatic hemangioma, the authors observed that cells with neutrophil nuclear morphology were inside apoptotic hepatocytes. The authors also further characterized this observation by staining the sections with neutrophil and apoptosis markers. In addition, the authors observed the same phenomena in mouse livers using intravital microscopy, which also recorded the time course of the disappearance of a neutrophil-associated apoptotic cell. The author went on further characterization of neutrophil-mediated efferocytosis of cultured hepatic cells in vitro and demonstrated the process was specific for apoptotic hepatic cells, but not HEK293 or endothelial cells. The in vitro system was then used to characterize the molecular bases for neutrophil-mediated efferocytosis of apoptotic hepatic cells. The evidence was provided to suggest that IL1b and IL-8 released from and selectins upregulated in apoptotic hepatic cells were important. Importantly, the authors used two methods to deplete the neutrophils and showed that the neutrophil depletion increased apoptotic cells in livers. Finally, the authors showed that neutrophil depletion caused defects in liver function parameters. At the end, the authors presented evidence to suggest that AIL disease may be due to defective neutrophils that fail to perform "perforocytosis."

Although the evidence in its totality indicates that neutrophils burrow into apoptotic hepatocytes, the significance of this "perforocytosis" phenomenon and the circumstances under which it may occur remain to be better defined. In both neutrophil depletion models, the TNUEL-positive cells were not definitively identified rather than assuming they were hepatocytes. In addition, there are discrepancies in the number of neutrophils and apoptotic cells in mouse liver studies; Figure 2a WT (many neutrophils; locations unclear) vs Figure 5A Ctr (a few neutrophils that appear in or near a vessel), and Figure 2a DTR (a few apoptotic cells) vs Figure 5A Depletion (many apoptotic cells). Importantly, Figure 5a Ctrl, which is presumably a section from a mouse without any surgical treatment or without inflammation, the sole TUNNEL signal does not appear to be associated with neutrophils. Does this mean that "perforocytosis" primarily occurs in inflamed livers (Of note, human liver samples in Figure 1 are from patient with tumors. There should be inflammation in the livers of these patients). The data on human AIL patient neutrophils raises more questions: how many AIL patients have been examined? Do these AIL neutrophils lack IL1, IL8 receptors, and/or selectin ligands? Are there increases in apoptotic hepatocytes in AIL patients? Additionally, the overall numbers of apoptotic cells even in the absence of neutrophils are rare; thus, it is questionable that such rarity of apoptotic cells can cause significant AIL phenotypes.

Reviewer #1 (Public Review):

In this manuscript, Mastrototaro et al. perform a series of experiments in transgenic murine models assessing the function of Palladin (PALLD) in the heart. Global PALLD KOs are embryonic lethal, precluding the assessment of the roles of this protein in adulthood. To circumvent this limitation, the authors generated a floxed Palld allele and ablated it with two cardiomyocyte-specific Cres: the constitutively active Myh6-Cre and the tamoxifen-inducible aMHC-MerCreMer. Interestingly, ablation with the constitutive Cre (cKO) did not produce any overt phenotype, but ablation in adulthood (cKOi) resulted in compromised cardiac function. These observations suggest a compensation mechanism that takes place when cardiomyocytes develop in the complete absence of this protein but not when cardiomyocytes develop in a wild-type background and are deprived of this protein after achieving full maturation. These experiments were complemented with yeast two-hybrid techniques to identify novel partners that bind to a region of PALLD for each no interactants had been previously identified. Experiments in human samples revealed an upregulation of PALLD transcripts in the hearts of patients.

This manuscript adds important information to our understanding of sarcomeric proteins. Data are generally of good quality and well presented in figures. The numbers of animals in echocardiographic studies are also adequate for proper conclusions. Authors achieve most of their goals, including the identification of novel partners of PALLD and the identification of a requirement for PALLD in cardiomyocytes for normal heart function. However, given that all experiments performed in this study were focused on the loss-of-function of PALLD, it is not clear what is the relevance of the PALLD upregulation observed in human patients. Authors should clearly state this limitation in their results.

Considering that authors have observed evidence for nuclear PALLD, which could hint at potential major gene expression changes when this protein is ablated, it would be interesting to perform an unbiased assessment of transcriptional alterations (RNA-seq) in cardiomyocytes isolated from control and cKOi hearts. In addition, to test if the compensation observed in the embryonic cKO involves mechanisms of transcriptional adaptation, it would be interesting to compare RNA-seq results from cKOi and cKO (genes encoding proteins similar to PALLD that are upregulated in cKO but not cKOi cardiomyocytes would be very strong candidates). However, these transcriptomic data are not essential to support current findings and can be performed in follow-up studies.

Reviewer #2 (Public Review):

The role of the actin-binding protein palladin (PALLD) in cardiomyocyte development, growth, and function has not been defined. In order to address this question, the authors first identified that CARP and FHOD1 interact with PALLD in cardiomyocytes. They then performed cardiomyocyte selective deletion of PALLD in embryonic and adult mice and discovered that deletion of PALLD in adult mice leads to dilated cardiomyopathy (DCM) and intercalated disc ultrastructural changes. In contrast, embryonic deletion of cardiomyocyte PALLD did not cause a cardiomyopathy phenotype in neonatal or adult animals.

1. The divergent cardiac phenotypes of the embryonic deletion of cardiomyocyte PALLD (no cardiomyopathy) versus the adult deletion of cardiomyocyte PALLD (dilated cardiomyopathy(DCM)) is an interesting result. The authors speculate that embryonic deletion of PALLD induces compensatory pathways that prevent the development of adult cardiomyopathy in these mice. However, these compensatory pathways remain unexplored.<br /> 2. The authors discovered that mice with adult cardiomyocyte deletion of PALLD had significant changes in the cardiomyocyte intercalated disc (ICD) ultrastructure. They suggest these changes in ICD ultrastructure contribute to DCM formation in the adult PALLD deletion mice (line 270). However, it remains unclear if these changes in ICD ultrastructure are specific to mice with adult deletion of PALLD.<br /> 3. The different transgenic Cre mouse lines may be an alternative explanation for the divergent cardiac phenotypes in the embryonic versus adult deletion of cardiomyocyte PALLD. The tamoxifen dose administered for the inducible Myh6:MerCreMer mice was 30mg/kg/day x 5 which has been reported to lead to the induction of cardiomyocyte DNA damage response pathways (Dis Model Mech. 2013 Nov; 6(6): 1459-1469, J Cardiovasc Aging 2022;2:8). The electron micrograph experiments in Figure 5 did not include a group of Myh6:MerCreMer mice administered tamoxifen. The authors only compared PALLD fl/fl and Myh6:MerCreMer/PALLD fl/fl mice.<br /> 4. The apoptosis assessment was performed 24 weeks after administration of tamoxifen to the Myh6:MerCreMer/PALLD fl/fl mice. However, cardiomyocyte apoptosis may have occurred much earlier if it was secondary to Myh6:MerCreMer tamoxifen-induced cardiotoxicity (or related to PALLD deletion).<br /> 5. The animal studies in Fig 3D show a DCM phenotype in mice with adult deletion of cardiomyocyte 200kDa PALLD which suggests a potential loss of function mechanism for DCM formation. However, the authors then report in Fig 6 that human DCM heart tissue samples have a ~2.5fold increase in mRNA expression of the 200kDa PALLD transcript which would suggest a possible gain of function mechanism for DCM formation. How do the authors reconcile these divergent results with regard to palladin's role in cardiomyocyte homeostasis and cardiomyopathy formation?

Reviewer #3 (Public Review):

This study shows for the first time changes in palladin expression under disease conditions and mRNA alterations in human samples. The authors have identified novel binding partners for the protein as a first step toward determining how palladin mediates its effects in the heart. Finally, through the use of mouse models to decrease palladin expression they identify a crucial role for palladin in the cardiac response to pathological stress, with some interesting findings that show the effects of palladin depend on when the protein is altered.

The novel findings of the study are supported by the data presented, but there are several instances where clarification is needed of the conclusions drawn from the data reach beyond what is presented in the Results section.

The focus on only male mice is a significant limitation of the paper, as it is well known that there are profound sex differences in the response to pathological stressors. While the ability to obtain sufficient heart samples from male and female patients may be a reasonable justification for focusing on males, the preclinical mouse model should have been examined in both sexes and the limitation of this choice should be clearly noted in the paper.

The changes in myopalladin expression were not measured in the disease model (TAC), which limits the ability to determine if myopalladin was altered in the disease state. This addition would strengthen the study.

Finally, the myofilament data are presented as evidence that changes in the contractile apparatus are contributors to the observed contractile dysfunction at the organ level. But these studies were conducted using levels of calcium that far exceed what is seen in vivo and, therefore, do not support the conclusion drawn.

Peer review report

Title: An Improved Peer-Review System to Compensate for Scientific Misconduct in Health-Sensitive Topics

version: 7

Referee: Cristina Candal-Pedreira

Institution: University of Santiago de Compostela

email: cristina.candal.pedreira@rai.usc.es

ORCID iD: 0000-0002-1703- 3592

General assessment

In this letter, the authors propose a series of actions that the main actors responsible for scientific integrity (researchers, scientific journals, academic institutions, and funding entities) could (and should) implement to prevent and/or detect cases of scientific misconduct. Although the authors refer primarily to high-sensitive publications, in my opinion, many (if not all) of the provided proposals can be applied to any type of publication. Examples of scientific misconduct are commonplace, and the policies implemented so far do not seem to be strong enough to prevent the publication of fraudulent articles. I believe that this article is necessary and very relevant.

Essential revisions that are required to verify the manuscript

In my opinion, this letter presents a very comprehensive list of potential strategies that different stakeholders can undertake to reduce the burden of research misconduct. Of course, there are many other actions that could be implemented, such as promoting post- publication review, imposing sanctions, or auditing research funding from an ethical point of view, among others. However, I consider all the strategies developed by the authors to be important and necessary, so I have no essential revisions to this manuscript.

Other suggestions to improve the manuscript

The text is well written, very clear and easy to follow.

Some comments/suggestions/reflections:

I would suggest introducing the definition of “high sensitivity topic” in the first part of the manuscript. Also, in the title another term is used (health-sensitivity topic), I would homogenize terms.

J2. In addition to solving the problem of coercive citations, open peer review can make the peer review process more transparent by making public how many rounds of review have been done and how the conclusion was reached to publish or reject the article. In addition, reviewers, because they are not anonymous, can take the review more seriously.

R1-R2-R3. Regarding regulatory agencies, funders and institutions, it could also be helpful for them to perform audits of the projects, not only justification of where the money was spent, but also whether the research is being done ethically, including during the phase of dissemination of results.

Decision

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

Reviewer #1 (Public Review):

The authors set out to analyse the pattern of movement of T cells in different tissues- lymph nodes, villi, and inflamed/infected lungs. The authors are comparing data sets from multiple sites in different studies but acquired using similar instruments, preparations, and imaging conditions.

The more confined movement pattern in the lung that has a turning angle distribution with more incidence of angles near 180 degrees is striking.

T cells in the infected inflamed lung search a smaller volume over time but will explore it more extensively.

The measurements of T cell movement are context-free such that obstacles and tissue boundaries that could account for some of the confined behaviours in the lung parenchyma are not discussed.

Nonetheless, the work will motivate further study of the biological significance of the different T cell movement patterns in the lung, which may also be considered in the context of recent data on changes in B cell motility- a potential interacting cell.

Reviewer #2 (Public Review):

This paper addresses the topic of how T cells migrate in different tissues. The authors provide experimental evidence that T cell migration in the lung is more confined than in lymph nodes and gut villi. While prior studies have started to define the way T cells migrate during normal and pathological conditions, there is still a lot to learn about the factors that control this process. Thus, the topic is significant and timely. The authors use previously acquired data with two-photon microscopy from murine tissues. They compare multiple motility parameters of T cells in lymph nodes, gut villi, and inflamed lungs. Experiments demonstrate that T cells in the lung have a particular mode of migration characterized by low speeds, back-and-forth motions, and confinement.

Strengths:<br /> Overall, this is a very well-performed study. The data presented is of excellent quality and, for the most part, supports the authors' conclusions. The imaging techniques used to track T cells in various organs and the mouse models implemented are very relevant and robust. The functional analysis of the different migration features of T cells is compelling and should be of use to the community. The conclusion that T cells use different migration modes depending on the organ appears novel. This is considered of major significance.

Weaknesses:<br /> The main weakness of the manuscript is that the study remains descriptive and comparative. It is important to analyze and describe different migration modes depending on the organ. Still, it would have been desirable for the authors to provide information on the reason for such differences. One of the striking observations is the back-and-forth motion of T cells in the lung. Searching for mechanisms underlying this unique mode of displacement would strengthen the quality of the study.

Reviewer #3 (Public Review):

The ability of T cells to move through a variety of complex and disparate tissue environments is fundamental to their success in surveying and responding to infectious challenges. A better understanding of the molecular cues that regulate T cell motility in tissues is needed in order to inform therapeutic targeting of T cell migration. Contributions that are intrinsic and extrinsic to the T cells themselves have been shown to shape the pattern of T cell movement. This study uses advanced quantitative image analysis tools to dissect differences in T cell motility in different tissue locations, to better define how the tissue environment shapes the pattern of motility and scope of tissue explored. The combination of different quantitative measures of motion enables the extensive characterization of CD8 T cell motility in the lymph node, lung, and villi of the small intestine. However, there are too many variables with respect to the CD8 T cell populations used for analysis to be able to gain new insight into the impact of the tissue microenvironment itself.

The use of these advanced quantitative imaging analysis tools has the potential to significantly expand our analysis capabilities of T cell movement within and across tissues. The strength of the paper is the comprehensive analysis of multiple motility parameters designed with T cell function in mind. Specifically, with respect to the need for T cells to search a tissue area to identify antigen-bearing cells for T cell activation and identify cellular targets for the delivery of anti-microbial effector functions. The inclusion of an analysis of the "patrolled volume per time" is seen as a particularly useful advance to compare T cell behaviors across tissues.

However, with the current data sets, it is difficult to draw definitive conclusions on the impact of the tissue environment on how T cell move, given the considerable variability in the CD8 T cells themselves. Extended experimentation would be needed to fully support their key claims. In particular:

1) The authors have separated out naïve and activated CD8 T cells for their analysis, but this is a marked over-simplification. There are too many variables within these groups to be able to distinguish between differences in the T cell populations versus differences in the tissue environment. Variables include:<br /> a) T cells pre-activated in vitro before in vivo transfer (LPS-lung) versus transfer of naïve T cells for activation in vivo (Flu-lung, LCMV-villi)<br /> b) Polyclonal CD8 T cells (naïve, LPS-lung, Flu-lung) versus monoclonal (P14) CD8 T cells (LCMV-villi)<br /> c) Presence of cognate-antigen (Flu-lung, LCMV-villi) versus absence of antigen (LPS-lung)<br /> d) Cell numbers, 104 polyclonal naïve for Flu-lung versus 5 x 104 monoclonal (P14 T cells) for LCMV-villi)<br /> e) Intravital imaging (LCMV-villi) versus tissue explants (Flu-lung)

The authors do present data that suggest similarities of motility patterns within the same tissue occur despite variabilities in the CD8 T cell source, for example, the MSD is not significantly different in the two lung groups despite differences in the way the CD8 T cells were activated. However, these similarities are lost when other parameters are analyzed suggesting additional variability independent of the tissue itself.

2) Controlled experiments are needed, where the input CD8 T cell population is kept constant and the target tissue differs, to substantiate any of the current conclusions. This could be done by using a single source and/or specificity of CD8 T cells (e.g., P14 or OT-I TCR transgenics, or polyclonal in vitro activated CD8 T cells) transferred into mice where the tissue providing the antigen or inflammation source is varied (lung with pOVA-flu versus small intestine with pOVA-LCMV for example).

Alternatively, activated polyclonal CD8 T cells could be analyzed in the LPS-lung draining LN as well as in the LPS-lung to make a direct comparison between the tissues (LN versus lung) using CD8 T cells of the same activation status.

3) Differences in the micro-anatomical regions of the tissues studied may also contribute to tissue differences in movement patterns between the lung and the small intestine. The region of the small intestine imaged was specifically focused on the villi, close to the gut epithelium. Details of the location within the lung where images were taken are missing, therefore the motility differences between the lung and small intestine could reflect differences in the micro-anatomical position of the CD8 T cells within the tissue (proximal to epithelium versus parenchymal), rather than differences between the tissues themselves.

Overall, the authors have developed a quantitative multi-parameter approach to the study of T-cell motility in different tissues. Application of these analytical tools to the study of T-cell behavior in different tissue locations has the potential to reveal tissue and/or T-cell-specific patterns of movement that may help to identify molecular requirements for context-specific dynamic T-cell behavior. Their quantitative approach reveals small but statistically significant differences in particular motility parameters, the functional significance of which will require further study. The careful design of experiments to reduce as many variables as possible will be needed to increase the impact of the work and ensure new insights into this important aspect of T-cell function.

Reviewer #1 (Public Review):

This study presents a resource aiming to unify language and rules used in the literature to describe, curate and assess biology experiments, published or not. Focusing on host-pathogen interactions, the work presents a new ontology and controlled vocabulary, as well as rules to describe 'metagenotypes', a term coined for the joint description of interacting host-pathogen genotypes. 'PHI-Canto' extends a previous resource by also enabling using UniProtKB IDs to curate proteins. Among other important by-products, PHI-Canto could contribute to damping proliferating names and acronyms for genes, processes, and interactions; a chronic annoyance in the biosciences.

The tool does give the impression that, with sufficient time and usage, it could become a rich and robust resource. Just addressing the Uniprot IDs issue is a nice move.

Reviewer #2 (Public Review):

In this paper, the authors propose a system for annotating and curating scientific publications in the context of interspecies host-pathogen interactions. This system, called PHI-Canto (the Pathogen-Host Interaction Community Annotation Tool), is an extension of an existing tool (called Canto). In addition, they present the development of new concepts, controlled vocabularies, and an ontology for annotating relevant aspects in this domain, called PHIPO (Pathogen-Host Interaction Phenotype Ontology).

The approach has been empirically validated by annotating ten publications. The application's source code is available, as well as the associated ontologies and vocabularies and an example of the data resulting from the annotation process.

Reviewer #3 (Public Review):

In this work, the authors have built a framework for the annotation of interactions between species. The framework includes ontologies, methodologies, and an annotation tool called PHI-Canto. The framework makes use of multiple existing ontologies that are in wide use in the biocuration community. In addition, the authors have built their own project-specific controlled vocabularies and ontologies for the capture of pathogen-host interaction phenotypes (PHIPO), diseases (PHIDO), and environmental conditions (PHI-ECO). Their work builds on and extends methods that have been developed within the Gene Ontology Consortium and model organism databases. The tool PHI-Canto is an extension of the tool Canto developed by PomBase for curation. The authors used this framework to annotate pathogen-host interactions within the Pathogen-Host Interactions Database.

Strengths: The manuscript is well-written and includes significant detail regarding curation policies/methods and the use of the actual PHI-Canto tool. The appendices are very detailed and provide useful illustrations of the annotation practices and tool interface. The work has built upon and extended well-established standards and methods that have proven their utility over many years of use in the biocuration community. The authors have rigorously tested their framework with the curation of a variety of publications providing a diverse assortment of annotation challenges. The concept of a "metagenotype" is important and providing such a structured system for the capture of this information is useful. All of the materials produced by the work are completely freely available for use by the wider community.

Weaknesses: There are some areas of the manuscript and appendices which are a bit confusing and could be improved. The authors have developed their own set of disease terms (PHIDO) but do not comment on why existing disease terminologies (such as Mondo or DO) were not used or if the PHIDO terms relate to those other vocabularies. There is no discussion of the possible use of a graph representation for the capture of this complex information (which is being done in many settings including the Gene Ontology with GO Causal Activity Models (GO-CAMs)) or why such a structure was not used. Although the abstract talks about the use of the framework within the PHI database as a test case for broader use regarding interspecies interactions, there is no mention of extending the use of the tool to other species interaction communities beyond pathogen-host interactions.

Reviewer #1 (Public Review):

Motivated by the premise that Alzheimer's disease (ADD) and major depressive disorder (MDD) have shared underlying environmental and genetic risk factors, Petrican and Fornito combine non-imaging risk factors and executive task-based functional network change indices into latent variables of resilience to AD and MDD. The authors find two latent variables (LVs): LV1 represents change in network membership over time of distributed nodes during task, which is associated with greater genetic MDD risk, less psychopathology, and more advanced puberty, all while adjusting for age and indices of environmental stressors. LV2 represents occipital lobe nodal flexibility across task and time, decreased AD genetic risk, increased MDD genetic risk and less psychopathology, again adjusted for age and environmental stressors. The authors validate the latent network variables by assessing their overlap with genes for which SNPs have been associated with both depression risk and change in gene expression. Finally, the authors create simple path models in order to break down the relationships between genetic risk, latent variables, and what the authors term "resilience", finding distinct path for MDD and (non-APOE) AD genetic risk. All of these analyses are then re-run using a different brain parcellation. LV2 replicates, while a new LV1 emerges with similar non-imaging variables now being correlated with a different set of distributed network nodes.

The authors conclude from this work that they have identified imaging indices of resilience manifest during adolescent brain development, and that they have found further evidence linking MDD to AD. However, the analyses do not fully support the conclusions. The premise of this work - to examine links between MDD and AD and to try to define indices of resilience during development - is fascinating and will hopefully motivate future work in this direction. However, the impact of this work as currently presented may be limited.

*STUDY STRENGTHS*

There are two premises motivating this study that deserve praise for their innovation and creativity. First, in the introduction the authors present several fairly new papers showing shared environmental and risk factors between AD and MDD. This is a very interesting line of study that certainly deserves more attention. Second, the authors are interested in finding aspects of adolescent brain development that may be helpful to understanding resilience to genetic or environmental risk later in life. The AD resilience community is very interested in contributions of early life experiences and development, but there is still very little research in this domain. I hope the authors continue to conduct research in the direction of these pursuits.

The authors demonstrate great methodological and statistical rigor in some aspects of data preprocessing and analysis. This is particularly salient in null modeling and permutation, graph-based analysis, treatment of motion for functional imaging, using eQTLs to inform disease-relevant genes, statistical considerations in PLS and path modeling, processing of Allen Brain Atlas gene expression data, and validating certain study variables. The methodology of these steps displays great attention to detail and a mastery of certain data types.

The authors reproduce all analyses using a second parcellation and carefully report the results. This type of painstaking analysis is nonetheless important in the context of network-based graph analysis that is reliant on nodal information.

*STUDY LIMITATIONS*

1) The overarching limitation of this study is that the study variables, both independent and dependent, are abstracted to the point where interpretations are challenging. The authors' own interpretations are not sufficiently justified and are often taken at face value rather than supported by analysis. These are further combined into latent variables with weak conceptual foundation, which are then abstracted even further to other analyses with cortical molecular data maps. It is not clear that the conclusions drawn are convincingly supported by this highly abstracted analysis.

2) The other major limitation of this study is that several PLS models are run but, while appropriate null modeling is used to identify "significant" LVs, none of the LVs are cross-validated. Null modeling can help to protect against overfitting to noise in data, but it does not necessarily provide a good index of generalizability nor reliability. Without cross-validation, I question the reliability of the LVs irrespective of how they are interpreted. This is once again partially driven by the fact that changing the atlas resulted in a different imaging LV.

3) The study notes that participants were selected based on "having contributed high-quality data on all measures of interest". This is of course meritorious from a methodological perspective, but the authors should be aware that this may create an important selection bias (10.1007/s11682-022-00665-2, 10.1016/j.ynirp.2022.100085, 10.1016/j.neuroimage.2022.119296)

4) The premise of this paper was interesting, as described in the Strengths section above. However, what was missing was a clear theory or hypothesis as to how resilience to AD and MDD are related, and how the analyses in this study were conducted in order to support that hypothesis. The relevance of the results to AD was not clear; a clear biological model would help put the pieces together.

5) The selection of relevant features involved in LVs was inconsistent. At several points, the authors use an arbitrary threshold of bootstrap ratio (BSR) > 4, which they equated to a p-value. A p-value doesn't make sense in this context, since bootstrap samples are not independent samples. Instead, features should be selected based on 95% CIs that don't cross 0, which the authors do in some places but not in others.

Reviewer #2 (Public Review):

The authors' manuscript has several strengths. First, the authors consider multiple relevant levels of biology including genomics, transcriptomics, structural and functional neuroimaging, cognitive neuroscience, and psychological/environmental factors. Such an approach is often necessary to deconvolute the complexities of psychiatric phenotypes. The authors have taken careful steps to think about potential confounds (e.g., ancestry for PRS) and to try to define their phenotypes (e.g., psychological resilience and biological aging) as best as they can, given the data they have access to from the ABCD study. The manuscript is well written overall.

My main concerns relate to core assumptions and techniques that underlie the premise of the study. First, while there is comorbidity between AD and MDD, a causal relationship between the two (in either direction) is not established. Though MDD often predates AD, this is to be expected given MDD's high lifetime prevalence (15-20% of the general population) and typical age of onset before age 65. Because AD typically presents late in life (>65 years of age), MDD will, by definition, usually predate AD. While new onset, late life MDD is often the first presenting symptom of AD/Parkinson's disease and other neurodegenerative conditions, it is also not clear that this is the same disorder as idiopathic MDD.

To this point, two genetic tools can help us determine the biological relationship between MDD/AD, genetic correlation and Mendelian Randomization. Using the data from the MDD PRS used in this analysis, the Supplementary Table 3 from the Howard et al. 2019 paper (https://doi.org/10.1038/s41593-018-0326-7) reveals a genetic correlation of -0.041 between the two. This indicates essentially no strong relationship between the MDD/AD (perhaps even a slightly inverse relationship). Mendelian Randomization studies in addition to the Howard et al paper (https://doi.org/10.1212/WNL.0000000000010463) find no causal role for MDD towards AD and vice versa. Thus, their comorbidity is likely mediated by additional factors. Additionally, while stress contributes to AD pathophysiology, AD is strongly genetic and, given its late onset, it is unclear how genetic risk for AD would meaningfully impact the psychological resilience of a 9 to 10-year-old.

My second concern is regarding the statement "adolescents at genetic risk for AD/MDD" when describing the sample. Per Howard et al 2019 out-of-sample prediction testing, the MDD PRS used by the authors explains between 1.5-3.2% of the phenotypic variance in MDD when used on a sample such as ABCD. MDD PRS is in its infancy and cannot reliably be used to identify individuals at high risk of MDD given that even individuals in the top 10th percentile of MDD PRS have an odds ratio for depression of only ~2.4. We would expect 90 or so individuals in this cohort to fall into this group leaving significant concerns about statistical power and the potential for false positive discoveries. While the AD PRS is significantly further along compared to MDD because of AD's simpler genetic architecture, the same concerns apply as, outside of APOE, the AD PRS does not capture the majority of phenotypic variance in AD.

The authors state that they wish to examine the effects of perinatal adversity directly/indirectly on biological aging and then assess the potential effects of biological aging on resilience. The authors use of pubertal age as a measure of accelerated aging is understandable given the data available, though not ideal. There are well validated measures of biological age such as Horvath's epigenetic clock. While advanced pubertal age is technically a form of accelerated aging, the majority of pubertal age as a phenotype is not likely to be explained by perinatal adversity. Rather, a combination of unmeasured variables including genetic variation, dietary factors, environmental exposures (endocrine disrupting chemicals), and obesity that play a substantial role in determining pubertal age. Childhood stress has been shown to have relatively small effects on pubertal age (d = -0.1) (10.1037/bul0000270).

Lastly, the authors employ the use of an as of yet unpublished technique to map neurotransmitters density to structural data from neuroimaging studies. While this technique is certainly interesting, its face validity is not clear given that many of the receptor-disease associations reported in the original preprint do not line up with what we know about the biology of these disorders from strong human genetics data or current FDA approved treatments. Moreover, the authors mention "Excitation/Inhibition" imbalance but the technique used appears to only include glutamate data from one receptor type, mGluR5. This may not be an adequate measure of E/I imbalance, despite there being a statistically significant finding.

Measuring both transcriptional output from GWAS loci and gene expression correlates from MRI data is a noisy and challenging prospect. Indeed, recent research has shown poor correlation between gene expression and neurotransmitter receptor density.(https://doi.org/10.1016/j.neuroimage.2022.119671).

Thus, fundamental aspects of this manuscript including the use of MDD PRS to identify "at risk" individuals, the unclear link between AD and adolescent psychological resilience, the use of prepubertal age as a measure of biological age, and the limited conclusions that can be drawn from the gene expression and receptor density technique limits confidence in the results as presented.

Reviewer #1 (Public Review):

The present study combines quantitative histomorphometry, live cell imaging and tracking, functional analyses, and computational modeling to define potentially pathologic interactions between lung CD8 T cells and fibrocytes in human COPD. The authors use multiple technical approaches to establish the close proximity of CD8 T cells with fibrocytes in peri-bronchial tissue in COPD subjects that notably correlate with functional disease parameters (FEV1/FEV). Their follow-on studies identify specific chemokine pathways and inflammatory consequences of these interactions. Collectively, these seminal data acquired in a unified experimental context, provide support for pathogenic interactions between lung CD8 T cells and fibrocytes and now offer the consideration of mediators and pathways that may be amenable to therapeutic targeting. The strength of the study is the integration of the multi-modality approach, the quality of the quantitative data, and the creation of a tenable model for the interaction role in COPD of CD8 T cells and fibrocytes. While both have been previously implicated in COPD, this new study is more definitive by using this integrated approach.

Reviewer #2 (Public Review):

The authors use a series of elegant methods to describe the nature of the interrelationship among CD8+ T cells and fibrocytes in the airways of COPD patients. They find an increased presence of these interactions in COPD and show that CXCL8-CXCR2 interactions are crucial for this interaction, leading to increased CD8+ T cell proliferation.

Major strengths of the work include the detailed functional experiments used to describe the nature of the CD8+ T cell - fibrocyte interaction. Another key strength is the translational approach of the work, building on clinical data and connecting back to these same clinical data. The conclusions of the authors are supported by the data. The impact of the work is significant and key to our understanding of the interrelationship between inflammation and tissue remodeling in COPD. Understanding this relationship holds strong potential for the identification of new drug targets and for the identification of patients at risk.

The derivation of the CXCL8/CXCR2 dependency is based on a limited number of COPD patients, which could be strengthened. Also, the impact of the interrelationship between CD8 cells and the fibrocytes is not fully described.

Reviewer #3 (Public Review):

Eyraud and colleagues examine how fibrocytes and CD8 cells can interact with each other to promote COPD. The key findings include that CD8 cells and fibrocytes are found to exist in close proximity to each other in COPD lungs using histopathological analysis of patient samples. The authors leverage pre-existing transcriptomic data on CD8 cells to focus on chemokine release by CD8 cells as a potential pathogenic mechanism by which they could affect fibrocyte migration. In vitro studies using peripheral blood-derived CD8 cells and fibrocytes confirm increased fibrocyte migration in the presence of CD8 cells. as drivers of COPD progression. Conversely, in vitro studies show that fibrocytes exert a pro-proliferative effect on CD8 cells. The authors also use a computational model to assess how these interactions could promote the development of fibrocyte-CD8 clusters as COPD progresses over the course of 20 years.

The strengths of the study include:

1) The multi-faceted research approach that integrates histopathology from clinical COPD lung sections, in vitro co-culture studies, and computational modeling.

2) Applying computational modeling to determine how cell-cell interactions of migration and proliferation can result in distribution patterns within the lung that approximate what is found in actual clinical samples

3) Propose a feedback loop of CD8 cells and fibrocytes that could become a potential therapeutic target to interrupt a vicious cycle that promotes COPD.

However, there are also some weaknesses:

1) Specificity of the role of CD8 cells: While much of the focus is on the proximity of and interactions between CD8 cells and fibrocytes, it is not clear whether other cells similarly interact with fibrocytes. For example, CD4 cells, dendritic cells, or interstitial macrophages may similarly interact with fibrocytes as several of these also release chemokines. In the absence of a more comprehensive assessment, it becomes difficult to parse out how specific and relevant the fibrocyte-CD8 cell interactions are for COPD progression when compared to other putative interactions.

2) The transcriptomic analysis which in many ways sets the stage for the chemokine studies uses a pre-existing dataset of COPD and non-COPD samples with only n=2. The robustness of such a sample size is limited and the narrow focus on chemokines or adhesion receptors of CD8 cells in this limited sample size does not provide a more comprehensive analysis that would require larger samples sizes, studying the transcriptomes of other cell types and a broader analysis of which pathways are the most likely to be dysregulated in the cells that surround fibrocytes.

3) Specificity of the findings for COPD: The in vitro studies use circulating cells which are different from lung cells and this is appropriately acknowledged by the authors. However, it appears from the description that the cells are all from COPD patients. It is therefore not clear whether these interactions between fibrocytes and CD8 cells are unique to COPD, whether they also occur between control CD8 and fibrocytes, or only in cells obtained from patients with inflammatory/pulmonary diseases.

Reviewer #1 (Public Review):

While the mechanism about arm-races between plant and specialist herbivores has been studied, such as detoxification of specific secondary metabolites, the mechanism of the wider diet breadth, so-called generalist herbivores have been less studied. Since the heterogeneity of host plant species, the experimental validation of phylogenetic generalism of herbivores seemed as hard to be conducted. The authors declared the two major hypotheses about the large diet breadth ("metabolic generalism" and "multi-host metabolic specialism"), and carefully designed the experiment using Drosophila suzukii as a model herbivore species.

By an untargeted metabolomics approach using UHPLC-MS, authors attempted to falsify the hypotheses both in qualitative- and quantitative metabolomic profiles. Intersections of four fruit (puree) samples and each diet-based fly individual samples from the qualitative data revealed that there were few ions that occur as the specific metabolite in each diet-based fly group, which could reject the "multi-host metabolic specialism" hypothesis. Quantitative data also showed results that could support the "metabolic generalism" hypothesis. Therefore, the wide diet breadth of D. suzukii seemed to be derived from the general metabolism rather than the adaptive traits of the diverse host plant species. On the other hand, the reduction of the metabolites (ions) set using GLM seemed logical and 2-D clustering from the reduced ions set showed that quantitative aspects of diet-associated ions could classify "what the flies ate". These interesting results could enhance the understanding of the diet breadth (niche) of herbivorous insects.

The authors' approach seemed clear to falsify the hypotheses based on the appropriate data processing. The intersection of shared ions from the qualitative dataset could distinguish the diet-specific metabolites in flies and commonly occurring metabolites among flies and/or fruits. Also, filtering on the diet-specific ions seemed to be a logical and appropriate way. Meanwhile, the discussion about the results seemed to be focused on different points regarding the research hypotheses which were raised in the introduction part. Discussion about the results mainly focused on the metabolism of D. suzukii itself, rather than the research hypotheses and questions that were raised from the evolution of the wide diet breadth of generalist herbivores. In particular, the conclusion seems to be far from the main context of the authors' research; e.g. frugivory. It makes the implication of the study weaker.

Reviewer #2 (Public Review):

The manuscript: "Metabolic consequences of various fruit-based diets in a generalist insect species" by Olazcuaga et al., addresses an interesting question. Using an untargeted metabolomics approach, the authors study how diet generalism may have evolved versus diet specialization which is generally more commonly observed, at least in drosophila species. Using the phytophagous species Drosophila suzukii, and by directly comparing the metabolomes of fruit purees and the flies that fed on them, the authors found evidence for "metabolic generalism". Metabolic generalism means that individuals of a generalist species process all types of diet in a similar way, which is in contrast to "multi-host metabolic specialism" which entails the use of specific pathways to metabolize unique compounds of different diets. The authors find strong evidence for the first hypothesis, as they could easily detect the signature of each fruit diet in the flies. The authors then go on to speculate on the evolutionary ramifications of this for how potentially diet specializations may have evolved from diet generalism. Overall, the paper is well written, the experiments well documented, and the conclusions convincing.

Reviewer #3 (Public Review):

Laure Olazcuaga et al. investigated the metabolomes of four fruit-based diets and corresponding individuals of Drosophila suzukii that reared on them using comparative metabolomics analysis. They observed that the four fruit-based diets are metabolically dissimilar. On the contrary, flies that fed on them are mostly similar in their metabolic response. From a quantitative point of view, they find that part of the fly metabolomes correlates well with that of the corresponding diet metabolomes, which is indicative of insect ingestive history. By further focusing on 71 metabolites derived from diet-specific fly ions and highly abundant fruit ions, the authors show that D. suzukii differentially accumulates diet metabolism in a compound-specific manner. The authors claim that the data support the metabolic generalism hypothesis while rejecting the multi-host metabolic specialism hypothesis. This study provides a valuable global chemical comparison of how diverse diet metabolites are processed by a generalist insect species.

Strengths:<br /> The rapid advances in high-resolution mass spectrometry have recently accelerated the discovery of many novel post-ingestive compounds through comparative metabolomics analysis of insect/frass and plant samples. Untargeted metabolomics is thus a very powerful approach for the systematic comparison of global chemical shifts when diverse plant-derived specialized metabolites are further modified or quantitatively metabolized after ingestion by insects. The technique can be readily extended to a larger micro- or macro-evolutionary context for both generalist and specialist insects to systematically investigate how plant chemical diversity contributes to dietary generalism and specialism.

Weaknesses:<br /> The authors claim that their data support the hypothesis of metabolic generalism, however, a total analysis of insect metabolism may not generate a clean dataset for direct comparison of fruit-derived metabolites with those metabolized by D. suzukii, given that much of these metabolites would be "diluted" proportionally by insect-derived metabolites. If the insect-derived metabolites predominate, then, as the authors observed, a tight clustering of D. suzukii metabolomes in the PCA plot would be expected. It is therefore very difficult to interpret these patterns.

The authors generated a qualitative dataset using the peak list produced by XCMS which contains quantitative peak areas, it is unclear how the threshold was selected to determine if a peak is present or absent in a given sample. The qualitative dataset would influence the output of their data analysis.

The authors reply on in-source fragmentation for peak annotation when authentic standards are not available. The accuracy of the annotation thus requires further validation.

Reviewer #1 (Public Review):

Much experimental work on understanding how the visual system processes optic flow during navigation has involved the use of artificial visual stimuli that do not recapitulate the complexity of optic flow patterns generated by actual walking through a natural environment. The paper by Muller and colleagues aims to carefully document "retinal" optic flow patterns generated by human participants walking a straight path in real terrains that differ in "smoothness". By doing so, they gain unique insights into an aspect of natural behavior that should move the field forward and allow for the development of new, more principled, computational models that may better explain the visual processing taking place during walking in humans.

Strengths:<br /> Appropriate, state-of-the-art technology was used to obtain a simultaneous assessment of eye movements, head movements, and gait, together with an analysis of the scene, so as to estimate retinal motion maps across the central 90 deg of the visual field. This allowed the team to show that walkers stabilize gaze, causing low velocities to be concentrated around the fovea and faster velocities at the visual periphery (albeit more the periphery of the camera used than the actual visual field). The study concluded that the pattern of optic flow observed around the visual field was most likely related to the translation of the eye and body in space, and the rotations and counter-rotations this entailed to maintain stability. The authors were able to specify what aspects of the retinal motion flow pattern were impacted by terrain roughness, and why (concentration of gaze closer to the body, to control foot placement), and to differentiate this from the impact of lateral eye movements. They were also able to identify generalizable aspects of the pattern of retinal flow across terrains by subsampling identical behaviors in different conditions.

Weaknesses:<br /> While the study has much to commend, it could benefit from additional methodological information about the computations performed to generate the data shown. In addition, an estimation of inter-individual variability, and the role of sex, age, and optical correction would increase our understanding of factors that could impact these results, thus providing a clearer estimate of how generalizable they are outside the confines of the present experiments.

Reviewer #2 (Public Review):

The goal of this study was to provide in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. To achieve this, they had human walkers navigate different natural terrains while they measured information about eyes, body, and the 3D environment. They found average flow fields that resemble the Gibsonian view of optic flow, an asymmetry between upper and lower visual fields, low velocities at the fovea, a compression of directions near the horizontal meridian, and a preponderance of vertical directions modulated by lateral gaze positions.

Strengths of the work include the methodological rigor with which the measurements were obtained. The 3D capture and motion capture systems, which have been tested and published before, are state-of-the-art. In addition, the authors used computer vision to reconstruct the 3D terrain structure from the recorded video. Together this setup makes for an exciting rig that should enable state-of-the-art measurements of eye and body movements during locomotion. The results are presented clearly and convincingly and reveal a number of interesting statistical properties (summarized above) that are a direct result of human walking behavior.

A weakness of the article concerns tying the behavioral results and statistical descriptions to insights about neural organization. Although the authors relate their findings about the statistics of retinal motion to previous literature, the implications of their findings for neural organization remain somewhat speculative and inconclusive. An efficient coding theory of visual motion would indeed suggest that some of the statistics of retinal motion patterns should be reflected in the tuning of neural populations in the visual cortex, but as is the present findings could not be convincingly tied to known findings about the neural code of vision. Thus, the behavioral results remain strong, but the link to neural organization principles appears somewhat weak.

Reviewer #3 (Public Review):

Gaze-stabilizing motor coordination and the resulting patterns of retinal image flow are computed from empirically recorded eye movement and motion capture data. These patterns are assessed in terms of the information that would be potentially useful for guiding locomotion that the retinal signals actually yield. (As opposed to the "ecological" information in the optic array, defined as independent of a particular sensor and sampling strategy).

While the question posed is fundamental, and the concept of the methodology shows promise, there are some methodological details to resolve. Also, some terminological ambiguities remain, which are the legacy of the field not having settled on a standardized meaning for several technical terms that would be consistent across laboratory setups and field experiments.

Technical limits and potential error sources should be discussed more. Additional ideas about how to extend/scale up the approach to tasks with more complex scenes, higher speed, or other additional task demands and what that might reveal beyond the present results could be discussed.

Reviewer #1 (Public Review):

Habituation to noxious insults is a conserved mechanism that may act through varying pain-sensitivity thresholds based on previous sensory experience. Impaired regulation of nociceptive habituation may lead to a chronic pain condition. In the current manuscript, the authors identified additional structural elements of the CaM kinase-1 that regulate the protein shuttling between the cytosol and nucleus during nociceptive habituation. Based on the presented findings, we get a more complex regulatory model and a better understanding of the CMK-1 protein redistribution during stimulation-dependent nociceptive plasticity.

The data is carefully planned and results conclusively support the claims of the authors. The performed experiments are easy to follow and the results obtained are robust and statistically well-powered. The complex regulatory model presented in the manuscript is well supported by the reported data. Finally, the presented data presents a complex and dynamic mechanism of nuclear import and export rates of the CMK-1 protein to control nociceptive plasticity.

Reviewer #2 (Public Review):

In this study, Ippolito and colleagues elucidated the molecular mechanism of CMK-1 shuttling between the nucleus and cytoplasm and its function in the context of regulated thermosensation in C. elegans. This study is built on their previous work that identified a specific Nuclear Export Sequence (NES) required for CMK-1 cytoplasmic localization at 20{degree sign}C, and a specific Nuclear Localization Signal (NLS) to promote prolonged heat (28{degree sign}C)-induced CMK-1 nuclear entry. Here they show additional functional NES and NLS which counteract previously identified elements: the NLS297-307-dependent nuclear entry pathway and the S325-dependent cytoplasmic accumulation. Combined with their previous study, their work suggests a model: upon prolonged FLP neuron stimulation by noxious heat, CaM binding to CMK-1 causes CKK-1-dependent phosphorylation of T179, which in turn has a context-dependent dual effect: it is sufficient for nuclear translocation at 20{degree sign}C in an NLS71-78-dependent manner, and it promotes NES288-294-dependent nuclear export at 28{degree sign}C.

The authors thereby established a direct link between the state of a signal transduction pathway and FLP neuronal activity in response to heat stimulation. They used multiple approaches, including transgenics and reporter quantification analysis to characterize CMK-1 nucleo-cytoplasmic dynamic equilibrium. The experiments are well-designed with appropriate controls and appropriate sample sizes. The data analysis is comprehensive and revealing. The findings expand the functionally relevant intrinsic CMK-1 subcellular localization determinants. The new understanding generated in this study will appeal to readers in the fields of cell biology, signal transduction, and physiology.

Reviewer #1 (Public Review):

In this work, the authors propose a phenomenological grounded theoretical framework to explain why microbial taxonomic richness can show positive, unimodal, as well as negative diversity-temperature gradients. They thus propose to introduce a temperature dependence in the form of the Boltzmann-Arrhenius equation in both species' competitive interaction and growth rates. By means of a mean-field-like approximation, they estimate the probability of having N feasible coexisting species as a function of the normalized growth rate, and average competition strength, which in turn depends on temperature. They find that the shape of the microbial community temperature-richness relationship depends on how rapidly the strength of competition between species pairs increases with temperature relative to an increase in the variance of their growth rates. Furthermore, the mean-field result predicts that the position of richness peak depends on the sign of the covariance between the two main parameters of the Boltzmann-Arrhenius law. Finally, they show that the real-world community-level temperature-richness responses observed are qualitatively reproduced by their model.

I found the work interesting and stimulating, surely tackling a relevant research question such as the effect of thermal physiology on biodiversity patterns through a simple, but quantitative model. Overall, I like the proposed approach.

At the same time, the central mathematical results are not clear in my view, some strong approximations are not discussed, but they hold only in very specific conditions. A lot of important details are missing or scattered here and there, the notation is a little sloppy, and in general, it has been difficult for me to reproduce their finding.

The overall structure and flow of the manuscript can be remarkably improved.

Reviewer #2 (Public Review):

In their paper Variation in thermal physiology can drive the temperature dependence of microbial community richness, Clegg and Parwar present a relatively simple phenomenological model for explaining the wide variety of empirically observed relationships between temperature and diversity in the microbial world. Previous theories such as the Metabolic theory of biodiversity (MTB) and the metabolic niche hypothesis have emphasized the role of energy through either more efficient cellular kinetics or temperature-dependent niches. This paper builds on these works by showing that if one accounts for the variation of temperature sensitivity across species, one can get a much richer set of behaviors consistent with empirical observations.

Overall, I find the manuscript quite compelling and the model presented as a very nice summary of how variability in temperature dependence, simple Arrhenius scaling, and arguments based on modern coexistence theory can be combined to explain empirical observations of species abundance distributions and temperature.

Reviewer #3 (Public Review):

In empirical data, the dependence of microbial diversity on environmental temperature can take multiple different functional forms, while the previous theory has not established a clear understanding of when the temperature-dependence of diversity should take a particular form, and why. The authors seek to understand what forms are possible, and when they will occur, via analysis of the feasibility (i.e. positivity) of Lotka-Volterra equation solutions. This is combined with an assumption for the way that species' growth rates depend on temperature, along with an assumption for the way species interaction rates depend on temperature. Together, this completely specifies the form of the Lotka-Volterra equations, and whether all species in the model can coexist indefinitely at a given temperature, or whether only a lower-diversity subset can persist.

The overall goal is valuable, and the overall approach of using this classic model of species interactions is justifiable. My main question marks relate to the way the conditions on feasibility (i.e. when all species will have positive equilibria), whether and when we need to consider the stability of these feasible solutions, and finally how general the way in which model parameters are specified to depend on temperature. I will expand on these three issues below. A more minor issue is that the authors set up this problem with extensive reference to the interaction of consumers and resources, referencing previous approaches that explicitly model these. Since resources are not explicitly present in the Lotka-Volterra formalism, it would be helpful to have a clearer justification for the authors' rationale in choosing this kind of model.

(1) Conditions on growth and interaction rates for feasibility and stability. The authors approach this using a mean field approximation, and it is important to note that there is no particular temperature dependence assumed here: as far as it goes, this analysis is completely general for arbitrary Lotka-Volterra interactions.

However, the starting point for the authors' mean field analysis is the statement that "it is not possible to meaningfully link the structure of species interactions to the exact closed-form analytical solution for [equilibria] 𝑥^*_𝑖 in the Lotka-Volterra model.

I may be misunderstanding, but I don't agree with this statement. The time-independent equilibrium solution with all species present (i.e. at non-zero abundances) takes the form

x^* = A^{-1}r

where A is the inverse of the community matrix, and r is the vector of growth rates. The exceptions to this would be when one or more species has abundance = 0, or A is not invertible. I don't think the authors intended to tackle either of these cases, but maybe I am misunderstanding that.

So to me, the difficulty here is not in writing a closed-form solution for the equilibrium x^*, it is in writing the inverse matrix as a nice function of the entries of the matrix A itself, which is where the authors want to get to. In this light, it looks to me like the condition for feasibility (i.e. that all x^* are positive, which is necessary for an ecologically-interpretable solution) is maybe an approximation for the inverse of A---perhaps valid when off-diagonal entries are small. A weakness then for me was in understanding the range of validity of this approximation, and whether it still holds when off-diagonal entries of A (i.e. inter-specific interactions) are arbitrarily large. I could not tell from the simulation runs whether this full range of off-diagonal values was tested.

As a secondary issue here, it would have been helpful to understand whether the authors' feasible solutions are always stable to small perturbations. In general, I would expect this to be an additional criterion needed to understand diversity, though as the authors point out there are certain broad classes of solutions where feasibility implies stability.

(2) I did not follow the precise rationale for selecting the temperature dependence of growth rate and interaction rates, or how the latter could be tested with empirical data, though I do think that in principle this could be a valuable way to understand the role of temperature dependence in the Lotka-Volterra equations.

First, as the authors note, "the temperature dependence of resource supply will undoubtedly be an important factor in microbial communities"

Even though resources aren't explicitly modeled here, this suggests to me that at some temperatures, resource supply will be sufficiently low for some species that their growth rates will become negative. For example, if temperature dependence is such that the limiting resource for a given species becomes too low to balance its maintenance costs (and hence mortality rate), it seems that the net growth rate will be negative. The alternative would be that temperature affects resource availability, but never such that a limiting resource leads to a negative growth rate when a taxon is rare.

On the other hand, the functional form for the distribution of growth rates (eq 3) seems to imply that growth rates are always positive. I could imagine that this is a good description of microbial populations in a setting where the resource supply rate is controlled independently of temperature, but it wasn't clear how generally this would hold.

Secondly, while I understand that the growth rate in the exponential phase for a single population can be measured to high precision in the lab as a function of temperature, the assumption for the form of the interaction rates' dependence on temperature seems very hard to test using empirical data. In the section starting L193, the authors seem to fit the model parameters using growth rate dependence on temperature, but then assume that it is reasonable to "use the same thermal response for growth rates and interactions". I did not follow this, and I think a weakness here is in not providing clear evidence that the functional form assumed in Equation (4) actually holds.

Reviewer #2 (Public Review):

Despite high bone mineral density, increased fracture risk has been associated with T2D in humans. In this study, the authors established a model that could mimic some aspects of T2D in mice and then study bone turnover and metabolism in detail.

Strengths<br /> This is an exciting study, the methods are detailed and well done, and the results are presented coherently and support the conclusions.<br /> Previous work from Dr. Long's group over this last decade has established a requirement for glycolysis in osteoblast differentiation. They showed the requirement for glycolysis not only for the anabolic action of PTH but also as an effector downstream of Wnt signaling. Using the T2D mouse model they have generated, they test if manipulating glycolysis and oxidative phosphorylation can rescue some of the detrimental effects on bone in this model.<br /> They use several novel approaches, they use glucose-labeling studies that are relatively underutilized, and it provides some insights into defective TCA cycle. They also utilize BMSCs that have been sorted for performing single-cell sequencing studies to identify specific populations modified with T2D. Unfortunately, the results are modest and need some clarification on what these populations add to the story.<br /> The authors use two approaches: a drug (Metformin) and a number of mouse genetic models to over-express genes involved in the glycolytic pathway using Dox inducible models. The results with overexpressing HIF1 and PFKFB3 show a potential rescue of bone defects with T2D, and Glut1 overexpression does not rescue T2D-induced bone loss.

Concerns<br /> The authors have generated several overexpression models to manipulate the glycolytic pathway to recuse T2D-induced bone loss. The use of DOX in drinking water has been shown to affect mitochondrial metabolism. Did the authors control for these effects? Since both the groups of mice got the DOX in drinking water, there is internal control.<br /> Only one of the rescue experiments had control with the Chow diet. There are some studies that have shown a high-fat diet to be protective of bone loss in TID models.<br /> The use of metformin to correct metabolic dysfunction and, thereby, bone mass is an exciting result. Did the authors test to see if they had in any way rescued this phenotype because of reducing ROS levels? The decrease in OxsPhos seen with the seahorse experiments suggests there could be mitochondrial dysfunction often associated with ROS generation.<br /> All of the experiments used male mice (because STZ use and ease of T2D establishment in males). It would be better if this were made clear in the title.<br /> Is the T2D model presented really represent what is observed in humans? Some experiments to test the other factors implicated in T2D and whether those are modulated in the rescue experiments might help address this.

Reviewer #3 (Public Review):

The manuscript entitled "Osteoblast-intrinsic defect in glucose metabolism impairs bone formation in type II diabetic mice" by Song et al. showed that osteoblast activity was compromised due to impaired glucose metabolism using a youth-onset T2D mouse model. The investigators induced youth-onset T2D in 22-week-old C57BL/6J male mice by a high-fat diet (HFD) starting at 6 weeks of age and injection of low-dose streptozotocin three times at 12-week-old. Then they demonstrated that metformin promoted glycolysis and osteoblast differentiation in vitro and increased bone mass in the diabetic mice. It was also demonstrated that targeted overexpression of Hif1a or Pfkfb3, but not Glut1, in osteoblasts reduced bone loss in T2D mice. Overall, the investigators made a great effort to characterize the changes in metabolism in the bone of the B6/C57 mice by HFD and metformin with microCT, dynamic histomorphometry, C13 isotype labeling in vivo, scRNA-seq and metabolic assays with bone marrow mesenchymal cells in vitro.

Reviewer #1 (Public Review):

The most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) is a G4C2 repeat expansion within the first intron of the C9ORF72 gene. However, how this repeat contributes to disease pathology is still an active area of research. This study takes a targeted approach to analyzing specifically how the C9ORF72 antisense transcript (C4G2) may be contributing to FTD/ALS.

Using an artificial (C4G2)75 antisense cassette, the authors show in both HEK293T cells and cultured neurons that the C4G2 antisense transcript leads to elevated levels of activated PKR and increased phosphorylated eIF2alpha. This then leads to a decreased level of translation, the formation of stress granules, and decreased survival, phenotypes that can be suppressed through the knockdown of PKR. The authors nicely demonstrate that PKR activation upon transfection with their antisense cassette is independent of toxic dipeptide repeat proteins by using reporter constructs that do not create these dipeptides but are still able to activate PKR. Furthermore, using a construct that expresses both sense and antisense transcripts, the authors show that knockdown of the antisense, but not the sense transcript, abrogates the PKR response (demonstrating the specificity of this stress pathway for the antisense RNA). The authors additionally show the relevance of PKR activation in FTD/ALS through the presence of activated PKR and elevated eIF2alpha in ALS postmortem brain tissue.

This paper shows that, at least in model systems, the C4G2 transcript can have cytotoxic effects through the stimulation of PKR. The experiments are well-controlled and fairly comprehensive. The claim that PKR activation occurs via the antisense RNA, and not the sense, is well supported by the data. However, some limitations exist, some of which the authors explicitly recognize. They are as follows:<br /> 1. It is not clear how the results from these reporter constructs inform on the repeat expansion RNAs produced in disease, which can be significantly longer, and might be expressed at different levels. Perhaps if the C4G2 repeat used in this work were expressed at levels comparable to what the antisense transcript is expressed in an actual disease, or in a similar RNA context, PKR would not be activated. This is important to keep in mind.<br /> 2. It is still unclear how PKR is being activated in the presence of C4G2 (it could be direct or indirect). The authors list a variety of explanations in the discussion. A prior study has shown that a similar repeat expansion leads to the accumulation of cytoplasmic dsRNA inclusions marked by TDP-43 (Rodriguez et al., 2021). It would be interesting to see if these inclusions are present upon expression of the antisense construct.<br /> 3. In the context of C9ORF72 FTD/ALS disease, it is still difficult to say how much of the disease pathology is on account of antisense triggered stress responses as opposed to dipeptide repeat, RBP titration, etc. This study nevertheless provides a new perspective to consider for how the C9ORF72 repeat expansion contributes to the diseased state.

Reviewer #2 (Public Review):

The underlying toxic species in C9ORF72 FTD/ALS is debated, with evidence for the contribution of both loss of function and gain of function of sense G4C2 repeat-expanded mRNAs and DRPS has been shown. The authors ask what the role - if any - of the antisense C4G2 repeat expanded mRNAs, which are equally abundant in patient brains, in producing toxicity. They convincingly show a role for these, independent of DRP expression, and distinct from sense G4C2repeat-expanded in toxicity in cell lines, neurons, and zebrafish, mediated via PKR activation. The latter is shown through increased p-eIF2alpha and reduced protein synthesis rates, associated with toxic phenotypes, rescued by PKR knockdown. The authors have achieved their aims, where the excellent data strongly support their conclusions.

The mechanism for PKR activation by antisense but sense repeat-expanded mRNAs is not examined, but the authors reasonably propose secondary structure differences in PKR activation. This could be tested in future work.

The work adds to our understanding of mechanisms of toxicity in repeat disorders, and this particular mechanism has implications for therapy via ISR modulation to reverse the effects of PKR activation.

The human data adds to the spectrum of protein-misfolding neurodegenerative diseases that show UPR/ISR activation, again with implications for therapy via ISR modulation.

Interestingly, PKR knockdown only partially rescues cell toxicity in neuronal cells, possibly reflecting other toxic mechanisms at play.

Reviewer #1 (Public Review):

In the manuscript "Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB", Sacco et. al. solved the crystal structure of S. aureus GpsB, an essential cell growth and division protein. The authors also identified its interactions with the master regulator of cell division FtsZ and a penicillin-binding protein PBP4 that is implicated in B-lactam insensitivity. Although GpsB is essential for growth in S. aureus the reason for its essentiality is poorly understood. The authors used biochemical, biophysical, and crystallographic methods to determine the structure of GpsB and characterized its binding with FtsZ and PBP4. The authors also solved the co-crystal structure of GpsB with the C-terminal peptide of PBP4. These results are significant because it details the interactions of an essential growth protein in S. aureus with known cell division proteins. However, the impact of the work could be further enhanced if the authors had more functional studies to demonstrate the importance of the new hinge motif, the binding with FtsZ C-terminal tail, and PBP4.

Reviewer #2 (Public Review):

This work continues the exploration of the GspB protein as a cytosolic hub for different cell wall enzymes. In particular, this manuscript presents evidence for the direct interaction of GspB with both FtsZ and PBP4 in Staphylococcus aureus. Structural determination is provided for the N-term region of GspB alone and in complex with the small cytosolic region of PBP4 recognized by GspB.

After previously published works from the same group identifying the connection between GspB and FtsZ, and from another group providing the structural basis for the interaction between GspB and PBPs in different bacterial species; the present work provides incremental information for the S. aureus case. The work is sound, and the experimental evidence supports the presented conclusions.

The main strength of the manuscript is providing pieces of evidence of the protein-protein interaction between GspB and FtsZ and between GspB and PBP4.

However, no structural information is provided for the GspB:FtsZ complex, and the 3D structure of the N-term domain of GspB is very similar to previous ones solved for other bacteria, but with the presence of a three-residues insertion that provides flexibility to the domain, a fact that seems to be important in vivo.<br /> The complex of N-term GspB with the cytosolic micro-domain of PBP4, reveals the interactions involved in the recognition; an interaction network that is similar to the previously reported for GspB and PBPs in bacillus subtilis and in Streptococcus pneumonia.

Reviewer #1 (Public Review):

The authors present a study to test the relationships between a measured dopamine marker in the brain - so-called, dopamine synthesis capacity - and various other measures purported to index dopamine function. These measures include questionnaire answers about behaviour, and measured behaviour. Various studies have used these other measures as indices or proxies of dopamine function with some evidence to support this. However, some of the evidence is in small groups or indirect.

The major strength of this study is the size of the sample (n=66-94) compared to other studies and the three different analytical strategies employed - frequentist, Bayesian, and predictive modelling.

Areas, where the study is more limited, are the use of only one marker of dopamine neurochemistry ([18F]FDOPA) and this does not discount relationships with other markers such as pre-synaptic receptors, post-synaptic receptors, and dynamic release. The authors acknowledge that this study does not speak to the general principle of dopamine relationships with other measures. While the numbers are impressive for this type of study the use of correlation means their power is for correlations of 0.32-0.37 and higher (G*power). It is possible genuine relationships between markers do exist but all studies to date, including this one, are underpowered. The Bayesian analysis conducted speaks to this and is a welcome addition. It is also possible that the conclusions are restricted by the participants recruited as they are limited to the ages of 18-43 and it is not clear how representative they are of the general community from the information provided.

The dopamine system is not one entity in terms of system components (pre-synaptic, post-synaptic, etc), but also in terms of subcortical area with a gradient of input from the brainstem and a distinct connectionist anatomy between the striatum and the cortex (via other structures). Here the authors use a segmentation of the striatum to test the relationships. While this is embedded in the methods and results the introduction's treatment of the subcortical dopamine system is as a single entity. This could be improved.

The results of this work have an important impact in that they strongly suggest one cannot use proxies to estimate endogenous neurochemistry (at least in the dopamine system). However, this implies that any other proxy for any other system needs to be (re-)assessed using similar methods. This is not to say that the proxies are not sensitive to dopamine manipulations, but that they cannot by themselves be used instead of direct measurement. Given the number of studies which suggest that a measure of baseline state may predict the effects of dopaminergic drugs, one must question what the baseline state is being measured.

Despite these limitations, the authors have provided the largest assessment of the relationships between [18F] FDOPA-assessed dopamine synthesis capacity and various markers previously linked to dopamine function. In this respect, it is an important negative. This does mean that the assessments used cannot be used to assess 'baseline' states in relation to dopaminergic drug effects, but the mechanism through which this baseline dependency operates is not well understood.

Reviewer #2 (Public Review):

This study examined the relationship between dopamine synthesis capacity, working memory, impulsivity, and spontaneous eye blink rate. The rationale for the study is sound and well-articulated given the results of prior studies suggesting relations between dopaminergic measures and these behavioral measures. Understanding these relationships is important both for understanding the neural and neurochemical correlates of behavioral traits, but also because it has been proposed that these measures might be used as a proxy for dopamine synthesis capacity, which is extremely expensive to collect and requires exposure to radiation. The study used appropriate methods and a major strength is that it was performed in a larger sample than is typical for PET studies, which are typically underpowered due to the expense of using radioligands. Critically, the study did not find evidence for associations. Although the results can be seen as disappointing in that they failed to confirm hypotheses, the findings nevertheless have substantial implications for the field. Specifically, the results argue against the use of these behavioral constructs as a proxy for dopamine synthesis activity. As such, the findings provide a critical corrective for prior conclusions that were derived from past smaller studies.

Reviewer #1 (Public Review):

The manuscript by Lujan and colleagues describes a series of cellular phenotypes associated with the depletion of TANGO2, a poorly characterized gene product but relevant to neurological and muscular disorders. The authors report that TANGO2 associates with membrane-bound organelles, mainly mitochondria, impacting in lipid metabolism and the accumulation of reactive-oxygen species. Based on these observations the authors speculate that TANGO2 function in Acyl-CoA metabolism.

The observations are generally convincing and most of the conclusions appear logical. While the function of TANGO2 remains unclear, the finding that it interferes with lipid metabolism is novel and important. This observation was not developed to a great extent and based on the data presented, the link between TANGO2 and acyl-CoA, as proposed by the authors, appears rather speculative.

1. The data with overexpressed TANGO2 looks convincing but I wonder if the authors analyzed the localization of endogenous TANGO2 by immunofluorescence using the antibody described in Figure S2. The idea that TANGO2 localizes to membrane contact sites between mitochondria and the ER and LDs would also be strengthened by experiments including multiple organelle markers.

2. The changes in LD size in TANGO2-depleted cells are very interesting and consistent with the role of TANGO2 in lipid metabolism. From the lipidomics analysis, it seems that the relative levels of the main neutral lipids in TANGO2-depleted cells remain unaltered (TAG) or even decrease (CE). Therefore, it would be interesting to explore further the increase in LD size for example analyze/display the absolute levels of neutral lipids in the various conditions.

3. Most of the lipidomics changes in TANGO2-depleted cells are observed in lipid species present in very low amounts while the relative abundance of major phospholipids (PC, PE PI) remains mostly unchanged. It would be good to also display the absolute levels of the various lipids analyzed. This is an important point to clarify as it would be unlikely that these major phospholipids are unaffected by an overall defect in Acyl-CoA metabolism, as proposed by the authors.

Reviewer #2 (Public Review):

This is an interesting study that seeks to deorphanize Tango2, a protein linked to muscle dysfunction but with no known function. It reveals that Tango2 primarily co-localizes with mitochondria, and its loss impacts mitochondrial homeostasis. Tango2-depleted cells also accumulate LDs. Lipidomic analysis indicated a partial depletion of diacyl lipids including PA in Tango2-depleted cells, and an accumulation of lyso-lipids such as LPA. The proposed model suggests that Tango2 plays a role in lipid metabolism, potentially in acyl-CoA trafficking and or delivery to lyso-lipids to generate diacyl-lipids for mitochondrial homeostasis, which is defective in tango2-deficient diseases like rhabdomyslosis. In general, this is a well-conducted and potentially important study. The first section which deals with Tango2 localization and profiling of cellular changes in Tango2-depleted cells is well conducted. However, the latter half which seeks to understand how Tango2 loss impacts lipid homeostasis is more preliminary. Lyso-lipids like LPA are definitely altered with tango2 loss, but additional work is necessary to understand whether this is due to increased lyso-lipid synthesis, a block in their acylation, or some combination of factors. Delineating these possibilities will significantly enhance this study.

Reviewer #1 (Public Review):

The manuscript provides a comprehensive analysis of the consequences of a mutation in WDR62 in human pluripotent stem cell-derived progenitor cells and neurons. The experiments are logical and presented well. The data support the conclusion that WDR62 dysfunction causes impaired cell cycle progression and defective neuronal differentiation. The data corroborate previous findings in mouse and human cells and cell lines and extend knowledge to cells that are relevant to the microcephaly characteristic of individuals with WDR62 mutations. The major shortcoming of the data is that it relies on cells from a single donor and so requires additional validation to support the generalization of the conclusions. In addition, limited mechanistic insight is provided.

Reviewer #2 (Public Review):

Dell'Amico and colleagues examine a C-terminal truncating mutation of WDR62, a gene identified as the 2nd most frequent cause of primary microcephaly. The authors generate neural progenitor cells and neurons from patient-derived IPSCs to examine the cell biological phenotypes of the truncation. This reveals the localization of WDR62 in the Golgi apparatus during interphase and suggests that shuttling from the GA to the spindle poles could be a potential mechanism underlying the effects of WDR62 truncation on cortical development.

Whereas these model systems are useful to study certain cell biological aspects of mutated cells, they do not fully recapitulate all features of the cortical development that the authors study. This model system lacks polarity of the tissue, which is important for a correct cell division of radial glia, which in turn is the key process impaired in microcephaly. Together with the inherent heterogeneity of the differentiation protocols, this poses a major weakness to the authors' approaches. On the other hand, the authors' system is well-suited for the analysis of co-localization and they show compelling evidence of the localization of WDR62 to the GA in interphase, which is the main strength of the study. These data are corroborated by immunostainings in fetal human tissue. Minor experiments are still needed to show a direct interaction of WDR62 with GA proteins and to further assess by immunofluorescence the GA-WDR62 co-localization in the radial glia of fetal human samples. Further, the author's interpretation that premature neurogenesis is not occurring in their system should be better supported by additional immunostaining. Finally, the manuscript is well written and the methods are adequately explained.

Reviewer #3 (Public Review):

WDR62 is a spindle pole-associated scaffold protein. Recessive mutations in WDR62 account for the second most common cause of autosomal recessive primary microcephaly (MCPH). This paper investigates how a C-terminal truncating mutation D955AfsX112 in WDR62 causes MCPH using iPSCs from a patient. The authors generated neuroepithelial (NES) cells, cortical progenitors, and neurons from the patient-derived and isogenic retro-mutated iPSC lines. They found that: (1) the mutant WDR62 fails to localize to the spindle poles during mitosis; (2) patient-derived iPS-NES cells exhibit shorter primary cilia and significantly smaller spindle angles; (3) the mutation leads to differentiation defects in iPSC-derived cortical neurons; (4) during the interphase-to-mitosis transition, WDR62 translocates from the Golgi apparatus to the spindle poles in a microtubule-dependent manner; and (5) the mutation prevents WDR62 shuttling from the Golgi to the spindle poles. Using the isogenic retro-mutated iPSC lines as the control increased the rigor of the current study. In general, this is a very carefully designed study, the data support the authors' conclusions, and confirm previous findings of WDR62 functions.

Reviewer #1 (Public Review):

The authors attempted to delete a rhodopsin allele with single-nucleotide mutation seen in a Chinese subpopulation of autosomal dominant retinitis pigmentosa patients, (Rho-T17M). This was done in vitro and in vivo, while keeping the Rho wild type allele intact in vitro and in vivo using CRISPR-SaCAS9 guide RNA-specific approach, a previously established technique. In this study, solid in vitro data was presented showing that one of the tested guide RNAs was effective to specifically delete targeted the Rho-T17M sequence of synthetic DNA as well as in iPSCs from RP patients. However, the in vivo part of this study is incomplete. The issues are: 1. confusing choice of disease animal model (Rho-5m mice that carry 4 additional rhodopsin mutations other than the targeted T17M); 2. no proof of gene editing efficiency at the cellular level of the targeted cell type (i.e. what percentage of rod photoreceptors lose the T17M disease mutation?); and 3) lack of evidence of therapeutic potential (i.e. is there any rescue of vision in the mouse disease model or any toxicity due to the vector itself?).

Reviewer #2 (Public Review):

The authors attempt to develop an allele-specific editing approach targeting RHO-T17M mutation for potential therapeutic use to treat the mutation associated with autosomal dominant retinitis pigmentosa.

1) The authors reported three sgRNAs for the RHO T17M allele for verification. It would be helpful to describe details of the discovery phase of these sgRNAs, including design, in silico predictions, inclusion criteria, off-target analysis, etc.

2) The authors claim that the targeted gene-editing efficiencies are dose-dependent. However, data were presented from only one mouse for the 5ｘ108 dose group (line 231-237), which might need more explanation.

3) With respect to Fig. 4C, the flat-mount retina is not representative. A better image of flat-mount of retina is preferred.

4) With respect to Fig. 6B & 6C, it seems that T17M protein and RHO-5m protein are likely detected in both cytoplasm and plasma membrane rather than being limited to the cytoplasm alone.

5) The therapeutic efficacy benefit should be supported by data of photoreceptor function and cell preservation after treatment. It is be better to include two more control groups, namely wild-type mice and untreated mutant mice, which may help evaluate improved response after treatment.

6) The mouse lines are confusing. Did the authors generate three lines of mice, including RHOwt/hum, Mut-RHOwt/hum, RHOhum/m-hum mice? Did the authors use the Rhohum/m-hum mice for verification of cutting efficiencies, whereas they use the other two lines of mice for rescue experiments? The authors should clarify.

7) Mut-RHOwt/hum mice have previously been reported to have fundus pigment abnormalities, so the fundus should be examined after rescue. The expression of Rho-5M mRNA was reduced in vitro. Was the expression of RHO mRNA also down regulated after rescue as well as in vitro? Did the subretinal injection of GFP spread to the whole retina? This can be determined with retinal flat mount or panretinal staining using GFP labeling. The authors showed that the cell numbers in the ONL were increased in the treatment group compared with the control group at 9 mpi. Were the other nuclear layers or plexiform layer also affected? Did the other retinal cells develop normally? Figure 8 showed retinal functions with AAV-based SaCas9/17-Sg2 in Mut-Rhowt/hum mice. ERG of Mut-Rhowt/hum mice without treatment are also needed.

The efficiency and safety of RHO T17M allele-specific editing in this paper are well supported by in vitro and in vivo experiments.

The fundamental basis of the study design should be clearly stated, ie which truncation variants in RHO cause disease or not. It is reported that truncation variants occurring before K296 are likely benign, which should be mentioned. This is the key starting point for this kind of study and is not limited to RHO. but as an allele-specific gene editing approach as a potential therapy for dominant mutations in any gene for which heterozygous loss-of-function is tolerated in the whole gene or in part of the gene (mostly at N-terminals). Apart from RHO, in fact, N-terminal truncating variants in several other IRD associated genes have been reported to be benign in heterozygotes, including CRX, TOPORS, RP1, etc. This study verified the efficiency and safety of this approach based on both patient derived iPSC and humanized animal models which are unique compared with other studies on RHO.

Reviewer #1 (Public Review):

According to current knowledge, zebrafish neurons maintain the capacity of regenerating with the exception of adult cerebellar Purkinje cells (PC), which are thought to have lost this property. Regeneration instead occurs at larval stages but whether newly generated PC form fully functional circuits is still unclear. This elegant and well-performed study takes advantage of a transgenic zebrafish line that enables inducing apoptosis under a tamoxifen-inducible system and at the same time visualizes PCs morphology through a membrane tagged RFP. Using this line (and other lines that tag radial glial and ventricular progenitors) in combination with morphological and functional analysis, the authors show that ventricular progenitors retain the lifelong ability to regenerate PCs. At larval stages, the newly regenerated PCs form fully functional circuits that lead to normal behavior. In adults, PC regeneration is less efficient (and PCs are also less prone to undergo apoptosis) but sufficient to support exploratory behavior. This study resolves the controversial issue of whether adult PC regeneration is possible and demonstrates that newly formed PCs at larval and adult stages can form functional circuits that support normal behavior.

This is a well-performed and carefully executed and quantified study. There is however a point that needs clarification:

The authors state that acute regeneration occurs between 5-10dpt. However, the graphs in Fig 1D, F, and 2F indicate that most PC generation occurs from 20-30 days. What happens in this period? Does proliferation increase? Can the authors perform BrdU incorporation between 6 days and 1 month? Related to this, as the authors indicate in lines 129-131, the regeneration of new PCs overlaps with normal development. Are other neuronal cell types generated in appropriate numbers?

Reviewer #2 (Public Review):

In this paper, Pose-Méndez and colleagues have investigated the lifelong ability of zebrafish for functional Purkinje cell regeneration after selective ablation. Previous studies have determined that the adult zebrafish cerebellum lacks the capacity to regenerate Purkinje cells after traumatic injury. The authors use an elegant approach to determine whether selective ablation of Purkinje cells, a scenario closer to neurodegenerative disease, would allow for regeneration. The overall message is, that Purkinje cell regeneration is accomplished at every age after targeted ablation. The authors find in a series of well-executed functional and behavioral experiments that selective loss of Purkinje cells leads to a change in neuronal circuit activity and behaviors. During the regeneration process and interestingly before the full recovery of Purkinje cell numbers compared to controls neuronal activity as well as behaviors are recovered.

Reviewer #3 (Public Review):

In "Lifelong regeneration of cerebellar Purkinje neurons after induced cell ablation in zebrafish" by Pose-Mendez and colleagues, the authors followed the regenerative properties that Purkinje cells have in larvae and adult Zebrafish. These properties common in teleostean and other animals are rare in mammals and, therefore, their study is of great interest to the neurodevelopmental community.

In this work, the authors use an already established animal model (PC-ATTACTM) to selectively ablate Purkinje cells in the larvae and adult Zebrafish, in a temporal control manner, that is by administering 4-OHT at defined stages. In doing so, the authors show that a full recovery of an ablated Purkinje cell population can be achieved when the ablation is induced in the larval stage, but this recovery is more modest when the ablation is induced in the adult stage, albeit very significant. The authors also show that regenerated Purkinje cells quickly elaborate their native electrical properties and integrate into functional circuits, which allow for the recuperation of motor behaviors produced by the loss of ablated Purkinje cells.

Overall, the work by Pose-Mendez and colleagues contributes to our understanding of neuronal regeneration in non-mammals. Technically, this study is well conducted and the provided data support most of the conclusions made by the authors.

Reviewer #1 (Public Review):

In this manuscript, Gonzalez et al investigated the dynamics of dopamine signals, measured with optophysiological methods in the lateral shell of the nucleus accumbens (LNAc), in response to different types of visual stimuli. Contrary to most current theories of dopamine signaling, the authors found that LNAcc dopamine transients tracked sensory transitions in visual stimulation rather than any immediately apparent motivational variable. This unorthodox finding is of potential interest to the field, as it suggests that dopamine in this particular area of the striatum supports a very different, albeit unclear behavioral function than what has been previously attributed to this neuromodulator. Many of the approaches used by the authors were very elegant, like the careful selection of visual stimuli parameters and the use of Gnat1/2 KO mice to demonstrate that the dopamine responses were directly dependent on the visual stimulation of rods and cones. That said, the authors did not discuss how their findings relate to much previously published work, many of which offer potential alternative explanations for their results. It is also not clear from the manuscript text which mice were used for which experiments, and how testing history might affect the results.

Reviewer #2 (Public Review):

In this elegant work,  the authors investigated dopamine release (measured by dLight sensor fiber photometry) in the nucleus accumbens shell, in response to salient luminance change. They show that abrupt visual stimuli - including stimuli not detectable by the human eye - can evoke robust dopamine release in the accumbens shell.

The fact that dopamine signals can be evoked by salient sensory stimuli is not itself novel, but the paper manages to make several important and new findings:

1. The authors show that the dopamine signal is not related to the level of threat evoked by the visual stimuli. <br /> 2. They provide important detail about the stimuli parameters relevant to dopamine release. For instance, they show that the rate of luminance change (or abruptness) is a key factor in evoking dopamine responses.<br /> 3. They show that robust dopamine responses can be evoked by visual stimuli of low intensity,  including stimuli not perceptible by the human eye.<br /> 4. They show that these dopamine responses can be evoked by all wavelengths in the visible spectrum (with some higher sensitivity at certain wavelengths).<br /> 5. Finally, by recording dopamine responses in two knockout mice strains, the authors show that the light-evoked dopamine release critically relies on rod and cone photoreceptors, but not melanopsin phototransduction. 

These results add to a series of recent findings showing that dopamine signals are not restricted to the encoding of reward prediction error, but instead contribute to signaling environmental changes more broadly. The study has been skillfully executed, the results are clear and appropriately analyzed, and the manuscript is very well written. Although the work did not include control mice lacking the dLight sensor, the fact that light-evoked dopamine responses were not observed in mice lacking cone + rod phototransduction is strong evidence that the fiberphotometry signals were not due to direct light artifacts.

Comment/concerns are minor:

1. The authors show that the dopamine response evoked by a brief visual stimulus is drastically reduced when the visual stimulus is repeated in rapid succession (stimulus train). The authors interpret this as evidence for the HABITUATION of this light-evoked dopamine release. An alternative explanation is that it is the prediction of the stimulus that is responsible for canceling the dopamine response (i.e. sensory prediction error). The authors should discuss this alternative explanation for this finding.

2. Although the study largely focuses on dopamine responses to visual stimuli, the results are largely consistent with previous studies showing dopamine signals encoding value-neutral changes in sensory inputs (i.e. sensory prediction errors) in different modalities (taste or odors; cf. Takahashi et al., 2017, Neuron; Howard & Kahnt, 2018, Nat. Comm.). The authors might want to cite those papers (note that I am not affiliated with those papers).

Reviewer #3 (Public Review):<br /> <br /> Gonzalez and colleagues investigate dopamine signals in response to visual stimuli. This work builds on the longstanding notion that dopamine neurons respond to unexpected sensory stimuli, including visual cues. Using fiber photometry measurements of a fluorescent dopamine sensor, they find that in the lateral ventral striatum, dopamine signals reliably report salient transitions in illuminance. Dopamine signals scale with light intensity and the speed of illuminance changes. They further find that the frequency of illuminance transitions, rather than the number, dictates the extent that dopamine signals habituate. In a number of studies, they characterize dopamine signals to light of different wavelengths, durations, and intensities. These results shed new "light" on the role of dopamine in signaling salience, independent of reward or threat learning. This work is elegantly done and compelling. While the results are potentially specific to this region of the striatum, rather than a broad dopaminergic profile of visual stimulus encoding, this work offers valuable insight into dopamine function, as well as a practical guide and considerations for the implementation of visual stimuli in behavioral tasks that assay dopamine systems.

Reviewer #1 (Public Review):

The endothelin ETB receptor is a G-protein coupled receptor activated by vasoactive peptide endothelins, causing vaslorelaxtion in smooth muscle. By determining the Cryo EM structure of human ETB in complex with the vasoconstricting peptide ET-1 and the inhibitory G-protein (Gi), the study represents a convincing insight into agonist-induced receptor activation and transducer-coupling. The complex structure is solid and will appeal to the GPCR and pharmacology communities.

Strengthens: The authors have managed to obtain the first G-protein complex structure of an ETB receptor by working with a receptor that still retains G-protein coupling (i.e. not a thermostabilized mutant) and by developing new methodologies into how the G-protein is remotely tethered to the GPCR. The Cryo EM structural details highlight clear differences into how the G-protein binds that also includes the more downward movement of TM7.

Weaknesses: While it is technically challenging to obtain an endothelin-1-ETB-Gi complex, the fusion approach means that there is equilibrium is already pushed towards a complex that may otherwise require lipids, such as PIP2. Whilst I don't know what may alter how alpha 5 interacts with ETB, this cannot be ruled out either.

Reviewer #2 (Public Review):

This study adds value in the relatively new field, specifically in the topic of ET-B receptor. In this study the authors provide a new structure in ET-B receptor that might be beneficial to the development of ET-B agonist. However, from the clinical and physiological point of view, the manuscript did not provide sufficient evidence in its current form.

Reviewer #3 (Public Review):

This manuscript by Sano et al., presents cryo-EM structure of endothelin-1-bound endothelin B receptor (ETbR) in complex with heterotrimeric G-proteins. The structural snapshot provides important information about agonist-induced receptor activation and transducer-coupling. This manuscript also designs and present a successful case example for a variation of previously used NanoBiT-fusion-based strategy to stabilize GPCR-G-protein complexes. This strategy may be broadly applicable to other GPCR-G-protein complexes as well, and therefore, also provides an important methodological advance. Overall, the experimental design and interpretation of the structure are excellent, and the manuscript present an easy-to-follow coherent story. Considering the importance of ETbR signaling in multiple physiological and disease conditions, this structural snapshot, taken together with earlier structural studies by the same laboratory, advances the ETbR biology significantly with potential for novel ligand discovery. This manuscript is also available as a preprint in bioRxiv as well as another manuscript from Xu and Jiang group. Considering the structural information presented in these manuscripts, I would strongly suggest that even if the other manuscript is published somewhere before this one, it should not be viewed as a compromise on novelty, and rather considered as complementary information from independent studies that further strengthen the impact.

Reviewer #1 (Public Review):

This manuscript describes efforts to understand how independence from ribonucleotide reduction might evolve in obligate intracellular bacterial pathogens using E. coli as a model for this process. The authors successfully deleted the three ribonucleotide reductase (RNR) operons present in E. coli and showed that growth of this knockout strain can be achieved with deoxyribonucleotide supplementation. They also performed evolutionary experiments and analysis of cell growth and morphology under conditions of low nucleotide availability. In this work, they established that certain genes are consistently mutated to compensate for the loss of RNR activity and the low availability of deoxynucleotides. Comparison to genomes of intracellular pathogens that lack RNR genes shows that these patterns are largely conserved.

While the experimental results support the conclusions of the study, the authors do report changes in cell morphology upon the growth of the RNR knockout strains with low concentrations of nucleotides. It would be ideal to note this complication earlier in the manuscript. And to clarify how the possibility of cell elongation might affect the OD measurements in Figure 3 describing the experiments to establish that dC is necessary for growth in the knockout strain. It would also be ideal to provide a more detailed explanation for that observation in the discussion.

Reviewer #2 (Public Review):

Ribonucleotide reductase (RNR) is crucial for de novo synthesis of the dNTP building blocks needed for DNA synthesis and is essential in nearly all organisms. In the current study, all three E. coli RNRs have been removed and the essential function of the enzyme is bypassed by the introduction of an exogenous deoxyribonucleoside kinase that enables dNTP production via salvage synthesis. This leads to a complete dependency on exogenously supplied deoxyribonucleosides (dNs), loss of control of dNTP regulation, and a highly increased mutation rate. The bacteria could also grow with only supplied deoxycytidine (and no other dNs), indicating that all dNTPs could be synthesized from deoxycytidine. An evolutionary analysis of the recombinant E. coli strain grown in multiple generations showed that mutations accumulated in genes involved in the catabolism of deoxycytidine and deoxyribose-1-P, supporting a model that all the other deoxyribonucleosides can be produced by a phosphorylase using nucleobases and deoxyribose-1-P as substrates and that the deoxycytidine (besides being a precursor of dCTP) could be a substrate to produce the deoxyribose-1-P needed by the phosphorylase working in the opposite direction.

The story is very interesting with novel findings, and the experiments are well performed. There are a few missing pieces of information, but on the other hand, it is many steps to cover if everything is going to be shown in a single paper and I came to the conclusion that the data is enough at this stage. One of the missing points for future research is to check what happens with the dNTP pools. RNR is a very important enzyme to control the dNTP levels and it is likely that it is unbalanced dNTP pools that lead to the increased mutation rates. However, it would be interesting to really measure the dNTP pools and connect them to the mutations reported. Another missing piece is to identify which nucleoside phosphorylase is involved and investigate its substrate specificity to better understand why the cells can live on deoxycytidine but not other dNs.

Reviewer #3 (Public Review):

The study focuses on a compelling question focusing on a largely indispensable mechanism, ribonucleotide reduction. The authors generate a unique specific bacterial strain where the ribonucleotide reducatase operon, entirely, is deleted. They grow the mutant strain in environments that have various amounts of the necessary deoxyribonucleoside levels, further, they perform evolution experiments to see whether and how the evolved lines would be able to adapt to the limited deoxyribonucleosides. Finally, researchers identify key mutations and generate key isogenic genetic constructs where target mutants are deleted. A summary postulation based on the evolutionary trajectory of ribonucleotide reduction by bacteria is presented. Overall, the study is well presented, well-justified, and builds on fairly classic genetic and evolution experiments. The select question and hypotheses and the overall framing of the story are fairly novel for the respective communities. The results should be interesting to evolutionary biology researchers, especially those interested in RNA>DNA directional evolution, as well as molecular microbiologists interested in the ribonucleotide reception dependence and selection by the environment. A discussion on the limitations of the laboratory study for the broader understanding of the host dependence during endosymbiosis and parasitism would be a good addition given the emphasis on this phenomenon as a part of the broader impacts of the study.

Reviewer #1 (Public Review):

This work presents a unification model (of sorts) for explaining how the flow of evidence through networks can be controlled during decision-making. The authors combine two general frameworks previously used as neural models of cortical decision-making, dynamic normalization (that implement value encoding via firing activity) and recurrent network models (which capture winner-take-all selection processes) into a unified model called the local disinhibition-based decision model (LDDM). The simple motif of the LDDM allows for the disinhibition of excitatory cells that represent the engagement of individual actions that happens through a recurrent inhibitory loop (i.e., a leaky competing accumulator). The authors show how the LDDM works effectively well at explaining both decision dynamics and the properties of cortical cells during perceptual decision-making tasks.

All in all, I thought this was an interesting study with an ambitious goal. But like any good study, there are some open issues worth noting and correcting.

MAJOR CONCERNS

1. Big picture

This was a comprehensive and extremely well-vetted set of theoretical experiments. However, the scope and complexity also made the take-home message hard to discern. The abstract and most of the introduction focus on the framing of LDDM as a hybrid of dynamic normalization models (DNM) and recurrent network models (RNMs). This is sold as a unification of value normalization and selection into a novel unified framework. Then the focus shifts to the role of disinhibition in decision-making. Then in the Discussion, the goal is stated as to determine whether the LDDM generates persistent activity and does this activity differ from RNMs. As a reader, it seems like the paper jumps between two high-level goals: 1) the unification of DNM and RNM architectures, and 2) the role of disinhibition. This constant changing makes it hard to focus as the reader goes on. So what is the big picture goal specifically?

Also, the framing of value normalization and WTA as a novel computational goal is a bit odd as this is a major focus of the field of reinforcement learning (both abstractly at the computational level and more concretely in models of the circuits that regulate it). I know that the authors do not think they are the first to unify value judgements with selection criteria. The writing just comes across that way and should be clarified.

2. Link to other models

The LDDM is described as a novel unification of value normalization and winner-take-all (WTA) selection, combining value processing and selection. While the authors do an excellent job of referencing a significant chunk of the decision neuroscience literature (160 references!) the motif they end up designing has a highly similar structure to a well-known neural circuit linked to decision-making: the cortico-basal ganglia pathways. Extensive work over the past 20+ years has highlighted how cortical-basal ganglia loops work via disinhibition of cortical decision units in a similar way as the LDDM (see the work by Michael Frank, Wei Wei, Jonathan Rubin, Fred Hamker, Rafal Bogacz, and many others). It was surprising to not see this link brought up in the paper as most of the framing was on the possibility of the LDDM representing cortical motifs, yet as far as I know, there does not exist evidence for such architectures in the cortex, but there is in these cortical-basal ganglia systems.

3. Model evaluations

The authors do a great job of extensively probing the LDDM under different conditions and against some empirical data. However, most of the time there is no "control" model or current state-of-the-art model that the LDDM is being compared against. In a few of the simulation experiments, the LDDM is compared against the DNM and RNM alone, so as to show how the two components of the LDDM motif compare against the holistic model itself. But this component model comparison is inconsistently used across simulation experiments.

Also, it is worth asking whether the DNM and RNM are appropriate comparison models to vet the LDDM against for two reasons. First, these are the components of the full LDDM. So these tests show us how the two underlying architectural systems that go into LDDM perform independently, but not necessarily how the LDDM compares against other architectures without these features. Second, as pointed out in my previous comment, the LDDM is a more complex model, with more parameters, than either the DNM or RNM. The field of decision neuroscience is awash in competing decision models (including probabilistic attractor models, non-recurrent integrators, etc.). If we really want to understand the utility of the LDDM, it would be good to know how it performs against similarly complex models, as opposed to its two underlying component models.

4. Comparison to physiological data

I quite enjoyed the comparisons of the excitatory cell activity to empirical data from the Shadlen lab experiments. However, these were largely qualitative in nature. In conjunction with my prior point on the models that the LDDM is being compared against, it would be ideal to have a direct measure of model fits that can be used to compare the performance of different competing "control" models. These measures would have to account for differences in model complexity (e.g., AIC or BIC), but such an analysis would help the reader understand the utility of the LDDM in connecting with empirical data much better.

Reviewer #2 (Public Review):

The aim of this article was to create a biologically plausible model of decision-making that can both represent a choice's value and reproduce winner-take-all ramping behavior that determines the choice, two fundamental components of value-based decision-making. Both of these aspects have been studied and modeled independently but empirical studies have found that single neurons can switch between both of the aspects (i.e., from representing value to winner-take-all ramping behavior) in ways that are not well described by current biological plausible models of decision making.

The current article provides a thorough investigation of a new model (the local disinhibition decision model; LDDM) that has the goal of combining value representations and winner-takes-all ramping dynamics related to choice. Their model uses biologically plausible disinhibition to control the levels of inhibition in a local network of simulated neurons. Through a careful series of simulation experiments, they demonstrate that their network can first represent the value of different options, then switch to winner-takes-all ramping dynamics when a choice needs to be made. They further demonstrate that their single model reproduces key components of value-based and winner-takes-all dynamics found in both neural and behavioral data. They additionally conduct simulation studies to demonstrate that recurrent excitatory properties in their network produce value-persistence behavior that could be related to memory. They end by conducting a careful simulation study of the influence of GABA agonists that provide clear and testable predictions of their proposed role of inhibition in the neural processes that underlie decision-making. This last piece is especially important as it provides a clear set of predictions and experiments to help support or falsify their model.

There are overall many strengths to this paper. As the authors note, current network models do not explain both value-based and ramping-like decision-making properties. Their thorough simulation studies and their validation against empirical neural and behavioral data will be of strong interest to neuroscientists and psychologists interested in value-based decision-making. The simulations related to persistence and the GABA-agonist experiments they propose also provide very clear guidelines for future research that would help advance the field of decision-making research.

Although the methods and model were generally clear, there was a fair amount of emphasis on the role of recurrence in the LDDM, but very little evidence that recurrence was important or necessary for any of the empirical data examined. The authors do demonstrate the importance of recurrence in some of their simulation studies (particularly in their studies of persistence), but these would need to be compared against empirical data to be validated. Nevertheless, the model and thorough simulation investigations will likely help develop more precise theories of value-based decision-making.

Reviewer #3 (Public Review):

Shen et al. attempt to reconcile two distinct features of neural responses in frontoparietal areas during perceptual and value-guided decision-making into a single biologically realistic circuit model. First, previous work has demonstrated that value coding in the parietal cortex is relative (dependent on the value of all available choice options) and that this feature can be explained by divisive normalization, implemented using adaptive gain control in a recurrently connected circuit model (Louie et al, 2011). Second, a wealth of previous studies on perceptual decision-making (Gold & Shadlen 2007) have provided strong evidence that competitive winner-take-all dynamics implemented through recurrent dynamics characterized by mutual inhibition (Wang 2008) can account for categorical choice coding. The authors propose a circuit model whose key feature is the flexible gating of 'disinhibition', which captures both types of computation - divisive normalization and winner-take-all competition. The model is qualitatively able to explain the 'early' transients in parietal neural responses, which show signatures of divisive normalization indicating a relative value code, persistent activity during delay periods, and 'late' accumulation-to-bound type categorical responses prior to the report of choice/action onset.

The attempt to integrate these two sets of findings by a unified circuit model is certainly interesting and would be useful to those who seek a tighter link between biologically realistic recurrent neural network models and neural recordings. I also appreciate the effort undertaken by the authors in using analytical tools to gain an understanding of the underlying dynamical mechanism of the proposed model. However, I have two major concerns. First, the manuscript in its current form lacks sufficient clarity, specifically in how some of the key parameters of the model are supposed to be interpreted (see point 1 below). Second, the authors overlook important previous work that is closely related to the ideas that are being presented in this paper (see point 2 below).

1) The behavior of the proposed model is critically dependent on a single parameter 'beta' whose value, the authors claim, controls the switch from value-coding to choice-coding. However, the precise definition/interpretation of 'beta' seems inconsistent in different parts of the text. I elaborate on this issue in sub-points (1a-b) below:

1a). For instance, in the equations of the main text (Equations 1-3), 'beta' is used to denote the coupling from the excitatory units (R) to the disinhibitory units (D) in Equations 1-3. However, in the main figures (Fig 2) and in the methods (Equation 5-8), 'beta' is instead used to refer to the coupling between the disinhibitory (D) and the inhibitory gain control units (G). Based on my reading of the text (and the predominant definition used by the authors themselves in the main figures and the methods), it seems that 'beta' should be the coupling between the D and G units.

1b). A more general and critical issue is the failure to clearly specify whether this coupling of D-G units (parameterized by 'beta') should be interpreted as a 'functional' one, or an 'anatomical' one. A straightforward interpretation of the model equations (Equations 5-8) suggests that 'beta' is the synaptic weight (anatomical coupling) between the D and G units/populations. However, significant portions of the text seem to indicate otherwise (i.e a 'functional' coupling). I elaborate on this in subpoints (i-iii) below:

(1b-i). One of the main claims of the paper is that the value of 'beta' is under 'external' top-down control (Figure 2 caption, lines 124-126). When 'beta' equals zero, the model is consistent with the previous DNM model (dynamic normalization, Louie et al 2011), but for moderate/large non-zero values of 'beta', the network exhibits WTA dynamics. If 'beta' is indeed the anatomical coupling between D and G (as suggested by the equations of the model), then, are we to interpret that the synaptic weight between D-G is changed by the top-down control signal within a trial? My understanding of the text suggests that this is not in fact the case. Instead, the authors seem to want to convey that top-down input "functionally" gates the activity of D units. When the top-down control signal is "off", the disinhibitory units (D) are "effectively absent" (i.e their activity is clamped at zero as in the schematic in Fig 2B), and therefore do not drive the G units. This would in-turn be equivalent to there being no "anatomical coupling" between D and G. However when the top-down signal is "on", D units have non-zero activity (schematic in Fig 2B), and therefore drive the G units, ultimately resulting in WTA-like dynamics.

(1b-ii). Therefore, it seems like when the authors say that beta equals zero during the value coding phase they are almost certainly referring to a functional coupling from D to G, or else it would be inconsistent with their other claim that the proposed model flexibly reconfigures dynamics only through a single top-down input but without a change to the circuit architecture (reiterated in lines 398-399, 442-444, 544-546, 557-558, 579-590). However, such a 'functional' definition of 'beta' would seem inconsistent with how it should actually be interpreted based on the model equations, and also somewhat misleading considering the claim that the proposed network is a biologically realistic circuit model.

(1b-iii). The only way to reconcile the results with an 'anatomical' interpretation of 'beta' is if there is a way to clamp the values of the 'D' units to zero when the top-down control signal is 'off'. Considering that the D units also integrate feed-forward inputs from the excitatory R units (Fig 2, Equations 1-3 or 5-8), this can be achieved either via a non-linearity, or if the top-down control input multiplicatively gates the synapse (consistent with the argument made in lines 115-116 and 585-586 that this top-down control signal is 'neuromodulatory' in nature). Neither of these two scenarios seems to be consistent with the basic definition of the model (Equations 1-3), which therefore confirms my suspicion that the interpretation of 'beta' being used in the text is more consistent with a 'functional' coupling from D to G.

2) The main contribution of the manuscript is to integrate the characteristics of the dynamic normalization model (Louie et al, 2011) and the winner-take-all behavior of recurrent circuit models that employ mutual inhibition (Wang, 2008), into a circuit motif that can flexibly switch between these two computations. The main ingredient for achieving this seems to be the dynamical 'gating' of the disinhibition, which produces a switch in the dynamics, from point-attractor-like 'stable' dynamics during value coding to saddle-point-like 'unstable' dynamics during categorical choice coding. While the specific use of disinhibition to switch between these two computations is new, the authors fail to cite previous work that has explored similar ideas that are closely related to the results being presented in their study. It would be very useful if the authors can elaborate on the relationship between their work and some of these previous studies. I elaborate on this point in (a-b) below:

2a) While the authors may be correct in claiming that RNM models based on mutual inhibition are incapable of relative value coding, it has already been shown previously that RNM models characterized by mutual inhibition can be flexibly reconfigured to produce dynamical regimes other than those that just support WTA competition (Machens, Romo & Brody, 2005). Similar to the behavior of the proposed model (Fig 9), the model by Machens and colleagues can flexibly switch between point-attractor dynamics (during stimulus encoding), line-attractor dynamics (during working memory), and saddle-point dynamics (during categorical choice) depending on the task epoch. It achieves this via a flexible reconfiguration of the external inputs to the RNM. Therefore, the authors should acknowledge that the mechanism they propose may just be one of many potential ways in which a single circuit motif is reconfigured to produce different task dynamics. This also brings into question their claim that the type of persistent activity produced by the model is "novel", which I don't believe it is (see Machens et al 2005 for the same line-attractor-based mechanism for working memory)

2b) The authors also fail to cite or describe their work in relation to previous work that has used disinhibition-based circuit motifs to achieve all 3 proposed functions of their model - (i) divisive normalization (Litwin-Kumar et al, 2016), (ii) flexible gating/decision making (Yang et al, 2016), and working memory maintenance (Kim & Sejnowski,2021)

Reviewer #1 (Public Review):<br /> <br /> The pH-dependent conformational change of the envelope protein in flaviviruses is required for the infection process, thus it represents an attractive target for drug development. In this study, the authors conducted extensive atomistic simulations for models for the envelope in six flaviviruses. Using a benzene-mapping approach, they were able to identify several cryptic binding sites that can be targeted for drug development. One of the cryptic binding site was observed in a previous study to be occupied by a detergent molecule, while the other cryptic binding site is located at domain interface. The second binding site involves a cluster of ionizable residues. Using constant pH simulations, the authors suggested that the cluster of ionizable residues contribute to the pH dependent conformational rearrangements. This cluster model helps to explain the inconsistencies reported in the literature regarding the role of several key histidine residues as pH sensors. Overall, the study has provided new mechanistic insights that can be taken advantage of in future drug developments that target flaviviruses. The work also highlights the importance of constant pH simulations to the analysis of pH sensitive biological processes.

Reviewer #2 (Public Review):

The authors made an applaudable attempt to identify druggable cryptic pockets and address a controversy regarding a pH switch of a very large system of significant biological and Pharmaceutical interest. Due to the size of the system and uncertainty in the membrane interactions/curvature the draft produces etc, it is a nontrivial task. By using a previously validated mixed solvent (i.e., benzene mapping) protocol, the authors were able to analyze the potential pockets in the entire system. This is big technical advance and the protocol can be used by other works in the field for studying cryptic pockets.

Reviewer #3 (Public Review):

This work dives into the inner molecular workings of viruses such as yellow fever, Zika, and tick borne encephalitis. Due to their pathogenic nature, these are active targets for drug development, and motivated by this, the authors set out to search for so-called "cryptic" binding pockets, concealed from the protein surface and therefore often missed. Using atomistic computer simulations of viral rafts embedded in lipid membranes, the authors present new methodology to detect and characterise structural and electrostatic features of viral envelope proteins. By mixing in a small organic co-solvent (benzene) that acts as a drug proxy, structural fluctuations are enhanced, which reveal hitherto hidden binding pockets. The authors convincingly show that this perturbation has only a minute effect on protein secondary structure. The technique revealed a new cryptic binding pocket that is well conserved across multiple flaviviruses.

The cryptic site involves four potentially charged residues and to understand their interplay, constant pH molecular dynamics simulations are combined with a detailed structural and electrostatic analysis of the binding pocket.<br /> Due it's multi-dimensional nature, the response to a possible pH change is a complex process and the authors present a compelling analysis involving charge states, inter-residue distances (reduced using PCA), and structural features of the pocket. An important conclusion is that the role of histidine is less important than previously thought: the pH dependent behaviour is a collective property of the pocket.

This study is an important contribution to computer aided drug-design. In particular, using co-solutes to induce structural fluctuations seems very helpful for uncovering new binding sites. Of equal importance are methodology to analyse complex trajectories. This work is a good example of how multiple dimensions can be reduced and rationalised using e.g. solvent accessibly surface area (SASA), radius of gyration, net-charge, and principal component analysis. There are likely several other properties that could aid in this rationalising and the present work is a solid platform for exploring these.

Reviewer #1 (Public Review):

This work introduces a new computational model of healthy blood cell formation and chronic myeloid leukemia (CML). By combining data from the literature, animal experiments and patients the authors aim to develop a detailed description of the regulatory mechanisms governing healthy blood cell formation and CML therapy response. The model is used to derive hypotheses explaining why some patients respond to tyrosine kinase inhibitors (TKI) better than others. Based on the model simulations the authors seek predictors of TKI efficacy and for concepts to improve CML therapy.

Strengths:

(1) The authors start from all possible ordinary differential equation models which describe positive and negative regulations of proliferation rates and self-renewal/differentiation probabilities. The models account for hematopoietic stem cells, multipotent progenitors, terminally differentiated myeloid cells, and terminally differentiated lymphoid cells. Using an automated approach referred to as design space analysis (DSA) the authors exclude models with unfeasible qualitative dynamics. Using data from mouse experiments the authors exclude all regulatory configurations except one. This systematic approach combining model analysis and data from various sources is clearly a strength of the work.

(2) The authors consider a large number of parameter sets that are in line with physiological steady-state cell counts and realistic responses to system perturbations. Thus the authors can potentially account for inter-patient differences.

(3) The model predictions are compared to experimental and published data. The proposed predictors of TKI efficacy are tested on retrospective patient data.

Weaknesses:

(1) In my opinion the sub-model of leukemic cells requires a more solid justification. The authors assume that the configuration of regulatory loops and most key parameters are identical for normal and leukemic cells. The only difference the proposed model accounts for is that leukemic cells exhibit a weaker response to the feedback signal acting on stem cell self-renewal. The weaker response of leukemic stem cells is justified by data from the literature supporting differential responses to CCL3. However, the authors propose no justification for the assumption that all other parameters, such as proliferation rates or maximal self-renewal probabilities, are identical or have minor impacts.

(2) The authors come to the conclusion that "a key predictor of refractory response to TKI treatment is an increased probability of self-renewal of normal hematopoietic stem cells" (Abstract). This conclusion is, in my opinion, not fully supported by the model as it is. In the model, it is assumed that normal and leukemic stem cells have the same maximal self-renewal probability. Only the regulation of self-renewal by feedback signals is different. The parameter which is a predictor in the presented analysis (p_{0,max}) is the maximal self-renewal probability of both normal AND leukemic stem cells. Therefore, the conclusion that normal stem cell self-renewal is a predictor of TKI response is, in my opinion, questionable. If I understand the analysis correctly, the authors show the following: Under the assumptions that the maximal self-renewal probability of normal and leukemic stem cells is identical and that the feedback inhibition of self-renewal is weaker in leukemic stem cells compared to normal stem cells, the maximal self-renewal probability of the two stem cell populations is a predictor of TKI response. Notably, if the value of maximal self-renewal probability is increased, the self-renewal probability of leukemic and normal stem cells increases simultaneously at all time points. Therefore, I find it difficult to argue that normal stem cell self-renewal [as opposed to leukemic stem cell self-renewal] is the relevant quantity.

(3) The simulation of differentiation therapy is interesting, however, due to a lack of knowledge in the field, the specific impacts of such therapy on normal versus leukemic cell differentiation have to be rather hypothetical.

(4) The used patient cohort is very small (n = 21).

The proposed model of the regulations governing blood cell formation is a valuable contribution to the fields of computational modeling and experimental hematology. The derived predictors of TKI efficacy are potentially useful.

Reviewer #2 (Public Review):

The authors want to capture the dynamics of CML therapy with TKI and understand why some patients fail to respond to therapy (primary resistance). They develop a mathematical model of hematopoiesis that includes stem cells, progenitor cells, and mature cells linked through feedback mechanisms. They explore parameter space using sophisticated algorithms to reduce this parameter space and the potential models to one final model and then apply it to chronic myeloid leukemia in the chronic phase under therapy with a tyrosine kinase inhibitor. The novelty in the model is the feedback mechanism introduced and the concomitant animal model data to understand the parameters.

The model is tractable and yet captures important physiologic aspects of hematopoiesis that have not been explored previously in CML. The animal data to validate it is also quite important. Finally, the application of the model to clinical data illustrates its applicability to real clinical scenarios and provides interesting insights.

One concern is whether the short-term transplantation experiments truly reflect the steady state of hematopoiesis and how CML develops in humans.

It is possible that the model can be applied to other hematologic conditions such as myeloproliferative disorders since one would expect the dynamics and interactions to be similar.

Reviewer #3 (Public Review):

Rodriguez et al. develop a nonlinear ordinary differential equation model of hematopoiesis under normal and chronic myeloid leukaemia (CML) conditions, incorporating feedback control, lineage branching, and signaling between normal and CML cells. Design space analysis is used to identify viable models of cell-cell signalling interaction. Data from mouse models are used to refine the set of cell-cell interactions considered viable, resulting in a novel feedback-feedforward model. Through this framework, the response to tyrosine kinase inhibitor (TKI) therapy is analysed. Model behaviour is qualitatively consistent with experimental data from mouse models, and clinical data. In particular, the model demonstrates varying responses to tyrosine kinase inhibitor therapy across a range of parameter sets consistent with "normal" hematopoietic cell counts; and predicts that a relatively high proportion of leukemic hematopoietic stem cells is a contributor to (though does not guarantee) primary tyrosine kinase inhibitor resistance, consistent with experimental and clinical data.

Strengths:<br /> Mathematical modelling in the work is validated using both experimental and clinical data.

The approach to model selection and identification of reasonable parameter regions is interesting and appealing, particularly in the context of modelling processes such as CML which can exhibit significant heterogeneity between patients.

I expect that this work will be useful to the community, as the approach employed in this work could be readily adapted to study other similar problems (for example, different conditions or treatments), provided that suitable experimental and/or clinical data are collected or available.

The work is supported by extensive supplementary material, clearly documenting in detail the techniques involved and assumptions made.

Weaknesses:<br /> Clinical data from CML patients treated with TKI therapy is limited (n=21).

As acknowledged by the authors, there are some physiological aspects that may be important that are not modelled; including stem cell-niche interactions in the bone marrow microenvironment, and interactions with immune cells.

Reviewer #1 (Public Review):

This is a fascinating effort from the Ryan laboratory, revisiting fundamental issues of calcium-dependent release probability at cultured synapses. The authors point out that our basic understanding of mammalian synapses rests on a foundation of older research that was not acquired at physiological temperature, and represented a statistical interpretation of data acquired electrophysiologically without direct knowledge of release at individual active zones. The authors employ techniques of calcium imaging and glutamate sensing and argue that single synapses can be 'silenced' by a moderate drop in extracellular calcium, a drop that is within the range of calcium channel inhibition following activation of GABAergic signaling. While fascinating, the conclusions are most powerful when the data can be distilled to direct observation of single release sites and this is not uniformly the case.

Reviewer #2 (Public Review):

Throughout the manuscript, the authors aim to distinguish signal from the lack of it. All conclusions depend on the success of this process. In such an endeavor, the sensitivity of the applied methods is critical. Thus, the authors must use the most sensitive tools to draw meaningful conclusions. The latest iGluSnFR has amazing sensitivity allowing the detection of single AP-evoked responses. This is not the case for vGpH, which requires hundred APs to get a meaningful signal. Similar, synthetic Ca2+ dyes have much better dynamic range, linearity and sensitivity compared to GCaMP6f.

The rate of silent boutons at 2 mM [Ca2+]e is lower for a single AP compared to 20 or 200 APs. The overall failure rate cannot be increased with increasing the number of APs. This clearly indicates a technical issue (e.g. insufficient sensitivity of vGpH and GCaMP6f).

The authors used three different measuring tools and used three different stimulation protocols, making the interpretation of the data challenging. It is impossible to tell how the failure rate changes from 1 to 20 APs without knowing the release probability, the pool size, depletion, recovery of SVs, and facilitation. These are all unknown.

The last experiment with the GABAB agonist has little novelty in its present form. The authors demonstrate that GABAB agonism increases the rate of silent terminals. The interesting issue would be to reveal how the effect of GABAB activation depends on the [Ca2+]e. This information is essential to see whether there is indeed a shoulder in its effectiveness curve.

The authors refer to a theoretical set-point in [Ca2+]e below which the function of the terminals is fundamentally different. From the presented experiments, the reviewer does not see any data that is inconsistent with a continuum. 'Thus, as with Ca2+ influx, SV recycling is modulated in an all-or-none manner by modest changes in [Ca2+]e around the physiological set point.' This statement is not supported by the data. The reviewer cannot see a set point.

Reviewer #3 (Public Review):

In this study Cook and Ryan examine, at physiological temperatures, the sensitivity of neurotransmitter release to external calcium concentrations close to physiological ones. Using hippocampal neurons in culture, field potential-based stimulation, a spatially confined genetically encoded calcium indicator (GCaMP6f) as well as fluorescent reporters of exocytosis and extracellular glutamate, the authors show that as extracellular calcium concentrations are reduced from 2.0, to 1.2 and finally to 0.8 mM, a disproportional fraction of presynaptic terminals cease to respond, as evidenced by no elevations in intracellular calcium concentrations, no detectable exocytosis or changes in extracellular glutamate. The phenomenon is quantitively modulated by blocking particular types of calcium channels, but is qualitatively conserved across all tested conditions. Finally, the authors show that effects of lower extracellular calcium concentrations can be mimicked by applying Baclofen, an agonist of type B GABA receptors. The authors reveal the sensitivity of all-or none calcium influx and exocytosis near extracellular calcium physiological set points and highlight the potential importance of this sensitivity as an effective control point for neural circuit modulation.

The findings described in the manuscript are potentially important as they seem to uncover a new, yet undescribed, all-or none (binary) phenomenon in the field of synaptic neuroscience, that is, of individual presynaptic terminals moving between two 'states' - 'active' and 'silenced'- which are set somehow by levels of extracellular calcium concentrations. Moreover, this dependency is observed at extracellular calcium concentrations that are quite close to the physiological concentration set point. The use of multiple reporters (intracellular calcium concentrations, synaptic vesicle fusion and extracellular glutamate) strengthens the validity of the observations.

On the other hand, there are two major points that need to be addressed.

The first is that alternative explanations should be ruled out more convincingly, first and foremost the matter of membrane excitability. Two observations are relevant here: The qualitative preservation of the phenomenon when two types of voltage gated calcium channels are blocked separately, and the large heterogeneity of the % of silenced boutons among neurons at a given extracellular calcium concentrations, which is at least as great as the range of modulation of the % of silenced synapses by extracellular calcium concentrations at single neurons. One then wonders if the findings might be attributed to a) the fidelity of the field potential-based stimulation system, that is, the degree to which neurons track the stimuli trains; b) the heterogeneity of neurons in this regard, c) this fidelity at different extracellular calcium concentrations for different neurons, and d) the identity of presynaptic sites analyzed in one run (are they all part of the same axon?). Along these lines, there is an assumption that the field potential-based stimulation system is the sole driver of excitation in these networks, which is reasonable given that excitatory synaptic transmission is mostly blocked pharmacologically (by CNQX and APV). Inhibitory transmission, however, was not blocked and thus, there is no guarantee that the inhibitory input neurons receive and its modulation by extracellular calcium does affect the degree to which neurons fire precisely and reliably at 20 Hz at all conditions. If it could be shown, at least for a substantial subset of the data, that all terminals analyzed for a particular neuron are part of an unambiguously identified axon stretch, with no branches (potential conduction failure points) and still demonstrate the claimed heterogeneity, this potential confound would be less of an issue.

The second issue relates to the ties made to neuromodulation. In spite of the title, introduction and discussion, not a single neuromodulator (such as dopamine, acetylcholine, noradrenaline, serotonin) was tested, only baclofen, which as a derivative of GABA, activates GABAB receptors, not receptors of canonical neuromodulators. The title of this manuscript is therefore not appropriate.

Reviewer #1 (Public Review):

In this manuscript the authors describe the development and application of hierarchical machine learning model to identify the likely source of S. Enteritidis using whole genome sequence data. The application makes use of a collection of 2,313 genomes from 4 continents, 11 sub-regions and 38 countries. The approach is, to the best of my knowledge, novel and represents a substantial advance over previous approaches. The model is demonstrated to have good performance at the continental level and - where sufficient training data were available - also at the country level.

Strengths of the work include the clear exposition of the methods, application to a large and detailed genomic database of clinical S. Enteritidis isolates, and the use of five independent validation data-sets.

Limitations include lack of validation using post-pandemic data (as the authors state, the model may need retraining in light of changes to the global food network). Also, claimed novelties of the work include greater geographic granularity and faster turnaround time compared to alternative methods, but no explicit comparison to other methods is made.

Overall, the authors achieve their aims in describing a hierarchical machine learning model for source attribution using pathogen whole genome sequences. The approach is likely to be of broad relevance and considerable public health utility.

Reviewer #2 (Public Review):

In this study, Bayliss et al. built a machine learning algorithm that predicts which country an isolate of Salmonella Enteritidis has come from based on its genome sequence. The study used S. Enteritidis isolates taken from clinical infections in the UK with recently reported travel, with the recent travel location being assumed as the source of infection.

The reason for developing this type of algorithm is to use it for source attribution in the case of gastroenteritis cases caused by imported food or cases of gastroenteritis picked up during travel overseas. S. Enteritidis is a major cause of gastroenteritis worldwide. Its transmission is tied in with the food chain, and understanding where it travels and how is key to reducing the burden of these infections. While a country's efforts to reduce the burden of these bacteria within its own borders can have tremendous benefits, imported food can still introduce contaminated meat and produce, and these have indeed become larger proportional risks following control efforts in the UK.

S. Enteritidis shows strong geographical substructuring across its phylogenetic tree. Traditional phylogenetic analysis is time-consuming (particularly to perform repeatedly on a routine basis) and required highly skilled staff to perform. Machine learning should be able to identify genetic markers linked to clades typically found in a single location, without the need to build and interpret a phylogenetic tree.

There is some nice methods development work in this paper, with the employment of a hierarchical structure to the ML modelling pipeline and the use of an array of classifier, resampler, feature selection and parameter optimisation techniques to increase accuracy.

However, the main strength of this paper is how well tailored the model is to a real world use case. Many groups are applying machine learning to genomic data, but often not with a clearly defined use case or realistic training and testing conditions. The results begin by giving the reader an understanding of the current state of this work in a UK context, where all clinically reported cases of Salmonella are sequenced and when appropriate, travel history is recorded. The algorithm is designed to fit into this existing practise and thought has been put into how this would be operationalised. For example, the authors have shown that this work can truly be done in real-time, by developing an algorithm that works directly on raw reads and takes <4 mins to run. A great touch in this work was determining the time horizon over which the model should be retrained to keep up with contemporary geographic distributions of this pathogen. The time horizon itself may not be highly generalizable in genomic epidemiology, but the methods provided make it easier for others to make the same assessment for their pathogen and use case.

A weakness of the work is the areas where predictions are not as accurate, but this relates to the extent of pathogen sequencing today rather than the method itself. Countries with less accurate predictions are ones which few people return from with an infection and if they do, it tends to be a different strain each time, making building an accurate algorithm for these cases impossible without denser sampling outside of clinical infections or more sequencing of infections occurring in other countries. Without proofs of concept like this, there is less of a strong economic argument to justify these investments. Therefore this work represents an important step in demonstrating the feasibility of the method itself and the value in gathering more data. In contrast, a major strength of this work is that it uses data collected routinely from existing practice in the UK, rather than a bespoke sampling strategy that may not be realistic for routine public health. A comparison of the collection to NCBI also found this sampling to be less biased by specific outbreaks of interest, which is encouraging.

The training dataset appears to be only based on infections acquired overseas, while I suspect the model would be more useful in investigating infections due to imported contaminated food. An unresolved question from this work is therefore whether the source of travel-acquired infections and infections caused by food imported from the same places is the same, or whether exported vs domestically consumed food around the world is treated differently in important ways that would affect the relative prevalence and success of strains in causing infections. Looking at clinical infections also may bias Salmonella to those that cause more severe forms of infection, as many people don't report to a doctor when they have food poisoning. The large egg-related outbreak that did not feature much at all in the UKHSA dataset is potentially a nice example of this.

The low accuracy on countries with low infection numbers and high genetic diversity indicates that these algorithms would likely become less accurate over time if food safety is improved, and that individual countries could avoid being confidently attributed as a source of infection by eliminating or controlling major circulating foodborne clones. More clearly communicating when a prediction is uncertain could be helpful in dealing with isolates from countries where it is hard to make a determination.

One final limitation I see is the exclusion of UK Salmonella isolates - in cases where it is uncertain whether a Salmonella infection is due to import or not, it does not seem possible to make this assessment using the ML tool. This also limits the utility of the tool for other countries that might also benefit.

The authors have done an excellent job of demonstrating the feasibility of this approach and honing their machine learning workflow to the specific demands of the task. The work presents a clear and well thought out use case with the overall performance of the algorithm broken down into test cases where the algorithm is successful and unsuccessful which provide useful insight into what we can expect from the performance of these approaches.

Finding a way to better communicate when the source of an outbreak is unclear due to poor representation of a clade or a clade that is found in many countries would be a valuable extension of this work in the future, but as it is the results represent a promising starting point for initiating investigations into the source of Salmonella infections.

Diarrheal disease is a huge health burden worldwide. Previous work to lower the burden of these infections has shown that targeted interventions can make a substantial difference to the burden of disease and success of clonal outbreaks. The availability of a tool that can be used routinely to assess the most likely overseas origin of an infection could potentially highlight previously unrecognised outbreaks or areas of suddenly increased importation rate. In turn, this could lead to better investigations and targeted improvement of food security.

This paper provides an excellent case for the value of collecting recent travel history and including it in metadata for pathogen genomic data. If this were done in more countries with different patterns of travel and the data could be shared, this would provide a valuable global resource and start to capture the flow of strains internationally.

I am curious about the implications of being better able to attribute clinical gastroenteritis cases in the UK (and elsewhere) to food imported or travel to specific countries with respect to trade and regulation. This is well outside the scope of the paper, however the ability to capture isolates commonly picked up from food around the world without the cooperation of these countries raises interesting issues, particularly when factoring in the authors' scenarios of the true country of origin being obscured by uneven travel patterns and complex food supply networks.

Reviewer #3 (Public Review):

The authors describe a machine learning method for classifying the geographic origin of a Salmonella enterica isolate based on its whole-genome sequencing data. This is done at a continent, region, and country level, and the method is shown to be robust to phylogenetic diversity, temporal trends, and possibly some amount of mislabelling (but please see the first concern below). The authors demonstrate that their pipeline produces results in 5 minutes or less, which makes it applicable to many public health microbiology settings.

Some clear strengths of the paper include:<br /> - the use of a hierarchical classification method, which ensures that only those samples that can be unambiguously classified as belonging to a specific region can get assigned to a sub-region within that region (e.g. continent to country)<br /> - leveraging the UKHSA dataset going back nearly a decade, and containing a comprehensive record of all clinically detected Salmonella enterica infections, which mitigates potential biases and ensures a maximal geographic coverage<br /> - making all the data (microreact) and the source code (GitHub) public, which facilitates replication as well as enables other researchers and public health microbiologists to use the trained models directly on their own data<br /> - the use of unitigs as the basis for prediction, which are more informative than K-mers yet more straightforward to identify than SNPs or gene alleles.

There are several methodological concerns that should ideally be addressed:<br /> - in addition to the more complex situation of a tourist visiting country A and consuming food from country B, it would be good to rule out a simpler one of the tourist visiting both countries on the same trip (including via a stopover at an airport); the authors should elaborate on the plausibility of missing data on such multi-country trips and their frequency based on the available travel data<br /> - similarly, there appears to be an underlying assumption that the UK is never at the origin of a Salmonella enterica infection in the dataset selected; the authors should explain why that is a reasonable assumption for this dataset<br /> - the increase of infection incidence during the summer months might be at least partly attributable to a greater number of trips abroad during that period - if the authors have corrected their data for this, they should explicitly say so<br /> - lastly, in discussing the outbreak due to Polish eggs, it should be possible to check explicitly what fraction of the training data may have originated from this outbreak to see if this is sufficient to explain the observed poor prediction

Overall, this is a paper representing a substantial body of work and combining algorithmic advances with practical utility given the rapid turnaround time. It is likely to be generalisable to other pathogens of public health importance and to become integrated into standard protocols for outbreak origin tracing.

Reviewer #1 (Public Review):

The author constructed a novel rat model with a clinically relevant PLS3 hemizygous E10-16del mutation (PLS3E10-16del/0), which presents a classic form of early-onset osteoporosis, which recapitulate the osteoporotic phenotypes. Treatment with alendronate and teriparatide significantly improved bone mass and bone microarchitecture. Their results showed alendronate and teriparatide treatment could be a potential treatment for early-onset osteoporosis induced by PLS3 mutation.

This experiment is very interesting and has clinical relevance. The authors used common clinical drugs to treat osteoporosis caused by PLS3 mutation and achieved certain results. This result will give a way to the treatment of osteoporosis induced by PLS3 mutation.

Reviewer #2 (Public Review):

The mechanism for early-onset osteoporosis (EOOP) is not well understood. The authors performed PLS3 knockout and characterized its bone phenotype in a rat model. This provides a very useful tool for studying EOOP and the potential treatment for EOOP. The authors did a very nice job of characterizing the phenotype including the assessments of bone turnover markers, bone histomorphometric analyses, and bone biomechanical tests. The results from these assessments led to the conclusion that this PLS3 knockout rat model mimics the human EOOP. In addition, treatment with currently available drugs for osteoporosis is effective in this EOOP model. These results support further clinical investigation of anti-osteoporosis drugs for EOOP management.

Reviewer #1 (Public Review):

The authors have achieved a demonstration of different stellate ganglion nerve cell functions and transmitter subtypes, of potential cardiac importance. They employ viral tracing techniques. These convincingly make this demonstration. The work will be key to our understanding of sympathetic function at the transmitter and physiological levels.

Reviewer #2 (Public Review):

The manuscript at hand by Sharma et al. presents new data on neurons of the stellate ganglia that are relevant for autonomic control of the heart. The authors identify stellate ganglionic neurons (SGN) that innervate the heart by retrograde tracing techniques and differentiate them from SGN neurons innervating other organs and tissues (mostly paw is used as a control). They subsequently employ single-cell RNAseq and morphological and functional (electrophysiological) studies. Their main finding is the identification of 3 SGN subtypes that they were further able to stratify into high and low neuropeptide Y cells. These subpopulations differ with regard to gene expression and action potential generation indicating different electrophysiological properties and different roles in the sympathoexcitation of the heart. They validate these findings by in vivo experiments where electrical stimulation of stellate ganglia after NPY-expressing neurons was depleted and find that heart rate change was lower under stimulation with high frequencies for NPY-depleted mice. The research question is very relevant and might have important therapeutic consequences for patients with cardiac diseases. The paper is written clearly. The methods applied are elegant and appropriate and the data support the conclusion.

The authors do report on some experiments in which stellate ganglion was used. Viral administration and physiological studies were performed on the right, while RNA sequencing was done from the right and left stellate ganglion. As there are physiological lateral differences between the effects of the left and right stellate ganglion, it would be useful to thoroughly report which side was used for which experiment throughout the manuscript and to discuss whether any lateral differences are relevant for the obtained results and conclusions.

Reviewer #3 (Public Review):

Using viral tracing and single-cell transcriptome profiling the authors investigated the electrophysiologic, morphologic, and physiologic roles for subsets of cardiac-specific neurons and found evidence that three adrenergic stellate ganglionic neuron subtypes innervate the heart.

The presented findings provide relevant insights into the properties of neurons modulating cardiac sympathetic control. The findings might open up new avenues to targeted modulation of cardiac sympathetic control. Additional insights from various models addressing for example ischemic and non-ischemic cardiomyopathy might allow to development of targeted therapies for various patient populations in the future.

Reviewer #1 (Public Review):

Pedigo et al, apply statistical modeling to a complete brain nanoscale network - a synaptic connectome of an insect brain: the Drosophila larva. They use a series of approaches to explore the symmetry of the right and left hemispheres. First, they compare network densities and find significant differences between the two hemispheres, with the right hemisphere having a higher density. They further grouped neurons by cell type to determine whether the differences were distributed across the entire brain or to specific connections and find the differences involving neurons in the learning and memory center, the mushroom body. Finally, they explored different definitions of an edge by using different thresholds either based on synaptic counts or proportions of synaptic inputs to a downstream neuron and found that when using the proportion of synaptic inputs, removing fewer edges (compared to when using synaptic count) was necessary to achieve left and right symmetry. The presentation of the methodology and writing is very clear and effective and is accessible to scientists from various backgrounds: both biologists and theoreticians. The methodology and approach used in this paper on the assessment of the degree of bilateral symmetry will serve as a basis for comparing networks and connectomes in general by providing a clear framework for statistical network modeling. This work is particularly timely as an increasing number of synaptic connectomes is being generated giving opportunities for various connectome comparisons. It will be of interest to neuroscientists in order to address various biological questions: to evaluate the degree of inter-individual variability/stereotypy of connectivity in the brain and how it relates to behavioral variability/stereotypy, to characterize changes in network connectivity due to different diseases, etc.

Reviewer #2 (Public Review):

The authors develop statistical tests for assessing whether two hemispheres of the Drosophila larval brain are bilaterally symmetric, and more generally to develop a framework for comparisons of connectomes. The study is organized in order of increasing complexity of the statistical test, beginning with a simple test of whether or not the two sides of the brain have equal connection density. A more sophisticated approach is applied to a model in which neurons are partitioned into groups defined by preexisting known cell types on the left and right hemispheres and densities are allowed to vary between groups (a stochastic block model). A correction is included for an overall difference in density between hemispheres. Finally, analyses are applied to assess which cell types contribute to differences in the larval connectome. This identifies Kenyon cells as particularly distinct - a density-corrected stochastic block model with Kenyon cells removed results in no significant bilateral asymmetry. Results are also compared across different choices for thresholding of connection weights.

This manuscript tackles an interesting and timely problem. The analyses are largely straightforward applications of standard hypothesis tests for binomially distributed random variables. However, the observation that a density correction is needed to account for the two hemispheres' connection probabilities, and that a stochastic block model is sufficient to describe these probabilities, with the exception of the Kenyon cells, is interesting and makes more precise the notion of bilateral symmetry, at least at the level of connection probabilities, than previous approaches.

There are still several questions that remain about the generality of the results. The first concerns assumptions about the generative model for the graph. As the authors acknowledge, an Erdos-Renyi random network is a strong simplifying assumption. In particular, independent edge weights may be a restrictive model of connectome data given the broad degree distribution, spatial dependencies, and other features that characterize biological connectivity. A second question concerns the issue of statistical power. After partitioning neurons into groups, the most significant difference in connection probabilities comes from Kenyon cells, with the smallest p-value in the density-corrected comparison coming from KC-to-KC connections (Fig. 4B). However, KCs represent a large group of neurons, and the KC-to-KC connection probability is among the highest in the larval brain (Fig. 3B), raising the question of whether the observation of a significant difference specifically for these neurons is simply due to increased power. Third, connection density is only one of the many graph features that may be relevant for evaluating connectome similarity.

In total, although the analyses are straightforward, the study represents a first step toward the evaluation of connectome similarity and should spur further work in this important direction.

Reviewer #1 (Public Review):

Tornini et al. investigate the function of long non-coding RNAs in vivo. In the manuscript, the authors show that two of these molecules linc-mipep and linc-wrb encode for a micropeptide that regulates zebrafish behavior. In the absence of this peptide, zebrafish larvae show dysregulation of NMDA receptor and glucocorticoid receptor-mediated signaling and immediate early gene induction. Given the homology of linc-mipep and linc-wrb encoded peptides with homology to chromosome binding and chromatin unwinding domain of HMGN1 the authors explore the altered chromatin accessibility in the mutant animals. This analysis revealed a broad dysregulation of 3D chromatin structure with some enrichment at loci regulating the expression of immediate early response genes. Finally, single cell analysis revealed that oligodendrocyte progenitor cells and cerebellar granule cells are more affected in the mutants.

This work represents a technical tour-de-force with extensive genomics data to characterize the molecular phenotype of linc-mipep and linc-wrb loss of function. This data show interesting findings in part consistent with the behavioral phenotype observed.

The manuscript provides compelling evidence that micropeptides encoded by what were previously identified as long non-coding RNAs have a precise biological function.

Reviewer #2 (Public Review):

The two new micropeptides are well characterized in the manuscript and appear to be functionally important with some chromatin-level consequences of their loss (which can be either direct or indirect), but the finding that lincRNA sequences encode micropeptides is not novel, and the two described in the paper appear to be zebrafish-specific and their function was tested only in zebrafish, which limits the interest in these genes. The use of ribosome profile data along behavioral screening to identify micropeptides is interesting and important, but the scope of the screen, the candidates selected for testing, etc. are not clear enough as presented. The ChIP-seq analysis of the new proteins is very interesting but is not described in any detail. Overall, the experimental part is well designed and the phenotypes reported by the authors appear to be strong and convincing, but the mechanistic understanding of what the two new proteins do and how, and the general interest in the results given the current scope of understanding of micropeptide is limited.

Reviewer #3 (Public Review):

The study aimed at the identification of functional micro-peptides encoded by transcripts previously annotated as long noncoding RNAs (lncRNAs). The authors pre-selected 10 candidates out of the ~500 zebrafish lncRNA data set based on their engagement with the ribosome (by ribosome profiling data) and their expression in the embryonic brain. By performing an F0 CRISPR/Cas9 screen coupled with embryonic behavioral assays, two transcripts encoding sequence-related micro-peptides were identified. Using a set of stable mutant alleles, the authors showed that mutations specifically affecting the open reading frame (ORF) of the putative micro-peptides cause changes in embryonic behavior when compared to wild-type embryos or embryos with mutations in the non-coding regions of the tested transcripts. The locomotor hyperactivity phenotype was even stronger in double homozygous mutants suggesting a redundant function of both micro-peptides. The authors demonstrated that the behavioral phenotype of one of the mutants was rescued by the transgene expression of the coding sequence (CDS). Sequence analyses of both peptides revealed their conservation and homology to the human non-histone chromosomal proteins (HMGN1 proteins). The authors demonstrated that the micro-peptide mutants exhibit changes in chromatin accessibility for transcription factors modifying neural activation, dysregulation of gene expression programs, and changes in oligodendrocyte and cerebellar cell states during development.

The study presents an important discovery of two sequence-related micro-peptides with important and potentially conserved functions during development. While it is still unclear how the micro-peptides act in the cell, it is evident that they are key regulators of cellular states. Whereas the study is well done, the data presentation should be improved as several important details were omitted.

Reviewer #4 (Public Review):

In this manuscript, Tornini and colleagues identify two previously un-characterized micropeptides encoded by linc-mipep and linc-wrb as important modulators of day-time activity in zebrafish larvae. The authors demonstrate that each single mutant shows an increase in day-time activity and that double mutants show a more pronounced effect. Of interest, ubiquitous overexpression of the ORF encoding the linc-mipep-derived peptide can rescue the day-time over-activity phenotype of linc-mipep mutant larvae, establishing that linc-mipep acts indeed as a protein and not at the level of RNA. Using a series of experimental approaches, including ATAC-Seq from double mutant brains and scRNA-Seq and scATAC-seq analyses from linc-mipep mutants as well as linc-mipep and linc-wrb CHIP analyses, the authors furthermore identify differences in chromatin accessibility and gene expression in specific cell types of the larval brain in the absence of linc-mipep (and in case of globale ATAC-Seq, in the absence of both peptides). They conclude that the micropeptides regulate behavior and neuronal states by modulating chromatin accessibility, revealing functional similarities to their known vertebrate homolog HMGN1.

Overall, the key finding of this paper, namely the identification of two functional microproteins that had previously been misannotated as lincRNAs but have homology to HMGN1 both based on their sequence and function is an exciting discovery since relatively few newly predicted micropeptides have been functionally characterized to date, and because it advances our understanding of the molecular mechanisms underlying vertebrate-specific neuronal function and diversity. The F0 screen leading to the identification of 2 functional micropeptides provides a major advance to the field since so far screens in the F0 generation have not been typically done (rather germline-transmission). Thus, this work provides a major step forward in this regard. In addition, it includes a series of scRNA- and scATAC analyses that are technologically at the forefront and not easy to conduct and analyse.

The weakest part of the paper in its current form is on the one hand missing the link between the behavioral phenotype in mutants and the molecular phenotypes in the larval brain. It remains unclear how one can reconcile the broad neuronal expression (in the case of linc-mipep preferentially in Purkinje cells) and linc-wrb with the cell-specific effects. Moreover, it is not clear whether both peptides act redundantly or in parallel but distinct pathways since the rescue is only shown for the single linc-mipep mutant by linc-mipep overexpression (and no rescue is shown for linc-wrb or the double mutant). While the authors suggest throughout the manuscript that both peptides have similar functions (act redundantly), no clear data is provided for this, and the use of either single linc-mipep mutants (all single-cell analyses in the last Figure) or double linc-mipep/linc-wrb mutants (global brain ATAC-Seq analyses) for different brain analyses makes the molecular analyses inconsistent and not easy to interpret. While the overall finding(s) of the paper is really interesting, to make this paper really solid, additional controls and analyses will be needed.

Reviewer #1 (Public Review):

This study presents a useful study, proposing the modelling of Buruli ulcer occurrence in humans based on detection of M. ulcerans in Australia. The data were collected and analyzed using solid and validated methodology and can be used as a starting point for the elucidation of M. ulcerans transmission in Australia.

Reviewer #2 (Public Review):

In this work, the authors have carried out an extensive and highly granular survey of Mycobacterium ulcerans carriage by possums who are living on the outskirts of Melbourne Australia, in areas that are known hot spots for cases of Buruli ulcer (BU). The work is the culmination of many years of endeavour by this team, who first identified that the faeces of possums can be highly positive for M. ulcerans DNA, genetically linked to the strains found in BU patients who live in, or have visited, the area.

Surveys across two seasons were performed. Based on qPCR data to identify M. ulcerans carriage, spatial mapping of this, and BU case data, a statistical model was generated using data from the Mornington Peninsula that was better predicted than a null model. This statistical model was then validated using a second independent site at Geelong. As a result of this data, there can now be little doubt that possums play a vital role in the transmission cycles of BU in the region, and will allow mitigation strategies to be designed and tested. As BU is a necrotising skin disease that can cause disability and permanent disfiguration even in a high-resource setting such as Australia, such approaches are urgently needed.

Strengths:

The scale (both in terms of geographic reach/granularity and time) of the surveillance effort to understand the distribution of M. ulcerans DNA in the local possum population is unprecedented.

Since BU is a notifiable disease in Australia, the researchers have access to comprehensive clinical information across the study period.

The statistical model developed had a strongly positive influence over the ability to predict where BU cases will arise, over areas with a small radius (several km) which is the first time this has been achieved. The process by which this model was developed and validated seems robust.

Weaknesses:

In their model, the authors have used an assumed "exposure window" for when patients were infected with M. ulcerans in the Mornington Peninsula. Correctly defining, and assigning, this is absolutely critical to the accuracy of the statistical model, as is "blinding" of researchers assigning mesh boxes to patients to the results of surveillance data (and vice versa). These aspects are not fully clear in the current version. Furthermore, the effects on the model of changing these assumptions are not discussed.

The presence of M. ulcerans DNA in possum excreta and in patient samples is defined by qPCR for IS2404, a multicopy insertion sequence. Greater justification for using this as the sole marker is required, as this insertion sequence is also present in other mycolactone-producing mycobacteria. Moreover, some samples were claimed to be 'positive' with Ct values of 40 without justification for using this value (such as standard curves).

Comparing the summer and winter surveys at the Mornington Peninsula, the distribution of M. ulcerans positive excreta appears to have changed quite substantially, especially given that the possums are reported to be highly territorial with a range of only 100m. This version of the manuscript does not formally compare these spatial distributions, only the averages. Such an analysis would help understand if it is the possums that are moving, whether the possums undergo 'waves' of carriage (or indeed any other explanation), or if these apparent differences are down to chance.

Reviewer #3 (Public Review):

K. Vandelannoote and collaborators report on using spatially-localized possum feces investigated for Mycobacterium ulcerans, as a proxy for cases of Buruli ulcer, South Australia. The report is a contributive, enforcing survey of animal excreta and is based on strong pieces of evidence.

Reviewer #1 (Public Review):

Francou et al. examine the dynamics of cell ingression at the primitive streak during mouse gastrulation and correlate this with the localization of elements of the apical Crumbs complex and the actomyosin cytoskeleton. Using time-lapse live imaging, they show that cells at the primitive streak ingress in a stochastic manner, by constricting their apical surface through a ratcheting shrinkage of individual junctions. Meticulous evaluation of immunofluorescent staining for many elements of the actomyosin contractile process as well as junctional and apical domain elements reveals anisotropic localization of Crumbs2, ZO1, and ppMLC. In addition, the localization of two groups of proteins showed a close correlation - actomyosin regulators and apical and junctional components - but there was a lack of correlation of localization of these two groups of proteins to each other. The localization of actomyosin and its activity, was altered and more homogeneous in Crumbs2-/- embryos, and there was a significant decrease in aPKC and Rock1. The authors conclude from these observations that Crumbs2 regulates anisotropic actomyosin contractility to promote apical constriction and cell ingression.

The strengths of this manuscript are the very detailed observations on the process of apical constriction and the meticulous evaluation of the localization of the many proteins likely to be involved in the process. While many of the general observations are not new, Francou et al. provide a much richer understanding of this process, as well as a paradigm with which to evaluate the effects of mutations on the gastrulation process. The figures are beautiful, clear, and informative, and support the conclusions made by the authors. The data provide a very compelling picture of both the dynamics of cell behavior and the anisotropies in protein localization associated with it.

However, much of the Crumbs2 mutant phenotype is not sufficiently explained by the authors' data or conclusions. First, the loss of Crumbs2 does not prevent ingression, as there are mesoderm cells evident between the epiblast and endoderm (Ramkumar et al., 2016, Xiao et al., 2011). There are certainly fewer, and the biggest effect appears to be during the elongation of the axis from E7.75 onward and not during the earlier migratory period (E6.5-E7.75) according to data from both previously published work (Xiao et al., 2011; Ramkumar et al., 2015, 2016) and the data presented here. Nor does the loss of Crumbs2 prevent apical constriction. Ramkumar et al. in their 2016 paper show by live imaging that the major effect of the Crumbs2 mutation is to prevent the cells from detaching from the epithelium, but that the apical domain does undergo constriction, leading to many elongated flask-shaped cells still attached at the apical end. These observations do not fit well with the model proposed by the authors of Crumbs2 regulating anisotropic actomyosin contractility to promote apical constriction and suggest a more complicated story. However, the complications of the Crumbs2 mutant do not detract from the value of the basic observations presented in this manuscript, which are solid and well-documented, and will be a valuable resource for the field.

Reviewer #2 (Public Review):

In their manuscript, Francou and colleagues study the delamination of epiblast cells into the mesodermal layers using live imaging of mouse embryos cultured ex vivo. By segmenting the apical area of delaminating cells, they quantify extensively the dynamic behavior of delaminating cells. Using immunostaining and crumbs2 mutants, they propose that apical constriction of cells results from pulsed contractions, which could be guided by crumbs2 signals.

The manuscript is interesting and provides extremely valuable data for our understanding of mouse gastrulation. Occasionally, the manuscript can be a bit confusing and contains a few inaccuracies. However, the main issues I have are with some of the interpretations from the authors, which may be incorrect due to limited time resolution (with a 5 min time resolution that was used, it might be difficult to distinguish pulses from measurement noise) and the analysis of immunostaining data, which would require more rigorous quantification.

Reviewer #3 (Public Review):<br /> <br /> The manuscript by Francou et al investigated cellular mechanisms of epiblast ingression during mouse gastrulation. The authors wanted to know whether/how epiblast cell-cell junctional dynamics correlate with apical constriction and subsequent ingression. Because mouse gastrula adopts an inverted-cup morphology (as a result of differential invasive behavior of polar and mural trophoblast cells), epiblast cells are located in the innermost position and are difficult to image. This is more so when one wants to perform live imaging of epiblast cells' apical surface. The authors tackled such problems/limitations by using a combination of ZO-1 GFP line, confocal time-lapse microscopy, fixed embryo immunostaining, and Crumbs2 mutant embryos. The authors observed that apical constriction was associated with cell ingression, that this constriction occurred in a pulsed fashion (i.e., 2-4 cycles with phases of contraction and expansion, eventually leading to reduction of apical surface and ingression), that this constriction took place asynchronously (i.e., neighboring epiblast cells did not exhibit coordinated behavior) and that junctional shrinkage during apical constriction also occurred in a pulsed and asynchronous manner. The authors also investigated localization/co-localization of several apical proteins (Crumbs2, Myosin2B, pMLC, ppMLC, Rock1, F-actin, PatJ, and aPKC) in fixed samples, uncovering somewhat reciprocal distribution of two groups of proteins (represented by Myosin2B in one group, and Crumbs2 in the other). Finally, the authors showed that Crumbs2 -/- embryos had disturbed actomyosin distribution/levels without affecting junctional integrity (partially explaining the ingression defect reported in Crumbs2 -/- mutant embryos). Overall, this manuscript offers high-quality live imaging data on the dynamic remodeling of epiblast apical junctions during mouse gastrulation. It would be interesting to see whether phenomena reported in this manuscript can be extended to the entire primitive streak (or are they specific only to a subset of mesoderm precursors) and to the entire period of mesendoderm formation. More importantly, it would be interesting to see whether the ingression behavior seen here is representative of all eutherian mammals regardless of their gastrular topography.

Reviewer #1 (Public Review):

In this study, Sapiro et al sought to develop technology for a transcriptomic analysis of B. burgdorferi directly from infected ticks. The methodology has exciting implications to better understand pathogen RNA profiles during specific infection timepoints, even beyond the Lyme spirochete. The authors demonstrate successful sequencing of the B. burgdorferi transcriptome from ticks and perform mass spectrometry to identify possible tick proteins that interact with B. burgdorferi. This technology and first dataset will be useful for the field. The study is limited in that no transcripts/proteins are followed-up by additional experiments and no biological interactions/infectious-processes are investigated.

Critiques and Questions:

This study largely develops a method and is a resource article. This should be more directly stated in the abstract/introduction.

Details of the infection experiment are currently unclear and more information in the results section is warranted. State the species of tick and life-stage (larval vs nymphal ticks) used for experiments. For RNA-seq, are mice are infected and ticks are naïve or are ticks infected and transmitting Borrelia to uninfected mice?

What is the limit of detection for this protocol? Experimental data should be provided about the number of B. burgdorferi required to perform this approach.

More information regarding RNA-seq coverage is required. Line 147-148 "read coverage was sufficient"; what defines sufficient? Browser images of RNA-seq data across different genes would be useful to visualize the read coverage per gene. What is the distribution of reads among tRNAs, mRNAs, UTRs, and sRNAs?

My lab group was excited about the data generated from this paper. Therefore, we downloaded the raw RNA-seq data from GEO and ran it through our RNA-seq computational pipeline. Our QC analysis revealed that day 4 samples have a different GC% pattern and that a high percentage of E. coli sequences were detected. This should be further investigated and addressed in the paper: Are other bacteria being enriched by this method? Why would this be unique to day 4 samples? Does this affect data interpretation?

Comprehensive data comparisons of this study and others are warranted. While the authors note examples of known differentially expressed genes (like lines 235-241), how does this global study compare to other global approaches? Are new expression patterns emerging with this RNA-seq approach compared to other methods? What differences emerged from day 1 to day 4 ticks compared to differences observed in unfed to fed ticks or fed ticks to DMC experiments? Directly compare to the following studies (PMID: 11830671; PMID: 25425211; PMID: 36649080).

Details about the categorization of gene functions should be further described. The authors use functional analysis from Drechtrah et al., 2015, but that study also lacks details of how that annotation file was generated. Here, the authors have seemed to supplement the Drechtrah et al., 2015 list with bacteriophage and lipoprotein predictions - which are the same categories they focus their findings. Have they introduced a bias to these functional groups? While it can be noted that many lipoproteins are upregulated (or comment on specific genes classes), there are even more "unknown" proteins upregulated. I argue that not much can be inferred from functional analysis given the current annotation of the B. burgdorferi genome.

Reviewer #2 (Public Review):

This manuscript documents the study of the transcriptome of Borrelia burgdorferi at 1, 2, 3 and 4 days post-feeding in nymphs of Ixodes scapularis. The authors use antibody-based pull-downs to separate bacteria from tick and mouse cells to perform an enrichment. The data presented support that the transcriptome of B. burgdorferi changes over time in the tick. This work is important as until now, only limited information on specific genes had been collected. This is the first study of its kind and is valuable for the field.

The manuscript is overall well written and easy to follow. The data are compelling and support the conclusions.

Reviewer #1 (Public Review):

In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 2 hundred and with very few present in the sample only when spermatozoa were incubated with the extracts.

The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures.

Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it's (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance since the protein identified may also be involved in other processes going-on in the oocyte at this time of early development.

Concerning the localisation of the 6 proteins further analysed, the authors must add how much the presented picture represents the observed patterns. They must include the details on the fraction of spermatozoa and embryos displaying the presented pattern.

Reviewer #2 (Public Review):

Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the post-fertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

Reviewer #3 (Public Review):

In this manuscript, a cytosolic extract of porcine oocytes is prepared. To this end, the authors have aspirated follicles from ovaries obtained from by first maturing oocytes to meiose 2 metaphase stage (one polar body) from the slaughterhouse. Cumulus cells (hyaluronidase treatment) and the zona pellucida (pronase treatment) were removed and the resulting naked mature oocytes (1000 per portion) were extracted in a buffer containing divalent cation chelator, beta-mercaptoethanol, protease inhibitors, and a creatine kinase phosphocreatine cocktail for energy regeneration which was subsequently triple frozen/thawed in liquid nitrogen and crushed by 16 kG centrifugation. The supernatant (1.5 mL) was harvested and 10 microliters of it (used for interaction with 10,000 permeabilized boar sperm per 10 microliter extract (which thus represents the cytosol fraction of 6.67 oocytes).

The sperm were in this assay treated with DTT and lysoPC to prime the sperm's mitochondrial sheath.

After incubation and washing these preps were used for Western blot (see point 2) for Fluorescence microscopy and for proteomic identification of proteins.

Points for consideration:

1) The treatment of sperm cells with DTT and lysoPC will permeabilize sperm cells but will also cause the liberation of soluble proteins as well as proteins that may interact with sperm structures via oxidized cysteine groups (disulfide bridges between proteins that will be reduced by DTT).

2) Figure 3: Did the authors really make Western blots with the amount of sperm cells and oocyte extracts as the description in the figures is not clear? This point relates to point 1. The proteins should also be detected in the following preparations (1) for the oocyte extract only (done) (2) for unextracted nude oocytes to see what is lost by the extraction procedure in proteins that may be relevant (not done) (3) for the permeabilized (LPC and DTT treated and washed) sperm only (not done) (4) For sperm that were intact (done) (5) After the assay was 10,000 permeabilized sperm and the equivalent of 6.67 oocyte extracts were incubated and were washed 3 times (or higher amounts after this incubation; not done). Note that the amount of sperm from one assay (10,000) likely will give insufficient protein for proper Western blotting and or Coomassie staining. In the materials and methods, I cannot find how after incubation material was subjected to western blotting the permeabilized sperm. I only see how 50 oocyte extracts and 100 million sperm were processed separately for Western blot.

3) Figures 4, 5, 6, 7, and 8 see point 2. I do miss beyond these conditions also condition 1 despite the fact that the imaged ooplasm does show positive staining.

4) These points 1-3 are all required for understanding what is lost in the sperm and oocyte treatments prior to the incubation step as well as the putative origin of proteins that were shown to interact with the mitochondrial sheath of the oocyte extract incubated permeabilized sperm cells after triple washing. Is the origin from sperm only (Figs 5-8) or also from the oocyte? Is the sperm treatment prior to incubation losing factors of interest (denaturation by DTT or dissolving of interacting proteins pre-incubation Figs 3-8)?

5) Mass spectrometry of the permeabilized sperm incubated with oocyte extracts and subsequent washing has been chosen to identify proteins involved in the autophagy (or cofactors thereof). The interaction of a number of such factors with the mitochondrial sheath of sperm has been shown in some cases from sperm and others for an oocyte origin. Therefore, it is surprising that the authors have not sub-fractionated the sperm after this incubation to work with a mitochondrial-enriched subfraction.

I am very positive about the porcine cell-free assay approach and the results presented here. However, I feel that the shortcomings of the assay are not well discussed (see points 1-5) and some of these points could easily be experimentally implemented in a revised version of this manuscript while others should at least be discussed.

Reviewer #1 (Public Review):

Mice and humans have two Cylicin genes (X-linked Cylicin 1 and the autosomal Cylicin 2) that encode cytoskeletal proteins. Cylicins are localized in the acrosomal region of round spermatids, yet they resemble a calyx component within the perinuclear theca of mature sperm nuclei. The function of Cylicins during this developmental stage of spermiogenesis (tail formation and head elongation/shaping) was not known. In this study, using CRISPR/Cas genome editing, the authors generated Cylc1-and Cylc2-knockout mouse lines to study the loss-of-function of each Cylicin or all together.

The major strengths of the study are the rigorous and comparative phenotypic analyses of all the combinatorial genotypes from the cross between the two mouse lines (Cylc1-/y, Cylc2-/-, Cylc1-/y Cylc2+/- and Cylc1-/y Cylc2-/-) at the levels of male fertility, cellular, and subcellular levels to support the conclusion of the study. While spermatogenesis appeared undisturbed, with germ cells of all types detected in the testis, low sperm counts in epididymis were observed. Mice were subfertile or infertile in a dose-dependent manner where fewer functional alleles had more severe phenotypes; the loss of Cylc2 was less tolerated than the loss of Cylc1. Thus, loss of Cylc1, and to an even greater extent, loss of Cylc2, leads to sperm structure anomalies and decrease sperm motility. Particularly, the sperm head and sperm head-neck region are affected, with calyx not forming in the absence of Cylicins, the acrosomal region being attached more loosely, and the sperm head itself appearing structurally rounder and shorter. Furthermore, manchette, which disassembles during spermiogenesis, persists in mature sperm of mice missing Cylc2. It is interesting that the study identifies a human male that has mutations in both CYLC1 and CYLC2 genes, and suffers from infertility, with similar motility and sperm structure defects compared to the mouse models. CYLC1 in the sperm from the infertile patient sperm is absent, providing evidence that in both rodents and primates, Cylicins are essential for male fertility.

The major weakness of the study is the less robust or absent of statistical analyses determining the statistical significance of some of the morphological phenotypes observed (e.g., the roundness/shortening of sperm head). Evolutionary analysis of two genes-while interesting- is less congruent with the other parts of the study and disrupts the overall flow of the functional studies. The authors show that the reason for the loss of Cylc2 being more severe is due to the higher conservation of Cylc2 compared to Cylc1 in rodents and primates, however, the conservation of these genes in other species is not discussed.

Overall, the work highlights the relevance and importance of Cylicins in male infertility and advances our understanding of perinuclear theca formation during spermiogenesis.

Reviewer #2 (Public Review):

The work presented in this manuscript focuses on the role of Cylicins in spermiogenesis and the consequences of their absence on infertility. The manuscript is presented in two parts: the first part studies the absence of Cylicins from KO mouse models and shows in mice that both isoforms of Cylicins are necessary for normal spermiogenesis. The evaluation of double heterozygotes is particularly useful for the second part which looks at the presence of mutations in these genes in a cohort of infertile men. A patient with two hemizygous/heterozygous mutations in the CYLC1 and 2 genes, respectively, was identified for the first time and the results obtained with the KO models support the hypothesis of the pathogenicity of the mutations.

In general, the experiments are perfectly performed and the results are clear. Numerous techniques in the state of the art in male reproduction are used to obtain high-quality phenotyping of the mouse models.

The discovery of two concomitant mutations in an infertile patient is very interesting and the work carried out on mice allows supporting that an absence of CYLC1 and a heterozygous mutation of CYLC2 could lead to a phenotype of complete infertility. However, as the mutation on CYLC2 is not identified as pathogenic, the pathogenicity of this mutation remains in question (the authors note this point in the discussion). It would be interesting to see if the mutated amino acid is conserved between different species. In mice, the authors have shown the importance of these proteins on the morphology of the acrosome. What about in humans?

Reviewer #3 (Public Review):

The authors tried to study the role of the cylicin gene in sperm formation and male fertility. They used the Crispr/cas 9 to knockout two mouse cylicin genes, cylicin 1 and cylicin 2. They used comprehensive methods to phenotype the mouse models and discovered that the two genes, particularly cylicin 2 are essential for sperm calyx formation. They further compared the evolution of the two genes. Finally, they identified mutations of the genes in a patient. The major strengths are the high quality of data presented, and the conclusion is supported by their findings from the animal models and patients. The major weakness is that the study is descriptive: no molecular mechanism studies were conducted or proposed, limiting its impact on the field.

Reviewer #3 (Public Review):

In this manuscript, the authors characterize antigen binding sites, mechanism of action, and in vivo efficacy of neutralizing monoclonal antibodies (mAbs) previously isolated from New World hantavirus survivors. Both hantavirus species-specific mAbs and broadly neutralizing hantavirus mAbs are analyzed.

The strengths of the manuscript are the presentation of both in vitro and in vivo data for mAbs that have different antigen binding sites and mechanisms of neutralization. Weaknesses include a lack of authentic virus experiments for the in vitro data.

The impact of the work on the field is the identification of different neutralizing sites on hantavirus glycoproteins in species-specific and broadly reactive mAbs. There are also interesting data on loss of broadly neutralizing activity of mAbs after reversion to the germline sequence.

Reviewer #1 (Public Review):

This work focuses on the characterization of neutralizing antibodies from humans survivors of SNV and ANDV hantavirus infections, including the mapping of epitopes located in the Gn and/or Gc glycoproteins, and their mechanism of viral interference blocking receptor binding or membrane fusion. It also confirms previous data on broadly neutralizing epitopes allowing inhibition of different hantavirus species. The work covers for the first time in vivo evidence of cross-protection against HNTV infection by a broadly neutralizing antibody prepared from SNV infection using a prophylaxis animal model and compares the data with protection from ANDV lethal challenge using ANDV-specific neutralizing antibodies. The work provides valuable information for the development of therapeutic measures that cross-protect against several hantavirus species which seems a promising strategy to rise pharmaceutical interest against a group of viruses causing orphan disease.

The strength of the work is based on the impressive amount of work and versatility of methods to identify residues involved in the binding and/or escape from seven different neutralizing antibody clones that allow for important conclusions on species-specific antigenic regions and confirm data on a region that seems broadly conserved among different hantavirus species. At the same time, the weakness of the work is that data processing does not allow for readers data analysis (Figs. 1b, 2a, 2c, Ext. Data Fig. 4).

The authors clearly achieve their aim of characterizing the antigenic sites of neutralizing antibodies. Yet, the presented data on binding to ANDV mutant constructs and negative-staining EM does not allow for the conclusion that the epitope of the broadly neutralizing antibodies ANDV-44 and SNV-53 involved the Gn capping loop. An alternative explanation of the escape mutations in the Gn capping loop could be produced by an allosteric effect on the Gc fusion loop region, and a role in structuring the Gc fusion loop has been previously demonstrated (References 7 and 9). In addition, it is not clear why SNV-24 has no broad neutralizing activity although escape mutations occurred at the highly conserved residues K833 and D822 in Gc domain I.

Finally, concerning the in vivo protection experiments, it would be important to show viral RNA levels in lungs and kidneys in the lethal ANDV animal model (Fig. 7) to allow for comparison with the prophylaxis from HTNV infection (Fig. 6).

Reviewer #2 (Public Review):

Treatment of human illnesses caused by infection by hantaviruses are currently not available and hence research on new therapies are needed. The manuscript by Engdahl et al describes the characterization of four neutralizing antibodies with potency against hantaviruses using several approaches. This knowledge of these antibodies and where they bind in these studies can be used in the design of vaccines or the development of passive immunotherapeutic approaches and are hence very valuable for the advancement of new treatments. Hence this new knowledge is a major strength of the manuscript. the studies, however, the in vitro studies are limited in the use of pseudotyped viruses and not the actual viruses. Inclusion of the potency and binding of these to their native viruses, and standardization of their use in treatments of hamsters with these viruses, would elevate this approach to stand as a valuable contribution to the development of treatments for hantaviruses.

Reviewer #1 (Public Review):

Gordon-Fennell et al., here present a relatively low-cost, open-source platform for head-fixed operant and consummatory behaviour, called OHRBETS (prounounced Orbitz). This setup provides a great advantage over other systems in that it enables the animal to perform a truly operant response (i.e.one that fulfills the criterion of bidirectionality) whilst head-fixed. The authors provide thorough evidence of the utility of this setup, showing that a number of behavioural paradigms can be performed whilst the animal is head-fixed, as well as consummatory behaviours, optogenetic manipulations, and photometry recordings. These findings will be of broad interest to neuroscientists across multiple fields.

Strengths:<br /> 1. The work presented here is extremely thorough and explores multiple different types of paradigms. There is a huge amount of data that will be immensely useful to individuals who hope to use this setup and build on these findings. The setup is generally well-explained.<br /> 2. The statistics reported are generally quite strong and the sample sizes are sufficient (although strictly speaking ANOVA and Tukey should not be used together - Tukey's 'overall' test is a test of the maximal comparison, if the maximal comparison is not significant then no other pairwise comparison will be).<br /> 3. The open-source nature of the system is a great advantage as the fact that it is relatively low cost (as long as a lab has access to a 3D printer). This and similar endeavours will promote equality throughout the field.<br /> 4. The response here is truly operant as it is bidirectional. In other words, the animal shows that its response is governed by the relation between that response and the outcome, not stimulus-outcome associations like so many other so-called 'operant' responses (e.g. licking, food approach behaviours). Here, the stimuli are kept constant but the animal will either turn the wheel to the left or to the right to receive the food, depending on which direction is reinforced. This means that the animal cannot be governed solely by a stimulus-outcome response as in Pavlovian conditioning, because their response would not flexibly reverse the way that it is shown to here, particularly in Figure 1Q.<br /> 5. The accumbens shell recordings are interesting data in their own right (i.e. not simply to demonstrate the viability of the system), particularly the heterogeneity of the responses in the medial and lateral shells. This could be interesting for future studies to follow up on.<br /> 6. The correlational data between the head-fixed and free-moving versions of paradigms is, for the most part, quite convincing.

Weaknesses<br /> 1. I was curious as to how novel this setup is. Although I do not do head-fixed research myself, I thought there were already some open-source, relatively cheap systems available. I'm not sure how the current setup differs from those already available. Personally, even if this system involves only the wheel turning, as this is a truly operant response, that is novel enough for my liking.<br /> 2. It would be useful to have a bit more detail in the manuscript (not just on the GitHub link - in supplemental material perhaps?) on how to build such a system, just to get a sense of how difficult building such a system might be and how many components it has.<br /> 3. I wasn't sure how to feel about the comparisons across experimental set-ups in Figures 2 and 3. Usually, these sorts of comparisons are not considered statistically valid due to the many variables that differ between set-ups. However, I do see that the intent here is a bit different - i.e. is to show that despite all these alterations in variables the behavioural outputs are still highly correlated. However, without commenting on this intent, I did find these comparisons a little jarring to read.<br /> 4. The only dataset I was not wholly convinced by was that in Figure 3 (real-time place preference and aversion). I think the authors have done the best job that they can of replicating such a procedure in a head-fixed mouse, but the head-fixed version is going to necessarily differ from the freely moving version in a fundamental way when the contextual cues and spatial navigation form part of the RTPT task. Giving a discrete cue, such as a tone, just is not a sufficient substitute for contextual cues, and I think the two types of task would engage fundamentally different brain cells and circuits (e.g. only the free-moving version is likely to engage place cells in the hippocampus).<br /> 5. Personally, I found having the statistics in a separate file confusing.<br /> 6. Line 589-594. Suggesting the medial/lateral shell recording results mean that the medial shell 'tracks value, and the range of values during the multi-spout consumption of gradients of NaCl is greater than the range of values during multi-spout consumption of gradients of sucrose" seems to engage in circular logic to me. That is, the authors should use behavioural data to infer what the animal is experiencing and whether it is a change in value, and/or a greater change in value during NaCl vs. sucrose consumption, and only then should they make an inference about what the larger medial shell response means.

Overall this is a very solid paper in which the authors achieve their aims of demonstrating an open-source system for head-fixed operant and consummatory behavioural assessment, that is successfully employed across a number of different behavioural assays as well as in conjunction with optogenetic manipulations and fibre photometry recordings.

Reviewer #2 (Public Review):

The manuscript by Gordon-Fennell et al. presents an open-source platform for the analysis of behavior in a head-fixed apparatus (termed OHRBETS). In addition to providing instruction on how to assemble and implement the apparatus itself, the authors validate its use across a set of procedures broadly relevant to the field of behavioral neuroscience - including operant conditioning and fluid consumption protocols run in conjunction with optical manipulation and/or recording of neural activity.

The manuscript is comprehensive and clearly very strong. It also has the potential to have a broad impact in the field as many labs start to move towards effective head-fixed behavior. I also appreciate the fact that this manuscript includes a range of very strong behavioral tests - including experiments where several reinforcer options are available. This could be used for studies assessing taste, preference, reinforcer value, etc. Overall, the manuscript is impactful and my enthusiasm for it is high.

Reviewer #3 (Public Review):

Head-fixed preparations should always be conceived more as a necessity (for example, to avoid damaging expensive lab equipment) than as a final path towards which the entire field of neuroscience must go. The ideal will always be to move towards a more naturalistic and ecological approach to understanding behavior. Said that. The Davis Rig seems to be a thing of the past, welcome the Open-Source Head-fixed Rodent Behavioral Experimental Training System (OHRBETS). OHRBETS represents a significant advantage over the Davis Rig equipment to measure oromotor palatability responses in a brief access test, to perform positive and negative reinforcement, and even real-time place preference in a head-fixed preparation.

This is a well-written manuscript; the work and results are impressive. The manuscript is quite relevant to the Neuroscience field and will be of general interest. The experiments were carefully done. It is expected that OHRBETS will be widely used in multiple Neuroscience labs.

Reviewer #1 (Public Review):

This paper provides new technological approaches to expand adipocytes and aggregate them into structures that resemble fat. The authors use two cell types: a mouse cell line, as well as primary porcine cells. They demonstrate excellent lipid droplet accumulation in the mouse cell line however, this does not have translational relevance. So they go on to also perform those same experiments with the porcine cell line. The results are also encouraging especially if the cultivation is carried out over a period of 97 days.<br /> The authors also demonstrate similar mechanically mechanical properties of their cultivated fat to the native fat as well as the ability to aggregate it using two different approaches.

Overall, I think this is a thorough manuscript in the area of food bioengineering. The limitations remain the ability to fully remove FBS during this production process.

Reviewer #2 (Public Review):

This work describes a new method to create three-dimensional macroscale fat tissues derived from adipocytes cultured in two-dimensional monolayers. By scraping the differentiated adipocytes from the tissue culture plastic and mixing them with an edible binding material, they have created fat tissues that demonstrate similar mechanical properties to native animal tissue. Additionally, using lipidomics, the authors demonstrate that lipid treatment of the cultured adipocytes modifies their fatty acid composition in the triglyceride as well as the phospholipid portions. The fatty acid profiles of the cultured adipocytes are then compared to those of native animal fat tissues.

Strengths:

This paper addresses the relevant issue of the development of a hypoxic and necrotic core during the culture of large three-dimensional structures. The authors describe a straightforward method to bypass the three-dimensional cell culture by assembling their macroscale fat tissues after the adipocytes have fully differentiated in a two-dimensional monolayer.

The authors use two different binders to assemble their fat tissues, alginate, and microbial transglutaminase, both GRAS-registered. As the authors recognized, in the field of cultivated fat production for food consumption, it is essential to use materials that result in an edible product. Importantly, the authors demonstrate with mechanical testing that the binder material is of more significance to the mechanical properties of the macroscale fat tissue than the degree of lipid accumulation of the adipocytes.

The authors describe a detailed fatty acid composition profile of murine and porcine cultured adipocytes, treated and untreated with Intralipid, and native fat tissues. This dataset gives valuable insight into the effect of lipid treatment on fatty acid composition.

Weaknesses:

In the introduction, the authors hypothesize that their approach reproduces the taste of native fat and describe that fatty acid composition provides insight into flavor. The paper does not provide an analysis of taste to test this hypothesis and the lipidomics data does not provide data on the flavor profile of the aggregated macroscale fat tissues. In the abstract, the authors describe that the 3D fats were visually similar based on uniaxial compression tests. However, this test does not describe visual similarity.

The authors describe that detachment of adipocytes during differentiation was avoided by carefully replacing media and adipocytes had to be scraped off the flask even after increased lipid accumulation as a result of Intralipid treatment in the porcine adipocytes. Cell detachment of adipocytes on tissue culture plastic is a common phenomenon limiting the long-term culture of adipocytes in 2D. It could be useful for the field if the authors could describe in more detail how they avoided cell detachment during adipocyte differentiation or if they could hypothesize why they did not observe this phenomenon.

The authors compare the fatty acid composition of cultured adipocytes to that of native animal fat tissue. In the discussion, the authors describe that genetics and diet likely have an influence on the fatty acid composition profile of animal fat tissue. To be able to understand better what the effect is of Intralipid treatment, and to determine if this treatment brings the fatty acid composition of cultured adipocytes closer to their native counterpart, the authors could have cultured adipocytes in vitro from cells derived from the same animals as those that provided the native animal fat tissue.

In the discussion, the authors claim that the aggregate of adipocytes after scraping looked like fat tissue. This claim is not supported by lipid staining of cryosections of these aggregates, which makes it not possible to visually compare to the images of cryosectioned native animal tissue.

At the end of the discussion, the authors imply that their macroscale aggregation concept can be applied to scalable bioreactor-based cell culture strategies. However, the authors do not demonstrate how their method of scraping adipocytes from a tissue culture flask (low degree of scalability) applies to the potential of combining large amounts of adipocytes cultured on microcarriers in suspension bioreactors (high degree of scalability). The authors have not addressed the limited scalability of monolayer cell expansion which is a significant part of their approach.

Reviewer #1 (Public Review):

This manuscript represents a substantial and well-executed body of work that contributes new data on 32 hymenopteran genomes, systematically identifies viral endogenization and domestication events, and tests whether this phenomenon is more common in hymenopteran species with specific lifestyles, eg. endoparasitism. The authors developed a pipeline to identify endogenization that improves upon previously described pipelines and is more comprehensive for the identification of endogenization events from a variety of virus types. Significant findings include the identification of previously undocumented cases of viral endogenization in several hymenopteran species and also moderate statistical support for a higher rate of dsDNA virus endogenization and domestication in endoparasitoids.

1. The authors have tested whether the lifestyle of hymenopteran species (endoparasitism, ectoparasitism, or free-living) is related to the incidence of virus endogenization and domestication. Addressing this kind of question has only become possible with the availability of genome sequences from many taxa so that any results can be statistically supported by appropriate sample sizes. It appears that the authors have not included new genomic data from hymenopteran genomes that have been published since 2019, which are of similar or better quality than the data used in this manuscript. A number of taxa with endogenous viruses (and also without) have become available since then. The best solution would be for the authors to use their pipeline to incorporate the new data, which may have an impact on their findings and could even strengthen their conclusions about virus domestication being more common in endoparasitoids. If this is not possible, the authors should at least justify their decision not to include the most recent data and discuss how it could affect their results.

2. Please summarize in the main manuscript (results or discussion) what the limitations of the pipeline to detect EVEs and dEVEs are - what are important factors to consider, including the availability of closely related "free-living" viruses, and of closely related wasp species for dN/dS analyses.

3. In this manuscript, a description of the methods that precede the results would make it much easier to appreciate the results shown. It appears that this is allowed in cases where it makes sense, according to the author's instructions.

4. The sensitivity and specificity of methods analysis are commendable, as is the availability of substantial supplementary data and scripts on GitHub. However, more effort could be made to align numbers reported in the text and in figures so that readers can verify support for the conclusions described.

Reviewer #2 (Public Review):

Guinet et al address the question of whether the divergent lifestyles in hymenopteran insects determine the rates of acquisition and domestication of viral genetic elements. As endoparasitoids are intimately associated with their hosts and often develop as broods herein, they predicted that the acquisition rate is higher compared to free-living and ectoparasitoid hymenopterans. Following viral domestication in the new recipient wasp genome, these viral elements have been shown to contribute to endoparasitism by promoting the delivery of secreted compounds in insect hosts (where immature wasps develop). Because of this functional importance, the authors predicted that the rate of domestication is also higher in endoparasitoid wasps. I was impressed with the solid and rigorous approach that was followed to test these two hypotheses. The authors carefully ruled out confounding factors, including contamination of genome assemblies. Previously characterized hymenopteran genomes were included as positive controls to assess the developed pipelines. There was also great merit in using a Bayesian model to study endogenization within the phylogenetic framework. To summarize, this multi-pronged strategy to mine animal genomes for viral genetic elements has the potential of becoming a new benchmark for future studies.

Although the authors do partially achieve their aim of coupling endogenization with an endoparasitoid lifestyle, I am afraid some of the assumptions and generalizations hinder a more solid conclusion. I feel that categorizing hymenopterans either as free-living, endoparasitoids, or ectoparasitoids is an oversimplification. Many of the authors' arguments to associate endogenization with endoparasitoids also apply to free-living eusocial hymenopterans. Both endoparasitoid and eusocial insects can be relatively more exposed to viruses because of intimate conspecific interactions within confined spaces. As endoparasitoids intimately interact with their host, so do eusocial insects with their social guests (melittophiles, myrmecophiles, and termitophiles). Perhaps, you could even argue that some gregarious insects also fit the bill. I would be interested to see whether the conclusions hold when "free-living" is further subdivided and "eusocial" is a separate category. Second, I wonder why the authors did not include Wolbachia infection as an explanatory variable to explain the endogenization rate. Wolbachia bacteria infect the insect germline and are often associated with phages. These phages could thus be a major source of viral genetic elements. Having said that, I do not see any Symbioviridae, the phylogenetic clade in which these phages reside (https://doi.org/10.1371/journal.pgen.1010227), in Figure 2B - so perhaps this is a minor point.

Finally, in addition to the dsDNA virus - endoparasitoids relationship, the authors also detect a link between ssRNA viruses and free-living hymenopterans. (Maybe eusociality is biasing these results?) In any case, I realize the manuscript is already heavy in content but it would be interesting to also dissect these observations in a bit more detail.

Reviewer #3 (Public Review):

In this manuscript, Guinet and colleagues explore the impact of endoparasitoid lifestyle in Hymenopterans on endogenization and domestication of viruses. Using a well-structured bioinformatic pipeline, they show that an endoparasitoid lifestyle promotes viral endogenization and domestication, particularly for dsDNA viruses. In their discussion, they provide multiple discussion points to hypothesize why this could be the case. It is, to my knowledge, one of the first to link life history traits of insects to particular bias in the genomic endogenization of viruses, which has implications for virology and host-parasite interaction at large.

The manuscript is well-written and structured. The amount of data generated and analyzed is impressive, and the authors have carefully set up their analysis. I have no reasons to doubt any of the analyses the authors have conducted on the output of the screening pipeline set up to discover and characterize endogenous viral elements. I would, however, have appreciated a more thorough investigation on the impact of the scoring system for EVE detection (Scaffold endogenization score), which strongly shapes the dataset used for the analysis, and thus might introduce biases. While I completely understand the need for a scoring system and agree that the parameters used seem reasonable, these are new for the field, and their impact has not been properly explored here. The authors have chosen to focus on a conservative threshold of EVEs scored above D (see Table S2): I wonder what the picture would be if they included all potential EVEs, even poorly scored. How dependent are the results of this unvalidated scoring system? I know several proven EVEs in mosquitoes (confirmed in vivo) that would have been poorly scored and excluded here. By being sure to exclude false positives, the authors may have biased their dataset in ways that influence the results.

Reviewer #1 (Public Review):

The article from Salas Lucia et al addresses the distribution and transport of thyroid hormones (TH, including T4 and T3) in the adult brain. This is a complex and important question. Overall, the manuscript is difficult to follow as it jumps from one question (Dio2 polymorphism) to another (Mct8 function in the uptake of TH in neurons, and then the connection between TRH neurons and tanycytes), without deepening any aspect. There are, however, interesting findings in the article, but they should be confirmed by additional experiments.

Part 1: Type 2 deiodinase<br /> T4 entry is easier than T3 entry in the brain. However, type 2 deiodinase (Dio2 expressed mainly in glial cells) converts T4 to T3 and produces around 80% of the brain T3. In the introduction, the authors mention the controversial observation according to which a polymorphism of type 2 deiodinase, Thr92Ala-DIO2, is detrimental to the entry of TH into the brain. One of the associated issues, mentioned by the authors, is that some patients treated with TH have normalized circulating levels of hormones but still complain of fatigue, a typical feature of brain hypothyroidism.<br /> Experiment 1: Hippocampal Responsiveness to L-T4 is Impaired in the Ala92-Dio2 Mouse<br /> This first part is a continuation of a previous study published by the same authors. Here, they use transgenic mice with Ala92-Dio2 and Thr92-Dio2 to address possible differences in the TH response of several areas of the brain. The readout is a reporter mRNA, coming from an additional reporter transgene.<br /> Table I is supposed to clarify and summarize the results but brings confusion. The text says that table I supports the claim that "in the cerebellum Luc-mRNA was lower in the Ala92-Dio2 mice" whereas figure 1G does not show any difference. It is unclear whether Table I and figure 1 report the same data, and what the statistical tests are actually addressing (effect of genotype vs effect of treatment, whereas what matters here is only the interaction between genotype and treatment). Overall, it is not acceptable to present quantitative data without giving numbers, standard deviation, p-value, etc. as in Table I. Also, evaluating T3 signaling by only looking at the luc reporter and the Hprt housekeeping gene is not always sufficient (many T3 responsive genes can be found in the literature and more than one housekeeping gene should be used as a reference).<br /> Another important weakness is that the wild-type mice have a proline at position 92. Why not include them? In absence of structural prediction, one wonders whether the mouse models are relevant to the human situation and whether the absence of the proline reduces the enzymatic activity when substituted for an Ala or Thr. This might have been addressed in previous work, but the authors should explain.<br /> Experiment 2: Ala92-Dio2 Astrocytes Have Limited Ability to Activate T4 to T3<br /> Here, the authors use primary cell cultures from different areas of the brain to measure the in vitro conversion of T4 to T3 by Dio2. They find that hippocampus astrocytes are less active, notably if they come from Ala92-Dio2 mice.<br /> This part has the following weaknesses:<br /> - This result correlates with the results from Fig 1F however the difference between Ala92-Dio2 and Thr92-Dio2 is significant in vitro, but not in vivo. What matters is not the activity/astrocytes, but the total activity of the brain area, which depends on the number of astrocytes x individual activity. This is not measured.<br /> - What the authors called 'primary astrocytes' is an undefined mixed population of glial cells, (including radial glial cells, stem cells, ependymal cells, progenitor cells, etc...) that proliferated differentially for more than a week in culture, among which an unknown ratio expresses Dio2. The cellular model is thus poorly characterized, and the interpretation must be prudent.<br /> - Again, wild-type mice are not included.

Part 2: Neuronal response to T3 Involves MCT8 and Retrograde TH transport<br /> The authors next move to primary neuronal cultures, prepared from the fetal cortex which they grow in the microfluidic chamber to study axonal transport. This is a surprising move: the focus is not on Dio2 anymore, but on the MCT8 transporter, which is known in humans to play an important role to transfer TH into the brain. It is expressed mainly in glia, but also in neurons. They study the influence of endosomes and type 3 deiodinase on the trafficking and metabolism of TH.<br /> It would be useful to perform an experiment, in which radioactive T3 is introduced in the "wrong" side of the chamber, in an attempt to detect a possible anterograde transport. This would address the possibility that Mct8 also promotes efflux and control so that the chamber is not leaking.<br /> The authors use sylichristin as an inhibitor of Mct8, to demonstrate that transport is Mct8 dependent. They do not provide indications or references that would clearly indicate that this drug is a fully selective antagonist of Mct8 (but not of Oatp1c1, Mct10, Lat1, Lat2, etc., the other TH transporters). A good alternative would be to use Mct8 KO mice as controls.<br /> The B27 used in primary neuronal culture might contain TH. This is not easy to know, but at least some batches do.<br /> The presence of astrocytes, probably expressing Mct8 and Dio2 is inevitable in primary neuronal cultures, and is not mentioned, but might interfere with TH metabolism.

Part 3: T3 Transport Triggers Localized TH Signaling in the Mouse Brain<br /> The authors return to in vivo experiments, implanting T3 crystals, labeled or not with radioactive iodine. They do so in the hypothalamus, where they address the retrograde transport of TH in TRH neurons, and in the cortex, looking for contralateral transport.<br /> These data are the most difficult to interpret.<br /> - First, T3 is hydrosoluble and would probably migrate without active transport.<br /> - The authors do not demonstrate that these specific neuronal populations contain Mct8, and that these observations are connected to the previous in vitro observation (which used cortical neurons prepared from the fetus). The possibility that astrocytes are involved, as reported in the literature, is not considered.<br /> - Here again, using Mct8KO mice would greatly help to interpret the data. In particular, the experiments with cold T3 involve a 48h delay which is very long in comparison to the 30 minutes required for long-distance transfer of radioactive T3.<br /> Discussion<br /> Considering the diversity of questions that are addressed in the study, it is not surprising that the discussion is not covering all aspects. The authors implicitly consider that their conclusions can be extended to all neurons, while they use in their experiments a variety of different populations coming from either the fetal cortex, hippocampus, adult cortex, or hypothalamus. The claim that they discovered a mechanism applying to all neurons is not supported by the data. Some highly relevant literature is not cited. In particular:<br /> - Mct8 KO mice do not have a marked brain hypothyroidism (PMID: 24691440) which at least suggests that the pathway discovered by the authors can be efficiently compensated by alternative pathways.<br /> - Dio3 KO only increases T3 signaling in a few areas of the brain and only in the long term (PMID: 20719855).<br /> - Anterograde transport of T3 has been reported for some brainstem neurons (PMID: 10473259)

Reviewer #2 (Public Review):

Salas-Lucia et al. investigated two main questions: whether the Thr92Ala-DIO2 mutation impairs brain responsiveness to T4 therapy under hypothyroidism induction and the mechanisms of neuronal retrograde transport of T3. They find that the Thr92Ala-DIO2 mutation reduces T4-initiated T3 signaling in the hippocampus, but not in other brain regions. Using neurons cultured in microfluidic chambers, they further describe a novel mechanism for retrograde transport of T3 that depends on MCT8 and endosomal loading (possibly protecting T3 from D3-mediated cytosolic degradation) and microtubule retrotransport. Finally, they present evidence of retrograde transport of T3 through hypothalamic projections and interhemispheric connections in vivo. The main novelty of this study is the delineation of the mechanism of T3 retrograde transport in neurons. This is interesting from the cell biology perspective. The notion of impaired hippocampal T3 signaling is relevant for the cognitive outcomes of hypothyroidism and its associated therapy. Although the data are exciting and relevant for the community, some issues need to be addressed so that conclusions are more clearly justified by data:

1) The title and the abstract mean that dissecting this novel mechanism of T3 retrograde transport may help improve cognition or brain responsiveness in patients taking T4 or L-T3 therapy. However, how initial results (Figs 1 and 2) connect to later data is not essentially clear. For example, do Thr92Ala-DIO2 mice present altered retrograde transport of T3? Would stimulation of retrograde transport in Thr92Ala-DIO2 mice rescue neurological phenotypes? Can the authors address this experimentally?

2) Although the authors present in vivo evidence of retrograde T3 transport in the hypothalamus and motor cortex, given the select susceptibility of the hippocampus to hypothyroidism, it would be especially interesting to test whether this mechanism also happens in a hippocampal circuit (CA3-CA1 Schaffer collaterals, mossy fibers or perforant pathway).

3) Table 1 should present the raw values for Ala92-DIO2 mice and treatments instead of only displaying the direction of change and statistical significance. From Panels 1E-J, it is unclear if Thr92Ala-DIO2 mice or treatments caused any real change in brain regions other than the hippocampus.

4) The authors put forward the notion that a rapid nondegradative endosome/lysosome incorporation protects T3 from D3 degradation in the cytosol. Their experiments with pharmacological modulation of MCT8, lysosomes, and microtubules are in this direction. However, they do not represent an unequivocal demonstration of this mechanism. Therefore, the authors should be more cautious in their interpretation and discuss the limitations of their approaches.

Reviewer #3 (Public Review):

Initially, Salas-Lucia et al examined the effect of deiodinase polymorphism on thyroid hormone-medicated transcription using a transgenic animal model and found that the hippocampus may be the region responsible for altered behavior. Then, by changing to topic completely, they examined T3 transport through the axon using a compartmentalized microfluid device. By using various techniques including an electron microscope, they identified that T3 is uptaken into clathrin-dependent, endosomal/non-degradative lysosomes (NDLs), transported in the axon to reach the nucleus and activate thyroid hormone receptor-mediated transcription.

Although both topics are interesting, it may not be appropriate to deal with two completely different topics in one paper. By deleting the topic shown in Table 1, Figure 1, and Figure 2, the scope of the manuscript can be more clear.

Their finding showing that triiodothyronine is retrogradely transported through axon without degradation by type 3 deiodinase provides a novel pathway of thyroid hormone transport to the cell nucleus and thus can contribute greatly to increasing our understanding of the mechanisms of thyroid hormone action in the brain.

Reviewer #1 (Public Review):

This article is somewhat far afield from my typical line of research, but, to not bury the lede, I thought that this article makes an important point and is rigorously argued but could use some space to breathe in order to increase its impact.

More precisely, the authors perform a set of detailed calculations and simulations to show that the purported benefits of having non-linear morphogen decays are small near the source and decidedly reversed near the far end. I didn't have any specific concerns with these calculations, but one question I did have was if the typical context of morphogen gradients needs to be taken into account a little more (the paper doesn't really discuss how downstream morphogen gradients' noise might be affected by the structure of noise discussed here).

That said, I think that this is a rigorous submission.

Reviewer #2 (Public Review):

In this work, the authors tackle the question of how a non-linear decay in a morphogen gradient might affect downstream patterning specificity. In the first section of the paper, they address this theoretically, by examining the nature of morphogen gradients assuming either linear or non-linear degradation of the morphogen, using previously-established equations. Assuming variation in the concentration of morphogen at the source, they show that a linear decay model results in uniform shifts in the location of a threshold concentration of morphogen that only depend on the relative concentration changes, while a non-linear decay model yield shifts with more complex dependencies on concentration.

The next section of the paper addresses gradient patterning precision by accounting for not only variation in the source concentration of morphogen, but also in the parameters that describe the production, degradation, diffusion, and cell size, for both a linear and non-linear decay model. The key finding from this section is that, while non-linear decay can produce some improvements in patterning reliability near the morphogen source, it fares far worse than linear decay in regions far from the morphogen gradient. Simulations that include explicit morphogen-producing cells demonstrate that simpler models that exclude this detail may have overestimated the benefits of a non-linear morphogen decay.

The strength of this work is tackling head-on the question of how a non-linear decay of morphogen affects patterning precision using both theory and simulations. Non-linear decays have been observed in nature, and therefore this question is one of interest. The methods used by the authors provide convincing evidence for their claims, and the results, particularly the importance of simulating morphogen-producing cells, are likely to be of interest to the community interested in the design principles of morphogens and developmental patterning.

Reviewer #3 (Public Review):

This paper addresses the impact of non-linear protein degradation on the precision of morphogen gradients. Since the predominant model for the formation of morphogen gradients is a production/diffusion/degradation model understanding the contribution of degradation is an important question. This paper investigates the properties of the simplest and most general mathematical model for gradient formation. As such, this work is of interest. The main conclusion of the paper is that non-linear protein degradation has little impact on the precision of the morphogen gradient near the source of production of the morphogen and it reduces precision far away from the source. These conclusions are supported by the mathematical analysis presented. The paper is a difficult read for people unfamiliar with the current literature.

Reviewer #1 (Public Review):

In this study 1458 Enterobacterales isolates, derived from animals, waste-water and human bloodstream infections, were genetically characterized. This also yielded 3697 plasmids and many AMR genes.

All isolates were derived in a restricted geographical region and within a few years time. They defined "groups of near-identical plasmids" with plasmids derived from different genera, species, and clonal background; 8% of these groups contained plasmids from the different ecological niches and 35% of these cross-niche groups plasmids carried AMR genes. This fits with the concept of recent transfer of AMR plasmids between these ecological niches. Through detailed analyses they provide evidence that for E. coli, AMR dissemination between human and livestock-associated niches is most likely not the result of clonal spread but rather that plasmids transit between ecological niches.

Strengths

This is - to the best of my knowledge - one of the largest and most detailed studies elucidating the epidemiology of plasmids and AMR genes in different ecological niches.

Reviewer #2 (Public Review):

In their study the authors aimed to investigate the dissemination of Enterobacterales plasmids between geographically and temporally restricted isolates recovered from different niches, such as human blood stream infections, livestock, and wastewater treatment works. By using a very strict similarity threshold (Mash distance < 0.0001) the authors identified so-called groups of near-identical plasmids in which plasmids from different genera, species, and clonal background co-clustered. Also, 8% of these groups contained plasmids from different niches (e.g., human BSI and livestock) while in 35% of these cross-niche groups plasmids carried antimicrobial resistance (AMR) genes suggesting recent transfer of AMR plasmids between these ecological niches.

Next, the authors set-out to examine the wider plasmid population structure by clustering plasmids based on 21-mer distributions capturing both coding and non-coding plasmid regions and using a data-driven threshold to build plasmid networks and the Louvain algorithm to detect the plasmid clusters. This yielded 247 clusters of which almost half of the clusters contained BSI plasmids and plasmids from at least one other niche, while 21% contained plasmids carrying AMR genes. To further assess cross-niche plasmids similarities, the authors performed an additional plasmid pangenome-like analysis. This highlighted patterns of gain and loss of accessory plasmid functions in the background of a conserved plasmid backbone.

By comparing plasmid core gene or plasmid backbone phylogenies with chromosome core gene phylogenies, the authors assessed in more detail the dissemination of plasmids between humans and livestock. This indicated that, at least for E. coli, AMR dissemination between human and livestock-associated niches is most likely not the result of clonal spread but that plasmid movement plays an important role in cross-niche dissemination of AMR.

Based on these data the authors conclude that in Enterobacterales plasmid spread between different ecological niches could be relatively common, even might be occurring at greater rates than estimated, as signatures of near-identity could be transient once plasmids occupy and adept to a different niche. After such a host jump, subsequent acquisition, and loss of parts of the accessory plasmid gene content, as a result of plasmid evolution after inter-host transfer, may obscure this near-identity signature. As stated by the authors, this will raise challenges for future One Health-based genomic studies.

Strengths<br /> The article is well written with a clear structure. The authors have used for their analysis a comprehensive collection of more than 1500 whole genome sequenced and fully assembled isolates, yielding a dataset of more than 3600 fully assembled plasmids across different bacterial genera, species, clonal backgrounds, and ecological niches. A strong asset of the collection, especially when analyzing dissemination of AMR contained on plasmids, is that isolates were geographically and temporally restricted. Bioinformatic analyses used to discern plasmid similarity are beyond state-of-the-art. The conclusions about dissemination of plasmids between genera, species, clonal background and across ecological niches are well supported by the data. Although conclusions about inter-host plasmid dissemination patterns may have been drawn before, this is to my knowledge the first time that patterns of dissemination of plasmids have been studied at such a high-level of detail in such a well selected dataset using so many fully assembled genomes.

Weaknesses<br /> One conclusion that is not entirely supported by the data is the general statement in the discussion that "cross-niche plasmid in not driven by clonal lineages". From the tanglegram, displaying the low congruence between the plasmid and chromosome core gene phylogeny in E. coli, this conclusion is probably valid for E. coli, but this not necessarily means that this is also the case for the other Enterobacterales genera and species included in this study. For these other genera, the data supporting this conclusion are not given, probably because total number of isolates for certain genera were low, or because certain niches were clearly underrepresented in certain genera.

Furthermore, the BSI as well as the livestock niches were analyzed as single niches while the BSI niche included both nosocomial and community-derived BSI isolates and the Livestock niche included samples from different livestock-related hosts. Given the fact that a substantial number of plasmids were available from cattle, sheep, pigs, and poultry, it would be interesting to see whether particular livestock hosts were more frequently found in the cross-niche plasmid clusters than other livestock hosts and whether the BSI plasmids in these cross-niche clusters were predominantly of community or nosocomial origin.

Reviewer #1 (Public Review):

The authors conducted an extensive characterization of canine H3N2 influenza viruses. By analyzing gene sequences of canine H3N2 influenza viruses isolated in their laboratory and those that are available in public databases, they identified various genetic clades (also somehow correlate with antigenic groups identified in serological assays) and human-like amino acid substitutions in these viruses, which indicated the evolution of these viruses towards potentially more adaptive to humans. By experiments with several selected canine H3N2 influenza isolates, they found that more recent canine H3N2 influenza viruses have acquired receptor specificity for both avian- and human-like receptors, enhanced low-pH stability and in vitro growth as well as improved replication and transmission in the dog and ferret models. They further identified amino acid substitutions underlying the improved transmissibility of these canine H3N2 influenza viruses. The study was well-designed and the conclusions in the manuscript are in general well supported by the experimental data. Findings from the study will certainly help understand the evolution of canine influenza viruses and assessing the risk posed by these viruses to public health.

Although the authors have identified some properties/molecular markers of canine H3N2 influenza viruses that highlight the potential for infecting humans, it needs to be cautious to emphasize the threat of these viruses to public health. One fact is that despite the increasing prevalence of these viruses in dogs and the close proximity between dogs and humans, there is so far no report of human infection with canine H3N2 influenza viruses. The authors are wished to discuss this in their manuscript so that the readers can have a more comprehensive understanding of their findings and the public health importance of canine influenza viruses.

Reviewer #2 (Public Review):

The authors show how an avian influenza A virus that jumped into dogs is now evolving in real time. Though its evolutionary adaptation to dogs, the virus is gaining properties that are increasingly consistent with the potential to infect humans.

The data are alarming, although it should be emphasized that this dog H3N2 influenza virus has not yet infected humans, and perhaps never will. It is also unknown how pathogenic (medically serious) the virus would be in humans if it were to jump. The authors show preliminary data that prior exposure to human seasonal H3N2 will not render us resistant to this dog virus should it jump to humans.

What is most remarkable about this study is the breadth of experimental approaches taken, and the holistic analysis of what is bound to become a classic tale in virus evolution and emergence through an intermediate host.

Reviewer #3 (Public Review):

The manuscript by Chen et al shows solid evidence that canine origin influenza viruses are evolving towards a more mammalian adapted phenotype. The data also show that humans may lack proper protection against these viruses if they were to evolve more prone to cross to humans. There are some aspects of the ms that need to be addressed: 1) The investigators should run neuraminidase inhibition assays to established the level of cross reactivity of human sera to the canine origin NA (one of reasons proposed as to the lower impact of the H3N2 pandemic was the presence of anti0N2 antibodies in the human population), 2) please tone down the significance of ferret-to-ferret transmission as a predictor of human-to-human transmission. Although flu viruses that transmit among humans do show the same capacity in ferrets, the opposite is NOT always true.

Reviewer #1 (Public Review):

In this manuscript, the authors have elegantly demonstrated the significance of asking fundamental questions in patient-derived models of patient-derived organoids (PDOs). This is especially relevant for studying complex cancers such as High-Grade Serous Ovarian Carcinoma (HSCOG). In addition to developing patient-derived organoids, this study has comprehensively examined transcriptomic, genomic, and single-cell data. In addition, based on this data, the authors have performed a complex drug sensitivity assay that further stratifies the PDOs into drug-sensitive and resistant categories. This approach would be central to identifying therapeutic regimens for difficult-to-treat cancers in the future.

Reviewer #2 (Public Review):

In this manuscript, Vias and co-authors develop HGSOC PDOs and characterized their genomes, transcriptomes, drug sensitivity, and intra-tumoural heterogeneity. They show that PDOs represent the high variability in copy number genotypes observed in HGSOC patients. Drug sensitivity was reproducible compared to parental tissues and the ability of these models to grow in vivo.

Overall, the manuscript lacks sufficient novelty. Several pieces of information and a number of conclusions that are presented here have been previously published by other groups (Nina Maenhoudt, Stem cell reports, 2020; Shuang Zhang, Cancer Discov, 2021).

Reviewer #3 (Public Review):

The manuscript adequately demonstrates that genomic instability is maintained in HGSOC tumourspheres. The use of 3-dimensional HGSOC models to more greatly resemble the in vivo environment has been used for more than a decade, but this is the first demonstration using a variety of genomic assessment tools to show genomic instability in the HGSOC tumoursphere model. It is clearly demonstrated that these HGSOC tumourspheres represent copy number variations similar to information in public datasets (TCGA, PAWG, BriTROC-1) and that cellular heterogeneity is present in these tumourspheres. The simple steps outlined to establish and passage tumourspheres will benefit the field to further study mechanisms of genomic instability in HGSOC.

A weakness of the manuscript is the lack of operational definitions for what constitutes an organoid and an appropriate definition to distinguish genomic instability from chromosomal instability (a distinct type of genomic instability). Line 147 states "As PDOs consist of 100% tumour cells...", although this does not appear to have been established by any assessment. This limited characterization of the 3D model is a weakness since no data is provided on whether the tumourspheres constitute only a single cell type (as indicated on line 147) or multiple cell types (e.g., HGSOC cell, mesothelial cells) using markers beyond p53 expression. Based on this information, this model cannot be called a PDO, rather it should be referred to as a tumoursphere.

Chromosome instability (CIN) is a type of genomic instability that is broadly defined as an increased rate of chromosome gains or losses and is best identified through analysis of single cells (e.g., karyotype analysis), something that bulk whole genome sequencing cannot determine since it is a reflection of cell populations and not individual cells. While the data demonstrate genomic instability is retained in the tumourspheres, and chromosome losses or copy-number amplifications were observed using single-cell whole genome sequencing, evaluation of samples from the same patient over time was not evaluated. While there is evidence to support CIN in these samples, in agreement with other published work that has demonstrated CIN in >95% of HGSOC samples analyzed at the single-cell level, this work is not conclusive. The title of the manuscript should be modified to more accurately represent what the evidence supports.

An additional weakness is missing information (e.g., Figure 1d, Supplementary Figure 3b, and Supplementary Table 4 were not included in the manuscript; the 13 anticancer compounds used to test drug sensitivity are not indicated) making an assessment of the data impossible, and assessment of some conclusions difficult.

Reviewer #1 (Public Review):

The basis of this method is to clone guides into a Crispr-based editing plasmid, transfect pools into Leishmania, maintain them as episomes, then look at phenotypes. The guides are designed to cause editing that converts codons to stop codons, and the authors have designed a computational tool that enables the design of guides that work for the first half of each gene. Selection for the episome is necessary and editing efficiencies were variable (99% to 0%) depending on the species, being worst for L. major. The use of premature termination codons also clearly raises issues for false positives and negatives, especially as there is no evidence for nonsense-mediated mRNA decay in Leishmania.

There are already two genome-wide screening options for Leishmania, so the advantages and disadvantages of the method proposed here need to be discussed in a much more detailed and balanced way.<br /> In the "LeishGEM" project (http://www.leishgem.org) all Leishmania mexicana genes will be knocked out and each KO will be bar-coded. At the end, 170 pooled populations of 48 bar-coded mutants will be publicly available. The only real reason the authors of the current paper give for not using this approach is that it is labour-intensive. However, LeishGEM is funded and underway, with several centres involved, so that argument is weak.<br /> There is also a preprint describing RNAi for functional analysis in Leishmania braziliensis.

Reviewer #2 (Public Review):

This is a well-written and clear manuscript, in which the authors describe the stepwise development of an approach for loss of function screens in a range of different Leishmania species, culminating in a small-scale screen. The method relies on CRSIPR/Cas9 directed mutation of cytosine bases to generate premature STOP codons. The conclusions of the manuscript are well supported by the data presented and this approach appears to have great potential to facilitate functional studies and discovery biology in a range of different species.

The authors have presented the development of their base editing toolbox in a stepwise manner, showing the optimisation steps they took. They initially used a tdTomato expressing cell line to optimise which base editor to use and examine constitutive versus episomal expression approaches. Before analysing specific proteins - PFR2, IFT88, PF16, MFT. This systematic approach gives confidence in their results and the utility of the system. The primer design resource with primer effectiveness score is great to see and will aid the adoption of this approach.

Line 482 - the authors wrote 'As expected, the proportion of cells showing a motility phenotype in the IFT88 targeted L. infantum population decreased further' Why is this result expected? Presumably, this is due to the fact that cells without a functional IFT system lack flagella and grow slower so can be outcompeted by faster-growing mutants. This speaks to the major caveat highlighted by the authors in the discussion and the final small-scale screen. In a population of cells, those with deleterious mutations in an essential gene or one whose disruption results in slower growth will be outcompeted by cells in which a non-deleterious mutation has occurred, which feeds into the issue of timing.

The authors show with CRK3 this process of non-deleterious mutants outcompeting deleterious mutants does result in a detectable drop in the number of parasites with specific CRK3 guides but not in those with IFT88. Is this due to the fact that the outgrowth of the non-deleterious IFT88 mutants occurs rapidly or that the mutation of the targets in IFT88 was ineffective? The data presented in Figure 5 shows that for some species at least a mutation of the IFT88 gene was possible. This might mean that for certain genes the outgrowth occurs within the first 12 days after transfections so will not be seen using this approach, without a wider study, which is beyond the scope of this manuscript it will be difficult to know.

The ability to readily generate cells resistant to miltefosine, highlight the strength of this approach in identifying the mode of actions/resistance mechanisms for anti-leishmanial drugs. Moreover, any screens using this base editing approach, in which cells expressing proteins without a changed functionality/expression are killed will likely be effective in identifying genes of interest. This could mirror the success that the genome-wide RNAi screens have had in Trypanosoma brucei.

This base editing approach now sits alongside using CRISPR/Cas9 to generate full gene deletion mutants and RNAi to help understand gene function in Leishmania. As discussed by the authors in their balanced discussion there are merits. A major advantage of this approach is the ability to simply generate a library of plasmids that will target the entire genome, whereas both full gene deletions and RNAi in L. braziliensis are more time-consuming and the latter lacks inducible control. However, as part of the LeishGEM project pools of barcoded deletion mutants are being generated, which have the potential to be used in other screens. Moreover, this base-editing approach has the potential to identify the function of essential genes, which is not possible when trying to generate stable deletion cell lines. However, this has only been demonstrated for one gene to date and the ability to detect slower-growing mutants varied greatly between different species.

The authors highlight that this base editing approach will leave potentially functional regions of the NT of proteins, which is true and may mean genes are missed. However, this may also provide extra information about the protein's function/domain structure if STOP codons in certain positions showed an effect on function whereas those in others don't.

Overall, the base editing approach in this manuscript looks to have great utility and in reality, is a complementary approach to the genetic tools we already have to study gene function in Leishmania. However, only time will tell how effective this method is through its adoption and effective use by different researchers.

Reviewer #1 (Public Review):

This umbrella review aims to synthesize the results of systematic reviews of the impact of the COVID-19 pandemic on various dimensions of cancer care from prevention to treatment. This is a challenging endeavour given the diversity of outcomes that can be assessed in cancer care.

Search and review methods are good and are in line with recommendations for umbrella reviews. Perhaps one weakness of the search strategy was that only one database (Pubmed) was searched. The search strategy appears adequate, though perhaps some more search terms related to reviews and cancer could have been included. It is therefore possible that some reviews may have been missed by the search strategy.

It is challenging to perform a good umbrella review that yields novel insights, as it is difficult to combine results from different reviews which themselves combine results from different studies with different methodologies. However, I think perhaps one of the main weaknesses of this study is that it is not clear to me what is the core objective of the umbrella review, and how analyses relate to that core objective. In other words, I do not understand based on the introduction what new information the authors are hoping to learn from their umbrella review that could not be learned from reading the individual systematic reviews, beyond a vague objective of "synthesizing" the literature. Because of this, it is not very clear to me how the data extracted and the analysis fits into the larger objectives, and what the new knowledge generated by this review is. Based on the reported results, it would appear that one of the main goals is to assess the quality of systematic reviews and of the underlying studies in the reviews, but it is hard to tell. I think there are potentially important insights this review could tell us, but the message and implications of current evidence remain for me a little confused in the current manuscript.

Reviewer #2 (Public Review):

This umbrella review summarizes the results of systematic reviews about the impact of the COVID-19 pandemic on cancer care. PRISMA checklist is used for reporting. The literature search was performed in PubMed and systematic reviews published until November 29th, 2022 were included. The quality of included systematic reviews was appraised using the AMSTAR-2 tool and data were reported descriptively due to the high heterogeneity of 45 included studies. Based on the results of this paper, regardless of the low quality of included evidence, COVID-19 affected cancer care in many ways including delay and postponement of cancer screening, diagnosis, and treatment. Also, patients with cancer had been affected psychologically, socially, and financially during the COVID-19 pandemic.

Strengths:

This umbrella review has summarized many important aspects of cancer care that were affected during the COVID-19 pandemic.

Weakness:

The main limitation of the current study is that the authors have searched only one database, which might have missed some relevant systematic reviews. Also, most of the included reviews in this paper had low and medium methodological quality.

Reviewer #1 (Public Review):

The article is a straightforward continuation of their previous 2016 study. The authors demonstrate an organism-level role of intermediate filaments (IFs) in C. elegans with a model highlighting intermediate filament functions in organism development, larval development, oxidative stress-resilience, size, and lifespan.

The study uses endotube morphogenesis in C. elegans as an elegant model to examine the effect of aberrant IF network morphogenesis on endotube morphology and how these effects are reflected in terms of progeny growth and development.

The study identifies the C. elegans IF protein IFB-2 as a core component of IF network morphogenesis where any mutation or dysfunction of IF interacting proteins such as SMA-5, IFO-1, and BBLN1 can be mostly rescued by silencing of IFB-2.

The observed mutations cause a range of systemic and functional defects of which endotube-related defects that include luminal widening and cytoplasmic invaginations are regarded as the key parameters to observe the direct result of IF network perturbation in the study. Based on these parameters authors narrowed down on IFB-2 head domain as a critical interactor in IF network morphogenesis and function.

On the whole, very interesting findings and an elegant study with excellent data that would be of broad interest for cytoskeletal research. The study has clear ramifications also for the understanding of the evolutionary development and roles of IF, both IF aspects that are still very poorly understood.

Reviewer #2 (Public Review):

The authors describe in the nematode C. elegans the effects of perturbed organization of Intermediate filaments (IFs), which form the cytoskeleton of animal cells together with actin filaments. They focus on a previously identified mutant of the kinase SMA-5, which when mutated leads to disorganized IF structure in intestinal cells of C. elegans. The authors found that the phenotypes caused by the mutated SMA-5 kinase concerning gut morphology and animal health can be reversed by removing IF network components such as the protein IFB-2. This finding is extended to other components of the IF network, which also display a certain degree of sma-5 phenotype alleviation when depleted.

Strength:<br /> The finding that suppressing the intestinal phenotypes caused in sma-5 mutants can be suppressed by removing functional IF components is an interesting observation. It confirms a previous study showing that bbln-1 mutation-caused IF phenotypes can be suppressed by depleting IFB-2.

Weakness:<br /> 1) The finding of suppressing the intestinal phenotypes caused in sma-5 mutants can be considered a minor conceptual advancement. However, the study comes short of providing insight into the molecular processes of how deranged IF networks and its consequence can be rescued/suppressed by removing e.g. the IFB-2 filaments. Many statements concerning the relationship between SMA-5 and the IFs are based on assumptions. The study requires protein biochemical analysis to show whether SMA-5 phosphorylates the IF proteins - mainly the IFB-2 polypeptide. The relationship between SMA-5 / IFB-2 is a central aspect of this study but the main conclusions are based on the notion that IFB-2 and other IF proteins may be phosphorylated by SMA-5. Mutating putative phosphorylation sites of IFB-2 without having shown any proof that the modification occurs by SMA-5 is futile. This important open question needs to be addressed. And will allow statements whether the ifb-2(kc20) mutant allele-encoded shorter IFB-2 protein lacks phosphorylation or not.

2) No quantification of the morphological defects such as using fluorescent-labeled IF proteins as in previous studies is provided in the manuscript. The EM pictures are not sufficient to provide information on how often the IF network perturbations and morphology defects occur. Also, the rescue of the actual morphological gut defects was not quantified. The assessment of development time and arrest, body length, lifespan, oxidative stress resistance, and others should be related to intestinal tube defects. They are useful and important but are an indirect measure of intestine defects and rescue.

3) It is not clear how exactly the mutant ifb-2 allele kc20 was identified. In the Materials and methods section, the authors provide information on the specific primers for the ifb-2 locus. But how did they know that the mutation lies within this region? Was there mutation mapping or whole-genome sequencing applied?

Reviewer #3 (Public Review):

This manuscript by Geisler and colleagues used suppressor genetics to identify suppressors of the sma-5(n678) allele, which results in a defective gut endotube (an IF layer just under the microvillar structure), small body size, slow development, and short life span. The authors identified an internal deletion allele in ifb-2, which stunningly rescues all of the phenotypes listed above (despite the apparent absence of an endotube). This suppression is also observed with a previously characterized knockout allele. Conversely, this allele also suppresses analogous defects that result from mutations in the ifo-1 gene and bbln-1.

This is an exceptionally rigorous set of experiments, beautifully described in a clear manuscript illustrated by nicely constructed figures. The overall finding, that some IF mutations result in toxic aggregates that can be eliminated by the loss of a single IF protein is interesting both from a fundamental understanding of IF networks and its clinical implications. With one minor exception, the conclusions are well supported by the data presented.

Reviewer #1 (Public Review):

This carefully done research paper presents a fundamental model of techniques that are useful for the elucidation of kinase substrates. The paper utilizes state-of-the-art approaches to define a kinetic phosphoproteome and how to integrate that data with complementary approaches using a chemical probe (in this case KTPyS, a triphosphate) to find these substrates. Using these approaches TgCDPK1 was demonstrated to affect microneme secretion via a direct interaction with a HOOK complex (defined as a HOOK protein TGG1_289100, an FTS TGGT1_264050 and 2 other proteins TGGT1_316650 and 306920).

This work is carefully controlled and the analysis pathways are logical and provide paradigms for how to approach the question of identifying substrates of kinases using proteomic approaches employing genetic and chemical strategies.

The authors succeeded in the identification of candidate substrates for TgCDPK1. Validation of the results was provided by previous studies in the literature that characterized some of these substrates as well as the experiments in this manuscript on the characterization of the HOOK complex that is phosphorylated by CDPK1.

The HOOK complex (defined as a HOOK protein TGG1_289100, an FTS TGGT1_264050, and 2 other proteins TGGT1_316650 and 306920) was clearly demonstrated to be involved in invasion via its role in microneme trafficking.

Reviewer #2 (Public Review):

In this study, the authors take a multipronged approach to identify the substrate repertoire of calcium-dependent protein kinase, CDPK1 in Toxoplasma that includes quantitative phosphoproteomics, myristoylation, thiophosphorylation, immunoprecipitation as well as proximity-based labeling. Their finding also reveals that CDPK1 functions in parasite invasion and egress by phosphorylating different protein candidates. More importantly, the authors successfully determine one branch of the CDPK1 signaling pathway that regulates invasion through the phosphorylation of the HOOK protein involved in the translocation and secretion of micronemal proteins.

Reviewer #3 (Public Review):

In this manuscript, Chan and collaborators investigate the role of CDPK1 in regulating microneme trafficking and exocytosis in Toxoplasma gondii. Micronemes are apicomplexan-specific organelles localized at the apical end of the parasite and depending on cortical microtubules. Micronemes contain proteins that are exocytosed in a Ca²+-dependent manner and are required for T. gondii egress, motility, and host-cell invasion. In Apicomplexa, Ca²+ signaling is dependent on Ca²+-dependent protein kinases (CDPKs). CDPK1 has been demonstrated to be essential for Ca²+-stimulated micronemes exocytosis allowing parasite egress, gliding motility, and invasion. It is also known that intracellular calcium storages are mobilized following a cyclic nucleotide-mediated activation of protein kinase G. This step, occurs upstream of CDPK1 functions. However, the exact signaling pathway regulated by CDPK1 remains unknown. In this paper, the authors used phosphoproteomic analysis to identify new proteins phosphorylated by CDPK1. They demonstrated that CDPK1 activity is required for calcium-stimulated trafficking of micronemes to the apical end, depending on a complex of proteins that include HOOK and FTS, which are known to link cargo to the dynein machinery for trafficking along microtubules. Overall, the authors identified evidence for a new protein complex involved in microneme trafficking through the exocytosis process for which circumstantial evidence of its functionality is demonstrated here.

Reviewer #1 (Public Review):

This study builds an odorant organization map as estimated by a neural network trained on several odor perceptual classification databases. The authors come up with an attractive hypothesis about the link of odor perception to metabolic connectedness, as opposed to a range of other ways of classifying odorant compounds. There are several interesting implications of this, which the authors touch upon, but could perhaps frame as specific predictions.

The authors clearly have generated a powerful methodology, a useful classifying network, and a well-organized database. The study would be much stronger if the methodology were more thoroughly explained, with open code and data availability as expected for a computational study, and as a resource for further research on the topic.

It would also be valuable to place the current findings in the context of considerable earlier work that has sought to map odor perception and place it in the context of structural and chemical features.

Reviewer #2 (Public Review):

In this manuscript, the authors use an embedding of human olfactory perceptual data within a graph neural network (which they term principal odor map, or POM). This embedding is a better predictor of a diverse set of olfactory neural and behavior data than methods that use chemical features as a starting point to create embeddings. The embedding is also seen to be better for comparison of pairwise similarities (distances of various sorts) - the claim is that proximity of pairs of odors in the POM is predictive of their similarity in neural data from olfactory receptor neurons.

A major strength of the paper is the conceptualization of the problem. The authors have previously described a graph neural net (GNN) to predict verbal odor descriptors from molecular features (here, a 2019 preprint is cited, but a newer related one in 2022 describing the POM is not cited). They now use the embedding created by that GNN to predict similarities in large and diverse datasets in olfactory neuroscience (which the authors have curated from published work). They show that predictions from POM are better than just generic chemical features. The authors also present an interesting hypothesis that the underlying latent structure discovered by the GNN relates to metabolic pathway proximity, which they claim accounts for the success in the prediction of a wide range of data (insect sensory neuron responses to human behavior). In addition to the creativity of the project, the technical aspects, are sound and thorough.

There are some questions about the ideas, and the size of the effects observed.

1. The authors frame the manuscript by invoking an analogy to other senses, and how natural statistics affect what's represented (and how similarity is defined). However, in vision or audition, the part of the world that different animals "look at" can be very different (different wavelengths, different textures and spatial frequencies, etc). It is still unresolved why any given animal has the particular range of reception it has. Each animal is presumably adapted for its ecological niche, which can have different salient sensory features. In vision, different animals pick different sound bandwidths or EM spectra. Therefore, it is puzzling to think that all animals will somehow treat chemicals the same way.

2. The performance index could be made clearer, and perhaps raw numbers shown before showing the differences from the benchmark (Mordred molecular descriptor). For example, can we get a sense of how much variance in the data does it explain, what percent of the hold-out tests does it fit well, etc.?

3. The "fitting" and predictions are in line with how ML is used for classification and regression in lots of applications. The end result is a better fit (prediction), but it's not actually clear whether there are any fundamental regularities or orders identified. The metabolic angle is very intriguing, but it looks like Mordred descriptor does a very good job as well (extended figure 5). Is it possible to show the relation between metabolic distance and Mordred distance in Figure 2c? In fact, even there, cFP distance looks very well correlated with metabolic distance (we are talking about r= 0.9 vs r = 0.8). This could simply be due to a slightly nonlinear mapping between chemical similarity and perceptual similarity (which was used to get POM distance).

4. How frequent are such examples shown in Fig 2d? Pentenal and pentenol are actually very similar in many ways, and it may be that Tanimoto distance is not a great descriptor of chemical similarity. cFFP edit distance is quite small, just like metabolic distance. The thiol example on the right is much better. Also, even in Fig 2C POM vs metabolic distance, the lowest metabolic distances have large variations in the POM values - so there too, metabolic reactions that create very different molecules in 1 step can vary widely in POM distance as well.

5. A major worry is that Mordred descriptors are doing fine, and POM offers only a small improvement (but statistically significant of course). Another way to ask this question is this: if you plot pairwise correlation/distance of pairs of odors from POM against that for Mordred, how correlated does this look? My suspicion is that it will be highly correlated.

6. The co-occurrence in mixtures and close POM distance may arise from the way the embedding was done - with perceptual descriptors used as a key variable. Humans may just classify molecules that occur in a mixture as similar just from experiencing them together. Can the authors show that these same molecules in Fig 4d,e have very similar representations in neural data from insects or mice?

Reviewer #1 (Public Review):

Collins et al use mesoscopic two-photon imaging to simultaneously record activity from basal forebrain cholinergic or noradrenergic axons in several distant regions of the dorsal cortex during spontaneous behavior in head-fixed awake mice. They find that activity in axons from both neuromodulatory systems is closely correlated with measures of behavioral state, such as whisking, locomotion and face movements. While axons were globally correlated with these behavioral state-related metrics across the dorsal cortex, they also find evidence of behavioral state independent heterogenous signals.

The use of simultaneous multiarea optical recordings across a large extent of dorsal cortex with single axon resolution for studying the coherence of neuromodulatory afferents across cortical areas is novel and addresses important questions regarding neuromodulation in the neocortex. The manuscript is clearly written, the data is well presented and, for the most part, carefully analyzed. Parts of the manuscript confirm previous results on the influence of behavioral state on norepinephrine and acetylcholine cortical afferents. However, the observation that these modulations are globally broadcasted to the dorsal cortex while behavioral state independent hetetogenous signals are also present in these axons is novel and important for the field.

While the evidence for a behavioral state driven global modulation of activity in both neuromodulatory systems is quite clear, I have concerns that the apparent heterogeneity in axonal responses might be driven by movement-induced artifacts. Moreover, even in the case that the heterogeneity in calcium activity across axons is confirmed, it might not be driven by differences in spiking activity across neuromodulatory axons as concluded, but by other mechanisms that are not explicitly discussed or considered.

1) Motion artifacts are always a concern when imaging from small structures in behaving animals. This issue is addressed in the manuscript in Fig 2A-C by comparing axonal responses to "autofluorescent blebs that did not have calcium-dependent activity" (line 1011). Still, as calcium-dependent activity and motion artifacts can both be locked to behavioral variables the "bleb" selection criterion seems biased and flawed with a circular logic. "Blebs" presenting motion-induced changes in fluorescence that may pass as neural activity will be wrongly excluded when from the "bleb" control group using this criterion. This will result in an underestimation of the extent of the contamination of the GCaMP signals by movement-induced artifacts. This potential confound might generate apparent heterogeneity across axons and regions as some axons and some cortical areas might be more prone to movements artifacts than others.

2) In the case that the heterogeneity is indeed due to differences in calcium activity, it might be not due to modularity in spiking activity within the LC or the BF as interpreted and discussed in the manuscript. As calcium signaling in axons not only relates to spiking activity but can also reflect presynaptic modulations, the observed heterogeneity might be due to local action of presynaptic modulators in a context of global identical broadcasted activity. The current dataset does not allow distinguishing which of the two different mechanisms underlies to the observed signal heterogeneity.

Reviewer #2 (Public Review):

This study uses behavioral monitoring and cutting-edge calcium imaging approaches to track the activity of cholinergic and noradrenergic axons in cortex of head-fixed mice, and correlate activity with behavioral state. The data confirm that much of this activity is dependent on behavioral state, and in particular is strongly correlated with arousal of the animal and is highly coordinated across axons. They also show that a small fraction of axonal activity is heterogenous, and does not seem to be dependent on global behavioral state. They describe additional details of this activity, such as that whisking activity is the best predictor of cholinergic and noradrenergic axon activity, and that noradrenergic activity is more transient during bouts of arousal (whisking) than cholinergic activity. Altogether this manuscript is generally very thorough analytically, most of the data appear technically sound, and the presentation is largely clear. However, the significance of the findings - exactly how much they enhance what is already known - is less clear.

The main advanced novelty of the approach is the use of mesoscale imaging, giving them the ability to analyze the degree to which neuromodulatory cholinergic and noradrenergic signals are uniform across cortex, or might be correlated with distinct behavioral states or events. They attempt to get at this in Figure 4, by determining how much of their detected signal from cholinergic and noradrenergic axon activity comes from a 'common signal' versus how much of the signal is residual once the common signal is subtracted, so presumably reflects a unique influence. This analysis and the reasoning behind it is very hard to follow, and it is not clear to us that these residual signals are truly meaningful (i.e. not coming just from some source of noise). The authors try to get at this meaning in Figure 4K by plotting partial minus ordinary correlations in different arousal states, but it is not clear to us what exactly this difference means, considering the ordinary correlation itself is different in those comparisons as well. The fact that there is a bigger difference between partial and ordinary correlations during whisking than in other states does not give us real information about where the partial correlation is from.

Reviewer #3 (Public Review):

Acetylcholine and Norepinephrine are two of the most powerful neuromodulators in the CNS. Recently developments of new methods allow monitoring of the dynamic changes in the activity of these agents in the brain in vivo. Here the authors explore the relationship between the dynamic changes in behavioral states and those of ACh and NE in the cortex. Since neuromodulatory systems cover most of the cortical tissue, it is essential to be able to monitor the activity of these systems in many cortical areas simultaneously. This is a daunting task because the axons releasing NE and ACh are very thin. To my knowledge, this study is the first to use mesoscopic imaging over a wide range of the cortex at the single axon resolution in awake animals. They find that almost any observable change in behavioral state is accompanied by a transient change in the activity of cortical ACh and NE axonal segments. Whisking is significantly correlated with ACh and NE. The authors also explore the spatial pattern of activity of ACh and NE axons over the dorsal cortex and find that most of the dynamics is synchronous over a wide spatial scale. They look for deviation from this pattern (which I will discuss later). Lastly, the authors monitor the activity of cortical interneurons capable of releasing ACh.

Comments:<br /> 1. On a broad overview, I find the discussion of behavioral states, brain states, and neuromodulation states quite confusing. To begin with, I am not convinced by the statement that "brain states or behavioral states change on a moment-to-moment basis." I find that the division of brain activity into microstates (e.g., microarousal) is counterproductive. After all, at the extreme, going along this path, we might eventually have an extremely high dimensional space of all neuronal activity, and any change in any neuron would define a new brain state. Similarly, mice can walk without whisking, can whisk without walking, can walk and whisk, are all these different behavioral states? And if so, are they all associated with different brain states? Most importantly, in the context of this manuscript, one would expect that different states (brain, behavior) would be associated with at least four potential states of the ACh x NE system (high ACh and High NE, High ACh and Low NE, etc.). However, the reported findings indicate that the two systems are highly synchronized (or at least correlated), and both transiently go on with any change from a passive state to an active state. Therefore, the manuscript describes a rather confined relationship of the neuromodulation systems with the rather rich potential of brain and behavioral states. Of course, this is only my viewpoint, and the authors are not obliged to accept it, but they should recognize that the viewpoint they take for granted is not shared by all and consider acknowledging it in the manuscript.<br /> 2. Most of the manuscript (bar one case) reports nearly identical dynamics of ACh and NE. Is that a principle? What makes these systems behave so similarly? Why have two systems that act nearly the same? Still, if there is a difference, it is the time scale of the ACh compared to the NE. Can the authors explain this difference or speculate what drives it?<br /> 3. Whisker activity explains most strongly the neuromodulators dynamics, but pupil dilation almost does not (in contrast to many previous reports including reports of the same authors). If I am not mistaken, this was nearly ignored in the presentation of the results and the discussion section. Could the author elaborate more on what is the reason for this discrepancy?<br /> 4. I find the question of homogenous vs. heterogenous signaling of both the ACh and NE systems quite important. It is one thing if the two systems just broadcast "one bit" information to the whole brain or if there are neuromodulation signals that are confined in space and are uncorrelated with the global signal. However, the way the analysis of this question is presented in the manuscript is very difficult to follow, and eventually, the take-home message is unclear. The discussion section indicates that the results support that beyond a global synchronized signal, there is a significant amount of heterogeneous activity. I think this question could benefit from further analysis. I suggest trying to demonstrate more specific examples of axonal ROIs where their activity is decorrelated with the global signal, test how consistent this property is (for those ROIs), and find a behavioral parameter that it predicts. Also, in the discussion part, I am missing a discussion of the potential mechanism that allows this heterogeneity. On the one hand, an area may receive NE/ACh innervation from different BF/LC neurons, which are not completely synchronized. But those neurons also innervate other areas, so what is the expected eventual pattern? Also, do the results support neuromodulation control by local interneuron circuits targeting the axons (as is the case with dopaminergic axons in the Basal Ganglia)?<br /> 5. The axonal signal seems to be very similar across the cortex. I am not sure this is technically possible, but given that NE axons are thin and non-myelinated and taking advantage of the mesoscopic scale, could the author find any clue for the propagation of the signal on the rostral to caudal axis?<br /> 6. While the section about local VCIN is consistent with the story, it is somehow a sidetrack and ends the manuscript on the wrong note. I leave it to the authors to decide but recommend them to reconsider if and where to include it. Unfortunately, the figure attached was on a very poor resolution, and I could not look into the details, so I am afraid that I could not review this section properly.

Reviewer #1 (Public Review):

In this study, the authors aim to identify the cell state dynamics and molecular mechanisms underlying melanocyte regeneration in zebrafish. By analyzing thousands of single-cell transcriptomes over regeneration in both wild-type and Kit mutant animals, they provide thorough and convincing evidence of (1) two paths to melanocyte regeneration and (2) that Kit signaling, via the RAS/MAPK pathway, is a key regulator of this process. Finally, the authors suggest that another proliferative subpopulation cells, expressing markers of a separate pigment cell type, constitute an additional population of progenitors with the ability to contribute to melanocytes. The data supporting this claim are not as convincing, and the authors failed to show that these cells did indeed differentiate into melanocytes. Despite the challenges of describing this third cell state, this study offers compelling new findings on the mechanisms of melanocyte regeneration and provides paths forward to understanding why some animals lack this capacity.

The majority of the main conclusions are well supported by the data, but one claim, in particular, should be revisited by the authors.

(1) Provided evidence that the aox5(hi)mitfa(lo) population of cells contributes to melanocyte regeneration is inconclusive and somewhat circumstantial. First, the transcriptional profiles of these cells are much more consistent with the xanthophore lineage. Indeed, xanthophores have been shown to express mitfa (in embryos in Parichy, et al. 2003 (PMID: 10862741), and in post-embryonic cells in Saunders, et al. 2019). Second, while the authors address this possibility in Supplemental figure 7 by showing that interstripe xanthophores fail to divide following melanocyte ablation, they fail to account for the stripe-resident xanthophores/xanthoblasts. The presence and dynamics of aox5+ stripe-resident xanthophores/xanthoblasts are detailed in McMenamin, et al., 2014 (PMID: 25170046) and Eom, et al., 2015 (PMID: 26701906). Without direct evidence that the symmetrically-dividing, aox5+ cells measured in this study do indeed differentiate into melanocytes, it is more likely that these cells are a dividing population of xanthophores/xanthoblasts. The authors should revise their claims accordingly.

Minor revisions

(1) At line 140, it is noted that Xanthophores are pteridine-producing, but they also get their yellow color from carotenoids (especially in adults). This should be noted as well, especially since the authors display the xanthophore marker, scarb1, which plays a key role in xanthophore carotenoid coloration.<br /> [Mapping expression levels onto UMAP space for scarb1 and perhaps other markers of xan, irid, or proliferation would be helpful as a supplement to the dot plot in Fig 1 and could help to clarify the transcriptomic signature of mitfa+ aox5-hi cells and plausibility of the model that they are an McSC population. -Parichy]

(2) The authors should provide the list of genes that comprise their cluster signatures (line 252) as part of the supplementary tables.

(3) The authors should more clearly describe how they performed lineage tracing (line 339). Additionally, for the corresponding figure 4E, the authors should list the number of cells traced. The source data only contains calculated percentages rather than counts for each type of differentiation. My understanding is that the number listed in the figure legend is the number of fish (i.e. n = 4), but this should be clarified as well.<br /> [A supplementary figure of labeled cells is important here with enough context to show that cells can be re-identified unambiguously. Additionally note that "lineage tracing" will typically be assumed to mean single-cell labeling and tracking, so if that is not the case for these experiments it would be preferable to use an alternative descriptor. -Parichy]

(4) Line 321, the authors list the mean regeneration percentages for the kita and kitlga(lf) mutants, but these differences are not significantly different according to Figure 4B. By listing the means (which should be noted), the authors seem to be highlighting the differences but then do not comment on them. The description and integration of this result into the main text should be clarified.

(5) In Figure 6E, the RNA-velocity result is not particularly consistent with the authors' claims. Visually, the arrows seem fairly randomly directed. The data in 6B, showing gene expression associated with the S phase and G2/M phase much more clearly convey the directionality of the loop (S phase, followed by G2/M). I suggest that the authors weaken their claim about the RNA-velocity result or remove it altogether and focus on the cell cycle-related gene expression signatures.

Reviewer #2 (Public Review):

Franz and colleagues set out to understand the mechanisms and cell types that contribute to melanocyte regeneration in the adult skin. Previously, they used genetics and imaging to identify cell populations (progenitors) in the adult skin that they believe contribute to melanocyte regeneration in adult zebrafish (Iyengar et al., 2015). Here, they use scRNA-seq to understand the molecular nature of these cells following melanocyte ablation with the copper chelator, neocuproine. From these studies, they claim to identify three types of progenitors (called melanocyte stem cells, McSCs): cells that give rise directly to differentiated melanocytes and depend on kit signaling; cells that undergo division before becoming fully differentiated; and cells that express high levels of a xanothophore marker (a yellow pigment cell) that also undergo cell division.

Strengths:<br /> The main strength of this work is the generation of scRNA-seq datasets of cells that express a melanocyte marker (mitfa) at multiple time points in adult skin during regeneration. This is an exciting dataset, and unique. The work gives an idea of the complexity of the regeneration process and paves the road for future studies on how McSC lineages contribute to melanoma. It is interesting to see how many of the processes and zebrafish cell types are conserved during evolution. By studying skin-associated melanocyte progenitors in adults, the authors provide insight into mechanisms poorly understood about melanocyte regeneration.

Weaknesses:<br /> (1) Data Interpretation in context: We have concerns regarding the labelling of the cells of interest "stem cells"; we prefer the term the authors themselves use "progenitors" (Iyengar et al., 2015). The authors do not place their work in the context of the wider field, especially with regards to the work on xanthophores and on regenerating melanocytes and adult McSCs in the embryo that contribute to the adult stripe.

(2) Cell type identity: Zebrafish contain another cell type called xanthophores that can also express mitfa and aox5 (Saunders et al., 2019). Indeed, in their supplementary tables, the authors call many of the mitfa+ aox5+ cells "xanthophores" based on their gene expression. There is no evidence here that these cells give rise to melanocytes. In their studies in Figure 7, we think that based on the shape of the cells, they may be looking at dividing xanthophores or unpigmented xanthophore precursors (McMenamin et al., 2014), rather than melanocyte stem cells. We don't know why these cells are dividing, but perhaps the loss of melanocytes in the adult stripe leads to an expansion of xanthophores.

(3) Analysis: The statistical approaches are not always correct, and some choices in the scRNA-seq analysis should be explained and/or revisited.

Reviewer #3 (Public Review):

This manuscript describes McSC states and McSC function during regeneration in zebrafish using both a scRNAseq timecourse and classic zebrafish experimentation, including lineage tracing and mutant lines. Altogether this study provides a more holistic look at pigment regeneration following injury and helps to validate the role of signaling pathways implicated in McSC biology by previous studies. The major question addressed by this manuscript is whether McSC heterogeneity can explain the highly regenerative nature of the zebrafish pigmentary system. The observations reported in this manuscript confirm this view, eloquently using a time course of single-cell transcriptomics for predictive purposes followed up by mechanistic studies to confirm the fate of different McSC subclusters. This study very nicely complements and extends our current understanding of how McSCs function during regeneration and provides novel datasets for further interrogation. Perhaps the most exciting aspect of the data is the identification of a novel marker (aox5) to identify self-renewing McSCs; this tool could be employed to identify these cells and address their potential in the context of expanding these cells for therapeutic purposes or address their contribution as melanoma stem cells. This study will be of general interest to researchers interested in pigment regeneration, stem cell-based therapeutics for pigment disorders, and the basic biology of stem cells and their heterogeneity.

While this paper certainly extends previous observations of McSCs, the idea of McSC heterogeneity is not necessarily novel. In mouse, KIT-dependent and KIT-independent McSC populations have been identified (Ueno 2015) as well as other McSC subpopulations with different potentials (CD34+/-, Joshi 2019). While this manuscript does a much more comprehensive job of describing this heterogeneity, which is fantastic, some of the previous literature on the topic could be better acknowledged and integrated. Despite this criticism, this manuscript provides the most comprehensive look to date at McSC dynamics across the regenerative period and provides ample datasets for secondary analyses to generate/confirm additional hypotheses.

Reviewer #1 (Public Review):

This study addresses the role of the general transcription factor TBP (TATA-binding protein), a subunit of the TFIID complex, in RNA polymerase II transcription. While TBP has been described as a key component of protein complexes involved in transcription by all three RNA polymerases, several previous studies on TBP loss of function and on the function of its TRF2 and TRF3 paralogues have questioned its essential role in RNA polymerase II transcription. This new study uses auxin induced TBP degradation in mouse ES cells to provide strong evidence that its loss does not affect ongoing polymerase II transcription or heat-shock and retinoic acid-induced transcription activation, but severely inhibits polymerase III transcription. The authors coupled TBP degradation with TRF2 knock out to show that it does not account for the residual TBP-independent transcription. Rather the study provides evidence that TFIID can assemble and is recruited to promoters in the absence of TBP.

All together the study provides compelling evidence for TBP-independent polymerase II transcription, but a better characterization of the residual TFIID complex and recruitment of other general transcription factors to promoters would strengthen the conclusions.

Reviewer #2 (Public Review):

The paper is intriguing, but to me, a main weakness is that the imaging experiments are done with overexpressed protein. Another is that the different results for the different subunits of TFIID would indicate that there are multiple forms of TFIID in the nucleus, which no one has observed/proposed before. Otherwise, the experimental data would have to be interpreted in a more nuance way. Additionally, there is no real model of how a TBP-depleted TFIID would recruit Pol II. Do the authors suggest that when TBP is present, it is not playing a role in Pol II transcription, despite being at all promoters? Or that in its absence an alternative mechanism takes over? In the latter case, are they proposing that it is just based on the rest of TFIID? How? The authors do not provide a mechanistic explanation of what is actually happening and how Pol II is being recruited to promoters.

Reviewer #3 (Public Review):

In this study, the authors set out to study the requirement of the TATA binding protein (TBP) in transcription initiation in mESCs. To this end they used an auxin inducible degradation (AID) system. They report that by using the AID-TBP system after auxin degradation, 10-20% of TBP protein is remaining in mESCs. The authors claim that as, the observed 80-90% decrease of TBP levels are not accompanied by global changes in RNA polymerase II (Pol II) chromatin occupancy or nascent mRNA levels, TBP is not required for Pol II transcription. In contrast, they find that under similar TBP-depletion conditions tRNA transcription and Pol III chromatin occupancy were impaired. The authors also asked whether the mouse TBP paralogue, TBPL1 (also called TRF2) could functionally replace TBP, but they find that it does not. From these and additional experiments the authors conclude that redundant mechanisms may exist in which TBP-independent TFIID like complexes may function in Pol II transcription.

The major strengths of this manuscript are the numerous genome-wide investigations, such as many different CUT&Tag experiments, and NET-seq experiments under control and +auxin conditions and their analyses. Weaknesses lie in some experimental setups (i.e. overexpression of Halo-tagged TAFs), mainly in the overinterpretation (or misinterpretation) of the data and in the lack of a fair discussion of the obtained data in comparison to observations described in the literature. As a result, very often the interpretation of data does not fully support the conclusions.<br /> Nevertheless, the findings that 80-90% decrease in cellular TBP levels do not have a major effect on Pol II transcription are interesting, but the manuscript needs some tuning down of many of the authors' very strong conclusions, correcting several weaker points and with a more careful and eventually more interesting Discussion.

Reviewer #1 (Public Review):<br /> <br /> Roberts et al have developed a tool called "XTABLE" for the analysis of publicly available transcriptomic datasets of premalignant lesions (PML) of lung squamous cell carcinoma (LUSC). Detection of PMLs has clinical implications and can aid in the prevention of deaths by LUSC. Hence efforts such as this will be of benefit to the scientific community in better understanding the biology of PMLs.

The authors have curated four studies that have profiled the transcriptomes of PMLs at different stages. While three of them are microarray-based studies, one study has profiled the transcriptome with RNA-seq. XTABLE fetches these datasets and performs analysis in an R shiny app (a graphical user interface). The tool has multiple functionalities to cover a wide range of transcriptomic analyses, including differential expression, signature identification, and immune cell type deconvolution.

The authors have also included three chromosomal instability (CIN) signatures from literature based on gene expression profiles. They showed one of the CIN signatures as a good predictor of progression. However, this signature performed well only in one study. The authors have further utilised the tool XTABLE to identify the signalling pathways in LUSC important for its developmental stages. They found the activation of squamous differentiation and PI3K/Akt pathways to play a role in the transition from low to high-grade PMLs

The authors have developed user-friendly software to analyse publicly available gene expression data from premalignant lesions of lung cancer. This would help researchers to quickly analyse the data and improve our understanding of such lesions. This would pave the way to improve early detection of PMLs to prevent lung cancer.

Strengths:

1. XTABLE is a nicely packaged application that can be used by researchers with very little computational knowledge.<br /> 2. The tool is easy to download and execute. The documentation is extensive both in the article and on the GitLab page.<br /> 3. The tool is user-friendly, and the tabs are intuitively designed for successive steps of analysis of the transcriptome data.<br /> 4. The authors have properly elaborated on the biological interest in investigating PMLs and their clinical significance.

Weaknesses:

The article is focused on the development and the utility of the tool XTABLE. While the tool is nicely developed, the need for a tool focussing only on the investigation of PMLs is not justified. Several shiny apps and online tools exist to perform transcriptomic analysis of published datasets. To list a few examples - i) http://ge-lab.org/idep/ ; ii) http://www.uusmb.unam.mx/ideamex/ ; iii) RNfuzzyApp (Haering et al., 2021); iv) DEGenR (https://doi.org/10.5281/zenodo.4815134); v) TCC-GUI (Su et al., 2019). While some of these are specific to RNA-seq, there are plenty of such shiny apps to perform both RNA-seq and microarray data analysis. Any of these tools could also be used easily for the analysis of the four curated datasets presented in this article. The authors could have elaborated on the availability of other tools for such analysis and provided an explanation of the necessity of XTABLE. Since 3 of the 4 datasets they curated are from microarray technology, another good example of a user-friendly tool is NCBI GEO2R. This is integrated with the NCBI GEO database, and the user doesn't need to download the data or run any tools. iDEP-READS (http://bioinformatics.sdstate.edu/reads/) provide an online user-friendly tool to download and analyse data from publicly available datasets. Another such example is GEO2Enrichr (https://maayanlab.cloud/g2e/). These tools have been designed for non-bioinformatic researchers that don't involve downloading datasets or installing/running other tools.

Secondly, XTABLE doesn't provide a solution to integrate the four datasets incorporated in the tool. One can only analyse one dataset at a time with XTABLE. The differences in terms of methodology and study design within these four datasets have been elaborated on in the article. However, attempts to integrate them were lacking.

The tool also lacks the flexibility for users to add more datasets. This would be helpful when there are more datasets of PMLs available publicly.

Understanding the biology of PML progression would require a multi-omics approach. XTABLE analyses transcriptome data and lacks integration of other omics data. The authors mention the availability of data from whole exome, methylation, etc from the four studies they have selected. However, apart from the CIN scores, they haven't integrated any of the other layers of omics data available.

Lastly, the authors could have elaborated on the limitations of the tool and their analysis in the discussion.

Reviewer #2 (Public Review):

In this manuscript, Roberts et al. present XTABLE, a tool to integrate, visualise and extract new insights from published datasets in the field of preinvasive lung cancer lesions. This approach is critical and to be highly commended; whilst the Cancer Genome Atlas provided many insights into cancer biology it was the development of accessible visualisation tools such as cbioportal that democratised this knowledge and allowed researchers around the world to interrogate their genes and pathways of interest. XTABLE is trying to do this in the preinvasive space and should certainly be commended as such. We are also very impressed by the transparency of the approach; it is quite simple to download and run XTABLE from their Gitlab account, in which all data acquisition and analysis code can be easily interrogated.

We would however strongly advocate deploying XTABLE to a web-accessible server so that researchers without experience in R and git can utilise it. We found it a little buggy running locally and cannot be sure whether this is due to my setup or the code itself. Some issues clearly need development; Progeny analysis brings up a warning "Not working for GSE109743 on the server and not sure why". GSEA analysis does not seem to work at all, raising an error "Length information for genome hg38 and gene ID ensGene is not available". In such relatively complex software, some such errors can be overlooked, as long as the authors have a clear process for responding to them, for example using Gitlab issue reporting. Some acknowledgement that this is an ongoing development would be helpful.

The authors discuss some very important differences between the datasets in the text. Most notably they differ in endpoints and in the presence of laser capture. We would advocate including some warning text within the XTABLE application to explain these. For example, the "persistent/progressive" endpoint used in Beane et al (next biopsy is the same or higher grade) is not the same as the "progressive" endpoint in Teixeira et al (next biopsy is cancer); samples defined as "persistent/progressive" may never progress to cancer. This may not be immediately obvious to a user of XTABLE who wishes to compare progressive and regressive lesions. Similarly, the use of laser capture is important; the authors state that not using laser capture has the advantage of capturing microenvironment signals, but differentiating between intra-lesional and stromal signals is important, as shown in the Mascaux and Pennycuick papers. The authors cannot do much about the different study designs, but as the goal is to make these data more accessible We think some brief description of these issues within the app would help to prevent non-expert users from drawing incorrect conclusions.

The authors themselves illustrate this clearly in their analysis of CIN signatures in progression potential. They observe that there is a much clearer progressive/regressive signal in GSE108124 compared to GSE114489 and GSE109743. This does not seem at all surprising, since the first study used a much stricter definition of progression - these samples are all about to become cancer whereas "progressive" samples in GSE109743 may never become cancer - and are much enriched for CIN signals due to laser capture. Their discussion states "CIN scores as a predictor of progression might be limited to microdissected samples and CIS lesions"; you cannot really claim this when "progression" in the two cohorts has such a different meaning. To their credit, the authors do explain these issues but they really should be clearly spelled out within the app.

We are not sure we agree with their analysis of CDK4/Cyclin-D1 and E2F expression in early lesions. The authors claim these are inhibited by CDKN2A and therefore are markers of CDKN2A loss of function. But these genes are markers of proliferation and can be driven by a range of proliferative processes. Histologically, low-grade metaplasias and dysplasias all represent proliferative epithelium when compared to normal control, but most never become cancer. It is too much of a leap to say that these are influenced by CDKN2A because that gene is inactivated in LUSC; do the authors have any evidence that this gene is altered at the genomic level in low-grade lesions?

Overall this tool is an important step forwards in the field. Whilst we are a little unconvinced by some of their biological interpretations, and the tool itself has a few bugs, this effort to make complex data more accessible will be greatly enabling for researchers and so should be commended. In the future, we would like to see additional molecular data integrated into this app, for example, the whole genome and methylation data mentioned in line 153. However, we think this is an excellent start to combining these datasets.

German academic publishing in Niklas Luhmann's day was dramatically different from the late 20th/early 21st centuries. There was no peer-review and as a result Luhmann didn't have the level of gatekeeping that academics face today which only served to help increase his academic journal publication record. (28:30)

Reviewer #1 (Public Review):

This manuscript builds on data from the same group showing that Lphn2 functions cell-autonomously as a receptor in CA1 pyramidal axons and cell-non-autonomously as a ligand in the neurons of the subiculum. In either case, binding of teneurin-3 to Lphn2 mediates repulsive events, and since different populations of neurons within each region express differing levels of both proteins, this mechanism allows proximal CA1 pyramidal axons to preferentially project to distal subiculum and distal CA1 pyramidal axons to project to proximal subiculum. The authors now ask mechanistic questions about the role of Lphn2 signaling in these wiring processes.

The authors demonstrate that G-protein signaling downstream of Lphn2, which is mediated by the tethered agonist, is necessary for the ability of ectopically expressed Lphn2 to redirect proximal CA1 axons from distal to proximal subiculum. Moreover, the authors show that while autoproteolytic activity of Lphn2 facilitates G-protein signaling, possibly by making the tethered agonist more available for signaling, it is not necessary for axonal mistargeting. Thus, the authors conclude that tethered agonist-dependent G-protein signaling is required for Lphn2-mediated hippocampal neural circuit assembly. Most of the data shown in support of these conclusions are convincing, though I have some concerns about the expression levels and/or effects of the tethered agonist mutants in CA1, which is important since the analyses assume that any defects are in the repulsive interactions described above.

The authors also use heterologous cells to determine that Lphn2 couples to Ga12/13, but not other heteromeric G-proteina-subunits. Within the context of heterologous cells, these experiments are well controlled and exhaustive, as every mutant used in vivo is carefully analyzed. One potential criticism of this work, however, is that perhaps the authors assume too much in simply translating their results in heterologous cells to neurons, especially when one of the most interesting conclusions of this paper (see below) is that Lphn2 signaling is context-dependent. Without further data to confirm the results of these experiments in the neuronal populations studied, these data primarily illustrate possibilities, but don't exclude other possibilities.

Finally, the authors test the role of Lphn2 functioning as a ligand in the subiculum by driving its expression in the normally Lphn2-low dorsal subiculum. As they reported before, this alteration decreases the ability of proximal CA1 axons to project to this area. Interestingly, and in contrast to the role of Lphn2 as a receptor above, neither Lphn2 autoproteolysis nor tethered agonist function are required for this effect.

In summary, this is an interesting paper that addresses timely and pressing issues in the adhesion-GPCR field.

Reviewer #2 (Public Review):

This is an intriguing study investigating the molecular mechanisms of the adhesion G-protein coupled receptor latrophilin-2 control of neural circuit developmental organization. Using the model CA1 to subiculum hippocampal circuit with its spatially segregated axon targeting, the authors experiments find that ectopic Lphn2 expression in CA1 neurons that normally do not express it, leads to axon mistargeting. The authors detail these circuitry alterations with Lphn2 genetic manipulations, finding that axon targeting is dependent on its GPCR signaling, likely through Galpha12/13 coupling.

Strengths: Building off the author's previous studies, the experiments are well designed and analyzed. The advance in this study is finding that Lphn2 expression in CA1 cells that normally do not express impacts its axon targeting. They go on to show compelling data that implicates this mistargeting is dependent on Lphn2 GPCR signaling properties, identified as likely Galpha12/13 dependent.

Weaknesses: The system used is a "misexpression system". By forcing cells with ordinally low levels to overexpress Lphn2, circuitry alterations are observed. While this gain of function assay demonstrates the importance as to why Lphn2 is not expressed in certain cell types, it isn't a physiologically relevant system to investigate Lphn2 dependent circuit development.

To strengthen this study, the following specific points could use addressing:<br /> • While the data is strong, some of the terminology used is unclear, including use of terms "repulsive receptor" and "repulsive ligand". The authors use "repulsive receptor" to describe Lphn2 action for axon targeting, but repulsion and attraction processes are simultaneous. Is Lphn2 really by acting as a repulsive receptor, or alternatively, by acting to shift axon attraction to Lphn2 expressing subiculum neurons?<br /> • For their proposed axon guidance model to work, Lphn2 has to be signaling through G12/13 proteins near the axon growth cone to induce its collapse and retraction. By using Flag-tagged Lphn2 constructs in their assays, this should be visible. Clear Flag-Lphn2 signal is observed in the dendrites of infected cells (Figure1-figure supplement 1; Figure5- figure supplement 1). But does Flag-Lphn2 also localize to the pCA1 axons that are projecting to the subiculum?<br /> • With their previous work, pCA1 to dSub circuit patterning is dependent on Ten3+ to Ten3+ homophilic attraction that exists between the two regions. Its unclear how ectopic Lphn2 is able to override this Ten3+ to Ten3+ connection patterning. Does ectopic Lphn2 outcompete Ten3 function in these neurons? Or alternatively, is Ten3 expression/localization impacted by the presence of ectopic Lphn2?

Reviewer #3 (Public Review):

The function of the nervous system relies on precisely connected neuronal networks. A previous study from the Luo lab reported an important pair of molecular interaction between an adhesion GPCR, latrophilin-2, and teneurin-3 in specifying the connections between CA1 neurons in the hippocampus and the subiculum. This new study continues to investigate the signaling mechanisms, particularly whether the trimeric G proteins are involved. Adhesion GPCRs are in general still under studied, esp in nervous system. This study also used a clever misexpression approach, which provide signaling studies in the in vivo context. The data are of high quality and convincing.

Reviewer #1 (Public Review):

Determination of the biomechanical forces and downstream pathways that direct heart valve morphogenesis is an important area of research. In the current study, potential functions of localized Yap signaling in cardiac valve morphogenesis were examined. Extensive immunostainings were performed for Yap expression, but Yap activation status as indicated by nuclear versus cytoplasmic localization, Yap dephosphorylation, or expression of downstream target genes was not examined. The goal of the work was to determine Yap activation status relative to different mechanical environments, but no biomechanical data on developing heart valves were provided in the study.

There are several major weaknesses that diminish enthusiasm for the study.<br /> 1. The Hippo/Yap pathway activation leads to dephosphorylation of Yap, nuclear localization, and induced expression of downstream target genes. However, there are no data included in the study on Yap nuclear/cytoplasmic ratios, phosphorylation status, or activation of other Hippo pathway mediators. Analysis of Yap expression alone is insufficient to determine activation status since it is widely expressed in multiple cells throughout the valves. The specificity for activated Yap signaling is not apparent from the immunostainings.

2. The specific regionalized biomechanical forces acting on different regions of the valves were not measured directly or clearly compared with Yap activation status. In some cases, it seems that Yap is not present in the nuclei of endothelial cells surrounding the valve leaflets that are subject to different flow forces (Fig 1B) and the main expression is in valve interstitial subpopulations. Thus the data presented do not support differential Yap activation in endothelial cells subject to different fluid forces. There is extensive discussion of different forces acting on the valve leaflets, but the relationship to Yap signaling is not entirely clear.

3. The requirement for Yap signaling in heart valve remodeling as described in the title was not demonstrated through manipulation of Yap activity.

Reviewer #2 (Public Review):

This study by Wang et al. examines changes in YAP expression in embryonic avian cultured explants in response to high and low shear stress, as well as tensile and compressive stress. The authors show that YAP expression is increased in response to low, oscillatory shear stress, as well as high compressive stress conditions. Inhibition of YAP signaling prevents compressive stress-induced increases in circularity, decreased pHH3 expression, and increases VE-cadherin expression. On the other hand, YAP gain of function prevents tensile stress-induced decreases in pHH3 expression and VE-cadherin expansion. It also decreases the strain energy density of embryonic avian valve explants. Finally, using an avian model of left atrial ligation, the authors demonstrate that unloaded regions within the primitive valve structures are associated with increased YAP expression, compared to regions of restricted flow where YAP expression is low. Overall, this study sheds light on the biomechanical regulation of YAP expression in developing valves.

Strengths of the manuscript include:<br /> - Novel insights into the dynamic expression pattern of YAP in valve cell populations during post-EMT stages of embryonic valvulogenesis.<br /> - Identify the positive regulation of YAP expression in response to low, oscillatory shear stress, as well as high compressive stress conditions.<br /> - Identify a link between YAP signaling in regulating stress-induced cell proliferation and valve morphogenesis.<br /> - The inclusion of the atrial left atrial ligation model is innovative, and the data showing distinguishable YAP expression levels between restricted, and non-restricted flow regions is insightful.

This is a descriptive study that focuses on changes in YAP expression following exposure to diverse stress conditions in embryonic avian valve explants. Overall, the study currently lacks mechanistic insights, and conclusions based on data are highly over-interpreted, particularly given that the majority of experimental protocols rely on one method of readout.

Reviewer #3 (Public Review):

In this manuscript, Wang et al. assess the role of wall shear stress and hydrostatic pressure during valve morphogenesis at stages where the valve elongates and takes shape. The authors elegantly demonstrate that shear and pressure have different effects on cell proliferation by modulating YAP signaling. The authors use a combination of in vitro and in vivo approaches to show that YAP signaling is activated by hydrostatic pressure changes and inhibited by wall shear stress.

There are a few elements that would require clarification:

1) The impact of YAP on valve stiffness was unclear to me. How is YAP signaling affecting stiffness? is it through cell proliferation changes? I was unclear about the model put forward:<br /> - Is it cell proliferation (cell proliferation fluidity tissue while non-proliferating tissue is stiffer?)<br /> - Is it through differential gene expression?<br /> This needs clarification.

2) The model proposes an early asymmetric growth of the cushion leading to different shear forces (oscillatory vs unidirectional shear stress). What triggers the initial asymmetry of the cushion shape? is YAP involved?

3) The differential expression of YAP and its correlation to cell proliferation is a little hard to see in the data presented. Drawings highlighting the main areas would help the reader to visualise the results better.

4) The origin of osmotic/hydrostatic pressure in vivo. While shear is clearly dependent upon blood flow, it is less clear that hydrostatic pressure is solely dependent upon blood flow. For example, it has been proposed that ECM accumulation such as hyaluronic acid could modify osmotic pressure (see for example Vignes et al.PMID: 35245444). Could the authors clarify the following questions:<br /> - How blood flow affects osmotic pressure in vivo?<br /> - Is ECM a factor that could affect osmotic pressure in this system?

Reviewer #1 (Public Review):

Farahani et al. describe the generation of pYtags, recombinant RTKs, and reporters, that exploit phosphotyrosine/tandem SH2 interaction pairs from immune-specific signaling proteins to allow spatiotemporal monitoring of the activation of different ligand-binding (EGFR and FGFR1) or ligandless (ERBB2) RTKs in living cells stimulated with high and low-affinity ligands (e.g. EGF and EREG or EPGN respectively in the case of EGFR). The study is well-explained and the experiments are clear and clean. Although the authors expanded tool generation to different RTKs and different cells, the potential utility of the approach is limited because the broad concept that different receptor dimers activate different downstream signalling pathways is already well established. Additionally, the results only examine the temporal kinetics of the receptors rather than their spatial organization, e.g. in different vesicular/endosomal compartments. The study also describes the use of CRISPR-Cas9 to generate a pYtag knock-in EGFR-expressing HEK 293T cell line to avoid complications arising from over-expression. There were significant differences in terms of receptor activation dynamics comparing knock-in and over-expressed cell lines.

The study is technologically innovative, yet the analysis of RTK spatial signalling over time in ligand-stimulated cells should be improved.

Reviewer #2 (Public Review):

The idea of using fluorescently labeled tandem SH2 domains to target tagged RTKs is brilliant and could potentially provide a powerful new way to assess the activation of RTKs in situ and in multiple physiological contexts. Thus, it was disappointing that there was insufficient characterization of the system to be able to interpret the data it generates. Although the paper shows that tagging the EGFR appears to have minimal impact on its biological activity, the readout for receptor kinase activity is % clearance of the fluorescent reporter tag from the cytosol. Such clearance is likely to depend on a variety of different factors, including the ratio of tagged receptors to probe, the number of functional pools in which the probe exists, the exchange rate between these pools, and the affinity of the probes for the tagged receptor. Without determining how each of these factors impacts % clearance, it is difficult to interpret either the dose-response curves or response kinetics.

For example, the difference in activation kinetics between EGFR and ErbB2 is very interesting, but the almost instantaneous rise (Fig S4B) is very surprising. The kinetics of activation of the EGFR have been extensively studied by mass-spectrometry and are generally limited by ligand binding, which has a characteristic time of several minutes, not seconds (pmid: 26929352; pmid: 1975591). Thus, such a response is suggestive of a freely exchanging ZtSH2 reporter pool that is mostly depleted in seconds with the slow secondary kinetics reflecting a slowly exchanging ZtSH2 reporter pool. Alternately, the cells could be accumulating an intracellular pool of activated receptors over time. That the authors are using concentrations of EGF >100-fold physiological levels (pmid: 29268862) further complicates the interpretation of these experiments.

There is also insufficient attention paid to either controlling or measuring important parameters, such as expression levels of tagged receptors or levels of endogenous receptors. 3T3 cells, contrary to the statement of the authors, do not have "negligible" numbers of EGFR: they have ~40K, which is typical for mouse fibroblasts. This is much higher than MCF7 cells, which are frequently used as a model system to study EGFR responses. Yet they do not see transactivation of their ErbB2 construct in 3T3 cells without expressing additional EGFR (Fig. 4C), suggesting low sensitivity of the assay. Conversely, they show a significant response mediated by endogenously tagged EGFR in HEK 293 cells, which are frequently used as an EGFR-negative cell line (PMID: 26368334). This indicates that their assay is extremely sensitive. Which is it? As mentioned above, it likely depends on the expression level and affinity of the different components of their system.

A great advantage of using the EGFR system as a test case for the new system is that thousands of investigations have been performed over the last four decades. This provides a strong foundation for determining whether the new technology is working correctly. For example, the dynamics of EGFR activation and trafficking at the single cell level have been documented in many studies, which show a remarkable consistency (e.g. see pmid: 24259669; pmid: 11408594; pmid: 25650738). Unfortunately, instead of using differences between the new results and previously reported data as a basis for refining their technique, the authors attempt to apply their raw data to address complex questions of EGFR dynamics, with less than satisfactory results.

For example, they attempt to use their technique to understand the basis of different signaling dynamics between EGFR ligands. Rather than being a relatively recent observation, differences in EGFR ligand signaling have been explored for over 30 years (pmcid: PMC361851), and are generally ascribed to differences in trafficking (pmid: 7876195). Based on these observations and resulting mathematical models, novel EGFR ligands have been designed with enhanced potency (pmid: 8195228 , pmid: 9634854 ). All this work was done over 20 years ago. Since then, new natural ligands for the EGFR have been discovered from sequence analysis and differences in their potency have similarly been ascribed to differences in their intracellular trafficking patterns (pmid: 19531065 - cited by the authors). An alternate hypothesis was proposed more recently by Freed et al (2017) as described by the authors, but that is what it is: an alternative hypothesis.

Unfortunately, the model that the authors use to test this hypothesis does not even include endocytosis or receptor trafficking but instead uses variable "scaling" factors to see if the data can fit the dimerization hypothesis. In the supplement, they state that "Since our simulations were run on relatively short time scales (~30 min post-stimulation), we did not consider trafficking and degradation of receptors." However, the half-life of EGFR internalization is generally ~3-4min (pmid: 1975591) and degradation ~1hr, so most of the signal shown in Figure 3 is likely to come from internalized rather than surface-associated ligand-EGFR complexes. A further complication is that internalization rates are strongly influenced by receptor expression levels (pmid: 3262110), which are not controlled for here. Thus, the omission of trafficking in their model is not appropriate. This does not mean that the authors are wrong, it simply means that without validation or calibration, their new technology is not ready to resolve current problems in the field.

Reviewer #3 (Public Review):

Farahani et al. developed a novel biosensor, pYtag, to monitor receptor tyrosine kinase activity using live cell fluorescence microscopy. The approach to the sensor design relies on adding a tyrosine activation motif to a receptor tyrosine kinase of interest which when phosphorylated recruits a fluorescently-tagged SH2 domain protein. The sensor was used to monitor EGFR and ErbB2 activity and characterize their activity in the presence of different ligands, allowing for the kinetics of receptor activity to be determined in live cells with high temporal resolution.

The design, characterization, and verification of the sensor with controls were rigorously done and the sensor appears to be a good approach to monitoring receptor tyrosine kinases. In addition to this, the biological characterization of RTK signaling kinetics allowed for mathematical modeling to determine the dimerization affinity of ligand-bound receptors is the rate-limiting step of receptor tyrosine kinase signaling dynamics. Proving these sensors can be used to monitor biological activities in live cells.

Initial proof of principles of pYtag was demonstrated in cell lines where the tags were expressed, the authors went beyond this and showed the tagging system could be gene edited to endogenous proteins allowing for the function of receptor tyrosine kinase to be measured under physiological concentrations.

Reviewer #1 (Public Review):

In this study, Mitterer et al continue their comprehensive investigation of the mechanisms underlying the biogenesis of the eukaryotic large, or 60S, ribosomal subunit. Specifically, they elucidate the roles that the DEAD-box helicase Spb4 and its interaction partner, Rrp17, play in the maturation of nucleolar 60S precursor particles. Using cell biology approaches, the authors demonstrate that Spb4 and Rrp17 are associated with late-stage nucleolar 60S precursor particles and that depletion of these factors arrests 60S biogenesis at a step just prior to nucleolar exit. Cryo-EM imaging of particles carrying Spb4 and Rrp17 (purified using affinity-tagged Spb4 or Rrp17) yielded high-quality structures of Spb4- and Rrp17-bound 60S precursor particles. The structures provide novel insights into the roles of Spb4 and Rrp17 in the maturation of nucleolar 60S precursor particles. In addition, the structures provide novel insights into the Spb4 function that may be of interest and importance to the function of other DEAD-box helicases. The authors then establish an in vitro maturation assay that, although unlikely to exactly recapitulate the in vivo maturation process, provides additional insights, particularly when coupled to cryo-EM structures of the in vitro-matured 60S particles.

A major strength of this work is the combination of cell biology, structural biology, and biochemistry. The cell biology-directed preparation of Spb4- and Rrp17-bound 60S precursor particles is particularly powerful and results in high-quality structures of these precursors. Another strength of the work is the remarkable view of a DEAD-box helicase in action and the interesting finding that the RecA domains of the helicase are in the open conformation while the helicase is likely bound to ADP-this will be an interesting and important observation for researchers working in the broader DEAD-box helicase field. An additional strength of the work is the development and use of an in vitro maturation assay that allowed further details of the activities of Spb4 and Rrp17 in nucleolar maturation of 60S precursor particles to be investigated and visualized.

A minor weakness of this work is a question about the confidence with which the authors can conclude, using just the structural data presented here, that Spb4 is bound to ADP rather than to ATP or ATP-Pi.

The considerable strengths of this work far outweigh the minor weakness, and I expect that this work will have a significant impact on the field.

Reviewer #2 (Public Review):

Mitterer et al investigated the role of the essential ATPase Spb4 in the maturation of the large ribosomal subunit precursor in the nucleolus using a combination of genetics, biochemistry, and cryo-EM. They suggest that the helicase Spb4 promotes limited RNA strand separation to drive reconfiguration of helices H62/H63/H63a at the base of domain IV of the 25S rRNA. The study also couples an in vitro pre-ribosome maturation assay with cryo-EM visualisation of pre-60S particles to recapitulate a major structural transition that is dependent on the recruitment of the AAA+ ATPase Rea1 to Spb4-bound particles. This structural transition is important as it promotes nucleolar exit of the 60S precursor from the nucleolus following the release of a limited set of ribosome assembly factors including the Ytm1-Erb1 complex together with the helicase Has1. The quality of the new cryo-EM maps provides a wealth of structural detail on the architecture of late pre-60S nucleolar maturation intermediates.

The paper is of high quality and clearly written with appropriately detailed methods. The figures are generally well-presented and informative. A strength of the study is that it provides insight into the function and mechanism of action of a poorly understood class of DEAD-box RNA helicases. The study reports the utility of in vitro pre-ribosome maturation combined with cryo-EM analysis to capture additional ribosome maturation intermediates, an approach that may become more widely adopted in the future among the ribosome synthesis community. The biochemical, genetic, and structural analyses strongly support the proposed mechanism for Spb4 function in reconfiguring helices H62/H63/H63a following induced RNA strand separation prior to the release of the Ytm1-Erb1 complex.

The authors suggest that Spb4 "induces" bending and strand separation of the rRNA at the base of ES27. They also suggest that the C-terminal domain of Spb4 "induces" substrate RNA strand disruption. However, an alternative possibility could be that the rRNA is sampling multiple conformations and that Spb4 stabilises one of these conformers. No direct experimental evidence for "induced" bending and strand separation by Spb4 is provided to support the claims.

The findings in the manuscript are generally consistent with a very recently published study on Spb4 function (Cruz et al., https://doi.org/10.1038/s41594-022-00874-9). However, the authors should cite this work and update the text to take account of this report.

Reviewer #3 (Public Review):

Over the past decade, Cryo-EM analysis of assembling ribosomes has mapped the major intermediates of the pathway. Our understanding of the mechanisms by which ATPases drive the transitions between states has been slower to develop because of the transient nature of these events. Here, the authors use cryo-EM and biochemical and molecular genetic approaches to examine the function of the DEAD-box ATPase Spb4 and the AAA-ATPase Rea1 in RNP remodeling. Spb4 works on the pre-60S in an early nucleolar state. The authors find that Spb4 acts to remodel the three-way junction of H62/H63/H63a at the base of expansion segment ES27. Interestingly, Spb4 appears to interact stably with a folding intermediate in the ADP rather than ATP-bound form. This work represents one of the few cases in which an RNA helicase of ribosome biogenesis has been captured and engaged with its substrate. The authors then show that the addition of the AAA-ATPase Rea1 to Spb4-purified particles results in the release of Ytm1, a known target of Rea1. However, they did not observe an efficient release of Ytm1 when particles were affinity purified via Ytm1, suggesting that the recruitment of Spb4 is important for this step. Cryo-EM analysis of Spb4-particles treated with Rea1 revealed the previously characterized state NE particles but no additional intermediates. Consequently, this analysis of Rea1 is less informative about its function than is their work on Spb4 helicase activity. In general, the data support the authors' conclusions and the data are well presented.

Major points<br /> 1. The Erzberger group has recently published work regarding the function of Spb4. They similarly found that Spb4 is necessary for remodeling the 3-way junction at the base of ES27. Although it was posted to Biorxiv in Feb 2022, it was not formally published until Dec 2022. The authors should cite this work and include a brief discussion comparing conclusions.<br /> 2. L311. The heading "Coupled pre-60S dissociation of the Ytm1-Erb1 complex and RNA helicase Has1" should be changed. Coupling implies a mechanistic interplay. Although the release of Ytm1 and Has1 both depend on Rea1, the data do not support the conclusion of mechanistic coupling. In fact, the authors write in lines 328-329 "Thus, the Rea1-dependent pre-60S release of the Ytm1-Erb1 complex occurs before and independently of Has1..." Independently cannot also imply coupling.<br /> 3. L339-342 Combining data sets for uniform processing was a great idea! This approach should be used more often in cryo-EM analyses of in vitro maturation reactions.<br /> 4. L428 The authors need to amend their comment that this is the first structure of Spb4-bound to the substrate as this has recently been published by the Erzberger group and was first posted as a preprint in early 2022.

Reviewer #1 (Public Review):

A quantitative understanding of the mechanisms underlying VDJ recombination is a prerequisite for a better understanding of adaptive immune repertoire generation. Here, Russel et al. study potential sequence-based factors that may drive VDJ trimming, a mechanism involved in VDJ recombination. This work provides a significant advance in the statistical modeling of immune repertoire generation.

Using a previously-published TCR𝛽 repertoire sequencing data set, the authors designed a probabilistic model of nucleotide trimming that allows the exploration of various mechanistically-interpretable sequence-level features. Using this model, they show that local sequence context and the capacity for sequence-breathing, together, can most accurately predict the trimming probabilities of a given V-gene sequence. Their model suggests that double-stranded DNA needs to be able to "breathe" for trimming to occur and provides evidence of a sequence motif that appears to get preferentially trimmed, independent of breathing. Importantly their findings are not dataset-dependent.

So far, there exists no model for VDJ trimming, a major mechanism in the process of VDJ recombination. With this model, we are now in the position to refine modeling tools for VDJ recombination. Importantly, the model developed by Russel et al. enables exploration of what biological sequence-based factors most contribute to VDJ trimming. To support their conclusions, the authors test their approach on multiple model architectures and AIRR datasets.

While I agree that this is important work, the authors might be overstating the mechanistic insight achieved given that solely statistical inference was used in this work. This is something that requires more discussion and support from the authors.

Reviewer #2 (Public Review):

In this work, the authors did a comprehensive model comparison to find the best predictor of where V genes are trimmed during the V(D)J recombination process, using their DNA sequence alone. This is an important step towards characterizing how the diversity of T-cell receptors and antibodies is generated and to better understanding the function of the enzymes involved in the process, such as Artemis.

The authors find that the best model uses a combination of the sequence-specific position-weight matrix, and the GC content of DNA on both sides of the cutting site, which they relate to the DNA's ability to "breathe." Their conclusions are based on a rigorous comparison of log-likelihoods using independent test data from other loci than the one on which the models were trained. The study also includes myriad tests and controls, increasing confidence in their conclusions.

Reviewer #1 (Public Review):

The study employs state-of-art techniques and model-driven fusion of MEG and 7T to characterize the fine spatiotemporal profiles of object recognition in human brains when stimuli are noisy. By using two models, the recognition and the two-state models, to characterize the representational format, the work demonstrates that the ventral visual pathway is more toward two-state representation while the dorsal visual pathway tends to display the recognition-like profile. Overall it is an interesting work addressing an important question. My major concern is on the two selected models and whether they could be fairly compared to address the question. Moreover, some details need more clarification and statistical support.

Reviewer #2 (Public Review):

This is an excellent study performed by a world-leading research group in the field of the neural mechanisms of perceptual processing. The strengths of this work are the application of the MEG-fMRI fusion approach that links spatial locations in fMRI and time points in MEG and rigorous model-based analyses. The weaknesses may be a lack of a more concise visual illustration of the main findings and an in-depth discussion of some of the findings. The weaknesses are minor and the authors' conclusions are well justified by their data.

Reviewer #1 (Public Review):

Gutiérrez-Martínez et al. present a detailed analysis of Siglec-1 nano-distribution on the surface of dendritic cells (DCs) and the role of Siglec-1 in HIV-1 interactions with DCs.

DCs have been proposed as key cellular intermediates in the transmission of HIV and other viruses. Not only can these cells be crucial for the presentation of virus-derived antigens, but, in tissue culture at least, mature DCs (mDC) have been observed to sequester HIV particles into compartments (virus-containing compartment [VCC]) from which the virus can be subsequently transmitted to CD4+ve T cells through cell-cell contacts often termed virological synapses. This so-called trans-infection mechanism is believed to be important in establishing HIV infection and transmission of the virus to immunological tissues. Although there is considerable evidence for this process, the molecular details of how HIV particles are captured by DCs and transferred to VCC are poorly understood. In recent years Siglec-1 (CD169), a plasma membrane-associated sialic acid-binding lectin expressed on monocytic cells has been implicated in the capture of HIV and other viruses. In this paper, the authors have used super-resolution and other imaging methods to perform a detailed quantitative analysis of the cell surface distribution of Siglec-1 on immature and mature DCs, the relationship between this distribution with actin and regulators of actin polymerization, and then how this impacts on the capture of HIV particles and their association with VCCs.

The principal findings, which for the most part are well supported by the data, suggest that small clusters of Siglec-1, which are restricted in their mobility by formin-associated actin, provide platforms with increased avidity for binding virus particles or large unilamellar vesicles through sialic-acid containing gangliosides. In mDCs at least this binding appears to induce the sequestration of bound particles into VCC-like structures. This is a topical and detailed study that addresses important questions of how viral engagement with cell surface receptors leads to events crucial for viral infection and, potentially, pathogenesis. These types of analyses have only recently become feasible with the implementation of super-resolution imaging and few virus-host cell systems have been examined in detail. Thus, this study has relevance not only to HIV but potentially to many other viruses.

Reviewer #2 (Public Review):

The authors first characterize Siglec-1 clustering on immature and mature DCs and observe that clustering increases in mature DCs. Concomitantly with clustering, the mobility of Siglec-1 reduced. At the cell periphery of mDCs, Siglec-1 was enriched in actin-rich areas. A role for actin, specifically for the formin-nucleated actin was supported using inhibitors. Concomitantly the clustering of Siglec-1 was reduced. The localization of Siglec-1 to actin-rich filopodia was dependent on formin activation and RhoA, ROCK-mediated ERM phosphorylation. With respect to consequences for the binding of HIV particles, forming, and Rho-dependent Siglec-1 nanoclustering, enhanced binding of virus particles indicating that clustering of Siglec-1 provides for better docking sites. On the ligand side, high amounts of GM1 lipids (4%) were needed for liposomes to be captured by Siglec-1, reinforcing the idea of docking sites. Consistent with the important role of actin in the process, time course studies of virus binding to mDCs revealed dramatic changes in the plasma membrane architecture including the emergence of membrane ruffles, shrinkage of the basal membrane, and constriction of the cell membrane where VLPs accumulate on route to the formation of the virus-containing compartment. Overall, the strength of this report is its comprehensive nature, detailed and quantitative imaging analysis, and confirmation of the importance of Siglec-1 clustering (receptor) with liposomes containing the ligand GM1.

Reviewer #3 (Public Review):

In this manuscript, the authors address the mechanism of concentration of HIV-1 particles following interaction with Siglec-1 and define important differences in this process between immature DCs and mature DCs. The methods are largely derived from imaging that is followed by quantitation of nanoclustering of Siglec-1, distance from the center of the cell, and the effects of inhibitors of actin and RhoA pathways. The quantitative imaging approach is a strength and appears quite carefully done. Another strength is the new findings regarding the role of the formin-dependent actin cytoskeletal rearrangements and RhoA activation on clustering and polarization leading to the formation of the virus-containing compartment (VCC). The results are convincing that mature DCs demonstrate more nanoclustering and that formins and RhoA are important in the clustering that occurs of viruses or virus-like particles following capture by Siglec-1. This information should be valuable to the field.

The weaknesses are not in the methods and major conclusions themselves, but there are a number of aspects of the study that could be strengthened. The definition of a VCC here is simply a spot of Siglec-1 that has coalesced with VLPs. A more complete study would include typical VCC markers such as CD81, CD9, and others and would extend the findings to prove that the mechanism invoked actually elicits VCC formation, as opposed to clustering of Siglec-1 and VLPs along the surface of the cell. This study does not establish the mechanism of membrane invagination or tubule formation that occurs with VCC formation, so perhaps it is really describing the initial, surface-related steps of VCC formation but not subsequent internalization events required to form the deeper, vacuole-like VCC.

Nevertheless, this study provides new insights into the initial steps of VCC formation and is provocative regarding how this can be achieved by Siglec-1 in the absence of the need for a cytoplasmic tail. The formin-dependence of VCC formation will be of interest in future studies of HIV uptake and trans-infection events mediated by dendritic cells and macrophages. Some of the findings can be directly translated to the biological context of how VCCs form in HIV-infected macrophages. These will all likely be of substantial interest to those working on HIV and other viruses that are captured by Siglec-1.

Reviewer #1 (Public Review):

In this exciting and well-written manuscript, Alvarez-Buylla and colleagues report a fascinating discovery of an alkaloid-binding protein in the plasma of poison frogs, which may help explain how these animals are able to sequester a diversity of alkaloids with different target sites. This work is a major advance in our knowledge of how poison frogs are able to sequester and even resist such a panoply of alkaloids. Their study also adds to our understanding of how toxic animals resist the effects of their own defenses. Although target site insensitivity and other mechanisms acting to prevent the binding of alkaloids to their targets (often ion channels) are well characterized now in poison frogs, less is known regarding how they regulate the movement of toxins throughout the animal and in blood in particular. In the fugu (pufferfish) a protein binds saxitoxin and tetrodotoxin and in some amphibians possibly the protein saxiphilin has been proposed to be a toxin sponge for saxitoxin. However, little is known about poison frogs in particular and if toxin-binding proteins are involved in their sequestration and auto-resistance mechanisms.

The authors use a clever approach wherein a fluorescently labeled probe of a pumiliotoxin analog (an alkaloid toxin sequestered by some poison frogs) is able to be crosslinked to proteins to which it binds. The authors then use sophisticated mass spectroscopy to identify the proteins and find an outlier 'hit' that is a serpin protein. A competition assay, as well as mutagenesis studies, revealed that this ~50-60 kDa plasma protein is responsible for binding much of the pumiliotoxin and a few other alkaloids known to be sequestered in the in vivo assay, but not nicotine, an alkaloid not sequestered by these frogs.

In general, their results are convincing, their methods and analyses robust and the writing excellent. Their findings represent a major breakthrough in the study of toxin sequestration in poison frogs. Below, a more detailed summary and both major and minor constructive comments are given on the nature of the discoveries and some ways that the manuscript could be improved.

Detailed Summary

The authors functionally characterize a serine-protease inhibitor protein in Oophaga sylvatica frog plasma, which they name O. sylvatica alkaloid-binding globulin (OsABG), that can bind toxic alkaloids. They show that OsABG is the most highly expressed serpin in O. sylvatica liver and that its expression is higher than that of albumin, a major small molecule carrier in vertebrates. Using a toxin photoprobe combined with competitive protein binding assays, their data suggest that OsABG is able to bind specific poison frog toxins including the two most abundant alkaloids in O. sylvatica skin. Their in vitro isolation of toxin-bound OsABG shows that the protein binds most free pumiliotoxin in solution and suggests that OsABG may play an important role in its sequestration. The authors further show that mutations in the binding pocket of OsABG remove its ability to bind toxins and that the binding pocket is structurally similar to that of other vertebrate serpins.

These results are an exciting advance in understanding how poison frogs, which make and use alkaloids as chemical defenses, prevent self-intoxication. The authors provide convincing evidence that OsABG can function as a toxin sponge in O. sylvatica which sets a compelling precedent for future work needed to test the role of OsABG in vivo.

The study could be improved by shifting the focus to O. sylvatica specifically rather than the convergent evolution of sequestration among different dendrobatid species. The reason for this is that most of the results (aside from some of the photoprobe binding results presented in Fig. 1 and Fig. 4) and the proteomics identification of OsABG itself are based on O. sylvatica. It's unclear whether ABG proteins are major toxin sponges in D. tinctorius or E. tricolor since these frogs may contain different toxin cocktails. The competitive binding results suggest that putative ABG proteins in D. tinctorius and E. tricolor have reduced binding affinity at higher toxin concentrations than ABG proteins in O. sylvatica. Although molecular convergence in toxin sponges may be at play in the dendrobatid poison frogs, more work is needed in non-O. sylvatica species to determine the extent of convergence.

Major constructive comments:

Although the protein gels in Fig.1-2 show clearly the role of ABG, a ~50 kDa protein, it's unclear whether transferrin-like proteins, which are ~80 kDa, may also play a role because the gels show proteins between 39-64 kDa (Fig.1). The gel in Fig.2A is specific to one O. sylvatica and extends this range, but the gel does not appear to be labeled accordingly, making it unclear whether other larger proteins could have been detected in addition to ABG. Clarifying this issue would facilitate the interpretation of the results.

There is what seems to be a significant size difference between the O. sylvatica bands and bands from the other toxic frog species, namely D. tinctorius and E. tricolor. Could the photoprobe be binding to other non-ABG proteins of different sizes in different frog species? Given that O. sylvatica bands are bright and this species was the only one subject to proteomics quantification, a possible conclusion may be that the ABG toxin sponge is a lineage-specific adaptation of O. sylvatica rather than a common mechanism of toxin sequestration among multiple independent lineages of poison frogs. It would be helpful if the authors could address this observation of their binding data and the hypothesis flowing from that in the manuscript.

Figure 1B: The species names should be labeled alongside the images in the phylogeny. In addition, please include symbols indicating the number of times toxicity has evolved (for example, once in the ancestors of O. sylvatica and D. tinctorius frogs and once in the ancestors of E. tricolor frogs).

Figure 4B-C: Photoprobe binding results in the presence of epi and nicotine appear to be missing for D. tinctorius and those in the presence of PTX and nicotine are missing for D. tricolor. Adding these results would make for a more complete picture of alkaloid binding by ABG in non-O. sylvatica species.

Using recombinant proteins with mutations at residues forming the binding pocket of O. sylvatica ABG (as inferred from docking simulations), the authors found that all binding pocket mutations disrupted photoprobe binding completely in vitro (L221-222, Fig. 4E). However, there is no information presented on non-binding pocket mutations. Mutations outside of the binding pocket would presumably maintain photoprobe binding - barring any indirect structural changes that might disrupt binding pocket interactions with the photoprobe. This result is important for the conclusion that the binding pocket itself is the sole mediator of toxin interactions. The authors do show that one binding pocket mutation (D383A) results in some degree of photoprobe binding (Fig. 4E) but more detail on the mutations in the binding pocket per se being causal would be helpful.

Please include concentrations in the descriptions of gel lanes in the main figures. The relative concentrations of the photoprobe and other toxins (eg., PTX, DHQ, epi, and nic) are essential for interpreting the competitive binding images. For example, this was done in Fig. S1 (e.g., PB + 10x PTX).

For clarity, the section "OsABG sequesters free PTX in solution with high affinity" could be presented directly after the section titled "Proteomic analysis identifies an alkaloid-binding globulin". The former highlights in vitro experiments confirming the binding affinity of the ABG protein identified in the latter.

Fig. 6E-F should be included as part of Fig. 1 or 2. Although complementary to the RNA sequencing data, these protein results are more closely related to the results in the first two figures which show the degree of competitive binding affinity of PB in the presence of different toxins. The expanded competitive binding results for total skin alkaloids and the two most abundant skin alkaloids from wild samples are most appropriate here.

Reviewer #2 (Public Review):

Poison frogs are able to sequester alkaloids to make themselves toxic or unpalatable to predators. Despite much research, the proteins that accomplish this sequestering role are not well known. Here, biochemical and proteomic analysis identifies a liver-derived alkaloid binding globulin (ABG) as the main alkaloid binding molecule in the blood of poison frogs. The results are solid and address a major void in our understanding of plasma alkaloid transport in frogs. While some additional analysis of ABG mutants would further enhance the interpretations, the study represents an important starting point that suggests specific new roles for serpins in animal ecophysiology.

Reviewer #1 (Public Review):

Elbaz-Hayoun et al. investigate the role of macrophages in the gliotic response of retinal Müller glia and photoreceptor cell death. Monocytes (a precursor of macrophages) were isolated from age-related macular degeneration (AMD) patients. When injected into light-damaged retinas, a reduction in the number of photoreceptors and ERG b-wave strength (evidence of abnormal photoreceptor function) was observed. The authors reasoned that macrophages generated from the injected monocytes might be responsible for the retinal damage. To test this hypothesis, macrophage subtypes were generated from AMD-derived human monocytes and injected into light-damaged mouse eyes. Interstingly, only the human hM2a macrophage subclass mimicked the retinal degeneration of monocyte injection in mouse retinas. Similarly, human M2a (hM2a) cells cultured on mouse retinal explants and even serum-free hM2a culture supernatant were sufficient to induce photoreceptor apoptosis. These effects were not observed with hM1 cells. To identify possible diffusible factors responsible, proteins present in hM2a and hM1 culture supernatants were identified. Nine cytokines were found at higher levels in the hM2a supernatant, and three of these were ligands for the C-C chemokine receptor CCR1. The authors confirmed CCR1 expression in the retina, which was predominantly detected in Müller glia. Importantly, Müller cell expression of CCR1 in the mouse retina was significantly increased following light damage. In contrast, CCR2 and CCR5 levels were unchanged in Müller cells. The increase in CCR1 expression, gliosis, and photoreceptor death was also observed in the rd10 mouse model of retinitis pigmentosa. Inhibiting CCR1 activity in light-damaged eyes using the drug BX471 had impressive effects. Müller activation and photoreceptor cell death were reduced and ERG b-wave levels were partially recovered - clearly indicating a role for CCR1 in retinal degeneration. Additional evidence was provided suggesting that CCR1 activation in M2a macrophages might also play a role in stimulating the movement of other macrophages into the retina and activating retinal microglia, which migrate to the ONL. These data identify a new link between cells of the immune system and those within the retina which contribute to the progression of retinal degeneration.

The data mostly support the conclusions of this paper. However, additional controls need to be added to some experiments.

Concerns:

1) To determine the effect of diseased monocytes on retinal health, light-injured mouse retinas were injected with monocytes isolated from AMD patients (Figure 1 - figure supplement 1). This resulted in a reduction in photoreceptor number and ERG b-wave amplitude. However, the light-injured control eye was injected with PBS only, so no cells were present. The reasoning for using this control was not provided. The appropriate injection control would include monocytes isolated from non-AMD patients. This control should be performed side-by-side with cells from AMD patients.

2) The authors hypothesize, from the experiments presented in Figure 1 - figure supplement 1, that the injected monocytes generated macrophages in the retina, which were responsible for the observed neurotoxicity (Lines 143-145). However, no direct evidence was presented. This idea should be tested in vivo. This could be done by injecting tracer-labeled human AMD-derived monocytes into light-injured mouse retinas. If the authors' hypothesis is true, collected retinas should contain tracer-labeled cells that express macrophage markers. Tracer-labeled M2a macrophage cells should be present since subsequent experiments identify this subclass as being associated with retinal cell death.

3) Photoreceptor number and b-wave amplitudes were measured in light-injured retinas injected with one of four macrophage cell types generated from human AMD-derived monocytes. The authors conclude that only injection of M2a cells reduced photoreceptor number and b-wave amplitudes (Figure 1C, E). This may be true, but it is difficult for the reader to make a conclusion (especially in Fig. 1E) due to the large error bars and five different traces overlapping each other. To make these results easier to interpret, graph control cells with only one experimental sample (cell type) at a time.

4) Most injected macrophages were located in the vitreous. In the case of M2a cells, the authors note that "several of the cells migrated across the retinal layers reaching the subretinal space" (Lines 167,168). One possible explanation for why M0, M1, and M2c macrophages did not induce retinal degeneration is that they did not migrate to the subretinal space and around the optic nerve head. Supplementary figures should be added to demonstrate that this is not the case.

5) Figure 1 - figure supplement 2: Panel A, B cells were stained with CD206 to demonstrate the presence of M2a macrophages (panel B). The authors conclude that panel A contains M1 and panel B contains M2a cells. The lack of CD206 expression illustrates that panel A cells are not M2a macrophages but do not demonstrate they are M1 macrophages. A control using an M1 cell marker is necessary to show that panel A cells are M1 and M1 cells are not detected in M2a cultures.

6) Ex vivo, apoptotic photoreceptor and RPE cells are observed when cultured with M2a macrophages (Figure 2). Do injected M2a cells also induce apoptosis of RPE cells in vivo? This is important to establish that retinal explants are a good model for in vivo experiments.

7) Reactive oxygen species (ROS) production was measured to determine if M2a cell-mediated neurotoxicity was due to oxidative stress. It is concluded that a ROS increase is partly responsible (Line 218). The data do not support this conclusion. ROS was detected in cultured M2a macrophages. More importantly, however, there was no increase in oxidative damage in vivo. The in vivo and cell culture results contradict each other so no conclusion can be made. The lack of in vivo confirmation weakens the argument that ROS drives M2a neurotoxicity. Text suggesting a role for ROS in neurotoxicity should be appropriately edited (Lines including 218, 244, 401,406,481).

8) The authors ask if the photoreceptor cell death is cytokine-mediated. Multiple cytokines were enriched in M2a-conditioned media. Of particular interest were CCR1 ligands MPIF1 and MCP4. The implication is that these two ligands mediate the M2a macrophages to photoreceptor cell death through CCR1. However, there is no attempt to show that either MPIF1 or MCP4 are present in vivo, or are sufficient to induce the retinal response observed. This could be demonstrated by injection of MPIF1 or MCP4. Evidence that either ligand phenocopies M2a macrophage injection would be direct evidence that CCR1 ligands activate the retinal response. Furthermore, co-injection with BX174 should block the effect of these ligands if they work through CCR1.

Reviewer #2 (Public Review):

Macrophages have been demonstrated to play a role in retinal diseases. Macrophage infiltration in melanomas is predictive of increased changes in metastases, and sub-types of macrophages play a role in diverse diseases including macular degeneration and diabetic retinopathy. Here the authors using a light-induced retinal degeneration model and using retinal explants, and peripheral blood-derived monocytes from patients with AMD show that M2a polarized macrophages drive this phenotype. The authors demonstrate this both in vivo and ex vivo and also demonstrate a role for cell-based and secreted factors. The work is fairly specialized and of interest to the vision research community but also has implications for macrophage biology. The data also connects systemic immunity to retinal cell death in diseases such as macular degeneration.

Reviewer #3 (Public Review):

The authors perform an elegant study where they show that intravitreal injection of human monocytes from patients with AMD cause reduced ERG B-wave amplitudes and photoceptor cell loss compared to controls in the photic retinal injury model. Differentiation of human monocytes from patients with AMD into M2a macrophages caused increased photoreceptor cell loss compared to M1 macrophages. Next, the authors show that after co-culturing retinal explants with M1 and M2a human macrophages followed by TUNEL staining, M2 human macrophages had significantly more apoptotic photoreceptor cells than M1 human macrophages. The authors show that human M2a macrophages have significantly more ROS compared to M0 and M1 human macrophages; however, injection of human M2a macrophages did not cause increased oxidative damage compared to control conditions. Using a multiplex cytokine assay of 120 cytokines between human M1 and M2a macrophages-conditioned medium, the authors found increased levels of 9 cytokines, including three HCC-1, MCP-4, and MPIF-1, which are ligands of the C-C chemokine receptor CCR1. Co-staining showed CCR1 expression in Muller cells following photic injury. In the rd10 mouse model of retinal degeneration as well as aged BALB/c mice CCR1 is upregulated in Muller cells. Injection of mice with the CCR1-specific inhibitor BX471 caused increased photoreceptor numbers and B-wave amplitudes in the photic-injury model. Overall the experiments are well performed and of interest to the field.

Joint Public Review:

The authors employ a range of microscopy, biochemical, and virologic techniques to evaluate the efficacy of CRISPR-nuPin to relocalize DNA and the subsequent impact of HSV-1 replication. There are many compelling experiments that utilize solid approaches to HSV-1 transcription, replication, and histone association. The microscopy images are particularly stunning, strongly supported by biochemical evaluation, and consistent with most of the authors' interpretations. Overall, the manuscript presents data that suggests the dCas9-emerin fusion protein can be used to manipulate the nuclear localization of smaller DNA elements like the HSV-1 viral genome. Chromosomal DNA, as tested by telomere targeting, reveal reduced capacity and elongated kinetics for retargeting. Using this system, authors find differing effects on HSV-1 replication based on the timing of sgRNA electroporation post-infection. Further experiments support that the transcriptional effects of either inhibitory or enhancing treatments may be related to chromatin modifications and expression of the viral protein ICP0.

There are many strengths to both the methodology and analysis in this work. That said, there are several areas where a more expansive explanation of methods and data analysis combined with tempered interpretations and language will greatly improve the manuscript.

Reviewer #1 (Public Review):

In this manuscript, the authors set out to identify the energy-generating protein responsible for powering heme transport through the Isd system of Staphylococcus aureus.

The manuscript convincingly demonstrates that FhuC is required for heme iron utilization and presents strong data to implicate FhuC in binding to IsdF. The authors report that IsdF localizes to functional membrane microdomains in S. aureus. These experiments would benefit from controls showing that the DRM fraction contains the functional membrane microdomains and that the fractionation was successful.

The authors also present strong data demonstrating that loss of floA prevents IsdF incorporation into the membrane although these data would also benefit from genetic complementation.

In a surprising result, the authors report that the IsdA protein is not localized in the functional membrane microdomains which are confounding since IsdA is modeled to work in concert with IsdF. These data suggest there is much more to learn regarding the spatial distribution of this transport system.

Finally, the authors report that FMMs are required for heme transport in the related organism Staphylococcus lugdunensis demonstrating the conservation of this localization across the genus.

Taken together, these exciting and significant data reveal how the canonical heme transporter of S. aureus is regionally localized and acquires energy for heme transport across the membrane.

Reviewer #2 (Public Review):

The manuscript entitled 'Functional membrane microdomains and the hydroxamate siderophore transporter ATPase FhuC govern Isd-dependent heme acquisition in Staphylococcus aureus' investigates the heme transport over the bacterial cell membrane. The novelty of this paper is proving the requirement of a highly structured cell envelope that depends on functional membrane microdomains FMMs for bacterial nutrient acquisition. The authors showed that the heme-specific permease (IsdF) is associated with FMMs, to directly interact with the FMM scaffolding protein flotillin A (FloA) and to co-localize with the latter on intact bacterial cells since IsdF needs an appropriate location within the membrane for functionality.

The strengths of the manuscript:

It provides new evidence on the different mechanisms used by S. aureus to acquire iron. These new findings are essential in understanding the way this bacterium survives nutritional immunity and thus can be a target for novel therapeutic approaches.<br /> All the results were based on the necessary molecular techniques that strongly support the conclusions.

The weaknesses of the manuscript:

More details concerning different strategies of iron acquisition should be mentioned in the introduction.<br /> Additional bibliographic literature is needed for explaining what unknown ATPase partially substitutes for the function of FhuC.<br /> More experiments are needed in order to verify the speculations presented in the last part of the manuscript.

Reviewer #1 (Public Review):

Idiosyncratic drug-induced liver injury is a disease that appears to be linked to mitochondrial DNA (mtDNA), but there is a lack of model cell lines for the study of this link. To help address this problem, the authors developed ten cybrid HepG2 cell lines that have had their mitochondrial DNA replaced with the mitochondrial DNA of ten human donors. Analysis of single nucleotide polymorphisms in all of the patients' mtDNA allowed the authors to assign the donors to two haplogroups (H and J) with five patients each. The authors also present the results of several assays (e.g. oxygen consumption, ATP production) performed on all ten cell lines in the absence and presence of five clinically-relevant drugs (or drug metabolites). Significant attention was paid to differences observed between the cell lines in the H and J haplogroups. The work is methodologically and scientifically rigorous, ethically conducted, and objectively presented according to the appropriate community standards.

While I feel that the manuscript will be useful to the research field and is an important step towards improving patient outcomes, I feel that the work lacks a broad interest. Much of the paper is spent discussing small and/or statistically insignificant differences between haplogroups H and J. While some interesting interpretations and suggestions are presented in the discussion, the authors didn't perform follow-up experiments to try to nail down any particular mechanistic insights that would be useful to the broader community. I also didn't feel a strong sense that the paper produced any specific suggestions for how clinical outcomes could be improved. Accordingly, any clear insights that would be interesting to a broad scientific community would probably require follow-up studies. The structure of the paper is also not friendly to a broad audience; the results are presented without interspersed commentary that could help the reader understand the meaning or utility of the results as they are being presented. Accordingly, I often felt unsure about how the results being presented were relevant to solving the broader problem established nicely in the introduction. Finally, it wasn't clear that the generated cell lines were made available for anyone to purchase through a cell bank (perhaps the authors did do this, but I don't recall seeing a mention of it). As these cell lines appear to be the primary output of this work, it seems important to better highlight the extent to which they are being made accessible to the scientific community.

Reviewer #2 (Public Review):

In this work, Ball et al. investigated the possibility to generate a novel set of HepG2 liver cell lines to generate "mitochondrial DNA-personalized" models as novel tools to study idiosyncratic drug-induced liver injury related to mitochondrial variation. This work represents the generation of a comprehensive collection of n=10 HepG2 lines, half reflecting haplogroup H and half reflecting haplogroup J. The authors then assessed their impact on basic mitochondrial function in liver cells. Interestingly, they find a greater respiratory complex activity driven by complex I and II of the haplogroup J lines relative to haplogroup H. Finally, the authors make an attempt at using this novel set of lines to probe the consequential effects of mitochondrial genotype on drug-induced liver toxicity. This work provides an interesting proof-of-concept study and is a starting point towards studying and predicting idiosyncratic drug-induced liver injury in a personalized manner. This technique may be broadly extrapolated to other commonly used liver cell models within the toxicology field.

Strengths:

1) This work presents an exciting initiative to study interindividual variability in idiosyncratic drug-induced liver injury focusing on mitochondrial haplotypes. In further follow-ups, this work could be extended to also represent other different haplogroups to establish a thorough "biobank". The established lines allow for future in-depth characterization and testing of many putative hepatotoxic compounds through a variety of toxicity measures that could shed further light on the impact of mitochondrial DNA variation on (idiosyncratic) drug-induced liver injury.

2) This technique may be broadly extrapolated to other commonly used liver cell lines within the toxicology field (e.g. HepaRG cells or iPSC-derived cells) that are potentially also more metabolically competent. A short discussion on this could be added to the current manuscript.

Weaknesses:

1) The major weakness of the current manuscript is the rather large variation across sample measurements regarding the proof-of-concept experiments to study drug effects (fig. 3-6). This makes much of the data rather hard to interpret and to infer conclusions. As an example, proton leak (fig. 3f/4f) seems to 2-fold increase in the J group even under basal conditions (0 uM flutamide/metabolite), while this is not observed in fig. 2a and this effect seems to be also absent under 0 uM tolcapone (fig. 5f). Unfortunately, the current data do not allow to draw confident conclusions about whether the tested drugs have effects on the mitochondrial respiration of the different haplogroups. This may well be linked to the methods used for measuring mitochondrial activity, but since this is the predominant method needed in the current paper, either increasing the number of experiments (across more lines) or identifying a more rigorous methodological manner to obtain consistencies of experiments would help the authors to make more confident claims about their data.

2) The data on the effects of inhibition of complex I/II activity are not sufficiently convincing to support the claim that haplogroup J is more susceptible to flutamide/metabolite (fig. 6). Both seem to respond rather identical to flutamide or its metabolite, i.e. at higher concentrations complex I/II activity decreases, but with the sole difference that the haplogroups represent different basal activity (not influenced by the drug). Estimating fold changes, for example, for both haplogroups, complex I and II activity decreases ca. 2-fold at the highest concentration of the metabolite (fig. 6c-d), therefore concluding that there is no difference between haplogroup susceptibility unlike the authors claim. It is furthermore unclear what the statistical significance currently represents: it should represent whether at different/increasing concentrations the activity of the complexes significantly differs vs. the previous/basal conditions from the same haplogroup. If it represents (which it seems to be) the significance of the haplogroup J vs. the haplogroup H, it is non-informative as it is obvious that haplogroup J presents with a higher baseline.

3) It would help to mention how many lines per haplogroup H/J were used in the analyses across all figures. This should be clarified, as the error bars for most experiments are rather high and therefore statistical significance is lacking, making data interpretation complex. It could be helpful if the authors present at least for some analyses single plots of data obtained across different lines from the same haplogroup to evaluate the consistency of the effects of the genotypes as supplementary figures. If only 1-2 lines were used per group, it would help to perform additional experiments to assess consistencies across groups.

Reviewer #1 (Public Review):

Utilizing mouse models as well as in-vitro studies, the authors demonstrate that cardiac cell mapping provides novel insights into intercellular communication drivers underlying pathological extracellular matrix remodeling during diabetic myocardial fibrosis.The work provides new perspectives to help understanding the cellular and molecular mechanisms of diabetes-induced cardiac pathology.

Reviewer #2 (Public Review):

In their manuscript, "Single-Cell RNA-seq of Heart Reveals Intercellular Communication Drivers of Myocardial Fibrosis in Diabetic Mice", Wei Li et al. study the pathogenesis of cardiac fibrosis in mouse hearts in response to high-fat-diet/streptozotocin-induced diabetes. They infer cellular interactions from single nucleus RNA-seq data and highlight some ligand-receptor pairs including PDGFs and PDGFRa. They further aim to identify fibroblast subtypes associated with fibrosis and to identify factors driving diabetic myocardial fibrosis.

This study addresses an important problem (cardiac fibrosis as a consequence of diabetes), using single nucleus RNA-seq and several follow-up experiments in a diabetic mouse model. While many of the described findings, including PDGFRa involvement in fibrosis and a Postn positive fibroblast population (reflecting activated fibroblasts), are expected, the most exciting novel insight would come from the Hrc+ fibroblast population and its characterization. However, based on the currently presented data and analysis it is not clear if this is indeed a fibroblast subtype or due to technical factors.

1) A major point of the manuscript is the description of Hrc+ fibroblasts (Fibroblast 3) as profibrogenic in diabetes. However, fibroblast 3 expresses several cardiomyocyte markers Nppa, Ryr2, Ttn alongside Hrc which is described to play a role in Ca2+ handling at the sarcoplasmic reticulum in cardiomyocytes (Fig. 4C) and shows a low correlation with other fibroblast clusters (Fig. 4B). A possible explanation is technical, e.g. if two nuclei (one fibroblast, one cardiomyocyte) were captured together in one droplet (barcode collisions or doublets). Unfortunately, this uncertainty makes interpretation of all following snRNA-seq analyses based on this fibroblast subpopulation impossible.

2) To follow the study and be able to appreciate the data quality, individual sample metadata and UMAPs colored based on a sample and/or condition (diabetes or control) would be helpful. The paper would benefit from an analysis to show if the differences in the number of detected genes are due to the number of nuclei per cluster or if the bigger clusters are really also the ones with the most dramatic changes. Instead of showing expression levels of differentially regulated genes in distinct clusters (Fig1 S2), the differential expression could be displayed with violin plots or heatmaps that illustrate values for both conditions. Clusters that did not reveal any differential expressed genes, e.g. Adipo can be removed. Fig 1F these KEGG enrichments are hard to interpret since they can be confounded by highly expressed cardiomyocyte genes that are detected in all clusters (1B) and thus drive the GO enrichment of e.g. "cardiac muscle contraction" in T cells.

3) The study looks into the pathogenesis of cardiac fibrosis in diabetic mice. The authors show that downregulation of Itgb1 with siRNA (Fig 6I) leads to less fibrosis in diabetic mice. This effect might be expected since Itgb1 is an extracellular matrix-linked gene and might indicate that downregulation could be beneficial. Given this, it is confusing to see the following analysis which links several genetic variants associated with Type 2 Diabetes to Itgb1 (one leading to premature stop) and its ligand. This analysis seems out of place in relation to the remainder of the study which focuses to identify the downstream effects of diabetes on cardiac fibrosis.

Reviewer #3 (Public Review):

The authors attempted to dissect the intercellular mechanisms implicated in the development of diabetic cardiomyopathy. They used one time point to determine the expressional changes in the STZ-high caloric diet model vs non-diabetic. They also attempted to interfere with fibrosis using a PFGFRa antagonist and silencing of Itgb1. Finally, they looked at some variants of the Itgb1 in patients with diabetes to determine a possible association.

Strengths: This is one of the first transcriptomics study a single cell level of the mouse diabetic heart. The study is technically sound.

Weakness: The study is mainly associative. A cause relationship effect is difficult to be extracted. A major problem is that they studied only a single time point at an advanced stage of the disease, therefore it is difficult to determine if the observed changes are epiphenomena. They also use only one diabetic model where STZ was superimposed on the high caloric diet. STZ can cause unspecific effects and more models are generally requested. They also used male mice only while diabetic cardiomyopathy is more prevalent in females. No functional data are provided to study the capacity of treatment to rescue cardiac contractility and diastolic function, which is certainly affected by fibrosis.<br /> The methodological part can help further studies provided the limits indicated above are considered.

Reviewer #1 (Public Review):

Han et al use sophisticated genetic approaches to investigate leptin-responsive neural circuits. Overall, this is an impressive series of studies that provide fairly convincing evidence for a key inhibitory pathway downstream of AGRP neurons. A few data sets require additional validation or explanation.

Reviewer #2 (Public Review):

Using a novel genetic system to conditionally ablate Lepr from Agrp neurons in adults, the authors discovered that leptin-AgRP neuron signaling strongly modulates the DMH and sought to understand the DMH targets and mechanisms of action in the response to AgRP neuron signaling. GABA signaling likely underlies the effects of AgRP neuron-mediated hyperphagia (etc). DMH Mc4R neurons appear to lie downstream of Agrp neurons. GABA in the DMH appears to mediate many of the effects of AgRP neurons on feeding and body weight. Furthermore, Deletion of Lepr from AgRP neurons increases DMH GABA-ARa3, and modulation of this receptor in the DMH alters food intake and the response to leptin.

Unfortunately, there is little quantification or other validation data from many of the systems deployed, and the analysis jumps around a fair amount, without really uniting the results in a way that paints a convincing picture of the final model that they build.

Reviewer #3 (Public Review):

The manuscript by Han et al characterizes a pathway from AgRP(LepR) neurons to DMH(MC4R) neurons that is involved in energy balance control. They use a conditional knockout strategy to show that AgRP(LepR) knockout increases body weight and this effect was reversible by blocking GABA signaling. They also showed that activation of AgRP-DMH projection increases food intake, and highlighted a role for alpha3-GABAA receptor signaling in the DMH for regulating feeding behavior. While these data highlight a potential circuit that modulates feeding, there are concerns about the paper in its current form that diminish enthusiasm. The lack of proper controls in many of the experiments raises doubts about the findings.

Strengths: The authors use new tools to characterize a new circuit for leptin-mediated energy balance control. The conditional knockout has several advantages over previous techniques that are described within the manuscript. Further, the authors use combinations of different techniques (gene knockout, optogenetic manipulation, in vivo activity monitoring) to make observations at multiple levels of analysis.

Weaknesses: Several experiments within the paper have worrisome caveats or lack proper controls, raising concerns about the overall conclusions made.

Reviewer #1 (Public Review):

Demographic inference is a notoriously difficult problem in population genetics, especially for non-model systems in which key population genetic parameters are often unknown and where the reality is always a lot more complex than the model. In this study, Rose et al. provided an elegant solution to these challenges in their analysis of the evolutionary history of human specialization in Ae. aegypti mosquitoes. They first applied state-of-the-art statistical phasing methods to obtain haplotype information in previously published mosquito sequences. Using this phased data, they conducted cross-coalescent and isolation-with-migration analyses, and they innovatively took advantage of a known historical event, i.e., the spread of Ae. aegypti to South America, to infer the key model parameters of generation time and mutation rate. With these parameters, they were able to confirm a previous hypothesis, which suggests that human specialists evolved at the end of the African Humid Period around 5,000 years ago when Ae. aegypti mosquitoes in the Sahel region had to adapt to human-derived water storage as their breeding sites during intense dry seasons. The authors further carried out an ancestry tract length analysis, showing that human specialists have recently introgressed into Ae. aegypti population in West African cities in the past 20-40 years, likely driven by rapid urbanization in these cities.

Given all the complexities and uncertainties in the system, the authors have done outstanding jobs coming up with well-informed research questions and hypotheses, carrying out analyses that are most appropriate to their questions, and presenting their findings in a clear and compelling fashion. Their results reveal the deep connections between mosquito evolution and past climate change as well as human history and demonstrate that future mosquito control strategies should take these important interactions into account, especially in the face of ongoing climate change and urbanization. Methodologically, the analytical approach presented in this paper will be of broad interest to population geneticists working on demographic inference in a diversity of non-model organisms.

In my opinion, the only major aspect that this paper can still benefit from is more explicit and in-depth communication and discussion about the assumptions made in the analyses and the uncertainties of the results. There is currently one short paragraph on this in the discussion section, but I think several other assumptions and sources of uncertainties could be included, and a few of them may benefit from some quantitative sensitivity analyses. To be clear, I don't think that most of these will have a huge impact on the main results, but some explicit clarification from the authors would be useful. Below are some examples:

1. Phasing accuracy: statistical phasing is a relatively new tool for non-model species, and it is unclear from the manuscript how accurate it is given the sample size, sequencing depth, population structure, genetic diversity, and levels of linkage disequilibrium in the study system. If authors would like to inspire broader adoption of this workflow, it would be very helpful if they could also briefly discuss the key characteristics of a study system that could make phasing successful/difficult, and how sensitive cross-coalescent analyses are to phasing accuracy.

2. Estimation of mutation rate and generation time: the estimation of these important parameters is made based on the assumption that they should maximize the overlap between the distribution of estimated migration rate and the number of enslaved people crossing the Atlantic, but how reasonable is this assumption, and how much would the violation of this assumption affect the main result? Particularly, in the MSMC-IM paper (Wang et al. 2020, Fig 2A), even with a simulated clean split scenario, the estimated migration rate would have a wide distribution with a lot of uncertainty on both sides, so I believe that the exact meaning and limitations of such estimated migration rate over time should be clarified. This discussion would also be very helpful to readers who are thinking about using similar methods in their studies. Furthermore, the authors have taken 15 generations per year as their chosen generation time and based their mutation rate estimates on this assumption, but how much will the violation of this assumption affect the result?

3. The effect of selection: all analyses in this paper assume that no selection is at play, and the authors have excluded loci previously found to be under selection from these analyses, but how effective is this? In the ancestry tract length analysis, in particular, the authors have found that the human-specialist ancestry tends to concentrate in key genomic regions and suggested that selection could explain this, but doesn't this mean that excluding known loci under selection was insufficient? If the selection has indeed played an important role at a genome-wide level, how would it affect the main results (qualitatively)?

Reviewer #1 (Public Review):

In this manuscript Sugatha et al. present a comprehensive study on sorting nexin 32 (SNX32) with a wide-spectrum of methodologies and model systems. Authors investigate binding to other sorting nexins involved in the same pathways (SNX1 and SNX4) as well as to its cargo in biochemical and cell-based experiments. They show the importance and explore mechanisms of SNX32 in Transferrin Receptor and Cation Independent Mannose-6-Phosphate Receptor trafficking. Moreover, this work also demonstrates the role of SNX32 in concert with Basigin in neuron differentiation.

Authors with the help of structure modelling and subsequent biochemical experiments find specific residues within the BAR domain of SNX32 that are crucial for heterodimer formation with its interaction partners on endosomal membranes: SNX1 and SNX4. Moreover, this study, by using various microscopy techniques, also demonstrates localization of SNX32 to early endosomes as well as its co-trafficking with Rab11 and Golgi marker. Furthermore, authors with knock-down and rescue experiments investigate the role of SNX32 in Transferrin Receptor and Cation Independent Mannose-6-Phosphate Receptor trafficking. With co-immunoprecipitation they show that the cargo interaction occurs via the conserved stretch in the PX domain and that single amino acid substitution can disrupt this binding. This feature is utilized in a subsequent neuroblastoma cell-based SILAC screen for SNX32 interactome that identifies Basigin (a transmembrane receptor belonging to the superfamily of immunoglobulins) as one of the most prominent interactors in these cells. Finally, authors identify SNX32 and Basigin as crucial factors involved in neurite outgrowth and network formation. Experiments demonstrate that SNX32, but not its homolog SNX6, assists in the surface localization of Basigin where this protein could potentially interact with monocarboxylate transporters crucial for neuro-glial coordination.