Reviewer #1 (Public Review):

Summary:<br /> The authors were trying to achieve that Tgif1 expression is regulated by EAK1/2 and PTH in a time-dependent manner, and its roles in suppressing Pak3 for facilitating osteoblast adhesion. The authors further tried to show that the Tgif1-Pak3 signaling plays a significant role in osteoblast migration to the site of bone repair and bone remodeling.

Strengths:<br /> - In a previous study, it was demonstrated that Tgif1 is a target gene of PTH, and the absence of Tgif1 failed to increase bone mass by PTH treatment (Saito et al., Nat Commun., 2019). In this study, the authors found that Tgif1-Pak3 signaling prompts osteoblast migration through osteoblast adhesion to prompt bone regeneration. This novel finding provides a better understanding of how Tgif1 expression in osteoblasts regulates adherence, spreading, and migration during bone healing and bone remodeling.

- The authors demonstrated that ERK1/2 and PTH regulate Tgif1 expression in a time-dependent manner and its role in suppressing Pak3 through various experimental approaches such as luciferase assay, ChIP assay, and gene silencing. These results contribute to the overall strength of the article.

Weaknesses:<br /> -The authors need to further justify why they focused on Pak3 in the introduction by mentioning its known function for cell adhesion.

-Some results indicated statistically significant but small changes. The authors need to explain in the discussion part why they believe this is the major mechanism or why there may be some other possible mechanisms.

-The study does not include enough in vivo data to claim that this mechanism is crucial for bone healing and bone remodeling in vivo.

Reviewer #2 (Public Review):

Summary:<br /> Bolamperti S. et al. 2023 investigate whether the expression of TG-interacting factor (Tgif1) is essential for osteoblastic cellular activity regarding morphology, adherence, migration/recruitment, and repair. Towards this end, germ-line Tgif1 deletion (Tgif1-/-) mice or male mice lacking expression of Tgif1 in mature osteoblastic and osteocytic cells (Dmp1-Cre+; Tgif1fl/fl) and corresponding controls were studied in physiological, bone anabolic, and bone fracture-repair conditions. Both Tgif1-/- and Dmp1-Cre+; Tgif1fl/fl exhibited decreased osteoblasts on cancellous bone surfaces and adherent to collagen I-coated plates. Tgif1-/- mice exhibit impaired healing in the tibial midshaft fracture model, as indicated by decreased bone volume (BV/Cal.V), osteoid (OS/BS), and low osteoblasts (number and surface). Likewise, both Tgif1-/- and Dmp1-Cre+; Tgif1fl/fl show impaired PTH 1-34, (100 µg/kg, 5x/wk for 3 wks) osteoblast activation in vivo, as detected by increases in quiescent bone surfaces. Mechanistic in vitro studies then utilized primary osteoblasts isolated from Tgif1-/- mice and siRNA Tgif1 knockdown OCY454 cells to further investigate and identify the downstream Tgif1 target driving these osteoblastic impairments. In vitro, Tgif1-/- osteoblastic and Tgif1 knockdown OCY454 cells exhibit decreased migration, abnormal morphology, and decreased focal adhesions/cells. Unexpectantly though, localization assays revealed Tgif1 to primarily concentrate in the nucleus and not to co-localize with focal adhesions (paxillin, talin). Also, the expression of major focal adhesion components (paxillin, talin, FAK, Src, etc.) or the Cdc42 family was not altered by loss of Tgif1 expression. In contrast, PAK3 expression is markedly upregulated by loss of Tgif1. In silico analysis followed by mechanistic molecular assays involving ChIP, siRNA (Tgif1, PAK3), and transfection (rat PAK3 promoter) techniques show that Tgif1 physically binds to a specific site in the PAK3 promoter region. Further, the knockdown of PAK3 rescues the Tgif1-deficient abnormal morphology in OCY454 cells. This is the first study to identify the novel transcriptional repression of PAK3 by Tgif1 as well as the specific Tgif1 binding site within the PAK3 promoter.

Strengths:<br /> This work has a plethora of strengths. The co-authors achieved their aim of eliciting the role of Tgif1 expression in osteoblastic cellular functions (morphology, spreading/attachment, migration). Further, this work is the first to depict the novel mechanism of Tgif1 transcriptional repression of PAK3 by a thorough usage of mechanistic molecular assays (in silico analysis, ChIP, siRNA, transfection etc.). The conclusions are well supported and justified by these findings, as the appropriate controls, sample sizes (statistical power), statistics, and assays were fully utilized.

The claims and conclusions are justified by the data.

Weaknesses:<br /> The discussion section could be expanded with a few sentences regarding limitations to the current study and potential future directions.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript entitled "Association with TFIIIC limits MYCN accumulation in hubs of active promoters and chromatin accumulation of non-phosphorylated RNA polymerase II" the authors examine how the cohesin complex component (and RNA pol III associated factor) TFIIIC interacts with MYCN and controls transcription. They confirm that TFIIIC co-purifies with MYCN, dependent on its amino terminus, as shown in previous work. The authors also find that TFIIIC and MYCN are both found in promoter hubs and suggest that TFIIIC inhibits MYCN's association with these hubs. Finally, the authors indicate that TFIIIC/MYCN alters exosome function, and BRCA1-dependent effects, at MYCN-regulated loci.

Strengths:<br /> The authors utilize multiple experimental approaches to investigate the potential biological and genomic impacts of MYCN association with TFIIIC - the findings are interesting in suggesting that this interaction may limit or otherwise regulate MYC activity.

Weaknesses:<br /> (1) In Figure 1, the authors show that TF3C binds to the amino terminus of MYCN (Myc box I region), as shown previously. The data in Figure 1 B-D support, but do not rigorously confirm a 'direct' interaction because it has not been ruled out that accessory proteins mediating the association may be present in the mixture.

(2) The authors indicate in Figure 2 that TF3C has essentially no effect on MYCN-dependent gene expression and/or transcription elongation. Yet a previous study (PMID: 29262328) associated with several of the same authors concluded that TF3C positively affects transcription elongation. The authors make no attempt to reconcile these disparate results and need to clarify this point.

(3) Figures 2B and C show that unphosphorylated pol2 is TSS-centered, and Ser2-P pol2 occupation is centered beyond the TES. From this data, however, the reader can't tell how much of the phospho-Ser2- pol2 is centered on the TSS. The authors should include overall plots over TSS and TES, and also perhaps the gene-body to allow a better comparison for TSS and TES plotted for both antibodies over the collected gene sets.

(4) The authors see more TF3C at promoters in cells with MYCN (Figure 2F). What are the levels of TF3C in the absence and presence of MYCN?

(5) The finding that TF3C is increased at TSS (Figure 2F) doesn't necessarily indicate that 1) MYCN is recruiting TF3C there, and 2) that this is due to the phosphorylation status of pol2. It could mean many other things. The logic of conflating these 3 points based on the data shown is questionable.

(6) Figure 3A doesn't add much to the paper, as it is overplotted and no relationship is clear, except that Pol2 and MYCN occupy many of the same sites. Perhaps a less complex or different type of plot would allow the interactions to be better visible.

(7) That depletion of TF3C leads to increased promoter hubs may or may not have anything to do with its association with MYCN (Figure 4E). This could be a direct consequence of its known structural function in cohesin complexes, and the MYCN changes as a secondary consequence of this (also see point 4, above).

(8) Depletion of TF3C5 results in a loss of EXOSC5 (exosome) at TSS in the presence and absence of MYCN (Figure 5B). As TF3C5 is a cohesin, could this simply be a consequence of genomic structure changes?

(9) The authors suggest that RNA dynamics are affected by changes in exosome function (RNA degradation, etc). What effect, if any does TF3C depletion have on the overall gene expression profile?

Reviewer #2 (Public Review):

This manuscript reports several interesting observations that invite follow-up. The notion that hubs, and perhaps condensates that may (or may not embrace them) are functionally and physiologically important is an open issue at this time. The authors note that TFIIIC helps to prune extraneous connections from hubs, but do not comment that the connections that are maintained are also reinforced. At the same time only modest changes in gene expression are associated with expanded or decreased connections and changes in bound proteins. One interesting possibility might be that standard methods for assessing expression miss changes in global or background transcription. It seems that the TFIIIC-MYCN-ER connection has features that would help to suppress such background. The results invite a more global consideration of TFIIIC than as primarily RNAPIII/small RNA transcription factor and of MYCN as an E-box dependent transcription factor. The results use state-of-the-art methods to develop interesting new ideas that have the potential to instruct further studies that may reveal new mechanisms of action for TFIIIC and MYCN

Strengths:<br /> Use of a variety of methods to assess the genomic response to increased MYCN in the presence or absence of TFIIIC. Establishes in vitro and in vivo the TFIIIC-MYCN complex.

Weaknesses:<br /> Dynamic inferences are made without kinetic experiments.

Reviewer #3 (Public Review):

Summary:<br /> Vidal et al. investigated how TFIIIC may mediate MYCN effects on transcription. The work builds upon previous reports from the same group where they describe MYCN interactors in neuroblastoma cells (Buchel et al, 2017), which include TFIIIC, and their different roles in MYCN-dependent control of RNA polymerase II function (Herold et al, 2019) (Roeschert et al, 2021) (Papadopoulus et al, 2022). Using baculovirus expression systems, they confirm that MYCN-TFIIIC interaction is direct and likely relevant for neuroblastoma cell proliferation. However, transcriptomics analyses led them to conclude that TFIIC is largely dispensable for MYCN-dependent gene expression. Instead, they propose that TFIIC limits MYCN-mediated promoter-promoter 3D chromatin contacts, which would in turn facilitate the recruitment of the nascent RNA degradation machinery and restrict the accumulation of non-phosphorylated RNA polymerase II at promoters. How this mechanism may impact on MYCN-driven neuroblastoma cell biology remains to be elucidated.

Strengths:<br /> This study presents a nice variety of genomic datasets addressing the specific role of TFIIIC in MYCN-dependent functions. In particular, the technically challenging HiChIP sequencing experiments performed under various conditions provide very useful information about the interplay between MYCN and TFIIIC in the regulation of 3D chromatin contacts. The authors show that MYCN and TFIIIC participate both in unique and overlapping long-range chromatin contacts and that the expression of each of these proteins limits the function of the other. Together, their results suggest a dynamic and interconnected relationship between MYCN and TFIIIC in regulating 3D chromatin contacts.

Weaknesses:<br /> The connection between the three major findings presented in this study regarding the role of TFIIIC in the regulation of MYCN function remains unclear. Specifically, how the TFIIIC-dependent restriction of MYCN localization to promoter hubs enhances the association of factors involved in nascent RNA degradation to prevent the accumulation of inactive RNA polymerase II at promoters is not apparent. As they are currently presented, these findings appear as independent observations. Cross-comparison of the different datasets obtained may provide some insight into addressing this question.

Another concern involves the disparities in RNA polymerase II ChIP-seq results between this study and earlier ones conducted by the same group. In Figure 2, the authors demonstrate that activation of MYCN results in a reduction of non-phosphorylated RNA polymerase II across all expressed genes. This discovery contradicts prior findings obtained using the same methodology, where it was concluded that the expression of MYCN had no significant effect on the chromatin association of hypo-phosphorylated RNA polymerase II (Buchel et al, 2017). In this regard, the choice of the 8WG16 antibody raises concern, as fluctuations in the signal may be attributed to changes in the phosphorylation levels of the C-terminal domain. It remains unclear why the authors decided against using antibodies targeting the N-terminal domain of RNA polymerase II, which are unaffected by phosphorylation and consistently demonstrated a significant signal reduction upon MYCN activation in their previous studies (Buchel et al, 2017) (Herold et al, 2019). Similarly, the authors previously proposed that depletion of TFIIIC5 abrogates the MYCN-dependent increase of Ser2-phosphorylated RNA polymerase II (Buchel et al, 2017), whereas they now show that it has no obvious impact. These aspects need clarification.

Finally, the varied techniques employed to explore the role of TFIIIC in MYCN-dependent recruitment of nascent RNA degradation factors make it challenging to draw definitive conclusions about which factor is affected and which one is not. While conducting ChIPseq experiments for all factors may be beyond the scope of this manuscript, incorporating proximity ligation assays (PLA) or ChIP-qPCR assays with each factor would have enabled a more direct and comprehensive comparison.

Reviewer #1 (Public Review):

Interactions known to be important for melanosome transport include exon F and the globular tail domain (GTD) of MyoVa with Mlph. Motivated by a discrepancy between in vitro and cell culture results regarding necessary interactions for MyoVa to be recruited to the melanosome, the authors used a series of pull-down and pelleting assays experiments to identify an additional interaction that occurs between exon G of MyoVa and Mlph. This interaction is independent of and synergistic with the interaction of Mlph with exon F. However, the interaction of the actin-binding domain of Mlph can occur either with exon G or with the actin filament, but not both simultaneously. These data lead to a modified recruitment model where both exon F and exon G enhance the binding of Mlph to auto-inhibited MyoVa, and then via an unidentified switch (PKA?) the actin-binding domain of Mlph dissociates from MyoVa and interacts with the actin filament to enhance MyoVa processivity.

The only weakness noted is that the authors could have had a more complete story if they pursued whether PKA phosphorylation/dephosphorylation of Mlph is indeed the switch for the actin-binding domain of Mlph to interact with exon G versus the actin filament.

Reviewer #2 (Public Review):

The authors identify a third component in the interaction between myosin Va and melanophilin- an interaction between a 32-residue sequence encoded by exon-g in myosin Va and melanophilin's actin-binding domain. This interaction has implications for how melanosome motility may be regulated.

While this work is largely well done, I believe that additional work would be required to make a more compelling case (e.g. some affinity measurements, necessary controls for the dominant negative experiments).  First, the study provides just one more piece to a well-developed story (the role of exon-F and the GTD in myosin Va: melanophilin (Mlph) interaction), much of which was published 20 years ago by several labs. Second, the study does not demonstrate a physiological significance for their findings other than that exon-G plays an auxiliary role in the binding of myosin Va to Mlph. For example, what dictates the choice between Mlph's actin binding domain (ABD) binding to actin or to exon-G. Is it a PTM or local actin concentration? It is unlikely to be alternative splicing as exon-G is present in all spliced isoforms of myosin Va. And what changes re melanosome dynamics in cells between these two alternatives? Similarly, the paper does not provide any in vitro evidence that binding to exon-G instead of actin effects the processivity of a Rab27a/Myosin Va/Mlph transport complex. For example, if the ABD sticks to exon-G instead of actin, does that block Mlph's ability to promote processivity through its interaction with the actin filament during transport? In summary, given that the authors did not directly test their model either in vitro or in cells, I do not think this story represent a significant conceptual advance.

Reviewer #1 (Public Review):

Summary:<br /> The authors establish a recombinant insect cell expression and purification scheme for the antiviral Dicer complex of C. elegans. In addition to Dicer-1, the complex harbors two additional proteins, the RIG-I-like helicase DRH-1, and the dsRNA-binding protein RDE-4. The authors show that the complex prefers blunt-end dsRNA over dsRNAs that contain overhangs. Furthermore, whereas ATP-dependent dsRNA cleavage only exacerbates regular dsRNA cleavage activity, the presence of RDE-4 is essential to ATP-dependent and ATP-independent dsRNA cleavage. Single-particle cryo-EM studies of the ternary C. elegans Dicer complex reveal that the N-terminal domain of DRH-1 interacts with the helicase domain of DCR-1, thereby relieving its autoinhibitory state. Lastly, the authors show that the ternary complex is able to processively cleave long dsRNA, an activity primarily relying on the helicase activity of DRH-1.

Strengths:<br /> • First thorough biochemical characterization of the antiviral activity of C. elegans Dicer in complex with the RIG-I-like helicase DRH-1 and the dsRNA-binding protein RDE-4.<br /> • Discovery that RDE-4 is essential to dsRNA processing, whereas ATP hydrolysis is not.<br /> • Discovery of an autoinhibitory role of DRH-1's N-terminal domain (in analogy to the CARD domains of RIG-I).<br /> • First structural insights into the ternary complex DCR-1:DRH-1:RDE-4 by cryo-EM to medium resolution.<br /> • Trap experiments reveal that the ternary DCR-1 complex cleaves blunt-ended dsRNA processively. Likely, the helicase domain of DRH-1 is responsible for this processive cleavage.

Weaknesses:<br /> • Cryo-EM Structure of the ternary Dicer-1:DRH-1:RED-4 complex to only medium resolution.<br /> • High-resolution structure of the C-terminal domain of DRH-1 bound to dsRNA does not reveal the mechanism of how blunt-end dsRNA and overhang-containing one are being discriminated.<br /> • The cryo-EM structure of DCR1:DRH-1:RDE-4 in the presence of ATP only reveals the helicase and CTD domains of DRH-1 bound to dsRNA. No information on dsRNA termini recognition is presented. The paragraph seems detached from the general flow of the manuscript.<br /> • The antiviral DCR-1:DRH-1:RDE-4 complex shows largely homologous activities and regulation than Drosophila Dicer-2.

Reviewer #2 (Public Review):

Summary:<br /> To investigate the evolutionary relationship between the RNAi pathway and innate immunity, this study uses biochemistry and structural biology to investigate the trimeric complex of Dicer-1, DRH-1 (a RIGI homologue), and RDE-4, which exists in C. elegans. The three subunits were co-expressed to promote stable purification of the complex. This complex promoted ATP-dependent cleavage of blunt-ended dsRNAs. A detailed kinetic analysis was also carried out to determine the role of each subunit of the trimeric complex in both the specificity and efficiency of cleavage. These studies indicate that RDE-4 is critical for cleavage while DRC-1 is primarily involved in the specificity of the reaction, and DRH-1 promotes ATP hydrolysis. Finally, a moderate density (6-7 angstrom) cryo-EM structure is presented with attempts to position each of the components.

Strengths:<br /> 1. Newly described methods for studying the C. elegans DICER complex.<br /> 2. New structure, albeit only moderate resolution.<br /> 3. Kinetic study of the complex in the presence and absence of individual subunits and mutations, provides detailed insight into the contribution of each subunit.

Weaknesses:<br /> 1. Limited insight due to limited structural resolution.<br /> 2. No attempts to extend findings to other Dicer or RLR systems.

Reviewer #1 (Public Review):

Summary:

The authors have developed and optimized a footprinting assay to monitor the recruitment of mRNAs to a reconstituted translation initiation system. This assay is named Recruitment-Sequencing (Rec-Seq) and enables the analysis of many purified mRNAs in the reconstituted system.

This system possesses the ability to determine how competition occurs between mRNAs for the initiation machinery. This is the first approach using a reconstituted system that enables this important feature, and this is an important advance for the field.

Strengths:

Using purified mRNAs in a fully reconstituted system and being able to monitor start site selection is an important advance. The method enables one to observe changes in mRNA recruitment and start site selection in response to the absence or presence of different initiation components or accessory proteins.

Weaknesses:

Start site fidelity in purified reconstituted systems can be dramatically altered in different buffer conditions. Interpretation of the observed changes to start site selection in mRNAs in the absence or presence of Ded1 using only the one buffer condition used is therefore limited.

Reviewer #1 (Public Review):

Summary:<br /> In their manuscript, Kong Fang et al describe a robust pipeline for the isolation of small extracellular vesicles through a combination of size exclusion chromatography and miniaturized density gradient separation. Subsequently, they prove that the method is reproducible and suitable for small-volume operations while at the same time not compromising the quality of vesicles.

Strengths:<br /> The paper narrates a robust method for purifying high-quality sEVs from small amounts of blood plasma. They also demonstrate that through this approach, they can derive sEVs without compromising the protein composition, integrity of the vesicles, or contamination with other proteins or lipids.

Weaknesses:<br /> The paper is a nice summary of how to enrich sEVs from blood samples. Although well performed and substantiated with data, the paper primarily deals with method development and optimisation.

Reviewer #2 (Public Review):

Summary:<br /> In this work, the authors manage to optimize a simple and rapid protocol using SEC followed by DGCU to isolate sEVs with adequate purity and yield from small volumes of plasma. Isolated fractions containing sEVs using SEC, DGCU, SEC-DGCU, and DGCU-SEC are compared in terms of their yield, purity surface protein profile, and RNA content. Although the combined use of these methodologies has already been evaluated in previous works, the authors manage to adapt them for the use of small volumes of plasma, which allows working in 1.5 mL tubes and reducing the centrifugation time to 2 hours.

The authors finally find that although both the SEC-DGCU and DGCU-SEC combinations achieve isolates with high purity, the SEC-DGCU combination results in higher yields.

This work provides an interesting tool for the rapid obtention of sEVs with sufficient yield and purity for detailed characterization which could be very useful in research and clinical therapy.

Strengths:<br /> -The work is well-written and organized.<br /> -The authors clearly state the problem they want to address, that is, optimizing a method that allows sEV to be isolated from small volumes of plasma.<br /> -Although these methodologies have been tested in previous works, the authors manage to isolate sEVs of high purity and good performance through a simple and fast methodology.<br /> -The characteristics of all isolated fractions are exhaustively analyzed through various state-of-the-art methodologies.<br /> -They present a good interpretation of the results obtained through the methodologies used.

Weaknesses:<br /> -Lack of references that support some of the results obtained.<br /> -Although this work focuses on comparing different techniques and their combinations to find an optimal option, the authors do not use any statistical method that reliably shows the differences between these techniques, except when repeatability is measured.

Reviewer #1 (Public Review):

In recent years, these investigators have been engaged in a debate regarding the classification of the sacral parasympathetic system as "sympathetic" rather than "parasympathetic," based on shared developmental ontogeny of spinal preganglionic neurons. In this current study, these investigators conducted single-cell RNAseq analyses of four groups of autonomic neurons: paravertebral sympathetic neurons (stellate and lumbar train ganglia), prevertebral sympathetic neurons (coeliac-mesenteric ganglia), rostral parasympathetic ganglia (sphenopalatine ganglia), and the caudal pelvic ganglia (containing traditionally recognized sacral "parasympathetic cholinergic neurons," which the investigators sought to challenge in terms of nomenclature). The authors argued that the pelvic ganglionic neurons shared the expression of more genes with sympathetic ganglia, as opposed to parasympathetic ganglia. Additionally, the pelvic neurons did not express a set of genes observed in the rostral parasympathetic sphenopalatine ganglia. Based on these findings, they claimed that the sacral autonomic system should be considered sympathetic rather than parasympathetic.

However, noradrenergic sympathetic neurons and cholinergic neurons, by the virtue of expressing different neurotransmitters, could have distinct roles. It is true that some cholinergic neurons reside in the sympathetic train ganglia as well, such as those innervating the sweat gland and some vascular systems; in this sense, the pelvic ganglia share some features with sympathetic ganglia, except that the pelvic ganglia contain a much higher percentage of cholinergic neurons compared with sympathetic ganglia. It is much simpler and easier to divide the autonomic nervous system into sympathetic neurons that relieve noradrenaline versus parasympathetic neurons that relieve acetylcholine, and these two systems often act in antagonistic manners, even though in some cases, these two systems can work synergistically. As such, it is not justified to claim that "pelvic organs receive no parasympathetic innervation".

Reviewer #2 (Public Review):

Summary:<br /> Recent advances in single cell profiling of gene expression (RNA) permit the analysis of specialized cell types, an approach that has great value in the nervous system which is characterized by prodigious neuronal diversity. The novel data in this study focus primarily on genetic profiling to compare autonomic neurons from ganglia associated with the cranial parasympathetic outflow (sphenopalatine (also known as pteropalatine), the thoraco-lumbar sympathetic outflow (stellate, coeliac) and the sacral parasympathetic outflow (pelvic). Using statistical methods to reduce the dimensionality of the data and map gene expression, the authors provide interesting evidence that cranial parasympathetic and sacral sympathetic ganglia differ from each other and from sympathetic ganglia (Figures 1, S1 - S4). The authors interpret the mapping analysis as evidence that the cranial and sacral outflows differ so that calling them both parasympathetic is unjustified. Based on anatomical localization of markers (Figure 2 ) (mainly transcription factors) the authors show a similarity between the sympathetic and pelvic ganglion. In Figure 3 they present evidence that some pelvic ganglionic neurons are dually innervated by sympathetic preganglionic neurons and sacral preganglionic neurons. These observations are interpreted to mean that the pelvic ganglion is not parasympathetic, but rather a modified sympathetic ganglion - hence the title of the manuscript.

Strengths:<br /> The extensive use of single cell profiling in this work is both interesting and exciting. Although still in its early stages, it holds promise for a deepened understanding of autonomic development and function. As noted in the introduction, this study extends previous work by Professor Brunet and his associates.

Weaknesses:<br /> This work further documents differences between the cranial and sacral parasympathetic outflows that have been known since the time of Langley - 100 years ago. The approach taken by Brunet et al. has focused on late neonatal and early postnatal development, a time when autonomic function is still maturing. In addition, the sphenopalatine and other cranial ganglia develop from placodes and the neural crest, while sympathetic and sacral ganglia develop from the neural crest alone. How then do genetic programs specifying brainstem and spinal development differ and how can this account for kinship that Brunet documents between spinal and sacral ganglia? One feature that seems to set the pelvic ganglion apart is the mixture of 'sympathetic' and 'parasympthetic' ganglion cells and the convergence of preganglionic sympathetic and parasympathetic synapses on individual ganglion cells (Figure 3). This unusual organization has been reported before using microelectrode recordings (see Crowcroft and Szurszewski, J Physiol (1971) and Janig and McLachlan, Physiol Rev (1987)). Anatomical evidence of convergence in the pelvic ganglion has been reported by Keast, Neuroscience (1995). It should also be noted that the anatomy of the pelvic ganglion in male rodents is unique. Unlike other species where the ganglion forms a distributed plexus of mini-ganglia, in male rodents the ganglion coalesces into one structure that is easier to find and study. Interestingly the image in Figure 3A appears to show a clustering of Chat-positive and Th-positive neurons. Does this result from the developmental fusion of mini ganglia having distinct sympathetic and parasympathetic origins. In addition, Brunet et al dismiss the cholinergic and noradrenergic phenotypes as a basis for defining parasympathetic and parasympathetic neurons. However, see the bottom of Figure S4 and further counterarguments in Horn (Clin Auton Res (2018)). What then about neuropeptides, whose expression pattern is incompatible with the revised nomenclature proposed by Brunet et al.? Figure 1B indicates that VIP is expressed by sacral and cranial ganglion cells, but not thoracolumbar ganglion cells. The authors do not mention neuropeptide Y (NPY). The immunocytochemistry literature indicates that NPY is expressed by a large subpopulation of sympathetic neurons but never by sacral or cranial parasympathetic neurons.

The title of this paper is misleading because it implies a conclusion that is not adequately supported by the data and that is difficult for a general reader to parse. Independent assessments by two referees both agreed on title's problematic message. If one can get beyond the title, then the paper does contain data that is of interest. The authors compared single cell gene expression in neurons from the cranial sphenopalatine ganglion, paravertebral chain ganglia (stellate and lumbar), the prevertebral coeliac ganglion and the bladder ganglion. The cranial and pelvic ganglia are parasympathetic, while the paravertebral and prevertebral ganglia are sympathetic. The gene expression data identified differences between the cranial, sympathetic, and pelvic ganglia. Based primarily on this finding the authors concluded that the sacral bladder ganglion is not parasympathetic. Since some genes suggest a kinship between the pelvic and sympathetic neurons, the authors conclude that the pelvic neurons are pelvo-sympathetic - hence the title. This nomenclature does little to improve understanding of the autonomic motor system and it ignores important anatomical and functional properties that underlie existing definitions of the sympathetic and parasympathetic systems. The idea that the cranial and sacral autonomic outflows have some differences is not new (see for example Nilsson, 1983 and Janig, 2022). Since many of the genes identified in the present study are HOX genes and other transcription factors that specify the rostro-caudal axis during development, it is also not surprising that these genes suggest a kinship between sacral parasympathetic neurons and sympathetic neurons, all of which derive from the neural crest and are supplied by the spinal cord. The different profile of cranial parasympathetic neurons is also not surprising given that they derive from a mixture of placodal and neural crest progenitors and are supplied by the brainstem. (see my previous comments for anatomical and functional criteria that further support the existing nomenclature for the sympathetic and parasympathetic motor systems.

Reviewer #1 (Public Review):

This paper aims to address the establishment and maintenance of neural circuitry in the case of a massive loss of neurons. The authors used genetic manipulations to ablate the principal projection neurons, the mitral/tufted cells, in the mouse olfactory bulb. Using diphtheria toxin (Tbx21-Cre:: loxP-DTA line) the authors ablated progressively large numbers of M/T cells postnatally. By injecting diphtheria toxin (DT) into the Tbx21-Cre:: loxP-iDTR line, the authors were able to control the timing of the ablation in the adult stage. Both methods led to the successful elimination of a majority of M/TCs by 4 months of age. The authors made a few interesting observations. First, they found that the initial pruning of the remaining M/T cell primary dendrite was unaffected. However, in adulthood, a significant portion of these cells extended primary dendrites to innervate multiple glomeruli. Moreover, the incoming olfactory sensory neuron (OSN) axons, as examined for those expressing the M72 receptor, showed a divergent innervation pattern as well. The authors conclude that M/T cell density is required to maintain the dendritic structures and the olfactory map. To address the functional consequences of eliminating a large portion of principal neurons, the authors conducted a series of behavioral assays. They found that learned odor discrimination was largely intact. On the other hand, mating and aggression were reduced. The authors concluded that learned behaviors are more resilient than innate ones.

The study is technically sound, and the results are clear-cut. The most striking result is the contrast between the normal dendritic pruning during early development and the expanded dendritic innervation in adulthood. It is a novel discovery that can lead to further investigation of how the single-glomerulus dendritic innervation is maintained. The authors conducted a few experiments to address potential mechanisms, but it is inconclusive, as detailed below. It is also interesting to see that the massive neuronal loss did not severely impact learned odor discrimination. This result, together with previous studies showing nearly normal odor discrimination in the absence of large portions of the olfactory bulb or scrambled innervation patterns, attests to the redundancy and robustness of the sensory system. The discussion should take into account these other studies in a historical context.

Main comments:

1. In previous studies, it has been concluded that dendritic pruning unfolds independently, regardless of the innervation pattern or activity of the OSNs. The new observation bolsters this conclusion by showing that a loss of neighboring M/T cells does not affect the developmental process. A more nuanced discussion comparing the results of these studies would strengthen the paper.

2. The authors propose that a certain density of M/T is required to prevent the divergent innervation of primary dendrites, but the evidence is not sufficient to support this proposal. The experiment with low-dose DT injection to ablate a smaller portion of M/T cells did not change the percentage of cells innervating two or more glomeruli. The authors suggest that a threshold must be met, but this threshold is not determined. It would be possible to adjust the DT injection dose to find this threshold.

3. The authors suggest that neural activity is not required for this plasticity. The evidence was derived primarily from naris occlusion and neuronal silencing using Kir2.1. While the results are consistent with the notion, it is a rather narrow interpretation of how neural activity affects circuit configuration. Perturbation of neural activity also entails an increase in firing. Inducing the activity of the neurons may alter this plasticity. Silencing per se may induce a homeostatic response that expands the neurite innervation pattern to increase synaptic input to compensate for the loss of activity. Thus, further silencing the cells may not reduce multi-glomerular innervation, but an increased activity may.

4. There is a discrepancy between this study and the one by Fujimoto et al. (Developmental Cell; 2023), which shows that not only glutamatergic inputs to the primary dendrite can facilitate pruning of remaining dendrites but also Kir2.1 overexpression can significantly perturb dendritic pruning. This discrepancy is not discussed by the authors.

5. An alternative interpretation of the discrepancy between the apparent normal pruning by p10 and expanded dendritic innervation in adulthood is that there are more cells before P10, when ~25% of M/T cells are present, but at a later date only 1-3% are present. The relationship between the number of M/T cells and single glomerulus innervation has not been explored during postnatal development. It would be important to test this hypothesis.

6. The authors attribute the change in the olfactory map to the loss of M/T cells. Another obvious possibility is that the diffused projection is a response to the change in the olfactory bulb size. With less space to occupy, the axons may be forced to innervate neighboring glomeruli. It is not known how the total number of glomeruli is affected. This question could be addressed by tracking developmental changes in bulb volume and glomerular numbers.

7. The retained ability to discriminate odors upon reinforced training is not surprising in light of a number of earlier studies. For example, Slotnick and colleagues have shown that rats losing ~90% of the OB can retain odor discrimination. Weiss et al have shown that humans without an olfactory bulb can perform normal olfactory tasks. Gronowitz et al have used theoretical prediction and experimental results to demonstrate that perturbing the olfactory map does not have a major impact on olfactory discrimination.<br /> Fleischmann et al have shown that mice with a monoclonal nose can discriminate odors. The authors should discuss their results in these contexts.

8. It should be noted that odor discrimination resulting from reinforcement training does not mean normal olfactory function. It is a highly artificial situation as the animals are overtrained. It should not be used as a measure of the robustness of the olfactory sense. Natural odor discrimination (without training), detection threshold, and innate appetitive/aversive response to certain odors may be affected. These experiments were not conducted.

9. The social behaviors were conducted using relatively coarse measures (vaginal plug and display of aggression). Moreover, these behaviors are most likely affected by the disruption of the AOB mitral cells and have little to do with the dendritic pruning process described in the paper. It is misleading to lump social behaviors with innate responses to odors.

Reviewer #2 (Public Review):

The authors make the interesting observation that the developmental refinement of apical M/T cell dendrites into individual glomeruli proceeds normally even when the majority of neighboring M/T cells are ablated. At later stages, the remaining neurons develop additional dendrites that invade multiple glomeruli ectopically, and similarly, OSN inputs to glomeruli lose projection specificity as well. The authors conclude that the normal density of M/T neurons is not required for developmental refinement, but rather for maintaining specific connectivity in adults.

The observations are indeed quite striking; however, the authors' conclusions are not entirely supported by the data.

1. It is unclear whether the expression of diphtheria toxin that eventually leads to the ablation of the large majority of M/T neurons compromises the cell biology of the remaining ones.

2. The authors interpret the growth of ectopic dendrites later in life as a lack of maintenance of dendrite structure; however, maybe the observed changes reflect actually adaptations that optimize wiring for extremely low numbers of M/T neurons. The finding that olfactory behavior was less affected than predicted supports this interpretation.

3. The number of remaining M/T neurons is much higher at P10 than later. Can the relatively large number of remaining neurons (or their better health status) be the reason that dendrites refine normally at the early developmental stages rather than a (currently unknown) developmental capacity that preserves refinement?

4. While the effect of reduced M/T neuron density on both M/T dendrites and OSN axons is described well, the relationship between both needs to be characterized better: Is one effect preceding the other or do they occur simultaneously? Can one be the consequence of the other?

5. Page 7: the observation that not all neurons develop additional dendrites is not a sign of differences between cell types, it may be purely stochastic.

6. Page 8: the fact that activity blockade did not affect the formation of ectopic dendrites does not suggest that the process is not activity-dependent: both manipulations have the same effect and may just mask each other.

7. It remains unclear how the observed structural changes can explain the behavioral effects.

https://peculiargenres.commons.msu.edu/schedule/

Reviewer #1 (Public Review):

The authors use a combination of crop modeling and field experiments to argue that drought during seedling establishment likely severely impacts the yield of pearl millet, an important but understudied cereal crop and that rapid seedling root elongation could play a major role in mitigating this. They further argue that this trait has a strong genetic basis and that major polymorphisms in candidate genes can be identified using standard methods from modern genetics and genomics. Finally, they use homology with the model plant Arabidopsis thaliana to argue that the function of one putatively causal gene is to regulate root cell elongation.

The major strength of this paper is that it convincingly demonstrates how modern methods from plant breeding and model organisms can be combined to address questions of great practical importance in important but poorly understood crops. The notion that it is possible to connect single-locus polymorphism and cellular biology to drought tolerance and crop yield in pearl millet is not a trivial one.

The weakness is obvious: while the argument made is convincing, it must be recognized that the strength of the evidence is by no means of the level expected in a model organism. Conclusions could easily be wrong, and there is no direct evidence that regulatory variation in PgGRXC9 leads to higher crop yield via cell elongation and seedling drought tolerance. However, generating such evidence in a poorly studied crop would be a monumental undertaking, and should probably not be the priority of people working on pearl millet!

The utility of this work is that it suggests that it is practicable to gain valuable insight into crop adaptation by clever use of modern methods from a variety of sources.

Reviewer #2 (Public Review):

Carla de la Fuente et al., utilize a diversity of approaches to understand which plant traits contribute to the stress resilience of pearl millet in the Sahelian desert environment. By comparing data resulting from crop modeling of pearl millet growth and meteorological data from a span of 20 years, the authors clearly determined that early season drought resilience is contributed by accelerated growth of the seedling primary root, which confirms a hypothesis generated in a previous study, Passot et al., 2016. To determine the genetic basis for this trait, they performed a combination of GWAS, QTL analysis, and RNA sequencing and identified a previously unannotated coding sequence of a glutaredoxin C9-like protein, PgGRXC9, as the strongest candidate. Phenotypic analysis using a mutant of the closest Arabidopsis homolog AtROXY19 suggests the broad conservation of this pathway. Comparisons between the transcript of PgGRXC9 by in situ hybridization (this work) and AtROXY19 pattern expression (Belin et al., 2014) support the hypothesis that this pathway acts in the elongation zone of the root. Additional analysis of cell production and elongation rates in root apex in both pearl millet and A. thaliana suggests that PgGRXC9 specifically regulates primary root through the promotion of cell elongation. While several studies have established the connection between redox status of cells and root growth, the current study represents an important contribution to the field because of the agricultural importance of the plant studied, and the connection made between this developmental trait and stress resilience in a specific and stressful environmental context of the Sahelian desert.

Reviewer #1 (Public Review):

Trenker et al. report cryo-EM structures of HER4/HER2 heterodimers and HER4 homodimers bound to Neuregulin-1β (Nrg1β) and Betacellulin (BTC). As observed for prior cryo-EM structures of full-length or near full-length HER-family receptors only the extracellular regions are visualized, presumably owing to flexibility in the relative orientation of extra- and intra-cellular regions. The authors observe no appreciable differences between Nrg1β and BTC bound heterodimers, both ligands, in this case being high-affinity ligands, and modest "scissor-like" differences in the subunit relationships in HER4 homodimers with Nrg1β and BTC bound.

The authors also show that, as they showed for HER3, the HER4 dimerization arm is not indispensable for forming heterodimers with HER2 despite the HER4 dimerization arm forming a more canonical interaction with HER2. Perhaps most interestingly, the authors observe glycan interactions that appear to stabilize intra- and inter-subunit interactions in HER4 homodimers but that inter-subunit glycans are not present in HER2/HER4 heterodimers. The authors speculate that these glycan interactions may contribute to the apparent propensity of HER4 to homodimerize vs. heterodimerize with HER2.

I realize that an important role of reviewers is to provide authors with informed and critical comments, but I found this manuscript a well-written, thoughtful, and important contribution. My only note is that I am not an electron microscopist so have assumed the microscopy has been carried out expertly and rely on other reviewers to vet structure determinations.

Reviewer #1 (Public Review):

Summary:<br /> The paper is an attempt to explain a geographic paradox between infection prevalence and antimalarial resistance emergence. The authors developed a compartmental model that importantly contains antigenic strain diversity and in turn antigen-specific immunity. They find a negative correlation between parasite prevalence and the frequency of resistance emergence and validate this result using empirical data of chloroquine-resistance. Overall, the authors conclude that strain diversity is a key player in explaining observed patterns of resistance evolution across different geographic regions.

The authors pose and address the following specific questions:<br /> 1. Does strain diversity modulate the equilibrium resistance frequency given different transmission intensities?<br /> 2. Does strain diversity modulate the equilibrium resistance frequency and its changes following drug withdrawal?<br /> 3. Does the model explain biogeographic patterns of drug resistance evolution?

Strengths:<br /> The model built by the authors is novel. As emphasized in the manuscript, many factors (e.g., drug usage, vectorial capacity, population immunity) have been explored in models attempting to explain resistance emergence, but strain diversity (and strain specific immunity) has not been explicitly included and thus explored. This is an interesting oversight in previous models, given the vast antigenic diversity of Plasmodium falciparum (the most common human malaria parasite) and its potential to "drive key differences in epidemiological features".

The model also accounts for multiple infections, which is a key feature of malarial infections, with individuals often infected with either multiple Plasmodium species or multiple strains of the same species. Accounting for multiple infections is critical when considering resistance emergence, as with multiple infections there is within-host competition which will mediate the fitness of resistant genotypes. Overall, the model is an interesting combination of a classic epidemiological model (e.g., SIR) and a population genetics model.

In terms of major model innovations, the model also directly links selection pressure via drug administration with local transmission dynamics. This is accomplished by the interaction between strain-specific immunity, generalized immunity and host immune response.

Weaknesses:<br /> The authors emphasize several model limitations, including the specification of resistance by a single locus (thus not addressing the importance of recombination should resistance be specified by more than one locus); the assumption that parasites are independently and randomly distributed among hosts (contrary to empirical evidence); and the assumption of a random association between the resistant genotype and antigenic diversity. However, each of these limitations are addressed in the discussion.

Did the authors achieve their goals? Did the results support their conclusion?<br /> Returning to the questions posed by the authors:<br /> 1. Does strain diversity modulate the equilibrium resistance frequency given different transmission intensities? Yes. The authors demonstrate a negative relationship between prevalence/strain diversity and resistance frequency (Figure 2).

2. Does strain diversity modulate the equilibrium resistance frequency and its changes following drug withdrawal? Yes. The authors find that, under resistance invasion and some level of drug treatment, resistance frequency decreased with the number of strains (Figure 4). The authors also find that lower strain diversity results in a slower decline in resistant genotypes after drug withdrawal and higher equilibrium resistance frequency (Figure 6).

3. Does the model explain biogeographic patterns of drug resistance evolution? Yes. The authors find that their full model (which includes strain-specific immunity) produces the empirically observed negative relationship between resistance and prevalence/strain diversity, while a model only incorporating generalised immunity does not (Figure 8).

Utility of work to others and relevance within and beyond the field?<br /> This work is important because antimalarial drug resistance has been an ongoing issue of concern for much of the 20th century and now 21st century. Further, this resistance emergence is not equitably distributed across biogeographic regions, with South America and Southeast Asia experiencing much of the burden of this resistance emergence. Not only can widespread resistant strains be traced back to these two relatively low-transmission regions, but these strains remain at high frequency even after drug treatment ceases.

Reviewer #2 (Public Review):

Summary:<br /> The evolution of resistance to antimalarial drugs follows a seemingly counterintuitive pattern, in which resistant strains typically originate in regions where malaria prevalence is relatively low. Previous investigations have suggested that frequent exposures in high-prevalence regions produce high levels of partial immunity in the host population, leading to subclinical infections that go untreated. These subclinical infections serve as refuges for sensitive strains, maintaining them in the population. Prior investigations have supported this hypothesis; however, many of them excluded important dynamics, and the results cannot be generalized. The authors have taken a novel approach using a deterministic model that includes both general and adaptive immunity. They find that high levels of population immunity produce refuges, maintaining the sensitive strains and allowing them to outcompete resistant strains. While general population immunity contributed, adaptive immunity is key to reproducing empirical patterns. These results are robust across a range of fitness costs, treatment rates, and resistance efficacies. Given sufficient antigenic diversity and high transmission, sensitive parasites remain in circulation even when there is no cost to resistance. This work demonstrates that future investigations cannot overlook adaptive immunity and antigenic diversity.

Strengths:<br /> Overall, this is a very nice paper that makes a significant contribution to the field. It is well-framed within the body of literature and achieves its goal of providing a generalizable, unifying explanation for otherwise disparate investigations. The model is innovative. The approach is elegant and rigorous, with results that are supported across a broad range of parameters when considered within an equilibrium setting. Their exploration of geographical patterns of resistance makes the results of their simulations even more compelling. As such, this work will likely serve as a foundation for many future investigations.

Weaknesses:

Although the authors model resistance invasion, it does not align with empirical observations of the spread of resistance. For example, Plasmodium's mutation rate and population size mean that mutations providing chloroquine resistance should arise repeatedly even within a single infection. Nevertheless, Africa remained free of chloroquine resistant strains until a lineage was introduced from Asia. Upon introduction, it spread across the continent within ten years. The difference between the fate of chloroquine resistance originating in Africa versus chloroquine resistance originating in Asia cannot be attributed to changes in population immunity and treatment.

The source of this disparity may be in part attributable to the use of a deterministic, compartmental model, as the authors mention in the discussion. Strains are not explicitly modeled. This means that in terms of the distribution of strain diversity, the resistant and the sensitive compartments are identical, and the locus determining resistance is equally distributed across all strain backgrounds. However, substantial rates of linkage disequilibrium and clonal reproduction are found even in high transmission settings. The model assumptions may be met at equilibrium, but are not appropriate for most scenarios involving the invasion of a rare mutation.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Janssens et al. addressed the challenge of mapping the location of transcriptionally unique cell types identified by single nuclei sequencing (snRNA-seq) data available through the Fly Cell Atlas. They identified 100 transcripts for head samples and 50 transcripts for fly body samples allowing the identification of every unique cell type discovered through the Fly Cell Atlas. To map all of these cell types, the authors divided the fly body into head and body samples and used the Molecular Cartography (Resolve Biosciences) method to visualize these transcripts. This approach allowed them to build spatial tissue atlases of the fly head and body, to identify the location of previously unknown cell types and the subcellular localization of different transcripts. By combining snRNA-seq data from the Fly Cell Atlas with their spatially resolved transcriptomics (SRT) data, they demonstrated an automated cell type annotation strategy to identify unknown clusters and infer their location in the fly body. This manuscript constitutes a proof-of-principle study to map the location of the cells identified by ever-growing single-cell transcriptomic datasets generated by others.

Strengths:<br /> The authors used the Molecular Cartography (Resolve Biosciences) method to visualize 100 transcripts for head samples and 50 transcripts for fly body samples in high resolution. This method achieves high resolution by multiplexing a large number of transcript visualization steps and allows the authors to map the location of unique cell types identified by the Fly Cell Atlas.

Weaknesses:<br /> Combining single-nuclei sequencing (snRNA-seq) data with spatially resolved transcriptomics (SRT) data is challenging, and the methods used by the authors in this study cannot reliably distinguish between cells, especially in brain regions where the processes of different neurons are clustered, such as in neuropils. This means that a grid that the authors mark as a unique cell may actually be composed of processes from multiple cells.

Reviewer #2 (Public Review):

Summary:<br /> The landmark publication of the "Fly Atlas" in 2022 provided a single cell/nuclear transcriptomic dataset from 15 individually dissected tissues, the entire head, and the body of male and female flies. These data led to the annotation of more than 250 cell types. While certainly a powerful and data-rich approach, a significant step forward relies on mapping these data back to the organism in time and space. The goal of this manuscript is to map 150 transcripts defined by the Fly Atlas by FISH and in doing so, provide, for the first time, a spatial transcriptomic dataset of the adult fly. Using this approach (Molecular Cartography with Resolve Biosciences), the authors, furthermore, distinguish different RNA localizations within a cell type. In addition, they seek to use this approach to define previously unannotated clusters found in the Fly Atlas. As a resource for the community at large interested in the computational aspects of their pipeline, the authors compare the strengths and weaknesses of their approach to others currently being performed in the field.

Strengths:<br /> 1. The authors use Resolve Biosciences and a novel bioinformatics approach to generate a FISH-based spatial transcriptomics map. To achieve this map, they selected 150 genes (50 body; 100 head) that were highly expressed in the single nuclear RNA sequencing dataset and were used in the 2022 paper to annotate specific cell types; moreover, the authors chose several highly expressed genes characteristic of unannotated cell types. Together, the approach and generated data are important next steps in translating the transcriptomic data to spatial data in the organism.<br /> 2. Working with Resolve, the authors developed a relatively high throughput approach to analyze the location of transcripts in Drosophila adults. This approach confirmed the identification of particular cell types suggested by the FlyAtlas as well as revealed interesting subcellular locations of the transcripts within the cell/tissue type. In addition, the authors used co-expression of different RNAs to unbiasedly identify "new cell types". This pipeline and data provide a roadmap for additional analyses of other time points, female flies, specific mutants, etc.<br /> 3. The authors show that their approach reveals interesting patterns of mRNA distribution (e.g alpha- and beta-Trypsin in apical and basal regions of gut enterocytes or striped patterns of different sarcomeric proteins in body muscle). These observations are novel and reveal unexpected patterns. Likewise, the authors use their more extensive head database to identify the location of cells in the brain. They report the resolution of 23 clusters suggested by the single-cell sequencing data, given their unsupervised clustering approach. This identification supports the use of spatial cell transcriptomics to characterize cell types (or cell states).<br /> 4. Lastly, the authors compare three different approaches --- their own described in this manuscript, Tangram, and SpaGE - which allow integration of single cell/nuclear RNA-seq data with spatial localization FISH. This was a very helpful section as the authors compared the advantages and disadvantages (including practical issues, like computational time).

Weaknesses:<br /> 1. Experimental setup. It is not clear how many and, for some of the data, the sex of the flies that were analyzed. It appears that for the body data, only one male was analyzed. For the heads, methods say male and female heads, but nothing is annotated in the figures. As such, it remains unclear how robust these data are, given such a limited sample from one sex. As such, the claims of a spatial atlas of the entire fly body and its head ("a rosetta stone") are overstated. Also, the authors should clearly state in the main text and figure legends the sex, the age, how many flies, and how many replicates contributed to the data presented (not just the methods). What also adds to the confusion is the use of "n" in para 2 of the results. " ... we performed coronal sections at different depths in the head (n=13)..." 13 sections in total from 1 head or sections from 13 heads? Based on the body and what is shown in the figure, one assumes 13 sections from one head. Please clarify.<br /> 2. Probes selected: Information from the methods section should be put into the main text so that it is clear what and why the gene lists were selected. The current main text is confusing. If the authors want others to use their approach, then some testing or, at the very least, some discussion of lower expressed genes should be added. How useful will this approach be if only highly expressed genes can be resolved? In addition, while it is understood that the company has a propriety design algorithm for the probes, the authors should comment on whether the probes for individual genes detect all isoforms or subsets (exons and introns?), given the high level of splicing in tissues such as muscle.<br /> 3. Imaging: it isn't clear from the text whether the repeated rounds of imaging impacted data collection. In many of what appear to be "stitched" images, there are gradients of signal (eg, figure 2F); please comment. Also, since this a new technique, could a before and after comparison of the original images and the segmented images be shown in the supplemental data so that the reader can better appreciate how the authors assessed/chose/thresholded their data? More discussion of the accuracy of spot detection would be helpful.<br /> 4. The authors comment on how many RNAs they detected (first paragraph of results). How do these numbers compare to the total mRNA present as detected by single-cell or single-nuclear sequencing?<br /> 5. Using this higher throughput method of spatial transcriptomics, the authors discern different cell types and different localization patterns within a tissue/cell type.<br /> a. The authors should comment on the resolution provided by this approach, in terms of the detection of populations of mRNAs detected by low throughput methods, for example, in glia, motor neuron axons, and trachea that populate muscle tissue. Are these found in the images? Please show.<br /> b. The authors show interesting localization patterns in muscle tissue for different sarcomere protein-coding mRNAs, including enrichment of sls in muscle nuclei located near the muscle-tendon attachment sites. As this high throughput approach is newly being applied to the adult fly, it would increase confidence in these data, if the authors would confirm these data using a low throughput FISH technique. For example, do the authors detect such alternating "stripes" ( Act 88F, TpnC4, and Mhc) or enriched localization (sls) using FISH that doesn't rely on the repeated colorization, imaging, decolorization of the probes?<br /> 6. The authors developed an unbiased method to identify "new cell types" which relies on co-expression of different transcripts. Are these new cell types or a cell state? While expression is a helpful first step, without any functional data, the significance of what the authors found is diminished. The authors need to soften their statements.

Appraisal:<br /> The authors' goal is to map single cell/nuclear RNAseq data described in the 2022 Fly Atlas paper spatially within an organism to achieve a spatial transcriptomic map of the adult fly; no doubt, this is a critical next step in our use of 'omics approaches. While this manuscript does the hard work of trying to take this next step, including developing and testing a new pipeline for high throughput FISH and its analysis, it falls short, in its present form, in achieving this goal. The authors discuss creating a robust spatial map, based on one male fly. Moreover, they do not reveal principles of mRNA localization, as stated in the abstract; they show us patterns, but nothing about the logic or function of these patterns. This same criticism can be said of the identification of "new cell types, just based on RNA colocalization. In both cases (mRNA subcellular localization or cell type identification), further data in the form of validation with traditional low throughput FISH and genetic manipulations to assess the relation to cell function are required for the authors to make such claims.

Discussion of likely impact:<br /> If revised, these data, and importantly the approach, would impact those working on Drosophila adults as well as those working in other model systems where single cell/nuclear sequencing is being translated to the spatial localization within the organism. The subcellular localization data - for example, the size of transcripts and how that relates to localization or the patterns of sarcomeric protein localization in muscle - are intriguing, and would likely impact our thinking on RNA localization, transport, etc if confirmed. Lastly, the authors compare their computational approaches to those available in the field; this is valuable as this is a rapidly evolving field and such considerations are critical for those wishing to use this type of approach.

Reviewer #1 (Public Review):

Summary:

In this study, Jeong and Choi examine neural correlates of behavior during a naturalistic foraging task in which rats must dynamically balance resource acquisition with the risk of threat. Rats first learn to forage for sucrose reward from a spout, and when a threat is introduced (an attack-like movement from a "LobsterBot"), they adjust their behavior to continue foraging while balancing exposure to the threat, adopting anticipatory withdrawal behaviors to avoid encounter with the LobsterBot. Using electrode recordings targeting the medial prefrontal cortex (PFC), they identify heterogenous encoding of task variables across prelimbic and infralimbic cortex neurons, including correlates of distance to the reward/threat zone, and correlates of avoidance behavior. Based on analysis of population responses, they suggest that the prefrontal cortex switches between coding schemes to process spatial information or behavioral responses in a context-dependent manner. Characterization of the heterogenous coding scheme by which the frontal cortex represents information in different goal states is an important contribution to our understanding of brain mechanisms underlying flexible behavior in ecological settings.

Strengths:

As many behavioral neuroscience studies employ highly controlled task designs, relatively less is known about how the brain organizes navigation and behavioral selection in naturalistic settings, where environment states and goals are more fluid. Here, the authors take advantage of a natural challenge faced by many animals - how to forage for resources in an unpredictable environment - to investigate neural correlates of behavior when goal states are dynamic. Related to this, they also investigate how prefrontal cortex (PFC) activity can reorganize to support different functional "modes" (here, between a navigational mode and an action-selection mode) for flexible behavior. Overall, an important strength and real value of this study is the design of the behavioral experiment, which is trial-structured, permitting the use of standard methods to analyze neural data, yet rich enough to encourage and permit more natural behavior. The experiment is also phased to measure behavioral changes as animals first encounter a threat, and then learn to adapt their foraging strategy to its presence. Characterization of this adaptation process is itself quite interesting and sets a foundation for further study of threat learning and risk management in the foraging context. Finally, the characterization of single-neuron activity from the prefrontal cortex in this naturalistic setting is an important contribution to the field - previous studies have identified the neural correlates of spatial and behavioral variables in the frontal cortex, but the nature of how these representations co-exist or are dynamically adjusted when animals shift their goals is less clear.

Weaknesses:

While the task design in this study is intentionally stimulus-rich and places a minimal constraint on the animal to preserve naturalistic behavior, this is, unfortunately, a double-edged sword, as it also introduces additional variables that confound some of the neural analysis. Because of this, a general weakness of the study is a lack of clear interpretability of the task variable neural correlates. This is a limitation of the task, which includes many naturally correlated variables - however, I think with some additional analyses, the authors could strengthen some of their core arguments and significantly improve clarity.

For example, the authors argue, based on an ANN decoding analysis (Figure 2b), that PFC neurons encode spatial information - but the spatial coordinate that they decode (the distance to the active foraging zone) is itself confounded by the fact that animals exhibit different behavior in different sections of the arena. From the way the data are presented, it is difficult to tell whether the decoder performance reflects a true neural correlate of distance, or whether it is driven by behavior-associated activity that is evoked by different behaviors in different parts of the arena. The author's claim that PFC neurons encode spatial information could be substantiated with a more careful analysis of single-neuron responses to supplement the decoder analysis. For example, 1) They could show examples of single neurons that are active at some constant distance away from the foraging site, regardless of animal behavior, and 2) They could quantify how many neurons are significantly spatially modulated, controlling for correlates of behavior events. One possible approach to disambiguate this confound could be to use regression-based models of neuron spiking to quantify variance in neuron activity that is explained by spatial features, behavioral features, or both.

The authors also claim that the heterogenous encoding of spatial and behavioral variables in PFC neurons is structured in a particular way that depends on the animal's goal state and/or context (a navigational mode and an action-selection mode). The main evidence supporting this interpretation is a population vector analysis based on principal component projections of neural data (Figure 4), which shows that the population response is different, on average, in the encounter zone compared to the foraging and nesting zones. But again, the different "zones" are obligately correlated with different types of behavior/stimuli. Since some neurons are modulated by events unique to the encounter zone (e.g., licking sucrose water, withdrawing from the LobsterBot, etc.), differences in population activity patterns may simply reflect this behavior/event coding. To substantiate the claim that PFC neurons really switch between different coding "modes," the authors could include a version of this analysis where they have regressed out, or otherwise controlled for, these confounds. Otherwise, the claim that the authors have identified "distinctively different states of ensemble activity," as opposed to simple coding of salient task features, seems premature.

Reviewer #3 (Public Review):

Summary:

This study investigates how various behavioral features are represented in the medial prefrontal cortex (mPFC) of rats engaged in a naturalistic foraging task. The authors recorded electrophysiological responses of individual neurons as animals transitioned between navigation, reward consumption, avoidance, and escape behaviors. Employing a range of computational and statistical methods, including artificial neural networks, dimensionality reduction, hierarchical clustering, and Bayesian classifiers, the authors sought to predict from neural activity distinct task variables (such as distance from the reward zone and the success or failure of avoidance behavior). The findings suggest that mPFC neurons alternate between at least two distinct functional modes, namely spatial encoding and threat evaluation, contingent on the specific location.

Strengths:

This study attempts to address an important question: understanding the role of mPFC across multiple dynamic behaviors. The authors highlight the diverse roles attributed to mPFC in previous literature and seek to explain this apparent heterogeneity. They designed an ethologically relevant foraging task that facilitated the examination of complex dynamic behavior, collecting comprehensive behavioral and neural data. The analyses conducted are both sound and rigorous.

Weaknesses:

The primary concern with this study is the absence of direct evidence regarding the role of the mPFC in the foraging behavior of the rats. The ability to predict heterogeneous variables from the population activity of a specific brain area does not necessarily imply that this brain area is computing or using this information. In light of recent reports revealing the distributed nature of neural coding, conducting direct causal experiments would be essential to draw conclusions about the role of the mPFC in spatial encoding and/or threat evaluation. Alternatively, a comparison with the activity from a different brain region could provide valuable insights (or at the very least, a comparison between PL and IL within the mPFC). Moreover, given that high-dimensional movement has been shown to be reflected in the neural activity across the entire dorsal cortex, more thorough comparisons between the neural encoding of task variables and movement would help rule out the possibility that the heterogeneous encoding observed in the mPFC is merely a reflection of the rats' movements in different behavioral modes. Lastly, the main claim of the paper is that the mPFC population switches between different functional modes depending on the context. However, no dynamic analysis or switching model has been employed to directly support this hypothesis.

Conclusion:

To strengthen the argument and offer novel insights into the functions of the mPFC, it would be important to conduct a more comprehensive analysis if additional data cannot be provided.

Reviewer #2 (Public Review):

Summary:

Jeong & Choi (2023) use a semi-naturalistic paradigm to tackle the question of how the activity of neurons in the mPFC might continuously encode different functions. They offer two possibilities: either there are separate dedicated populations encoding each function, or cells alter their activity depending on the current goal of the animal. In a threat-avoidance task rats procured sucrose in an area of a chamber where, after remaining there for some amount of time, a 'Lobsterbot' robot attacked. To initiate the next trial rats had to move through the arena to another area before returning to the robot encounter zone. Therefore the task has two key components: threat avoidance and navigating through space. Recordings in the IL and PL of the mPFC revealed encoding that depended on what stage of the task the animal was currently engaged in. When animals were navigating, neuronal ensembles in these regions encoded distance from the threat. However, whilst animals were directly engaged with the threat and simultaneously consuming reward, it was possible to decode from a subset of the population whether animals would evade the threat. Therefore the authors claim that neurons in the mPFC switched between two functional modes: representing allocentric spatial information, and representing egocentric information pertaining to the reward and threat.

Strengths:

As the authors point out, whilst these multiple functions of activity in the mPFC have generally been observed in tasks dedicated to the study of a singular function, less work has been done in contexts where animals continuously switch between different modes of behaviour in a more natural way. Being able to assess whether previous findings of mPFC function apply in natural contexts is very valuable to the field, even outside of those interested in the mPFC directly. This also speaks to the novelty of the work; although mixed selectivity encoding of threat assessment and action selection has been demonstrated in some contexts (e.g. Grunfeld & Likhtik, 2018) understanding the way in which encoding changes on-the-fly in a self-paced task is valuable for verifying whether current understanding holds true.

The authors are also generally thoughtful in their analyses and use a variety of approaches to probe the information encoded in the recorded activity. In particular, they also use relatively close analysis of behaviour as well as manipulating the task itself by removing the threat to verify their own results. The use of such a rich task also allows them to draw comparisons, e.g. in different zones of the arena or different types of responses to threats, that a more reduced task would not otherwise allow.

Weaknesses:

The central question the paper seeks to answer is whether 'individual cells are dedicated to spatial representation and emotional stimuli processing or if they adapt their function to the current goal'. However, there does not seem to be a direct analysis that answers this question. It is not clear what proportion of each of the ensembles recorded is necessary for decoding distance from the threat, and whether it is these same neurons that directly 'switch' to responding to head entry or withdrawal in the encounter phase within the total population. The PCA gets closest to answering this question by demonstrating that activity during the encounter is different from activity in the nesting or foraging zones, but in principle this could be achieved by neurons or ensembles that did not encode spatial parameters. The population analyses are focused on neurons sensitive to behaviours relating to the threat encounter, but even before dividing into subtypes etc., this is at most half of the recorded population. And again it is difficult to ascertain how the final ensemble analysis of the avoidance response relates to the prior spatial encoding. As a result, the model of the results proposed in Fig. 7 cannot be validated by the data as is.

A second concern is also illustrated by Fig. 7: in the data presented, separate reward and threat encoding neurons were not shown - in the current study design, it is not possible to dissociate reward and threat responses as the data without the threat present were only used to study spatial encoding integrity. To be able to claim this working model, a key additional analysis is to compare PETHs around head entry and withdrawal for sucrose without attack. Alternatively, a small proportion of probe trials could have been added where rats did not receive any reward for being in the encounter zone. This would allow the authors to ascertain whether the elevated response of the Type 2 neurons in particular is partially driven by reward receipt.

Thirdly, the findings of this work are not mechanistic or functional but are purely correlational. For example, it is claimed that analysing activity around the withdrawal period allows for ascertaining their functional contributions to decisions. But without a direct manipulation of this activity, it is difficult to make such a claim. The authors later discuss whether the elevated response of Type 2 neurons might simply represent fear or anxiety motivation or threat level, or whether they directly contribute to the decision-making process. As is implicit in the discussion, the current study cannot differentiate between these possibilities. However, the language used throughout does not reflect this.

Fourthly, the authors mention the representation of different functions in 'distinct spatiotemporal regions' but the bulk of the analyses, particularly in terms of response to the threat, do not compare recordings from PL and IL although - as the authors mention in the introduction - there is prior evidence of functional separation between these regions.

Reviewer #1 (Public Review):

Summary:<br /> The authors aimed to infer the trajectories of long range and local neuronal synchrony across the Alzheimer's disease continuum, relative to neurodegeneration and cognitive decline. The trajectories are inferred using event-based models, which infer a set of data-driven disease stages from a given dataset. The authors develop an adapted event-based modelling approach, in which they characterise each stage as a particular biomarker increasing by a particular z-score deviation from controls. Fitting infers the optimal set of z-scores to use for each biomarker and the order in which each biomarker reaches each z-score. The authors apply this approach to data from 148 individuals (70 cognitively unimpaired older adults and 78 individual with mild cognitive impairment or Alzheimer's disease), identifying trajectories in which long-range (amplitude-envolope correlation) and local (regional spectral power) neuronal synchrony in the alpha and beta bands becomes abnormal prior to neurodegeneration (measured as the volume of the parahippocampal gyrus) and cognitive decline (measured using the mini-mental state examination).

Strengths:<br /> - The main strength is that the authors assess two models. In the first they derive a staging system based only on the volume of the parahippocampal gyrus and mini-mental state examination score. They then investigate how neuronal synchrony metrics change compared to this staging system. In the second they derive a staging system that also includes an average (combined long-range and local) neuronal synchrony metric and investigate how long-range and local synchrony metrics change relative to this staging system. This is a strength as the first model provides confidence that there is not overfitting to the neuronal synchrony data, and the second provides more detailed insights into the dynamics of the early neuronal synchrony changes.<br /> - Another strength is that the authors automatically infer the optimal z-scores to choose, rather than having to pre-select them manually, as in previous approaches.

Weaknesses:<br /> - The authors do not have a dataset for external validation.

Reviewer #2 (Public Review):

Summary: This work presented by Kudo and colleagues is of great importance to strengthen our understanding of electrophysiological changes in the course of AD. Although the main conclusions regarding functional connectivity and spectral power change through the course of the disease are not new and have been largely studied and theorised on, this article offers an innovative approach that certainly consolidates previous knowledge on the topic. Not only that, this article also broadens our knowledge presenting useful and important details on the specificity of frequency and cortical distribution of these early alterations. The main take-home message of this work is the early disruption of electrophysiological signatures that precedes detectable alterations in other more commonly used pathology markers (i.e. gray matter atrophy and cognitive impairment). More specifically, these signatures include long-range connectivity in the alpha and beta bands, and local synchrony (spectral power) in the same frequency bands.

Strengths: The present work has some major strengths that make it paramount for the advance of our understanding of AD electrophysiology. It is a very well written manuscript that, despite the complexity of the analyses employed, runs the reader through the different steps of the analysis in a pedagogic and clever way, making the points raised by the results easy to grasp. The methodology itself is carefully chosen and appropriate to the nature of the question posed by the researchers, as event-based models are well-suited for cross-sectional data.

The quality of the figures is outstanding; not only are they aesthetic but, more importantly, the figures convey information exceptionally well and facilitate comprehension of the main results.<br /> The conclusions of the paper are, in general, well described and discussed, and consider the state-of-the-art works of AD electrophysiology. Furthermore, even though the conclusions themselves are not groundbreaking at all (synaptic damage preceding structural and cognitive impairment is one of the epitomes of the pathological cascading model proposed by Jack in 2010), this article is innovative and groundbreaking in the way they address with clever analyses in a relatively large sample for neuroimaging standards.

Weaknesses: The authors increased the clarity of sample description after revisions (particularly control group characterization). However, even though it is true that a certain percentage of AB positivity is to be expected amongst cognitively healthy individuals, that doesn´t discard they are not expressing preclinical AD to some extent. I still feel that including only biomarker negative participants in the control group would increase the quality of the work. However, the sample is relatively well characterized as a whole and the results are interesting and in line with previous literature, thus limiting the apparent impact of these possible confounds.

Reviewer #1 (Public Review):

In this study, Lin et al developed a protocol termed MOCAT, to perform tissue clearing and labelling on large-scale FFPE mouse brain specimens. They have optimised protocols for dewaxing and adequate delipidation of FFPE tissues to enable deep immunolabelling, even for whole mouse brains. This was useful for the study of disease models such as in an astrocytoma model to evaluate spatial architecture of the tumour and its surrounding microenvironment. It was also used in a traumatic brain injury model to quantify changes in vasculature density and differences in monoaminergic innervation. They have also demonstrated the potential of multi-round immunolabelling using photobleaching, as well as expansion microscopy with FFPE samples using MOCAT.

Strengths:<br /> This paper has demonstrated, with some good imaging examples, that it is possible to perform deep immunostaining with detailed analysis on FFPE samples using MOCAT. The figures provided appeared to be largely convincing with good amount of details.

They have showcased different ways to perform analysis on cleared tissue. For example, the use of lectin-labelled blood vessels as a structural reference for multi-round immunolabelling was very useful. They have also demonstrated how to generate comparable quantitative data on various mouse disease models which will be important for future tissue-clearing studies.

Weaknesses:<br /> Although the authors have proven the feasibility of their techniques on FFPE samples, it is questionable whether this will translate well for human brain tissues. The vast majority of the study data was generated using rodent brain tissues and it appears the technique was only performed on human FFPE tissues no larger than 1 mm in thickness. The PFA/formalin fixation time for the tissue was also limited to 24 hours in this study. Whilst this may be true for most surgical specimens, whole brain specimens in brain banks will often have formalin fixation time exceeding 3 weeks. The issue of prolonged formalin fixation prior to embedding in paraffin wax was not addressed in this study.

Inherent differences in human and rodent brain tissues may affect the effectiveness of immunostaining. In this study, results on human brain specimens appeared to show a reduction in clarity and staining quality at greater imaging depth at 900 µm, particularly for MAP2 and GFAP (Figure 5).

In addition, there are inadequate details in the materials and methods section which may limit the readers' ability to successfully replicate the study or proposed method for tissue clearing. Further details on the optimisation of this protocol and brief details from previously published protocols were not described in the methods section.

Reviewer #2 (Public Review):

The manuscript details an investigation aimed at developing a protocol to render centimeter-scale formalin-fixed paraffin-embedded specimens optically transparent and suitable for deep immunolabeling. The authors evaluate various detergents and conditions for epitope retrieval such as acidic or basic buffers combined with high temperatures in entire mouse brains that had been paraffin-embedded for months. They use various protein targets to test active immunolabeling and light-sheet microscopy registration of such preparations to validate their protocol. The final procedure, called MOCAT pipeline, briefly involves 1% Tween 20 in citrate buffer, heated in a pressure cooker at 121 {degree sign}C for 10 minutes. The authors also note that part of the delipidation is achieved by the regular procedure.

Major Strengths<br /> - The simplicity and ease of implementation of the proposed procedure using common laboratory reagents distinguish it favorably from more complex methods.

- Direct comparisons with existing protocols and exploration of alternative conditions enhance the robustness and practicality of the methodology.

Major Weaknesses<br /> - There is no evidence of actual transparency of the entire mouse brain across different treatments. The suggested protocol is very good at removing lipids (as assessed by DiD staining) and by results of fluorescence registration deep within the brain. BUT, since in many places of the manuscript authors speak of "transparency" the reader will expect the typical picture in which control and processed brains are on top of a white graphical pattern that would evidence transparency (see as an example Figure 1 and 2 of Wan et al. 2018 (Neurophotonics. 2018 Jul;5(3):035007. doi: 10.1117/1.NPh.5.3.035007.)

- The manuscript lacks clarity on the applicability of MOCAT to regular formalin-fixed tissue and tissues other than the brain.

- Insufficient information is provided on the "epoxy treatment" or "hydrogel," and a more detailed explanation is warranted.

- The differences between passive and active immunolabeling, as well as photobleaching data, should be addressed for a comprehensive understanding.

- The assertion that MOCAT can be rapidly applied in hospital pathology departments seems overstated due to the limited availability of light-sheet microscopes outside research labs.

- The compatibility of MOCAT with genetically encoded fluorescent proteins remains unclear and warrants further investigation.

- The control of equivalent depths in cryosections for evaluating the intensity of DiD staining should be elaborated upon.

- The composition of NFC1 and NFC2 solutions for refractive index matching should be provided.

Final considerations<br /> The evidence presented supports the effectiveness of the proposed method in rendering thick FFPE samples transparent and facilitating repeated rounds of immunolabeling.

The developed procedure holds promise for advancing tissue and 3D-specific determination of proteins of interest in various settings, including hospitals, basic research, and clinical labs, particularly benefiting neuroscience research.

The methodological findings suggest that MOCAT could have broader applications beyond FFPE samples, differentiating it from other tissue-clearing approaches in that the equipment and chemicals needed are broadly accessible.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, the authors set out to develop genetic tools that can specifically and comprehensively label Axo-Axonic Cells (AACs), also known as Chandelier cells. These AACs possess unique morphological and connectivity features, making them an ideal subject for studying various aspects of cell types across different experimental methods. To achieve both specificity and comprehensiveness in AAC labeling, the authors employ an intersectional strategy that combines lineage origin and molecular markers. This approach successfully targets AACs across the mouse brain and reveals their widespread distribution in various brain structures beyond the previously known regions. Additionally, the authors utilize rabies transneuronal labeling to provide a comprehensive overview of AACs, their variations, and input sources throughout the brain. This experimental approach offers a powerful model system for investigating the role of AACs in circuit development and function across diverse brain regions.

Strengths:<br /> Genetic Tools and Specificity: The authors' genetic tools show qualitative evidence of specificity for AACs, opening new avenues for targeted research on these cells. The use of intersectional strategies enhances the precision of AAC labeling.

Widespread Distribution: The study significantly broadens our understanding of AAC distribution, revealing their presence in brain regions beyond what was previously documented. This expanded knowledge is a valuable contribution to the field.

Transneuronal Labeling: The inclusion of rabies transneuronal labeling provides a comprehensive view of AACs, their variations, and input sources, allowing for a more holistic understanding of their role in neural circuits.

Weaknesses:<br /> Quantitative Analysis: While the claim of specificity appears qualitatively convincing, the manuscript could be improved with more quantitative analysis.

Comprehensiveness Claim: The assertion of comprehensiveness, implying labeling "almost all" AACs in all brain regions, is challenging to substantiate conclusively. Acknowledging the limitations of proving complete comprehensiveness and discussing them in the discussion section would be more appropriate than asserting it in the results section.

Local Inputs: While the manuscript focuses on inter-areal inputs to AACs, it would benefit from exploring local inputs as well. Identifying the local neurons that target AACs and analyzing their patterns could provide valuable insights into AAC function within specific brain regions.

Discussion Focus: The discussion section should delve deeper into the biological implications of the findings, moving beyond technical significance. Exploring similarities and differences in input patterns between AACs and other cell types, and linking them to the locations of starter cells or specific connectivity patterns in the brain, would enrich the discussion. For instance, investigating whether input patterns can be predicted based on the locations of starter cells or connectivity specificity could provide valuable insights.

Reviewer #2 (Public Review):

Summary:<br /> The goals of this study were to develop a genetic approach that would specifically and comprehensively target axo-axonic cells (AACs) throughout the brain and then to describe the patterns and characteristics of the targeted AACs in multiple, selected brain regions. The investigators have been successful in providing the most complete description of the regional distribution of putative (pAACs) throughout the brain to date. The supporting evidence is convincing, even though incomplete in some brain regions. The findings should serve as a guide for more detailed studies of AACs within each brain region and lead to new insights into the connectivity and functional organization of this important group of GABAergic interneurons.

Strengths:<br /> The study has numerous strengths. A major strength is the development of a unique intersectional genetic strategy that uses cell lineage (Nkx2.1) and molecular (Unc5b or Pthlh) markers to identify axo-axonic AACs specifically and, apparently, nearly completely throughout the mouse brain. While AACs have been described previously in the cerebral cortex, hippocampus, and amygdala, there has been no specific genetic marker that selectively identifies all AACs in these regions.

The current genetic strategy has labeled pAACs in a large number of additional brain regions, including the claustrum-insular complex, extended amygdala, and several olfactory centers. In general, the findings provide support for the specificity of the methods for targeting AACs, and include some examples of labeling near markers of axon initial segments. However, the Investigators are careful to refer to labeled neurons as "putative AACs" as they have not been fully characterized and their identity verified.

The descriptions and numerous low-magnification images of the brain provide a roadmap for subsequent, detailed studies of AACs in numerous brain regions. The overview and summaries of the findings in the Abstract, Introduction, and Discussion are particularly clear and helpful in placing the extensive regional descriptions of AACs in context.

Weaknesses:<br /> One weakness of the study is the lack of an illustration of the high-resolution cell labeling that can be achieved with the methods, including labeling of numerous rows of axon terminals in contact with axon initial segments. The initial images of the brain-wide distribution of putative AACs are necessarily presented at low magnification. Although the authors indicate that the cells have "highly characteristic AAC labeling patterns throughout the neocortex, hippocampus and BLA", these morphological details cannot be visualized by the reader at the current magnification, even when the images are enlarged on the computer screen. Some of the details become evident in later Figures, but an initial illustration of single cell labeling with confocal microscopy, or tracing of their characteristic axonal arbors, would support the specificity of the labeling in the low magnification images.

Table 1 indicates that the AAC identity of the cells has been validated in many brain regions but not in all. The methods used for validation have not been described and should be included for completeness. The authors are careful to acknowledge that labeled cells in some regions have not been validated and refer to such cells as pAACs.

The intersectional genetic methods included the use of the lineage marker Nkx2.1 with either Unc5b or Pthlh as the molecular marker. As described, the mice with intersectional targeting of Nkx2.1 and Unc5b appear to show the most specific brain-wide labeling for AACs, and the majority of the descriptions are from these mice. The targeting with Nkx2.1 and Pthlh is less convincing. The title for Figure 1 Supplemental Figure 3 suggests a similar AAC distribution in the Pthlh;Nkx2.1 mouse compared to the Unc5b;Nkx2.1 mouse. However, the descriptions of the individual panels suggest a number of inconsistencies and non-AAC labeling. The heavy labeling in the caudate and cells in layer 4 is particularly problematic. Based on the data presented, it appears that heavy labeling achieved in these mice could not be relied on for specific labeling of all AACs, although specific labeling could be achieved under some conditions, such as following tamoxifen administration at select ages.

The methods described for dense labeling and single-cell labeling are described briefly in the methods. Some discussion of the development of the methods would be useful, including how it was determined that methods for heavy labeling identified AACs specifically and completely.

Reviewer #3 (Public Review):

Summary:<br /> Raudales et al. aimed at providing an insight into the brain-wide distribution and synaptic connectivity of bona fide GABAergic inhibitory interneuron subtypes focusing on the axo-axonic cell (AAC), one of the most distinctive interneuron subtypes, which innervates the axon initial segments of glutamatergic projection neurons. They establish intersectional genetic strategies that enable them to specifically and comprehensively capture AACs based on their lineage (Nkx2.1) and marker expression (Unc5b, Pthlh). They find that AACs are deployed across essentially all the pallium-derived brain structures as well as the anterior olfactory nucleus, taenia tecta, and lateral septum. They show that AACs in distinct areas and layers of the neocortex as well as different subregions of the hippocampal formation display unique soma and synaptic density and morphological variations. Rabies virus-based retrograde monosynaptic input tracing reveals that AACs in the neocortex, the hippocampus, and the basolateral amygdala receive synaptic inputs from common as well as specific brain regions and supports the utility of this novel genetic approach. This study elucidates brain-wide neuroanatomical features and morphological variations of AACs with solid techniques and analysis. Their novel AAC-targeting strategies will facilitate the study of their development and function in different brain regions. The conclusions in this paper are well supported by the data. However, there are a few comments to strengthen this study.

1) The definition of putative AAC (pAAC) is unclear and Table 1 may not be accurate. Although the authors find synaptic cartridges of RFP-labeled cells in the claustro-insular complex and the dorsal endopiriform nuclei, they still consider these cells as pAACs (not validated). The authors claim that without examining the presence of synaptic cartridges, RFP-labeled cells in the hypothalamus and the bed nuclei of the stria terminalis (BNST) are pAACs while those in the L4 of the somatosensory cortex in Pthlh;Nkx2.1;Ai65 mice are non-AACs. In Table 1, the BNST is supposed to contain AACs (validated), but in the text, the authors claim that RFP-labeled cells in the BNST are pAACs. Could the authors clarify how AACs, pAACs, and non-AACs are defined?

2) The intersectional strategies presented in this study could also specifically capture developing AACs. If so, how early are AACs labeled in the brain? It would also be nice if the authors could add a simple schematic like Fig. 1a showing the time course of Pthlh expression.

Reviewer #1 (Public Review):

Summary:<br /> This describes the molecular identity of the intermediate status of cranial neural crest cells (NCCs) during the initial delamination process. Taking advantage of single-cell RNA seq, the authors identify new populations of cells during EMT characterized by a specific set of gene expressions, including Dlc1. Promigratory cranial NCCs differentiate through different trajectories depending on their cell cycle phases but converge into a common progenitor, then differentiate into mesenchymal cells expressing region-specific genes.

Strengths:<br /> Single-cell RNA seq data convincingly support what the authors claim. This is the first time to identify intermediate states between premigratory and migratory cranial NCCs. Silencing one of the marker genes, Dlc1, reduces the migratory activity of cranial NCCs. These findings deepen our understanding of the mechanism of EMT in general.

Weaknesses:<br /> Common and specific features between cranial and trunk NCCs could be described/discussed in-depth. Phenotypic relations between the reduction of delamination and defects found in Dlc1 mutant mice can be discussed.

Reviewer #2 (Public Review):

Zhao et al., focus on mechanisms through which cells convert from epithelium to mesenchyme and become migratory. This phenomenon of epithelial-to-mesenchymal transition (EMT) occurs during both embryonic development and cancer progression. During cancer progression, EMT seemingly includes cells at intermediate states as defined by the combinatorial expression of epithelial and mesenchymal markers. However, the importance of these markers and the role of these intermediate states remains unclear. Moreover, whether EMT during development also involves equivalent intermediate cell states is not known. To address this gap in knowledge, the authors devise a strategy to identify and characterize changes that an embryonic population of cells called the cranial neural crest undergo as they delaminate from the neuroepithelium and become a highly migratory population of mesenchymal cells that ultimately give rise to a broad range of derivatives.

To isolate and study the neural crest, the authors use embryos collected at E8.5 from two transgenic mouse lines. Wnt1-Cre;RosaeYFP labels Wnt1-positive neuroepithelial cells in the dorsolateral neural plate, which includes pre-migratory neural crest that resides in the dorsal neuroectoderm and neural plate border before induction (as well as some other lineages). Mef2c-F10N-LacZ leverages a neural crest cell-specific enhancer of Mef2c to control LacZ expression in the predominantly migratory neural crest. This dual genetic approach that allows the authors to distinguish and compare pre-migratory and migratory neural crest cells is a strength of the work. However, one potential weakness needing to be addressed is that some workers (e.g., Lewis et al., 2013) have reported phenotypic effects of Wnt1-Cre transgene expression including ectopic Wnt pathway activation, abnormal neuroepithelial development, and increases in CyclinD1 expression and cell proliferation. The authors should discuss the extent to which the results of their study were or were not influenced by these potentially confounding effects, especially since Wnt canonical signaling is known to regulate the G1/S transition and promote delamination of the neural crest.

To assay for the differential expression of genes involved in the EMT and migration of cranial neural crest, the authors perform single-cell RNA sequencing (scRNA-seq) using current methods. A strength is a large sample size per mouse line, and relatively high numbers of single cells analyzed. The authors identify six major cell/tissue types present in mouse E8.5 cranial tissues using known markers, which they then segregate into a cranial neural crest cluster using a well-reasoned bioinformatic strategy. The cranial neural crest cluster contains pre-migratory and migratory cells that they partition further into five subclusters and then characterize using the differential expression and combinatorial patterns of neural crest specifier genes, markers of pre-migratory neural crest, markers of early versus late migratory neural crest, markers of undifferentiated versus differentiated neural crest, tissue-specific markers, and region-specific markers. One weakness is that there is no attempt to map potential novel genes and/or pathways that also distinguish these clusters.

The authors then go on to subdivide the five cranial neural crest subclusters into almost two dozen smaller subclusters, again using the combinatorial expression of known markers (e.g., neural crest genes, cell junction genes, and cell cycle genes). A weakness is that the marker analysis and accompanying interpretation of the results rely heavily on the purported roles of different genes as described in the published work of others, which potentially introduces some untested assumptions and a bit of hand-waving into the study. Moreover, the limited correlation between mRNA and protein abundance for cell cycle markers is well documented in the literature but the authors rely heavily on gene expression to determine cell cycle status. Even though the authors add a compelling Edu/pHH3 double-labeling experiment and cell cycle inhibition studies, the work would be strengthened by including some analysis of protein expression to see if the cell cycle correlations hold up. Nonetheless, the subcluster and cell cycle analyses lead the authors to conclude that there are a series of intermediate cell states between neural crest EMT and delamination, and that cell cycle regulation is a defining feature and necessary component of those states. These novel findings are generally well supported by the data.

To test if there are spatiotemporal differences in the localization of neural crest cells during EMT in vivo, the authors apply a cutting-edge technique called signal amplification by exchange reaction for multiplexed fluorescent in situ hybridization (SABER-FISH), which they validate using standard in situ hybridization. The authors select specific marker genes that seem justified based on their scRNA-seq dataset, and they generate a series of convincing images and quantitative data that add valuable depth to the story.

As a functional test of their hypothesis that one of the genes indicative of an EMT intermediate stage (i.e., Dlc1) is essential for neural crest migration, the authors use a lentivirus-mediated knockdown strategy. A strength is that the authors include appropriate scramble and cell death controls as part of their experimental design. However, a weakness is that the authors do not justify why they chose a knockdown strategy, which has its limitations including its systemic injection into the amniotic cavity, its likely global and more variable effects, and its need to be conducted in culture. Why the authors did not instead use a Wnt1-Cre-mediated deletion of Dlc1, which would have been "cleaner" and more specific to the neural crest, is not clear (maybe so they could specifically target different Dcl1 isoforms?). Also, the authors use Sox10 as a marker to count neural crest cells, but Sox10 may only label a subset of neural crest cells and thus some unaffected lineages may not have been counted. The authors should mention what is known about the regulation of Dcl1 by Sox10 in the neural crest. Although the data are persuasive, a second marker for counting neural crest cells following knockdown would make the analysis more robust. Can the authors explain why they did not simply use the Mef2c-F10N-LacZ line and count LacZ-positive cells (if fluorescence signal was required for the quantification workflow, then could they have used an anti-beta Galactosidase antibody to label cells)?

Overall, this is a first-rate study with many more strengths than weaknesses. The authors generate high-quality data, and their interpretations are reasonable and balanced. Another strength is the writing, which is clear and well organized, and the figures (including supplemental), which are excellent and provide unambiguous visualization of some very complex data sets. The methods are state-of-the-art and are effectively executed, and they will be useful to the broader cell and developmental biology community. The work contains well-substantiated findings and supports the conclusion that EMT is a highly dynamic, multi-step process, which was previously thought to be more-or-less binary. Such findings will alter the way the field thinks about EMT in neural crest and the work will likely serve as an important example alongside cancer metastasis.

Reviewer #3 (Public Review):

Summary:<br /> Zhao et al. address the question of whether intermediate states of the epithelial-to-mesenchymal transition (EMT) exist in a natural developmental context as well as in cancer cells. This is important not only for our understanding of these developmental systems but also for their development as resources for new anti-cancer approaches. Guided by single-cell RNA sequencing analysis of delaminating mouse cranial neural crest cells, they identify two distinct populations with transcriptional signatures intermediate between neuroepithelial progenitors and migrating crest. Both clusters are intermediate spatially and actively cycling, with one in S-phase and one in G2/M. They show that blocking progression through S phase prior to the onset of delamination and knockdown of intermediate state marker Dlc1 both reduce the number of migratory cells that have completed EMT. Overall, the work provides a modern take and new insights into the classical developmental process of neural crest delamination.

Strengths:<br /> • Deep analysis of the scRNAseq dataset revealed previously unappreciated cell populations intermediate between premigratory and migratory crest.<br /> • The observation that delaminating/intermediate neural crest cells appear to be in S or G2/M phase is interesting and worth reporting, though the ultimate significance remains unclear, given that they do not make distinct derivatives depending on their cycle state.<br /> • The authors employ new methods for multiplex spatial imaging to more accurately define their populations of interest and their relative positions.<br /> • The authors present evidence that intermediate state gene Dlc1 (a Rho GAP) is not just a marker but functionally required for neural crest delamination in mice, as previously shown in chicken.

Weaknesses:<br /> • Similar experiments involving blockade of cell cycle progression and Dlc1 dose manipulation were previously performed in chick models, as noted in the discussion. The newly-defined intermediate states give added context to the results, but they are not entirely novel.<br /> • The putative intermediate cells differentially express mRNAs for genes involved in cell adhesion, polarity, and protrusion relative to bona fide premigratory cells (Fig. 2E). This is persuasive evidence, but only differentially expressed genes are shown. Discussing those markers that have not yet changed, e.g. Cdh1 or Zo1 (?), would be instructive and help to clarify the order of events.<br /> • It is unclear whether the two putative intermediate state clusters differ other than their stage of the cell cycle. Based on the trajectory analysis in Fig. 3C-D, the authors state that these two populations form simultaneously and independently but then merge into a single population. However, without further differential expression, it seems more plausible that they represent a single population that is temporarily bifurcated due to cell cycle asynchrony.<br /> • The authors do not present an in-depth comparison of these neural crest intermediate states to previously reported cancer intermediate states. This analysis would reveal how similar the signatures are and thus how extrapolatable these and future findings in delaminating neural crest are to different types of cancer.<br /> • Lines 265-289 (Fig. 4): The aphidicolin treatments appear to have been started before NC delamination begins in earnest, so the fact that there are any migratory SOX10+ neural crest in the treated embryos at all indicates that progression through S-phase is not explicitly required for delamination. The authors surmise that the successfully delaminated cells may instead have been in G2/M phase (perhaps representing cluster 10') already at the start of treatment and thus able to progress through EMT, while S phase intermediate and true premigratory cells were not. This is plausible. However, the reduction in SOX10+ cells may be in part or wholly attributable to inhibition of proliferation AFTER delamination. Showing that there are premigratory NCCs in G2/M at ~E8.0 would bolster the argument that this population is present from the earliest stages.

Reviewer #1 (Public Review):

In this manuscript, Seba et al., investigate the mechanism of chromosome organization by the MukBEF complex in E. coli. They use a combination of Hi-C and ChIP analysis to understand the steps of MukBEF regulation: its unloading from DNA (how MukBEF activity is prevented in the terminus regions of the chromosome by MatP), and its loading onto DNA (how DNA replication influences MukBEF association with the chromosome). Seba et al., induce chromosomal rearrangements to flip the sections of the ter region, thus perturbing matS site numbers and position. They find that MukBEF activity is prevented around matS sites and that higher matS density has greater effect on MukBEF. Separately, using replication mutants and inducible MukBEF expression, they find that MukBEF can associate with the chromosome even in the absence of replication (as seen by the emergence of long-range contacts). However, ChIP data suggests that MukBEF binding to DNA is enriched on newly replicated DNA.

Altogether, this work provides a valuable and comprehensive view of MukBEF-mediated chromosome organization, with insights on the mechanism of the exclusion of MukBEF from the terminus region of the chromosome. The use of the programmed genetic rearrangements is powerful and allows the authors to provide clear and convincing evidence for MukBEF exclusion from ter by matS sites. It is particularly striking to see that MukBEF can promote long-range contacts even in chromosomal regions between two matS, but the complex is excluded from the matS 'zones'. Experiments using cells blocked for replication show that MukBEF can influence chromosome organization in the absence of replication as well. While previous studies have reported some evidences in support of both of the above conclusions, the experiments described here offer a clear and direct demonstration of the same.

Reviewer #2 (Public Review):

Summary:<br /> Chromosome organization in E. coli and related species ('transversal') deviates starkly from the pattern more commonly found in bacteria ('longitudinal'). The underlying mechanisms and the physiological roles, however, are not well understood. This manuscript by Seba et al. investigates the activity and regulation of MukBEF in chromosome folding in E. coli. Using a construct for inducible expression of MukBEF, the authors first demonstrate that the initiation of long-range chromosome contacts (likely by loop extrusion) is not restricted to few positions on the chromosome and rather widely distributed but excluding the replication terminus region. Using ChIP-Seq, the authors show that the distribution of MukBEF over the chromosome is consistent with widely distributed loading and moreover indicate a connection of chromosome folding and DNA replication with newly replicated DNA shower an increased tendency for MukBEF binding. To dissect this further, they then redistribute matS sites on the chromosome by a clever strategy based on large-scale transpositions. The results reveal that matS-free DNA segments undergo MukBEF dependent folding regardless of their position relative to the origin of replication, being consistent with a broad distributed loading of MukBEF. By fine-mapping with smaller transposition events, they show that few matS sites are sufficient to impede MukBEF activity. Surprisingly, however, E. coli and most related genomes harbor many matS sites, which are particularly highly concentrated near the chromosome dimer resolution dif site (Fig. 5).

This is a well-executed and well-presented study. The findings show that the MatP/matS system acts locally and independent of DNA replication to restrict MukBEF in the replication terminus region. Few of the many matS sites are sufficient for MukBEF restriction. The main conclusions of the work are clear and well supported by the data.

Reviewer #3 (Public Review):

Seba et al. investigate whether chromosomal recruitment of the E. coli SMC complex MukBEF is initiated at a single site, how MukBEF activity is excluded from the replication terminus region, and whether its recruitment and activity depend on DNA replication. Upon induction of MukBEF, the authors find that chromosomal long-range contacts increase globally rather than from a single site. Using large-scale chromosome rearrangements, they show that matS sites can insulate separate areas of high MukBEF activity from each other. This suggests that MukBEF loads at multiple sites in the genome. Finally, the authors propose that MukBEF associates preferentially with newly replicated DNA, based on ChIP-seq experiments after DNA replication arrest.

The conclusions of the paper are well supported by the data. The ratiometric contact analyses and range-of-contact analyses are compelling and nicely show the interplay between MukBEF and its proposed unloader MatP/matS. I particularly enjoyed the chromosome re-arrangement experiments, which lend strong support to the idea that MukBEF activity is independent of a centralized loading site.<br /> The enrichment of MukBEF in newly replicated regions is convincing, despite somewhat small effect sizes. The suggestion that matS density controls MukBEF activity is appealing, but will need additional support from more systematic studies. It is based on a comparison of only two strains (looking at different combinations of three matS sites), and the effect size is small. As it is, differences in matS sequence composition and genomic context cannot be factored out.

Overall, the work is an important advance in our understanding of bacterial chromosome organization. It will be of broad interest to chromosome biologists and bacterial cell biologists.

Reviewer #1 (Public Review):

In this study, the authors seek to characterize the role of splicing factor SRSF1 during spermatogenesis using Vasa-Cre;Srsf1Fl/del mice model. The authors first revealed that spermatogonia-related genes (e.g., Plzf, Id4, Setdb1, Stra8, Tial1/Tiar, Bcas2, Ddx5, Srsf10, Uhrf1, and Bud31) were bound by SRSF1 in the mouse testes by CLIP-seq. The authors convincingly demonstrated that specific deletion of SRSF1 in mouse gem cells with vasa-cre lead to NOA by impairing homing and failure survival of spermatogonia. To investigate the molecular mechanisms of SRSF1 in spermatogonia, further multiomics analysis including CLIP-seq, IP-MS, and RNA-seq were conducted. The results showed that SRSF1 coordinated with other RNA splicing-related proteins to directly bind and regulate the expression of nine spermatogonia-related genes especially Tial1/Tiar via alternative splicing. The authors revealed the critical role of SRSF1-mediated AS in precursor SSCs homing and survival, which may provide a framework to elucidate the molecular mechanisms of the posttranscriptional network underlying the formation of SSC pools and the establishment of niches. This work will be of interest to stem cell and reproductive biologists. The experiments are well-designed and conducted, and the overall methods and results are convincing except for the claim that altered splicing of the Tial1 transcript mediates the effect of SRSF1 loss.

Reviewer #2 (Public Review):

Summary<br /> The authors seek to characterize the role of splicing factor SRSF1 during spermatogenesis. Using a conditional deletion of Srsf1 in germ cells, they find that SRSF1 is required for male fertility. Via immunostaining and RNA-seq analysis of the Srsf1 conditional knockout (cKO) testes, combined with SRSF1 CLIP-seq and IP-MS data from the testis, they ultimately conclude that Srsf1 is required for homing of precursor spermatogonial stem cells (SCCs) due to alternative splicing.

Strengths<br /> The overall methods and results are robust. The histological analysis of the Srsf1 cKO traces the origins of the fertility defect to the postnatal testis, and the authors have generated interesting datasets characterizing SRSF1's RNA targets and interacting proteins specifically in the testis.

Ultimately, the authors have shown that SRSF1's effects on alternative splicing are required to establish spermatogenesis. In the absence of Srsf1, the postnatal gonocytes do not properly mature into spermatogonia and consequently never initiate spermatogenesis.

Reviewer #3 (Public Review):

In this study, Sun et al examine the role of the splicing factor SRSF1 in spermatogenesis in mice. Alternative splicing is important for spermatogenic development, but its regulation and major developmental roles during spermatogenesis are not well understood. The authors set out to better define both SRSF1 function in testes and the contribution of alternative splicing. They generate several large 'omics datasets to define SRSF1 targets in testis, including RNA interactions by CLIP-seq in whole testis, protein interactions by IP-mass spec in whole testis, and RNA sequencing to detect expression levels and splice variants. They also examine the phenotype of germline conditional knockouts (cKO) for Srsf1, using the early-acting Vasa-Cre, and find a severe depletion of germ cells starting at 7 days post partum (dpp) and culminating with a lack of germ cells (Sertoli Cell Only Syndrome) by adulthood. They detect differences in gene expression as well as differences in splicing between control and knockout, including 9 genes that are downregulated, experience alternative splicing, and whose transcripts are also bound by SRSF1, and identify the Tial1/Tiar transcript as one of these targets. They conclude that SRSF1 is required for homing and self-renewal of precursor spermatogonial stem cells, and suggest that this role may be mediated in part though its regulation of Tial1/Tiar splicing.

Strengths of the paper include detailed phenotyping of the Srsf1 cKO, which convincingly supports the Sertoli Cell Only phenotype, establishes the timing of the first appearance of the spermatogonial defect, and provides new insight into the role of splicing factors and SRSF1 specifically in spermatogenesis. Another strength is the generation of CLIP-seq, IP-MS, and RNA-seq datasets which will be a useful resource for the field of germ cell development. Overall, the results support the claims made. While the study does not provide a full mechanistic understanding of how alternative splicing mediated by SRSF1 affects SSC precursors, the contributions are novel and useful, and will be of interest to the fields of alternative splicing and male reproductive biology.

Reviewer #1 (Public Review):

The manuscript aims to provide mechanistic insight into the activation of PI3Kbeta by its known regulators tyrosine phosphorylated peptides, GTP-loaded Rac1 and G-protein beta-gamma subunits. To achieve this the authors have used supported lipid bilayers, engineered recombinant peptides and proteins (often tagged with fluorophores) and TIRF microscopy to enable bulk (averages of many molecules) and single molecule quantitation. The great strength of this approach is the precision and clarity of mechanistic insight. Although the study does not use "in transfecto" or in vivo models the experiments are performed using "physiologically-based" conditions and provide a powerful insight into core regulatory principles that will be relevant in vivo.<br /> The results are beautiful, high quality, well controlled and internally consistent (and with other published work that overlaps on some points) and as a result are compelling. The primary conclusion is that the primary regulator of PI3Kbeta are tyrosine phosphorylated peptides (and by inference tyrosine phsophorylated receptors/adaptors) and that the other activators can synergise with that input but have relatively weak impacts on their own.

Although the methodology is not easily imported, for reasons of both cost and the experience needed to execute them well, the results have broad importance for the field and reverse an impression that had built in large parts of the broader signalling and PI3K communities that all of the inputs to PI3Kbeta were relatively equivalent, however, these conclusions were based on "in cell" or in vivo studies that were very difficult to interpret clearly.

Reviewer #2 (Public Review):

The manuscript of Duewell et al has made critical observations that help to understand the mechanisms of activation of the class IA PI3Ks. By using single-molecule kinetic measurements, the authors have made outstanding progress toward understanding how PI3Kbeta is uniquely activated by phosphorylated tyrosine kinase receptors, Gbeta/gamma heterodimers and the small G protein Rac1. While previous studies have defined these as activators of PI3Kbeta, the current manuscript makes clear the quantitative limitations of these previous observations. Most previous quantitative in vitro studies of PI3Kbeta activation have used soluble peptides derived from bis-phosphorylated receptors to stimulate the enzyme. These soluble peptides stimulate the enzyme, and even stimulate membrane interaction. Although these previous studies showed that the release of p85-mediated autoinhibition unmasks an intrinsic affinity of the enzyme for lipid membranes, they ignored what would be the consequence of these peptide sequences being present in the context of intrinsic membrane proteins. The current manuscript shows that the effect of membrane-conjugated peptides on the enzyme activity is profound, in terms of recruiting the enzyme to membranes. In this context, the authors show that G proteins associated with the membranes have an important contribution to membrane recruitment, but they also have a profound allosteric effect on the activity on the membrane, These are observations that would not have been possible with bulk measurements, and they do not simply recapitulate observations that were made for other class IA PI3Ks.

An important observation that the authors have made is that Gbeta/gamma heterodimers and RAc1 alone have almost no ability to recruit PI3Kbeta to the membranes that they are using, and this is central to one of the most profoundly novel activation mechanisms offered by the manuscript. The authors propose that the nSH2- and Gbeta/gamma binding sites partially overlap, so that Gbeta/gamma can only bind once the nSH2 domain releases the p110beta subunit. This mechanism would mean that once the nSH2 is engaged by membrane-congugated pY, the Gbg heterodimer can bind and increase the association of the enzyme with membranes. Indeed, this increased membrane association is observed by the authors. However, the authors also show that this increased recruitment to membranes accounts for relatively little increase in activity, and that the far greater component of activation is due to an allosteric effect of the membrane association on the activity of the enzyme. The proposal for competition between Gbg binding and the nSH2 is consistent with the behavior of an nSH2 mutant that cannot bind to pY and which, consequently, does not vacate the Gbg-binding site. In addition to the outstanding contribution to understanding the kinetics of activation of PI3Kbeta, the authors have offered the first structural interpretation for the kinetics of Gbg activation in synergy with pY activation. The proposal for an overlapping nSH2/Gbg binding site is supported by predictions made by John Burke, using alphafold multimer. Although there is no experimental structure to support this structural model, it is consistent with HDX-MS analyses that were published previously.

Reviewer #1 (Public Review):

In this revised preprint the authors investigate whether a presumably allosteric P2RX7 activating compound that they previously discovered reduces fibrosis in a bleomycin mouse model. They chose this particular model as publicly available mRNA data indicate that the P2RX7 pathway is downregulated in idiopathic pulmonary fibrosis patients compared to control individuals. In their revised manuscript, the authors use three proxies of lung damage, Ashcroft score, collagen fibers, and CD140a+ cells, to assess lung damage following the administration of bleomycin. These metrics are significantly reduced on HEI3090 treatment. Additional data implicate specific immune cell infiltrates and cytokines, namely inflammatory macrophages and damped release of IL-17A, as potential mechanistic links between their compound and reduced fibrosis. Finally, the researchers transplant splenocytes from WT, NLRP3-KO, and IL-18-KO mice into animals lacking the P2RX7 receptor to specifically ascertain how the transplanted splenocytes, which are WT for P2RX7 receptor, respond to HEI3090 (a P2RX7 agonist). Based on these results, the authors conclude that HEI3090 enhanced IL-18 production through the P2RX7-NLRP3 inflammasome axis to dampen fibrosis.

These findings could be interesting to the field, as there are conflicting results as to whether NLRP3 activation contributes to fibrosis and if so, at what stage(s) (e.g., acute damage phase versus progression). The revised manuscript is more convincing in that three orthogonal metrics for lung damage were quantified.

However, deletion of the P2RX7 receptor itself reduces the extent of fibrosis, suggesting that P2RX7 signaling can be pro-fibrotic. In the absence of P2RX7, the effects of HEI3900 are also abolished, suggesting that HEI3900 acts in part via P2RX7 signaling. This suggests a paradox that P2RX7 signaling can be both detrimental and beneficial in fibrosis and there is need for a better understanding of when P2RX7 signaling is beneficial and when it is detrimental in lung fibrosis. HEI3900-induced activation of P2RX7 seems to be beneficial but this primarily is shown for when fibrosis is already established. As the P2RX7 genetic deletion mouse model has less fibrosis, P2RX7 signaling and inflammasome activation may be deleterious during the formation of disease but it is also possible that HEI3900 has other beneficial effects that are not directly related to P2RX7.

Molecularly, additional evidence on specificity, such as thermal proteome profiling and direct biophysical binding experiments, would also enhance the authors' argument that the compound indeed binds P2RX7 directly and specifically. Since all small molecules have some degree of promiscuity, the absence of an additional P2RX7 modulator, or direct recombinant IL-18 administration, is needed to orthogonally validate the functional importance of this pathway. Another way the authors could probe pathway specificity would involve co-administering α-IL-18 with HEI3090 in several key experiments (similar to Figure 4L).

Reviewer #2 (Public Review):

In the study by Hreich et al, the potency of P2RX7-specific positive modulator HEI3090, developed by the authors, for the treatment of Idiopathic pulmonary fibrosis (IPF) was investigated. Recently, the authors have shown that HEI3090 can protect against lung cancer by stimulating dendritic cell P2RX7, resulting in IL-18 production that stimulates IFN-γ production by T and NK cells (DOI: 10.1038/s41467-021-20912-2). Interestingly, HEI3090 increases IL-18 levels only in the presence of high eATP. Since the treatment options for IPF are limited, new therapeutic strategies and targets are needed. The authors first show that P2RX7/IL-18/IFNG axis is downregulated in patients with IPF. Next, they used a bleomycin-induced lung fibrosis mouse model to show that the use of a positive modulator of P2RX7 leads to the activation of the P2RX7/IL-18 axis in immune cells that limits lung fibrosis onset or progression. Mechanistically, treatment with HEI3090 enhanced IL-18-dependent IFN-γ production by lung T cells leading to a decreased production of IL-17 and TGFβ, major drivers of IPF. The major novelty is the use of the small molecule HEI3090 to stimulate the immune system to limit lung fibrosis progression by targeting the P2RX7, which could be potentially combined with current therapies available. Overall, the study was well performed and the manuscript is clear.

Reviewer #1 (Public Review):

Summary:<br /> The study follows the role of yeast eIF2A protein as potential translation initiation factor engaged in the non-canonical translation initiation under stress conditions and as a substitute for eIF2. Using ribosome profiling, RNA-Seq and reporter based assays authors evaluated the role of eIF2A protein under regular or stress conditions (cells starved for branched amino acids). Authors found that yeast cells depleted of eIF2A protein do not change significantly their translation initiation, or translation in general. In the contrast to previously reported data for human homolog yeast eIF2A does not significantly contribute to regulation of the uORFs, regardless if they start with canonical AUG or near cognate start codons. eIF2A is not involved in the repression of IRES element in URE2 gene or has a role in purine biosynthesis. It appears that in yeast eIF2A contributes to regulation of very limited number of mRNAs (32 with significant changes in translation efficiency), where only 17 of such messages indeed are consistent with eIF2A deletion and single mRNA (HKR1) could be validated in reporter assay.

Strengths:<br /> The strength of the manuscript is complete analysis and unbiased approach using genomic analysis methods (ribosome profiling and RNA-seq) as well as reporter validation studies. Additional strength of the manuscript is scientific rigor and statistics associated with data analyses, clear data presentation and discussion of the results in the context of the previous studies and results.

Weaknesses:<br /> none noted

Reviewer #2 (Public Review):

Summary:<br /> Gaikwad et al. investigated the role of eIF2A in translational response to stress in yeast. For this purpose, the authors conducted ribosome profiling under SM treatment in eIF2A-depleted strain. Data analysis revealed that eIF2A did not influence translation from mRNAs bearing uORFs or cellular IRESes, in the stress condition, broadly. The authors found that only a small number of mRNAs were supported by eIF2A. The data should be helpful for researchers in the fields.

Major points:<br /> 1. The weakness of this work is the lack of clarification on the function of eIF2A in general. The novelty of this study was limited.

2. Related to this, it would be worth investigating common features in mRNAs selectively regulated (surveyed in Figure 3A). Also, it would be worth analyzing the effect of eIF2A deletion on elongation (ribosome occupancy on each codon and/or global ribosome footprint distribution along CDS) and termination/recycling (footprint reads on stop codon and on 3′ UTR).

3. Regarding Figure 3D, the reporters were designed to include promoter and 5′ UTR of the target genes. Thus, it should be worth noting that reporter design was based on the assumption that eIF2A-dependency in translation regulation was not dependent on 3′ UTR or CDS region. The reason why the effects on ribosome profiling-supported mRNAs could not be recapitulated in reporter assay may originate from this design. This should be also discussed.

4. Related to the point above, the authors claimed that eIF2A affects "possibly only one" (HKR1) mRNA. However, this was due to the reporter assay which is technically variable and could not allow some of the constructs to pass the authors' threshold. Authors may be worth considering better wording for this point.

5. For Figure 3D, it would be worth considering to test all the #-marked genes (in Figure 3C) in this set up.

6. In box plots, the authors should provide the statistical tests, at least where the authors explained in the main text.

Reviewer #3 (Public Review):

Summary:

The authors have undertaken a study to rigorously characterize the possible role of eIF2A in regulating translation in yeast. The authors test for a role of eIF2A in the absence or presence of cellular stress and conclude that eIF2A does not play any significant role in regulating translation initiation in yeast.

The authors have used rigorous experimental approaches, including genome wide ribosome profiling analysis in the absence or presence of stress, to show that eIF2A does not function in translation initiation on most mRNAs in yeast. Interestingly, the authors do identify a small number of mRNAs that possess some eIF2A dependency, so they constructed reporters to rigorously test them. One mRNA, HKR1, appears to possess a degree of eIF2A-dependent translation regulation.

No role of eIF2A in translation initiation is apparent and one limitation of the study is that the authors do not determine what function eIF2A plays in yeast.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the goal of the authors is to understand the process of mature sprout formation from mini-sprouts to develop new blood vessels during angiogenesis. For this, they use their earlier experimental setup of engineered blood vessels in combination with a modified spatio-temporal model for Notch signalling. The authors first study the role of VEGF on Tip (Delta-rich) and Stalk (Notch-rich) patterning. The Tip cells are further examined for their space-time dynamics as Mini-sprouts and mature Sprouts. The Notch signalling model is later supplemented with a phenomenological _random uniform model_ for Sprout selection as a plausible mechanism for Sprout formation from Mini-Sprouts. Finally, the authors look into the role of fibronectin in the Sprout formation process. Overall, the authors propose that VEGF interacts with Notch signalling in blood vessels to generate spatially disordered and co-localized Tip cells. VEGF and fibronectin then provide external cues to dynamically modulate mature Sprout formation from Mini-Sprouts that could control the location and density of developing blood vessels with a process that is consistent with a Turing-like mechanism.

Strengths and Weaknesses

In this manuscript, work motivation, problem definition, experimental procedures, analysis techniques, mathematical methods (including the parameters), and findings are all presented quite clearly. Moreover, the authors carefully indicate whenever they make any assumptions, and do not mix unproven hypothesis with deduced or known facts. The experimental techniques and most of the mathematical methods used in this paper are borrowed from the earlier works of the corresponding authors, and thus are not completely novel. However, the use of these ideas to provide a simple elucidation of the role of VEGF and fibronectin in Sprout formation, in an otherwise complex system, is very interesting and useful. Some of the data analysis methods presented in the paper - (i) quantification of Tip spatial patterns (Fig. 3) and (ii) Sprout temporal dynamics using Sankey diagram (Fig. 4) - seem quite novel to me in the context of Notch signalling literature. Similarly, the authors also provide a new mechanism (VEGF) to obtain disordered Delta-Notch patterning without explicitly including _noise_ in the system (Fig. 2 and Fig. S1). The authors also systematically quantify the statistics of spacing between the Sprouts and show that the Sprouts have a tendency to be away from each other, something that they could also partially recapitulate by additionally including a novel _random uniform model_ for Sprout selection (Fig. 5). Although the association between fibronectin and angiogenesis is known in the literature, in this manuscript, the authors could clearly demonstrate that fibronectin is present in high and low levels, respectively, around Sprouts and Mini-sprouts (Fig. 6). A combination of these findings could then motivate the authors to hypothesize, as mentioned above, a Turing-like mechanism for Sprout formation, something that I find interesting.

Although I find the relative simplicity of the experimental system and theoretical model and the clear findings they generate appealing, some aspects raise a few questions. The authors experimentally find 20 +- 0.08 percent of Tip cells in the model blood-vessels that is consistent with the salt-and-pepper pattern seen in Notch signalling model (~25 %). However, it is not clear to me if the reverse is true, i.e., 25% of Tip cells automatically imply a salt-and-pepper pattern - the authors do not seem to provide a direct experimental evidence. Furthermore, the authors use their Notch signalling model on a regular hexagonal lattice, but there is a large variability in the cell sizes (Fig. 3) in the experimental system. Since it is observed in the literature that signalling depends on the contact area between the neighbouring cells, it is not clear how that would affect the findings presented in this paper. Similarly, since some of the cells are quite small compared to the others, I worry how appropriate it is to express the distance between the Tip cells in terms of _cell numbers_ (Fig. 3). Regarding Sprout classification, as per Table 1, a bridge of two cells is formed as per early-stage-I mechanism for Sprout. On the other hand, the entire data interpretation of experiments seems to be based on early Stage II and matured stage in that same table (also Figs. 3 and 4) in which only one Tip cell seems to be counted per mature Sprout. However, if some Sprouts are formed via early stage-I mechanism, a projection in 2D for analysis would give a count of __two__ adjacent Tip cells, but corresponding to a __single__ Sprout. It could be possible that the presence of such two-cell Sprouts affects the statistics of inter-Sprout distances (Fig. 5). Finally, I find the proposed mechanism of Sprout formation dynamics to be somewhat unsatisfactory. Other than the experimental evidence regarding the spacing of Sprouts and the fibronectin levels around Sprouts and Mini-sprouts (Figs. 4 and 5), there is very little evidence to support the hypothesis about a Turing-like mechanism for Sprouting. Moreover, it seems to me that Turing patterns can appear in a wide variety of settings and could be applied to the current problem in an abstract manner without making any meaningful connections with the system variables. Also, from a modeling point of view, cell migration and mechanics, are expected to take a major part in Sprout formation, while cell division and inclusion would most likely influence Tip-Stalk cell formation. However, it seems that in the present work, these effects are coarse-grained into Notch signalling parameters and the Sprout selection model, thus making any experimental connection quite vague.

Overall Assessment

I feel that the authors, on the whole, do achieve their main goals. Although I have a few concerns that I have raised above, overall, I find the work presented in this manuscript to be a solid addition to the broad field of collective cell dynamics. The authors use well established experimental and mathematical methods while adding a few novel analysis techniques and modeling ideas to provide a compelling, albeit incomplete, picture of Sprout formation during angiogenesis. While the direct application of this work in the context of angiogenesis is obvious, the broad set of ideas and techniques (discussed above) in this work would also be useful to researchers who work on Notch signalling in morphogenesis, collective cell migration, and epithelial-mesenchymal-transition.

Reviewer #1 (Public Review):

The authors succeeded in establishing experimental and mathematical models for the formation of new blood vessels. The experimental model relies on temporal imaging of multilcellular projections and lumen formation from a single blood vessel embedded in an engineered extracellular matrix. The mathematical model combines both discrete and continuum elements. It would be helpful to understand how the authors came up with phenotypic classes for analyzing their live imaging data. On the modeling side, it would be useful to see whether the claims about Turing patterns could be supported by either a mean-field model or a more thorough parametric analysis of the discreet continuum model. The authors did a good job in comparing their VEGF/Notch mechanism to the EGF/Notch vulval patterning mechanism in C. elegans. The authors might want to look into the literature from studies of the tracheal patterning system in Drosophila when the combined actions of the FGF and Notch signaling specify tip and stalk cells. The similarities are quite striking and are worth noting.

Reviewer #1 (Public Review):

In their study, Osorio-Valeriano and colleagues seek to understand how bacterial-specific polymerizing proteins called bactofilins contribute to morphogenesis. They do this primarily in the stalked budding bacterium Hyphomonas neptunium, with supporting work in a spiral-shaped bacterium, Rhodospirillum rubrum. Overall the study incorporates bacterial genetics and physiology, imaging, and biochemistry to explore the function of bactofilins and cell wall hydrolases that are frequently encoded together within an operon. They demonstrate an important, but not essential, function for BacA in morphogenesis of H. neptunium. Using biochemistry and imaging, they show that BacA can polymerize and that its localization in cells is dynamic and cell-cycle regulated. They further demonstrate that BacA likely limits movement of the elongasome into the stalk, spatially confining its activity. The authors then focus on lmdC, which encodes a putative M23 endopeptidase upstream of bacA in H. neptunium, and find that is essential for viability. The purified LmdC C-terminal domain could cleave E. coli peptidoglycan in vitro suggesting that it is a DD-endopeptidase. LmdC interacts directly with BacA in vitro and co-localizes with BacA in cells. To expand their observations, the authors then explore a related endopeptidase/bactofilin pair in R. rubrum; those observations support a function for LmdC and BacA in R. rubrum morphogenesis as well.

An overall strength of this study is the breadth and completeness of approaches used to assess bactofilin and endopeptidase function in cells and in vitro. The authors establish a clear function for BacA in morphogenesis in two bacterial systems, and demonstrate a physical relationship between BacA and the cell wall hydrolase LmdC that may be broadly conserved. The eventual model the authors favor for BacA regulation of morphogenesis in H. neptunium is that it serves as a diffusion barrier and limits movement of morphogenetic machinery like the elongasome into the elongating stalk and/or bud.

The data presented illuminate aspects of bacterial morphogenesis and the physical and functional relationship between polymerizing proteins and cell wall enzymes in bacteria, a recurring theme in bacterial cell biology with a variety of underlying mechanisms. Bactofilins in particular are relatively recently discovered and any new insights into their functions and mechanisms of action are valuable. The findings presented here are likely to interest those studying bacterial morphogenesis, peptidoglycan, and cytoskeletal function.

Reviewer #2 (Public Review):

This is an excellent study. It starts with the identification of two bactofilins in H. neptunium, a demonstration of their important role for the determination of cell shape and discovery of an associated endopeptidase to provide a convincing model for how these two classes of proteins interact to control cell shape. This model is backed up by a quantitative characterisation of their properties using high-resolution imaging and image analysis methods.

Overall, all evidence is very convincing and I do not have many recommendations on how to improve the manuscript.

In my opinion, there are only two issues that I have with the paper:

1. The single particle dynamics of BacA is presented and analysed and I would like to give some suggestions on how to maybe extract even more information from the already acquired data:

1.1. Presentation: Figure 5A is only showing projections of single particle time-lapse movies. To convince the reader that it was indeed possible to detect single molecules it would be helpful if the authors present individual snapshots and intensity traces. In case of single molecules these will show step wise bleaching<br /> 1.2. Analysis: Figure 5B and Supplement Figure 1 are showing the single particle tracking results, revealing that there are two populations of BacA-YFP in the cell. However, this data does not show if individual BacA particles transition between these two populations or not. A more detailed analysis of the existing data, where one can try to identify confinement events in single particle trajectories could be very revealing and help to understand the behaviour of BacA in more detail.

2. The title of Fig. 3 says that BacA and BacD copolymerise, however, the data presented to confirm this conclusions is actually rather weak. First, the Alphafold prediction does not show the co-polymer, and second, the in vitro polymerisation experiments were only done with BacA in the absence of BacD. Accordingly, the only evidence that supports this is their colocalization in fluorescence microscopy. I suggest to either weaken the statement or change the title and add more evidence.

Finally, did the authors think about biochemical experiments to study the interaction between the cytoplasmic part of LmdC and the bactofilins? These could further support their model.

Joint Public Review:

Summary:

This paper reports how mycobacterial cAMP level is increased under stressful conditions and that the increase is important in the survival of the bacterium in animal hosts.

Strengths:

The authors show that under different stresses the response regulator PhoP represses a phosphodiesterase (PDE) that degrades cAMP specifically. Identification of a PDE specific to cAMP is significant progress in understanding Mtb pathogenesis. An increase in cAMP apparently increases bacterial survival upon infection. On the practical side, the reduction of cAMP by increasing PDE can be a means to attenuate the growth of the bacilli. The results have wider implications since PhoP is implicated in controlling diverse mycobacterial stress responses and many bacterial pathogens modulate host cell cAMP level. The results here are straightforward, internally consistent, and of both theoretical and applied interests.

Weaknesses:

Repression of PDE promoter by binding of phosphorylated PhoP could have been shown at higher precision. The binding is now somewhere along a roughly 500 bp region. Although the regulation of PDE is shown to be by transcriptional repression only, it has been described as a homeostatic mechanism. The latter would have required a demonstration of both repression and activation by negative feedback.

Reviewer #1 (Public Review):

The paper aims to determine the impact of forest cover and fragmentation on the prevalence of malaria in non-human primates. The paper uses existing spatial datasets, as well as data obtained through published studies on zoonotic malaria. The findings of this study are important, as forest loss is still occurring in the tropics which will impact human infections of zoonotic malaria.

Reviewer #2 (Public Review):

This is the first comprehensive study aimed at assessing the impact of landscape modification on the prevalence of P. knowlesi malaria in non-human primates in Southeast Asia. This is a very important and timely topic both in terms of developing a better understanding of zoonotic disease spillover and the impact of human modification of landscape on disease prevalence.

This study uses the meta-analysis approach to incorporate the existing data sources into a new and completely independent study that answers novel research questions linked to geospatial data analysis. The challenge, however, is that neither the sampling design of previous studies nor their geospatial accuracy are intended for spatially-explicit assessments of landscape impact. On the one hand, the data collection scheme in existing studies was intentionally opportunistic and does not represent a full range of landscape conditions that would allow for inferring the linkages between landscape parameters and P. knowlesi prevalence in NHP across the region as a whole. On the other hand, the absolute majority of existing studies did not have locational precision in reporting results and thus sweeping assumptions about the landscape representation had to be made for the modeling experiment. Finally, the landscape characterization was oversimplified in this study, making it difficult to extract meaningful relationships between the NHP/human intersection on the landscape and the consequences for P. knowlesi malaria transmission and prevalence.

Despite study limitations, the authors point to the critical importance of understanding vector dynamics in fragmented forested landscapes as the likely primary driver in enhanced malaria transmission. This is an important conclusion particularly when taken together with the emerging evidence of substantially different mosquito biting behaviors than previously reported across various geographic regions.

Another important component of this study is its recognition and focus on the value of geospatial analysis and the availability of geospatial data for understanding complex human/environment interactions to enable monitoring and forecasting potential for zoonotic disease spillover into human populations. More multi-disciplinary focus on disease modeling is of crucial importance for current and future goals of eliminating existing and preventing novel disease outbreaks.

Reviewer #1 (Public Review):

Summary

This article by Zhai et al, investigates sterol transport in bacteria. Synthesis of sterols is rare in bacteria but occurs in some, such as, M capsulatus where the sterols are found primarily in the outer membrane. In a previous paper the authors discovered an operon consisting of five genes, with two of these genes encoding demethylases involved in sterol demethylation. In this manuscript the authors set out to investigate the functions of the other three genes in the operon. Interestingly, through a bioinformatic analysis they show that they are an inner membrane transporter of the RND family, a periplasmic binding protein and an outer membrane associated protein, all potentially involved with lipid transport, so providing a means of transporting the lipids to the outer membrane. These proteins are then extensively investigated through lipid pulldowns, binding analysis on all three, and X-ray crystallography and docking of the latter two.

Strengths<br /> The lipid pulldowns and associated MST binding analysis are convincing, clearly showing that sterols are able to bind to these proteins. The structures of BstB and BstC are high resolution with excellent maps that allow docking studies to be carried out. These structures are distinct from sterol binding proteins in eukaryotes.

Weaknesses<br /> While the docking and molecular dynamics studies are consistent with the binding of sterols to BstB and BstC, this is not backed up particularly well. Their discussion, however, is measured and clearly provides a strong case for further investigation.

Reviewer #2 (Public Review):

Summary:<br /> In eukaryotes, sterols are crucial for signaling and regulating membrane fluidity, however, the mechanism governing cholesterol production and transport across the cell membrane in bacteria remains enigmatic. The manuscript by Zhai et al. sheds light on this topic by uncovering three potential cholesterol transport proteins. Through comprehensive bioinformatics analysis, the authors identified three genes bstA, bstB, and bstC encoding proteins which share homology with transporters, periplasmic binding proteins, and periplasmic components superfamily, respectively. Furthermore, the authors confirmed the specific interaction between these three proteins and C-4 methylated sterols and determined the structures of BstB and BstC. Combining these structural insights with molecular dynamics simulation, they postulated several plausible substrate binding sites within each protein.

Strengths:<br /> The authors have identified 3 proteins that seem likely to be involved in sterol transport between the inner and outer membrane. The structures are of high quality, and the sterol binding experiments support a role for these proteins in sterol transport.

Weaknesses:<br /> While the author's model is very plausible, direct evidence for a role of BstABC in transport, or that the 3 proteins function together in a single pathway, is limited.

Reviewer #3 (Public Review):

Summary:<br /> The work in this manuscript builds on prior efforts by this team to understand how sterols are biosynthesized and utilized in bacteria. The study reports a new function for three genes encoded near sterol biosynthesis enzymes, suggesting the resulting proteins function as a sterol transport system. Biochemical and structural characterization of the two soluble components of the pathway establishes that both proteins can bind sterols, with a preference for 4-methylated derivatives. High-resolution x-ray structures of the apoproteins reveal hydrophobic cavities of the appropriate size to accommodate these substrates. Docking and molecular dynamics simulations confirm this observation and provide specific insights into residues involved in substrate binding.

Strengths:<br /> The manuscript is comprehensive and well-written. The annotation of a new function in a set of proteins related to bacterial sterol usage is exciting and likely to enable further study of this phenomenon - which is currently not well understood. The work also has implications for improving our understanding of lipid usage in general among bacterial organisms.

Reviewer #1 (Public Review):

Summary:

This paper makes important contributions to the structural analysis of the DNA replication-linked nucleosome assembly machine termed Chromatin Assembly Factor-1 (CAF-1). The authors focus on the interplay of domains that bind DNA, histones and replication clamp protein PCNA.

Strengths:<br /> The authors analyze soluble complexes containing full-length versions of all three fission yeast CAF-1 subunits, an important accomplishment given that many previous structural and biophysical studies have focused on truncated complexes. New data here supports previous experiments indicating that the KER domain is a long alpha helix that binds DNA. Via NMR, the authors discover structural changes at the histone binding site, defined here with high resolution. Most strikingly, the experiments here show that for the S. pombe CAF-1 complex, that the WHD domain at the C-terminus of the large subunit lacks DNA binding activity observed in the human and budding yeast homologs, indicating a surprising divergence in the evolution of this complex. Together, these are important contributions to the understanding of how the CAF-1 complex works.

Weaknesses:<br /> 1. Given the strong structural predication about the roles of residues L359 and F380 (Fig. 2f), mutation of these residues would be the definitive test of their contribution to histone binding.

2. Could it be that the apparent lack of histone deposition by the delta-WHD mutant complex occurs because this mutant complex is unstable when added to the Xenopus extract?

Reviewer #2 (Public Review):

Summary:<br /> The authors describe the structure-functional relationship of domains in S. pombe CAF-1, which promotes DNA replication-coupled deposition of histone H3-H4 dimer. The authors nicely showed that the ED domain with an intrinsically disordered structure binds to histone H3-H4, that the KER domain binds to DNA and that, in addition to a PIP box, the KER domain also contributes to the PCNA binding. The ED and KER domains as well as the WHD domain are essential for nucleosome assembly in vitro. The ED, KER domains and the PIP box are important for the maintenance of heterochromatin.

Strengths:<br /> The combination of structural analysis using NMR and Alphafold2 modeling with biophysical and biochemical analysis provided strong evidence on the role of the different domain structures of the large subunit of SpCAF-1, spPCF-1 in the binding to histone H3-H4, DNA as well as PCNA. The conclusion was further supported by genetic analysis of the various pcf1 mutants. The large amounts of data provided in the paper support the authors' conclusion very well.

Weaknesses:

Reviewer #3 (Public Review):

Summary: The study conducted by Ouasti et al. is an elegant investigation of fission yeast CAF-1, employing a diverse array of technologies and genetic alterations to dissect its functions and their interdependence. These functions play a critical role in specifying interactions vital for DNA replication, heterochromatin maintenance, and DNA damage repair, and their dynamics involve multiple interactions. The authors have extensively utilized various in vitro and in vivo tools to validate their model and emphasize the dynamic nature of this complex.

Strengths: Their work is supported by robust experimental data from multiple techniques, including NMR and SAXS, which validate their molecular model. They conducted in vitro interactions using EMSA and isothermal microcalorimetry, in vitro histone deposition using Xenopus high-speed egg extract, and systematically generated and tested various genetic mutants for functionality in in vivo assays. They successfully delineated domain-specific functions using in vitro assays and could validate their roles to large extent using genetic mutants. One significant revelation from this study is the unfolded nature of the acidic domain, observed to fold when binding to histones. Additionally, the authors also elucidated the role of the long KER helix in mediating DNA binding and enhancing the association of CAF-1 with PCNA. The paper effectively addresses its primary objective.

Weaknesses: A few relatively minor unresolved aspects persist, which, if clarified or experimentally addressed by the authors, could further bolster the study.<br /> 1. The precise function of the WHD domain remains elusive. Its deletion does not result in DNA damage accumulation or defects in heterochromatin maintenance. This raises questions about the biological significance of this domain and whether it is dispensable. While in vitro assays revealed defects in chromatin assembly using this mutant (Figure 5), confirming these phenotypes through in vivo assays would provide additional assurance that the lack of function is not simply due to the in vitro system lacking PTMs or other regulatory factors.<br /> 2. The observation of increased Pcf2-gfp foci in pcf1-ED* cells, particularly in mono-nucleated (G2-phase) and bi-nucleated cells with septum marks (S-phase), might suggest the presence of replication stress. This could imply incomplete replication in specific regions, leading to the persistence of Caf1-ED*-PCNA factories throughout the cell cycle. To further confirm this, detecting accumulated single-stranded DNA (ssDNA) regions outside of S-phase using RPA as an ssDNA marker could be informative.<br /> 3. Moreover, considering the authors' strong assertion of histone binding defects in ED* through in vitro assays (Figure 2d and S2a), these claims could be further substantiated, especially considering that some degree of histone deposition might still persist in vivo in the ED* mutant (Figure 7d, viable though growth defective double ED*+hip1D mutants). For example, the approach, akin to the one employed in Fig. 6a (FLAG-IPs of various Pcf1-FLAG-tagged mutants), could also enable a comparison of the association of different mutants with histones and PCNA, providing a more thorough validation of their findings.<br /> 4. It would be valuable for the authors to speculate on the necessity of having disordered regions in CAF1. Specifically, exploring the overall distribution of these domains within disordered/unfolded structures could provide insightful perspectives. Additionally, it's intriguing to note that the significant disparities observed among mutants (ED*, PIP*, and KER*) in in vitro assays seem to become more generic in vivo, except for the indispensability of the WHD-domain. Could these disordered regions potentially play a crucial role in the phase separation of replication factories? Considering these questions could offer valuable insights into the underlying mechanisms at play.

Reviewer #1 (Public Review):

The study investigates the role of PARP-1 in transcriptional regulation. Biochemical and ChIP-seq analyses demonstrate specific binding of PARP-1 to active histone marks, particularly H4K20me, in polytene chromosomes of Drosophila third instar larvae. Under heat stress conditions, PARP-1's dynamic repositioning from the Hsp70 promoter to its gene body is observed, facilitating gene activation. PARP-1, in conjunction with PR-Set7, plays a crucial role in the activation of Hsp70 and a subset of heat shock genes, coinciding with an increase in H4K20me1 levels at these gene loci. This study proposes that H4K20me1 is a key facilitator of PARP-1 binding and gene regulation. However, there are several critical concerns that are yet to be addressed. The experimental validation and demonstration of results in the main manuscript are scant. Recent developments in the area are omitted, as an important publication hasn't been discussed anywhere in the work (PMID: 36434141). The proposed mechanism operates quite selectively, and any extrapolations require intensive scientific evidence.

Major Comments:

1. PARP1 hypomorphic mutant validation data must be provided at RNA levels as the authors have mentioned about its global reduction in RNA levels.

2. The authors should provide immunoblot data for global Poly (ADP) ribosylation levels in PARP1 hypomorphic mutant condition as compared to the control. They must also provide the complete details of the mouse anti-pADPr antibody used in their immunoblot in Figure 5B.

3. PR-Set7 mutant validation results should be provided in the main manuscript, as done by the authors using qRT-PCR. Also, immunoblot data for the PR-set7 null condition should be supplemented in the main manuscript as the authors have already mentioned their anti-PR-Set7 (Rabbit, 1:1000, Novus Biologicals, 44710002) antibody in the materials and methods section.

4. The authors have probably missed out on a very important recent report (PMID: 36434141), suggesting the antagonistic nature of the PARP1 and PR-SET7 association. In light of these important observations, the authors must check for the levels of PR-Set7 in PARP1 hypomorphic conditions.

5. Also, the results of the aforementioned study should be adequately discussed in the present study along with its implications in the same.

6. Gene transcriptional activation requires open chromatin and RNA polymerase II binding to the promoter. Since, differentially expressed genes in both PR-Set7 null and PARP1 hypomorph mutants, co-enriched with PARP-1 and H4K20me1 were mainly upregulated, the authors should provide RNA polymerase II occupancy data of these genes via RNA-Pol II ChIP-seq to further attest their claims.

7. As discussed in Figure 4, the authors found transcriptional activation of group B genes even after a significant reduction of H3K20me1 in their gene body after heat shock. Given the dynamic equilibrium shift in epigenetic marks that regulate gene expression and their locus-specific transcriptional regulation, the authors should further look for the enrichment of other epigenetic marks and even H4K20me1 specific demethylases such as PHF8 (PMID: 20622854), and their cross-talk with PARP1 to further bridge the missing links of this tale. This will add more depth to this work.

Reviewer #2 (Public Review):

Summary:<br /> This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:<br /> The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

3) Parp1 directly binds H4K20me in vitro.

Weaknesses:<br /> 1) The histone array experiment in Fig1 strongly suggests that PARP binds to all mono-methylated histone residues (including H3K27, which is not discussed). Phosphorylation of nearby residues sometimes blocks this binding (S10 and T11 modifications block binding to K9me1, and S28P blocks binding to K27me1). However, H3S3P did not block H3K4me1, which may be worth highlighting. The H3K9me2/3 "blocking effect" is not nearly as strong as some of these other modifications, yet the authors chose to focus on it. Rather than focusing on subtle effects and the possibility that PARP "reads" a "histone code," the authors should consider focusing on the simple but dramatic observation that PARP binds pretty much all mono-methylated histone residues. This result is interesting because nucleosome mono-methylation is normally found on nucleosomes with high turnover rates (Chory et al. Mol Cell 2019)- which mostly occurs at promoters and highly transcribed genes. The author's binding experiments could help to partially explain this correlation because PARP could both bind mono-methylated nucleosomes and then further promote their turnover and lower methylation state.

2) The RNAseq analysis of Parp1/PR-Set7 mutants is reasonable, but there is a caveat to the author's conclusion (Line 251): "our results indicate H4K20me1 may be required for PARP-1 binding to preferentially repress metabolic genes and activate genes involved in neuron development at co-enriched genes." An alternative possibility is that many of the gene expression changes are indirect consequences of altered development induced by Parp1 or PR-Set7 mutants. For example, Parp1 could activate a transcription factor that represses the metabolic genes that they mention. The authors should consider discussing this possibility.

3) The section on the inducibility of heat shock genes is interesting but missing an important control that might significantly alter the author's conclusions. Hsp23 and Hsp83 (group B genes) are transcribed without heat shock, which likely explains why they have H4K20me without heat shock. The authors made the reasonable hypothesis that this H4K20me would recruit Parp-1 upon heat shock (line 270). However, they observed a decrease of H4K20me upon heat shock, which led them to conclude that "H4K20me may not be necessary for Parp1 binding/activation" (line 275). However, their RNA expression data (Fig4A) argues that both Parp1 and H40K20me are important for activation. An alternative possibility is that group B genes indeed recruit Parp1 (through H4K20me) upon heat shock, but then Parp1 promotes H3/H4 dissociation from group B genes. If Parp1 depletes H4, it will also deplete H4K20me1. To address this possibility, the authors should also do a ChIP for total H4 and plot both the raw signal of H4K20me1 and total H4 as well as the ratio of these signals. The authors could also note that Group A genes may similarly recruit Parp1 and deplete H3/H4 but with different kinetics than Group B genes because their basal state lacks H4K20me/Parp1. To test this possibility, the authors could measure Parp association, H4K20methylation, and H4 depletion at more time points after heat shock at both classes of genes.

Reviewer #1 (Public Review):

Summary:<br /> Ngoune et al. present compelling evidence that Slender cells are challenged to infect tsetse flies. They explore the experimental context of a recent important paper in the field, Schuster et al., that presents evidence suggesting the proliferative Slender bloodstream T.brucei can infect juvenile tsetse flies. Schuster et al. was disruptive to the widely accepted paradigm that the Stumpy bloodstream form is solely responsible for tsetse infection and T.brucei transmission potential.

Evidence presented here shows that in all cases, Stumpy form parasites are exponentially more capable of infecting tsetse flies. They further show that Slender cells do not infect mature flies.

However, they raise questions of immature tsetse immunological potential and field transmission potential that their experiments do not address. Specifically, they do not show that teneral tsetse flies are immunocompromised, that tsetse flies must be immunocompromised for Slender infection nor that younger teneral tsetse infection is not pertinent to field transmission.

Strengths:<br /> Experimental Design is precise and elegant, outcomes are convincing. Discussion is compelling and important to the field. This is a timely piece that adds important data to a critical discussion of host:parasite interactions, of relevance to all parasite transmission.

Weaknesses:<br /> As above, the authors dispute the biological relevance of teneral tsetse infection in the wild, without offering evidence to the contrary. Statements need to be softened for claims regarding immunological competence or relevance to field transmission.

Reviewer #2 (Public Review):

Summary:<br /> In contrast to the recent findings reported by Schuster S et al., this brief paper presents evidence suggesting that the stumpy form of T. brucei is likely the most pre-adapted form to progress through the life cycle of this parasite in the tsetse vector.

Strengths:<br /> One significant experimental point is that all fly infection experiments are conducted in the absence of "boosting" metabolites like GlcNAc or S-glutathione. As a result, flies infected with slender trypanosomes present very low or nonexistent infection rates. This provides important experimental evidence that the findings of Schuster S and colleagues may need to be revisited.

Weaknesses:<br /> However, I believe the authors should have included their own set of experiments demonstrating that the presence of these metabolites in the infectious bloodmeal enhances infection rates in flies receiving blood meals containing slender trypanosomes. Considering the well-known physiological variabilities among flies from different facilities, including infection rates, this would have strengthened the experimental evidence presented by the authors.

Reviewer #3 (Public Review):

The dogma in the Trypanosome field is that transmission by Tsetse flies is ensured by stumpy forms. This has been recently challenged by the Engstler lab (Schuster et al. ), who showed that slender forms can also be transmitted by teneral flies. In this work, the authors aimed to test whether transmission by slender forms is possible and frequent. The authors observed that most stumpy forms infections with teneral and adult flies were successful while only 1 out of 24 slender form infections were successful.

In this revised version of the manuscript, the authors made some text changes and included statistical testing as a new section of the Materials and Methods. It seems the comparison of midgut infection in adult vs teneral flies was significant in most of the conditions. However, the critical comparison is still missing: within each type of fly (adult or teneral), was the MG infection significantly different between slender and stumpy forms?

Given no additional experiments were performed, it remains unknown why this work and Schuster et al. reached different conclusions. As a result it remains unclear in which conditions slender forms could be important for transmission. Several variables could explain differences between the two groups: the strain used, the presence or absence of N-acetylglucosamine and/or glutathione, how Tsetse colonies were maintained, thorough molecular and cellular characterisation of slender and stumpy forms (to avoid using intermediate forms as slender forms), comparison to recent field parasite strains.

Joint Public Review:

The authors develop reporter constructs in E. coli that are repressed by the mammalian Musashi-1 (MSI-1) RNA-binding protein. Using a set of rigorously controlled experiments, the authors convincingly show that MSI-1 can be directed to control translation, and that translational control by MSI-1 can be modulated allosterically by oleic acid. This is a potentially useful tool for synthetic biologists, with the advantage over transcriptional regulation that one gene in an operon could be targeted. The authors' MSI-1-regulated reporter constructs could also be useful for mechanistic studies of MSI-1.

The authors initial construct design led to only weak regulation by MSI-1, presumably because the MSI-1 binding sites were not suitably positioned to repress translation initiation. A more rationally designed construct led to considerably greater repression. A minor weakness of the paper is that the authors used their initial, weakly regulated construct to assess the effect of MSI-1 binding site mutations and for their mathematical modeling; these experiments would be better suited to the more strongly regulated construct.

Reviewer #1 (Public Review):

Summary:<br /> The authors aim to address a critical challenge in the field of bioinformatics: the accurate and efficient identification of protein binding sites from sequences. Their work seeks to overcome the limitations of current methods, which largely depend on multiple sequence alignments or experimental protein structures, by introducing GPSite, a multi-task network designed to predict binding residues of various molecules on proteins using ESMFold.

Strengths:<br /> 1. Benchmarking. The authors provide a comprehensive benchmark against multiple methods, showcasing the performances of a large number of methods in various scenarios.

2. Accessibility and Ease of Use. GPSite is highlighted as a freely accessible tool with user-friendly features on its website, enhancing its potential for widespread adoption in the research community.

Weaknesses:<br /> 1. Lack of Novelty. The method primarily combines existing approaches and lacks significant technical innovation. This raises concerns about the original contribution of the work in terms of methodological development. Moreover, the paper reproduces results and analyses already presented in previous literature, without providing novel analysis or interpretation. This further diminishes the contribution of this paper to advancing knowledge in the field.

2. Benchmark Discrepancies. The variation in benchmark results, especially between initial comparisons and those with PeSTo. GPSite achieves a PR AUC of 0.484 on the global benchmark but a PR AUC of 0.61 on the benchmark against PeSTo. For consistency, PeSTo should be included in the benchmark against all other methods. It suggests potential issues with the benchmark set or the stability of the method. This inconsistency needs to be addressed to validate the reliability of the results.

3. Interface Definition Ambiguity. There is a lack of clarity in defining the interface for the binding site predictions. Different methods are trained using varying criteria (surfaces in MaSIF-site, distance thresholds in ScanNet). The authors do not adequately address how GPSite's definition aligns with or differs from these standards and how this issue was addressed. It could indicate that the comparison of those methods is unreliable and unfair.

While GPSite demonstrates the potential to surpass state-of-the-art methods in protein binding site prediction, the evidence supporting these claims seems incomplete. The lack of methodological novelty and the unresolved questions in benchmark consistency and interface definition somewhat undermine the confidence in the results. Therefore, it's not entirely clear if the authors have fully achieved their aims as outlined.

The work is useful for the field, especially in disease mechanism elucidation and novel drug design. The availability of genome-scale binding residue annotations GPSite offers is a significant advancement. However, the utility of this tool could be hampered by the aforementioned weaknesses unless they are adequately addressed.

Reviewer #2 (Public Review):

Summary:<br /> This work provides a new framework, "GPsite" to predict DNA, RNA, peptide, protein, ATP, HEM, and metal ions binding sites on proteins. This framework comes with a webserver and a database of annotations. The core of the model is a Geometric featurizer neural network that predicts the binding sites of a protein. One major contribution of the authors is the fact that they feed this neural network with predicted structure from ESMFold for training and prediction (instead of native structure in similar works) and a high-quality protein Language Model representation. The other major contribution is that it provides the public with a new light framework to predict protein-ligand interactions for a broad range of ligands.

The authors have demonstrated the interest of their framework with mostly two techniques: ablation and benchmark.

Strengths:<br /> The performance of this framework as well as the provided dataset and web server make it useful to conduct studies.

The ablations of some core elements of the method, such as the protein Language Model part, or the input structure are very insightful and can help convince the reader that every part of the framework is necessary. This could also guide further developments in the field. As such, the presentation of this part of the work can hold a more critical place in this work.

Weaknesses:<br /> Overall, we can acknowledge the important effort of the authors to compare their work to other similar frameworks. Yet, the lack of homogeneity of training methods and data from one work to the other makes the comparison slightly unconvincing, as the authors pointed out. Overall, the paper puts significant effort into convincing the reader that the method is beating the state of the art. Maybe, there are other aspects that could be more interesting to insist on (usability, interest in protein engineering, and theoretical works).

Reviewer #3 (Public Review):

Summary<br /> The authors of this work aim to address the challenge of accurately and efficiently identifying protein binding sites from sequences. They recognize that the limitations of current methods, including reliance on multiple sequence alignments or experimental protein structure, and the under-explored geometry of the structure, which limit the performance and genome-scale applications. The authors have developed a multi-task network called GPSite that predicts binding residues for a range of biologically relevant molecules, including DNA, RNA, peptides, proteins, ATP, HEM, and metal ions, using a combination of sequence embeddings from protein language models and ESMFold-predicted structures. Their approach attempts to extract residual and relational geometric contexts in an end-to-end manner, surpassing current sequence-based and structure-based methods.

Strengths<br /> 1. The GPSite model's ability to predict binding sites for a wide variety of molecules, including DNA, RNA, peptides, and various metal ions.<br /> 2. Based on the presented results, GPSite outperforms state-of-the-art methods in several benchmark datasets.<br /> 3. GPSite adopts predicted structures instead of native structures as input, enabling the model to be applied to a wider range of scenarios where native structures are rare.<br /> 4. The authors emphasize the low computational cost of GPSite, which enables rapid genome-scale binding residue annotations, indicating the model's potential for large-scale applications.

Weaknesses<br /> 1. One major advantage of GPSite, as claimed by the authors, is its efficiency. Although the manuscript mentioned that the inference takes about 5 hours for all datasets, it remains unclear how much improvement GPSite can offer compared with existing methods. A more detailed benchmark comparison of running time against other methods is recommended (including the running time of different components, since some methods like GPSite use predicted structures while some use native structures).<br /> 2. Since the model uses predicted protein structure, the authors have conducted some studies on the effect of the predicted structure's quality. However, only the 0.7 threshold was used. A more comprehensive analysis with several different thresholds is recommended.<br /> 3. To demonstrate the robustness of GPSite, the authors performed a case study on human GR containing two zinc fingers, where the predicted structure is not perfect. The analysis could benefit from more a detailed explanation of why the model can still infer the binding site correctly even though the input structural information is slightly off.<br /> 4. To analyze the relatively low AUC value for protein-protein interactions, the authors claimed that it is "due to the fact that protein-protein interactions are ubiquitous in living organisms while the Swiss-Prot function annotations are incomplete", which is unjustified. It is highly recommended to support this claim by showing at least one example where GPSite's prediction is a valid binding site that is not present in the current Swiss-Prot database or via other approaches.<br /> 5. The authors reported that many GPSite-predicted binding sites are associated with known biological functions. Notably, for RNA-binding sites, there is a significantly higher proportion of translation-related binding sites. The analysis could benefit from a further investigation into this observation, such as the analyzing the percentage of such interactions in the training site. In addition, if there is sufficient data, it would also be interesting to see the cross-interaction-type performance of the proposed model, e.g., train the model on a dataset excluding specific binding sites and test its performance on that class of interactions.

Reviewer #1 (Public Review):

Summary:<br /> The authors have developed a zebrafish model of glioblastoma and characterized this, with a particular focus on the role of recruited myeloid cells in the tumours. Microglia/macrophages in the tumours are proposed to have an inflammatory phenotype and are engaged in phagocytosis. Knockout of Irf7 and Irf8 genes enhanced tumour initiation. Depleting mature myeloid cell types with chlodronate also enhanced tumour intitiation. It is proposed that in early-stage tumours, microglia/macrophages have tumour suppressive activity.

Strengths:<br /> The authors have generated a novel glioblastoma model in zebrafish. Two key strengths of the zebrafish model are that early-stage tumours can be studied and in vivo visualization can be readily performed. The authors show a video of microglia/macrophages adopting the ameboid phenotype in tumours (as is observed in human tumours) and engaging in phagocytosis. Video 1 was very impressive in my opinion and shows the model is a very useful tool to study microglia/macrophage:glioblastoma cell interactions. The irf7/irf8 knockdown and the chlodronate experiments are consistent with a role for mature myeloid cells in suppressing tumour initiation, suggesting that the model may also be very valuable in understanding immune surveillance in glioblastoma initiation.

Weaknesses:<br /> EGFRvIII is mainly associated with the classical subtype, so the mesenchymal subtype might be unexpected here. This could be commented on. Some more histologic characterization of the tumours would be helpful. Are they invasive, do larger tumours show necrosis and microvascular proliferation? This would help with understanding the full potential of the new model. Current thinking in established human glioblastoma is that the M1/M2 designations for macrophages are not relevant, with microglia macrophage populations showing a mixture of pre- and anti-inflammatory features. Ideally, there would be a much more detailed characterization of the intratumoral microglia/macrophage population here, as single markers can't be relied upon. Phagocytosis could have antitumour effects through the removal of live cancer cells, or could be cancer-promoting if apoptotic cancer cells are being rapidly cleared with concomitant activation of an immunosuppressive phenotype in the phagocytes (i.e. efferocytosis). It may be possible to distinguish between these two types of phagocytosis experimentally. Do the irf7/8 and chlodronate experiments distinguish between effects on microglia/macrophages and dendritic cells?

Reviewer #2 (Public Review):

Summary:<br /> Glioblastoma is a common primary brain cancer, that is difficult to treat and has a low survival rate. The lack of genetically tractable and immunocompetent vertebrate animal models has prevented the discovery of new therapeutic targets and limited efforts for screening pharmaceutical agents for the treatment of the disease. Here Weiss et al., express oncogenic variants frequently observed in human glioblastoma within zebrafish lacking the tumor suppressor TP53 to generate a patient-relevant in vivo model. The authors demonstrate that loss of TP53 and overexpression of EGFR, PI3KCA, and mScarlet (p53EPS) in neural progenitors and radial glia leads to visible fluorescent brain lesions in live zebrafish. The authors performed RNA expression analysis that uncovered a molecular signature consistent with human mesenchymal glioblastoma and identified gene expression patterns associated with inflammation. Live imaging revealed high levels of immune cell infiltration and associations between microglia/macrophages and tumor cells. To define functional roles for regulators of inflammation on specific immune-related responses during tumorigenesis, transient CRISPR/Cas9 gene targeting was used to disrupt interferon regulator factor proteins and showed Inflammation-associated irf7 and irf8 are required to inhibit p53EPS tumor formation. Further, experiments to deplete the macrophages using clodronate liposomes suggest that macrophages contribute to the suppression of tumor engraftment following transplantation. The authors' conclusions are largely supported by the data and the experiments are thoroughly controlled throughout. Taken together, these results provide new insights into the regulation of glioblastoma initiation and growth by the surrounding microenvironment and provide a novel in vivo platform for the discovery of new molecular mechanisms and testing of therapeutics.

Strengths/Weaknesses:<br /> The authors convincingly show that co-injection of activated human EGFRviii, PI3KCAH1047R, and mScarlet into TP53 null zebrafish promotes the formation of fluorescent brain lesions and glioblastoma-like tumor formation. The authors state that oncogenic MAPK/AKT pathway activation drives this glial-derived tumor formation. It would be important to include a wild-type or uninjected control for the pERK and pAKT staining shown in Fig1 I-K to aid in the interpretation of these results. Likewise, quantification of the pERK and pAKT staining would be useful to demonstrate the increase over WT, and would also serve to facilitate comparison with the similar staining in the KPG model (Supp Fig 2D).

The authors use a transplantation assay to further test the tumorigenic potential of dissociated cells from glial-derived tumors. Listing the percentage of transplants that generate fluorescent tumor would be helpful to fully interpret these data. Additionally, it was not clear based on the description in the results section that the transplantation assay was an "experimental surrogate" to model the relapse potential of the tumor cells. This is first mentioned in the discussion. The authors may consider adding a sentence for clarity earlier in the manuscript as it helps the reader better understand the logic of the assay.

The authors nicely show high levels of immune cell infiltration and associations between microglia/macrophages and tumor cells. However, a quantification of the emergence of macrophages over time in relation to tumor initiation and growth would provide significant support to the observations of tumor suppressive activity of the phagocytes. Along these lines, the inclusion of a statement about when leukocytes emerge during normal development would be informative for those not familiar with the zebrafish model.

From the data provided in Figure 4G and Supp Fig 7b, the authors suggest that "increased p53EPS tumor initiation following Ifr gene knock-down is a consequence of irf7 and irf8 loss-of-function in the TME". Given the importance of the local microenvironment highlighted in this study, spatial information in the form of in situ hybridization to identify the relevant location of the expression change would be important to support this conclusion.

The authors used neutral red staining that labels lysosomal-rich phagocytes to assess enrichment at the early stages of tumor initiation. The images in Figure 3 panel A should be labeled to denote the uninjected controls to aid in the interpretation of the data. In Supplemental Figure 6, the neutral red staining in the irf8 CRISPR-injected larvae looks to be increased, counter to the quantification. Can the authors comment if the image is perhaps not representative?

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors investigate a very interesting but often overlooked aspect of abstract vs. concrete processing in language. Specifically, they study if the differences in processing of abstract vs. concrete concepts in the brain are static or dependent on the (visual) context in which the words occur. This study takes a two-step approach to investigate how context might affect the perception of concepts. First, the authors analyze if concrete concepts, expectedly, activate more sensory systems while abstract concepts activate higher-order processing regions. Second, they measure the contextual situatedness vs. displacement of each word with respect to the visual scenes it is spoken in and then evaluate if this contextual measure correlates with more activation in the sensory vs. higher-order regions respectively.

Strengths:<br /> This study raises a pertinent and understudied question in language neuroscience. It also combines both computational and meta-analytic approaches.

Weaknesses:<br /> Overall, the study had many intermediary steps that required manual subsection / random sampling and variable choices (like the time lag of analysis) with almost no visualization and interpretation of how these choices affect the observed results. The approach was also roundabout.

Peaks and Valleys Analysis:<br /> 1. Doesn't this method assume that the features used to describe each word, like valence or arousal, will be linearly different for the peaks and valleys? What about non-linear interactions between the features and how they might modulate the response?<br /> 2. Doesn't it also assume that the response to a word is infinitesimal and not spread across time? How does the chosen time window of analysis interact with the HRF? From the main figures and Figures S2-S3 there seem to be differences based on the timelag.<br /> 3. Were the group-averaged responses used for this analysis?<br /> 4. Why don't the other terms identified in Figure 5 show any correspondence to the expected categories? What does this mean? Can the authors also situate their results with respect to prior findings as well as visualize how stable these results are at the individual voxel or participant level? It would also be useful to visualize example time courses that demonstrate the peaks and valleys.

Estimating contextual situatedness:<br /> 1. Doesn't this limit the analyses to "visual" contexts only? And more so, frequently recognized visual objects?<br /> 2. The measure of situatedness is the cosine similarity of GloVE vectors that depend on word co-occurrence while the vectors themselves represent objects isolated by the visual recognition models. Expectedly, "science" and the label "book" or "animal" and the label "dog" will be close. But can the authors provide examples of context displacement? I wonder if this just picks up on instances where the identified object in the scene is unrelated to the word. How do the authors ensure that it is a displacement of context as opposed to the two words just being unrelated? This also has a consequence on deciding the temporal cutoff for consideration (2 seconds).<br /> 3. While the introduction motivated the problem of context situatedness purely linguistically, the actual methods look at the relationship between recognized objects in the visual scene and the words. Can word surprisal or another language-based metric be used in place of the visual labeling? Also, it is not clear how the process identified in (2) above would come up with a high situatedness score for abstract concepts like "truth".<br /> 4. It is a bit hard to see the overlapping regions in Figures 6A-C. Would it be possible to show pairs instead of triples? Like "abstract across context" vs. "abstract displaced"? Without that, and given (2) above, the results are not yet clear. Moreover, what happens in the "overlapping" regions of Figure 3?

Miscellaneous comments:<br /> 1. In Figure 3, it is surprising that the "concrete-only" regions dominate the angular gyrus and we see an overrepresentation of this category over "abstract-only". Can the authors place their findings in the context of other studies?<br /> 2. The following line (Pg 21) regarding the necessary differences in time for the two categories was not clear. How does this fall out from the analysis method?<br /> 3. Both categories overlap **(though necessarily at different time points)** in regions typically associated with word processing.

Reviewer #2 (Public Review):

Summary:<br /> This study tests a plausible and intriguing hypothesis that one cause of the differences in the neural underpinnings of concrete and abstract words is differences in their grounding in the current sensory context. The authors reasoned that, in this case, an abstract word presented with a relevant visual scene would be processed in a more similar way to a concrete word. Typically, abstract and concrete words are tested in isolation. In contrast, this study takes advantage of naturalistic movie stimuli to assess the neural effects of concreteness in both abstract and concrete words (the speech within the film), when the visual context is more or less tied to the word meaning (measured as the similarity between the word co-occurrence-based vector for the spoken word and the average of this vector across all present objects). This novel approach allows a test of the dynamic nature of abstract and concrete word processing, and as such could extend the literature and add a useful perspective accounting for differences in processing these word types.

The critical contrasts needed to test the key hypothesis are not presented or not presented in full within the core text. To test whether abstract processing changes when in a situated context, the situated abstract condition would first need to be compared with the displaced abstract condition as in Supplementary Figure 6. Then to test whether this change makes the result closer to the processing of concrete words, this result should be compared to the concrete result. The correlations shown in Figure 6 in the main text are not focused on the differences in activity between the situated and displaced words or comparing the correlation of these two conditions with the other (concrete/abstract) condition. As such they cannot provide conclusive evidence as to whether the context is changing the processing of concrete/abstract words to be closer to the other condition. Additionally, it should be considered whether any effects reflect the current visual processing only or more general sensory processing.

Overall, the study would benefit from being situated in the literature more, including a) a more general understanding of the areas involved in semantic processing (including areas proposed to be involved across different sensory modalities and for verbal and nonverbal stimuli), and b) other differences between abstract and concrete words and whether they can explain the current findings, including other psycholinguistic variables which could be included in the model and the concept of semantic diversity (Hoffman et al.,). It would also be useful to consider whether difficulty effects (or processing effort) could explain some of the regional differences between abstract and concrete words (e.g., the language areas may simply require more of the same processing not more linguistic processing due to their greater reliance on word co-occurrence). Similarly, the findings are not considered in relation to prior comparisons of abstract and concrete words at the level of specific brain regions.

The authors use multiple methods to provide a post hoc interpretation of the areas identified as more involved in concrete, abstract, or both (at different times) words. These are designed to reduce the interpretation bias and improve interpretation, yet they may not successfully do so. These methods do give some evidence that sensory areas are more involved in concrete word processing. However, they are still open to interpretation bias as it is not clear whether all the evidence is consistent with the hypotheses or if this is the best interpretation of individual regions' involvement. This is because the hypotheses are provided at the level of 'sensory' and 'language' areas without further clarification and areas and terms found are simply interpreted as fitting these definitions. For instance, the right IFG is interpreted as a motor area, and therefore sensory as predicted, and the term 'autobiographical memory' is argued to be interoceptive. Language is associated with the 'both' cluster, not the abstract cluster, when abstract >concrete is expected to engage language more. The areas identified for both vs. abstract>concrete are distinguished in the Discussion through the description as semantic vs. language areas, but it is not clear how these are different or defined. Auditory areas appear to be included in the sensory prediction at times and not at others. When they are excluded, the rationale for this is not given. Overall, it is not clear whether all these areas and terms are expected and support the hypotheses. It should be possible to specify specific sensory areas where concrete and abstract words are predicted to be different based on a) prior comparisons and/or b) the known locations of sensory areas. Similarly, language or semantic areas could be identified using masks from NeuroSynth or traditional meta-analyses. A language network is presented in Supplementary Figure 7 but not interpreted, and its source is not given. Alternatively, there could be a greater interpretation of different possible explanations of the regions found with a more comprehensive assessment of the literature. The function of individual regions and the explanation of why many of these areas are interpreted as sensory or language areas are only considered in the Discussion when it could inform whether the hypotheses have been evidenced in the results section.

Additionally, these methods attempt to interpret all the clusters found for each contrast in the same way when they may have different roles (e.g., relate to different senses). This is a particular issue for the peaks and valleys method which assesses whether a significantly larger number of clusters is associated with each sensory term for the abstract, concrete, or both conditions than the other conditions. The number of clusters does not seem to be the right measure to compare. Clusters differ in size so the number of clusters does not represent the area within the brain well. Nor is it clear that many brain regions should respond to each sensory term, and not just one per term (whether that is V1 or the entire occipital lobe, for instance). The number of clusters is therefore somewhat arbitrary. This is further complicated by the assessment across 20 time points and the inclusion of the 'both' category. It would seem more appropriate to see whether each abstract and concrete cluster could be associated with each different sensory term and then summarise these findings rather than assess the number of abstract or concrete clusters found for each independent sensory term. In general, the rationale for the methods used should be provided (including the peak and valley method instead of other possible options e.g., linear regression).

The measure of contextual situatedness (how related a spoken word is to the average of the visually presented objects in a scene) is an interesting approach that allows parametric variation within naturalistic stimuli, which is a potential strength of the study. This measure appears to vary little between objects that are present (e.g., animal or room), and those that are strongly (e.g., monitor) or weakly related (e.g., science). Additional information validating this measure may be useful, as would consideration of the range of values and whether the split between situated (c > 0.6) and displaced words (c < 0.4) is sufficient.

Finally, the study assessed the relation of spoken concrete or abstract words to brain activity at different time points. The visual scene was always assessed using the 2 seconds before the word, while the neural effects of the word were assessed every second after the presentation for 20 seconds. This could be a strength of the study, however almost no temporal information was provided. The clusters shown have different timings, but this information is not presented in any way. Giving more temporal information in the results could help to both validate this approach and show when these areas are involved in abstract or concrete word processing. Additionally, no rationale was given for this long timeframe which is far greater than the time needed to process the word, and long after the presence of the visual context assessed (and therefore ignores the present visual context).

Reviewer #3 (Public Review):

Summary:<br /> The primary aim of this manuscript was to investigate how context, defined from visual object information in multimodal movies, impacts the neural representation of concrete and abstract conceptual knowledge. The authors first conduct a series of analyses to identify context-independent regional responses to concrete and abstract concepts in order to compare these results with the networks observed in prior research using non-naturalistic paradigms. The authors then conduct analyses to investigate whether the regional response to abstract and concrete concepts changes when the concepts are either contextually situated or displaced. A concept is considered displaced if the visual information immediately preceding the word is weakly associated with the word whereas a concept is situated if the association is high. The results suggest that, when ignoring context, abstract and concrete concepts engage different brain regions with overlap in core language areas. When context is accounted for, however, similar brain regions are activated for processing concrete and situated abstract concepts and for processing abstract and displaced concrete concepts. The authors suggest that contextual information dynamically changes the brain regions that support the representation of abstract and concrete conceptual knowledge.

Strengths:<br /> There is significant interest in understanding both the acquisition and neural representation of abstract and concrete concepts, and most of the work in this area has used highly constrained, decontextualized experimental stimuli and paradigms to do so. This manuscript addresses this limitation by using multimodal narratives which allows for an investigation of how context-sensitive the regional response to abstract and concrete concepts is. The authors characterize the regional response in a comprehensive way.

Weaknesses:<br /> The context measure is interesting, but I'm not convinced that it's capturing what the authors intended. In analysing the neural response to a single word, the authors are presuming that they have isolated the window in which that concept is processed and the observed activation corresponds to the neural representation of that word given the prior context. I question to what extent this assumption holds true in a narrative when co-articulation blurs the boundaries between words and when rapid context integration is occurring. Further, the authors define context based on the preceding visual information. I'm not sure that this is a strong manipulation of the narrative context, although I agree that it captures some of the local context. It is maybe not surprising that if a word, abstract or concrete, has a strong association with the preceding visual information then activation in the occipital cortex is observed. I also wonder if the effects being captured have less to do with concrete and abstract concepts and more to do with the specific context the displaced condition captures during a multimodal viewing paradigm. If the visual information is less related to the verbal content, the viewer might process those narrative moments differently regardless of whether the subsequent word is concrete or abstract. I think the claims could be tailored to focus less generally on context and more specifically on how visually presented objects, which contribute to the ongoing context of a multimodal narrative, influence the subsequent processing of abstract and concrete concepts.

Reviewer #1 (Public Review):

The manuscript by Wagstyl et al. describes an extensive analysis of gene expression in the human cerebral cortex and the association with a large variety of maps capturing many of its microscopic and macroscopic properties. The core methodological contribution is the computation of continuous maps of gene expression for >20k genes, which are being shared with the community. The manuscript is a demonstration of several ways in which these maps can be used to relate gene expression with histological features of the human cortex, cytoarchitecture, folding, function, development and disease risk. The main scientific contribution is to provide data and tools to help substantiate the idea of the genetic regulation of multi-scale aspects of the organisation of the human brain. The manuscript is dense, but clearly written and beautifully illustrated.

Reviewer #2 (Public Review):

This is a valuable contribution that will facilitate brain transcriptomic analyses and the joint analyses of gene expression and structural and functional imaging. The methods used are solid, and the authors conducted a wide range of analyses to demonstrate the value of the dense gene expression data.

Reviewer #1 (Public Review):

Despite numerous studies on quinidine therapies for epilepsies associated with GOF mutant variants of Slack, there is no consensus on its utility due to contradictory results. In this study Yuan et al. investigated the role of different sodium selective ion channels on the sensitization of Slack to quinidine block. The study employed electrophysiological approaches, FRET studies, genetically modified proteins and biochemistry to demonstrate that Nav1.6 N- and C-tail interacts with Slack's C-terminus and significantly increases Slack sensitivity to quinidine blockade in vitro and in vivo. This finding inspired the authors to investigate whether they could rescue Slack GOF mutant variants by simply disrupting the interaction between Slack and Nav1.6. They find that the isolated C-terminus of Slack can reduce the current amplitude of Slack GOF mutant variants co-expressed with Nav1.6 in HEK cells and prevent Slack induced seizures in mouse models of epilepsy. This study adds to the growing list of channels that are modulated by protein-protein interactions, and is of great value for future therapeutic strategies.

Reviewer #2 (Public Review):

This is a very interesting paper about the coupling of Slack and Nav1.6 and the insight this brings to the effects of quinidine to treat some epilepsy syndromes.

Slack is a sodium-activated potassium channel that is important to hyperpolarization of neurons after an action potential. Slack is encoded by KNCT1 which has mutations in some epilepsy syndromes. These types of epilepsy are treated with quinidine but this is an atypical antiseizure drug, not used for other types of epilepsy. For sufficient sodium to activate Slack, Slack needs to be close to a channel that allows robust sodium entry, like Nav channels or AMPA receptors. but more mechanistic information is not available. Of particular interest to the authors is what allows quinidine to be effective in reducing Slack.

In the manuscript, the authors show that Nav, not AMPA receptors, are responsible for Slack's sensitization to quinidine blockade, at least in cultured neurons (HeK293, primary cortical neurons). Most of the paper focuses on the evidence that Nav1.6 promotes Slack sensitivity to quinidine.

Reviewer #3 (Public Review):

Yuan et al., set out to examine the role of functional and structural interaction between Slack and NaVs on the Slack sensitivity to quinidine. Through pharmacological and genetic means they identify NaV1.6 as the privileged NaV isoform in sensitizing Slack to quinidine. Through biochemical assays, they then determine that the C-terminus of Slack physically interacts with the N- and C-termini of NaV1.6. Using the information gleaned from the in vitro experiments the authors then show that virally-mediated transduction of Slack's C-terminus lessens the extent of SlackG269S-induced seizures. These data uncover a previously unrecognized interaction between a sodium and a potassium channel, which contributes to the latter's sensitivity to quinidine.

Reviewer #1 (Public Review):

In this preprint, Zhang et al. describe a new tool for mapping the connectivity of mouse neurons. Essentially, the tool leverages the known peculiar infection capabilities of Rabies virus: once injected into a specific site in the brain, this virus has the capability to "walk upstream" the neural circuits, both within cells and across cells: on one hand, the virus can enter from a nerve terminal and infect retrogradely the cell body of the same cell (retrograde transport). On the other hand, the virus can also sometimes spread to the presynaptic partners of the initial target cells, via retrograde viral transmission.

Similarly to previously published approaches with other viruses, the authors engineer a complex library of viral variants, each carrying a unique sequence ('barcode'), so they can uniquely label and distinguish independent infection events and their specific presynaptic connections, and show that it is possible to read these barcodes in-situ, producing spatial connectivity maps. They also show that it is possible to read these barcodes together with endogenous mRNAs, and that this allows spatial mapping of cell types together with anatomical connectivity.

The main novelty of this work lies in the combined use of rabies virus for retrograde labeling together with barcoding and in-situ readout. Previous studies had used rabies virus for retrograde labeling, albeit with low multiplexing capabilities, so only a handful of circuits could be traced at the same time. Other studies had instead used barcoded viral libraries for connectivity mapping, but mostly focused on the use of different viruses for labeling individual projections (anterograde tracing) and never used a retrograde-infective virus.

The authors creatively merge these two bits of technology into a powerful genetic tool, and extensively and convincingly validate its performance against known anatomical knowledge. The authors also do a very good job at highlighting and discussing potential points of failure in the methods.

Unresolved questions, which more broadly affect also other viral-labeling methods, are for example how to deal with uneven tropism (ie. if the virus is unable or inefficient in infecting some specific parts of the brain), or how to prevent the cytotoxicity induced by the high levels of viral replication and expression, which will tend to produce "no source networks", neural circuits whose initial cell can't be identified because it's dead. This last point is particularly relevant for in-situ based approaches: while high expression levels are desirable for the particular barcode detection chemistry the authors chose to use (gap-filling), they are also potentially detrimental for cell survival, and risk producing extensive cell death (which indeed the authors single out as a detectable pitfall in their analysis). This is likely to be one the major optimisation space for future implementations of this barcoding approach.

Overall the paper is well balanced, the data are well presented and the conclusions are strongly supported by the data. Impact-wise, the method is definitely going to be very useful for the neurobiology community.

Reviewer #2 (Public Review):

Although the trans-synaptic tracing method mediated by the rabies virus (RV) has been widely utilized to infer input connectivity across the brain to a genetically defined population in mice, the analysis of labeled pre-synaptic neurons in terms of cell-type has been primarily reliant on classical low-throughput histochemical techniques. In this study, the authors made a significant advance toward high-throughput transcriptomic (TC) cell typing by both dissociated single-cell RNAseq and the spatial TC method known as BARseq to decode a vast array of molecularly labeled ("barcoded") RV vector library. First, they demonstrated that a barcoded RV vector can be employed as a simple retrograde tracer akin to AAVretro. Second, they provided a theoretical classification of neural networks at the single-cell resolution that can be attained through barcoded-RV and concluded that the identification of the vast majority (ideally 100%) of starter cells (the origin of RV-based trans-synaptic tracing) is essential for the inference of single-cell resolution neural connectivity. Taking this into consideration, the authors opted for the BARseq-based spatial TC that could, in principle, capture all the starter cells. Finally, they demonstrated the proof-of-concept in the somatosensory cortex, including infrared connectivity from 381 putative pre-synaptic partners to 31 uniquely barcoded-starter cells, as well as many insightful estimations of input convergence at the cell-type resolution in vivo. Collectively, this work will establish a cornerstone for future advancements in rabies-barcode technology.

This revised version incorporates imaging data to assess the stringency of identifying the starter cells in comparison with conventional protein-based detection methods. Additionally, it encompasses insightful discussions concerning potential limitations and offers perspectives on future improvements. The method section is systematically subdivided with subsection numbers, facilitating the cross-referencing of the corresponding sections in the main text and figure legends. I posit that adopting this stylistic approach as the standard for manuscripts delineating innovative methodological strides would be prudent. The clarity of the figure legends has been significantly enhanced, contributing to a more accessible understanding of the figure panels. In sum, this manuscript is articulate and thorough, epitomizing scientific rigor.

Reviewer #3 (Public Review):

The manuscript by Zhang and colleagues attempts to combine genetically barcoded rabies viruses with spatial transcriptomics in order to genetically identify connected pairs. The major shortcoming with the application of a barcoded rabies virus, as reported by 2 groups prior, is that with the high dropout rate inherent in single cell procedures, it is difficult to definitively identify connected pairs. By combining the two methods, they are able to establish a platform for doing that, and provide insight into connectivity, as well as pros and cons of their method, which is well thought out and balanced.

The authors did a nice job of addressing my comments which mainly centered around the presentation of data, specificity, and wording.

Reviewer #2 (Public Review):

Summary: In the revised manuscript, the authors aim to investigate brain-wide activation patterns following administration of the anesthetics ketamine and isoflurane, and conduct comparative analysis of these patterns to understand shared and distinct mechanisms of these two anesthetics. To this end, they perform Fos immunohistochemistry in perfused brain sections to label active nuclei, use a custom pipeline to register images to the ABA framework and quantify Fos+ nuclei, and perform multiple complementary analyses to compare activation patterns across groups.

In the latest revision, the authors have made some changes in response to our previous comments on how to fix the analyses. However, the revised analyses were not changed correctly and remain flawed in several fundamental ways.

Critical problems:

(1) Before one can perform higher level analyses such as hiearchal cluster or network hub (or PC) analysis, it is fundamental to validate that you have significant differences of the raw Fos expression values in the first place. First of all, this means showing figures with the raw data (Fos expression levels) in some form in Figures 2 and 3 before showing the higher level analyses in Figures 4 and 5; this is currently switched around. Second and most importantly, when you have a large number of brain areas with large differences in mean values and variance, you need to account for this in a meaningful way. Changing to log values is a step in the right direction for mean values but does not account well for differences in variance. Indeed, considering the large variances in brain areas with high mean values and variance, it is a little difficult to believe that all brain regions, especially brain areas with low mean values, passed corrections for multiple comparisons test. We suggested Z-scores relative to control values for each brain region; this would have accounted for wide differences in mean values and variance, but this was not done. Overall, validation of anesthesia-induced differences in Fos expression levels is not yet shown.

(2) Let's assume for a moment that the raw Fos expression analyses indicate significant differences. They used hierarchal cluster analyses as a rationale for examining 53 brain areas in all subsequent analyses of Fos expression following isoflurane versus home cage or ketamine versus saline. Instead, the authors changed to 201 brain areas with no validated rationale other than effectively saying 'we wanted to look at more brain areas'. And then later, when they examined raw Fos expression values in Figures 4 and 5, they assess 43 brain areas for ketamine and 20 brain areas for isoflurane, without any rationale for why choosing these numbers of brain areas. This is a particularly big problem when they are trying to compare effects of isoflurane versus ketamine on Fos expression in these brain areas - they did not compare the same brain areas.

Less critical comments:

(3) The explanation of hierarchical level's in lines 90-95 did not make sense.

(4) I am still perplexed by why the authors consider the prelimbic and infralimbic cortex 'neuroendocrine' brain areas in the abstract. In contrast, the prelimbic and infralimbic were described better in the introduction as "associated information processing" areas.

5- It looks like overall Fos levels in the control group Home (ISO) are a magnitude (~10-fold) lower than those in the control group Saline (KET) across all regions shown. This large difference seems unlikely to be due to a biologically driven effect and seems more likely to be due to a technical issue, such as differences in staining or imaging between experiments. The authors discuss this issue but did not answer whether the Homecage-ISO experiment or at least the Fos labeling and imaging performed at the same time as for the Saline-Ketamine experiment?

Reviewer #3 (Public Review):

The present study presents a comprehensive exploration of the distinct impacts of Isoflurane and Ketamine on c-Fos expression throughout the brain. To understand the varying responses across individual brain regions to each anesthetic, the researchers employ principal component analysis (PCA) and c-Fos-based functional network analysis. The methodology employed in this research is both methodical and expansive. Notably, the utilization of a custom software package to align and analyze brain images for c-Fos positive cells stands out as an impressive addition to their approach. This innovative technique enables effective quantification of neural activity and enhances our understanding of how anesthetic drugs influence brain networks as a whole.

The primary novelty of this paper lies in the comparative analysis of two anesthetics, Ketamine and Isoflurane, and their respective impacts on brain-wide c-Fos expression. The study reveals the distinct pathways through which these anesthetics induce loss of consciousness. Ketamine primarily influences the cerebral cortex, while Isoflurane targets subcortical brain regions. This finding highlights the differing mechanisms of action employed by these two anesthetics-a top-down approach for Ketamine and a bottom-up mechanism for Isoflurane. Furthermore, this study uncovers commonly activated brain regions under both anesthetics, advancing our knowledge about the mechanisms underlying general anesthesia.

Reviewer #1 (Public Review):

Summary:<br /> The authors ran a series of experiments with separate subject populations, different stimuli, and on two different MRI scanners (one 3T, one 7T) to establish a scenes-selective region on the intraparietal gyrus that they decided to name PIGS. I think that IPA (intraparietal place area) would also have been a good choice with an allusion to a beverage rather than a domestic animal. The authors show that PIGS can be detected robustly through a series of experiments. They anatomically and functionally separate PIGS from nearby V6, which encodes optic flow. The authors determined that PIGS encodes ego-motion.

Strengths:<br /> The robust detection of PIGS in several experiments with different sets of participants and on different scanners makes these results convincing. The functional differentiation is well executed.

Weaknesses:<br /> The distinction of PIGS from nearby OPA, which has also been implied in navigation and ego-motion, is not as clear as it could be.

Impact:<br /> Overall, this is a valuable contribution to the cognitive neuroscience of the visual system. It shows that there is still room for discovering details of visual processing, given recent advances in scanning technology, statistical methods, and larger sample sizes.

Reviewer #2 (Public Review):

Summary<br /> The authors report an extensive series of neuroimaging experiments (at both 3T and 7T) to provide evidence for a scene-selective visual area in the human posterior parietal cortex (PIGS) that is distinct from the main three (parahippocampal place area, PPA; occipital place area, OPA; medial place area, MPA) typically reported in the literature. Further, they argue that in comparison with the other three, this region may specifically be involved in representing ego-motion in natural contexts. The characterization of this scene-selective region provides a useful reference point for studies of scene processing in humans.

Strengths<br /> One of the major strengths of the work is the extensive series of experiments reported, showing clear reproducibility of the main finding and providing functional insight into the region studied. The results are clearly presented and for the most part, convincing.

Weaknesses<br /> One of the major weaknesses of the work is the failure to relate the current results to other findings in the literature, making it hard to assess whether it is is a "previously undescribed scene-selective site".

First, the scene-selective region identified appears to overlap with regions that have previously been identified in terms of their retinotopic properties. In particular, it is unclear whether this region overlaps with V7/IPS0 and/or IPS1. This is particularly important since prior work has shown that OPA often overlaps with v7/IPS0 (Silson et al, 2016, Journal of Vision). The findings would be much stronger if the authors could show how the location of PIGS relates to retinotopic areas (other than V6, which they do currently consider). I wonder if the authors have retinotopic mapping data for any of the participants included in this study. If not, the authors could always show atlas-based definitions of these areas (e.g. Wang et al, 2015, Cerebral Cortex).

Second, recent studies have reported a region anterior to OPA that seems to be involved in scene memory (Steel et al, 2021, Nature Communications; Steel et al, 2023, The Journal of Neuroscience; Steel et al, 2023, biorXiv). Is this region distinct from PIGS? Based on the figures in those papers, the scene memory-related region is inferior to V7/IPS0, so characterizing the location of PIGS to V7/IPS0 as suggested above would be very helpful here as well.

If PIGS overlaps with either of V7/IPS0 or the scene memory-related area described by Steel and colleagues, then arguably it is not a newly defined region (although the characterization provided here still provides new information).

Another reason that it would be helpful to relate PIGS to this scene memory area is that this scene memory area has been shown to have activity related to the amount of visuospatial context (Steel et al, 2023, The Journal of Neuroscience). The conditions used to show the sensitivity of PIGS to ego-motion also differ in the visuospatial context that can be accessed from the stimuli. Even if PIGS appears distinct from the scene memory area, the degree of visuospatial context is an alternative account of what might be represented in PIGS.

Reviewer #3 (Public Review):

Summary:<br /> The authors report a scene-selective area in the posterior intraparietal gyrus (PIGS). This area lies outside the classical three scene-selective regions (PPA/TPA, RSC/MPA, TOS/OPA), and is selective for ego-motion.

Strengths:<br /> The authors firmly establish the location and selectivity of the new area through a series of well-crafted controlled experiments. They show that the area can be missed with too much smoothing, thus providing a case for why it has not been previously described. They show that it appears in much the same location in different subjects, with different magnetic field strengths, and with different stimulus sets. Finally, they show that it is selective for ego-motion - defined as a series of sequential photographs of an egocentric trajectory along a path. They further clarify that the area is not generically motion-selective by showing that it does not respond to biological motion without an ego-motion component to it. All statistics are standard and sound; the evidence presented is strong.

Weaknesses:<br /> There are few weaknesses in this work. If pressed, I might say that the stimuli depicting ego-motion do not, strictly speaking, depict motion, but only apparent motion between 2m apart photographs. However, this choice was made to equate frame rates and motion contrast between the 'ego-motion' and a control condition, which is a useful and valid approach to the problem. Some choices for visualization of the results might be made differently; for example, outlines of the regions might be shown in more plots for easier comparison of activation locations, but this is a minor issue.

This is a very strong paper.

Reviewer #1 (Public Review):

Summary:<br /> The present study evaluates the role of visual experience in shaping functional correlations between extrastriate visual cortex and frontal regions. The authors used fMRI to assess "resting-state" temporal correlations in three groups: sighted adults, congenitally blind adults, and neonates. Previous research has already demonstrated differences in functional correlations between visual and frontal regions in sighted compared to early blind individuals. The novel contribution of the current study lies in the inclusion of an infant dataset, which allows for an assessment of the developmental origins of these differences.

The main results of the study reveal that correlations between prefrontal and visual regions are more prominent in the blind and infant groups, with the blind group exhibiting greater lateralization. Conversely, correlations between visual and somato-motor cortices are more prominent in sighted adults. Based on these data, the authors conclude that visual experience plays an instructive role in shaping these cortical networks. This study provides valuable insights into the impact of visual experience on the development of functional connectivity in the brain.

Strengths:<br /> The dissociations in functional correlations observed among the sighted adult, congenitally blind, and neonate groups provide strong support for the study's main conclusion regarding experience-driven changes in functional connectivity profiles between visual and frontal regions.

In general, the findings in sighted adult and congenitally blind groups replicate previous studies and enhance the confidence in the reliability and robustness of the current results.

Split-half analysis provides a good measure of robustness in the infant data.

Weaknesses:<br /> There is some ambiguity in determining which aspects of these networks are shaped by experience.

This uncertainty is compounded by notable differences in data acquisition and preprocessing methods, which could result in varying signal quality across groups. Variations in signal quality may, in turn, have an impact on the observed correlation patterns.

The study's findings could benefit from being situated within a broader debate surrounding the instructive versus permissive roles of experience in the development of visual circuits.

Reviewer #2 (Public Review):

Summary:<br /> Tian et al. explore the developmental organs of cortical reorganization in blindness. Previous work has found that a set of regions in the occipital cortex show different functional responses and patterns of functional correlations in blind vs. sighted adults. In this paper, Tian et al. ask: how does this organization arise over development? Is the "starting state" more like the blind pattern, or more like the adult pattern? Their analyses reveal that the answer depends on the particular networks investigated; some functional connections in infants look more like blind than sighted adults; other functional connections look more like sighted than blind adults; and others fall somewhere in the middle, or show an altogether different pattern in infants compared with both sighted and blind adults.

Strengths:<br /> The question raised in this paper is extremely important: what is the starting state in development for visual cortical regions, and how is this organization shaped by experience? This paper is among the first to examine this question, particularly by comparing infants not only with sighted adults but also blind adults, which sheds new light on the role of visual (and cross-modal) experience. Another clear strength lies in the unequivocal nature of many results. Many results have very large effect sizes, critical interactions between regions and groups are tested and found, and infant analyses are replicated in split halves of the data.

Weaknesses:<br /> A central claim is that "infant secondary visual cortices functionally resemble those of blind more than sighted adults" (abstract, last paragraph of intro). I see two potential issues with this claim. First, a minor change: given the approaches used here, no claims should be made about the "function" of these regions, but rather their "functional correlations". Second (and more importantly), the claim that the secondary visual cortex in general resembles blind more than sighted adults is still not fully supported by the data. In fact, this claim is only true for one aspect of secondary visual area functional correlations (i.e., their connectivity to A1/M1/S1 vs. PFC). In other analyses, the infant secondary visual cortex looks more like sighted adults than blind adults (i.e., in within vs. across hemisphere correlations), or shows a different pattern from both sighted and blind adults (i.e., in occipito-frontal subregion functional connectivity). It is not clear from the manuscript why the comparison to PFC vs. non-visual sensory cortex is more theoretically important than hemispheric changes or within-PFC correlations (in fact, if anything, the within-PFC correlations strike me as the most important for understanding the development and reorganization of these secondary visual regions). It seems then that a more accurate conclusion is that the secondary visual cortex shows a mix of instructive effects of vision and reorganizing effects of blindness, albeit to a different extent than the primary visual cortex.

Relatedly, group differences in overall secondary visual cortex connectivity are particularly striking as visualized in the connectivity matrices shown in Figure S1. In the results (lines 105-112), it is noted that while the infant FC matrix is strongly correlated with both adult groups, the infant group is nonetheless more strongly correlated with the blind than sighted adults. I am concerned that these results might be at least partially explained by distance (i.e., local spread of the bold signal), since a huge portion of the variance in these FC matrices is driven by stronger correlations between regions within the same system (e.g., secondary-secondary visual cortex, frontal-frontal cortex), which are inherently closer together, relative to those between different systems (e.g., visual to frontal cortex). How do results change if only comparisons between secondary visual regions and non-visual regions are included (i.e., just the pairs of regions within the bold black rectangle on the figure), which limits the analysis to long-rang connections only? Indeed, looking at the off-diagonal comparisons, it seems that in fact there are three altogether different patterns here in the three groups. Even if the correlation between the infant pattern and blind adult pattern survives, it might be more accurate to claim that infants are different from both adult groups, suggesting both instructive effects of vision and reorganizing effects of blindness. It might help to show the correlation between each group and itself (across independent sets of subjects) to better contextualize the relative strength of correlations between the groups.

It is not clear that differences between groups should be attributed to visual experience only. For example, despite the title of the paper, the authors note elsewhere that cross-modal experience might also drive changes between groups. Another factor, which I do not see discussed, is possible ongoing experience-independent maturation. The infants scanned are extremely young, only 2 weeks old. Although no effects of age are detected, it is possible that cortex is still undergoing experience-independent maturation at this very early stage of development. For example, consider Figure 2; perhaps V1 connectivity is not established at 2 weeks, but eventually achieves the adult pattern later in infancy or childhood. Further, consider the possibility that this same developmental progression would be found in infants and children born blind. In that case, the blind adult pattern may depend on blindness-related experience only (which may or may not reflect "visual" experience per se). To deal with these issues, the authors should add a discussion of the role of maturation vs. experience and temper claims about the role of visual experience specifically (particularly in the title).

The authors measure functional correlations in three very different groups of participants and find three different patterns of functional correlations. Although these three groups differ in critical, theoretically interesting ways (i.e., in age and visual/cross-modal experience), they also differ in many uninteresting ways, including at least the following: sampling rate (TR), scan duration, multi-band acceleration, denoising procedures (CompCor vs. ICA), head motion, ROI registration accuracy, and wakefulness (I assume the infants are asleep).

Addressing all of these issues is beyond the scope of this paper, but I do feel the authors should acknowledge these confounds and discuss the extent to which they are likely (or not) to explain their results. The authors would strengthen their conclusions with analyses directly comparing data quality between groups (e.g., measures of head motion and split-half reliability would be particularly effective).

Reviewer #3 (Public Review):

Summary:<br /> This study aimed to investigate whether the differences observed in the organization of visual brain networks between blind and sighted adults result from a reorganization of an early functional architecture due to blindness, or whether the early architecture is immature at birth and requires visual experience to develop functional connections. This question was investigated through the comparison of 3 groups of subjects with resting-state functional MRI (rs-fMRI). Based on convincing analyses, the study suggests that: 1) secondary visual cortices showed higher connectivity to prefrontal cortical regions (PFC) than to non-visual sensory areas (S1/M1 and A1) in sighted infants like in blind adults, in contrast to sighted adults; 2) the V1 connectivity pattern of sighted infants lies between that of sighted adults (stronger functional connectivity with non-visual sensory areas than with PFC) and that of blind adults (stronger functional connectivity with PFC than with non-visual sensory areas); 3) the laterality of the connectivity patterns of sighted infants resembled those of sighted adults more than those of blind adults, but sighted infants showed a less differentiated fronto-occipital connectivity pattern than adults.

Strengths:<br /> - The question investigated in this article is important for understanding the mechanisms of plasticity during typical and impaired development, and the approach considered, which compares different groups of subjects including, neonates/infants and blind adults, is highly original.

- Overall, the analyses considered are solid and well-detailed. The results are quite convincing, even if the interpretation might need to be revised downwards, as factors other than visual experience may play a role in the development of functional connections with the visual system.

Weaknesses:<br /> - While it is informative to compare the "initial" state (close to birth) and the "final" states in blind and sighted adults to study the impact of post-natal and visual experience, this study does not analyze the chronology of this development and when the specialization of functional connections is completed. This would require investigating when experience-dependent mechanisms are important for the setting- establishment of multiple functional connections within the visual system. This could be achieved by analyzing different developmental periods in the same way, using open databases such as the Baby Connectome Project. Given the early, "condensed" maturation of the visual system after birth, we might expect sighted infants to show connectivity patterns similar to those of adults a few months after birth.

- The rationale for mixing full-term neonates and preterm infants (scanned at term-equivalent age) from the dHCP 3rd release is not understandable since preterms might have a very different development related to prematurity and to post-natal (including visual) experience. Although the authors show that the difference between the connectivity of visual and other sensory regions, and the one of visual and PFC regions, do not depend on age at birth, they do not show that each connectivity pattern is not influenced by prematurity. Simply not considering the preterm infants would have made the analysis much more robust, and the full-term group in itself is already quite large compared with the two adult groups. The current study setting and the analyses performed do not seem to be an adequate and sufficient model to ascertain that "a few weeks of vision after birth is ... insufficient to influence connectivity".

In a similar way, excluding the few infants with detected brain anomalies (radiological scores higher or equal to 4) would strengthen the group homogeneity by focusing on infants supposed to have a rather typical neurodevelopment. The authors quote all infants as "sighted" but this is not guaranteed as no follow-up is provided.

The post-menstrual age (PMA) at scan of the infants is also not described. The methods indicate that all were scanned at "term-equivalent age" but does this mean that there is some PMA variability between 37 and 41 weeks? Connectivity measures might be influenced by such inter-individual variability in PMA, and this could be evaluated.

- The rationale for presenting results on the connectivity of secondary visual cortices before one of the primary cortices (V1) was not clear to understand. Also, it might be relevant to better justify why only the connectivity of visual regions to non-visual sensory regions (S1-M1, A1) and prefrontal cortex (PFC) was considered in the analyses, and not the ones to other brain regions.

- In relation to the question explored, it might be informative to reposition the study in relation to what others have shown about the developmental chronology of structural and functional long-distance and short-distance connections during pregnancy and the first postnatal months.

- The authors acknowledge the methodological difficulties in defining regions of interest (ROIs) in infants in a similar way as adults. The reliability and the comparability of the ROIs positioning in infants is definitely an issue. Given that brain development is not homogeneous and synchronous across brain regions (in particular with the frontal and parietal lobes showing delayed growth), the newborn brain is not homothetic to the adult brain, which poses major problems for registration. The functional specialization of cortical regions is incomplete at birth. This raises the question of whether the findings of this study would be stable/robust if slightly larger or displaced regions had been considered, to cover with greater certainty the same areas as those considered in adults. And have other cortical parcellation approaches been considered to assess the ROIs robustness (e.g. MCRIB-S for full-terms)?

Reviewer #1 (Public Review):

Summary:

Songbirds provide a tractable system to examine neural mechanisms of sequence generation and variability. In past work, the projection from LMAN to RA (output of the anterior forebrain pathway) was shown to be critical for driving vocal variability during babbling, learning, and adulthood. LMAN is immediately adjacent to MMAN, which projects to HVC. MMAN is less well understood but, anatomically, appears to resemble LMAN in that it is the cortical output of a BG-thalamocortical loop. Because it projects to HVC, a major sequence generator for both syllable phonology and sequence, a strong prediction would be that MMAN drives sequence variability in the same way that LMAN drives phonological variability. This hypothesis predicts that MMAN lesions in a Bengalese finch would reduce sequence variability. Here, the authors test this hypothesis. They provide a surprising and important result that is well motivated and well analyzed: MMAN lesions increase sequence variability - this is exactly the opposite result from what would be predicted based on the functions of LMAN.

Strengths:

1. A very important and surprising result shows that lesions of a frontal projection from MMAN to HVC, a sequence generator for birdsong, increase syntactical variability.

2. The choice of Bengalese finches, which have complex transition structures, to examine the mechanisms of sequence generation, enabled this important discovery.

3. The idea that frontal outputs of BG-cortical loops can generate vocal variability comes from lesions/inactivations of a parallel pathway from LMAN to RA. The difference between MMAN and LMAN functions is striking and important.

Weaknesses:

1. If more attention was paid to how syllable phonology was (or was not) affected by MMAN lesions then the claims could be stronger around the specific effects on sequence.

Reviewer #2 (Public Review):

Summary:

This study investigates the neural substrates of syntax variation in Bengalese finch songs. Here, the authors tested the effects of bilateral lesions of mMAN, a brain area with inputs to HVC, a premotor area required for song production. Lesions in mMAN induce variability in syntactic elements of song specifically through increased transition entropy, variability within stereotyped song elements known as chunks, and increases in the repeat number of individual syllables. These results suggest that mMAN projections to HVC contribute to multiple aspects of song syntax in the Bengalese finch. Overall the experiments are well-designed, the analysis excellent, and the results are of high interest.

Strengths:

The study identifies a novel role for mMAN, the medial magnocellular nucleus of the anterior nidopallium, in the control of syntactic variation within adult Bengalese finch song. This is of particular interest as multiple studies previously demonstrated that mMAN lesions do not affect song structure in zebra finches. The study undertakes a thorough analysis to characterise specific aspects of variability within the song of lesioned animals. The conclusions are well supported by the data.

Weaknesses:

The study would benefit from additional mechanistic information. A more fine-grained or reversible manipulation, such as brain cooling, might allow additional insights into how mMAN influences specific aspects of syntax structure. Are repeat number increases and transition entropy resulting from shared mechanisms within mMAN, or perhaps arising from differential output to downstream pathways (i.e. projections to HVC)? Similarly, unilateral manipulations would allow the authors to further test the hypothesis that mMAN is involved in inter-hemispheric synchronization.

Reviewer #1 (Public Review):

Summary:<br /> The authors investigated causal inference in the visual domain through a set of carefully designed experiments, and sound statistical analysis. They suggest the early visual system has a crucial contribution to computations supporting causal inference.

Strengths:<br /> I believe the authors target an important problem (causal inference) with carefully chosen tools and methods. Their analysis rightly implies the specialization of visual routines for causal inference and the crucial contribution of early visual systems to perform this computation. I believe this is a novel contribution and their data and analysis are in the right direction.

Weaknesses:<br /> In my humble opinion, a few aspects deserve more attention:

1. Causal inference (or causal detection) in the brain should be quite fundamental and quite important for human cognition/perception. Thus, the underlying computation and neural substrate might not be limited to the visual system (I don't mean the authors did claim that). In fact, to the best of my knowledge, multisensory integration is one of the best-studied perceptual phenomena that has been conceptualized as a causal inference problem. Assuming the causal inference in those studies (Shams 2012; Shams and Beierholm 2022; Kording et al. 2007; Aller and Noppeney 2018; Cao et al. 2019) (and many more e.g., by Shams and colleagues), and the current study might share some attributes, one expects some findings in those domains are transferable (at least to some degree) here as well. Most importantly, underlying neural correlates that have been suggested based on animal studies and invasive recording that has been already studied, might be relevant here as well. Perhaps the most relevant one is the recent work from the Harris group on mice (Coen et al. 2021). I should emphasize, that I don't claim they are necessarily relevant, but they can be relevant given their common roots in the problem of causal inference in the brain. This is a critical topic that the authors may want to discuss in their manuscript.

2. If I understood correctly, the authors are arguing pro a mere bottom-up contribution of early sensory areas for causal inference (for instance, when they wrote "the specialization of visual routines<br /> for the perception of causality at the level of individual motion directions raises the possibility that this function is located surprisingly early in the visual system *as opposed to a higher-level visual computation*."). Certainly, as the authors suggested, early sensory areas have a crucial contribution, however, it may not be limited to that. Recent studies progressively suggest perception as an active process that also weighs in strongly, the top-down cognitive contributions. For instance, the most simple cases of perception have been conceptualized along this line (Martin, Solms, and Sterzer 2021)<br /> and even some visual illusion (Safavi and Dayan 2022), and other extensions (Kay et al. 2023). Thus, I believe it would be helpful to extend the discussion on the top-down and cognitive contributions of causal inference (of course that can also be hinted at, based on recent developments). Even adaptation, which is central in this study can be influenced by top-down factors (Keller et al. 2017). I believe, based on other work of Rolfs and colleagues, this is also aligned with their overall perspective on vision.

3. The authors rightly implicate the neural substrate of causal inference in the early sensory system. Given their study is pure psychophysics, a more elaborate discussion based on other studies that used brain measurements is needed (in my opinion) to put into perspective this conclusion. In particular, as I mentioned in the first point, the authors mainly discuss the potential neural substrate of early vision, however much has been done about the role of higher-tier cortical areas in causal inference e.g., see (Cao et al. 2019; Coen et al. 2021).

There were many areas in this manuscript that I liked: clever questions, experimental design, and statistical analysis.

Bibliography<br /> \============

Aller, Mate, and Uta Noppeney. 2018. "To Integrate or Not to Integrate: Temporal Dynamics of Bayesian Causal Inference." Biorxiv, December, 504118. .

Cao, Yinan, Christopher Summerfield, Hame Park, Bruno Lucio Giordano, and Christoph Kayser. 2019. "Causal Inference in the Multisensory Brain." Neuron 102 (5): 1076-87.e8. .

Coen, Philip, Timothy P. H. Sit, Miles J. Wells, Matteo Carandini, and Kenneth D. Harris. 2021. "The Role of Frontal Cortex in Multisensory Decisions." Biorxiv, April. Cold Spring Harbor Laboratory, 2021.04.26.441250. .

Kay, Kendrick, Kathryn Bonnen, Rachel N. Denison, Mike J. Arcaro, and David L. Barack. 2023. "Tasks and Their Role in Visual Neuroscience." Neuron 111 (11). Elsevier: 1697-1713. .

Keller, Andreas J, Rachael Houlton, Björn M Kampa, Nicholas A Lesica, Thomas D Mrsic-Flogel, Georg B Keller, and Fritjof Helmchen. 2017. "Stimulus Relevance Modulates Contrast Adaptation in Visual Cortex." Elife 6. eLife Sciences Publications, Ltd: e21589.

Kording, K. P., U. Beierholm, W. J. Ma, S. Quartz, J. B. Tenenbaum, and L. Shams. 2007. "Causal Inference in Multisensory Perception." PloS One 2: e943. .

Martin, Joshua M., Mark Solms, and Philipp Sterzer. 2021. "Useful Misrepresentation: Perception as Embodied Proactive Inference." Trends Neurosci. 44 (8): 619-28. .

Safavi, Shervin, and Peter Dayan. 2022. "Multistability, Perceptual Value, and Internal Foraging." Neuron, August. .

Shams, L. 2012. "Early Integration and Bayesian Causal Inference in Multisensory Perception." In The Neural Bases of Multisensory Processes, edited by M. M. Murray and M. T. Wallace. Frontiers in<br /> Neuroscience. Boca Raton (FL).

Shams, Ladan, and Ulrik Beierholm. 2022. "Bayesian Causal Inference: A Unifying Neuroscience Theory." Neuroscience & Biobehavioral Reviews 137 (June): 104619. .

Reviewer #2 (Public Review):

This paper seeks to determine whether the human visual system's sensitivity to causal interactions is tuned to specific parameters of a causal launching event, using visual adaptation methods. The three parameters the authors investigate in this paper are the direction of motion in the event, the speed of the objects in the event, and the surface features or identity of the objects in the event (in particular, having two objects of different colors).

The key method, visual adaptation to causal launching, has now been demonstrated by at least three separate groups and seems to be a robust phenomenon. Adaptation is a strong indicator of a visual process that is tuned to a specific feature of the environment, in this case launching interactions. Whereas other studies have focused on retinotopically-specific adaptation (i.e., whether the adaptation effect is restricted to the same test location on the retina as the adaptation stream was presented to), this one focuses on feature-specificity.

The first experiment replicates the adaptation effect for launching events as well as the lack of adaptation event for a minimally different non-causal 'slip' event. However, it also finds that the adaptation effect does not work for launching events that do not have a direction of motion more than 30 degrees from the direction of the test event. The interpretation is that the system that is being adapted is sensitive to the direction of this event, which is an interesting and somewhat puzzling result given the methods used in previous studies, which have used random directions of motion for both adaptation and test events.

The obvious interpretation would be that past studies have simply adapted to launching in every direction, but that in itself says something about the nature of this direction-specificity: it is not working through opposed detectors. For example, in something like the waterfall illusion adaptation effect, where extended exposure to downward motion leads to illusory upward motion on neutral-motion stimuli, the effect simply doesn't work if motion in two opposed directions is shown (i.e., you don't see illusory motion in both directions, you just see nothing). The fact that adaptation to launching in multiple directions doesn't seem to cancel out the adaptation effect in past work raises interesting questions about how directionality is being coded in the underlying process. In addition, one limitation of the current method is that it's not clear whether the motion-direction-specificity is also itself retinotopically-specific, that is, if one retinotopic location were adapted to launching in one direction and a different retinotopic location adapted to launching in the opposite direction, would each test location show the adaptation effect only for events in the direction presented at that location?

The second experiment tests whether the adaptation effect is similarly sensitive to differences in speed. The short answer is no; adaptation events at one speed affect test events at another. Furthermore, this is not surprising given that Kominsky & Scholl (2020) showed adaptation transfer between events with differences in speeds of the individual objects in the event (whereas all events in this experiment used symmetrical speeds). This experiment is still novel and it establishes that the speed-insensitivity of these adaptation effects is fairly general, but I would certainly have been surprised if it had turned out any other way.

The third experiment tests color (as a marker of object identity), and pits it against motion direction. The results demonstrate that adaptation to red-launching-green generates an adaptation effect for green-launching-red, provided they are moving in roughly the same direction, which provides a nice internal replication of Experiment 1 in addition to showing that the adaptation effect is not sensitive to object identity. This result forms an interesting contrast with the infant causal perception literature. Multiple papers (starting with Leslie & Keeble, 1987) have found that 6-8-month-old infants are sensitive to reversals in causal roles exactly like the ones used in this experiment. The success of adaptation transfer suggests, very clearly, that this sensitivity is not based only on perceptual processing, or at least not on the same processing that we access with this adaptation procedure. It implies that infants may be going beyond the underlying perceptual processes and inferring genuine causal content. This is also not the first time the adaptation paradigm has diverged from infant findings: Kominsky & Scholl (2020) found a divergence with the object speed differences as well, as infants categorize these events based on whether the speed ratio (agent:patient) is physically plausible (Kominsky et al., 2017), while the adaptation effect transfers from physically implausible events to physically plausible ones. This only goes to show that these adaptation effects don't exhaustively capture the mechanisms of early-emerging causal event representation.

One overarching point about the analyses to take into consideration: The authors use a Bayesian psychometric curve-fitting approach to estimate a point of subjective equality (PSE) in different blocks for each individual participant based on a model with strong priors about the shape of the function and its asymptotic endpoints, and this PSE is the primary DV across all of the studies. As discussed in Kominsky & Scholl (2020), this approach has certain limitations, notably that it can generate nonsensical PSEs when confronted with relatively extreme response patterns. The authors mentioned that this happened once in Experiment 3 and that a participant had to be replaced. An alternate approach is simply to measure the proportion of 'pass' reports overall to determine if there is an adaptation effect. I don't think this alternate analysis strategy would greatly change the results of this particular experiment, but it is robust against this kind of self-selection for effects that fit in the bounds specified by the model, and may therefore be worth including in a supplemental section or as part of the repository to better capture the individual variability in this effect.

In general, this paper adds further evidence for something like a 'launching' detector in the visual system, but beyond that, it specifies some interesting questions for future work about how exactly such a detector might function.

Kominsky, J. F., & Scholl, B. J. (2020). Retinotopic adaptation reveals distinct categories of causal perception. Cognition, 203, 104339. https://doi.org/10.1016/j.cognition.2020.104339

Kominsky, J. F., Strickland, B., Wertz, A. E., Elsner, C., Wynn, K., & Keil, F. C. (2017). Categories and Constraints in Causal Perception. Psychological Science, 28(11), 1649-1662. https://doi.org/10.1177/0956797617719930

Leslie, A. M., & Keeble, S. (1987). Do six-month-old infants perceive causality? Cognition, 25(3), 265-288. https://doi.org/10.1016/S0010-0277(87)80006-9

Reviewer #3 (Public Review):

Summary:<br /> This paper presents evidence from three behavioral experiments that causal impressions of "launching events", in which one object is perceived to cause another object to move, depending on motion direction-selective processing. Specifically, the work uses an adaptation paradigm (Rolfs et al., 2013), presenting repetitive patterns of events matching certain features to a single retinal location, then measuring subsequent perceptual reports of a test display in which the degree of overlap between two discs was varied, and participants could respond "launch" or "pass". The three experiments report results of adapting to motion direction, motion speed, and "object identity", and examine how the psychometric curves for causal reports shift in these conditions depending on the similarity of the adapter and test. While causality reports in the test display were selective for motion direction (Experiment 1), they were not selective for adapter-test speed differences (Experiment 2) nor for changes in object identity induced via color swap (Experiment 3). These results support the notion that causal perception is computed (in part) at relatively early stages of sensory processing, possibly even independently of or prior to computations of object identity.

Strengths:<br /> The setup of the research question and hypotheses is exceptional. The experiments are carefully performed (appropriate equipment, and careful control of eye movements). The slip adaptor is a really nice control condition and effectively mitigates the need to control motion direction with a drifting grating or similar. Participants were measured with sufficient precision, and a power curve analysis was conducted to determine the sample size. Data analysis and statistical quantification are appropriate. Data and analysis code are shared on publication, in keeping with open science principles. The paper is concise and well-written.

Weaknesses:<br /> The biggest uncertainty I have in interpreting the results is the relationship between the task and the assumption that the results tell us about causality impressions. The experimental logic assumes that "pass" reports are always non-causal impressions and "launch" reports are always causal impressions. This logic is inherited from Rolfs et al (2013) and Kominsky & Scholl (2020), who assert rather than measure this. However, other evidence suggests that this assumption might not be solid (Bechlivanidis et al., 2019). Specifically, "[our experiments] reveal strong causal impressions upon first encounter with collision-like sequences that the literature typically labels "non-causal"" (Bechlivanidis et al., 2019) -- including a condition that is similar to the current "pass". It is therefore possible that participants' "pass" reports could also involve causal experiences.

Furthermore, since the only report options are "launch" or "pass", it is also possible that "launch" reports are not indications of "I experienced a causal event" but rather "I did not experience a pass event". It seems possible to me that different adaptation transfer effects (e.g. selectivity to motion direction, speed, or color-swapping) change the way that participants interpret the task, or the uncertainty of their impression. For example, it could be that adaptation increases the likelihood of experiencing a "pass" event in a direction-selective manner, without changing causal impressions. Increases of "pass" impressions (or at least, uncertainty around what was experienced) would produce a leftward shift in the PSE as reported in Experiment 1, but this does not necessarily mean that experiences of causal events changed. Thus, changes in the PSEs between the conditions in the different experiments may not directly reflect changes in causal impressions. I would like the authors to clarify the extent to which these concerns call their conclusions into question.

Leaving these concerns aside, I am also left wondering about the functional significance of these specialised mechanisms. Why would direction matter but speed and object identity not? Surely object identity, in particular, should be relevant to real-world interpretations and inputs of these visual routines? Is color simply too weak an identity?

References:

Bechlivanidis, C., Schlottmann, A., & Lagnado, D. A. (2019). Causation without realism. Journal of Experimental Psychology: General, 148(5), 785-804. https://doi.org/10.1037/xge0000602

Kominsky, J. F., & Scholl, B. J. (2020). Retinotopic adaptation reveals distinct categories of causal perception. Cognition, 203, 104339.

Rolfs, M., Dambacher, M., & Cavanagh, P. (2013). Visual Adaptation of the Perception of Causality. Current Biology, 23(3), 250-254. https://doi.org/10.1016/j.cub.2012.12.017

Reviewer #1 (Public Review):

Summary and strengths. This paper starts with an exceptionally fair and balanced introduction to a topic, the mirror neuron literature, which is often debated and prone to controversies even in the choice of the terminology. In my opinion, the authors made an excellent job in this regard, and I really appreciated it. Then, they propose a novel method to look at population dynamics to compare neural selectivity and alignment between execution and observation of actions performed with different types of grip.

Weakness. Unfortunately, the goal and findings within this well-described framework are less clear to me. The authors aimed to investigate, using a novel analytic approach, whether and to what extent a match exists between population codes and neural dynamics when a monkey performs an action or observes it performed by an experimenter. This motivation stems from the fact that the general evidence in the literature is that the match between visual and motor selectivity of mirror neuron responses is essentially at a chance level. While the approach devised by the author is generally well-described and understandable, the main result obtained confirms this general finding of a lack of matching between the two contexts in 2 out of the three monkeys. Nevertheless, the authors claim that the patterns associated with execution and observation can be re-aligned with canonical correlation, indicating that these distinct neural representations show dynamical similarity that may enable the nervous system to recognize particular actions. This final conclusion is hardly acceptable to me, and constitutes my major concern, at least without a more explicit explanation: how do we know that this additional operation can be performed by the brain? Is this a computational trick to artificially align something that is naturally non-aligned, or can it capture something real and useful?<br /> Based on the accumulated evidence on space-constrained coding of others' actions by mirror neurons (e.g., Caggiano et al. 2009; Maranesi et al. 2017), recent evidence also cited by the authors (Pomper et al. 2023), and the most recent views supported even by the first author of the original discovery (i.e., Vittorio Gallese, see Bonini et al. 2022 on TICS), it seems that one of the main functions of these cells, especially in monkeys, might be to prepare actions and motor responses during social interaction rather than recognizing the actions of others - something that visual brain areas could easily do better than motor ones in most situations. In this perspective, and given the absence of causal evidence so far, the lack of visuo-motor congruence is a potentially relevant feature of the mechanism rather than something to be computationally cracked at all costs.

Specific comments on Results/Methods:<br /> I can understand, based on the authors' hypothesis, that they employed an ANOVA to preliminarily test whether and which of the recorded neurons fit their definition of "mirror neurons". However, given the emphasis on the population level, and the consolidated finding of highly different execution and observation responses, I think it could be interesting to apply the same analysis on (at least also) the whole recorded neuronal population, without any preselection-based on a single neuron statistic. Such preselection of mirror neurons could influence the results of EXE-OBS comparisons since all the neurons activated only during EXE or OBS are excluded. Related to this point, the authors could report the total number of recorded neurons per monkey/session, so that also the fraction of neurons fitting their definition of mirror neuron is explicit.<br /> Furthermore, the comparison of the dynamics of the classification accuracy in figures 4 and 5, and therefore the underlying assumption of subspaces shift in execution and observation, respectively, reveal substantial similarities between monkeys despite the different contexts, which are clearly greater than the similarities among neural subspaces shifts across task epochs: to me, this suggests that the main result is driven by the selected neural populations in different monkeys/implants rather than by an essential property of the neuronal dynamics valid across animals. Could the author comment on this issue? This could easily explain the "strange" result reported in figure 6 for monkey T.

Reviewer #2 (Public Review):

In this work, the authors set out to identify time-varying subspaces in the premotor cortical activity of monkeys as they executed/observed a reach-grasp-hold movement of 4 different objects. Then, they projected the neural activity to these subspaces and found evidence of shifting subspaces in the time course of a trial in both conditions, executing and observing. These shifting subspaces appear to be distinct in execution and observation trials. However, correlation analysis of neural dynamics reveals the similarity of dynamics in these distinct subspaces. Taken together, Zhao and Schieber speculate that the condition-dependent activity studied here provides a representation of movement that relies on the actor.<br /> This work addresses an interesting question. The authors developed a novel approach to identify instantaneous subspaces and decoded the object type from the projected neural dynamics within these subspaces. As interesting as these results might be, I have a few suggestions and questions to improve the manuscript:<br /> 1- Repeating the analyses in the paper, e.g., in Fig5, using non-MN units only or the entire population, and demonstrating that the results are specific to MNs would make the whole study much more compelling.<br /> 2- The method presented here is similar and perhaps related to principal angles (https://doi.org/10.2307/2005662). It would be interesting to confirm these results with principal angles. For instance, instead of using the decoding performance as a proxy for shifting subspaces, principal angles could directly quantify the 'shift' (similar to Gallego et al, Nat Comm, 2018). Relatedly, why the decoding of the 'object type' is used to establish the progressive shifting of the subspaces? I would be interested to see the authors' argument. The object type should be much more decodable during movement or hold, than instruction, which is probably why the chance-level decoding performance (horizontal lines) is twice the instruction segment for the movement segment.<br /> 3- Why aren't execution and observation subspaces compared together directly? Especially given that there are both types of trials in the same session with the same recorded population of neurons. Using instantaneous subspaces, or the principal angles between manifolds during exec trials vs obs trials.<br /> 4- The definition of the instantaneous subspaces is a critical point in the manuscript. I think it is slightly unclear: based on the Methods section #715-722 and the main text #173-#181, I gather that the subspaces are based on trial averaged neural activity for each of the 4 objects, separately. So for each object and per timepoint, a vector of size (1, n) -n neurons- is reduced to a vector of (1, 2 or 3 -the main text says 2, methods say 3-) which would be a single point in the low-d space. Is this description accurate? This should be clarified in the manuscript.<br /> 5- Isn't the process of projecting segments of neural dynamics and comparing the results equivalent to comparing the projection matrices in the first place? If so, that might have been a more intuitive avenue to follow.<br /> 6- Lines #385-#389: This process seems unnecessarily complicated. Also, given the number of trials available, this sometimes doesn't make sense. E.g. Monkey R exec has only 8 trials of one of the objects, so bootstrapping 20 trials 500 times would be spurious. Why not, as per Gallego et al, Nat Neurosci 2020 and Safaie et al, Nat 2023 which are cited, concatenate the trials?<br /> 7- Related to the CCA analysis, what behavioural epoch has been used here, the same as the previous analyses, i.e. 100ms? how many datapoint is that in time? Given that CCA is essentially a correlation value, too few datapoints make it rather meaningless. If that's the case, I encourage using, let's say, one window combined of I and G until movement, and one window of movement and hold, such that they are both easier to interpret. Indeed low values of exec-exec in CC2 compared to Gallego et al, Nat Neurosci, 2020 might be a sign of a methodological error.

Reviewer #3 (Public Review):

Summary:<br /> In their study, Zhao et al. investigated the population activity of mirror neurons (MNs) in the premotor cortex of monkeys either executing or observing a task consisting of reaching to, grasping, and manipulating various objects. The authors proposed an innovative method for analyzing the population activity of MNs during both execution and observation trials. This method enabled to isolate the condition-dependent variance in neural data and to study its temporal evolution over the course of single trials. The method proposed by the authors consists of building a time series of "instantaneous" subspaces with single time step resolution, rather than a single subspace spanning the entire task duration. As these subspaces are computed on an instant time basis, projecting neural activity from a given task time into them results in latent trajectories that capture condition-dependent variance while minimizing the condition-independent one. The authors then analyzed the time evolution of these instantaneous subspaces and revealed that a progressive shift is present in subspaces of both execution and observation trials, with slower shifts during the grasping and manipulating phases compared to the initial preparation phase. Finally, they compared the instantaneous subspaces between execution and observation trials and observed that neural population activity did not traverse the same subspaces in these two conditions. However, they showed that these distinct neural representations can be aligned with Canonical Correlation Analysis, indicating dynamic similarities of neural data when executing and observing the task. The authors speculated that such similarities might facilitate the nervous system's ability to recognize actions performed by oneself or another individual.

Strengths:<br /> Unlike other areas of the brain, the analysis of neural population dynamics of premotor cortex MNs is not well established. Furthermore, analyzing population activity recorded during non-trivial motor actions, distinct from the commonly used reaching tasks, serves as a valuable contribution to computational neuroscience. This study holds particular significance as it bridges both domains, shedding light on the temporal evolution of the shift in neural states when executing and observing actions. The results are moderately robust, and the proposed analytical method could potentially be used in other neuroscience contexts.

Weaknesses:<br /> While the overall clarity is satisfactory, the paper falls short in providing a clear description of the mathematical formulas for the different methods used in the study. Moreover, it was not immediately clear why the authors did not consider a (relatively) straightforward metric to quantity the progressive shift of the instantaneous subspaces, such as computing the angle between consecutive subspaces, rather than choosing a (in my opinion) more cumbersome metric based on classification of trajectory segments representing different movements.

Specific comments:<br /> In the methods, it is stated that instantaneous subspaces are found with 3 PCs. Why does it say 2 here? Another doubt on how instantaneous subspaces are computed: in the methods you state that you apply PCA on trial-averaged activity at each 50ms time step. From the next sentence, I gather that you apply PCA on an Nx4 data matrix (N being the number of neurons, and 4 being the trial-averaged activity of the four objects) every 50 ms. Is this right? It would help to explicitly specify the dimensions of the data matrix that goes into PCA computation.

It would help to include some equations in the methods section related to the LSTM decoding. Just to make sure I understood correctly: after having identified the instantaneous subspaces (every 50 ms), you projected the Instruction, Go, Movement, and Holding segments from individual trials (each containing 100 samples, since they are sampled from a 100ms window) onto each instantaneous subspace. So you have four trajectories for each subspace. In the methods, it is stated that a single LSTM classifier is trained for each subspace. Do you also have a separate classifier for each trajectory segment? What is used as input to the classifier? Each trajectory segment should be a 100x3 matrix once projected in an instantaneous subspace. Is that what (each of) the LSTMs take as input? And lastly, what is the LSTM trained to predict exactly? Just a label indicating the type of object that was manipulated in that trial? I apologize if I overlooked any detail, but I believe a clearer explanation of the LSTM, preferably with mathematical formulas, would greatly help readers understand this section.

Reviewer #1 (Public Review):

The manuscript by Hariani et al. presents experiments designed to improve our understanding of the connectivity and computational role of Unipolar Brush Cells (UBCs) within the cerebellar cortex, primarily lobes IX and X. The authors develop and cross several genetic lines of mice that express distinct fluorophores in subsets of UBCs, combined with immunocytochemistry that also distinguishes subtypes of UBCs, and they use confocal microscopy and electrophysiology to characterize the electrical and synaptic properties of subsets of so-labelled cells, and their synaptic connectivity within the cerebellar cortex. The authors then generate a computer model to test possible computational functions of such interconnected UBCs.

Using these approaches, the authors report that:<br /> 1) GRP-driven TDtomato is expressed exclusively in a subset (20%) of ON-UBCs, defined electrophysiologically (excited by mossy fiber afferent stimulation via activation of UBC AMPA and mGluR1 receptors) and immunocytochemically by their expression of mGluR1.

2) UBCs ID'd/tagged by mCitrine expression in Brainbow mouse line P079 is expressed in a similar minority subset of OFF-UBCs defined electrophysiologically (inhibited by mossy fiber afferent stimulation via activation of UBC mGluR2 receptors) and immunocytochemically by their expression of Calretinin. However, such mCitrine expression was also detected in some mGluR1 positive UBCs, which may not have shown up electrophysiologically because of the weaker fluorophore expression without antibody amplification.

3) Confocal analysis of crossed lines of mice (GRP X P079) stained with antibodies to mGluR1 and calretinin documented the existence of all possible permutations of interconnectivity between cells (ON-ON, ON-OFF, OFF-OFF, OFF-ON), but their overall abundance was low, and neither their absolute or relative abundance was quantified.

4) A computational model (NEURON ) indicated that the presence of an intermediary UBC (in a polysynaptic circuit from MF to UBC to UBC) could prolong bursts (MF-ON-ON), prolong pauses (MF-ON-OFF), cause a delayed burst (MF-OFF-OFF), cause a delayed pause (MF-OFF-ON) relative to solely MF to UBC synapses which would simply exhibit long bursts (MF-ON) or long pauses (MF-OFF).

The authors thus conclude that the pattern of interconnected UBCs provides an extended and more nuanced pattern of firing within the cerebellar cortex that could mediate longer lasting sensorimotor responses.

The cerebellum's long known role in motor skills and reflexes, and associated disorders, combined with our nascent understanding of its role in cognitive, emotional, and appetitive processing, makes understanding its circuitry and processing functions of broad interest to the neuroscience and biomedical community. The focus on UBCs, which are largely restricted to vestibular lobes of the cerebellum reduces the breadth of likely interest somewhat. The overall design of specific experiments is rigorous and the use of fluorophore expressing mouse lines is creative. The data that is presented and the writing are clear.

Reviewer #2 (Public Review):

In this paper, the authors presented a compelling rationale for investigating the role of UBCs in prolonging and diversifying signals. Based on the two types of UBCs known as ON and OFF UBC subtypes, they have highlighted the existing gaps in understanding UBCs connectivity and the need to investigate whether UBCs target UBCs of the same subtype, different subtypes, or both. The importance of this knowledge is for understanding how sensory signals are extended and diversified in the granule cell layer.

The authors designed very interesting approaches to study UBCs connectivity by utilizing transgenic mice expressing GFP and RFP in UBCs, Brainbow approach, immunohistochemical and electrophysiological analysis, and computational models to understand how the feed-forward circuits of interconnected UBCs transform their inputs.

This study provided evidence for the existence of distinct ON and OFF UBC subtypes based on their electrophysiological properties, anatomical characteristics, and expression patterns of mGluR1 and calretinin in the cerebellum. The findings support the classification of GRP UBCs as ON UBCs and P079 UBCs as OFF UBCs and suggest the presence of synaptic connections between the ON and OFF UBC subtypes. In addition, they found that GRP and P079 UBCs form parallel and convergent pathways and have different membrane capacitance and excitability. Furthermore, they showed that UBCs of the same subtype provide input to one another and modify the input to granule cells, which could provide a circuit mechanism to diversify and extend the pattern of spiking produced by mossy fiber input. Accordingly, they suggested that these transformations could provide a circuit mechanism for maintaining a sensory representation of movement for seconds.

Overall, the article is well written in a sound detailed format, very interesting with excellent discovery and suggested model.

Reviewer #1 (Public Review):

Summary:<br /> In this paper, the authors provide a thorough demonstration of the role that one particular type of voltage-gated potassium channel, Kv1.8, plays in a low voltage-activated conductance found in type I vestibular hair cells. Along the way, they find that this same channel protein appears to function in type II vestibular hair cells as well, contributing to other macroscopic conductances. Overall, Kv1.8 may provide especially low input resistance and short time constants to facilitate encoding of more rapid head movements in animals that have necks. Combination with other channel proteins, in different ratios, may contribute to the diversified excitability of vestibular hair cells.

Strengths:<br /> The experiments are comprehensive and clearly described, both in the text and in the figures. Statistical analyses are provided throughout.

Weaknesses:<br /> None.

Reviewer #2 (Public Review):

The focus of this manuscript was to investigate whether Kv1.8 channels, which have previously been suggested to be expressed in type I hair cells of the mammalian vestibular system, are responsible for the potassium conductance gK,L. This is an important study because gK,L is known to be crucial for the function of type I hair cells, but the channel identity has been a matter of debate for the past 20 years. The authors have addressed this research topic by primarily investigating the electrophysiological properties of the vestibular hair cells from Kv1.8 knockout mice. Interestingly, gK,L was completely abolished in Kv1.8-deficient mice, in agreement with the hypothesis put forward by the authors based on the literature. The surprising observation was that in the absence of Kv1.8 potassium channels, the outward potassium current in type II hair cells was also largely reduced. Type II hair cells express the largely inactivating potassium conductance g,K,A, but not gK,L. The authors concluded that heteromultimerization of non-inactivating Kv1.8 and the inactivating Kv1.4 subunits could be responsible for the inactivating gK,A. Overall, the manuscript is very well written and most of the conclusions are supported by the experimental work. The figures are well described, and the statistical analysis is robust.

My only comment relates to the statement regarding the results providing "evidence" that Kv1.4 form heteromultimers with Kv1.8 channels (see Discussion). The only data I can see from the results is that Kv1.4 channels are expressed in the membrane of type II hair cells, which is not sufficient evidence for the above claim. Is the distribution of Kv1.8 and Kv1.4 overlapping in type II hair cells? Have the authors attempted to perform some pharmacological studies on Kv1.4? For example, would gK,A be completely blocked by a Kv1.4 antagonist? Addressing at least some of these questions would strengthen your argument.

Reviewer #3 (Public Review):

Summary:<br /> This paper by Martin et al. describes the contribution of a Kv channel subunit (Kv1.8, KCNA10) to voltage-dependent K+ conductances and membrane properties of type I and type II hair cells of the mouse utricle. Previous work has documented striking differences in K+ conductances between vestibular hair cell types. In particular amniote type I hair cells are known to express a non-typical low-voltage-activated K+ conductance (GK,L) whose molecular identity has been elusive. K+ conductances in hair cells from 3 different mouse genotypes (wildtype, Kv1.8 homozygous knockouts, and heterozygotes) are examined here and whole-cell patch-clamp recordings indicate a prominent role for Kv1.8 subunits in generating GK,L. Results also interestingly support a role for Kv1.8 subunits in type II hair cell K+ conductances; inactivating conductances in null mice are reduced in type II hair cells from striola and extrastriola regions of the utricle. Kv1.8 is therefore proposed to contribute as a pore-forming subunit for 3 different K+ conductances in vestibular hair cells. The impact of these conductances on membrane responses to current steps is studied in the current clamp. Pharmacological experiments use XE991 to block some residual Kv7-mediated current in both hair cell types, but no other pharmacological blockers are used. In addition, immunostaining data are presented and raise some questions about Kv7 and Kv1.8 channel localization. Overall, the data present compelling evidence that the removal of Kv1.8 produces profound changes in hair cell membrane conductances and sensory capabilities. These changes at hair cell level suggest vestibular function would be compromised and further assessment in terms of balance behavior in the different mice would be interesting.

Strengths:

This study provides strong evidence that Kv1.8 subunits are major contributors to the unusual K+ conductance in type I hair cells of the utricle. It also indicates that Kv1.8 subunits are important for type II hair cell K+ conductances because Kv1.8-/- mice lacked an inactivating A conductance and had reduced delayed rectifier conductance compared to controls. A comprehensive and careful analysis of biophysical profiles is presented of expressed K+ conductances in 3 different mouse genotypes. Voltage-dependent K+ currents are rigorously characterized at a range of different ages and their impact on membrane voltage responses to current input is studied. Some pharmacological experiments are performed in addition to immunostaining to bolster the conclusions from the biophysical studies. The paper has a significant impact in showing the role of Kv1.8 in determining utricular hair cell electrophysiological phenotypes.

Weaknesses:

1. From previous work it is known that GK,L in type I hair cells have unusual ion permeation and pharmacological properties that differ greatly from type II hair cell conductances. Notably GK,L is highly permeable to Cs+ as well as K+ ions and is slightly permeable to Na+. It is blocked by 4-aminopyridine and divalent cations (Ba2+, Ca2+, Ni2+), enhanced by external K+, and modulated by cyclic GMP. The question arises, if Kv1.8 is a major player and pore-forming subunit in type I and type II cells (and cochlear inner hair cells as shown by Dierich et al. 2020) how are subunits modified to produce channels with very different properties? A role for Kv1.4 channels (gA) is proposed in type II hair cells based on previous findings in bird hair cells and immunostaining for Kv1.4 channels in rat utricle presented here in Fig. 6. However, hair cell-specific partner interactions with Kv1.8 that result in GK,L in type I hair cells and Cs+ impermeable, inactivating currents in type II hair cells remain for the most part unexplored.

2. Data from patch-clamp and immunocytochemistry experiments are not in close alignment. XE991 (Kv7 channel blocker) decreases remaining K+ conductance in type I and type II hair cells from null mice supporting the presence of Kv7 channels in hair cells (Fig. 7). Also, Holt et al. (2007) previously showed inhibition of GK,L in type I hair cells (but not delayed rectifier conductance in type II hair cells) using a dominant negative construct of Kv7.4 channels. However, immunolabelling indicates Kv7.4 channels on the inner face of calyx terminals adjacent to hair cells (Fig. 5). Some reconciliation of these findings is needed.

3. Strong immunosignal appears in the cuticle plates of hair cells in addition to signal in basal regions of hair cells and supporting cells. Please provide a possible explanation for this.

4. A previous paper reported that a vestibular evoked potential was abnormal in Kv1.8-/- mice (Lee et al. 2013) as briefly mentioned (lines 94-95). It would be very interesting to know if any vestibular-associated behaviors and/or hearing loss were observed in the mice populations. If responses are compromised at the sensory hair cell level across different zones, degradation of balance function would be anticipated and should be elucidated.

Joint Public Review:

Zhang et. al. presents compelling results that support the identification of epigenetically mediated control for the recognition of dihydropyrimidine dehydrogenase (DPYD) gene expression that is linked with cancer treatment resistance 5-fluorouracil. The experimental approach was developed and pursued with in vitro and in vivo strategies. Combining molecular, cellular, and biochemical approaches, the authors identify a germline variant with compromised enhancer control. Several lines of evidence were presented that are consistent with increased CEBP recruitment to the DPYD regulatory domain with consequential modifications in promoter-enhancer interactions that are associated with compromised 5-fluorouracil resistance. Functional identification of promoter and enhancer elements was validated by CRISPRi and CRISPRa assays. ChIP and qPCR documented histone marks that can account for the control of DPYD gene expression were established. Consistency with data from patient-derived specimens and direct assessment of 5-fluorouracil sensitivity provides confidence in the proposed mechanisms. The model is additionally supported by genome data from a population with high "compromised allele frequency". It can be informative to directly demonstrate DPYD promoter-enhancer interactions. However, the genetic variants support the integration of regulatory activities.

Reviewer #1 (Public Review):

Summary:<br /> The authors originally investigated the function of p53 isoforms with an alternative C-terminus encoded by the Alternatively Spliced (AS) exon in place of exon 11 encoding the canonical "α" C-terminal domain. For this purpose, the authors create a mouse model with a specific deletion of the AS exon.

Strengths:<br /> Interestingly, wt or p53ΔAS/ΔAS mouse embryonic fibroblasts did not differ in cell cycle control, expression of well-known p53 target genes, proliferation under hyperoxic conditions, or the growth of tumor xenografts. However, p53-AS isoforms were shown to confer male-specific protection against lymphomagenesis in Eμ-Myc transgenic mice, prone to highly penetrant B-cell lymphomas. In fact, p53ΔAS/ΔAS Eμ-Myc mice were less protected from developing B-cell lymphomas compared to WT counterparts. The important difference that the authors find between WT and p53ΔAS/ΔAS Eμ-Myc males is a higher number of immature B cells in p53ΔAS/ΔAS vs WT mice. Higher expression of Ackr4 and lower expression of Mt2 was found in p53+/+ Eμ-Myc males compared to p53ΔAS/ΔAS counterparts, suggesting that these two transcripts are in part regulators of B-cell lymphomagenesis and enrichment for immature B cells.

Weaknesses:<br /> The manuscript is interesting but the data are not so striking and are very correlative. The authors should add functional experiments to reinforce their hypotheses and to provide, beyond potential prognostic factors, any potential mechanism at the basis of the different rates of B-cell lymphomagenesis in males vs females individuals and in WT vs p53ΔAS/ΔAS Eμ-Myc males.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript provides a detailed analysis of B-cell lymphomagenesis in mice lacking an alternative exon in the region encoding the C-terminal (regulatory) domain of the p53 protein and thus enable to assemble the so-called p53AS isoform. This isoform differs from canonical p53 by the replacement of roughly 30 c-terminal residues by about 10 residues encoded by the alternative exon. There is biochemical and biological evidence that p53AS retains strong transcriptional and somewhat enhanced suppressive activities, with mouse models expressing protein constructs similar to p53AS showing signs of increased p53 activity leading to rapid and lethal anemia. However, the precise role of the alternative p53AS variant has not been addressed so far in a mouse model aimed at demonstrating whether the lack of this particular p53 isoform (trp53ΔAS/ΔAS mice) may cause a specific pathological phenotype.

Results show that lack of AS expression does not noticeably affect p53 transcriptional activity but reveals a subtle pathogenic phenotype, with trp53ΔAS/ΔAS males, but not females, tending to develop more frequently and earlier B-cell lymphoma than WT. Next, the authors then introduced ΔAS in transgenic Eμ-Myc mice that show accelerated lymphomagenesis. They show that lack of AS caused increased lethality and larger tumor lymph nodes in p53ΔAS Eμ-Myc males compared to their p53WT Eμ-Myc male counterparts, but not in females. Comparative transcriptomics identified a small set of candidate, differentially expressed genes, including Ackr4 (atypical chemokine receptor 4), which was significantly less expressed in the spleens of ΔAS compared to WT controls. Ackr4 encodes a dummy receptor acting as an interceptor for multiple chemokines and thus may negatively regulate a chemokine/cytokine signalling axis involved in lymphomagenesis, which is down-regulated by estrogen signalling. Using in vitro cell models, the authors provide evidence that Ackr4 is a transcriptional target for p53 and that its p53-dependent activation is repressed by 17b-oestradiol. Finally, seeking evidence for a relevance for this gene in human lymphomagenesis, the authors analyse Burkitt lymphoma transcriptomic datasets and show that high ACKR4 expression correlated with better survival in males, but not in females

Strengths:<br /> A convincing demonstration of a subtle, gender-specific pathogenic phenotype associated with the lack of p53AS. The characterization of trp53ΔAS/ΔAS is well described and the data presented are convincing. This represents a significant achievement since, as mentioned, in vivo data establishing the relevance of p53AS isoform remains scarce. Based on this initial observation, the authors provide strong correlative evidence that this particular phenotype is associated by differential expression of Ackr4.

Weaknesses:<br /> The study does not demonstrate how p53AS may specifically and differentially contribute to the regulation of Ackr4, nor whether restoring Ackr4 expression may nullify the observed phenotype.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript "comparative transcriptomics reveal a novel tardigrade specific DNA binding protein induced in response to ionizing radiation" aims to provide insights into the mediators and mechanisms underlying tardigrade radiation tolerance. The authors start by assessing the effect of ionizing radiation (IR) on the tardigrade lab species, H. exemplaris, as well as the ability of this organism to recover from this stress - specifically, they look at DNA double and single-strand breaks. They go on to characterize the response of H. exemplaris and two other tardigrade species to IR at the transcriptomic level. Excitingly, the authors identify a novel gene/protein called TDR1 (tardigrade DNA damage response protein 1). They carefully assess the induction of expression/enrichment of this gene/protein using a combination of transcriptomics and biochemistry - even going so far as to use a translational inhibitor to confirm the de novo production of this protein. TDR1 binds DNA in vitro and co-localizes with DNA in tardigrades.

Reverse genetics in tardigrades is difficult, thus the authors use a heterologous system (human cells) to express TDR1 in. They find that when transiently expressed TDR1 helps improve human cell resistance to IR.

This work is a masterclass in integrative biology incorporating a holistic set of approaches spanning next-gen sequencing, organismal biology, biochemistry, and cell biology. I find very little to critique in their experimental approaches.

Strengths:<br /> 1. Use of trans/interdisciplinary approaches ('omics, molecular biology, biochemistry, organismal biology)<br /> 2. Careful probing of TDR1 expression/enrichment<br /> 3. Identification of a completely novel protein seemingly involved in tardigrade radio-tolerance.<br /> 4. Use of multiple, diverse, tardigrade species of 'omics comparison.

Weaknesses:<br /> 1. No reverse genetics in tardigrades - all insights into TDR1 function from heterologous cell culture system.<br /> 2. Weak discussion of Dsup's role in preventing DNA damage in light of DNA damage levels measured in this manuscript.<br /> 3. Missing sequence data which is essential for making a complete review of the work.

Overall, I find this to be one of the more compelling papers on tardigrade stress-tolerance I have read. I believe there are points still that the authors should address, but I think the editor would do well to give the authors a chance to address these points as I find this manuscript highly insightful and novel.

Reviewer #3 (Public Review):

Summary:<br /> This paper describes transcriptomes from three tardigrade species with or without treatment with ionizing radiation (IR). The authors show that IR produces numerous single-strand and double-strand breaks as expected and that these are substantially repaired within 4-8 hours. Treatment with IR induces strong upregulation of transcripts from numerous DNA repair proteins including Dsup specific to the Hypsobioidea superfamily. Transcripts from the newly described protein TDR1 with homologs in both Hypsibioidea and Macrobiotoidea supefamilies are also strongly upregulated. They show that TDR1 transcription produces newly translated TDR1 protein, which can bind DNA and co-localizes with DNA in the nucleus. At higher concentrations, TDR appears to form aggregates with DNA, which might be relevant to a possible function in DNA damage repair. When introduced into human U2OS cells treated with bleomycin, TDR1 reduces the number of double-strand breaks as detected by gamma H2A spots. This paper will be of interest to the DNA repair field and to radiobiologists.

Strengths:<br /> The paper is well-written and provides solid evidence of the upregulation of DNA repair enzymes after irradiation of tardigrades, as well as upregulation of the TRD1 protein. The reduction of gamma-H2A.X spots in U2OS cells after expression of TRD1 supports a role in DNA damage.

Weaknesses:<br /> Genetic tools are still being developed in tardigrades, so there is no mutant phenotype to support a DNA repair function for TRD1, but this may be available soon.

Reviewer #4 (Public Review):

The manuscript brings convincing results regarding genes involved in the radio-resistance of tardigrades. It is nicely written and the authors used different techniques to study these genes. There are sometimes problems with the structure of the manuscript but these could be easily solved. According to me, there are also some points which should be clarified in the result sections. The discussion section is clear but could be more detailed, although some results were actually discussed in the results section. I wish that the authors would go deeper in the comparison with other IR-resistant eucaryotes. Overall, this is a very nice study and of interest to researchers studying molecular mechanisms of ionizing radiation resistance.

I have two small suggestions regarding the content of the study itself.

1) I think the study would benefit from the analyses of a gene tree (if feasible) in order to verify if TDR1 is indeed tardigrade-specific.<br /> 2) It would be appreciated to indicate the expression level of the different genes discussed in the study, using, for example, transcript per millions (TPMs).

Reviewer #1 (Public Review):

Summary: Szathmary and colleagues explore the parabolic growth regime of replicator evolution. Parabolic growth occurs when nucleic acid strain separation is the rate-limiting step of the replication process which would have been the case for non-enzymatic replication of short oligonucleotide that could precede the emergence of ribozyme polymerases and helicases. The key result is that parabolic replication is conducive to the maintenance of genetic diversity, that is, the coexistence of numerous master sequences (the Gause principle does not apply). Another important finding is that there is no error threshold for parabolic replication except for the extreme case of zero fidelity.

Strengths:<br /> I find both the analytic and the numerical results to be quite convincing and well-described. The results of this work are potentially important because they reveal aspects of a realistic evolutionary scenario for the origin of replicators.

Weaknesses:<br /> There are no obvious technical weaknesses. It can be argued that the results represent an incremental advance because many aspects of parabolic replication have been explored previously (the relevant publications are properly cited). Obviously, the work is purely theoretical, experimental study of parabolic replication is due. In the opinion of this reviewer, though, these are understandable limitations that do not actually detract from the value of this work.

Reviewer #2 (Public Review):

Summary:

A dominant hypothesis concerning the origin of life is that, before the appearance of the first enzymes, RNA replicated non-enzymatically by templating. However, this replication was probably not very efficient, due to the propensity of single strands to bind to each other, thus inhibiting template replication. This phenomenon, known as product inhibition, has been shown to lead to parabolic growth instead of exponential growth. Previous works have shown that this situation limits competition between alternative replicators and therefore promotes RNA population diversity. The present work examines this scenario in a model of RNA replication, taking into account finite population size, mutations, and differences in GC content. The main results are (1) confirmation that parabolic growth promotes diversity, but that when the population size is small enough, sequences least efficient at replicating may nevertheless go extinct; (2) the observation that fitness is not only controlled by the replicability of sequences, but also by their GC content ; (3) the observation that parabolic growth attenuates the impact of mutations and, in particular, that the error threshold to which exponentially growing sequences are subject can be exceeded, enabling sequence identity to be maintained at higher mutation rates.

Strengths:

The analyses are sound and the observations are intriguing. Indeed, it has been noted previously that parabolic growth promotes coexistence, its role in mitigating the error threshold catastrophe - which is often presented as a major obstacle to our understanding of the origin of life - had not been examined before.

Weaknesses:

Although all the conclusions are interesting, most are not very surprising for people familiar with the literature. As the authors point out, parabolic growth is well known to promote diversity (Szathmary-Gladkih 89) and it has also been noted previously that a form of Darwinian selection can be found at small population sizes (Davis 2000). Given that under parabolic growth, no sequence is ever excluded for infinite populations, it is also not surprising to find that mutations have a less dramatic exclusionary impact.

A general weakness is the presentation of models and parameters, whose choices often appear arbitrary. Modeling choices that would deserve to be further discussed include the association of the monomers with the strands and the ensuing polymerization, which are combined into a single association/polymerization reaction (see also below), or the choice to restrict to oligomers of length L = 10. Other models, similar to the one employed here, have been proposed that do not make these assumptions, e.g. Rosenberger et al. Self-Assembly of Informational Polymers by Templated Ligation, PRX 2021. To understand how such assumptions affect the results, it would be helpful to present the model from the perspective of existing models.

The values of the (many) parameters, often very specific, also very often lack justifications. For example, why is the "predefined error factor" ε = 0.2 and not lower or higher? How would that affect the results? Similarly, in equation (11), where does the factor 0.8 come from? Why is the kinetic constant for duplex decay reaction 1.15e10−8? Are those values related to experiments, or are they chosen because specific behaviors can happen only then?

The choice of the model and parameters potentially impact the two main results, the attenuation of the error threshold and the role of GC content:

Regarding the error threshold, it is also noted (lines 379-385) that it disappears when back mutations are taken into account. This suggests that overcoming the error threshold might not be as difficult as suggested, and can be achieved in several ways, which calls into question the importance of the particular role of parabolic growth. Besides, when the concentration of replicators is low, product inhibition may be negligible, such that a "parabolic replicator" is effectively growing exponentially and an error catastrophe may occur. Do the authors think that this consideration could affect their conclusion? Can simulations be performed?

Regarding the role of the GC content, GC-rich oligomers are found to perform the worst but no rationale is provided. One may assume that it happens because GC-rich sequences are comparatively longer to release the product. However, it is also conceivable that higher GC content may help in the polymerization of the monomers as the monomers attach longer on the template (as described in Eq.(9)). This is an instance where the choice to pull into a single step the association and polymerization reactions are pulled into a single step independent of GC content may be critical. It would be important to show that the result arises from the actual physics and not from this modeling choice.

Some more specific points that would deserve to be addressed:

- Line 53: it is said that p "reflects how easily the template-reaction product complex dissociates". This statement is not correct. A reaction order p<1 reflects product inhibition, the propensity of templates to bind to each other, not slow product release. Product release can be limiting, yet a reaction order of 1 can be achieved if substrate concentrations are sufficiently high relative to oligomer concentrations (von Kiedrowski et al., 1991).

- Population size is a key parameter, and a comparison is made between small (10^3) and large (10^5) populations, but without explaining what determines the scale (small/large relative to what?).

- In the same vein, we might expect size not to be the only important parameter, but also concentration.

- Lines 543-546: if understanding correctly, the quantitative result is that the error threshold rises from 0.1 in the exponential case to 0.196 in the parabolic. Are the authors suggesting that a factor of 2 is a significant difference?

- Figure 3C: this figure shows no statistically significant effect?

- line 542: "phase transition-like species extension (Figure 4B)": such a clear threshold is not apparent.

Reviewer #1 (Public Review):

In their manuscript, Arjun et al. investigate the role of the histone acetyltransferase Gcn5 in the control of drosophila blood cell homeostasis in the larval lymph gland. They use gcn5 zygotic mutants as well as targeted knock-down and over-expression of Gcn5 in various lymph gland populations to show that these modulations impact (in a rather haphazard manner) niche cell number, blood cell progenitor maintenance, plasmatocyte differentiation, crystal cell differentiation or DNA damage accumulation. Their results suggest that Gcn5 controls autophagy and they show that decreasing the expression of the autophagy machinery increases blood cell differentiation. Using drugs to modulate the mTOR pathway, they conclude that Gcn5 levels are regulated by mTOR but that the impact of this pathway on blood cell homeostasis can override Gcn5 function.

While the authors did a lot of experiments and good quantifications of the blood cell phenotypes, many results do not make much sense or do not bring valuable information about Gcn5 mode of action. Several conclusions of the manuscripts are not backed by solid data (e.g. that Gcn5 action is mediated by TFEB and the autophagy machinery) and different aspects of the literature are not well taken into consideration. Some results (such as the validation of the knockdown and overexpression of Gcn5) seem flawed. There are some concerns about the results obtained with gcn5 zygotic mutants and an interpretation of the phenotypes observed upon manipulation of Gcn5 expression in different cell types is missing.

Important revisions are needed to improve the quality of the manuscript and confirm the authors' findings.

Reviewer #2 (Public Review):

Summary:<br /> Drosophila hematopoiesis has been shown to be governed by a number of signaling pathways such as JAK/STAT and Dpp. This important study shows the role of nutrient sensing and autophagy in determining blood cell differentiation. The authors show that General control non-derepressible 5 (Gcn5), a histone acetyltransferase affects blood cell differentiation. Gcn5 also negatively regulates autophagy through its effector TFEB which directly regulates autophagy genes. The authors also show that mTORC1 modulates Gcn5 levels and through it, TFEB activity thus acting as a fine-tuning mechanism that maintains optimal levels of autophagy.

Strengths:<br /> The main strength of the work lies in the interesting finding that cellular metabolic processes such as autophagy have a direct role in blood cell differentiation and has the potential to be of interest to those working on vertebrate haematopoiesis as well. The report has generated intriguing data, using promoters specific for sub-sections of the lymph gland, that different cellular subsets of the lymph gland contribute differently towards haematopoiesis, but this is not followed up in detail and the final conclusions are derived from a combination of whole lymph gland perturbations as well as those from specific promoters.

Weaknesses:<br /> 1. Gc5 seems to be expressed throughout the lymph gland but modulating it in the subsections does not have the same result. It is very striking that the knockdown of Gcn5 in the prohemocyte population does not have an effect on differentiation whereas overexpression does. The modulations of Gcn5 in PSC also have variable effects across hemocyte subpopulations which is not explored in the manuscript. Interestingly, also the domain deletion constructs show a differential effect on blood cell differentiation when altered solely in the prohemocytes which is not explained. While Gcn5 can be seen in all sections of the lymph gland in the first figure, under the HHLT-Gal4 and Hml-Gal4, Gcn5 looks cytoplasmic and almost completely excluded from the nucleus strikingly unlike Gcn5 expression under the Collier-Gal4 and Dome-Gal4. The rest of the experiments in the manuscript are done with multiple promoters, with autophagy flux measured by modulating Gcn5 with a pan hemocyte promoter, but the mTORC1-Gcn5 axis is explored using chemical modulators which affect the whole of the lymph gland (Fig7) or using two pro-hemocyte promoters (Fig8).

2. The knockdown of Gcn5 seems to affect the gland size (A compared to B and C). Since mTORC1 is a central regulator of cell size, it is possible that some of the effects seen in these knockdowns are potentially through mTORC1 affecting size suggesting that the signalling axis between mTORC1 and Gcn5 might not be a one-way axis as suggested in Figure 9. Also, this would mean that in experiments where absolute cell counts of crystal cells or niche cells are used to assess blood cell differentiation, further analysis to consider total cell numbers in the lymph gland would strengthen the manuscript.

3. A genetic manipulation of mTORC1 specifically in the pro hemocytes would strengthen the role of mTORC1 in the pathway rather than the chemical modulation which affects the whole of the lymph gland.

Reviewer #2 (Public Review):

Summary:<br /> This work describes the structure of Heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT), a lysosomal membrane protein that catalyzes the acetylation reaction of the terminal alpha-D-glucosamine group required for the degradation of heparan sulfate (HS). HS degradation takes place during the degradation of the extracellular matrix, a process required for restructuring tissue architecture, regulation of cellular function, and differentiation. During this process, HS is degraded into monosaccharides and free sulfate in lysosomes.

HGSNAT catalyzes the transfer of the acetyl group from acetyl-CoA to the terminal non-reducing amino group of alpha-D-glucosamine. The molecular mechanism by which this process occurs has not been described so far. One of the main reasons to study the mechanism of HGSNAT is that multiple mutations spanning the entire sequence of the protein, such as nonsense mutations, splice-site variants, and missense mutations lead to dysfunction that causes abnormal accumulation of HS within the lysosomes. This accumulation is a cause of mucopolysaccharidosis IIIC (MPS IIIC), an autosomal recessive neurodegenerative lysosomal storage disorder, for which there are no approved drugs or treatment strategies.

This paper provides a 3.26A structure of HGSNAT, determined by single-particle cryo-EM. The structure reveals that HGSNAT is a dimer in detergent micelles and a density assigned to acetyl-CoA. The authors speculate about the molecular mechanism of the acetylation reaction, map the mutations known to cause MPS IIIC on the structure and speculate about the nature of the HGSNAT disfunction caused by such mutations.

Strengths:<br /> The description of the architecture of HGSNAT is the highlight of the paper since this corresponds to the first description of the structure of a member of the transmembrane acyl transferase (TmAT) superfamily. The high resolution of an HGSNAT bound to acetyl-CoA is an important leap in our understanding of the HGSNAT mechanism. The density map is of high quality, except for the luminal domain. The location of the acetyl-CoA allows speculation about the mechanistic role of multiple residues surrounding this molecule. The authors thoroughly describe the architecture of HGSNAT and map the mutations leading to MPS IIIC. The description of the dimeric interphase is a novel result, and future studies are left to confirm the importance of oligomerization for function.

Weaknesses:<br /> Apart from the cryo-EM structure, the article does not provide any other experimental evidence to support or explain a molecular mechanism. Due to the complete absence of functional assays, mutagenesis analysis, or other structures such as a ternary complex or an acetylated enzyme intermediate, the mechanistic model depicted in Figure 5 should be taken with caution.

The authors discuss that H269 is an essential residue that participates in the acetylation reaction, possibly becoming acetylated during the process. However, there is no solid experimental evidence, e.g. mutagenesis analysis or structural analysis, in this or previous articles, that demonstrates this to be the case.

In the discussion part, the authors mention previous studies in which it was postulated that the catalytic reaction can be described by a random order mechanistic model or a Ping Pong Bi Bi model. However, the authors leave open the question of which of these mechanisms best describes the acetylation reaction. The structure presented here does not provide evidence that could support one mechanism or the other.

Although the authors map the mutations leading to MPS IIIC on the structure and use FoldX software to predict the impact of these mutations on folding and fold stability, there is no experimental evidence to support FoldX's predictions.

Reviewer #1 (Public Review):

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

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

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

Reviewer #3 (Public Review):

Summary:<br /> Navratna et al. have solved the first structure of a transmembrane N-acetyltransferase (TNAT), resolving the architecture of human heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT) in the acetyl-CoA bound state using single particle cryo-electron microscopy (cryoEM). They show that the protein is a dimer, and define the architecture of the alpha- and beta- GSNAT fragments, as well as convincingly characterizing the binding site of acetyl-CoA.

Strengths:<br /> This is the first structure of any member of the transmembrane acyl transferase superfamily, and as such it provides important insights into the architecture and acetyl-CoA binding site of this class of enzymes.

The structural data is of a high quality, with an isotropic cryoEM density map at 3.3Å facilitating the building of a high-confidence atomic model. Importantly, the density of the acetyl-CoA ligand is particularly well-defined, as are the contacting residues within the transmembrane domain.

The open-to-lumen structure of HSGNAT presented here will undoubtedly lay the groundwork for future structural and functional characterization of the reaction cycle of this class of enzymes.

Weaknesses:<br /> While the structural data for the open-to-lumen state presented in this work is very convincing, and clearly defines the binding site of acetyl-CoA, to get a complete picture of the enzymatic mechanism of this family, additional structures of other states will be required.

A potentially significant weakness of the study is the lack of functional validation. The enzymatic activity of the enzyme characterized was not measured, and the enzyme lacks native proteolytic processing, so it is a little unclear whether the structure represents an active enzyme.

Reviewer #1 (Public Review):

Summary:

This study describes all tangential neurons of the lobula plate (LOPs) of the fruit fly Drosophila melanogaster. Importantly, this is done in a complete manner, for the first time in any species. This means that for the first time, all neurons involved in transmitting wide-field optic flow information to the central brain are known. Exploiting known structure-function relations in these neurons (which are based on solid physiological data in different species of flies), the authors provide estimates of the physiological properties of all described neurons. Combined with transmitter predictions of these cells, this yields a full account of what information about wide-field motion is available to the central fly brain in order to derive behavioral commands from. The study goes one step further and includes anatomical descriptions and physiological property predictions for all major downstream target cells of LOPs.

Main strengths:

The paper is exceptional in three ways. First, it is the first comprehensive account of all tangential neurons of the lobula plate of an insect. This now provides the ground truth for similar studies in other insects. In particular, these results will allow neurons emerging in other species to be confidently described as novel/different from Drosophila, if they were not found in the current study. This is a major change from previously, when confidence in the non-existence of neuronal cell types in this system was impossible, as that system was not fully described.

Second, the rigorous prediction of physiological characteristics (flow-field encoding) in all anatomically described neurons provides a solid basis for system-wide modeling of optic flow encoding in Drosophila. Importantly, the presented physiological predictions include the downstream partner cells of the LOPs in the central brain, neurons for which only very few physiological descriptions exist, but which are essential for transforming optic flow input into behavioral outputs. This paper therefore opens a path towards closing the gap between sensory processing and behavior not only for a few identified and well-studied pathways, but for all wide-field motion processing that exists in a species.

Third, the connectomics work is not only based on one individual sample, but incorporates two EM volumes, analyzed with two different methods (manual tracing and auto segmentation/proofreading), using interhemispheric correspondence and inter-individual correspondence to validate the obtained neuron catalogue. Additionally, light microscopical data was used to validate the EM data. All of this provides exceptional levels of confidence in the presented results.

Main weaknesses:

While the authors compare their results with data from both larger flies and other work in Drosophila, a recent paper (Henning et al 2022) that presented novel data on the distribution of preferred motion directions in the fly lobula plate is not mentioned. This is unfortunate, as the claim of that paper is that the lobula plate contains six instead of four main tuning directions, both at the level of LOPs and T4/T5 input cells - a claim that could likely be directly confirmed or dismissed, or at least incorporated in the data presented in the current study. How would the flow-field predictions change if the data from Henning et al on T4 neurons was used as an input for the modeling rather than the classic four tuning directions?

While the authors nicely perform comparison to other fly species, a more general discussion of how the found cells relate to other insects, e.g. cells known from bees (e.g. Honkanen et al., 2023) or older work from locusts, could give the data more general relevance. While the comparison can likely not be done on a cell type level, given that the structure of the lobula complex is very different between those insects, the types of projections found and their physiologies, i.e. the overall patterns of how wide field motion is sent to the central brain, might be comparable and informative for highlighting general principles of motion processing.

Reviewer #2 (Public Review):

Summary:

In this study, Zhao, Nern, et al. investigate a population of neurons in the optic lobe of Drosophila melanogaster that process optic flow, relative motion between the insect's eyes and its environment that is generated during flight and provides useful information to the fly about its own self-motion. Although a sample of these Lobula Plate Tangential (LPT) neurons has been studied across Diptera in prior work, the full population has not been exhaustively and thoroughly cataloged in a single species, limiting our understanding of how LPT tuning properties across the population convey features of optic flow fields relevant to downstream motor regions.

Through extensive manual reconstructions in a fly electron microscopy volume, the authors of this study identify 58 LPT neurons in the fruit fly encompassing previously studied Horizontal and Vertical cells and novel cells that have not been previously characterized. Using the detailed anatomy of each cell and knowledge of upstream T4/T5 selectivity, the authors derive the predicted motion pattern map (PMPM) of each neuron. To understand how optic flow field tunings of individual LPTs align with global optic flow patterns flies are expected to encounter during flight such as translation and rotation, the authors compute the average angular difference between each PMPM and idealized rotation and translation optic flow fields. The authors also map individual LPTs to their counterparts in a second fly brain to explore LPT-LPT connectivity and downstream connectivity to central brain neuropils. They find that distinct groupings of LPTs have diverse downstream connectivity patterns and that downstream neurons align more closely to global optic flow fields that are expected during flight. This study is a valuable resource to researchers studying motion vision in the insect brain and is of interest to researchers studying sensorimotor processing by providing hypotheses for how optic flow information is integrated downstream to guide fly behavior.

Strengths:

A key strength of this study is the thoroughness with which the authors comprehensively identify individual LPT neurons in the FAFB volume. They not only conduct an impressive number of careful manual reconstructions to recover individual LPTs, but they also attempt, and often succeed, to map each individual neuron to its counterpart in light microscopy, studies across Diptera, and available auto-segmented connectome datasets such as FlyWire, FAFB-FFN1, and Hemibrain. The authors are similarly thorough when surveying individual LPT properties such as neurotransmitter identities, in some cases using multiple datasets to reconcile ambiguous neurotransmitter predictions. The care with which the complete LPT population has been identified establishes this study as a useful resource for future studies of insect motion.

In addition to providing a comprehensive catalog of individual LPTs, the authors also contextualize their findings within broader sensorimotor circuitry by considering connectivity between LPTs and from LPTs to downstream regions. Exploration of structure in downstream connectivity suggests that optic flow information is directed to various central brain neuropils through specific groups of LPTs. With some additional analyses, these results broaden the scope of this study by providing useful hypotheses for sensorimotor circuit organization.

Weaknesses:

A novel method introduced in this study is the derivation of individual LPT-predicted motion pattern maps (PMPMs) using T4 preferred directions and LPT morphology. Although this method underlies core findings in this study, such as alignment to global optic flow fields and properties of downstream integration, aspects of the methods used to derive PMPMs are not explained sufficiently well, particularly in the main text. For example, in the Methods, the authors briefly describe the process of computing a weighted sum of T4 preferred directions to obtain the PMPM for each LPT, but a detailed understanding of these preferred directions combined is missing in Figure 2 or the associated descriptions in the main text. It is also not clear how PMPMs are derived in cases where LOP layer coverages are overlapping (for example VS 13-1 in Figure 3) to yield smooth PMPMs. In addition, it is not clear how the PMPMs of bilateral LPTs such as LPT-45 and LPT-50 in Figure 4 were integrated to compute downstream target composite PMPMs. Finally, all the PMPMs were derived from the T4 preferred direction that relies on the ommatidial viewing directions ("Eyemap") introduced in Zhao et al. 2022. It is also important for the current study to give an indication of how sensitive their results are to possible inaccuracies in this map and derived T4/T5 direction selectivities.

Although the authors explore some features of connectivity from LPT to downstream partners (Figure 6), there is a lack of reconciliation of these findings with individual LPT properties explored earlier in the study, such as those presented in Figures 2-4. In that sense, there is a disconnect between the two parts of the manuscript (and a missed opportunity). For instance, an important follow-up analysis would be to use knowledge about LPT-LPT connectivity to better predict effective PMPMs of LPTs taking into account network effects. This extension would lead to a better understanding of how LPT-LPT interactions shape optic flow responses in the LOP. In addition, in Figure 6 Supplement 2 (which I recommend to move to the main figures), the authors show that LPTs can be grouped together based on similarity of output connectivity (Panel B-D) and that this structure corresponds to output synapses located in different groups of central brain neuropils. However, they do not attempt to explicitly link these groupings with individual LPT PMPMs, alignment to global optic flow patterns, LPT layer enervation, cell morphologies, and input connectivity patterns. Such an analysis would be an important step to bring the manuscript together and to get a better understanding of the organization of the whole system.

Reviewer #3 (Public Review):

Summary:

The fruit fly visual system has provided a powerful context in which to investigate fundamental questions in neural development, phototransduction, and systems neuroscience. Of recent interest is motion processing, particularly how visual motion cues are estimated locally, and then pooled to derive behaviorally meaningful signals. Many of these pooling operations have been shown to take place in the wide-field neurons in the lobula plate, cell types that have been explored using electrophysiological recordings for more than 50 years in a variety of Diptera. However, our understanding of the diversity and connectivity of these cells remains incompletely understood, and is of interest to many.

In this context, Reiser and colleagues describe the anatomy and connectivity of the complete set of Lobula Plate Tangential neurons in Drosophila, using a careful and systematic reconstruction of the FAFB dataset. Leveraging a previous study of retinal geometry, combined with their characterization of the anatomical inputs to the elementary motion detectors, T4 and T5, they then predict the motion sensitivities of each cell, their neurotransmitter identities, and map the connections of many of these cells into the central brain and contralateral optic lobe.

Strengths:

The quality of the connectomic analysis is exceptional, and the quantitative analysis that links connectivity to function is rigorous and impressive. This paper will be an important resource for the community.

Weaknesses:

Some of the findings could be better linked to previously published work in this field, and there may be a minor limitation to the predicted optimal motion axes, given one of the simplifying assumptions made.

Reviewer #1 (Public Review):

This study examined whether mitochondrial acyl-CoA thioesterase-2 (ACOT2) regulates mitochondrial matrix acyl-CoA levels. Acot2 deletion in murine skeletal muscle (SM) resulted in acyl-CoA build-up. When energy demand and pyruvate availability were elevated, a lack of ACOT2 activity promoted glucose oxidation. This preference for glucose over fatty acid oxidation was recapitulated in C2C12 myotubes with acute depletion of Acot2. In mice fed a high-fat diet, ACOT2 enabled the accretion of acyl-CoAs and ceramide derivatives in glycolytic SM, and this was associated with worse glucose homeostasis compared to when ACOT2 was absent. The authors suggest that ACOT2 supports CoASH availability to facilitate β-oxidation in glycolytic SM when lipid supply is modest. However, when lipid supply is high, ACOT2 enables acyl-CoA and lipid accumulation, CoASH sequestration, and poor glucose homeostasis. Thus, ACOT2 regulates matrix acyl-CoA concentration in glycolytic muscle, and its impact depends on lipid supply.

Based on the data provided in this study, the authors propose that ACOT2 regulates mitochondrial matrix acyl-CoA levels in white skeletal muscle to facilitate fatty acid oxidation β-oxidation. However, I do not believe the data supports this concept, since ACOT2 deletion actually increased fatty acid oxidation in the mitochondrial JO2 studies. In addition, there are some problems with the experimental data that the authors need to address. This includes the experimental conditions used to assess JO2 in the mitochondria, and not using Cre control mice.

Reviewer #2 (Public Review):

Summary:

The manuscript from Bekeova et al. entitled "Acyl-CoA thioesterase-2 facilitates P-oxidation in glycolytic skeletal muscle in a lipid supply dependent manner" examines whether loss of acyl-CoA thioesterase-2 (ACOT2) in the mitochondrial matrix of skeletal muscle alters mitochondrial fatty acid metabolism. The authors generate data demonstrating that under normal chow conditions, loss of ACOT2 increases mitochondrial respiration of long-chain fatty acid, but also increases susceptibility to the build-up of metabolic intermediates. However, during short-term high-fat feeding (7 days), mice with knockout of skeletal muscle ACOT2 had better glucose and insulin tolerance. Interestingly, skeletal muscle ACOT2 knockout mice on chow and high-fat diet utilized more glucose during the active (dark cycle) portion of the day. These data suggest that ACOT2 may be a potential therapeutic target to improve glucose homeostasis.

Strengths:

The use of creatine kinase cre recombinase to specifically target striated muscle localizes the genetic manipulation, thus increasing the rigor of these experiments by limiting potential off-site changes in ACOT2 expression. Also, the assessment of mitochondrial respiration and response to changes in energy change via the creatine kinase clamp technique is a strength. These data provide a measurement of isolated mitochondrial respiration at physiologically relevant concentrations of ATP and ADP, while also allowing for assessment of how these mitochondria respond to changes in free energy (Fisher-Wellman et al. 2018). The indirect calorimetry data provides systemic physiological context to the striated muscle-specific genetic manipulation, while also allowing for the examination of how this change in skeletal muscle ACOT2 impacts systemic responses to different energy challenges. Finally, the extensive metabolomics, transcriptomics, and lipidomics analysis, not only provides a wealth of data but is used to further the authors' investigation of skeletal muscle ACOT2 activity in mitochondrial fatty acid oxidation and glucose homeostasis.

Weaknesses:

Several general confounding factors exist in the experimental design that could potentially impact the interpretation of the observed outcomes. First, all mice were housed at housing temperatures (22C) below the thermoneutral zone, which has been well described by many investigators to result in dramatically increased energy expenditure. Changes in total and resting energy expenditure could alter the skeletal muscle and systemic utilization of lipids, response to high-fat diet, and glucose homeostasis. Second, no dietary control was observed in these experiments. While this did not impact outcomes when the diets were not compared, once the authors began to compare normal chow to high-fat diet, numerous differences in the composition of these diets could impact the outcomes. Third, the extended food withdrawal before the glucose- and insulin tolerance tests puts the mouse in a state of extreme energy stress more akin to starvation than fasting, which can negatively impact outcomes (Ayala et al. 2010, Virtue & Vidal-Puig 2021). Fourth, the use of the Seahorse platform for the assessment of respiration of isolated mitochondria is highly debatable (Schmidt et al. 2021), particularly when the investigators also used high-resolution respirometry specifically designed for the purpose of measuring isolated mitochondrial oxygen consumption. Importantly, the use of the Seahorse platform to assess cellular respiration in this investigation is quite appropriate. Finally, while the authors present data demonstrating that ACOT2 expression is highest in Type I fibers compared to the various Type II fiber types, a large number of the experiments are performed in a muscle that is primarily composed of Type II fibers. The authors briefly acknowledge this limitation. But, is important for the reader to keep this in mind when trying to consider how these findings would translate to humans.

Impact:

The authors have generated data that implicates skeletal muscle mitochondrial coenzyme A handling as a therapeutic target in the improvement of glucose homeostasis. While the exact role of increased tissue lipid burden on insulin action, glucose uptake, and substrate metabolism is still debated, the association between increased tissue lipid and impaired tissue- and systemic glucose handling is very strong. The data herein suggest that ACOT2 represents a pharmaceutical target to improve systemic glucose homeostasis in the population with obesity.

Reviewer #3 (Public Review):

Cells can oxidize diverse substrates in the mitochondria to sustain cellular energy metabolism. However, all of these substrates require covalent thioester linkage to coenzyme A (CoA). Thus, multiple energy metabolism substrates could potentially compete for a limited pool of mitochondrial CoA. Cells encode a set of mitochondrial acyl-CoA thioesterases (ACOTs) that free CoA up by removing attached substrates. The authors hypothesized that ACOT2, a mitochondrial ACOT with a preference for long-chain acyl-CoA substrates that arise during the oxidation of lipids as a fuel source, could regulate the balance of substrates used in the mitochondria by reducing the oxidation of lipids by removing them from CoA and freeing the mitochondrial pool of CoA for use by other substrates.

To test this hypothesis, the authors generated mice with loss of ACOT2 in the skeletal muscle, where this is most expressed, and assayed the CoA composition of muscle and their glucose/fatty acid catabolism in mice that were challenged with different diets, fasting or exercise to expose the muscle to different substrates conditions. These experiments were complemented with biochemical analysis of mitochondria isolated from the muscle of control and ACOT2 animals exposed to a variety of substrates and challenged with different simulated energy demands.

On the basis of these convincing experiments, the authors argue that loss of ACOT2 both in vivo and in vitro interestingly increases glucose oxidation, while not increasing oxidation of lipids. This is particularly surprising as the CoA competition model would predict that ACOT2 loss would increase lipid oxidation while hindering glucose oxidation. The authors argue that ACOT2 facilitates lipid oxidation due to ACOT2 reversal of lipid ligation to CoA preventing feedback inhibition of the lipid oxidation pathway that occurs when lipid supply outstrips the ability of the lipid oxidation pathway to metabolize the lipids. These findings will be valuable for the field of metabolism providing insight into how ACOTs regulate substrate catabolism in cells and tissues.

Reviewer #1 (Public Review):

The authors focused on genetic variability in relation to insulin resistance. The used genetically different lines of mice and exposed them to the same diet. They found that genetic predisposition impacts the overall outcome of metabolic disturbances.

Reviewer #2 (Public Review):

Summary:<br /> In the present study, van Gerwen et al. perform deep phosphoproteomics on muscle from saline or insulin-injected mice from 5 distinct strains fed a chow or HF/HS diet. The authors follow these data by defining a variety of intriguing genetic, dietary or gene-by-diet phosphor-sites which respond to insulin accomplished through application of correlation analyses, linear mixed models and a module-based approach (WGCNA). These findings are supported by validation experiments by intersecting results with a previous profile of insulin-responsive sites (Humphrey et al, 2013) and importantly, mechanistic validation of Pfkfb3 where overexpression in L6 myotubes was sufficient to alter fatty acid-induced impairments in insulin-stimulated glucose uptake. To my knowledge, this resource provides the most comprehensive quantification of muscle phospho-proteins which occur as a result of diet in strains of mice where genetic and dietary effects can be quantifiably attributed in an accurate manner. Utilization of this resource is strongly supported by the analyses provided highlighting the complexity of insulin signaling in muscle, exemplified by contrasts to the "classically-used" C57BL6/J strain. As it stands, I view this exceptional resource as comprehensive with compelling strength of evidence behind the mechanism explored. I raised several comments in the last round of assessment but all of them have now been thoughtfully addressed.

Strengths: Generation of a novel resource to explore genetic and dietary interactions influencing the phospho-proteome in muscle. This is accompanied by elegant application of in silico tools to highlight the utility

Weaknesses: none noted

Reviewer #3 (Public Review):

Summary:<br /> The authors aimed to investigate how genetic and environmental factors influence the muscle insulin signaling network and its impact on metabolism. They utilized mass spectrometry-based phosphoproteomics to quantify phosphosites in skeletal muscle of genetically distinct mouse strains in different dietary environments, with and without insulin stimulation. The results showed that genetic background and diet both affected insulin signaling, with almost half of the insulin-regulated phosphoproteome being modified by genetic background on an ordinary diet, and high-fat high-sugar feeding affecting insulin signaling in a strain-dependent manner.

Strengths:<br /> Study uses state-of-the-art phosphoproteomics workflow allowing quantification of a large number of phosphosites in skeletal muscle, providing a comprehensive view of the muscle insulin signaling network. The study examined five genetically distinct mouse strains in two dietary environments, allowing for the investigation of the impact of genetic and environmental factors on insulin signaling. The identification of coregulated subnetworks within the insulin signaling pathway expanded our understanding of its organization and provided insights into potential regulatory mechanisms. The study associated diverse signaling responses with insulin-stimulated glucose uptake, uncovering regulators of muscle insulin responsiveness.

Weaknesses:<br /> The limitations acknowledged by the authors, such as the need for larger cohorts and the inclusion of female mice. Moreover as acknowledged by authors, they are unable to dissect to what extent the obesity and different life span cycle for different strain affects insulin signaling. This suggest that further research is needed to validate and expand upon the findings.

Reviewer #2 (Public Review):

The authors use a high-throughput sequencing-based enrichment assay to measure how individual amino acids substitutions in the Rep proteins of AAV change the production of AAV. The key experiment involved the creation of all possible single codon mutations of the AAV2 rep gene in a barcoded format, transfection of the library into HEK293T cells for production of AAV, and sequencing to see which rep variants were enriched in the viral particles produced from the library. As the library rep variants were flanked by inverted terminal repeats for packaging into viral particles, the authors could use high-throughput sequencing of the barcodes to determine how much each rep variant supported the production of AAV. The rep gene libraries were cleverly made through a cloning process that ensured each mutant was attached to an exactly known 20nt barcode included in each mutagenic oligo (and subsequently moved to the end of the library genes by another cloning step). This allowed the authors to confidently observe nearly all rep variants in their experiments, resulting in a comprehensive map between Rep protein variants and AAV production. The overall map should act as a useful guide for AAV engineering. Not only did certain variants improve AAV production by ~2-fold and show generality across AAV capsid serotypes, the map might be used to predict greater effects through combinations of mutations, especially if augmented by natural evolutionary datasets and statistical learning.

In interpreting the results of this study, the reader should bear in mind that what has been measured and validated in high throughput is the production of intact genome-containing AAVs. The authors also successfully show transduction for selected high production variants. This is important as the efficiency by which an AAV preparations transduce cells is most relevant property for gene therapy.

Overall, this is a well-executed and well-analyzed study. The results support the conclusions and claims of the work. I see this work as a useful resource for engineering recombinant AAVs to increase their production, which should have broad impact as the use of AAVs in gene therapy grows.

Reviewer #3 (Public Review):

The study by Jain et al. on recombinant adeno-associated viruses (rAAVs) represents a valuable contribution to the fields of virus genetics and gene therapy. As non-pathogenic vectors, rAAVs have become a popular choice for delivering gene therapies. The authors have previously investigated the effects of all possible single codon substitutions, deletions, and insertions in the AAV2 cap gene on AAV production. In this study, they extend their analysis to the AAV2 rep gene and rep genes in two additional capsid serotypes, establishing a genotype-phenotype landscape that enhances our understanding of Rep protein function and offers potential strategies for improving Rep function in gene therapy applications. The experimental design is rigorous, the analyses well-executed, and the interpretations of the data are convincing. While I have a few suggestions to further refine the study, I believe it is overall an excellent piece of research.

One aspect that may warrant further consideration is the assumption, as mentioned in Figure 2's legend, that synonymous mutations are neutral and can serve as controls for normalizing the production rate. However, Figures S5-6 and Figures S11-12 suggest that synonymous mutations are not necessarily neutral, as their distribution is similar to that of nonsynonymous mutations. Thus, it may be beneficial to more thoroughly examine the potential effects of synonymous mutations on the genotype-phenotype landscape.

Additionally, previous research by Jeff Collar and others has reported that synonymous mutations can affect mRNA levels through mRNA degradation rate. It would be interesting to determine if the 20-bp barcodes located at the 3' end are positioned within the untranslated regions and could thus be employed to quantify the mRNA levels of individual variants. This information could offer insight into another potential mechanism by which single codon mutations impact the production rate of rAAV.

The authors discovered several novel mutations that enhance AAV production yet are absent in natural occurrences. This intriguing finding could benefit from further elaboration, particularly with regard to the distribution of these mutations within the protein structure and the nature of the amino acid transitions involved. It would also be informative if the authors could provide a brief discussion as to why these mutations have not been observed in nature. For instance, could it be that optimal viral fitness necessitates an intermediate production rate rather than an excessively rapid one? Expanding on these points may further enrich the paper and offer valuable insights for readers.

The authors have taken commendable steps to address the concerns I raised in my previous evaluation. They have provided comprehensive clarifications, performed necessary revisions, and expanded upon certain key points in the manuscript.

Reviewer #2 (Public Review):

Summary:

In this manuscript Nie et al investigate the effect of PARG KO and PARG inhibition (PARGi) on pADPR, DNA damage, cell viability and synthetic lethal interactions in HEK293A and Hela cells. Surprisingly, the authors report that PARG KO cells are sensitive to PARGi and show higher pADPR levels than PARG KO cells, which is abrogated upon deletion or inhibition of PARP1/PARP2. The authors explain the sensitivity of PARG KO to PARGi through incomplete PARG depletion and demonstrate complete loss of PARG activity when incomplete PARG KO cells are transfected with additional gRNAs in the presence of PARPi. Furthermore, the authors show that the sensitivity of PARG KO cells to PARGi is not caused by NAD depletion but by S-phase accumulation of pADPR on chromatin coming from unligated Okazaki fragments, which are recognized and bound by PARP1. Consistently, PARG KO or PARG inhibition show synthetic lethality with Pol beta, which is required for Okazaki fragment maturation. PARG expression levels in ovarian cancer cell lines correlate negatively with their sensitivity to PARGi.

Strengths:

The authors show that PARG is essential for removing ADP-ribosylation in S-phase.

Weaknesses:

1) This begs the question as to the relevant substrates of PARG in S-phase, which could be addressed, for example, by analysing PARylated proteins associated with replication forks in PARG-depleted cells (EdU pulldown and Af1521 enrichment followed by mass spectrometry).<br /> 2) The results showing the generation of a full PARG KO should be moved to the beginning of the Results section, right after the first Results chapter (PARG depletion leads to drastic sensitivity to PARGi), otherwise the reader is left to wonder how PARG KO cells can be sensitive to PARGi when there should be presumably no PARG present.<br /> 3) Please indicate in the first figure which isoforms were targeted with gRNAs, given that there are 5 PARG isoforms. You should also highlight that the PARG antibody only recognizes the largest isoform, which is clearly absent in your PARG KO, but other isoforms may still be produced, depending on where the cleavage sites were located.<br /> 4) FACS data need to be quantified. Scatter plots can be moved to Supplementary while quantification histograms with statistical analysis should be placed in the main figures.<br /> 5) All colony formation assays should be quantified and sensitivity plots should be shown next to example plates.<br /> 6) Please indicate how many times each experiment was performed independently and include statistical analysis.

Reviewer #3 (Public Review):

In the revised version the authors have addressed some of the reviewers' concerns, but, despite the new explanatory paragraph on page 16, the paper remains confusing because as shown in Figure 7 at the end of the Results the PARG KO 293A cells that were analyzed at the beginning of the Results are not true PARG knockouts. The authors stated that they did not rewrite the Results because they wanted to describe the experiments in the order in which they were carried out, but there is no imperative for the experiments to be described in the order in which they were done, and it would be much easier for the uninitiated reader to appreciate the significance of these studies if the true PARG KO cell data were presented at the beginning, as all three of the original reviewers proposed.

While the authors have to some extent clarified the nature of the PARG KO alleles, they have not been able to identify the source of the residual PARG activity in the PARG KO cells, in part because different commercial PARG antibodies give different and conflicting immunoblotting results. Additional sequence characterization of PARG mRNAs expressed in the PARG cKO cells, and also in-depth proteomic analysis of the different PARG bands could provide further insight into the origins and molecular identities of the various PARG proteins expressed from the different KO PARG alleles, and determine which of them might retain catalytic activity.

The authors have made no progress in identifying which are the key PARG substrates required for S phase progression, although they suggest that PARP1 itself may be an important target.

Reviewer #1 (Public Review):

Hu et al. performed sc-RNA-seq analyses of kidney cells with or without virus infection, vaccines, and vaccines+virus infections from pooled adult zebrafish. They compared within these experimental groups as well as kidney vs spleen. Their analyses identified expected populations but also revealed new hematopoietic stem/progenitor cell (HSPC), even in the spleen. Their analyses show that HSPCs in the kidney can respond to virus infection differentially and can be trained to recognize the same infection and argue that zebrafish kidney can serve as a secondary immune organ. The findings are important and interesting. The manuscript is well written and a pleasure to read. However, there are several issues with their figure presentation and figure qualities, as well as the lack of clarity in some of figure legends. Some of the data presentation can be improved for better clarity. It is also important to outline what is conserved and what is unique for fish.

Major concerns:

1. The visualization for several figure panels is very poor. Please provide high resolution images and larger font sizes for gene list or Y and X axis labels. This includes Figure 1B, Figure 1-figure supplement 2, Figure 2B-2C, 3A-3D, 4F, 5B, 6G, Figure 6-figure supplement 1B, Figure 6-figure supplement 2. Figure 7B, 8C-8E, Figure 8-figure supplement 1., 10F, 10G-10J, Figure 10-figure supplement 1.<br /> 2. What are the figures at the end of the manuscript without any figure legends?<br /> 3. It would be better to use a Table to organize the gene signatures that define each unique population of immune cells such as T, B, NK, etc.<br /> 4. What are the similarities for HSPC and immune cell populations between fish and man based on this research? It is better to form a table to compare and discuss.<br /> 5. It is highly likely that sex and age could be the biological variation for how HSPC responds to virus infections and vaccination. The author should clearly state the fish sex and age from their samples and discuss their results taking into consideration of these variations.<br /> 6. The authors claim that the spleen and kidney share HSPCs. However, their data did not demonstrate this result clearly in Figure 4A. Perhaps they should use different color to make the overlay becoming more obvious? Or include a table to show which HSPCs are shared between the kidney and spleen? Are they sure if these are just HSPCs seeding the spleen to differentiate into B cells or other immune cells?

Reviewer #2 (Public Review):

In this manuscript, the authors have meticulously constructed a comprehensive atlas delineating hematopoietic stem/progenitor cell (HSPC) and immune-cell types within the zebrafish kidney, employing single-cell transcriptome profiling analysis. Notably, these cell populations exhibited distinctive responses to viral infection. Intriguingly, the investigation revealed that HSPCs manifest positive reactivities to viral infection, indicating the effective induction of trained immunity in select HSPCs. Furthermore, the study unveiled the capacity for the generation of antigen-stimulated adaptive immunity within the kidney, suggesting a role for the zebrafish kidney as a secondary lymphoid organ. This research elucidates the distinctive features of the fish immune system and underscores the multifaceted biology of the kidney in ancient vertebrates.

Reviewer #1 (Public Review):

Summary:<br /> This useful work provides insight into agonist binding to muscle nicotinic receptors. The authors want to understand the fundamental steps in ligand binding to muscle nicotinic receptors using computational methods. The study builds on a large basis of empirical studies of the various states involved in receptor activation. However, the evidence supporting the conclusions is incomplete, because little support is available for the starting structures that are derived from ligand docking. This work is a useful starting point for more detailed work on ligand binding to this important class of receptors.

Strengths:<br /> The strengths include the number of ligands tried, and the relation to the mature analysis of the receptor function.

Weaknesses:<br /> The weaknesses are the brevity of the simulations, the concomitant lack of scope of the simulations, the lack of depth in the analysis, and the incomplete relation to other relevant work.

Reviewer #2 (Public Review):

Summary:<br /> The aim of this manuscript is to use molecular dynamics (MD) simulations to describe the conformational changes of the neurotransmitter binding site of a nicotinic receptor. The study uses a simplified model including the alpha-delta subunit interface of the extracellular domain of the channel and describes the binding of four agonists to observe conformational changes during the weak-to-strong affinity transition.

Strength:<br /> The 200 ns-long simulations of this model suggest that the agonist rotates about its centre in a 'flip' motion, while loop C 'flops' to restructure the site. The changes appear to be reproduced across simulations and different ligands and are thus a strong point of the study.

Weaknesses:<br /> After carrying out all-atom molecular dynamics, the authors revert to a model of binding using continuum Poisson-Boltzmann, surface area, and vibrational entropy. The motivations for and limitations associated with this approximate model for the thermodynamics of binding, rather than using modern atomistic MD free energy methods (that would fully incorporate configurational sampling of the protein, ligand, and solvent) could be provided. Despite this, the authors report a correlation between their free energy estimates and those inferred from the experiment. This did, however, reveal shortcomings for two of the agonists. The authors mention their trouble getting correlation to experiment for Ebt and Ebx and refer to up to 130% errors in free energy. But this is far worse than a simple proportional error, because -24 Vs -10 kcal/mol is a massive overestimation of free energy, as would be evident if the authors were to instead express results in terms of KD values (which would have an error exceeding a billion fold). The MD analysis could be improved with better measures of convergence, as well as a more careful discussion of free energy maps as a function of identified principal components, as described below. Overall, however, the study has provided useful observations and interpretations of agonist binding that will help understand pentameric ligand-gated ion channel activation.

Main points:<br /> Regarding the choice of model, some further justification of the reduced 2 subunit ECD-only model could be given. On page 5 the authors argue that, because binding free energies are independent of energy changes outside the binding pocket, they could remove the TMD and study only an ECD subunit dimer. While the assumption of distant interactions being small seems somewhat reasonable, provided conformational changes are limited and localised, how do we know the packing of TMD onto the ECD does not alter the ability of the alpha-delta interface to rearrange during weak or strong binding? They further write that "fluctuations observed at the base of the ECD were anticipated because the TMD that offers stability here was absent.". As the TMD-ECD interface is the "gating interface" that is reshaped by agonist binding, surely the TMD-ECD interface structure must affect binding. It seems a little dangerous to completely separate the agonist binding and gating infrastructure, based on some assumption of independence. Given the model was only the alpha and delta subunits and not the pentamer with TMD, I am surprised such a model was stable without some heavy restraints. The authors state that "as a further control we carried out MD simulation of a pentamer docked with ACh and found similar structural changes at the binding pocket compared to the dimer." Is this sufficient proof of the accuracy of the simplified model? How similar was the model itself with and without agonist in terms of overall RMSD and RMSD for the subunit interface and the agonist binding site, as well as the free energy of binding to each model to compare?

Although the authors repeatedly state that they have good convergence with their MD, I believe the analysis could be improved to convince us. On page 8 the authors write that the RMSD of the system converged in under 200 ns of MD. However, I note that the graph is of the entire ECD dimer, not a measure for the local binding site region. An additional RMSD of local binding site would be much more telling. You could have a structural isomerisation in the site and not even notice it in the existing graph. On page 9 the authors write that the RMSF in Figure S2 showed instability mainly in loops C and F around the pocket. Given this flexibility at the alpha-delta interface, this is why collecting those regions into one group for the calculation of RMSD convergence analysis would have been useful. They then state "the final MD configuration (with CCh) was well-aligned with the CCh-bound cryo-EM desensitized structure (7QL6)... further demonstrating that the simulation had converged." That may suggest a change occurred that is in common with the global minimum seen in cryo EM, which is good, but does not prove the MD has "converged". I would also rename Figure S3 accordingly.

The authors draw conclusions about the dominant states and pathways from their PCA component free energy projections that need clarification. It is important first to show data to demonstrate that the two PCA components chosen were dominant and accounted for most of the variance. Then when mapping free energy as a function of those two PCA components, to prove that those maps have sufficient convergence to be able to interpret them. Moreover, if the free energies themselves cannot be used to measure state stability (as seems to be the case), that the limitations are carefully explained. First, was PCA done on all MD trajectories combined to find a common PC1 & PC2, or were they done separately on each simulation? If so, how similar are they? The authors write "the first two principal components (PC-1 and PC-2) that capture the most pronounced C. displacements". How much of the total variance did these two components capture? The authors write the changes mostly concern loop C and loop F, but which data proves this? e.g. A plot of PC1 and PC2 over residue number might help.

The authors map the -kTln rho as a free energy for each simulation as a function of PC1 & PC2. It is important to reveal how well that PC1-2 space was sampled, and how those maps converged over time. The shapes of the maps and the relative depths of the wells look very different for each agonist. If the maps were sampled well and converged, the free energies themselves would tell us the stabilities of each state. Instead, the authors do not even mention this and instead talk about "variance" being the indicator of stability, stating that m3 is most stable in all cases. While I can believe 200ns could not converge a PC1-2 map and that meaningful delta G values might not be obtained from them, the issue of lack of sampling must be dealt with. On page 12 they write "Although the bottom of the well for 3 energy minima from PCA represent the most stable overall conformation of the protein, they do not convey direct information regarding agonist stability or orientation". The reasons why not must be explained; as they should do just that if the two order parameters PC1 and PC2 captured the slowest degrees of freedom for binding and sampling was sufficient. The authors write that "For all agonists and trajectories, m3 had the least variance (was most stable), again supporting convergence by 200 ns." Again the issue of actual free energy values in the maps needs to be dealt with. The probabilities expressed as -kTln rho in kcal/mol might suggest that m2 is the most stable. Instead, the authors base stability only on variance (I guess breadth of the well?), where m3 may be more localised in the chosen PC space, despite apparently having less preference during the MD (not the lowest free energy in the maps).

The motivations and justifications for the use of approximate PBSA energetics instead of atomistic MD free energies should be dealt with in the manuscript, with limitations more clearly discussed. Rather than using modern all-atom MD free energy methods for relative or absolute binding free energies, the author selects clusters from their identified states and does Poisson-Boltzmann estimates (electrostatic, vdW, surface area, vibrational entropy). I do believe the following sentence does not begin to deal with the limitations of that method: "there are limitations with regard to MM-PBSA accurately predicting absolute binding free energies (Genheden & Ryde, 2015; Hou et al., 2011) that depends on the parameterization of the ligand (Oostenbrink et al., 2004)." What are the assumptions and limitations in taking continuum electrostatics (presumably with parameters for dielectric constants and their assignments to regions after discarding solvent), surface area (with its assumptions and limitations), and of course assuming vibration of a normal mode can capture entropy. On page 30, regarding their vibrational entropy estimate, they write that the "entropy term provides insights into the disorder within the system, as well as how this disorder changes during the binding process". It is important that the extent of disorder captured by the vibrational estimate be discussed, as it is not obvious that it has captured entropy involving multiple minima on the system's true 3N-dimensional energy surface, and especially the contribution from solvent disorder in bound Vs dissociated states.

As discussed above, errors in the free energy estimates need to be more faithfully represented, as fractional errors are not meaningful. On page 21 the authors write "The match improved when free energy ratios rather than absolute values were compared." But a ratio of free energies is not a typical or expected measure of error in delta G. They also write "For ACh and CCh, there is good agreement between.Gm1 and GLA and between.Gm3 and GHA. For these agonists, in silico values overestimated experimental ones only by ~8% and ~25%. The agreement was not as good for the other 2 agonists, as calculated values overestimated experimental ones by ~45%(Ebt) and ~130% (Ebt). However, the fractional overestimation was approximately the same for GLA and GHA." See the above comment on how this may misrepresent the error. On page 21 they write, in relation to their large fractional errors, that they "do not know the origin of this factor but speculate that it could be caused by errors in ligand parameterization". However the estimates from the PBSA approach are, by design, only approximate. Both errors in parameterisation (and their likely origin) and the approximate model used, need discussion.

Reviewer #3 (Public Review):

Summary:<br /> The authors use docking and molecular dynamics (MD) simulations to investigate transient conformations that are otherwise difficult to resolve experimentally. The docking and simulations suggest an interesting series of events whereby agonists initially bind to the low-affinity site and then flip 180 degrees as the site contracts to its high-affinity conformation. This work will be of interest to the ion channel community and to biophysical studies of pentameric ligand-gated channels.

Strengths:<br /> I find the premise for the simulations to be good, starting with an antagonist-bound structure as an estimate of the low affinity binding site conformation, then docking agonists into the site and using MD to allow the site to relax to a higher affinity conformation that is similar to structures in complex with agonists. I cannot speak to the details of the simulation methods, but the predictions are interesting and provide a view into what a transient conformation that is difficult to observe experimentally might be like.

Weaknesses:<br /> Although the match in simulated vs experimental energies for two ligands was very good, the calculated energies for two other ligands were significantly different than the experiment. It is unclear to what extent the choice of method for the energy calculations influenced the results.

A control simulation, such as for an apo site, is lacking.

Reviewer #4 (Public Review):

Summary:<br /> In their manuscript "Conformational dynamics of a nicotinic receptor neurotransmitter binding site," Singh and colleagues present cogent molecular docking and dynamics simulations to explore the initial conformational changes associated with agonist binding in the muscle nicotinic acetylcholine receptor, aligned with the extensive experimental literature on this system. Their central findings are of a consistently preferred pose for agonists upon initial association with a resting channel, followed by a dramatic rotation of the ligand and contraction of a critical loop over the binding site. Principal component analysis also suggests the formation of an intermediate complex, not yet captured in structural studies. Binding free energy calculations are consistent with the evolution of a higher-affinity complex following agonist binding, with a ligand efficiency notably similar to experimental values. Snapshot comparisons provide a structural rationale for these changes on the basis of pocket volume, hydration, and rearrangement of key residues at the subunit interface.

Strengths:<br /> Docking results are clearly presented and remarkably consistent. Simulations are produced in triplicate with each of four different agonists, providing an informative basis for internal validation. They identify an intriguing transition in ligand pose, not well documented in experimental structures, and potentially applicable to mechanistic or even pharmacological modeling of this and related receptor systems. The paper seems a notable example of integrating quantitative structure-function analysis with systematic computational modeling and simulations, likely applicable to the wider journal audience.

Weaknesses:<br /> Timescales (200 ns) do not capture global rearrangements of the extracellular domain, let alone gating transitions of the channel pore, though this work may provide a launching point for more extended simulations. A more general concern is the reproducibility of the simulations, and how representative states are defined. It is not clear whether replicates were included in principal component analysis or subsequent binding energy calculations, nor how simulation intervals were associated with specific states. Structural analysis largely focuses on snapshots, with limited direct evidence of consistency across replicates or clusters. Figure legends and tables could be clarified.

Reviewer #3 (Public Review):

Summary:

In the manuscript "Ebola Virus Sequesters IRF3 in Viral Inclusion bodies to Evade Host Antiviral Immunity " by Lin Zhu et al, the authors elucidated an evasion mechanism by which EBOV evades host innate immunity.

Strengths:

Using data from immunofluorescence analysis, TEM and Western Blot, the authors conclude that Ebola virus VP35 protein evades host antiviral immunity by interacting with STING to sequester IRF3 into IBs and inhibit type-I interferon production.

Weaknesses:

Similar mechanisms have already been found in other viruses, such as SFTSV, RSV and so on. In addition, the presented results are also relatively rough, and the mechanism explained is not deep enough, so this story is not innovative

Reviewer #4 (Public Review):

The manuscript entitled "Ebola Virus Sequesters IRF3 in Viral Inclusion Bodies to Evade Host Antiviral Immunity" mainly describes that the function of IBs formed by the viral proteins VP35 and NP in evading host antiviral immunity. They proved that Ebola virus VP35 protein can interact with STING, but not IRF3, to sequester IRF3 into inclusion bodies and thereby inhibit type-I interferon production. This work will be of some interest to readers in the Ebola Virus field, however, the current data do not clearly explain the relationship of VP35 protein and IRF3.

Reviewer #1 (Public Review):

Bian et al showed that biomarker-informed PhenoAgeAccel was consistently related to an increased risk of site-specific cancer and overall cancer within and across genetic risk groups. The results showed that PhenoAgeAccel and genetic liability of a bunch of cancers serve as productive tools to facilitate the identification of cancer-susceptible individuals under an additive model. People with a high genetic risk for cancer may benefit from PhenoAgeAccel-informed interventions.

As the authors pointed out, the large sample size, the prospective design UK Biobank study, and the effective application of PhenoAgeAccel in predicting the risk of overall cancer are the major strengths of the study. Meanwhile, the CPRS seems to be a solid and comprehensive score based on incidence-weighted site-specific polygenic risk scores across 20 well-powered GWAS for cancers.

It wouldn't be very surprising to identify the association between PhenoAgeAccel and cancer risk, since the PhenoAgeAccel was constructed as a predictor for mortality which attributed a lot to cancer. Although cancer is an essential mediator for the association, sensitivity analyses using cancer-free mortality may provide an additional angle. It would be interesting to see, to what extent, PhenoAgeAccel could be reversed by environmental or lifestyle factors. G by E for PhenoAgeAccel might be worth a try.

Reviewer #2 (Public Review):

Summary:

Bian et al. calculated Phenotypic Age Acceleration (PhenoAgeAccel) via a linear model regressing Phenotypic Age on chronological age. They examined the associations between PhenoAgeAccel and cancer incidence using 374,463 individuals from the UK Biobank and found that older PhenoAge was consistently related to an increased risk of incident cancer, even among each risk group defined by genetics.

Strengths:

The study is well-designed, and uses a large sample size from the UK biobank.

Weaknesses:

Since the UK biobank has a large sample size, it should have enough power to split the dataset into discovery and validation sets. Why did the authors use 10-fold cross-validation instead of splitting the dataset?

Reviewer #1 (Public Review):

The objective of this study was to investigate the influence of the C. trachomatis effector Cdu1 on the ubiquitination of proteins in infected host cells and its correlation with the previously identified role of Cdu1 in facilitating Golgi distribution around the Chlamydia inclusion.

To achieve this, the authors created a cdu1-null mutant in C. trachomatis and employed proteomics to analyze ubiquitinated proteins in cells infected with Cdu1-producing and Cdu1-deficient chlamydiae, comparing them to mock-infected cells. The results revealed that, among the proteins specifically ubiquitinated after infection with Cdu1-deficient chlamydiae, three were other C. trachomatis effectors (InaC, IpaM, and CTL0480), members of a large family of Chlamydia effectors (Incs) that insert in the inclusion membrane.

Subsequently, the authors focused on understanding how Cdu1 shields InaC, IpaM, and CTL0480 from ubiquitination and the implications of this protection for the protein levels and functions of these Incs during infection. Data is presented showing that Cdu1 can bind to InaC, IpaM, and CTL0480, and protects these Incs and itself from ubiquitination and proteasomal degradation. This protective role of Cdu1 is dependent on its acetylation, but not on its deubiquitinating activity. Host cells infected by the cdu1 null mutant displayed defects resembling those observed in cells infected by inaC, ipaM, or ctl0480 null mutants.

Additionally, it was previously established that CTL0480 inhibits a chlamydial egress pathway involving the extrusion of the inclusion. This study now revealed that InaC and IpaM also play a role in promoting the extrusion of C. trachomatis inclusion, and the cdu1 null mutant exhibited a defect in this process. This leads to the title's conclusion that Cdu1 regulates chlamydial exit from host cells by safeguarding specific C. trachomatis effectors from degradation.

In summary, this work is excellent and impressive, both technically and conceptually, providing mechanistic insights into the action of Cdu1. The data provides convincing support for the proposed model, illustrating how the acetylation activity of Cdu1 protects itself and three Incs (InaC, IpaM, and CTL0480) from degradation. While the study indicates that the observed phenotypes in cells infected by the cdu1 null mutant are linked to reduced levels of InaC, IpaM, and CTL0480, these Incs are still detectable in cells infected by the cdu1 null mutant. Even if very unlikely, this leaves room for the possibility that Cdu1 directly promotes assembly of F-actin and Golgi repositioning around the inclusion, MYPT1 recruitment to the inclusion, and extrusion of the inclusion. Nevertheless, the major significance of this work lies in the integration of proteomics and chlamydial genetics to unveil a unique mechanism in which one effector controls the levels of other effectors, emphasizing the intricate relationships among bacterial effectors injected into host cells.

Reviewer #2 (Public Review):

Based on the corresponding author's response, the questions I raised were not addressed for various reasons. This is not necessarily a negative. The authors indicated that most of the points raised will be addressed in a separate manuscript. Specifically, the Cdu1 targeting of IkBa. They mentioned intriguing findings regarding IkBa in cells infected with a cdu1-null strain C. trachomatis in their response to reviewers. Similar to this, there appears to be a planned manuscript that will address the question of the timing of CTL0480's function in inclusion extrusion.

The lack of more direct infection-related evidence of Cdu1 interaction with various type III effectors was raised; and the authors attributed this to technical difficulties and low abundance of starting materials. It was not clear if they tried other approaches to demonstrate interaction.

Another suggestion was the quantitation of the three target effectors of Cdu1 in wild type and cdu1-null background. The authors provided western blot data and immunofluorescence images that revealed potential differences in stability/turnover kinetics. The authors might want to discuss the implications of the different kinetics of stability/turnover. For example, if all three proteins are necessary for optimal extrusion of inclusions, and concertedly act to mediate this process, all three would need to be present at the required levels. Could this be a temporal regulation strategy? Does acetylation also regulate function, interactions, etc.?

In short, the response to some of the questions is forthcoming in the form of follow-up manuscripts. New observations on the different stability profiles could be elaborated in the Discussion section, with a brief discussion on functional and/or regulatory implications.

Reviewer #3 (Public Review):

In this article by Bastidas et al. the authors examine the functions of the Chlamydia deubiquitinating enzyme 1 (Cdu1) during infections of human cells. First, a mutant lacking Cdu1 but not Cdu2 was constructed using targetron and quantitative proteomics was used to identify differences in ubiquitinated proteins (both host and bacterial) during infection. While they found minimal changes in host protein ubiquitination, they identified three Chlamydia effector proteins, IpaM, InaC and CTL0480 were all ubiquitinated in the absence of Cdu1. Microscopy and immunoprecipitations found Cdu1 directly interacts with these Chlamydia effectors and confirmed that Cdu1 mediates the stabilization of these effectors at the inclusion membrane during late infection time points. Surprisingly rather than deubiquitination driving this stabilization, the acetylation function of Cdu1 was required, and acetylation on lysine residues prevented degradative ubiquitination of Cdu1, IpaM, InaC and CTL0480. In line with this observation the authors show that loss of Cdu1 phenocopies the loss of single effector mutants of InaC, IpaM and CTL0480, including golgi stack formation and the recruitment of MYPT1 to the inclusion. The aggregation of changes to the Chlamydia inclusion does not alter growth but controls extrusion of chlamydia from cells with reduced extrusion in Cdu1 mutant Chlamydia infections. The strengths of the manuscript are the range of assays used to convincingly examine the biochemical and cellular biology underlying Cdu1 functions. The finding that acetylation of lysine residues is a mechanisms for bacterial effectors to block degradative ubiqutination is impactful and will open new investigations into this mechanism for many intracellular pathogens. The authors revisions to the manuscript have addressed my primary concerns and the authors present compelling arguments for remaining questions that are outside the scope of this study. Altogether this is an important series of findings that help to understand the mechanisms underpinning Chlamydia pathogenesis using orthologous methods and is an impactful study.

Reviewer #1 (Public Review):

In this paper, the authors developed an image analysis pipeline to automatically identify individual ‎‎neurons within a population of fluorescently tagged neurons. This application is optimized to deal with ‎‎multi-cell analysis and builds on a previous software version, developed by the same team, to resolve ‎‎individual neurons from whole-brain imaging stacks. Using advanced statistical approaches and ‎‎several heuristics tailored for C. elegans anatomy, the method successfully identifies individual ‎‎neurons with a fairly high accuracy. Thus, while specific to C. elegans, this method can ‎become ‎instrumental for a variety of research directions such as in-vivo single-cell gene expression ‎analysis ‎and calcium-based neural activity studies.‎

Reviewer #2 (Public Review):

The authors succeed in generalizing the pre-alignment procedure for their cell identification method to allow it to work effectively on data with only small subsets of cells labeled. They convincingly show that their extension accurately identifies head angle, based on finding auto florescent tissue and looking for a symmetric l/r axis. They demonstrate method works to allow the identification of a particular subset of neurons. Their approach should be a useful one for researchers wishing to identify subsets of head neurons in C. elegans, and the ideas might be useful elsewhere.

The authors also assess the relative usefulness of several atlases for making identity predictions. They attempt to give some additional general insights on what makes a good atlas, but here insights seem less clear as available data does not allow for experiments that cleanly decouple: 1. the number of examples in the atlas 2. the completeness of the atlas. and 3. the match in strain and imaging modality discussed. In the presented experiments the custom atlas, besides the strain and imaging modality mismatches discussed is also the only complete atlas with more than one example. The neuroPAL atlas, is an imperfect stand in, since a significant fraction of cells could not be identified in these data sets, making it a 60/40 mix of Openworm and a hypothetical perfect neuroPAL comparison. This waters down general insights since it is unclear if the performance is driven by strain/imaging modality or these difficulties creating a complete neuroPal atlas. The experiments do usefully explore the volume of data needed. Though generalization remains to be shown the insight is useful for future atlas building that for the specific (small) set of cells labeled in the experiments 5-10 examples is sufficient to build a accurate atlas.

Reviewer #1 (Public Review):

In this study, the authors examined the putative functions of hypothalamic groups identifiable through Foxb1 expression, namely the parvofox Foxb1 of the LHA and the PMd Foxb1, emphasizing innate defensive responses. First, they reported that chemogenetic activation of Foxb1hypothalamic cell groups led to tachypnea. The authors tend to attribute this effect to the activation of hM3Dq expressed in the parvofox Foxb1 but did not rule out the participation of the PMd Foxb1 cell group, which may as well have expressed hM3Dq, particularly considering the large volume (200 nl) of the viral construct injected. Notably, the activation of the Foxb1hypothalamic cell groups in this experiment did not alter the gross locomotor activity, such as time spent immobile state. Thus, this contrasts with the authors' finding on the optogenetic activation of the Foxb1hypothalamic fibers projecting to the dorsolateral PAG. In the second experiment, the authors applied optogenetic ChR2-mediated excitation of the Foxb1+ cell bodies' axonal endings in the dlPAG, leading to freezing and, in a few cases, bradycardia. The effective site to evoke freezing was the rostral PAGdl, and fibers positioned either ventral or caudal to this target had no response. Considering the pattern of Foxb1hypothalamic cell groups projection to the PAG, the fibers projecting to the rostral PAGdl are likely to arise from the PMd Foxb1 cell group and not from the parvofox Foxb1 of the LHA. Here, it is important to consider that activation of PMd CCK cell group, which consists of around 90% of the PMd cells, evokes escape, not freezing. According to the present findings, a specific population of PMd Foxb1 cells may be involved in producing freezing. In addition, only a few of the animals with correct fiber placement presented sudden onset of bradycardia in response to the photostimulation. Considering the authors' findings, the Foxb1+ hypothalamic groups are likely to mediate behavioral responses related to innate defensive responses, where the parvofox Foxb1 of the LHA would be involved in promoting tachypnea and the PMd Foxb1group in mediating freezing and bradycardia. These findings are exciting, and, at this point, they need to be tested in a scenario of actual exposure to a natural predator.

Reviewer #2 (Public Review):

The authors aimed to examine the role of a group of neurons expressing Foxb1 in behaviors through projections to the dlPAG. Standard chemogenetic activation or inhibition and optogentic terminal activation or inhibition at local PAG were used and results suggested that, while activation led to reduced locomotion and breathing, inhibition led to a small degree of increased locomotion.

The observed effects on breathing are evident and dramatic. However, due to the circumstance that does not permit to perform additional experiments, the conclusion is not as strong as it could be.

Reviewer #1 (Public Review):

This study investigates the underlying mechanisms of information-seeking in infancy. Eight-month-old Dutch infants were tested in a screen-based eye-tracking task in which one of two geometrical shape cues (differing in their shape and motion) either announced the location of an upcoming reward cartoon (informative) or not (non-informative). The authors measured the infants' pupil size before the cartoon appeared. Infants showed smaller pupil sizes when presented with the informative cue as compared to the noninformative cue. The decrease in pupil size in the informative condition emerged over the course of trials whereas infants' pupil size remained unchanged in the noninformative condition. The authors interpret their findings as supportive evidence of statistical learning and generalization processes organizing infants' information-seeking.

It was a pleasure to read the paper and I think the study makes a valuable contribution to our understanding of information-seeking in infancy. The manuscript is very well written and the study is cleverly designed. My following comments are based on my reading of the manuscript and the supplemental materials. It should be noted that evaluating the details of the statistical procedure the authors used lies outside my expertise. The same applies to some decisions of the authors related to pre-processing and filtering the pupil data. I very much appreciate that the authors shared all their raw data and analysis scripts openly accessible on the Open Science Framework. The study was unfortunately not preregistered, making it difficult to trace when in the study process certain decisions or assumptions were made.

My two main concerns relate to the conceptualization and definition of information-seeking and the proposed speed of the mechanisms explaining infants' behavior. I outline my general comments below before listing some more concrete issues.

1) While reading the manuscript, I was sometimes confused about what the authors refer to when talking about information-seeking - both in terms of the broader conceptualization of the phenomenon as well as when referring to their own study. What information are infants seeking? The informative value of the cue shape in terms of their motion (because it carries information about the location of a rewarding animation)? Or is the target (the rewarding video) the information being sought? From how the study is set up, I assume the authors refer mainly to the first aspect, but I think the manuscript would benefit from some clearer distinctions and definitions of terms.

More specifically, I think it could help if the authors would specify the different aspects involved in information-seeking in the introduction (e.g., seeking information "directly", seeking cues guiding them towards information, etc.). Secondly, it would help if they would sharpen their (already in some parts existing) definitions for their study and then keep consistent with their definitions throughout the methods, results, and discussion. Is the cue the information being sought or the "behavior" (motion) of the cue? Or is the target animation the information being sought and guided via the cueing?

2) Speed of the generalization process:<br /> From my understanding of the study design, the shape of the geometrical shape gains informative value over time (serving as an informative cue) and the *motion* of the shape is the actual informative or non-informative visual cue in that it either reliably highlights the actual target region (or all regions). In the generalization trials, only the shape was manipulated while the motion aspect remained consistent with the previous trials. Based on infants' behavior across learning and generalization trials, the authors make an argument about two distinct processes taking place: a slower allowing to learn where to find info and a faster generalization process. Apologies if I missed something, but given that the motion remains consistent, it's maybe not surprising that the generalization trials are "faster"? Maybe the generalization process would have been slower if not only the shape had changed but if also a novel informative motion had been introduced. Also, it would be helpful if the authors could clarify what they mean by the statistical learning process being more "data-hungry" (line 274).

3) I would find it very helpful if the authors would discuss statistical learning and information-seeking processes from other possible mechanisms such as reward learning mechanisms. For example, the authors use a "rewarding" (not informative) stimulus as the target-wouldn't it be possible that the results can be also explained by reinforcement learning processes? Relatedly, in line 396 they write that they used TD learning to predict whether "information will be delivered" and contrast this with the approach being used to predict whether a reward will be delivered. But in their study reward was being delivered, too (in the form of the target), in addition to the informative motion of the cue.

Reviewer #2 (Public Review):

Summary<br /> The study used eye tracking with a focus on pupillometry to examine how infants can learn to distinguish between informative and uninformative visual cues. Infants (n = 30, mean age = 8.2-months-old) viewed displays consisting of a sequence of stimuli: a fixation point, a central cue that predicted a subsequent informative or uninformative signal, the signal itself, and the target event (a cartoon animal, referred to as the reward). The key results are that: (1) pupil size differs depending on whether the infants anticipated an informative or uninformative signal, (2) this difference develops across trials, consistent with a slow learning process, and (3) there is rapid generalization when new shapes were introduced that shared features with the informative vs uninformative cues. The study complements a rich literature, including from this same group, showing that children are sensitive to information gains, and is interesting and important in revealing that pupil size is a physiological marker of information anticipation. We have several comments and concerns and believe that addressing them would substantially strengthen the manuscript.

Major points are related to interpretation, statistical robustness, and clarity

1. There is a tendency to overinterpret the findings.<br /> a. Throughout, the authors interpret the findings as meaning that pupil size tracks the "value" of information; however, the results do not demonstrate conclusively whether, or what kind of value information has in this task. A natural hypothesis is that infants are intrinsically motivated to predict - i.e., value the ability to predict the target event as early as possible. In a supplementary figure, the authors present evidence that infants indeed fixate on the target event sooner after seeing informative vs uninformative cues, consistent with the idea that they use the information for improving predictions. However, those results are not fully convincing, as we detail in point 2. Most importantly, the analysis is not integrated or even mentioned in the main analyses analysis. Making the link between the pupil reaction and the use of the information would greatly strengthen the paper (whether or not the supplementary findings hold up to more thorough scrutiny). Either this link should be made and discussed, or the authors should soften their conclusions about the utility of the informative cues.

b. On line 236, the text states that the evidence "...supports the growing body of evidence indicating that infants are proactive in shaping their learning environment by searching for and focusing on information-rich stimuli". The results do not show that the infants search for information, only that they have a pupil reaction that differentiates between informative and uninformative stimuli.

c. On lines 248-249, it seems a stretch to relate the changes in pupil dilation to a shift in information value onto the cue. Without some other measure (e.g., EEG), this remains speculative. While I believe the suggestion is plausible, the language should be softened to highlight this as a follow-up research question that the present research cannot directly speak to.

2. Several findings are statistically weak and several analyses are insufficiently controlled.

a. The analysis in Supplementary Figure 2, which shows that the latencies of target fixations are shorter after informative vs uninformative cues, raises several questions.<br /> i. We were unable to fully test these analyses as the OSF project seems to only contain latency data for 33 participants (including 22 of the 30 that remain in the final sample).<br /> ii. The results are described as revealing a significant difference, but the 89% confidence interval of the difference contains 0. How did the authors establish significance here?<br /> iii. How do the authors distinguish incidental fixations (which just happened to land near the target) from true predictive gaze shifts? Fixations were pooled if they occurred from 1.25 seconds before to 1 second after target onset. This is sufficient time for the eye to move in and out of the window several times. The authors should analyse the distributions of fixation durations to rule out various artifacts unrelated to target prediction.<br /> iv. Latencies to fixation were standardized, bringing the mean across each participant to 0, and yet the statistical model includes a random intercept; is there a justification for this?<br /> v. Standardizing removes information about whether fixations were proactive or reactive. It would be very interesting to see if/how information affects these two differently.<br /> vi. Since informativeness was learned across trials, it seems desirable that the model should include as random effects a trial number and an interaction between trial number and informativeness. This would allow a comparison between learning to predict and the pupil reaction. Are infants who have a stronger (or earlier) pupil reaction also more likely to show stronger learning to anticipate?

b. The main finding that pupil size differs between informative and uninformative cues is based on a 3-second analysis window. This long window most likely spans many saccades, which can affect pupil size on its own or by bringing the eye on or off visual stimuli. There is no analysis to show that the statistics of saccades or fixation locations are equivalent between the two trial types - but this is necessary to convincingly rule out a spurious artifact.

c. The second main finding that the effect of informativeness grows across trials seems statistically weak. The text (line 138) states that the interaction had a beta of 0.002, which was equal to the lower border of the 89%HDI ([0.002, 0.003]). For the second claim that pupil size decreased across informative trials, the beta is -0.002, and 89% HID is non-existent - i.e., [-0.002, -0.002]. (In general, the authors should check their numbers more carefully and make sure they are presented with a degree of precision that allows the reader to interpret them meaningfully.

d. The analyses do not indicate how well the TD model fits; we are shown only that it fits better than a linear model. On line 177 a correlation analysis is mentioned between the data and model, but the statistic cited for this test on line 179 is a mean beta coefficient, so it is impossible to know what this means. An analysis of goodness of fit or, at the very least, a figure superimposing the model and data, would be much more convincing.

3. The descriptions are very unclear in some key parts of the paper

a. The description of the TD model applied to pupil learning (starting on line 391) is very unclear. The model has to include some measure of informativeness - i.e., the match between the cued and true target location - but it is unclear how this was formalized. It is also very unclear how time within the trial is incorporated (the meaning of the TDE equation).

b. The description of the generalization analysis (Fig. 5) is also very unclear. Every single sentence in it evoked some confusion, so I will go through them one by one. "A Bayesian additive model showed that infants' pupil dilation was reduced for novel cues." Reduced relative to what? "This was specific to those novel cues that shared the features of the familiar informative cues (estimated mean difference = -0.05, 89%HDI = [-0.062, -0.038])." All the novel cues shared features with the informative cues; do the authors mean the novel cues that had the critical feature indicative of the informative cue? "The size of this effect approximated the difference between conditions that were observed for familiar stimuli (estimated mean difference = -0.067, 89% HDI = [-201 0.077, -0.057])." What is "this effect"? "Crucially, this difference was not observable at the start of the task, when the familiar stimuli were first introduced (estimated mean difference = -0.007, 89%HDI = [-0.015, 0.001])." At the start of the task, the stimuli were novel, and not familiar.

Reviewer #3 (Public Review):

Summary:<br /> The study attempts to shed light on the mechanisms underlying information-seeking in infants by investigating whether infants distinguish between informative and uninformative stimuli to resourcefully allocate their attention. The authors show that 8-month-old infants can learn whether a visual stimulus is informative or uninformative about the location of a later appearing rewarding stimulus by employing statistical regularities from the input. Specifically, infants showed decreased pupil dilation for informative over uninformative cues, which developed over the course of trials as more and more information was gathered from the input. The pattern of learning was in line with a reinforcement learning model which employed a steep learning curve in the beginning followed by a more shallow but steady learning growth over trials. After 17 trials, the authors presented novel cues that shared certain visual features with the previous stimuli and showed that pupil dilation was reduced for novel cues that shared features with the previous informative stimuli, suggesting that infants were able to generalize their acquired knowledge about the informativeness of certain features to novel stimuli. The present study adds to the existing literature about the underlying mechanisms of learning by showing that infants cannot only predict an upcoming stimulus based on statistical regularities of a preceding cue but also the informativeness of the cue itself.

Strengths:<br /> The authors use a suitable method to test the highly relevant question of whether and how infants infer the informativeness of stimuli from experience and whether they can generalize this knowledge to new stimuli. Their experiment is carefully designed and well controlled with conditions closely matched (e.g., the shape and color of objects and the structure of each trial). Their measure of interest (i.e., pupil dilation) is also examined at a time point in each trial when the conditions are the most similar, which further points to a thought-through and careful design. This empirical data is backed up with a computational approach (using a Bayesian model and training a reinforcement learning algorithm) to elucidate the learning mechanisms at play. This approach is explained concisely to readers not familiar with the models.

The results are convincing showing a clear difference between informative and uninformative condition and development over trials. Specifically, this difference is not apparent in the first trial (Fig. 2c) but develops over time which supports a learning trajectory. The data support the authors' conclusion that infants learn about the informativeness of the object cue from the input, and the employed learning algorithms give further insights into the learning trajectory of the infants. Overall, the statistical analyses seem solid and the priors for the Bayesian models are well reported.

Data and scripts are openly available fostering transparency.

Overall, the manuscript is very well and concisely written.

Weaknesses:<br /> The authors' conclusion that infants can generalize the acquired knowledge to similar but novel stimuli is weakened by methodological concerns regarding the analysis. It is not fully clear which trials the authors excluded and analyzed as they do not consistently report the trials in the manuscript (e.g., it is stated that after trial 17 the first generalization trial started, but also that trial 17 was excluded as the first trial of the generalization phase). As there are only a few novel trials and novel and familiar trials alternated, the inclusion or exclusion of trial analyses might have a significant impact on the results. Thus, this needs further clarification. The authors also mentioned that the novel stimuli shared relevant as well as irrelevant features, but it was not clear to me whether the authors could establish that only the relevant features contributed to the observed generalization effect.

Some methodological decisions were not explained and need justification, in particular, as the study is not preregistered. This includes, for example, the exclusion criteria and the choice not to analyze all generalization trials. Further, the authors did not perform model comparison (e.g., their model against a null model) and therefore do not report the strength of evidence for a difference in conditions.

Another weakness is that the sample sizes of 30 infants for the initial part and 19 infants for the generalization part of the experiment are rather small (especially with regard to the chosen weakly informative priors).

Reviewer #1 (Public Review):

Summary:<br /> This manuscript uses optical coherence tomography (OCT) to visualize tissue microstructures about 1-2 mm under the finger pad skin surface. Their geometric features are tracked and used to generate tissue strains upon skin surface indentation by a series of transparent stimuli both normal and tangential to the surface. Then movements of the stratum corneum and the upper portion of the viable epidermis are evaluated. Based upon this data, across a number of participants and ridges, around 300 in total, the findings report upon particular movements of these tissue microstructures in various loading states. A better understanding of the mechanics of the skin microstructures is important to understand how surface forces propagate toward the locations of mechanoreceptive end organs, which lie near the edge of the epidermis and dermis, from which tactile responses of at least two peripheral afferents originate. Indeed, the microstructures of the skin are likely to be important in shaping how neural afferents respond and enhance their sensitivity, receptive field characteristics, etc.

Strengths:<br /> The use of OCT in the context of analyzing the movements of skin microstructures is novel. Also novel and powerful is the use of distinct loading cases, e.g., normal, tangential, and stimulus features, e.g., edges, and curves. I am unaware of other empirical visualization studies of this sort. They are state-of-the-art in this field. Moreover, in addition to the empirical imaging observations, strain vectors in the tissues are calculated over time.

Weaknesses:<br /> The interpretation of the results and their framing relative to the overall hypotheses/questions and prior works could be articulated more clearly. In particular, the major findings of the manuscript are in newly describing a central concept regarding "ridge flanks," but such structures are neither anatomically nor mechanistically defined in a clear fashion. For example, "... it appears that the primary components of ridge deformation and, potentially, neural responses are deformations of the ridge flanks and their relative movement, rather than overall bending of the ridges themselves." From an anatomical perspective, I think what the authors mean by "ridge flanks" is a differential in strain from one lateral side of a papillary ridge to the other. But is it unclear what about the continuous layers of tissue would cause such behaviors. Perhaps a sweat duct or some other structure (not visible to OCT) would subdivide the "flanks" of a papillary ridge somehow? If not due to particular anatomy, then is the importance of the "ridge flank" due to a mechanistic phenomenon of some sort? Given that the findings of the manuscript center upon the introduction of this new concept, I think a greater effort should be made to define what exactly are the "ridge flanks." It is clear from the results, especially the sliding case, that there is something important that the manuscript is getting at with this concept.

The OCT used herein cannot visualize deep and fully into what the manuscript refers to as a "ridge" (note others have previously broken apart this concept apart into "papillary", "intermediate" and "limiting" ridges) near locations of the mechanoreceptive end organs lie at the epidermal-dermal border. Therefore, the OCT must make inferences about the movements of these deeper tissues, but cannot see them directly, and it is the movements of these deeper tissues that are likely driving the intricacies of neural firing. Note the word "ridge" is used often in the manuscript's abstract, introduction, and discussion but the definition in Fig. 1 and elsewhere differs in important ways from prior works of Cauna (expert in anatomy). Therefore, the manuscript should clarify if "ridge" refers to the papillary ridge (visible at the exterior of the skin), intermediate ridge (defined by Cauna as what the authors refer to as the primary ridge), and limiting ridge (defined by Cauna as what the authors refer to as the secondary ridge). What the authors really mean (I think) is some combination of the papillary and intermediate ridge structures, but not the full intermediate ridge. The manuscript acknowledges this in the "Limitations and future work" section, stating that these ridges cannot be resolved. This is important because the manuscript is oriented toward tracking this structure. It sets up the narrative and hypotheses to evaluate the prior works of Cauna, Gerling, Swensson, and others who all directly addressed the movement of this anatomical feature which is key to understanding ultimately how stresses at these locations might move the peripheral end organs (i.e., Merkel cells, Meissner corpuscles).

Reviewer #2 (Public Review):

Summary:<br /> The authors investigate sub-skin surface deformations to a number of different, relevant tactile stimuli, including pressure and moving stimuli. The results demonstrate and quantify the tension and compression applied from these types of touch to fingerprint ridges, where pressure flattens the ridges. Their study further revealed that on lateral movement, prominent vertical shearing occurred in ridge deformation, with somewhat inconsistent horizontal shear. This also shows how much the deeper skin layers are deformed in touch, meaning the activation of all cutaneous mechanoreceptors, as well as the possibility of other deeper non-cutaneous mechanoreceptors.

Strengths:<br /> The paper has many strengths. As well as being impactful scientifically, the methods are sound and innovative, producing interesting and detailed results. The results reveal the intricate workings of the skin layers to pressure touch, as well as sliding touch over different conditions. This makes it applicable to many touch situations and provides insights into the differential movements of the skin, and thus the encoding of touch in regards to the function of fingerprints. The work is very clearly written and presented, including how their work relates to the literature and previous hypotheses about the function of fingerprint ridges. The figures are very well-presented and show individual and group data well. The additional supplementary information is informative and the video of the skin tracking demonstrates the experiments well.

Weaknesses:<br /> There are very few weaknesses in the work, rather the authors detail well the limitations in the discussion. Therefore, this opens up lots of possibilities for future work.

Impact/significance:<br /> Overall, the work will likely have a large impact on our understanding of the mechanics of the skin. The detail shown in the study goes beyond current understanding, to add profound insights into how the skin actually deforms and moves on contact and sliding over a surface, respectively. The method could be potentially applied in many other different settings (e.g. to investigate more complex textures, and how skin deformation changes with factors like dryness and aging). This fundamental piece of work could therefore be applied to understand skin changes and how these impact touch perception. It can further be applied to understand skin mechanoreceptor function better and model these. Finally, the importance of fingertip ridges is well-detailed, demonstrating how these play a role in directly shaping our touch perception and how they can shape the interactions we have with surfaces.

Reviewer #3 (Public Review):

Summary:<br /> The publication presents unique in-vivo images of the upper layer of the epidermis of the glabrous skin when a flat object compresses or slides on the fingertip. The images are captured using OCT, and are the process of recovering the strain that fingerprints experience during the mechanical stimulation.

The most important finding is, in my opinion, that fingerprints undergo pure compression/tension without horizontal shear, hinting at the fact that the shear stress caused by the tangential load is transferred to the deeper tissues and ultimately to the mechanoreceptors (SA-I / RA-I).

Strengths:<br /> - Fascinating new insights into the mechanics of glabrous skin. To the best of my knowledge, this is the first experimental evidence of the mechanical deformation of fingerprints when subjected to dynamic mechanical stimulation. The OCT measurement allows an unprecedented measurement of the depth of the skin whereas previous works were limited to tracking the surface deformation.<br /> - The robust data analysis reveals the continuum mechanics underlying the deformation of the fingerprint ridges.

Weaknesses:<br /> I do not see any major weaknesses. The work is mainly experimental and is rigorously executed. Two points pique my curiosity, however:

1. How do the results presented in this study compare with previous finite element analysis? I am curious to know if the claim that the horizontal shear strain is transferred to the previous layer is also captured by these models. The reason is that the FEA models typically use homogeneous materials and whether or not the behavior in-silico and in-vivo matches would offer an idea of the nature of the stratum corneum.<br /> 2. Was there a specific reason why the authors chose to track only one fingerprint? From the method section, it seems that nothing would have prevented tracking a denser point cloud and reconstructing the stain on a section of the skin rather than just one ridge. With such data, the author could extend their analysis to multiple ridges interaction and get a better sense of the behavior of the entire strip of skin.

Reviewer #1 (Public Review):

This study aims to identify gene expression differences exclusively caused by cis-regulatory genetic changes by utilizing hybrid cell lines derived from human and chimpanzee. While previous attempts have focused on specific tissues, this study expands the comparison to six different tissues to investigate tissue specificity and derive insights into the evolution of gene expression.

One notable strength of this work lies in the use of composite cell lines, enabling a comparison of gene expression between human and chimpanzee within the same nucleus and shared trans factors environment. However, a potential weakness of the methodology is the use of bulk RNA-seq in diverse tissues, which limits the ability to determine cell-type-specific gene expression and chromatin accessibility regions. Their approach, using hybrid lines, naturally accounts for cell type heterogeneity avoiding the risk of false positives introduced by the otherwise confounding differences in cell type abundances between species, albeit the challenge of false negatives remains an issue. The authors now dully acknowledge this limitation in the manuscript.

Another concern is the use of two replicates derived from the same pair of individuals. While the authors produced cell lines from two pairs of individuals in a previous study (Agloglia et al., 2021). The reason for this experimental design is cost limitations. The authors now acknowledge that the use of replicates could enhance the ability to detect "more" species-specific changes in expression and chromatin accessibility. I would emphasize that replicates would increase robustness to the present findings, given that they are derived from a single pair of individuals.

Furthermore, the study offers the opportunity to relate inter-species differences to trends in molecular evolution. The authors discovered that expression variance and haploinsufficiency score do not fully account for the enrichment of divergence in cell-type-specific genes. The reviewer suggested exploring this further by incorporating external datasets that bin genes based on interindividual transcriptomics variation as a measure of extant transcriptomics constraint (e.g., GTEx reanalysis by Garcia-Perez et al., 2023 - PMID: 36777183). The authors considered this question to be out of the scope of the paper, yet in my opinion this would enhance one of the main findings of this study.

Additionally, stratifying sequence conservation on ASCA regions, which exhibit similar enrichment of cell-type-specific features, using the Zoonomia data mentioned also in the text (Andrews et al., 2023 -- PMID: 37104580) could provide valuable insights. While the author did not find Zoonomia Phastcons values available, they used PhastCons derived from a 470-way alignment of mammals. I commend the authors for their diligent efforts, which undoubtedly bolster their findings that an enrichment in ASCA is evident across all levels of sequence conservation. However, this recent analysis indicates the presence of a potential relationship between sequence conservation and ASCA. It may be advantageous to consider evaluating more quantile subdivisions of maxZ values and pPhastCons values, with the inclusion of these results in the supplementary materials. This approach would be preferable, even if the precise reasons behind the observed discrepancy are not fully elucidated.

Another potential strength of this study is the identification of specific cases of paired allele-specific expression (ASE) and allele-specific chromatin accessibility (ASCA) with biological significance. Prioritizing specific variants remains a challenge, and the authors apply a machine learning approach to identify potential causative variants that disrupt binding sites in two examples (FABP7 and GAD1 in motor neurons). However, additional work is needed to convincingly demonstrate the functionality of these selected variants. Strengthening this section with additional validation of ASE, ASCA, and the specific putative causal variants identified would enhance the overall robustness of the paper. The authors have opted to defer these validations to future studies.

Additionally, the authors support the selected ASE-ASCA pairs by examining external datasets of adult brain comparative genomics (Ma et al., 2022) and organoids (Kanton et al., 2019). While these resources are valuable for comparing observed species biases, the analysis is not systematic, even for the two selected genes. For example, it would be beneficial to investigate if FABP7 exhibits species bias in any cell type in Kanton et al.'s organoids or if GAD1 is species-biased in adult primate brains from Ma et al. Comparing these datasets with the present study, along with the Agoglia et al. reference, would provide a more comprehensive perspective. In the revised version of the manuscript the authors have evaluated the expression of GAD1 in Ma et al, and FABP7 in Sousa et al 2017. For instance, GAD1 show cell type specific species biases in the later. The authors opted for not showing this in the manuscript, However, it remains unclear why certain datasets were favored over others, or why FABP7 should not be evaluated in Kanton et al.

The use of the term "human-derived" in ASE and ASCA has now been avoided.

Finally, throughout the paper, the authors refer to "hybrid cell lines." It has been suggested to use the term "composite cell lines" instead to address potential societal concerns associated with the term "hybrid," which some may associate with reproductive relationships (Pavlovic et al., 2022 -- PMID: 35082442). The authors have presented an eloquent and persuasive explanation that I found to be highly informative.

Reviewer #3 (Public Review):

The authors utilize chimpanzee-human hybrid cell lines to assess cis-regulatory evolution. These hybrid cell lines offer a well-controlled environment, enabling clear differentiation between cis-regulatory effects and environmental or other trans effects.<br /> In their research, Wang et al. expand the range of chimpanzee-human hybrid cell lines to encompass six new developmental cell types derived from all three germ layers. This expansion allows them to discern cell type-specific cis-regulatory changes between species from more pleiotropic ones. Although the study investigates only two iPSC clones, the RNA- and ATAC-seq data produced for this paper is a valuable resource.

The authors begin their analysis by examining the relationship between allele-specific expression (ASE) as a measure of species divergence and cell type specificity. They find that cell-type-specific genes exhibit more divergent expression. By integrating this data with measures of constraint within human populations, the authors conclude that the increased divergence of tissue-specific genes is, at least in part, attributable to positive selection. A similar pattern emerges when assessing allele-specific chromatin accessibility (ASCA) as a measure of divergence of cis-regulatory elements (CREs) in the same cell lines.

By correlating these two measures, the authors identify 95 CRE-gene pairs where tissue-specific ASE aligns with tissue-specific ASCA. Among these pairs, the authors select two genes of interest for further investigation. Notably, the authors employ an intriguing machine learning approach in which they compare the inferred chromatin state of the human sequence with that of the chimpanzee sequence to pinpoint putatively causal variants.

Overall, this study delves into the examination of gene expression and chromatin accessibility within hybrid cell lines, showcasing how this data can be leveraged to identify potential causal sequence differences underlying between-species expression changes.

All in all most conclusions appear solid, with the exception of the interpretation of a cell type/state identification machine learning model to pinpoint putatively causal variants. The described variants lack any functional validation and there is no data that measure the certainty of the results.

Joint Public Review:

In this manuscript, the authors introduced an explicit ion model using the coarse-grained modelling approach to model the interactions between nucleosomes and evaluate their effects on chromatin organization. The strength of this method lies in the explicit representation of counterions, especially divalent ions, which are notoriously difficult to model. To achieve their aims and validate the accuracy of the model, the authors conducted coarse-grained molecular dynamics simulations and compared predicted values to the experimental values of the binding energies of protein-DNA complexes and the free energy profile of nucleosomal DNA unwinding and inter-nucleosome binding. Additionally, the authors employed umbrella sampling simulations to further validate their model, reproducing experimentally measured sedimentation coefficients of chromatin under varying salt concentrations of monovalent and divalent ions.

The significance of this study lies in the authors' coarse-grained model which can efficiently capture the conformational sampling of molecules while maintaining a low computational cost. The model reproduces the scale and, in some cases, the shape of the experimental free energy profile for specific molecule interactions, particularly inter-nucleosome interactions. Additionally, the authors' method resolves certain experimental discrepancies related to determining the strength of inter-nucleosomal interactions. Furthermore, the results from this study support the crucial role of intrinsic physicochemical interactions in governing chromatin organization within the nucleus.

The authors have successfully addressed the majority of my key concerns. I appreciate the clarification regarding the parameterization from Pablo's lab and the addition of comparisons of energy profiles as a function of inter-nucleosome distances.

However, the statement "The agreement is evident" may not sufficiently capture the essence of Figure S4, as there is a shortage of substantial agreement. The authors rightly acknowledge it but should delineate the nature of the observed discrepancies.

Reviewer #1 (Public Review):

Continuous attractor networks endowed with some sort of adaptation in the dynamics, whether that be through synaptic depression or firing rate adaptation, are fast becoming the leading candidate models to explain many aspects of hippocampal place cell dynamics, from hippocampal replay during immobility to theta sequences during run. Here, the authors show that a continuous attractor network endowed with spike frequency adaptation and subject to feedforward external inputs is able to account for several previously unaccounted aspects of theta sequences, including (1) sequences that move both forwards and backwards, (2) sequences that alternate between two arms of a T-maze, (3) speed modulation of place cell firing frequency, and (4) the persistence of phase information across hippocampal inactivations.

I think the main result of the paper (findings (1) and (2)) are likely to be of interest to the hippocampal community, as well as to the wider community interested in mechanisms of neural sequences. In addition, the manuscript is generally well written and the analytics are impressive. However, several issues should be addressed, which I outline below.

Major comments:

In real data, population firing rate is strongly modulated by theta (i.e., cells collectively prefer a certain phase of theta - see review paper Buzsaki, 2002) and largely oscillates at theta frequency during run. With respect to this cyclical firing rate, theta sweeps resemble "Nike" check marks, with the sweep backwards preceding the sweep forwards within each cycle before the activity is quenched at the end of the cycle. I am concerned that (1) the summed population firing rate of the model does not oscillate at theta frequency, and (2) as the authors state, the oscillatory tracking state must begin with a forward sweep. With regards to (1), can the authors show theta phase spike preference plots for the population to see if they match data? With regards to (2), can the authors show what happens if the bump is made to sweep backwards first, as it appears to do within each cycle?

I could not find the width of the external input mentioned anywhere in the text or in the table of parameters. The implication is that it is unclear to me whether, during the oscillatory tracking state, the external input is large compared to the size of the bump, so that the bump lives within a window circumscribed by the external input and so bounces off the interior walls of the input during the oscillatory tracking phase, or whether the bump is continuously pulled back and forth by the external input, in which case it could be comparable to the size of the bump. My guess based on Fig 2c is that it is the latter. Please clarify and comment.

I would argue that the "constant cycling" of theta sweeps down the arms of a T-maze was roughly predicted by Romani & Tsodyks, 2015, Figure 7. While their cycling spans several theta cycles, it nonetheless alternates by a similar mechanism, in that adaptation (in this case synaptic depression) prevents the subsequent sweep of activity from taking the same arm as the previous sweep. I believe the authors should cite this model in this context and consider the fact that both synaptic depression and spike frequency adaptation are both possible mechanisms for this phenomenon. But I certainly give the authors credit for showing how this constant cycling can occur across individual theta cycles.

The authors make an unsubstantiated claim in the paragraph beginning with line 413 that the Tsodyks and Romani (2015) model could not account for forwards and backwards sweeps. Both the firing rate adaptation and synaptic depression are symmetry breaking models that should in theory be able to push sweeps of activity in both directions, so it is far from obvious to me that both forward and backward sweeps are not possible in the Tsodyks and Romani model. The authors should either prove that this is the case (with theory or simulation) or excise this statement from the manuscript.

The section on the speed dependence of theta (starting with line 327) was very hard to understand. Can the authors show a more graphical explanation of the phenomenon? Perhaps a version of Fig 2f for slow and fast speeds, and point out that cells in the latter case fire with higher frequency than in the former?

I had a hard time understanding how the Zugaro et al., (2005) hippocampal inactivation experiment was accounted for by the model. My intuition is that while the bump position is determined partially by the location of the external input, it is also determined by the immediate history of the bump dynamics as computed via the local dynamics within the hippocampus (recurrent dynamics and spike rate adaptation). So that if the hippocampus is inactivated for an arbitrary length of time, there is nothing to keep track of where the bump should be when the activity comes back on line. Can the authors please explain more how the model accounts for this?

Can the authors comment on why the sweep lengths oscillate in the bottom panel of Fig 5b during starting at time 0.5 seconds before crossing the choice point of the T-maze? Is this oscillation in sweep length another prediction of the model? If so, it should definitely be remarked upon and included in the discussion section.

Perhaps I missed this, but I'm curious whether the authors have considered what factors might modulate the adaptation strength. In particular, might rat speed modulate adaptation strength? If so, would have interesting predictions for theta sequences at low vs high speeds.

I think the paper has a number of predictions that would be especially interesting to experimentalists but are sort of scattered throughout the manuscript. It would be beneficial to have them listed more prominently in a separate section in the discussion. This should include (1) a prediction that the bump height in the forward direction should be higher than in the backward direction, (2) predictions about bimodal and unimodal cells starting with line 366, (3) prediction of another possible kind of theta cycling, this time in the form of sweep length (see comment above), etc.

Reviewer #2 (Public Review):

In this work, the authors elaborate on an analytically tractable, continuous-attractor model to study an idealized neural network with realistic spiking phase precession/procession. The key ingredient of this analysis is the inclusion of a mechanism for slow firing-rate adaptation in addition to the otherwise fast continuous-attractor dynamics. The latter continuous-attractor dynamics classically arises from a combination of translation invariance and nonlinear rate normalization.

For strong adaptation/weak external input, the network naturally exhibits an internally generated, travelling-wave dynamics along the attractor with some characteristic speed. For small adaptation/strong external stimulus, the network recovers the classical externally driven continuous-attractor dynamics. Crucially, when both adaptation and external input are moderate, there is a competition with the internally generated and externally generated mechanisms leading to an oscillatory tracking regime. In this tracking regime, the population firing profile oscillates around the neural field tracking the position of the stimulus. The authors demonstrate by a combination of analytical and computational arguments that oscillatory tracking corresponds to realistic phase precession/procession. In particular the authors can account for the emergence of unimodal and bimodal cells, as well as some other experimental observations with respect the dependence of phase precession/procession on the animal's locomotion.

The strengths of this work are at least three-fold: 1) Given its simplicity, the proposed model has a surprisingly large explanatory power of the various experimental observations. 2) The mechanism responsible for the emergence of precession/procession can be understood as a simple yet rather illuminating competition between internally driven and externally driven dynamical trends. 3) Amazingly, and under some adequate simplifying assumptions, a great deal of analysis can be treated exactly, which allows for a detailed understanding of all parametric dependencies. This exact treatment culminates with a full characterization of the phase space of the network dynamics, as well as the computation of various quantities of interest, including characteristic speeds and oscillating frequencies.

As mentioned by the authors themselves, the main limitation of this work is that it deals with a very idealized model and it remains to see how the proposed dynamical behaviors would persists in more realistic models. For example, the model is based on a continuous attractor model that assumes perfect translation-invariance of the network connectivity pattern. Would the oscillating tracking behavior persist in the presence of connection heterogeneities? Another limitation is that the system needs to be tuned to exhibit oscillation within the theta range and that this tuning involves a priori variable parameters such as the external input strength. Is the oscillating-tracking behavior overtly sensitive to input strength variations? The author mentioned that an external pacemaker can serve to drive oscillation within the desired theta band but there is no evidence presented supporting this. A final and perhaps secondary limitation has to do with the choice of parameter, namely the time constant of neural firing which is chosen around 3ms. This seems rather short given that the fast time scale of rate models (excluding synaptic processes) is usually given by the membrane time constant, which is typically about 15ms. I suspect this latter point can easily be addressed.

Reviewer #1 (Public Review):

The study isolated extracellular vesicles (EV) from healthy controls (HCs) and Parkinson patients (PwP), using plasma from the venous blood of non-fasting people. Such EVs were characterized and validated by the presence of markers, their size, and their morphology. The main aim of the manuscript is to correlate the presence of synaptic proteins, namely SNAP-25, GAP-43, and SYNAPTOTAGMIN-1, normalized with HSP70, with the clinical progression of PwP. Changes in synaptic proteins have been documented in the CSF of Alzheimer's and Parkinson's patients. The demographics of participants are adequately presented. One important limiting, as well as puzzling aspect, is the fact that authors did not find differences between groups at the beginning of the study nor after one year, after age and sex adjustment.

Reviewer #2 (Public Review):

Hong and collaborators investigated variations in the amount of synaptic proteins in plasma extracellular vesicles (EV) in Parkinson's Disease (PD) patients on one-year follow-up. Their findings suggest that plasma EV synaptic proteins may be used as clinical biomarkers of PD progression.

It is a preliminary study using semi-quantitative analysis of synaptic proteins.

The authors have a cohort of PD patients with clinical examination and a know-how on EV purification. Regarding this latter part, they may improve their description of EV purification. EV may be broken into smaller size EV after freezing. Does it explain the relatively small size in their EV preparation? Do the authors refer to the MISEV guidelines for EV purity? Regarding synaptic protein quantification, the choice of western blotting may not be the best one. ELISA and other multiplex arrays are available. How the authors do justify their choice? Do the authors try to sort plasma EV by membrane-associated neuronal EV markers using either vesicle sorting or immunoprecipitation?

Many technical aspects may be improved. Such technical questions weakened the authors' conclusions.

Reviewer #1 (Public Review):

Summary:<br /> The authors used several zebrafish reporter lines to demonstrate the presence, regional distribution, and transcriptional profile of the immune cells in adult zebrafish brains. They identified DC-like cells distinct from microglia or other macrophages, resembling murine cDC1s. Analysis of different mutants further revealed that this DC population was dependent on Irf8, Batf3, and Csf1rb, but did not rely on Csf1ra.

Strengths:<br /> It is an elegantly designed study providing compelling evidence for further heterogeneity among brain mononuclear phagocytes in zebrafish, consisting of microglia, macrophages, and DC-like cells. This will provide a better understanding of the immune landscape in the zebrafish brain and will help to better distinguish the different cell types from microglia, and to assign specific functions.

Weaknesses:<br /> While scRNA-seq data clearly revealed different subsets of microglia, macrophages, and DCs in the brain, it remains somewhat challenging to distinguish DC-like cells from P2ry12- macrophages by immunohistochemistry or flow cytometry.

Reviewer #2 (Public Review):

The authors made an atlas of single-cell transcriptome of on a pure population of leukocytes isolated from the brain of adult Tg(cd45:DsRed) transgenic animals by flow cytometry. Seven major leukocyte populations were identified, comprising microglia, macrophages, dendritic-like cells, T cells, natural killer cells, innate lymphoid-like cells, and neutrophils. Each cluster was analyzed to characterize subclusters. Among lymphocytes, in addition to 2 subclusters expressing typical T cell markers, a group of il4+ il13+ gata3+ cells was identified as possible ILC2. This hypothesis is supported by the presence of this population in rag2KO fish, in which the frequency of lck and zap70+ cells is strongly reduced. The use of KO lines for such validations is a strength of this work (and the zebrafish model).

The subcluster analysis of mpeg1.1 + myeloid cells identified 4 groups of microglial cells, one novel group of macrophage-like cells (expressing s100a10b, sftpbb, icn, fthl27, anxa5b, f13a1b and spi1b), and several groups of DC like cells expressing the markers siglec15l, ccl19a.1, ccr7, id2a, xcr1a.1, batf3, flt3, chl1a and hepacam2. Combining these new markers and transgenic reporter fish lines, the authors then clarified the location of leukocyte subsets within the brain, showing for example that DC-like cells stand as a parenchymal population along with microglia. Reporter lines were also used to perform a detailed analysis of cell subsets, and cross with a batf3 mutant demonstrated that DC-like cells are batf3 dependent, which was similar to mouse and human cDC1. Finally, analysis of classical mononuclear phagocyte deficient zebrafish lines showed they have reduced numbers of microglia but exhibit distinct DC-like cell phenotypes. A weakness of this study is that it is mainly based on FACS sorting, which might modify the proportion of different subtypes.

This atlas of zebrafish brain leukocytes is an important new resource for scientists using the zebrafish models for neurology, immunology, and infectiology, and for those interested in the evolution of the brain and immune system.

Reviewer #3 (Public Review):

Rovira, et al., aim to characterize immune cells in the brain parenchyma and identify a novel macrophage population referred to as "dendritic-like cells". They use a combination of single-cell transcriptomics, immunohistochemistry, and genetic mutants to conclude the presence of this "dendritic-like cell" population in the brain. The strength of this manuscript is the identification of dendritic cells in the brain, which are typically found in the meningeal layers and choroid plexus. A weakness is the lack of specific reporters or labeling of this dendritic cell population using specific genes found in their single-cell dataset. Additionally, it is difficult to remove the meningeal layers from the brain samples and thus can lead to confounding conclusions. Overall, I believe this study should be accepted contingent on sufficient labeling of this population and addressing comments.

Reviewer #1 (Public Review):

Summary:<br /> This is a detailed description of the role of PKCδ in Drosophila learning and memory. The work is based on a previous study (Placais et al. 2017) that has already shown that for the establishment of long-term memory, the repetitive activity of MP1 dopaminergic neurons via the dopamine receptor DAMB is essential to increase mitochondrial energy flux in the mushroom body.

In this paper, the role of PKCδ is now introduced. PKCδ is a molecular link between the dopaminergic system and the mitochondrial pyruvate metabolism of mushroom body Kenyon cells. For this purpose, the authors establish a genetically encoded FRET-based fluorescent reporter of PKCδ-specific activity, δCKAR.

Strengths:<br /> This is a thorough study of the long-term memory of Drosophila. The work is based on the extensive, high-quality experience of the senior authors. This is particularly evident in the convincing use of behavioral assays and imaging techniques to differentiate and explore various memory phases in Drosophila. The study also establishes a new reporter to measure the activity of PKCδ - the focus of this study - in behaving animals. The authors also elucidate how recurrent spaced training sessions initiate a molecular gating mechanism, linking a dopaminergic punishment signal with the regulation of mitochondrial pyruvate metabolism. This advancement will enable a more precise molecular distinction of various memory phases and a deeper comprehension of their formation in the future.

Weaknesses:<br /> Apart from a few minor technical issues, such as the not entirely convincing visualisation of the localisation of a PKCδ reporter in the mitochondria, there are no major weaknesses. Likewise, the scientific classification of the results seems appropriate, although a somewhat more extensive discussion in relation to Drosophila would have been desirable.

Reviewer #2 (Public Review):

Summary<br /> This study deepens the former authors' investigations of the mechanisms involved in gating the long-term consolidation of an associative memory (LTM) in Drosophila melanogaster. After having previously found that LTM consolidation 1. costs energy (Plaçais and Préat, Science 2013) provided through pyruvate metabolism (Plaçais et al., Nature Comm 2017) and 2. is gated by the increased tonic activity in a type of dopaminergic neurons ('MP1 neurons') following only training protocol relevant for LTM, i.e. interspaced in time (Plaçais et al., Nature Neuro 2012), they here dig into the intra-cell signalling triggered by dopamine input and eventually responsible for the increased mitochondria activity in Kenyon Cells. They identify a particular PKC, PKCδ, as a major molecular interface in this process and describe its translocation to mitochondria to promote pyruvate metabolism, specifically after spaced training.

Methodological approach<br /> To that end, they use RNA interference against the isozyme PKCδ, in a time-controlled way and in the whole Kenyon cell populations or in the subpopulation forming the α/β lobe. This knock-down decreased the total PKCδ mRNA level in the brain by ca. 30%, and is enough to observe decreased in flies performances for LTM consolidation. Using Pyronic, a sensor for pyruvate for in vivo imaging, and pharmacological disruption of mitochondrial function, the authors then show that PKCδ knock-down prevents a high level of pyruvate from accumulating in the Kenyon cells at the time of LTM consolidation, pointing towards a role of PKCδ in promoting pyruvate metabolism. They further identify the PDH kinase PDK as a likely target for PKCδ since knocking down both PKCδ and PDK led to normal LTM performances, likely counterbalancing PKCδ knock-down alone.

To understand the timeline of PKCδ activation and to visualise its mitochondrial translocation in a subpart of Mushroom body lobes they imported in fruitfly the genetically-encoded FRET reporters of PKCδ, δCKAR, and mitochondria-δCKAR (Kajimoto et al 2010). They show that PKCδ is activated to the sensor's saturation only after spaced training, and not other types of training that are 'irrelevant' for LTM. Further, adding thermogenetic activation of dopaminergic neurons and RNA interference against Gq-coupled dopamine receptor to FRET imaging, they identify that a dopamine-triggered cascade is sufficient for the elevated PKCδ-activation.

Strengths and weaknesses<br /> The authors use a combination of new fluorescent sensors and behavioral, imaging, and pharmacological protocols they already established to successfully identify the molecular players that bridge the requirement for spaced training/dopaminergic neurons MP1 oscillatory activity and the increased metabolic activity observed during long-term memory consolidation.

The study is dense in new exciting findings and each methodological step is carefully designed. Almost all possible experiments one could think of to make this link have been done in this study, with a few exceptions that do not prevent the essential conclusions from being drawn.

The discussion is well conducted, with interesting parallels with mammals, where the possibility that this process takes place as well is yet unknown.

Impact<br /> Their findings should interest a large audience:<br /> They discover and investigate a new function for PKCδ in regulating memory processes in neurons in conjunction with other physiological functions, making this molecule a potentially valid target for neuropathological conditions. They also provide new tools in drosophila to measure PKCδ activation in cells. They identify the major players for lifting the energetic limitations preventing the formation of a long-term memory.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript reports the effects of a heterozygous mutation in the KCNT1 potassium channels on the properties of ion currents and the firing behavior of excitatory and inhibitory neurons in the cortex of mice expressing KCNT1-Y777H. In humans, this mutation as well as multiple other heterozygotic mutations produce very severe early-onset seizures and produce a major disruption of all intellectual function. In contrast, in mice, this heterozygous mutation appears to have no behavioral phenotype or any increased propensity to seizures. A relevant phenotype is, however, evident in mice with the homozygous mutation, and the authors have previously published the results of similar experiments with the homozygotes. As perhaps expected, the neuronal effects of the heterozygous mutation presented in this manuscript are generally similar but markedly smaller than the previously published findings on homozygotes. There are, however, some interesting differences, particularly on PV+ interneurons, which appear to be more excitable than wild type in the heterozygotes but more excitable in the heterozygotes. This raises the interesting question (which could be more explicitly discussed by the authors) as to whether the reported changes represent homeostatic events that suppress the seizure phenotype in the mouse heterozygotes or simply changes in excitability that do not reach the threshold for behavioral outcomes.

Strengths and Weaknesses:<br /> 1) The authors find that the heterozygous mutation in PV+ interneurons increases their excitability, a result that is opposite from their previous observation in neurons with the corresponding homozygous mutation. They propose that this results from the selective upregulation of a persistent sodium current INaP in the PV+ interneurons. While the observations are very interesting, there are three issues concerning this interpretation that should be addressed:<br /> A) The protocol for measuring the INaP current could potentially lead to results that could be (mis)interpreted in different ways in different cells. First, neither K currents nor Ca currents are blocked in these experiments. Instead, TTX is applied to the cells relatively rapidly (within 1 second) and the ramp protocol is applied immediately thereafter. It is stated that, at this time, Na currents and INaP are fully blocked but that any effects on Na-activated K currents are minimal. In theory, this would allow the pre- to post-difference current to represent a relatively uncontaminated INaP. This would, however, only work if activation of KNa currents following Na entry is very slow, taking many seconds. A good deal of literature has suggested that the kinetics of activation of KNa currents by Na influx vary substantially between cell types, such that single action potentials and single excitatory synaptic events rapidly evoke KNa currents in some cell types. This is, of course, much faster than the time of TTX application. Most importantly, the kinetics of KNa activation may be different in different neuronal types, which would lead to errors that could produce different estimates of INaP in PV+ interneurons vs other cell types.<br /> B) As the authors recognize, INaP current provides a major source of cytoplasmic sodium ions for the activation. An expected outcome of increased INaP is, therefore, further activation of KNa currents, rather than a compensatory increase in an inward current that counteracts the increase in KNa currents, as is suggested in the discussion.<br /> C) Numerical simulations, in general, provide a very useful way to evaluate the significance of experimental findings. Nevertheless, while the in-silico modeling suggests that increases in INaP can increase firing rate in models of PV+ neurons, there is as yet insufficient information on the relative locations of the INaP channels and the kinetics of sodium transfer to KNa channels to evaluate the validity of this specific model.

2) The greatest effect of TTX application would be expected to be the elimination of large transient inward sodium currents. Why are no such currents visible in the control (pre-TTX) or the difference currents (Fig. 2)? Is it possible I missed something in the methods?

3) As expected, the changes in many of the measured parameters are smaller in the present study with heterozygotes than those previously reported for the homozygous mutation. Some of the statements on the significance of some of the present findings need to be stated more clearly. For example, in the results section describing Fig. 2, it is stated that "In glutamatergic and NFS GABAergic YH-HET neurons, the overall KNa current was increased ...as measured by a significant effect of genotype ...." Later in the same paragraph it is stated that the increases in KNa current are not significant. Apparently, different tests lead to different conclusions. Both for the purpose of understanding the pathophysiological effects of changes in KNa current and for making further numerical simulations, more explicit clarifying statements should be made.

4) The effects of the KCNT1 channel blocker VU170 on potassium currents are somewhat larger and different from those of TTX, suggesting that additional sources of sodium may contribute to activating KCNT1, as suggested by the authors. Because VU170 is, however, a novel pharmacological agent, it may be appropriate to make more careful statements on this. While the original published description of this compound reported no effect on a variety of other channels, there are many that were not tested, including Na and cation channels that are known to activate KCNT1, raising the possibility of off-target effects.

5) The experiments were carried out at room temperature. Is it possible that different effects on firing patterns in heterozygotes and homozygotes would be observed at more physiological temperatures?

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Shore et al. investigate the consequent changes in excitability and synaptic efficacy of diverse neuronal populations in an animal model of juvenile epilepsy. Using electrophysiological patch-clamp recordings from dissociated neuronal cultures, the authors find diverging changes in two major populations of inhibitory cell types, namely somatostatin (SST)- and parvalbumin (PV)-positive interneurons, in mice expressing a variant of the KCNT1 potassium channel. They further suggest that the differential effects are due to a compensatory increase in the persistent sodium current in PV interneurons in pharmacological and in silico experiments.

Strengths:<br /> 1) Heterozygous KCNT1 gain of function variant was used which more accurately models the human disorder.<br /> 2) The manuscript is clearly written, and the flow is easy to follow. The authors explicitly state the similarities and differences between the current findings and the previously published results in the homozygous KCNT1 gain of function variant.<br /> 3) This study uses a variety of approaches including patch clamp recording, in silico modeling, and pharmacology that together make the claims stronger.<br /> 4) Pharmacological experiments are fraught with off-target effects and thus it bolsters the authors' claims when multiple channel blockers (TTX and VU170) are used to reconstruct the sodium-activated potassium current. Having said that, it would be helpful to see the two drug manipulations be used in the same experiment. Notably, does the more selective blocker VU170 mimic the results of TTX for NFS GABAergic cells in Figure 2? And does it unmask a genotype difference for FS GABAergic cells like the one seen in PV interneurons in Figure 5C3.

Weaknesses:<br /> 1) This study relies on recordings in dissociated cortical neurons. Although specific WT interneurons showed intrinsic membrane properties like those reported for acute brain slices, it is unclear whether the same will be true for those cells expressing KCNT1 variants. This reviewer highly recommends confirming some of the key findings using an ex vivo slice preparation. This is especially important given the discrepant result of reduced excitability of PV cells reported by Gertler et al., 2022 (cited here in the manuscript but not discussed in this context) in acute hippocampal slices for a different KCTN1 gain of function variant.<br /> 2) It is unclear how different pieces of results fit together to form a story about the disease pathophysiology. For example, hyperexcitability of PV cells would suggest more inhibition which would counter seizure propensity. However, spontaneous inhibitory postsynaptic currents show no change in pyramidal neurons. Moreover, how do the authors reconcile that the reductions in synaptic inputs onto interneurons in Figure 3B with the increases in Figure 8? This should be discussed.<br /> 3) Similarly, the results in this work are not entirely internally consistent. For example, given the good correspondence between FS and NFS GABAergic cells with PV and SST expression, why are FS GABAergic cells hyperexcitable in Figure 1? If anything, there is a tendency to show reduced excitability like the NFS GABAergic cells. Also, why do the WT I-V curves look so different between Figures 2 and 5? This reviewer suggests at least a brief explanation in the discussion.<br /> 4) Given the authors' claim that the KCNT1 activation curve is a major contributor to the observed excitability differences in specific GABA cell subtypes, it would be helpful to directly measure the activation curve in the variants experimentally as was done for WT KCNT1 in Figure 6A and use the derived kinetics in the compartmental model.

Reviewer #3 (Public Review):

Summary:<br /> The present manuscript by Shore et al. entitled Reduced GABAergic Neuron Excitability, Altered Synaptic Connectivity, and Seizures in a KCNT1 Gain-of-Function Mouse Model of Childhood Epilepsy" describes in vitro and in silico results obtained in cortical neurons from mice carrying the KCNT1-Y777H gain-of-function (GOF) variant in the KCNT1 gene encoding for a subunit of the Na+-activated K+ (KNa) channel. This variant corresponds to the human Y796H variant found in a family with Autosomal Dominant Nocturnal Frontal lobe epilepsy. The occurrence of GOF variants in potassium channel encoding genes is well known, and among potential pathophysiological mechanisms, impaired inhibition has been documented as responsible for KCNT1-related DEEs. Therefore, building on a previous study by the same group performed in homozygous KI animals, and considering that the largest majority of pathogenic KCNT1 variants in humans occur in heterozygosis, the Authors have investigated the effects of heterozygous Kcnt1-Y777H expression on KNa currents and neuronal physiology among cortical glutamatergic and the 3 main classes of GABAergic neurons, namely those expressing vasoactive intestinal polypeptide (VIP), somatostatin (SST), and parvalbumin (PV), crossing KCNT1-Y777H mice with PV-, SST- and PV-cre mouse lines, and recording from GABAergic neurons identified by their expression of mCherry (but negative for GFP used to mark excitatory neurons).

The results obtained revealed heterogeneous effects of the variant on KNa and action potential firing rates in distinct neuronal subpopulations, ranging from no change (glutamatergic and VIP GABAergic) to decreased excitability (SST GABAergic) to increased excitability (PV GABAergic). In particular, modelling and in vitro data revealed that an increase in persistent Na current occurring in PV neurons was sufficient to overcome the effects of KCNT1 GOF and cause an overall increase in AP generation.

Strengths:<br /> The paper is very well written, the results clearly presented and interpreted, and the discussion focuses on the most relevant points.

The recordings performed in distinct neuronal subpopulations are a clear strength of the paper. The finding that the same variant can cause opposite effects and trigger specific homeostatic mechanisms in distinct neuronal populations is very relevant for the field, as it narrows the existing gap between experimental models and clinical evidence.

Weaknesses:<br /> My main concern is in the epileptic phenotype of the heterozygous mice investigated. In fact, in their previous paper the Authors state that "...Kcnt1-Y777H heterozygous mice did not exhibit any detectable epileptiform activity" (first sentence on page 4). However, in the present manuscript, they indicate twice in the discussion section that these mice exhibit "infrequent seizures". This relevant difference needs to be clarified to correctly attribute to the novel pathophysiological mechanism a role in seizure occurrence. Were such infrequent seizures clearly identified on the EEG, or were behavioral seizures? Could the authors quantify this "infrequent" value? This is crucial also to place in the proper perspective the Discussion statement regarding "... the increased INaP contribution to ... network hyperexcitability and seizures".

Also, some statistical analysis seems to be missing. For example, I could not find any for the data shown in Fig. 6. Thus, the following statement: "the model PV neurons responded to KCNT1 GOF with decreased AP firing and an increased rheobase" requires proper statistical evaluation.

Reviewer #1 (Public Review):

Summary: This paper reported interesting aberrant calcium microwaves in the hippocampus when synapsin promoter driven GCaMPs were expressed for a long period of time. These aberrant hippocampal Ca2+ micro-waves depend on the viral titre of the GECI. The microwave of Ca2+ was not observed when GECI was expressed only in a sparse set of neurons.

Strengths: These findings are important to the wide neuroscience community, especially considering a great number of investigators are using similar approaches. Results look convincing and are consistent across several laboratories.

Weaknesses: One important question is needed to further clarify the mechanisms of aberrant Ca2+ microwaves as described below.

Synapsin promoter labels both excitatory pyramidal neurons and inhibitory neurons. To avoid aberrant Ca2+ microwave, a combination of Flex virus and CaMKII-Cre or Thy-1-GCaMP6s and 6f mice were tested. However, all these approaches limit the number of infected pyramidal neurons. While the comprehensive display of these results is appreciated, a crucial question remains unanswered. To distinguish whether the microwave of Ca2+ is caused selectively via the abnormality of interneurons, or just a matter of pyramidal neuron density, testing Flex-GCaMP6 in interneuron specific mouse lines such as PV-Cre and SOM-Cre will be critical.

Reviewer #2 (Public Review):

Summary:

The authors describe and quantify a phenomenon in the CA1 and CA3 of the hippocampus that they call aberrant Ca2+ micro-waves. Micro-waves are sometimes seen during 2-photon calcium imaging of populations of neurons under certain conditions. They are spatially confined slow calcium events that start in a few cells and slowly spread to neighboring groups of cells. This phenomenon has been uttered between researchers in the field at conferences, but no one has taken the time to carefully capture and quantify micro-waves and pin down the causes. The authors show that micro-waves are dependent on the viral titre of the genetically encoded calcium indicators (GECIs), the genetic promoter (synapsin), the neuronal subtype (granule cells in the dentate gyrus do not produce micro-waves and they are not seen in the neocortex), and the density of GECI expression. The authors should be commended for their work and raising awareness to all labs doing any form of calcium imaging in populations of neurons. The authors also come up with alternative approaches to avoid artifactual micro-waves such as reducing the transduction titre (1:2 dilution of virus) and a transduction method employing sparser and cre-dependent GECI expression in principal cells using a CaMKII promoter.

Strengths:

The micro-waves reported in the paper were robustly observed across 4 laboratories and 3 different countries with various experimenters and calcium imaging set-ups. This adds significant strength to the work.

The age of mice used covered a broad range (from 6 to 43 weeks). This is a strength because is covers most ages that are used in labs that regularly do calcium imaging.

Another strength is they used different GCaMP variants (GCaMP6m, GCaMP6s, GCaMP7f), as well a red indicator: RCaMP. This shows the micro-waves are not an issue with any particular GECI, as the authors suggest.

The authors include many movies of micro-waves. This is extremely useful for researchers in the field to view them in real-time so they can identify them in their own data.

They provide a useful table with specific details of the virus injected, titre, dilution, and other information along with the incidence of micro-waves. A nice look-up table for researchers to see if their viral strategy is associated with a high or low incidence of micro-waves.

Weaknesses:

Whether micro-waves are associated with the age of mice was not quantified. This would be good to know and the authors do have this data.

The effect of mico-waves on single cell function was not analyzed. It would be useful, for example, if we knew the influence of micro-waves on place fields. Can a place cell still express a place field in a hippocampus that produces micro-waves? What effect might a microwave passing over a cell have on its place field? Mice were not trained in these experiments, so the authors do not have the data.

The CaMKII-Cre approach for flexed-syn-GCaMP expression shows no micro-waves and is convincing, but it is only from 2 animals, even though both had no micro-waves.

The authors state in their Discussion that even without observable microwaves, a syn-Ca2+-indicator transduction strategy could still be problematic. This may be true, but they do not check this in their analysis, so it remains unknown.

Reviewer #3 (Public Review):

Summary:<br /> The work by Masala and colleagues highlights a striking artifact that can result from a particular viral method for expressing genetically encoded calcium indicators (GECIs) in neurons. In a cross-institutional collaboration, the authors find that viral transduction of GECIs in the hippocampus can result in aberrant slow-traveling calcium (Ca2+) micro-waves. These Ca2+ micro-waves are distinct from previously described ictal activity but nevertheless are likely a pathological consequence of overexpression of virally transduced proteins. Ca2+ micro-waves will most likely obscure the physiology that most researchers are interested in studying with GECIs, and their presence indicates that the neural circuit is in an unintended pathological state. Interestingly this pathology was not observed using the same viral transduction methods in the visual cortex. The authors recommend several approaches that may help other experimenters avoid this confound in their own data such as reducing the titer of viral injections or using recombinase-dependent expression. The intent of this manuscript is to raise awareness of the potential unintended consequences of viral overexpression, particularly for GECIs. A rigorous investigation into the exact causes of Ca2+ micro-waves or the mech

Strengths:

The authors clearly demonstrate that Ca2+ micro-waves occur in the CA1 and CA3 regions of the hippocampus following large volume, high titer injections of adeno-associated viruses (AAV1 and AAV9) encoding GECIs. The supplementary videos provide undeniable proof of their existence.

By forming an inter-institutional collaboration, the authors demonstrate that this phenomenon is robust to changes in surgical techniques or imaging conditions.

Weaknesses:

I believe that the weaknesses of the manuscript are appropriately highlighted by the authors themselves in the discussion. I would, however, like to emphasize several additional points.

As the authors state, the exact conditions that lead to Ca2+ micro-waves are unclear from this manuscript. It is also unclear if Ca2+ micro-waves are specific to GECI expression or if high-titer viral transduction of other proteins such as genetically encoded voltage indicators, static fluorescent proteins, recombinases, etc could also cause Ca2+ micro-waves.

The authors almost exclusively tested high titer (>5x10^12 vg/mL) large volume (500-1000 nL) injections using the synapsin promoter and AAV1 serotypes. It is possible that Ca2+ micro-waves are dramatically less frequent when titers are lowered further but still kept high enough to be useful for in vivo imaging (e.g. 1x10^12 vg/mL) or smaller injection volumes are used. It is also possible that Ca2+ micro-waves occur with high titer injections using other viral promoter sequences such as EF1α or CaMKIIα. There may additionally be effects of viral serotype on micro-wave occurrence.

The number of animals in any particular condition are fairly low (Table 1) with the exception of V1 imaging and thy1-GCaMP6 imaging. This prohibits rigorous comparison of the frequency of pathological calcium activity across conditions.

Reviewer #1 (Public Review):

Summary:<br /> This study delves into the roles of dact1 and dact2 during zebrafish embryonic axis formation and craniofacial morphogenesis. The researchers seek to unravel the mechanisms by which dact1/2 influences Wnt signaling modulation throughout embryonic development and patterning. They propose distinct spatiotemporal roles for Dact1 and Dact2 proteins in zebrafish embryonic development, highlighting their involvement in modulating noncanonical Wnt signaling during convergent extension events. Their findings demonstrate that dact1 and dact2 exhibit distinct spatiotemporal expression domains during development and that dact1/2 mutation leads to convergent extension defects. Furthermore, the study attempts to establish a link between convergent extension defects resulting from dact1/2 mutation and subsequent craniofacial abnormalities during development. To investigate the connection between dact1 and dact2, compound mutants were employed since single mutants did not exhibit craniofacial phenotypes. Additionally, the research encompasses comprehensive transcriptomics and pathway analyses of differentially expressed genes in dact1/2 mutants. This analysis reveals the overexpression of a calcium-dependent cysteine protease, calpain 8. The study suggests a connection between the upregulation of calpain 8 and the observed craniofacial dysmorphology in dact1/2 mutants, implying a potential link between the altered expression of calpain 8 and the craniofacial abnormalities observed in these mutants.

Strengths:<br /> The study beautifully recapitulates previous findings on the role of dact1/2 in modulating convergent extension during zebrafish embryogenesis.

A combination of multiple approaches, including in vivo time-lapse imaging, has been employed to elucidate the etiology of the rod-like neurocranial phenotype in dact1/2 double mutant.<br /> This study utilizes and discusses several 'traditional' mutant lines and newly created ones, analyzing them through single-cell transcriptomics.

Weaknesses:<br /> 1. Enhancing Reproducibility and Robustness:<br /> To enhance the reproducibility and robustness of the findings, it would be valuable for the authors to provide specific numbers of animals used in each experiment.<br /> Explicitly stating the penetrance of the rod-like neurocranial shape in dact1/2-/- animals would provide a clearer understanding of the consistency of this phenotype.

2. Strengthening Single-Cell Data Interpretation:<br /> To further validate the single-cell data and strengthen the interpretation of the gene expression patterns, I recommend the following:<br /> -Provide a more thorough explanation of the rationale for comparing dact1/2 double mutants with gpc4 mutants.<br /> -Employ genotyping techniques after embryo collection to ensure the accuracy of animal selection based on phenotype and address the potential for contamination of wild-type "delayed" animals.<br /> -Supplement the single-cell data with secondary validation using RNA in situ or immunohistochemistry techniques.

3. Directly Investigating Non-Cell-Autonomous Effects:<br /> To directly assess the proposed non-cell-autonomous role of dact1/2, I suggest conducting transplantation experiments to examine the ability of ectodermal/neural crest cells from dact1/2 double mutants to form wild-type-like neurocranium.

4. Further Elucidating Calpain 8's Role:<br /> To strengthen the evidence supporting the critical role of Calpain 8, I recommend conducting overexpression experiments using a sensitized background to enhance the statistical significance of the findings.

Reviewer #2 (Public Review):

Summary:<br /> Non-canonical Wnt signaling plays an important role in morphogenesis, but how different components of the pathway are required to regulate different developmental events remains an open question. This paper focuses on elucidating the overlapping and distinct functions of dact1 and dact2, two Dishevelled-binding scaffold proteins, during zebrafish axis elongation and craniofacial development. By combining genetic studies, detailed phenotypic analysis, lineage tracing, and single-cell RNA-sequencing, the authors aimed to understand (1) the relative function of dact1/2 in promoting axis elongation, (2) their ability to modulate phenotypes caused by mutations in other non-canonical wnt components, and (3) pathways downstream of dact1/2.

Strong qualitative evidence was provided to support dact1/2's role in genetically modulating non-canonical wnt signaling to regulate body axis elongation and the morphology of the anterior neurocranium (ANC). However, there is currently insufficient evidence supporting the author's claim that suppression of calpain 8 by dact1/2 is important for craniofacial development and that "embryonic fields determined during gastrulation affect the CNCC ability to contribute to the craniofacial skeleton".

Strengths:<br /> (1) The generation of dact1/2 germline mutants and the use of genetic approaches to dissect their genetic interactions with wnt11f2 and gpc4 provide unambiguous and consistent results that inform the relative functions of dact1 and dact2, as well as their combined effects.

(2) Because the anterior neurocranium exhibits a spectrum of phenotypes in different genetic mutants, it is a useful system for studying how tissue morphology can be modulated by different components of the same pathway, as demonstrated in this study.

(3) The authors leveraged lineage tracing by photoconversion to dissect how dact1/2 differentially impacts the ability of different cranial neural crest populations to contribute to the anterior neurocranium. This revealed that distinct mechanisms can lead to similar phenotypes in different mutants.

Weaknesses:<br /> (1) While the qualitative data show altered morphologies in each mutant, quantifications of these phenotypes are lacking in several instances, making it difficult to gauge reproducibility and penetrance, as well as to assess the novel ANC forms described in certain mutants.

(2) Germline mutations limit the authors' ability to study a gene's spatiotemporal functional requirement. They therefore cannot concretely attribute nor separate early-stage phenotypes (during gastrulation) to/from late-stage phenotypes (ANC morphological changes).

(3) Given that dact1/2 can regulate both canonical and non-canonical wnt signaling, this study did not specifically test which of these pathways is altered in the dact1/2 mutants, and it is currently unclear whether disrupted canonical wnt signaling contributes to the craniofacial phenotypes, even though these phenotypes are typical non-canonical wnt phenotypes.

(4) The use of single-cell RNA sequencing unveiled genes and processes that are uniquely altered in the dact1/2 mutants, but not in the gpc4 mutants during gastrulation. However, how these changes lead to the manifested ANC phenotype later during craniofacial development remains unclear. The authors showed that calpain 8 is significantly upregulated in the mutant, but the fact that only 1 out of 142 calpain-overexpressing animals phenocopied dact1/2 mutants indicates the complexity of the system.

(5) Craniofacial phenotypes observed in this study are attributed to convergent extension defects but convergent extension cell movement itself was not directly examined, leaving open if changes in other cellular processes, such as cell differentiation, proliferation, or oriented division, could cause distinct phenotypes between different mutants.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors explore the roles of dact1 and dact2 during zebrafish gastrulation and craniofacial development. Previous studies used morpholino (MO) knockdowns to show that these scaffolding proteins, which interact with disheveled (Dsh), are expressed during zebrafish gastrulation and suggested that dact1 promotes canonical Wnt/B-catenin signaling, while dact2 promotes non-canonical Wnt/PCP-dependent convergent-extension (Waxman et al 2004). This study goes beyond this work by creating loss-of-function mutant alleles for each gene and unlike the MO studies finds little (dact2) to no (dact1) phenotypic defects in the homozygous mutants. Interestingly, dact1/2 double mutants have a more severe phenotype, which resembles those reported with MOs as well as homozygous wnt11/silberblick (wnt11/slb) mutants that disrupt non-canonical Wnt signaling (Heisenberg et al., 1997; 2000). Further analyses in this paper try to connect gastrulation and craniofacial defects in dact1/2 mutants with wnt11/slb and other wnt-pathway mutants. scRNAseq conducted in mutants identifies calpain 8 as a potential new target of dact1/2 and Wnt signaling.

Strengths:<br /> When considered separately the new mutants are an improvement over the MOs and the paper contains a lot of new data.

Weaknesses:<br /> The hypotheses are very poorly defined and misinterpret key previous findings surrounding the roles of wnt11 and gpc4, which results in a very confusing manuscript. Many of the results are not novel and focus on secondary defects. The most novel result of overexpressing calpain8 in dact1/2 mutants is preliminary and not convincing.

Major Comments:<br /> 1) One major problem throughout the paper is that the authors misrepresent the fact that wnt11f2 and gpc4 act in different cell populations at different times. Gastrulation defects in these mutants are not similar: wnt11 is required for anterior mesoderm CE during gastrulation but not during subsequent craniofacial development while gpc4 is required for posterior mesoderm CE and later craniofacial cartilage morphogenesis (LeClair et al., 2009). Overall, the non-overlapping functions of wnt11 and gpc4, both temporally and spatially, suggest that they are not part of the same pathway.

2) There are also serious problems surrounding attempts to relate single-cell data with the other data in the manuscript and many claims that lack validation. For example, in Fig 1 it is entirely unclear how the Daniocell scRNA-seq data have been used to compare dact1/2 with wnt11f2 or gpc4. With no labeling in panel 1E of this figure these comparisons are impossible to follow. Similarly, the comparisons between dact1/2 and gpc4 in scRNA-seq data in Fig. 6 as well as the choices of DEGs in dact1/2 or gpc4 mutants in Fig. 7 seem arbitrary and do not make a convincing case for any specific developmental hypothesis. Are dact1 and gpc4 or dact2 and wnt11 co-expressed in individual cells? Eyeballing similarity is not acceptable.

3) Many of the results in the paper are not novel and either confirm previous findings, particularly Waxman et al (2004), or even contradict them without good evidence. The authors should make sure that dact2 loss-of-function is not compensated for by an increase in dact1 transcription or vice versa. Testing genetic interactions, including investigating the expression of wnt11f2 in dact1/2 mutants, dact1/2 expression in wnt11f2 mutants, or the ability of dact1/2 to rescue wnt11f2 loss of function would give this work a more novel, mechanistic angle.

4) The identification of calpain 8 overexpression in Dact1/2 mutants is interesting, but getting 1/142 phenotypes from mRNA injections does not meet reproducibility standards.