Reviewer #1 (Public Review):

Summary:<br /> The authors characterize S. enterica WbaP biochemically and structurally. The enzyme catalyzes the initial step in O antigen biosynthesis by transferring a phospho-galactosyl unit from UDP-galactose to undecaprenyl-phosphate. This initial primer is then extended by other glycosyltransferases to form the O antigen repeat unit.

To preserve the biologically functional unit of WbaP, the authors chose a 'detergent-free' purification method based on membrane extraction using SMALP polymers. The obtained material was characterized biochemically and by single-particle cryo-electron microscopy.

Strengths:<br /> The authors were able to isolate WbaP in a catalytically active and oligomeric form and determined a low-resolution cryo-EM structure of the dimeric complex. Using a disulfide cross-linking approach and other biophysical methods, the authors validated an AlphaFold predicted WbaP model used to interpret the experimental cryo-EM map.

Weaknesses:<br /> The rationale for using SMALP to extract WbaP from the membrane was to 'preserve' the native lipid bilayer surrounding the protein. However, the physical properties of the lipids co-purifying with the protein are unclear. The volume of the EM map assigned to the SMALP polymers suggests a more micellar character.

Overall, the obtained cryo-EM map appears to be at fairly low resolution. Based on Figure 6, individual helices are not resolved, suggesting an overall resolution significantly below the stated 4.1 Å. Thus, the presented structure is the one of an AlphaFold WbaP model.

I believe the UMP titration analysis could be improved. The authors assume that a 'domain of unknown function (DUF)' binds UMP and regulates the enzyme's activity. UMP, a reaction product of WbaP, may also inhibit the enzyme competitively. Therefore, deleting the DUF for the UMP inhibition studies could help with data interpretation.

Reviewer #2 (Public Review):

Summary:<br /> The authors focused on delivering a comprehensive structural characterization of WbaP, a membrane-bound phosphoglycosyl transferase from Salmonella that is instrumental in bacterial glycoconjugate synthesis. Notably, the authors employed SMALP-200, an amphipathic copolymer, to extract WbaP in the form of native lipid bilayer nanodiscs. They then determined its oligomerization state through cross-linking and procured higher-resolution structural data via cryo-electron microscopy (cryo-EM). While the authors successfully characterized WbaP in a native-like lipid bilayer setting, and their findings support this, the paper's claim of introducing a novel methodology is not robust. The real contribution of this work lies in the newfound insights about WbaP's structure.

Strengths:<br /> The manuscript provides novel insights into WbaP's structure and oligomerization state, highlighting potentially significant interactions. The methodologies employed represent state-of-the-art practices in the field. Most of the drawn conclusions are well-supported by either experimental or computational data, with a few exceptions noted below.

Weaknesses:<br /> • Organization: The manuscript's organization lacks clarity. The authors seem to describe their processes in the sequence they occurred rather than a logical flow, leading to potential confusion. For instance, the authors delve into a series of inconclusive experiments to determine the oligomerization state of WbaP, utilizing techniques like SEC, SEC-MALS, mass photometry, and mass spectrometry. They then transition to cryo-EM but subsequently return to address the oligomerization issue, which they conclusively resolve using cross-linking experiments. Following this, they shift their focus to interpreting and discussing the structural features obtained from the cryo-EM data.


• Ambiguous and incorrect statements: There are instances of vague and at times inaccurate statements. Using more precise terminology like "native nanodiscs" or "lipid bilayer nanodiscs" would enhance clarity compared to the term "liponanoparticles." The claim on page 8 concerning the refractive index increment of SMA polymers needs rectification. The real reason why SEC-MALS cannot provide absolute particle masses in this case is that using two independent concentration detectors (typically, absorbance and refractive index), the decomposition of elution profiles is necessarily limited to two chemical species of a known molar or specific absorbance and refractive index. Thus, it is clear that nanodiscs containing a protein, a polymer, and a chemically undefined mixture of native lipids cannot be analyzed by this technique.

• Overstating of technical aspects: The technical aspects seem overstated. While the extraction of membrane proteins into native lipid bilayer nanodiscs and their characterization by cross-linking and cryo-EM are standard (and were published before by the same authors in ref. 29), the authors appear to promote them as groundbreaking. The statement that this study presents a novel, universal strategy and toolkit for examining small membrane proteins within liponanoparticles seems overstated, especially given the previous existence of similar methods.

Reviewer #1 (Public Review):

Martinez-Gutierrez and colleagues presented a timeline of important bacteria and archaea groups in the ocean and based on this they correlated the emergence of these microbes with GOE and NOE, the two most important geological events leading to the oxygen accumulation of the Earth. The whole study builds on molecular clock analysis, but unfortunately, the clock analysis contains important errors in the calibration information the study used, and is also oversimplified, leaving many alternative parameters that are known to affect the posterior age estimates untested. Therefore, the main conclusion that the oxygen availability and redox state of the ocean is the main driver of marine microbial diversification is not convincing.

Basically, what the molecular clock does is to propagate the temporal information of the nodes with time calibrations to the remaining nodes of the phylogenetic tree. So, the first and the most important step is to set the time constraints appropriately. But four of the six calibrations used in this study are debatable and even wrong.

(1) The record for biogenic methane at 3460 Ma is not reliable. The authors cited Ueno et al. 2006, but that study was based on carbon isotope, which is insufficient to demonstrate biogenicity, as mentioned by Alleon and Summons 2019.

(2) Three calibrations at Aerobic Nitrososphaerales, Aerobic Marinimicrobia, and Nitrite oxidizing bacteria have the same problem - they are all assumed to have evolved after the GOE where the Earth started to accumulate oxygen in the atmosphere, so they were all capped at 2320 Ma. This is an important mistake and will significantly affect the age estimates because maximum constraint was used (maximum constraint has a much greater effect on age estimates and minimum constraint), and this was used in three nodes involving both Bacteria and Archaea. The main problem is that the authors ignored the numerous evidence showing that oxygen can be produced far before GOE by degradation of abiotically-produced abundant H2O2 by catalases equipped in many anaerobes, also produced by oxygenic cyanobacteria evolved at least 500 Ma earlier than the onset of GOE (2500 Ma), and even accumulated locally (oxygen oasis). It is well possible that aerobic microbes could have evolved in the Archaean.

Once the phylogenetic tree is appropriately calibrated with fossils and other time constraints, the next important step is to test different clock models and other factors that are known to significantly affect the posterior age estimates. For example, different genes vary in evolutionary history and evolutionary rate, which often give very different age estimates. So it is very important to demonstrate that these concerns are taken into account. These are done in many careful molecular dating studies but missing in this study.

Reviewer #2 (Public Review):

In this paper, Martinez-Gutierrez and colleagues present a dated, multidomain (= Archaea+Bacteria) phylogenetic tree, and use their analyses to directly compare the ages of various marine prokaryotic groups. They also perform ancestral gene content reconstruction using stochastic mapping to determine when particular types of genes evolved in marine groups.

Overall, there are not very many papers that attempt to infer a dated tree of all prokaryotes, and this is a distinctive and up-to-date new contribution to that oeuvre. There are several particularly novel and interesting aspects - for example, using the GOE as a (soft) maximum age for certain groups of strictly aerobic Bacteria, and using gene content enrichment to try to understand why and how particular marine groups radiated.

Comments:

One overall feature of the results is that marine groups tend to be quite young, and there don't seem to be any modern marine groups that were in the ocean prior to the GOE. It might be interesting to study the evolution of the marine phenotype itself over time; presumably some of the earlier branches were marine? What was the criterion for picking out the major groups being discussed in the paper? My (limited) understanding is that the earliest prokaryotes, potentially including LUCA, LBCA and LACA, was likely marine, in the sense that there would not yet have been any land above sea level at such times. This might merit discussion in the paper. Might there have been earlier exclusively marine groups that went extinct at some point?

What do the stochastic mapping analyses indicate about the respective ancestors of Gracilicutes and Terrabacteria? At least in the latter case, the original hypothesis for the group was that they possessed adaptations to life on land - which seems connected/relevant to the idea of radiating into the sea discussed here - so it might be interesting to discuss what your analyses say about that idea.

I very much appreciate that finding time calibrations for microbes is challenging, but I nonetheless have a couple of comments or concerns about the calibrations used here:

The minimum age for LBCA and LACA (Nodes 1 and 2 in Fig. 1) was calibrated with the earliest evidence of biogenic methane ~3.4Ga. In the case of LACA, I suppose this reflects the view that LACA was a methanogen, which is certainly plausible although perhaps not established with certainty. However, I'm less clear about the logic of calibrating the minimum age of Bacteria using this evidence, as I am not aware that there is much evidence that LBCA was a methanogen. Perhaps the line of reasoning here could be stated more explicitly. An alternative, slightly younger minimum age for Bacteria could perhaps be obtained from isotope data ~3.2Ga consistent with Cyanobacteria (e.g., see https://pubmed.ncbi.nlm.nih.gov/30127539/).

I am also unclear about the rationale for setting the minimum age of the photosynthetic Cyanobacteria crown to the time of the GOE. Presumably, oxygen-generating photosynthesis evolved on the stem of (photosynthetic) Cyanobacteria, and it therefore seems possible that the GOE might have been initiated by these stem Cyanobacteria, with the crown radiating later? My confusion here might be a comprehension error on my part - it is possible that in fact one node "deeper" than the crown was being calibrated here, which was not entirely clear to me from Figure 1. Perhaps mapping the node numbers directly to the node, rather than a connected branch, would help? (I am assuming, based on nodes 1 and 2, that the labels are being placed on the branch directly antecedent to the node of interest)?

Reviewer #1 (Public Review):

Martinez-Gutierrez and colleagues presented a timeline of important bacteria and archaea groups in the ocean and based on this they correlated the emergence of these microbes with GOE and NOE, the two most important geological events leading to the oxygen accumulation of the Earth.

The following suggestion is very important and requires additional clock analysis.

"Three calibrations at Aerobic Nitrososphaerales, Aerobic Marinimicrobia, and Nitrite oxidizing bacteria have the same problem - they are all assumed to have evolved after the GOE where the Earth started to accumulate oxygen in the atmosphere, so they were all capped at 2320 Ma. This is an important mistake and will significantly affect the age estimates because maximum constraint was used (maximum constraint has a much greater effect on age estimates and minimum constraint), and this was used in three nodes involving both Bacteria and Archaea. The main problem is that the authors ignored the numerous evidence showing that oxygen can be produced far before GOE by degradation of abiotically-produced abundant H2O2 by catalases equipped in many anaerobes, also produced by oxygenic cyanobacteria evolved at least 500 Ma earlier than the onset of GOE (2500 Ma), and even accumulated locally (oxygen oasis). It is well possible that aerobic microbes could have evolved in the Archaean."

Reviewer #2 (Public Review):

In this paper, Martinez-Gutierrez and colleagues present a dated, multidomain (= Archaea+Bacteria) phylogenetic tree, and use their analyses to directly compare the ages of various marine prokaryotic groups. They also perform ancestral gene content reconstruction using stochastic mapping to determine when particular types of genes evolved in marine groups.

Overall, there are not very many papers that attempt to infer a dated tree of all prokaryotes, and this is a distinctive and up-to-date new contribution to that oeuvre. There are several particularly novel and interesting aspects - for example, using the GOE as a (soft) maximum age for certain groups of strictly aerobic Bacteria, and using gene content enrichment to try to understand why and how particular marine groups radiated.

One overall feature of the results is that marine groups tend to be quite young, and there don't seem to be any modern marine groups that were in the ocean prior to the GOE. This seems an interesting strand to pursue in future work. Presumably, the earliest branches of the bacterial tree were marine, so what happened in the intervening period? The authors' character mapping approach could also be used to infer the habitat of the Gracilicutes and Terrabacteria ancestors, and it might be interesting to revisit the question of the ancestral ecological differences between these groups, if any can be clearly distinguished.

Finally, some comments in which I disagree with a couple of the authors' methodological decisions. I don't think these disagreements are likely to have a major impact on the findings, but I feel it is worth mentioning them in any case, to stimulate future discussion and work. I very much appreciate that finding time calibrations for microbes is challenging, but I nonetheless have a couple of comments or concerns about the calibrations used here.

1. It is not clear that the earliest evidence for biogenic methane provides a minimum age for both Bacteria and Archaea. For Archaea, potentially --- if the methane is indeed biogenic, and if the last archaeal common ancestor was a methanogen. For Bacteria (and extant life as a whole), the link is harder to draw. The authors pointed out that there is other evidence from around this time for life, for example from the Strelley Pool at ~3.3Ga. This is a reasonable argument for a minimum on LUCA, but then the optimal approach would be to calibrate the root node with this minimum, rather than the two descendant clades.

2. I am also unclear about the rationale for setting the minimum age of the photosynthetic Cyanobacteria crown to the time of the GOE. Presumably, oxygen-generating photosynthesis evolved on the stem of (photosynthetic) Cyanobacteria - since the crown seems to have had it ancestrally - and it therefore seems possible that the GOE might have been initiated by these stem Cyanobacteria, with the crown radiating later. In their response to my comment, the authors confirm that they are calibrating the crown Cyanobacteria using the GOE as a minimum. I don't agree with the logic here: it seems a formal possibility that crown Cyanobacteriia are younger than the GOE. The authors argued that, although oxygenic photosynthesis likely evolved on the stem, due to extinction (or non-sampling) of intervening lineages there are no nodes on the tree that directly sample that event. I agree, but I would then suggest placing the minimum on the older, not the younger, end of the stem.

Reviewer #3 (Public Review):

This is an interesting manuscript that builds off of this group's previous work focused on the interface between Hsf1, heat shock protein (HSP) mRNA production, and 3D genome topology. Here the group subjects the yeast Saccharomyces cerevisiae to either heat stress (HS) or ethanol stress (ES) and examines Hsf1 and Pol II chromatin binding, Histone occupancy, Hsf1 condensates, HSP gene coalescence (by 3C and live cell imaging), and HSP mRNA expression (by RT-qPCR and live cell imaging). The manuscript is well written, and the experiments seem well done, and generally rigorous, with orthogonal approaches performed to support conclusions. The main findings are that both HS and ES result in Hsf1/Pol II-dependent intergenic interactions, along with the formation of Hsf1 condensates. Yet, while HS results in rapid and strong induction of HSP gene expression and Hsf1 condensate resolution, ES results in slow and weak induction of HSP gene expression without Hsf1 condensate resolution. Thus, the conclusion is somewhat phenomenological - that the same transcription factor can drive distinct transcription, topologic, and phase-separation behavior in response to different types of stress. While identifying a mechanistic basis for these results would be a tough task perhaps beyond the scope of this study, it would nevertheless be helpful to place these results in context with a series of other studies demonstrating across various organisms showing Hsf1 driving distinct activities dependent on the context of activation. Perhaps even more importantly, this work left out PMID: 32015439 which is particularly relevant considering that it shows that it is human HSF1 condensate resolution rather than simple condensate formation that is associated with HSF1 transcriptional activity - which is similar to the findings here with this particular dose of HS resulting in resolution and high transcriptional activity versus ES resulting in resolution failure and lower activity. It is also worth noting that the stresses themselves are quite different - ethanol can be used as a carbon source and so beyond inducing proteotoxic stress, the yeast are presumably adapting to this distinct metabolic state. Basically, it is not clear whether these differences are due to the dose of stress, versus we are looking at an early timepoint as ES initiates a genome-wide chromatin restructuring and gene expression reprogramming that goes beyond a response to proteotoxic stress. This reviewer is not suggesting a barrage of new experiments, but perhaps discussion points to contextualize results.

Reviewer #1 (Public Review):

Summary:<br /> The study compares the transcriptional and epigenetic response of baker's yeast cells to heat shock and ethanol shock. The authors made several interesting observations. In response to heat shock, the transcription factor HSF1 rapidly forms foci, binds upstream elements of heat-shock-response genes, facilitates long-distance genomic contacts between heat-shock-response genes, and the genes are rapidly transcribed. In response to ethanol shock, the transcription factor HSF1 rapidly forms foci, binds upstream elements of heat-shock-response genes, facilitates long-distance genomic contacts between heat-shock-response genes, and yet transcription of the genes is substantially delayed. These insights are potentially important, as current models of eukaryotic gene control predict that physical contact between genes and regulatory elements is necessary, and in some cases sufficient to transcribe a gene. The current study indicates that the two effects are virtually decoupled in response to ethanol shock in yeast cells.

Overall, the conclusions appear appropriately supported by the data, and the data appear of high quality.

Strengths:<br /> The particular strengths of the paper include an impressive combination of genomic and imaging-based approaches and insightful genetically engineered cell systems. The manuscript reports interesting and potentially important findings. The text is generally very well written, the ideas are clearly explained, and the reasoning is easy to follow.

Weaknesses:<br /> The main weakness seems to be that the heat and ethanol shock approaches likely elicit pleiotropic effects, and therefore it is a challenge to test the causal relationship between various observations. Nevertheless, even as indirect effects might contribute to some of the authors' observations, the results are definitively worth reporting. Also, the presentation of some of the data could be improved.

Reviewer #2 (Public Review):

Significance<br /> Rubio et al. study the behavior of the transcription factor Hsf1 under ethanol stress, examining its distribution within the nucleus and the coalescence of heat shock response genes in budding yeast. In comparison to the heat shock response, the response to ethanol stress shows similar gene coalescence and Hsf1 binding. However, there is a notable delay in the transcriptional response to ethanol, and a disconnect between it and the appearance of irreversible Hsf1 condensates/puncta, highlighting important differences in how Hsf1 responds to these two related but distinct environmental stresses.

Overview and general concerns<br /> The authors studied how yeast responds to ethanol stress (8.5%) and compared it to the heat shock response (from 25{degree sign}C to 39{degree sign}C). They observed a more gradual increase in the expression of heat shock response (HSR) genes during ethanol stress compared to heat shock. Additionally, the recruitment of Hsf1 and Pol II to HSR genes, and the inter- and intrachromosomal interactions among these genes, showed slower kinetics under ethanol stress. They attribute the delay in transcriptional response to chromatin compaction induced by ethanol. Despite this delay, these interactions persisted longer. Hsf1 clusters, previously documented during the heat shock response, were also observed during ethanol stress and persisted for an extended period. The conditional degradation of Hsf1 and Rpb1 eliminated most inter- and intrachromosomal interactions for heat shock responsive genes in both ethanol stress and heat shock conditions, indicating the importance of these factors for long-distance interactions between HSR genes. Overall, this manuscript provides novel insights into the differential behavior of HSR genes under different stress conditions. This contributes to the broader understanding of how different stressors might elicit unique responses at the genomic and topographical level under the regulation of transcription factor Hsf1.

The central finding of the study highlights the different dynamics of Hsf1, Pol II, and gene organization in response to heat shock versus ethanol stress. However, one important limitation to consider is that the two chosen conditions may not be directly comparable. For a balanced assessment, the authors should ideally expose yeast to various ethanol concentrations and different heat shock temperatures, ensuring the observed differences stem from the nature of the stressor rather than suboptimal stress intensity. At the very least, an additional single ethanol concentration point on each side of 8.5% should be investigated to ensure that 8.5% is near the optimum. In fact, comparing the number of Hsp104 foci in the two conditions in Fig. 1E and F suggests that the yeast is likely experiencing different intensities of stress for the chosen heat shock condition and ethanol concentration used in this study.

A second significant concern is the use of the term "Hsf1 condensate". Chowdhary et al.'s 2022 Molecular Cell study highlighted an inhomogeneous distribution and rapid dynamics of Hsf1 clustering upon heat shock, with sensitivity to 1,6-hexandiol, which is interpreted as evidence for condensation by LLPS. However this interpretation has been criticized severely by McSwiggen et al. Genes Dev 2019 and Mussacchio EMBO J 2022. It is important to mention that 1,6-hexandiol is known to affect chromatin organization (Itoh et al. Life Science Alliance 2021). Describing such clusters as 'condensates' without further experimental evidence is premature. I encourage authors to settle on their neutral term 'puncta' which they use interchangeably with 'condensate' so as not to confuse the reader. The dynamic binding and unbinding of the low-abundance Hsf1 at coalescent chromatin target sites might explain the liquid-like properties of these clusters without the need for invoking the phase-separation hypothesis. While Hsf1 clusters exhibit features consistent with phase-separated condensates, other equally plausible alternative mechanisms, such as dynamic site-specific interactions (Musacchio, EMBO J, 2022), should also be considered. This is best left for the discussion where the underlying mechanism for puncta formation can be addressed.

Specific comments:

- Figure 1: Why does ethanol stress at 0 min display a larger number of Hsp104 foci per cell than heat shock at the same time? How are foci defined by the authors? In Fig. 1D, there are many smaller puncta. A comparative assessment of the number and size of foci for heat shock and ethanol stress would be beneficial.

- Figure 2: Selecting a housekeeping gene with consistent expression levels is crucial for meaningful qPCR analysis. Do SCR1 mRNA levels fluctuate during heat shock or ethanol stress? Additionally, certain genes, such as TMA10 and SSA4, lack visible bars at time 0. Are these levels undetectable? The varying y-axis scales are confusing; presenting data as relative fold changes could offer a clearer perspective.

- Line 239: The evidence for chromatin compaction is unconvincing. An increase in H3 occupancy by ChIP might indicate a reduction in histone exchange dynamics but may not relate to overall chromatin compaction. The authors use H2A-mCherry to suggest a decrease in chromatin volume, but this data is not persuasive. Did the authors observe any changes in nuclear size? Perhaps quantifying chromatin compaction more directly, using signal intensity per volume, would be informative.

- Line 340: The claim of a "strong spatiotemporal correlation" isn't evident from the data. Could correlation coefficients be provided? There is potential anti-correlation in Fig. 6 - Figure Supplement 1C.

- Figure 8: The WT data in Fig 8 seem inconsistent with Fig. 4 (e.g. the interaction frequency for HSP104 and SSA2). Are these fluctuations between experiments, or are they side effects of IAA treatment? The use of ethanol as an IAA solvent vehicle raises concerns. It would be beneficial if the authors could demonstrate that 1.7% ethanol in the control does not induce ethanol stress.

Joint Public Review:

In the manuscript by Rajan et al., the authors have highlighted the direct interaction between Dbp5 and tRNA, wherein Dbp5 serves as a mediator for tRNA export. This export process is subject to spatial regulation, as Dbp5 ATPase activation occurs specifically at nuclear pore complexes. Notably, this regulation is independent of the Los1-mediated pre-tRNA export route and instead relies on Gle1.

The manuscript is well constructed and nicely written. The authors have addressed the concerns as raised by the previous reviewers and added additional experiments.

I have a few comments for polishing the manuscript.

Major comments:<br /> 1. In their previous paper (Lari et al, 2019; Azra Lari Arvind Arul Nambi Rajan Rima Sandhu Taylor Reiter Rachel Montpetit Barry P Young Chris JR Loewen Ben Montpetit (2019) A nuclear role for the DEAD-box protein Dbp5 in tRNA export eLife 8:e48410.) as well as in the current manuscript the authors states that Dbp5 is involved in the export of tRNA that is independent of and parallel to Los1. They state that Dbp5 binds to the tRNA independent of known tRNA export proteins. The obtained conclusion is both intriguing and innovative, since it suggests that there are other variables, beyond the ones previously identified as tRNA factors, that might interact with Dbp5 to facilitate the export process. In order to find out additional factors aiding this process the authors may employ total RNA‐associated protein purification (TRAPP) experiments ( Shchepachevto et al., 2019; Shchepachev V, Bresson S, Spanos C, Petfalski E, Fischer L, Rappsilber J, Tollervey D. Defining the RNA interactome by total RNA-associated protein purification. Mol Syst Biol. 2019 Apr 8;15(4):e8689. doi: 10.15252/msb.20188689. PMID: 30962360; PMCID: PMC6452921) to identify extra factors involved in conjunction with Dbp5. The process elucidates hitherto uninvestigated tRNA export components that function in conjunction with Dbp5.

2. Various reports suggest that eukaryotic translation elongation factor 1 eEF1A is involved tRNA export Bohnsack et al., 2002 (Bohnsack MT, Regener K, Schwappach B, Saffrich R, Paraskeva E, Hartmann E, Görlich D. Exp5 exports eEF1A via tRNA from nuclei and synergizes with other transport pathways to confine translation to the cytoplasm. EMBO J. 2002 Nov 15;21(22):6205-15. doi: 10.1093/emboj/cdf613. PMID: 12426392; PMCID: PMC137205), Grosshans etal., 2002; Grosshans H, Hurt E, Simos G. An aminoacylation-dependent nuclear tRNA export pathway in yeast. Genes Dev. 2000 Apr 1;14(7):830-40. PMID: 10766739; PMCID: PMC316491). The presence of mutations in eEF1A has been seen to hinder the nuclear export process of all transfer RNAs (tRNAs). eEF1A has been shown to interact with Los1 aiding in tRNA export. The authors can also explore the crosstalk between Dbp5 and eEF1A in this study. Additionally, suppressor screening analysis in dbp5R423A , los1∆dbp5R423A los1∆msn∆dbp5R423A could shed more light on this.

3. Unfortunately, this article is not significantly different from that published in eLife in 2018. In fact, it raises more questions than it brings answers by not identifying a transporter for export and not identifying a role for the helicase activity of Dbp5. The addition of Gle1 is potentially novel but it's unclear why the authors didn't address the potential involvement of IP6.

Reviewer #1 (Public Review):

The authors have shown the following:<br /> 1. SY1 aggregation enhances (in terms of number of aggregates) when Sphingolipid biosynthesis is blocked.<br /> 2. In a normal cell (where sphingolipid biosynthesis is not hampered), the aggregate of SY1 (primarily the Class I aggregate) is localized only on the mitochondrial endomembrane system.<br /> 3. The localization is due to the association of SY1 (aggregates) with mitochondrial proteins like Tom70, Tim44, etc. (Is the localization completely lost? What happens to the toxicity when the aggregates are not localized on mitochondria?)<br /> 4. This fuels the loss of mitochondrial function.<br /> 5. Mitochondrial function is further abrogated when there is a block in sphingolipid biosynthesis.<br /> 6. A similar phenomenon is conserved in mammalian cell lines.

However, my major concern is that the role of sphingolipid in the mitochondrial association of the aggregates is not proven beyond doubt. I am also missing the importance of mitochondrial association in the context of IB maturation and cellular toxicity.

Reviewer #2 (Public Review):

Summary:<br /> The authors used a yeast model for analyzing Parkinson's disease-associated synphilin-1 inclusion bodies (SY1 IBs). In this model system, large SY1 IBs are efficiently formed from smaller potentially more toxic SY1 aggregates. Using a genome-wide approach (synthetic genetic array, SGA, combined with a high-content imaging approach), the authors identified the sphingolipid metabolic pathway as pivotal for SY1 IBs formation. Disturbances of this pathway increased SY1-triggered growth deficits, loss of mitochondrial membrane potential, increased production of reactive oxygen species (ROS), and decreased cellular ATP levels pointing to an increased energy crisis within affected cells. Notably, SY1 IBs were found to be surrounded by mitochondrial membranes using state-of-the-art super-resolution microscopy. Finally, the effects observed in the yeast for SY1 IBs turned out to be evolutionarily conserved in mammalian cells. Thus, sphingolipid metabolism might play an important role in the detoxification of misfolded proteins by large IBs formation at the mitochondrial membrane.

Strengths:<br /> • The SY1 IB yeast model is very suitable for the analysis of genes involved in IB formation.<br /> • The genome-wide approach combining a synthetic genetic array (SGA) with a high-content imaging approach is a compelling approach and enables the reliable identification of novel genes. The authors tightly checked the output of the screen.<br /> • The authors clearly showed, including a couple of control experiments, that the sphingolipid metabolic pathway is crucial for SY1 IB formation and cytotoxicity.<br /> • The localization of SY1 IBs at mitochondrial membranes has been clearly demonstrated with state-of-the-art super-resolution microscopy and biochemical methods.<br /> • Pharmacological manipulation of the sphingolipid pathway influenced mitochondrial function and cell survival.

Weaknesses:<br /> • It remains unclear how sphingolipids are involved in SY1 IB formation.<br /> • It remains undefined whether failure of sphingolipid-dependent SY1 IB formation from smaller potentially more toxic aggregates occurs at the mitochondrial membrane.<br /> • It remains open whether mitochondrial activity (e.g., respiratory activity) is needed for sphingolipid-dependent SY1 IB formation.

Reviewer #1 (Public Review):

Summary:<br /> This study investigated the role of CD47 and TSP1 in extramedullary erythropoiesis by utilization of both global CD47-/- mice and TSP1-/- mice.

Strengths:<br /> Flow cytometry combined with spleen bulk and single-cell transcriptomics were employed. The authors found that stress-induced erythropoiesis markers were increased in CD47-/- spleen cells, particularly genes that are required for terminal erythroid differentiation. Moreover, CD47 dependent erythroid precursors population was identified by spleen scRNA sequencing. In contrast, the same cells were not detected in TSP1-/- spleen. These findings provide strong evidence to support the conclusion that the differential role of CD47 and TSP1 in extramedullary erythropoiesis in mouse spleen.

Weaknesses:<br /> Methods and data analysis are appropriate. However, some clarifications are required. The discussion section needs to be expanded.<br /> 1). The sex of mice that were used in the study is unknown.<br /> 2). In the method of Single-cell RNA sequencing (page 10), it mentioned that single cell suspensions from mouse spleens were depleted of all mature hematopoietic cell lineages by passing through CD8a microbeads and CD8a+ T cell isolation Kit. As described, it is confusing what cell types are obtained for performing scRNAseq. More information is required for clarity.<br /> 3). The constitutive CD47 knockout mouse model is utilized in this study. The observed accumulation of erythroid precursors in the spleens of CD47-/- mice suggests a chronic effect of CD47 on spleen function. Can the current findings be extrapolated to acute scenarios involving CD47 knockdown or loss, as this may have more direct relevance to the potential side effects associated with anti-CD47-mediated cancer therapy? Please expand on this topic in the discussion section.

Reviewer #2 (Public Review):

Summary:<br /> The authors used existing mouse models to compare the effects of ablating the CD47 receptor and its signaling ligand Thrombospondin. The CD47-KO model used in this study was generated by Kim et al, 2018, where hemolytic anemia and splenomegaly was reported. This study analyzes the cell composition of the spleens from CD47-KO and Thsp-KO, focusing on early hematopoietic and erythroid populations. The data broadly shows that splenomegaly in the CD47-KO is largely due to an increase in committed erythroid progenitors as seen by Flow Cytometry and single-cell sequencing, whereas the Thsp-KO shows a slight depletion of committed erythroid progenitors but is otherwise similar to WT in splenic cell composition.

Strengths: The techniques used are appropriate for the study and the data support the main conclusions of the study. This study provides novel insights into a putative role of Thsp-CD47 signaling in triggering definitive erythropoiesis in the mouse spleen in response to anemic stress and constitutes a good resource for researchers seeking to understand extramedullary erythropoiesis.

Weaknesses: The Flow cytometry data alone supports the authors' main conclusion and single-cell sequencing confirms them but does not add further information, other than those already observed in the Flow data. The single-cell sequencing analysis and presentation could be improved by using alternate clustering methods as well as separating the data by genotype and displaying them in order for readers to fully grasp the nuanced differences in marker expression between the genotypes. Further, it is not clear from the authors' description of their results whether the increased splenic erythropoiesis is a direct consequence of CD47-KO or a response to the anemic stress in this mouse model. The enrichment of cKit+ Ter119+ Sca1- cells in CD47-KO indicates that these are likely stress erythroid progenitors. Another CD47-KO mouse model (Lindberg et al 1996) has no reported erythroid defects and was also not examined in this study.

Reviewer #1 (Public Review):

The work analyzes how centrosomes mature before cell division. A critical aspect is the accumulation of pericentriolar material (PCM) around the centrioles to build competent centrosomes that can organize the mitotic spindle. The present work builds on the idea that the accumulation of PCM is catalyzed either by the centrioles themselves (leading to a constant accumulation rate) or by enzymes activated by the PCM itself (leading to autocatalytic accumulation). These ideas are captured by a previous model derived for PCM accumulation in C. elegans (ref. 8) and are succinctly summarized by Eq. 1. The main addition of the present work is to allow the activated enzymes to diffuse in the cell, so they can also catalyze the accumulation of PCM in other centrosomes (captured by Eqs. 2-4). The authors claim that this helps centrosomes to reach the same size, independent of potential initial mismatches.

A strength of the paper is the simplicity of the equations, which are reduced to the bare minimum and thus allow a detailed inspection of the physical mechanism. One shortcoming of this approach is that all equations assume that the diffusion of molecules is much faster than any of the reactive time scales, although there is no experimental evidence for this.

Another shortcoming of the paper is that it is not clear what species the authors are investigating and how general the model is. There are huge differences in centrosome maturation and the involved proteins between species. However, this is not mentioned in the abstract or introduction. Moreover, in the main body of the paper, the authors mention C. elegans on pages 2 and 3, but refer to Drosophila on page 4, switching back to C. elegans on page 5, and discuss Drosophila on page 6. This is confusing and looks as if they are cherry-picking elements from various species. The original model in ref. 8 was constructed for C. elegans and it is not clear whether the autocatalytic model is more general than that. In any case, a more thorough discussion of experimental evidence would be helpful.

The authors show convincingly that their model compensates for initial size differences in centrosomes and leads to more similar final sizes. These conclusions rely on numerical simulations, but it is not clear how the parameters listed in Table 1 were chosen and whether they are representative of the real situation. Since all presented models have many parameters, a detailed discussion on how the values were picked is indispensable. Without such a discussion, it is not clear how realistic the drawn conclusions are. Some of this could have been alleviated using a linear stability analysis of the ordinary differential equations from which one could have gotten insight into how the physical parameters affect the tendency to produce equal-sized centrosomes.

The authors use the fact that their model stabilizes centrosome size to argue that their model is superior to the previously published one, but I think that this conclusion is not necessarily justified by the presented data. The authors claim that "[...] none of the existing quantitative models can account for robustness in centrosome size equality in the presence of positive feedback." (page 1; similar sentence on page 2). This is not shown convincingly. In fact, ref 8. already addresses this problem (see Fig. 5 in ref. 8) to some extent. More importantly, the conclusion seems to largely be based on the analysis shown in Fig. 2A, but the parameters going into this figure are not clear (see the previous paragraph). In particular, the initial size discrepancy of 0.1 µm^3 seems quite large, since it translates to a sphere of a radius of 300 nm. A similarly large initial discrepancy is used on page 3 without any justification. Since the original model itself already showed size stability, a careful quantitative comparison would be necessary.

The analysis of the size discrepancy relies on stochastic simulations (e.g., mentioned on pages 2 and 4), but all presented equations are deterministic. It's unclear what assumptions go into these stochastic equations, and how they are analyzed or simulated. Most importantly, the noise strength (presumably linked to the number of components) needs to be mentioned. How is this noise strength determined? What are the arguments for this choice? This is particularly crucial since the authors quote quantitative results (e.g., "a negligible difference in steady-state size (∼ 2% of mean size)" on page 4).

Moreover, the two sets of testable predictions that are offered at the end of the paper are not very illuminative: The first set of predictions, namely that the model would anticipate an "increase in centrosome size with increasing enzyme concentration, the ability to modify the shape of the sigmoidal growth curve, and the manipulation of centrosome size scaling patterns by perturbing growth rate constants or enzyme concentrations.", are so general that they apply to all models describing centrosome growth. Consequently, these observations do not set the shared enzyme pool apart and are thus not useful to discriminate between models. The second part of the first set of predictions about shifting "size scaling" is potentially more interesting, although I could not discern whether "size scaling" referred to scaling with cell size, total amount of material, or enzymatic activity at the centrioles. The second prediction is potentially also interesting and could be checked directly by analyzing published data of the original model (see Fig. 5 of ref. 8). It is unclear to me why the authors did not attempt this.

Taken together, I think the shared enzyme pool is an interesting idea, but the experimental evidence for it is currently lacking. Moreover, the model seems to make little testable predictions that differ from previous models.

Reviewer #2 (Public Review):

Summary:

In this paper, Banerjee & Banerjee argue that a solely autocatalytic assembly model of the centrosome leads to size inequality. The authors instead propose a catalytic growth model with a shared enzyme pool. Using this model, the authors predict that size control is enzyme-mediate and are able to reproduce various experimental results such as centrosome size scaling with cell size and centrosome growth curves in C. elegans.

The paper contains interesting results and is well-written and easy to follow/understand.

Suggestions:

● In the Introduction, when the authors mention that their "theory is based on recent experiments uncovering the interactions of the molecular components of centrosome assembly" it would be useful to mention what particular interactions these are.<br /> ● In the Results and Discussion sections, the authors note various similarities and differences between what is known regarding centrosome formation in C. elegan and Drosophila. It would have been helpful to already make such distinctions in the Introduction (where some phenomena that may be C. elegans specific are implied to hold centrosomes universally). It would also be helpful to include more comments for the possible implications for other systems in which centrosomes have been studied, such as human, Zebrafish, and Xenopus.<br /> ● For Fig 1.C, the two axes are very close to being the same but are not. It makes the graph a little bit more difficult to interpret than if they were actually the same or distinctly different. It would be more useful to have them on the same scale and just have a legend.<br /> ● The authors refer to Equation 1 as resulting from an "active liquid-liquid phase separation", but it is unclear what that means in this context because the rheology of the centrosome does not appear to be relevant.<br /> ● The authors reject the non-cooperative limit of Eq 1 because, even though it leads to size control, it does not give sigmoidal dynamics (Figure 2B). While I appreciate that this is just meant to be illustrative, I still find it to be a weak argument because I would guess a number of different minor tweaks to the model might keep size control while inducing sigmoidal dynamics, such as size-dependent addition of loss rates (which could be due to reactions happen on the surface of the centrosome instead of in its bulk, for example). Is my intuition incorrect? Is there an alternative reason to reject such possible modifications?<br /> ● While the inset of Figure 3D is visually convincing, it would be good to include a statistical test for completeness.<br /> ● The authors note that the pulse in active enzyme in their model is reminiscent of the Polo kinase pulse observed in Drosophila. Can the authors use these published experimental results to more tightly constrain what parameter regime in their model would be relevant for Drosophila? Can the authors make predictions of how this pulse might vary in other systems such as C. elegans?<br /> ● The authors mention that the shared enzyme pool is likely not diffusion-limited in C. elegans embryos, but this might change in larger embryos such as Drosophila or Xenopus. It would be interesting for the authors to include a more in-depth discussion of when diffusion will or will not matter, and what the consequence of being in a diffusion-limit regime might be.<br /> ● The authors state "Firstly, our model posits the sharing of the enzyme between both centrosomes. This hypothesis can potentially be experimentally tested through immunofluorescent staining of the kinase or by constructing FRET reporter of PLK1 activity." I don't understand how such experiments would be helpful for determining if enzymes are shared between the two centrosomes. It would be helpful for the authors to elaborate.

Reviewer #1 (Public Review):

This important study from Jahncke et al. demonstrates inhibitory synaptic defects and elevated seizure susceptibility in multiple models of dystroglycanopathy. A strength of the paper is the use of a wide range of genetic models to disrupt different aspects of dystroglycan protein or glycosylation in forebrain neurons. The authors use a combination of immunohistochemistry and electrophysiology to identify cellular migration, lamination, axonal targeting, synapse formation/function, and seizure phenotypes in forebrain neurons. This is an elegant study with extensive data supporting the conclusions. The role of dystroglycan and the dystrophin glycoprotein complex (DGC) in cellular migration and synapse formation are of broad interest.<br /> A strength of this paper is the use of several transgenic mouse lines with mutations in genes involved in glycosylation of dystroglycan. Knockout of POMT2 abolishes the majority of dystroglycan glycosylation, while point mutations in B4GAT and FKRP presumably produce more minor changes in glycosylation. This is a powerful approach to investigate the role of glycosylation in dystroglycan function.

Reviewer #2 (Public Review):

The manuscript by Jahncke and colleagues is centered on the CCK+ synaptic defects that are a consequence of Dystroglycanopathy and/or impaired dystroglycan-related protein function. The authors use conditional mouse models for Dag1 and Pomt2 to ablate their function in mouse forebrain neurons and demonstrate significant impairment of CCK+/CB1R+ interneuron (IN) development in addition to being prone to seizures. Mice lacking the intracellular domain of Dystroglycan have milder defects, but impaired CCK+/CB1R+ IN axon targeting. The authors conclude that the milder dystroglycanopathy is due to the partially reduced glycosylation that occurs in the milder mouse models as opposed to the more severe Pomt2 models. Additionally, the authors postulate that inhibitory synaptic defects and elevated seizure susceptibility are hallmarks of severe dystroglycanopathy and are required for the organization of functional inhibitory synapse assembly.

The manuscript is overall, fairly well-written and the description of the phenotypic impact of disruption of Dystroglycan forebrain neurons (and similar glycosyltransferase pathway proteins) demonstrate impairment in axon targeting and organization. There are some questions with regards to interpretation of some of the results from these conditional mouse models. The study is mostly descriptive, and some validation of subunits of the dystroglycan-glycoprotein complex and laminin interactions would go towards defining the impact of disruption of dystroglycan's function in the brain. The statistics and basic analysis of the manuscript appear to be appropriate and within parameters for a study of this nature. Some clarification between the discrepancies between the Walker Warburg Syndrome (WWS) patient phenotypes and those observed in these conditional mouse models is warranted. This manuscript has the potential to be impactful in the Dystroglycanopathy and general neurobiology fields.

The authors have made significant improvements to address my concerns in this resubmission and the previous critiques of the other reviewers since the prior submission. The work is comprehensive in scope and the statistics are appropriate where required. I believe the conclusions to be valid for this study and I don't have any additional recommendations. I believe this work to be of importance to the Dystroglycanopathy and neurobiology fields.

Reviewer #3 (Public Review):

The study presents a systematic analysis of how a range of dystroglycan mutations alter CCK/CB1 axonal targeting and inhibition in hippocampal CA1 and impact seizure susceptibility. The study follows up on prior literature identifying a role for dystroglycan in CCK/CB1 synapse formation. The careful assay includes comparison of 5 distinct dystroglycan mutation types known to be associated with varying degrees of muscular dystrophy phenotypes: a forebrain specific Dag1 knockout in excitatory neurons at 10.5, a forebrain specific knockout of the glycosyltransferase enzyme in excitatory neurons, mice with deletion of the intracellular domain of beta-Dag1 and 2 lines with missense mutations with milder phenotypes. They show that forebrain glutamatergic deletion of Dag1 or glycosyltransferase alters cortical lamination while lamination is preserved in mice with deletion of the intracellular domain or missense mutation. The study extends prior works by identifying that forebrain deletion of Dag1 or glycosyltransferase in excitatory neurons impairs CCK/CB1 and not PV axonal targeting and CB1 basket formation around CA1 pyramidal cells. Mice with deletion of the intracellular domain or missense mutation show<br /> limited reductions in CCK/CB1 fibers in CA1. Carbachol enhancement of CA1 IPSCs was reduced both in forebrain knockouts. Interestingly, carbachol enhancement of CA1 IPSCs was reduced when the intracellular domain of beta-Dag1was deleted, but not I the missense mutations, suggesting a role of the intracellular domain in synapse maintenance. All lines except the missense mutations , showed increased susceptibility to chemically induced behavioral seizures. Together, the study, is carefully designed, well controlled and systematic. The results advance prior findings of the role for dystroglycans in CCK/CB1 innervations of PCs by demonstrating effects of more selective cellular deletions and site specific mutations in extracellular and intracellular domains.

Prior concerns regarding CCK/CB1 cell numbers and potential changes in basal synaptic inhibition are addressed in the revision.

Reviewer #1 (Public Review):

Mature mammalian olfactory sensory neurons (OSN) express only one of the hundreds of possible odor receptors (ORs) encoded in the genome. The process of selecting this OR in each OSN is the consequence of both deterministic developmental processes involving transcription factors, and more stochastic processes. How this balance is implemented is a major problem in molecular neuroscience, one whose solution has significant systems-level implications for odor coding. In Bashkirova et al the authors substantially revise the canonical view of how this process works. By querying single cell transcriptomes and genetic architecture across OSN development, the authors demonstrate that OSN progenitors express ORs for their zone and for more dortsal zones, and that the degree of heterochromatinization of non-expressed ORs varies as a function of which zone a given OSN resides in. Through additional genetic experiments (including knockouts of transcription factors that seem to be associated with zonal identity, and the clever use of OR transgenes) they synthesize these findings into a model in which progenitors co-express many ORs - both ORs that are appropriate for their zone and ORs that are dorsal to their zone - and that this expression both facilitates heterochromatinzation of non-selected and extra-zonal ORs, and enables singular OR selection. The experiments are careful and the data are novel, and definitely revise our simplistic current view of how this process works; as such this work will have significant impact on the field. As presented the model requires additional experiments to fully flesh it out, and to definitively demonstrate that i.e., precocious expression leads to gene silencing, but with some additional clarifications in the discussion this paper both breaks new ground and sets the stage for future work exploring mechanisms of OSN development and OR selection.

Reviewer #2 (Public Review):

In this study, Bashkirova et al. analyzed how the gene choice of olfactory receptors (ORs) is regulated in olfactory sensory neurons (OSNs) during development. In the mouse olfactory system, there are more than 1000 functional OR genes and several hundred pseudogenes. It is well-established that each individual OSN expresses only one functional OR gene in a mono-allelic manner. This is referred to as the one neuron - one receptor rule. It is also known that OR gene choice is not entirely stochastic but restricted to a particular area or zone in the olfactory epithelium (OE) along the dorsoventral axis. It is interesting to study how this stochastic but biased gene-choice is regulated during OSN development, narrowing down the number of OR genes to be chosen to eventually achieve the monogenic OR expression in OSNs.

In the present study, the authors cell-sorted OSNs into three groups; immediate neuronal precursors (INPs), immature OSNs (iOSNs), and mature OSNs (mOSNs). They found that OR gene choice is differentially regulated positively by transcription factors in INPs and negatively by heterochromatin-mediated OR gene silencing in iOSNs. The authors propose that by the combination of two opposing forces of polygenic transcription (positive) and genomic silencing (negative), each OSN finally expresses only one OR gene out of over 2000 alleles in a stochastic but stereotypic manner.

The authors' model of OR gene choice is supported by well-designed experiments and by large amounts of data. In general, the paper is clearly written and easy to follow. It will attract a wide variety of readers in the fields of neuroscience, developmental biology, and immunology. The present finding will give new insight into our understanding of gene choice in the multigene family in the mammalian brain and shed light on the long-standing question of monogenic expression of OR genes.

Reviewer #3 (Public Review):

This manuscript investigates how a seemingly random choice of odourant receptor (OR) gene expression is organised into sterotypic zones of OR expression along the olfactory epithelium. Using a varietty of functional genomics methods, the authors find that along the differentiation axis (progenitor to mature olfactory sensory neuron, OSN) multiple ORs are initally transcribed and from among these, only one OR is selected for expression. The rest are suppressed through chromatin silencing. In addition to this, the authors report a dorso-ventral gradient in OR expression at the immature stage - dorsally expressed ORs are also expressed ventrally and these then get silenced. The expression of the ventrally expressed ORs, on the other hand, are restricted to the ventral region. They suggest a role for the transcription factor NF1 in this dorsoventral process.

This is a valuable study. The data are compelling and generally well presented.

Reviewer #1 (Public Review):

In this study, Jiamin Lin et al. investigated the potential positive feedback loop between ZEB2 and ACSL4, which regulates lipid metabolism and breast cancer metastasis. They reported a correlation between high expression of ZEB2 and ACSL4 and poor survival of breast cancer patients, and showed that depletion of ZEB2 or ACSL4 significantly reduced lipid droplets abundance and cell migration in vitro. The authors also claimed that ZEB2 activated ACSL4 expression by directly binding to its promoter, while ACSL4 in turn stabilized ZEB2 by blocking its ubiquitination.

Reviewer #2 (Public Review):

In this study, the authors validated a positive feedback loop between ZEB2 and ACSL4 in breast cancer, which regulates lipid metabolism to promote metastasis.

Overall, the study is original, well structured, and easy to read.

Reviewer #3 (Public Review):

The manuscript by Lin et al. reveals a novel positive regulatory loop between ZEB2 and ACSL4, which promotes lipid droplets storage to meet the energy needs of breast cancer metastasis.

Reviewer #1 (Public Review):

In order to find small molecules capable of enhancing regenerative repair, this study employed a high throughput YAP-activity screen method to query the ReFRAME library, identifying CLK2 inhibitor as one of the hits. Further studies showed that CLK2 inhibition leads to AMOTL2 exon skipping, rendering it unable to suppress YAP.

The novelty of the study is that it showed that inhibition of a kinase not previously associated with the HIPPO pathway can influence YAP activity through modification of mRNA splicing. The major arguments appear solid.

In the revised manuscript, additional discussion was provided regarding drug concentration and molecular mechanisms, which helps clear some of the confusing points in the original manuscript.

Reviewer #2 (Public Review):

In this manuscript, the authors have screened the ReFRAME library and identified candidate small molecules that can activate YAP. They found that SM04690, an inhibitor of the WNT signaling pathway, could efficiently activate YAP through CLK2 kinase which has been shown to phosphorylate SR proteins to alter gene alternative splicing. They further demonstrated that SM04690 mediated alternative splicing of AMOTL2 and rendered it unlocalized on the membrane. Alternatively spliced AMOTL2 prevented YAP from anchoring to the cell membrane which results in decreased YAP phosphorylation and activated YAP. Previous findings showed that WNT signaling more or less activates YAP. The authors revealed that an inhibitor of WNT signaling could activate YAP. Thus, these findings are potentially interesting and important. However, the present manuscript provided a lot of indirect data and lacked key experiments.

Major points:<br /> 1. In Figure S3, since inhibition of CLK2 resulted in extensive changes in alternative splicing, why did the authors choose AMOTL2? How to exclude other factors such as EEF1A1 and HSPA5, do they affect YAP activation? Angiomotin-related AMOTL1 and AMOTL2 were identified as negative regulators of YAP and TAZ by preventing their nuclear translocation. It has been reported that high cell density promoted assembly of the Crumbs complex, which recruited AMOTL2 to tight junctions. Ubiquitination of AMOTL2 K347 and K408 served as a docking site for LATS2, which phosphorylated YAP to promote its cytoplasmic retention and degradation. How to determine that alternative splicing rather than ubiquitination of AMOTL2 affects YAP activity? Does AMOTL2 Δ5 affect the ubiquitination of AMOTL2? Does overexpression of AMOTL2 Δ5Δ9 cause YAP and puncta to co-localize?<br /> 2. The author proposed that AMOTL2 splicing isoform formed biomolecular condensates,.However, there was no relevant experimental data to support this conclusion. AMOTL2 is located not only on the cell membrane but also on the circulating endosome of the cell, and the puncta formed after AMOTL2 dissociation from the membrane is likely to be the localization of the circulating endosome. The author should co-stain AMOTL2 with markers of circulating endosomes, or conduct experiments to prove the liquidity of puncta to verify the phase separation of AMOTL2 splicing isoform.<br /> 3. The localization of YAP in cells is regulated by cell density, and YAP usually translocates to the nucleus at low cell density. In Figure 2E, the cell densities of DMSO and SM04690-treated groups are inconsistent. In Figure 4A, the magnification of t DMSO and SM04690-treated groups is inconsistent, and the SM04690-treated group seems to have a higher magnification.<br /> 4. There have been many reports that the WNT signaling pathway and the Hippo signaling pathway can crosstalk with each other. The authors should exclude the influence of the WNT signaling pathway by using SM04690.

Reviewer #3 (Public Review):

This study on drug repurposing presents the identification of potent activators of the Hippo pathway. The authors successfully screen a drug library and identify two CLK kinase inhibitors as YAP activators, with SM04690 targeting specifically CLK2. They further investigate the molecular basis of SM04690-induced YAP activity and identify splicing events in AMOTL2 as strongly affected by CLK2 inhibition. Exon skipping within AMOTL2 decreases the interactions with membrane bound proteins and is sufficient to induce YAP target gene expression. Importantly, inhibitor concentrations that are sufficient to change YAP target gene expression show differential alternative splicing of AMOTL2. Overall the study is well designed, the conclusions are supported by sufficient data and represent an exciting connection between alternative splicing and the HIPPO pathway.

Reviewer #1 (Public Review):

The work in this paper is in general done carefully. Reconstructions are done appropriately and the effects of statistical uncertainty are quantified properly. I was glad to see that the tree and alignment are now deposited.

The paper identifies which mutations are crucial for the functional differences between the ancestors tested. This is done quite carefully - the authors even show that the same substitutions also work in extant proteins.<br /> These substitutions very slightly lower the affinity and increase the cooperativity of the C-terminal peptide binding to the alpha crystallin domain - a key oligomeric interaction. These relatively minor changes nevertheless apparently affect the subunit exchange behaviour and oligomerization of the sHSP.

Lastly, the authors use likelihood methods to test for signatures of selection. This reviewer is not a fan of these methods, as they are easily misled by common biological processes (see PMID 37395787 for a recent critique). The paper is relatively careful in the interpretation of this test though, and I think the importance of the other findings does not depend on the action of selection along this branch.

Reviewer #2 (Public Review):

This was an interesting study, and I enjoyed seeing different experimental approaches used to compare the properties of the different native proteins, the ancestral reconstructions, and the other mutants. In the original manuscript, I felt that the authors had over-simplified their explanations, as the differences between the ancestral proteins, and the changes induced by the two mutations, only partially explain the differences between IbpA proteins from the two different species. However, with their revised version, I think the presentation and discussion of their results are much better. Overall, I think this represents a valuable contribution to the field, providing convincing mechanistic evidence as to how these small heat shock proteins have evolved.

Reviewer #1 (Public Review):

The goal of this paper is to characterize the molecular mechanisms that lead to lung cyst formation in a murine model wherein the Bmpr1a receptor gene has been inactivated in the fetal lung mesenchyme. In this context, it is important to note that very little is known regarding how lung cysts form, and generally the presumption has been that these pathological structures result from dysregulated events in the epithelium. Thus, the emphasis in this paper on derangements in a fundamental developmental signaling pathway in the lung mesenchyme that results in cyst formation is both novel and significant.

In this manuscript, the authors seek to understand how abnormal lung development leads to the formation of cysts in the lung. Cysts are enlarged pathological balloon-like structures that interfere with normal gas exchange and characterize a variety of pediatric and adult lung diseases. To date, the molecular signals underlying cyst formation are poorly understood. Using genetically modified mice, the focus herein is on how inactivation of a specific gene known to transduce key developmental signals (Bmpr1a) leads to the development of cysts. One novelty of this work is that the gene inactivation has been targeted to a set of primitive fetal lung cells that give rise to structural and contractile cells supporting bronchial airways. Alterations in the function of this particular cell type has not previously been examined in the context of lung cyst pathogenesis.

Notably, the experiments and models are state-of-art and the authors are careful in their interpretations. It should be noted, however, that there are also several concerns that limit enthusiasm at this time. These include a lack of data evaluating relative histological similarities and differences between cysts generated in their murine model and human lung cysts, and whether there is information implicating a role for the gene studied in this paper in human cysts. Secondly, despite an abundance of data, at the end of the day, the key molecular signals are not clearly identified.

Additional Feedback

Overall, this is a well-executed paper that addresses how derangements in signals emanating from the fetal lung mesenchyme in embryonic life lead to cyst formation. This work, therefore, seeks to fill in basic deficiencies in knowledge since the pathogenesis of lung cyst formation is poorly understood and the role of altered mesenchymal cell activity in this process has not been carefully addressed. For the most part, the experiments are clearly presented, and the models are relevant and state-of-the art. Although enthusiasm is high, there are several overriding concerns, which the authors should consider.

While the paper seeks to understand the key molecular events leading to cyst formation and a plethora of data is provided, this goal is largely not clearly met. As a result, the paper ends up being descriptive. Further, without these data, a so-called definitive rescue experiment is not possible at this time. In addition, the experiments, particularly toward the end of the manuscript are not well integrated with the overall body of the Results. This is particularly true for figure 7. While interesting, the results in some of these latter figures are insufficiently linked to the primary observations. This issue further contributes to concerns that the manuscript is largely descriptive.

Importantly, it would be useful to have provided more detailed information on the structure and histological properties of the murine cysts and how such findings relate to human lung cysts. Also, the authors should examine whether there is any information on Bmpr1a in human cyst formation (i.e GWAS data).

Throughout the paper, there is a lack of quantification for the histological findings. Littermate controls should also be clearly defined genetically,

Specific Concerns by figure

Figure 1 suppl: "Doxycycline" is misspelled.

Figure1c Suppl: Hard to discern clear-cut expression of Bmpr1a protein in mesenchyme in WT. Comparable images with similar sizes of airways should be used.

Figure 2a: Expression of several genes studied and altered should be identified on scatter plot.

Figure 2c: Authors should also consider staining for other smooth muscle markers.

Figure 3: ELN expression should be defined in a clear quantitative manner.

Figure 4: Additional information on p38 dependent signaling (? Including in vivo studies) would potentially help to understand key molecular events and perhaps could help to address key mechanistic events, including their location and identity.

Figure 6: Would be helpful to know whether Bmpr1a receptor is expressed in Myocd KO.

Figure 7: Not clear how these findings, though interesting, relate to the body of studies and the pathogenesis of cyst formation. Other points: 1) The authors should re-examine/repeat co-staining in the KO mouse lung (right 2 images in the top group of 4) for Foxj1, Sox2, and CDH (right 2 images, Figure 7A). For one thing, the cadherin stain in the 2 KO images seems localized to the lumen. Secondly, the pattern of cadherin staining looks exactly the same in both KO images, suggesting an error and/or duplication 2) authors should place arrows on the heat map showing the location of SPC, Sox2, Sox9, and FoxJ1 bands 3) figure 7D graph needs numbers on y axis.

Reviewer #2 (Public Review):

Congenital cystic airway abnormalities (CPAM) are a common disorder in airway lung development whose etiology is poorly understood and can be fatal if not effectively treated at birth. This study by Luo and colleagues provides compelling new evidence in mice and cultured fetal mesenchymal cells that loss of mesenchymal Bmpr1a signaling disrupts branching morphogenesis, leading to the formation of numerous pulmonary cysts. Their airways were deficient in underlying smooth muscle and subepithelial elastin fibers along with perturbations in Sox2-Sox9 proximal-distal epithelial development. Interestingly, these changes were independent of canonical Smad1/5 signaling and suggestive of non-canonical signaling perhaps through p38 signaling. They were also independent of simply ablating non-vascular mesenchymal cells using Myocd-ko mice. Although the study does not define how loss of Bmpr1a causes cystic formation or whether this pathway is related to human CPAM disease, the findings are considered highly significant because they provide new evidence for BMP signaling in branching morphogenesis. The knowledge may pave the way for future studies designed to understand and prevent or treat newborn infants with CPAM. There are only a few weaknesses.

Major Weaknesses:<br /> 1. The authors may be aware that a recent paper (https://doi.org/10.1038/s41598-022-24858-3) reported on transcriptional changes seen in human CPAM. It would seem that some of the molecular changes seen in human CPAM move in the opposite direction of what is reported in mice lacking mesenchymal Bmrp1a. Perhaps the authors could comment on these differences in the discussion and whether they potentially explain the etiology of CPAM or branching morphogenesis in general.<br /> 2. Figure 4 shows that BMP4 increases SMADs, p38, and several muscle genes in mesenchymal cells. Figure 5 extends this finding with a clever strategy to label airway and vascular smooth muscle with different fluorescent molecules used to isolate different types of mesenchymal cells. It shows that non-vascular smooth muscle cells but not perivascular smooth muscles are responsive to BMP4 signaling as defined by increased expression of Myh11. Are there cell-restricted responses to the other genes shown in Figure 4? Given the lack of SMAD signaling and the increase seen in p38 signaling, would blocking p38 signaling influence the BMP responsiveness of these nonvascular smooth muscle cells?<br /> 3. Figure 6 shows that mesenchymal loss of Myocd causes a deficiency of airway smooth muscle cells, but this was not sufficient to create cysts. Did the authors ever check to see if it changed Sox2-Sox9 staining in the airway epithelium?<br /> 4. Figure 7 shows that mesenchymal loss of Bmpr1a proximalizes the distal airway as defined by loss of Sox2 and FoxJ1 (a ciliated marker) and gain in (Sox9 and SP-C) staining. But Club cells expressing Scgb1a1 and Cyp2F2 are the predominant epithelial cells in the distal airway. The transcriptomics data in panel B shows expression of these genes is less in the mutant mice. Does this mean they fail to generate Club cells or there is just less expression per cell? In other words, what are the primary epithelial cells present in the airways of mice with loss of mesenchymal Bmpr1a?

Reviewer #1 (Public Review):

Summary<br /> This fascinating paper by M. Alfatah et al. describes work to uncover novel genes affecting lifespan in the budding yeast S. cerevisiae, eventually identifying and further characterizing a gene, YBR238C, now named AAG1 by the authors.<br /> The authors began by considering published gene sets pulled from the Saccharomyces genome database that described increases or decreases in either chronological lifespan or replicative lifespan in yeast. They also began with gene sets known to be downregulated upon treatment with the lifespan-extending TOR inhibitor rapamycin.

YBR283C was unique in being largely uncharacterized, downregulated upon rapamycin treatment, and linked to both increased replicative lifespan and increased chronological lifespan upon deletion.

The authors show that YBR283C may act to negatively regulate mitochondrial function, in ways that are both dependent on and independent of the stress-responsive transcription factor Hap4, largely by looking at relative expression levels of relevant mitochondrial genes.

In a hard-to-fully interpret but well-documented series of experiments the authors note that the two paralogues YBR283C and RMD9 (which have ~66% similarity) (a) have opposite effects when acting alone, and (b) appear to interact in that some phenotypes of ybr283c are dependent on RMD9.

A particularly interesting finding in light of the current literature and of the authors' strategy in identifying YBR283C is that changes in electron transport chain genes upon rapamycin treatment appear to be affected via YBR283C.

Based on a series of experiments the authors move to conclude the existence of "a feedback loop between TORC1 and mitochondria (the TORC1-Mitochondria-TORC1 (TOMITO) signaling process) that regulates cellular aging processes."

Strengths<br /> Overall, this study describes a great deal of new data from a large number of experiments, that shed light on the potential specific roles of YBR238C and its paralog RMD9 in aging in yeast, and also underscore the potential of an approach looking for "dark matter" such as uncharacterized genes when seining the increasing deluge of published datasets for new hypotheses to test. This work when revised will become a valuable addition to the field.

Weaknesses<br /> A paralog of YBR283C, RMD9, also exists in the yeast genome. While the authors indicate that part of their interest in YBR283C lies in its uncharacterized nature, its paralogue, RMD9, is not uncharacterized but is named due to its phenotype of Required for Meiotic nuclear Division, which is not mentioned or discussed anywhere in the manuscript currently.

In the context of the current work, in addition to the cited Hillen, H.S et al. and Nouet C. et al, the authors might be very interested in the 2007 Genetics paper "Translation initiation in Saccharomyces cerevisiae mitochondria: functional interactions among mitochondrial ribosomal protein Rsm28p, initiation factor 2, methionyl-tRNA-formyltransferase and novel protein Rmd9p" (PMID: 17194786), which does not appear to be cited or discussed in the current version of the manuscript.

Reviewer #2 (Public Review):

The effectors of cellular aging in yeast have not been fully elucidated. To address this, the authors curated gene expression studies to link genes influenced by rapamycin - a well-known mediator of longevity across model systems - to genes known to affect chronological and replicative lifespan (RLS) in yeast. Through their analyses, they find one gene, ybr238c, whose deletion increases both CLS and RLS upon deletion and that is downregulated by rapamycin. Curiously, despite these selection criteria, the authors only use CLS as a proxy for cellular aging throughout their study and do not explore the effects of ybr238c deletion on RLS. This does not diminish their conclusions, but given the importance of this phenotype in their selection criteria, it is surprising that the authors did not choose to test both types of aging throughout their study.

Nonetheless, the authors demonstrate that deletion of ybr238c increases CLS across multiple yeast strains and through multiple assays. The authors also test the effects of YBR238C overexpression on lifespan and find the opposite effect, with overexpression yeast showing decreased survival relative to wild-type cells, consistent with "accelerated aging" as the authors propose. The authors also note that ybr238c has a paralog, rmd9, whose deletion decreases CLS and seems to be epistatic to ybr238c, as a double ybr238c/rmd9 mutant has decreased CLS relative to a wild-type strain.

Collectively, the data presented by the authors convincingly demonstrate that ybr238c influences lifespan in a manner that is distinct from (and likely opposite to) rmd9. However, the authors then link the increased CLS in Δybr238c yeast to mitochondrial function using only a handful of assays that do not directly test mitochondrial function. These include total cellular ATP levels, levels of reactive oxygen species, and the transcript levels of select nuclear-encoded mitochondrial genes. Yeast is well established to generate ATP through non-mitochondrial pathways such as glycolysis in fermentive conditions. While it is possible that the ATP levels assayed in the manuscript were tested in stationary phase, which would more likely reflect "mitochondrial function," the methods nor the figure legends contain these details, which are critical for the interpretation of these data. Similarly, ROS can be generated through non-mitochondrial pathways, and the transcription of nuclear-encoded mitochondrial genes is an indirect measure of mitochondrial function at best. Thus, the authors' proposed connection of ybr238c to mitochondrial function is correlative and should be substantiated with assays that more closely align with organellar function, such as respirometry or assaying the activity of oxidiative phosphorylation complexes. Finally, the authors attempt to tie the phenotypes of mitochondrial dysfunction caused by the deletion of ybr238c to TORC1 signaling, as the gene is influenced by rapamycin. However, the presentation of the data, such as reporting ATP levels as relative percentages or failing to perform appropriate statistical comparisons between conditions in which the authors derive conclusions, renders the data difficult to interpret. As such, this manuscript establishes that ybr238c is rapamycin responsive and influences CLS, but its influence on mitochondrial activity and ties to TORC1 signaling remain speculative.

Reviewer #3 (Public Review):

Summary:<br /> The study by Alfatah et al. presented a role for YBR238C in mediating lifespan through improved mitochondrial function in a TOR1-dependent metabolic pathway. The authors used a dataset comparison approach to identify genes positively modulating yeast chronological (CLS) and Replicative (RLS) lifespan when deleted, and their expression is reduced under Rapamycin treatment condition. This approach revealed an unknown, mitochondria-localized yeast gene YBR238C, and through mechanistic studies, they identified its paralogous gene RMD9 regulating lifespan in an antagonistic effect.

Strengths:<br /> Findings have valuable implications for understanding the YBR238C-mediated, mitochondrial-dependent yeast lifespan regulation, and the interplay between two paralogous genes in the regulation of mitochondrial function represents an inserting case for gene evolution.

Weaknesses:<br /> Overall, the implication/findings of this study are restricted only to the yeast model since these two genes do not have any homology in higher eukaryotes. The primary methods must be carefully designed by considering two different metabolic states: respiration-associated with CLS and fermentation-associated with RLS in a single comparative approach. Yeast CLS and RLS are two completely different processes. It is already known that most gene-regulating CLS is not associated with RLS or vice versa. The method section is poorly written and missing important information. The experimental approaches are poorly designed, and variability across the datasets (e.g., media condition "YPD," "SC" etc.) and their experimental conditions are not well described/considered; thus, presented data are not conclusive, which decreases the overall rigor of the study.

Reviewer #1 (Public Review):

In this manuscript, the authors aimed to compare, from testis tissues at different ages from mice in vivo and after culture, multiple aspects of Leydig cells. These aspects included mRNA levels, proliferation, apoptosis, steroid levels, protein levels, etc. A lot of work was put into this manuscript in terms of experiments, systems, and approaches. The technical aspects of this work may be of interest to labs working on the specific topics of in vitro spermatogenesis for fertility preservation.

Reviewer #2 (Public Review):

Moutard, Laura, et al. investigated the gene expression and functional aspects of Leydig cells in a cryopreservation/long-term culture system. The authors found that critical genetic markers for Leydig cells were diminished when compared to the in-vivo testis. The testis also showed less androgen production and androgen responsiveness. Although they did not produce normal testosterone concentrations in basal media conditions, the cultured testis still remained highly responsive to gonadotrophin exposure, exhibiting a large increase in androgen production. Even after the hCG-dependent increase in testosterone, genetic markers of Leydig cells remained low, which means there is still a missing factor in the culture media that facilitates proper Leydig cell differentiation. Optimizing this testis culture protocol to help maintain proper Leydig cell differentiation could be useful for future human testis biopsy cultures, which will help preserve fertility and child cancer patients.

Overall, the authors addressed most comments and questions from the previous review. The additional data regarding the necrotic area is helpful for interpreting the quality of the cultures.

The authors did not conduct multiple comparison tests although there are multiple comparisons conducted for a single dependent variable (Fig 2J, Fig 3F, among many others), however, the addition of this multiple comparison is unlikely to change the conclusions of the paper or the figure and, thus is a minor technical detail in this case.

Reviewer #1 (Public Review):

Summary:<br /> This paper provides strong evidence for the roles of JH in an ametabolous insect species. In particular, it demonstrates that:<br /> • JH shifts embryogenesis from a growth mode to a differentiation mode and is responsible for terminal differentiation during embryogenesis. This, and other JH roles, are first suggested as correlations, based on the timing of JH peaks, but then experimentally demonstrated using JH antagonists and rescue thereof with JH mimic. This is a robust approach and the experimental results are very convincing.<br /> • JH redirects ecdysone-induced molting to direct formation of a more mature cuticle<br /> • Kr-h1 is downstream of JH in Thermobia, as it is in other insects, and is a likely mediator of many JH effects<br /> • The results support the proposed model that an ancestral role of JH in promoting and maintaining differentiation was coopted during insect radiations to drive the evolution of metamorphosis. However, alternate evolutionary scenarios should also be considered.

Strengths:<br /> Overall, this is a beautiful, in-depth student. The paper is well-written and clear. The background places the work in a broad context and shows its importance in understanding fundamental questions about insect biology. The researchers are leaders in the field, and a strength of this manuscript is their use of a variety of different approaches (enzymatic assays, gene expression, agonists & antagonists, analysis of morphology using different types of microscopy and detection, and more) to attack their research questions. The experimental data is clearly presented and carefully executed with appropriate controls and attention to detail. The 'multi-pronged' approach provides support for the conclusions from different angles, strengthening conclusions. In sum, the data presented are convincing and the conclusions about experimental outcomes are well-justified based on the results obtained.

Weaknesses:<br /> This paper provides more detail than is likely needed for readers outside the field but also provides sufficient depth for those in the field. This is both a strength and a weakness. I would suggest the authors shorten some aspects of their text to make it more accessible to a broader audience. In particular, the discussion is very long and accompanied by two model figures. The discussion could be tightened up and much of the text used for a separate review article (perhaps along with Figure 11) that would bring more attention to the proposed evolution of JH roles.

Reviewer #2 (Public Review):

The authors have studied in detail the embryogenesis of the ametabolan insect Thermobia domestica. They have also measured the levels of the two most important hormones in insect development: juvenile hormone (JH) and ecdysteroids. The work then focuses on JH, whose occurrence concentrates in the final part (between 70 and 100%) of embryo development. Then, the authors used a precocene compound (7-ethoxyprecocene, or 7EP) to destroy the JH producing tissues in the embryo of the firebrat T. domestica, which allowed to unveil that this hormone is critically involved in the last steps of embryogenesis. The 7EP-treated embryos failed to resorb the extraembryonic fluid and did not hatch. More detailed observations showed that processes like the maturational growth of the eye, the lengthening of the foregut and posterior displacement of the midgut, and the detachment of the E2 cuticle, were impaired after the 7EP treatment. Importantly, a treatment with a JH mimic subsequent to the 7EP treatment restored the correct maturation of both the eye and the gut. It is worth noting that the timing of JH mimic application was essential for correcting the defects triggered by the treatment with 7EP.

This is a relevant result in itself since the role of JH in insect embryogenesis is a controversial topic. It seems to have an important role in hemimetabolan embryogenesis, but not so much in holometabolans. Intriguingly, it appears important for hatching, an observation made in hemimetabolan and in holometabolan embryos. Knowing that this role was already present in ametabolans is relevant from an evolutionary point of view, and knowing exactly why embryos do not hatch in the absence of JH, is relevant from the point of view of developmental biology.

Then, the authors describe a series of experiments applying the JH mimic in early embryogenesis, before the natural peak of JH occurs, and its effects on embryo development. Observations were made under different doses of JHm, and under different temporal windows of treatment. Higher doses triggered more severe effects, as expected, and different windows of application produced different effects. The most used combination was 1 ng JHm applied 1.5 days AEL, checking the effects 3 days later. Of note, 1.5 days AEL is about 15% embryonic development, whereas the natural peak of JH occurs around 85% embryonic development. In general, the ectopic application of JHm triggered a diversity of effects, generally leading to an arrest of development. Intriguingly, however, a number of embryos treated with 1 ng of JHm at 1.5 days AEL showed a precocious formation of myofibrils in the longitudinal muscles. Also, a number of embryos treated in the same way showed enhanced chitin deposition in the E1 procuticle and showed an advancement of at least a day in the deposition of the E2 cuticle.

While the experiments and observations are done with great care and are very exhaustive, I am not sure that the results reveal genuine JH functions. The effects triggered by a significant pulse of ectopic JHm when the embryo is 15% of the development will depend on the context: the transcriptome existing at that time, especially the cocktail of transcription factors. This explains why different application times produce different effects. This also explains why the timing of JHm application was essential for correcting the effects of 7EP treatment. In this reasoning, we must consider that the context at 85% development, when the JH peaks in natural conditions and plays its genuine functions, must be very different from the context at 15% development, when the JHm was applied in most of the experiments. In summary, I believe that the observations after the application of JHm reveal effects of the ectopic JHm, but not necessarily functions of the JH. If so, then the subsequent inferences made from the premise that these ectopic treatments with JHm revealed JH functions are uncertain and should be interpreted with caution.

Those inferences affect not only the "JH and the progressive nature of embryonic molts" section, but also, the "Modifications in JH function during the evolution of hemimetabolous and holometabolous life histories" section, and the entire "Discussion". In addition to inferences built on uncertain functions, the sections mentioned, especially the Discussion, I think suffer from too many poorly justified speculations. I love speculation in science, it is necessary and fruitful. But it must be practiced within limits of reasonableness, especially when expressed in a formal journal.

Finally, In the section "Modifications in JH function during the evolution of hemimetabolous and holometabolous life", it is not clear the bridge that connects the observations on the embryo of Thermobia and the evolution of modified life cycles, hemimetabolan and holometabolan.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors use inhibitors and mimetics of juvenile hormone (JH) to demonstrate that JH has a key role in late embryonic development in Thermobia, specifically in gut and eye development but also resorption of the extraembryonic fluid and hatching. They then exogenously apply JH early in development (when it is not normally present) to examine the biological effects of JH at these stages. This causes a plethora of defects including developmental arrest, deposition of chitin, limb development, and enhanced muscle differentiation. The authors interpret these early effects on development as JH being important for the shift from morphogenetic growth to differentiation - a role that they speculate may have facilitated the evolution of metamorphosis (hemi- and holo-metaboly). This paper will be of interest to insect evo-devo researchers, particularly those with interests in the evolution of metamorphosis.

Strengths:<br /> The experiments are generally conducted very well with appropriate controls and the authors have included a very detailed analysis of the phenotypes.<br /> The manuscript significantly advances our understanding of Thermobia development and the role of JH in Thermobia development.<br /> The authors interpret this data to present some hypotheses regarding the role of JH in the evolution of metamorphosis, some aspects of which can be addressed by future studies.

Weaknesses:<br /> The results are based on using inhibitors and mimetics of JH and there was no attempt to discern immediate effects of JH from downstream effects. The authors show, for instance, that the transcription of myoglianin is responsive to JH levels, it would have been interesting to see if any of the phenotypic effects are due to myoglianin upregulation/suppression (using RNAi for example). These kinds of experiments will be necessary to fully work out if and how the JH regulatory network has been co-opted into metamorphosis.

The results generally support the authors' conclusions. However, the discussion contains a lot of speculation and some far-reaching conclusions are made about the role of JH and how it became co-opted into controlling metamorphosis. There are some interesting hypotheses presented and the author's speculations are consistent with the data presented. However, it is difficult to make evolutionary inferences from a single data point as although Thermobia is a basally branching insect, the lineage giving rise to Thermobia diverged from the lineages giving rise to the holo- and hemimetabolous insects approx.. 400 mya and it is possible that the effects of JH seen in Thermobia reflect lineage-specific effects rather than the 'ancestral state'. The authors ignore the possibility that there has been substantial rewiring of the networks that are JH responsive across these 400 my. I would encourage the authors to temper some of the discussion of these hypotheses and include some of the limitations of their inferences regarding the role of JH in the evolution of metamorphosis in their discussion.

Reviewer #1 (Public Review):

Zhang et al. tackle the important topic of primate-specific structural features of the brain and the link with functional specialization. The authors explore and compare gyral peaks of the human and macaque cortex through non-invasive neuroimagery, using convincing techniques that have been previously validated elsewhere. They show that nearly 60% of the macaque peaks are shared with humans, and use a multi-modal parcellation scheme to describe the spatial distribution of shared and unique gyral peaks in both species.

The claim is made that shared peaks are mainly located in lower-order cortical areas whereas unique peaks are located in higher-order regions, however, no systematic comparison is made. The authors then show that shared peaks are more consistently found across individuals than unique peaks, and show a positive but small and non-significant correlation between cross-individual counts of the shared peaks of the human and the macaque i.e. the authors show a non-significant trend for shared peaks that are more consistently found across humans to be those that are also more found across macaques.

In order to identify if unique and shared peaks could be identified based on the structural features of the cortical regions containing them, the authors compared them with t-tests. A correction for multiple comparisons should be applied and t-values reported. Graph-theoretical measures were applied to functional connectivity datasets (resting-state fMRI) and compared between unique and shared peak regions for each species separately. Again the absence of multiple comparison correction and t-values make the results hard to interpret. The same comment applies to the analysis reporting that shared peaks are surrounded by a larger number of brain regions than unique peaks. Finally, the potentially extremely interesting results about differential human gene expression of shared and unique peaks regions are not systematically reported e.g. the 28 genes identified are not listed and the selection procedure of 7 genes is not fully reported.

The paper is well written and the methods used for data processing are very compelling i.e. the peak cluster extraction pipeline and cross-species registration. However, the analysis and especially the reporting of statistics, as they stand now, constitutes the main weakness of the paper. Some aspects of the statistical analysis need to be clarified.

Reviewer #2 (Public Review):

Summary:

The authors compared the cortical folding of human brains with folding in macaque monkey brains to reveal shared and unique locations of gyral peaks. The shared gyral peaks were located in cortical regions that are functionally similar and less changed in humans from those in macaques, while the locations of unique peaks in humans are in regions that have changed or expanded functions. These findings are important in that they suggest where human brains have changed more than macaque brains in their subsequent evolution from a common ancestor. The massive analysis of comparative results provides evidence of where humans and macaques are similar or different in cortical markers, as well as noting some of the variations within each of the two primates.

Strengths:

The study includes massive detail.

Weaknesses:

The manuscript is too long and there is not enough focus on the main points. A brief listing of previous views on why fissures form and what factors are important would be helpful.

Reviewer #1 (Public Review):

Summary:<br /> This study assumes and weakly tests that auditory rhythm processing is produced by internal oscillating systems, and it evaluates the properties of such putative oscillators across individuals. The authors designed an experiment and performed analyses that address individuals' preferred rate and flexibility, with a special focus on how much past rhythms influence subsequent trials. They find evidence for such historical dependence and show that we adapt less well to new rhythms as we age. While I have important doubts about the entrainment-based interpretation of the results, this work offers a useful contribution to our understanding of individual differences in rhythm processing regardless.

Strengths:<br /> The inclusion of two tasks -- a tapping and a listening task -- complement each other methodologically. By analysing both the production and tracking of rhythms, the authors emphasize the importance of the characteristics of the receiver, the external world, and their interplay. The relationship between the two tasks and components within tasks are explored using a range of analyses. The visual presentation of the results is very clear. The age-related changes in flexibility are useful and compelling.

Weaknesses:<br /> At times, I found it challenging to evaluate the scientific merit of this study from what was provided in the introduction and methods. It is not clear what the experiment assumes, what it evaluates, and which competing accounts or predictions are at play. While some of these questions are answered, clear ordering and argumentative flow is lacking. With that said, I found the Abstract and General Discussion much clearer, and I would recommend reformulating the early part of the manuscript based on the structure of those segments.

Second, in my reading, it is not clear to what extent the study assumes versus demonstrates the entrainment of internal oscillators. I find the writing somewhat ambiguous on this count: on the one hand, an entrainment approach is assumed a priori to design the experiment ("an entrainment approach is adopted") yet a primary result of the study is that entrainment is how we perceive and produce rhythms ("Overall, the findings support the hypothesis that an oscillatory system with a stable preferred rate underlies perception and production of rhythm..."). While one could design an experiment assuming X and find evidence for X, this requires testing competing accounts with competing hypotheses -- and this was not done.

In my view, more evidence is required to bolster the findings as entrainment-based regardless of whether that is an assumption or a result. Indeed, while the effect of previous trials into the behaviour of the current trial is compatible with entrainment hypotheses, it may well be compatible with competing accounts as well. And that would call into question the interpretation of results as uncovering the properties of oscillating systems and age-related differences in such systems. Thus, I believe more evidence is needed to bolster the entrainment hypothesis.

For example, a key prediction of the entrainment model -- which assumes internal oscillators as the mechanism of action -- is that behaviour in the SMT and PTT tasks follows the principles of Arnold's Tongue. Specifically, tapping and listening performance should worsen systematically as a function of the distance between the presented and preferred rate. On a participant-by-participant, does performance scale monotonically with the distance between the presented and preferred rate? Some of the analyses hint at this question, such as the effect of 𝚫IOI on accuracy, but a recontextualization, further analyses, or additional visualizations would be helpful to demonstrate evidence of a tongue-like pattern in the behavioural data. Presumably, non-oscillating models do not follow a tongue-like pattern, but again, it would be very instructive to explicitly discuss that.

Fourth, harmonic structure in behaviour across tasks is a creative and useful metric for bolstering the entrainment hypothesis specifically because internal oscillators should display a preference across their own harmonics. However, I have some doubts that the analyses as currently implemented indicate such a relationship. Specifically, the main analysis to this end involves summing the residuals of the data closest to y=x, y=2*x and y=x/2 lines and evaluating whether this sum is significantly lower than for shuffled data. Out of these three dimensions, y=x does not comprise a harmonic, and this is an issue because it could by itself drive the difference of summed residuals with the shuffled data. I am uncertain whether rerunning the same analysis with the x=y dimension excluded constitutes a simple resolution because presumably there are baseline differences in the empirical and shuffled data that do not have to do with harmonics that would leak into the analysis. To address this, a simulation with ground truths could be helpful to justify analyses, or a different analysis that evaluates harmonic structure could be thought of.

Reviewer #2 (Public Review):

Summary:<br /> In the current work, authors deploy a set of behavioral tasks to explore individual differences in the preferred perceptual and motor rhythms. They found a consistent individual preference for a given perceptual and motor frequency across tasks and, while these were correlated, the latter is slower than the former one. Additionally, they show that the accuracy of adaptation to rate changes is proportional to the amount of rate variation and, crucially, the amount of adaptation decreases with age.

Strengths:<br /> Authors carefully designed several experiments to measure individual preferred motor and perceptual tempo. Furthermore, before completing the main experiment they validated the experimental design by testing the consistency across tasks and test-retest. Additionally, to the value of the reported findings, the introduced paradigm represents a useful tool for future research.<br /> The obtained data is rigorously analyzed using a diverse set of tools, each adapted to the specificities across the different research questions and tasks.<br /> This study identifies several relevant behavioral features: (i) each individual shows a preferred and reliable motor and perceptual tempo and, while both are related, the motor is consistently slower than the pure perceptual one; (ii) the existence of hysteresis in the adaptation to rate variations; and (iii) the decrement of this adaptation with age. All these observations are valuable for the auditory-motor integration field of research, and they could potentially inform existing biophysical models to increase their descriptive power.

Weaknesses:<br /> The current study is presented in the framework of the ongoing debate of oscillator vs. timekeeper mechanisms underlying perceptual and motor timing, and authors claim that the observed results support the former mechanism. In this line, every obtained result is related by the authors to a specific ambiguous (i.e., not clearly related to a biophysical parameter) feature of an internal oscillator. As pointed out by an essay on the topic (1), claiming that a pattern of results is compatible with an "oscillator" could be misleading, since some features typically used to validate or refute such mechanisms are not well grounded on real biophysical models. Relatedly, a recent study (2) shows that two quantitatively different computational algorithms (i.e., absolute vs relative timing) can be explained by the same biophysical model. This demonstrates that what could be interpreted as a timekeeper, or an oscillator can represent the same biophysical model working under different conditions. For this reason, if authors would like to argue for a given mechanism underlying their observations, they should include a specific biophysical model, and test its predictions against the observed behavior. For example, it's not clear why authors interpret the observation of the trial's response being modulated by the rate of the previous one, as an oscillator-like mechanism underlying behavior. As shown in (1) a simple oscillator returns to its natural frequency as soon as the stimulus disappears, which will not predict the long-lasting effect of the previous trial. Furthermore, a timekeeper-like mechanism with a long enough integration window is compatible with this observation.<br /> Still, authors can choose to disregard this suggestion, and not testing a specific model, but if so, they should restrict this paper to a descriptive study of the timing phenomena.

1. Doelling, K. B., & Assaneo, M. F. (2021). Neural oscillations are a start toward understanding brain activity rather than the end. PLoS biology, 19(5), e3001234.<br /> 2. Doelling, K. B., Arnal, L. H., & Assaneo, M. F. (2022). Adaptive oscillators provide a hard-coded Bayesian mechanism for rhythmic inference. bioRxiv, 2022-06.

Reviewer #1 (Public Review):

Summary:<br /> The authors conducted two tasks at 300 days of separation. First, a social perception task, where Ps responded whether a pictured person either deserved or needed help. Second, an altruism task, where Ps are offered monetary allocations for themselves and a partner. Ps decide whether to accept, or a default allocation of 20 dollars each. The partners differed in perceived merit, such that they were highly deserving, undeserving, or unknown. This categorisation was decided on the basis of a prisoner's dilemma game the partner played beforehand. "Need" was also manipulated, by altering the probability that the partner must have their hand in cold water at the end of the experiment and this partner can use the money to buy themselves out. These two tasks were conducted to assess the perception of need/merit in the first instance, and how this relates to social behaviour in the second. fMRI data were collected alongside behavioural.

The authors present many analyses of behaviour (including DDM results) and fMRI. E.g., they demonstrate that they could decode across the mentalising network whether someone was making a need or deserving judgement vs control judgement but couldn't decode need vs deserving. And that brain responses during merit inferences (merit - control) systematically covaried with participants' merit sensitivity scores in the rTPJ. They also found relationships between behaviour and rTPJ in the altruism task. And that merit sensitivity in the perception task predicted the influence of merit on social behaviour in the altruism task.

Strengths:<br /> This manuscript represents a sensible model to predict social perceptions and behaviours, and a tidy study design with interesting findings. The introduction introduced the field especially brilliantly for a general audience.

Weaknesses:<br /> 1. The authors do acknowledge right at the end that these are small samples. This is especially the case for the correlational questions. While the limitation is acknowledged at the end, it is not truly acknowledged in the way that the data are interpreted. I.e. much is concluded from absent relationships, where the likelihood of Type II error is high in this scenario. I suggest that throughout the manuscript, authors play down their conclusions about absence of effects.

2. I found the results section quite a marathon, and due to its length I started to lose the thread concerning the overarching aims - which had been established so neatly in the introduction. I am unsure whether all of these analyses were necessary for addressing the key questions or whether some were more exploratory. E.g. it's unclear to me what one would have predicted upfront about the decoding analyses.

3. More specifically, the decoding analyses were intriguing to me. If I understand the authors, they are decoding need vs merit, and need+merit vs control, not the content of these inferences. Do they consider that there is a distributed representation of merit that does not relate to its content but is an abstracted version that applies to all merit judgements? I certainly would not have predicted this and think the analyses raise many questions.

Reviewer #2 (Public Review):

When people help others is an important psychological and neuroscientific question. It has received much attention from the psychological side, but comparatively less from neuroscience. The paper translates some ideas from a social Psychology domain to neuroscience using a neuroeconomically oriented computational approach. In particular, the paper is concerned with the idea that people help others based on perceptions of merit/deservingness, but also because they require/need help. To this end, the authors conduct two experiments with an overlapping participant pool:

1) A social perception task in which people see images of people that have previously been rated on merit and need scales by other participants. In a blockwise fashion, people decide whether the depicted person a) deserves help, b) needs help, and c) whether the person uses both hands (== control condition).

2) In an altruism task, people make costly helping decisions by deciding between giving a certain amount of money to themselves or another person. How much the other person needs and deserves the money is manipulated.

The authors use a sound and robust computational modelling approach for both tasks using evidence accumulation models. They analyse behavioural data for both tasks, showing that the behaviour is indeed influenced, as expected, by the deservingness and the need of the shown people. Neurally, the authors use a block-wise analysis approach to find differences in activity levels across conditions of the social perception task (there is no fMRI data for the other task). The authors do find large activation clusters in areas related to the theory of mind. Interestingly, they also find that activity in TPJ that relates to the deservingness condition correlates with people's deservingness ratings while they do the task, but also with computational parameters related to helping others in the second task, the one that was conducted many months later. Also, some behavioural parameters correlate across the two tasks, suggesting that how deserving of help others are perceived reflects a relatively stable feature that translates into concrete helping decisions later-on.

The conclusions of the paper are overall well supported by the data.

1) I found that the modelling was done very thoroughly for both tasks. Overall, I had the impression that the methods are very solid with many supplementary analyses. The computational modelling is done very well.

2) A slight caveat, however, regarding this aspect, is that, in my view, the tasks are relatively simplistic, so even the complex computational models do not do as much as they can in the case of more complex paradigms. For example, the bias term in the model seems to correspond to the mean response rate in a very direct way (please correct me if I am wrong).

3) Related to the simple tasks: The fMRI data is analysed in a simple block-fashion. This is in my view not appropriate to discern the more subtle neural substrates of merit/need-based decision-making or person perception. Correspondingly, the neural activation patterns (merit > control, need > control) are relatively broad and unspecific. They do not seem to differ in the classic theory of mind regions, which are the focus of the analyses.

4) However, the relationship between neural signal and behavioural merit sensitivity in TPJ is noteworthy.

5) The latter is even more the case, as the neural signal and aspects of the behaviour are correlated across subjects with the second task that is conducted much later. Such a correlation is very impressive and suggests that the tasks are sensitive for important individual differences in helping perception/behaviour.

6) That being said, the number of participants in the latter analyses are at the lower end of the number of participants that are these days used for across-participant correlations.

Reviewer #3 (Public Review):

Summary:<br /> The paper aims to provide a neurocomputational account of how social perception translates into prosocial behaviors. Participants first completed a novel social perception task during fMRI scanning, in which they were asked to judge the merit or need of people depicted in different situations. Secondly, a separate altruistic choice task was used to examine how the perception of merit and need influences the weights people place on themselves, others, and fairness when deciding to provide help. Finally, a link between perception and action was drawn in those participants who completed both tasks.

Strengths:<br /> The paper is overall very well written and presented, leaving the reader at ease when describing complex methods and results. The approach used by the author is very compelling, as it combines computational modeling of behavior and neuroimaging data analyses. Despite not being able to comment on the computational model, I find the approach used (to disentangle sensitivity and biases, for merit and need) very well described and derived from previous theoretical work. Results are also clearly described and interpreted.

Weaknesses:<br /> My main concern relates to the selection of the social perception task, which to me is the weakest point. Such weakness has been also addressed by the same authors in the limitation section, and related to the fact that merit and need are evaluated by means of very different cues that rely on different cognitive processes (more abstract thinking for merit than need). I wonder whether and how such difference can bias the overall computational model and interpretation of the results (e.g. ideal you vary merit and need to leave all other aspects invariant).

A second weakness is related to the sample size which is quite small for study 2. I wonder, given that study 2 fRMI data are not analyzed, whether is possible to recover some of the participants' behavioral results, at least the ones excluded because of bad MR image quality.

Finally, on a theoretical note, I would elaborate more on the distinction of merit and need. These concepts tap into very specific aspects of morality, which I suspect have been widely explored. At the moment I am missing a more elaborate account of this.

Reviewer #1 (Public Review):

Summary:

This is an important work showing that loss of LRRK function causes late-onset dopaminergic neurodegeneration in a cell-autonomous manner. One of the LRRK members, LRRK2, is of significant translational importance as mutations in LRRK2 cause late-onset autosomal dominant Parkinson's disease (PD). While many in the field assume that LRRK2 mutant causes PD via increased LRRK2 activity (i.e., kinase activity), it is not a settled issue as not all disease-causing mutant LRRK2 exhibit increased activity. Further, while LRRK2 inhibitors are under clinical trials for PD, the consequence of chronic, long-term LRRK2 inhibition is unknown. Thus, studies evaluating the long-term impact of LRRK deficit have important translational implications. Moreover, because LRRK proteins, particularly LRRK2, are known to modulate immune response and intracellular membrane trafficking, the study's results and the reagents will be valuable for others interested in LRRK function.

Strengths:

This report describes a mouse model where the LRRK1 and LRRK2 gene is conditionally deleted in dopaminergic neurons. Previously, this group showed that while loss of LRRK2 expression does not cause brain phenotype, loss of both LRRK1 and LRRK2 causes a later onset, progressive degeneration of catecholaminergic neurons and dopaminergic (DAergic) neurons in the substantia nigra (SN), and noradrenergic neurons in the locus coeruleus (LC). However, because LRRK genes are widely expressed with some peripheral phenotypes, it was unknown if the neurodegeneration in the LRRK double knockout (DKO) was cell autonomous. To rigorously test this question, the authors have generated a double conditional (cDKO) allele where both LRRK1 and LRRK2 genes were targeted to contain loxP sites. In my view, this was beyond what is usually required, as most investigators might might combine one KO allele with another floxed allele. The authors provide a rigorous validation showing that the Driver (DAT-Cre) is expressed in most DAergic neurons in the SN and that LRRK levers are decreased selectively in the ventral midbrain. Using these mice, the authors show that the number of DAergic neurons is normal at 15 but significantly decreased at 20 months of age. Moreover, the authors show that the number of apoptotic neurons is increased by ~2X in aged SN, demonstrating increased ongoing cell death, as well as an increase in activated microglia. The degeneration is limited to DAergic neurons as LC neurons are not lost as this population does not express DAT. Overall, the mouse genetics and experimental analysis were performed rigorously, and the results were statistically sound and compelling.

Weaknesses:

I only have a few minor comments. First is that in PD and other degenerative conditions, loss of axons and terminals occurs prior to cell bodies. It might be beneficial to show the status of DAergic markers in the striatum. Second, previous studies indicate that very little, if any, LRRK1 is expressed in SN DAergic neurons. This also the case with the Allen Brain Atlas profile. Thus, authors should discuss the discrepancy as authors seem to imply significant LRRK1 expression in DA neurons.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Shen and collaborators described the generation of cDKO mice lacking LRRK1 and LRRK2 selectively in DAT-positive DAergic neurons. The Authors asked whether selective deletion of both LRRK isoforms could lead to a Parkinsonian phenotype, as previously reported by the same group in germline double LRRK1 and LRRK2 knockout mice (PMID: 29056298). Indeed, cDKO mice developed a late reduction of TH+ neurons in SNpc that partially correlated with the reduction of NeuN+ cells. This was associated with increased apoptotic cell and microglial cell numbers in SNpc. Unlike the constitutive DKO mice described earlier, however, cDKO mice did not replicate the dramatic increase in the number of autophagic vacuoles. The study supports the authors' hypothesis that loss of function rather than gain of function of LRRK2 leads to PD.

Strengths:

The study described for the first time a model where both the PD-associated gene LRRK2 and its homolog LRRK1 are deleted selectively in DAergic neurons, offering a new tool to understand the physiopathological role of LRRK2 and the compensating role of LRRK1 in modulating DAergic cell function.

Weaknesses:

The model has no construct validity since loss of function mutations of LRRK2 are well-tolerated in humans and do not lead to PD. The evidence of a Parkinsonian phenotype in these cDKO mice is limited and should be considered preliminary.

Reviewer #3 (Public Review):

Kang, Huang, and colleagues investigated the impact of LRRK1 and LRRK2 deletion, specifically in dopaminergic neurons, using a novel cDKO mouse model. They observed a significant reduction in DAergic neurons in the substantia nigra in their conditional LRRK1 and LRRK2 KO mice and a corresponding increase in markers of apoptosis and gliosis. This work set out to address a long-standing question within the field around the role and importance of LRRK1 and LRRK2 in DAergic neurons and suggests that the loss of both proteins triggers some neurodegeneration and glial activation.

The studies included in this work are carefully performed and clearly communicated, but additional studies are needed to strengthen further the authors' claims around the consequences of LRRK2 deletion in DAergic neurons.

1) In Figures 2E and F, the authors assess the protein levels of LRRK1 and LRRK2 in their cDKO mouse model to confirm the deletion of both proteins. They observe a mild loss of LRRK1 and LRRK2 signals in the ventral midbrain compared to wild-type animals. While this is not surprising given other cell types that still express LRRK1 and LRRK2 would be present in their dissected ventral midbrain samples, it does not sufficiently confirm that LRRK1 and LRRK2 are not expressed in DAergic neurons. Additional data is needed to more directly demonstrate that LRRK1 and LRRK2 protein levels are reduced in DAergic neurons, including analysis of LRRK1 and LRRK2 protein levels via immunohistochemistry or FACS-based analysis of TH+ neurons.

2) The authors observed a significant but modest effect of LRRK1 and LRRK2 deletion on the number of TH+ neurons in the substantia nigra (12-15% loss at 20-24 months of age). It is unclear whether this extent of neuron loss is functionally relevant. To strengthen the impact of these data, additional studies are warranted to determine whether this translates into any PD-relevant deficits in the mice, including motor deficits or alterations in alpha-synuclein accumulation/aggregation.

3) The authors demonstrate that, unlike in the germline LRRK DKO mice, they do not observe any alterations in electron-dense vacuoles via EM. Given their data showing increased apoptosis and gliosis, it remains unclear how the loss of LRRK proteins leads to DAergic neuronal cell loss. Mechanistic studies would be insightful to understand better potential explanations for how the loss of LRRK1 and LRRK2 may impair cellular survival, and additional text should be added to the discussion to discuss potential hypotheses for how this might occur.

4) The authors discuss the potential implications of the neuronal cell loss observed in cDKO mice for LRRK1 and LRRK2 for therapeutic approaches targeting LRRK2 and suggest this argues that LRRK2 variants may exert their effects through a loss-of-protein function. However, all of the data generated in this work focus on a mouse in which both LRRK1 and LRRK2 have been deleted, and it is therefore difficult to make any definitive conclusions about the consequences of specifically targeting LRRK2. The authors note potential redundancy between the two LRRK proteins, and they should soften some of their conclusions in the discussion section around implications for the effects of LRRK2 variants. Human subjects that carry LRRK2 loss-of-function alleles do not have an increased risk for developing PD, which argues against the author's conclusions that LRRK2 variants associated with PD are loss-of-function. Additional text should be included in their discussion to better address these nuances and caution should be used in terms of extrapolating their data to effects observed with PD-linked variants in LRRK2.

Reviewer #1 (Public Review):

In this manuscript, the authors identified compound heterozygous mutations in CFAP52 recessively cosegregating with male infertility status in a non-consanguineous family. The Cfap52-mutant patient exhibits a mixed acephalic spermatozoa syndrome (ASS) and multiple morphological abnormalities of the sperm flagella (MMAF) phenotype. The influence of mutations on CFAP52 protein function is well validated by in vitro cell experiments and immunofluorescence staining. Cfap52-KO mice are further constructed and perfectly resemble the Cfap52-mutant patient's infertile phenotype, also showing a mixed ASS and MMAF phenotype. The phenotype and underlying mechanisms of the disruption of sperm head-tail connection and flagella development are carefully analyzed by TEM, Western blotting, and immunofluorescence staining. The data presented revealed a prominent role for CFAP52 in sperm development, suggesting that CFAP52 is a novel diagnostic target for male infertility with defects of sperm head-tail connection and flagella development.

Reviewer #2 (Public Review):

Summary:<br /> The authors tried to identify the genetic factors for asthenoteratozoospermia. Using whole-exome sequencing, they analyzed a family with an infertile male and identified CFAP52 variants. They further knockout mouse Cfap52 gene and the homozygous mice phenocopied the patient. CFAP52 interacts with several other sperm proteins to maintain normal sperm morphology. Finally, CFAP52-associated male infertility in humans and mice could be overcome by using intracytoplasmic sperm injections (ICSI).

Strengths:<br /> The major strength of this study is to identify genetic factors contributing to asthenoteratozoospermia, and to generate a mouse knockout model to validate the factor.

Weaknesses:<br /> The authors did not use the OMICS to dissect the potential mechanisms. Instead, they took the advantage of direct co-IP experiment to fish the binding partners. They also did not discuss in detail why other motile cilia have different behavior.

Reviewer #3 (Public Review):

Summary:<br /> In this study, Jin et al. report the first evidence of CFAP52 mutations in human male infertility by identifying deleterious compound heterozygous mutations of CFAP52 in infertile human patients with acephalic and multiple morphological abnormalities in flagella (MMAF) phenotypes but without other abnormalities in motile cilia. They validated the pathogenicity of the mutations by an in vitro minigene assay and the absence of proteins in the patient's spermatozoa. Using a Cfap52 knockout mouse model they generated, the authors showed that the animals are hydrocephalic and the sperm have coupling defects, head decapitation, and axonemal structure disruption, supporting what was observed in human patients.

Strengths:<br /> The major strengths of the study are the rigorous phenotypic and molecular analysis of normal and patient spermatozoa and the demonstration of infertility treatment by ICSI. The authors demonstrated the interaction between CFAP52 and SPATA6, a head-tail coupling regulator and structural protein, and showed that CFAP52 can interact with components of the microtubule inner protein (MIP), radial spoke, and outer dynein arm proteins.

Weaknesses:<br /> The weakness of the study is some inconsistency in the localization of the CFAP52 protein in human spermatozoa in the figures and the lack of such localization information completely missing in mouse spermatozoa. Putting their findings in the context of the newly available structural information from the recent series of unambiguous and unequivocal identification of CFAP52 as an MIP in the B tubule will not only greatly benefit the interpretation of the study, but also resolve the inconsistent sperm phenotypes reported by an independent study. Since the mouse model is not designed to exactly recapitulate the human mutations but a complete knockout and the knockout mice show hydrocephaly phenotype as well, some of the claims of causality and ICSI as a treatment need to be tempered. Discussing the frequency of acephaly and MMAF in primary male infertility will be beneficial to justify CFAP52 as a practical diagnostic tool.

Reviewer #1 (Public Review):

Summary:<br /> TRIP13/Pch2 is a conserved essential regulator of meiotic recombination from yeast to humans. In this manuscript, the authors generated TRIP13 null mice and Flag-tagged TRIP13 knock-in mice to study its role in meiosis. They demonstrate that TRIP13 regulates MORMA domain proteins and is essential for meiotic completion and fertility. The main impact of this manuscript is its clarification of the in vivo function of TRIP13 during mouse meiosis and its previously unrecognized role as a dose-sensitive regulator of meiosis.

Strengths:<br /> Two previously reported Trip13 mutations in mice are both hypomorphic alleles with distinct phenotypes, precluding a conclusion on its function. This study for the first time generated the TRIP13 null mice, definitively revealing the function of TRIP13 in meiosis. The authors also show the novel localization of TRIP13 at SC and its independence from the axial element components. The finding of dose-sensitive regulation of meiosis by TRIP13 has implications in understanding human meiosis and disease phenotypes.

Weaknesses:<br /> This manuscript would be more impactful if more mechanistic advancements could be made. For example, the authors could follow up with one of the new interactors identified by MS to offer new insight into the molecular function of TRIP13.

Reviewer #2 (Public Review):

Summary and Strengths:<br /> In this manuscript, Chotiner and colleagues demonstrated the localization of TRIP13 and clarified the phenotypes of Trip13-null mice in mouse meiosis. The meiotic phenotypes of Trip13 have been well characterized using the hypomorph alleles in the literature. However, the null phenotypes have not been examined, and the localization of TRIP13 was not clearly demonstrated. The study fills these important knowledge gaps in the field. The demonstration of TRIP13 localization to SC in mice provides an explanation of how HOMRA domain proteins are evicted from SC in diverse organisms. This conclusion was confirmed in both IF and TRIP13-tagged Tg mice. Further, the phenotypes of Trip13-null mice are very clear. The manuscript is well crafted, and the discussion section is well organized and comprehends the topic in the field. All in all, the manuscript will provide important knowledge in the field of meiosis.

Weaknesses:<br /> The heterozygous phenotypes demonstrate that TRIP13 is a dosage-sensitive regulator of meiosis. In relation to this conclusion, as summarized in the discussion section, other mutants defective in meiotic recombination showed dosage-sensitive phenotypes. However, the authors did not examine meiotic recombination in the Trip13-null mice.

Reviewer #3 (Public Review):

Summary:<br /> The authors perform a thorough examination of the phenotypes of a newly generated Trip13 null allele in mice, noting defects in chromosome synapsis and impact on localization of other key proteins (namely HORMADs) on meiotic chromosomes. The vast majority of data confirms observations of several prior studies of Trip13 alleles (moderate and severe hypomorphs). The original or primary aims of the study aren't clear, but it can be assumed that the authors wanted to better study the role of this protein in evicting HORMADs upon synapsis by studying phenotypes of mutants and better characterizing TRIP13 localization data (which they find localizes to the central element of synapsed chromosomes using a new epitope-tagged allele). Their data confirm prior reports and are consistent with localization data of the orthologous Pch2 protein in many other organisms.

Strengths:<br /> The quality of data is high. Probably the most important data the authors find is that TRIP13 is localized along the CE of synapsed chromosomes. However, this was not unexpected because PCH2 is also similarly localized. Also, the authors use a clear null (deletion allele), whereas prior studies used hypomorphs.

Weaknesses:<br /> There is limited new data; most are confirmatory or expected (i.e., SC localization), and thus the impact of this report is not high. The claim that TRIP13 "functions as a dosage-sensitive regulator of meiosis" is exaggerated in my opinion. Indeed, the authors make the observation that hets have a phenotype, but numerous genes have haploinsufficient phenotypes. In my opinion, it is a leap to extrapolate this to infer that TRIP13 is a "regulator" of meiosis. What is the definition of a meiosis regulator? Is it at the apex of the meiosis process, or is it a crucial cog of any aspect of meiosis?

Reviewer #1 (Public Review):

Summary:<br /> The authors appear to be attempting to describe dynamic changes in the chromatin landscape in spermatogonial cells during postnatal development ranging from prepubertal stages at postnatal days 8 or 15 to adult stages. The authors attempt to relate differences they observe in chromatin accessibility at these different stages to changes in gene expression to better understand the molecular mechanisms regulating this differential gene expression.

Strengths:<br /> The primary strength of the manuscript is that it provides additional datasets describing gene expression and chromatin accessibility patterns in spermatogonial cells at different postnatal ages.

Weaknesses:<br /> There appears to be a lack of basic knowledge of the process of spermatogenesis. For instance, the statement that "During the first week of postnatal life, a population of SCs continues to proliferate to give rise to undifferentiated Asingle (As), Apaired (Apr) and Aaligned (Aal) cells. The remaining SCs differentiate to form chains of daughter cells that become primary and secondary permatocytes around postnatal day (PND) 10 to 12." is inaccurate. The Aal cells are the spermatogonial chains, the two are not distinct from one another. In addition, the authors fail to mention spermatogonial stem cells which form the basis for steady-state spermatogenesis. The authors also do not acknowledge the well-known fact that, in the mouse, the first wave of spermatogenesis is distinct from subsequent waves. Finally, the authors do not mention the presence of both undifferentiated spermatogonia (aka - type A) and differentiating spermatogonia (aka - type B). The premise for the study they present appears to be the implication that little is known about the dynamics of chromatin during the development of spermatogonia. However, there are published studies on this topic that have already provided much of the information that is presented in the current manuscript.

It is not clear which spermatogonial subtype the authors intended to profile with their analyses. On the one hand, they used PLZF to FACS sort cells. This typically enriches for undifferentiated spermatogonia. On the other hand, they report detection in the sorted population of markers such as c-KIT which is a well-known marker of differentiating spermatogonia, and that is in the same population in which ID4, a well-known marker of spermatogonial stem cells, was detected. The authors cite multiple previously published studies of gene expression during spermatogenesis, including studies of gene expression in spermatogonia. It is not at all clear what the authors' data adds to the previously available data on this subject.

The authors analyzed cells recovered at PND 8 and 15 and compared those to cells recovered from the adult testis. The PND 8 and 15 cells would be from the initial wave of spermatogenesis whereas those from the adult testis would represent steady-state spermatogenesis. However, as noted above, there appears to be a lack of awareness of the well-established differences between spermatogenesis occurring at each of these stages.

In general, the authors present observational data of the sort that is generated by RNA-seq and ATAC-seq analyses, and they speculate on the potential significance of several of these observations. However, they provide no definitive data to support any of their speculations. This further illustrates the fact that this study contributes little if any new information beyond that already available from the numerous previously published RNA-seq and ATAC-seq studies of spermatogenesis. In short, the study described in this manuscript does not advance the field.

The phenomenon of epigenetic priming is discussed, but then it seems that there is some expression of surprise that the data demonstrate what this reviewer would argue are examples of that phenomenon. The authors discuss the "modest correspondence between transcription and chromatin accessibility in SCs." Chromatin accessibility is an example of an epigenetic parameter associated with the primed state. The primed state is not fully equivalent to the actively expressing state. It appears that certain histone modifications along with transcription factors are critical to the transition between the primed and actively expressing states (in either direction). The cell types that were investigated in this study are closely related spermatogenic, and predominantly spermatogonial cell types. It is very likely that the differentially expressed loci will be primed in both the early (PND 8 or 15) and adult stages, even though those genes are differentially expressed at those stages. Thus, it is not surprising that there is not a strict concordance between +/- chromatin accessibility and +/- active or elevated expression.

Reviewer #2 (Public Review):

The objective of this study from Lazar-Contes et al. is to examine chromatin accessibility changes in "spermatogonial cells" (SCs) across testis development. Exactly what SCs are, however, remains a mystery. The authors mention in the abstract that SCs are undifferentiated male germ cells and have self-renewal and differentiation activity, which would be true for Spermatogonial STEM Cells (SSCs), a very small subset of total spermatogonia, but then the methods they use to retrieve such cells using antibodies that enrich for undifferentiated spermatogonia encompass both undifferentiated and differentiating spermatogonia. Data in Fig. 1B prove that most (85-95%) are PLZF+, but PLZF is known to be expressed both by undifferentiated and differentiating (KIT+) spermatogonia (Niedenberger et al., 2015; PMID: 25737569). Thus, the bulk RNA-seq and ATAC-seq data arising from these cells constitute the aggregate results comprising the phenotype of a highly heterogeneous mixture of spermatogonia (plus contaminating somatic cells), NOT SSCs. Indeed, Fig. 1C demonstrates this by showing the detection of Kit mRNA (a well-known marker of differentiating spermatogonia - which the authors claim on line 89 is a marker of SCs!), along with the detection of markers of various somatic cell populations (albeit at lower levels). This admixture problem influences the results - the authors show ATAC-seq accessibility traces for several genes in Fig. 2E (exhibiting differences between P15 and Adult), including Ihh, which is not expressed by spermatogenic cells, and Col6a1, which is expressed by peritubular myoid cells. Thus, the methods in this paper are fundamentally flawed, which precludes drawing any firm conclusions from the data about changes in chromatin accessibility among spermatogonia (SCs?) across postnatal testis development. In addition, there already are numerous scRNA-seq datasets from mouse spermatogenic cells at the same developmental stages in question. Moreover, several groups have used bulk ATAC-seq to profile enriched populations of spermatogonia, including from synchronized spermatogenesis which reflects a high degree of purity (see Maezawa et al., 2018 PMID: 29126117 and Schlief et al., 2023 PMID: 36983846 and in cultured spermatogonia - Suen et al., 2022 PMID: 36509798) - so this topic has already begun to be examined. None of these papers was cited, so it appears the authors were unaware of this work. The authors' methodological choice is even more surprising given the wealth of single-cell evidence in the literature since 2018 demonstrating the exceptional heterogeneity among spermatogonia at these developmental stages (the authors DID cite some of these papers, so they are aware). Indeed, it is currently possible to perform concurrent scATAC-seq and scRNA-seq (10x Genomics Multiome), which would have made these data quite useful and robust. As it stands, given the lack of novelty and critical methodological flaws, readers should be cautioned that there is little new information to be learned about spermatogenesis from this study, and in fact, the data in Figures 2-5 may lead readers astray because they do not reflect the biology of any one type of male germ cell. Indeed, not only do these data not add to our understanding of spermatogonial development, but they are damaging to the field if their source and identity are properly understood. Here are some specific examples of the problems with these data:

1. Fig. 2D - Gata4 and Lhcgr are not expressed by germ cells in the testis.

2. Fig. 3A - WT1 is expressed by Sertoli cells, so the change in accessibility of regions containing a WT1 motif suggests differential contamination with Sertoli cells. Since Wt1 mRNA was differentially high in P15 (Fig. 3B) - this seems to be the most likely explanation for the results. How was this excluded?

3. Fig. 3D - Since Dmrt1 is expressed by Sertoli cells, the "downregulation" likely represents a reduction in Sertoli cell contamination in the adult, like the point above. Did the authors consider this?

Reviewer #3 (Public Review):

In this study, Lazar-Contes and colleagues aimed to determine whether chromatin accessibility changes in the spermatogonial population during different phases of postnatal mammalian testis development. Because actions of the spermatogonial population set the foundation for continual and robust spermatogenesis and the gene networks regulating their biology are undefined, the goal of the study has merit. To advance knowledge, the authors used mice as a model and isolated spermatogonia from three different postnatal developmental age points using a cell sorting methodology that was based on cell surface markers reported in previous studies and then performed bulk RNA-sequencing and ATAC-sequencing. Overall, the technical aspects of the sequencing analyses and computational/bioinformatics seem sound but there are several concerns with the cell population isolated from testes and lack of acknowledgment for previous studies that have also performed ATAC-sequencing on spermatogonia of mouse and human testes. The limitations, described below, call into question the validity of the interpretations and reduce the potential merit of the findings.

I suggest changing the acronym for spermatogonial cells from SC to SPG for two reasons. First, SPG is the commonly used acronym in the field of mammalian spermatogenesis. Second, SC is commonly used for Sertoli Cells.

The authors should provide a rationale for why they used postnatal day 8 and 15 mice.

The FACS sorting approach used was based on cell surface proteins that are not germline-specific so there were undoubtedly somatic cells in the samples used for both RNA and ATAC sequencing. Thus, it is essential to demonstrate the level of both germ cell and undifferentiated spermatogonial enrichment in the isolated and profiled cell populations. To achieve this, the authors used PLZF as a biomarker of undifferentiated spermatogonia. Although PLZF is indeed expressed by undifferentiated spermatogonia, there have been several studies demonstrating that expression extends into differentiating spermatogonia. In addition, PLZF is not germ-cell specific and single-cell RNA-seq analyses of testicular tissue have revealed that there are somatic cell populations that express Plzf, at least at the mRNA level. For these reasons, I suggest that the authors assess the isolated cell populations using a germ-cell specific biomarker such as DDX4 in combination with PLZF to get a more accurate assessment of the undifferentiated spermatogonial composition. This assessment is essential for the interpretation of the RNA-seq and ATAC-seq data that was generated.

A previous study by the Namekawa lab (PMID: 29126117) performed ATAC-seq on a similar cell population (THY1+ FACS sorted) that was isolated from pre-pubertal mouse testes. It was surprising to not see this study referenced in the current manuscript. In addition, it seems prudent to cross-reference the two ATAC-seq datasets for commonalities and differences. In addition, there are several published studies on scATAC-seq of human spermatogonia that might be of interest to cross-reference with the ATAC-seq data presented in the current study to provide an understanding of translational merit for the findings.

Reviewer #1 (Public Review):

Summary:<br /> Liao et al leveraged two powerful genomics techniques-CUT&RUN and RNA sequencing-to identify genomic regions bound by and activated or inactivated by SMAD1, SMAD5, and the progesterone receptor during endometrial stromal cell decidualization.

Strengths:<br /> The authors utilized powerful next generation sequencing and identified important transcriptional mechanisms of SMAD1/5 and PGR during decidualization in vivo.

Weaknesses:<br /> Overall, the manuscript and study are well structured and provide critical mechanistic updates on the roles of SMAD1/5 in decidualization and preparation of the maternal endometrium for pregnancy. Please consider the following to improve the manuscript:

• Figure 4: A and C show bar graphs, not histograms. Please alter this phrasing.<br /> • What post hoc test was performed on qPCR analyses? (Figure 6). It is evident that any assumptions of equal variance need to be negated due to the wide dispersion in experimental response invalidating the assumptions of a one-way ANOVA.<br /> • Figure 6: what data points are plotted? Are these technical replicates from individual wells or qPCR technical replicates?<br /> • Figure 6: Consider changing graph colors to increase visibility of error bars and data points.<br /> • Figure 6 legend: no histograms are shown in this figure. Refer to all gene names utilizing proper nomenclature and conventions (gene names should be italicized).<br /> • qPCR analyses: qPCR normalization should be done to at least two internal control genes, preferably three according to the MIQE guidelines (PMID: 19246619).<br /> • Supplement figure 2: graphs are bar graphs, not histograms.

Reviewer #2 (Public Review):

Summary:

Liao and colleagues generated tagged SMAD1 and SMAD5 mouse models and identified genome occupancy of these two factors in the uterus of these mice using the CUT&RUN assay. The authors used integrative bioinformatic approaches to identify putative SMAD1/5 direct downstream target genes and to catalog the SMAD1/5 and PGR genome co-localization pattern. The role of SMAD1/5 on stromal decidualization was assayed in vitro on primary human endometrial stromal cells. The new mouse models offer opportunities to further dissect SMAD1 and SMAD5 functions without the limitation from SMAD antibodies, which is significant. The CUT&RUN data further support the usefulness of these mouse models for this purpose.

Strengths:<br /> The strength of this study is the novelty of new mouse models and the valuable cistromic data derived from these mice.

Weaknesses:<br /> The weakness of the present version of the manuscript includes the self-limited data analysis approaches such as the proximal promoter based bioinformatic filter and a missed opportunity to investigate the role of SMAD1/5 on determining the genome occupancy of major uterine transcription regulators.

Reviewer #3 (Public Review):

Summary:<br /> As SMAD1/5 activities have previously been indistinguishable, these studies provide a new mouse model to finally understand unique downstream activation of SMAD1/5 target genes, a model useful for many scientific fields. Using CUT&RUN analyses with gene overlap comparisons and signaling pathway analyses, specific targets for SMAD1 versus SMAD5 were compared, identified, and interpreted. These data validate previous findings showing strong evidence that SMADs directly govern critical genes required for endometrial receptivity and decidualization, including cell adhesion and vascular development. Further, SMAD targets were overlapped with progesterone receptor binding sites to identify regions of potential synergistic regulation of implantation. The authors report strong correlations between progesterone receptor and SMAD1/5 direct targets to cooperatively promote embryo implantation. Finally, the authors validated SMAD1/5 gene regulation in primary human endometrial stromal cells. These studies provide a data-rich survey of SMAD family transcription, defining its role as a governor of early pregnancy.

Strengths:<br /> This manuscript provides a valuable survey of SMAD1/5 direct transcriptional events at the time of receptivity. As embryo implantation is controlled by extensive epithelial to stromal molecular crosstalk and hormonal regulation in space and time, the authors state a strong, descriptive narrative defining how SMAD1/5 plays a central role at the site of this molecular orchestration. The implementation of cutting-edge techniques and models and simple comparative analyses provide a straightforward, yet elegant manuscript.

Although the progesterone receptor exists as a major regulator of early pregnancy, the authors have demonstrated clear evidence that progesterone receptor with SMAD1/5 work in concert to molecularly regulate targets such as Sox17, Id2, Tgfbr2, Runx1, Foxo1 and more at embryo implantation. Additionally, the authors pinpoint other critical transcription factor motifs that work with SMADs and the progesterone receptor to promote early pregnancy transcriptional paradigms.

Weaknesses:<br /> Although a wonderful new tool to ascertain SMAD1 versus SMAD5 downstream signaling, the importance of these factors in governing early pregnancy is not novel. Furthermore, functional validation studies are needed to confirm interactions at promoter regions. Addtionally, the authors presume that all overlapped genes are shared between progesterone receptor and SMAD1/5, yet some peak representations do not overlap. Although, transcriptional activation can occur at the same time, they may not occur in the same complex. Thus, further confirmation of these transcriptional events is warranted.

Since whole murine uterus was used for these studies, the specific functions of SMAD1/5 in the stroma versus the epithelium (versus the myometrium) remain unknown. Specific roles for SMAD1/5 in the uterine stroma and epithelial compartments still need to be examined. Also, further work is needed to delineate binding and transcriptional activation of SMAD1/5 and the progesterone receptor in stromal versus epithelial uterine compartments.

There are asynchronous gene responses in the SMAD1/5 ablated mouse model compared to the siRNA-treated human endometrial stromal cells. These differences can be confounding, and more clarity is required in understanding the meaning of these differences and as they relate to the entire SMAD transcriptome.

Reviewer #1 (Public Review):

Summary:<br /> The authors start out by doing a time-calibrated gene/species tree analysis of the animal gasdermin family, resulting in a dendrogram showing the relationship of the individual gasdermin subfamilies and suggesting a series of gene duplication events (and gene losses) that lead to the gasdermin distribution in extant species. They observe that the GSDMA proteins from birds, reptiles, and amphibians do not form a clade with the mammalian GSDMAs and notice that the non-mammalian GSDMA proteins share a conserved caspase-1 cleavage motif at the predicted activation site. The authors provide several series of experiments showing that the non-mammalian GSDMA proteins can indeed be activated by caspase-1 and that this activation leads to cell death (in human cells). They also investigate the role of the caspase-1 recognition tetrapeptide for cleavage by caspase-1 and for the pathogen-derived protease SpeB.

Strengths:<br /> The evolutionary analysis performed in this manuscript appears to use a broader data basis than what has been used in other published work. An interesting result of this analysis is the suggestion that GSDMA is evolutionarily older than the main mammalian pyroptotic GSDMD, and that birds, reptiles, and amphibians lack GSDMD but use GSDMA for the same purpose. The consequence that bird GSDMA should be activated by an inflammatory caspase (=caspase1) is convincingly supported by the experiments provided in the manuscript.

Weaknesses:<br /> 1) As a non-expert in phylogenetic tree reconstruction, I find the tree resulting from the authors' analysis surprising (in particular the polyphyly of GSDMA) and at odds with several other published trees of this family. The differences might be due to differences in the data being used or due to the tree construction method, but no explanation for this discrepancy is provided.

2) While the cleavability of bird/reptile GSDMA by caspase-1 is well-supported by several experiments, the role of this cleavage for pyroptotic cell killing is addressed more superficially. One cell viability assay upon overexpression of GSDMA-NTD in human HEK293 cells is shown and one micrograph shows pyroptotic morphology upon expression in HeLa cells. It is not clear why these experiments were limited to human cells and why two different cell types were used for the two complementary results.

3) The introduction mentions as a motivation for this work our lack of knowledge of how human GSDMA is activated. This is indeed an interesting and pressing question, but it is not really addressed in the manuscript. This is particularly true when believing the authors' dendrogram results that the bird and mammalian GSDMA families do not form a clade.

As a consequence, the significance of this finding is mostly limited to birds and reptiles.

Reviewer #2 (Public Review):

Summary:<br /> The authors investigated the molecular evolution of members of the gasdermin (GSDM) family. By adding the evolutionary time axis of animals, they created a new molecular phylogenetic tree different from previous ones. The analyzed result verified that non-mammalian GSDMAs and mammalian GSDMAs have diverged into completely different and separate clades. Furthermore, by biochemical analyses, the authors demonstrated non-mammalian GSDMA proteins are cleaved by the host-encoded caspase-1. They also showed mammalian GSDMAs have lost the cleavage site recognized by caspase-1. Instead, the authors proposed that the newly appeared GSDMD is now cleaved by caspase-1.

Through this study, we have been able to understand the changes in the molecular evolution of GSDMs, and by presenting the cleavage of GSDMAs through biochemical experiments, we have become able to grasp the comprehensive picture of this family of molecules. However, there are some parts where explanations are insufficient, so supplementary explanations and experiments seem to be necessary.

Strengths:<br /> It has a strong impact in advancing ideas into the study of pyroptotic cell death and even inflammatory responses involving caspase-1.

Weaknesses:<br /> Based on the position of mammalian GSDMA shown in the molecular phylogenetic tree (Figure 1), it may be difficult to completely agree with the authors' explanation of the evolution of GSDMA.

1) Focusing on mammalian GSDMA, this group, and mammalian GSDMD diverged into two clades, and before that, GSDMA/D groups and mammalian GSDMC separated into two, more before that, GSDMB, and further before that, non-mammalian GSDMA, when we checked Figure 1. In the molecular phylogenetic tree, it is impossible that GSDMA appears during evolution again. Mammalian GSDMAs are clearly paralogous molecules to non-mammalian GSDMAs in the figure. If they are bona fide orthologous, the mammalian GSDMA group should show a sub-clade in the non-mammalian GSDMA clade. It is better to describe the plausibility of the divergence in the molecular evolution of mammalian GSDMA in the Discussion section.

2) Regarding (1), it is recommended that the authors reconsider the validity of estimates of divergence dates by focusing on mammalian species divergence. Because the validity of this estimation requires a recheck of the molecular phylogenetic tree, including alignment.

3) If GSDMB and/or GSDMC between non-mammalian GSDMA and mammalian GSDMD as shown in the molecular phylogenetic tree would be cleaved by caspase-1, the story of this study becomes clearer. The authors should try that possibility.

Reviewer #1 (Public Review):

The authors present a detailed analysis of a set of molecular dynamics computer simulations of several variants of a T-cell receptor (TCR) in isolation and bound to a Major Histocompatibility Complex with peptide (pMHC), with the aim of improving our understanding of the mechanism T cell activation in immunity. By analyzing simulations of peptide mutants and partially truncated TCRs, the authors find that native peptide agonists lead to a so-called catch-bond response, whereby tensile force applied in the direction of separation between TCR/pMHC appears to strengthen the TCR/pMHC interface, whereas mutated peptides exhibit the more common slip-bond response, in which applied force destabilizes the binding interface.

Using various computational metrics and simulation statistics, the authors propose a model in which tensile force preferentially suppresses thermal fluctuations in the variable α domain of the TCR (vs the β domain) in a peptide-dependent manner, which orders and strengthens the binding interface by bringing together the complementarity-determining regions (CDRs) in the TCR variable chains, but only if the peptide is correctly matched to the TCR.

The study is detailed and written clearly, and conclusions appear convincing and are supported by the simulation data. However, the actual motions at the molecular or amino-acid level of how the catch-bond vs slip bond response originates remain somewhat unclear, and will probably warrant further investigations. Specific hypotheses that could be testable in experiments, such as predictions of which peptide (or TCR) mutations or which peptides could generate a catch-vs-slip response or activation, would have especially strengthened this study.

Reviewer #2 (Public Review):

In this work, Chang-Gonzalez and co-workers investigate the role of force in peptide recognition by T-cells using a model T-cell/peptide recognition complex. By applying forces through a harmonic restraint on distances, the authors probe the role of mechanical pulling on peptide binding specificity. They point to a role for force in distinguishing the different roles played by agonist and antagonist peptides for which the bound configuration is not clearly distinguishable. Overall, I would consider this work to be extensive and carefully done, and noteworthy for the number of mutant peptides and conditions probed. From the text, I'm not sure how specific these conclusions are to this particular complex, but I do not think this diminishes the specific studies.

I have a couple of specific comments on the methodology and analysis that the authors could consider:<br /> 1) It is not explained what is the origin of force on the peptide-MHC complex. Although I do know a bit about this, it's not clear to me how the force ends up applied across the complex (e.g. is it directional in any way, on what subdomains/residues do we expect it to be applied), and is it constant or stochastic. I think it would be important to add some discussion of this and how it translates into the way the force is applied here (on terminal residues of the complex).

2) In terms of application of the force, I find the use of a harmonic restraint and then determining a distance at which the force has a certain value to be indirect and a bit unphysical. As just mentioned, since the origin of the force is not a harmonic trap, it would be more straightforward to apply a pulling force which has the form -F*d, which would correspond to a constant force (see for example comment articles 10.1021/acs.jpcb.1c10715, 10.1021/acs.jpcb.1c06330). While application of a constant force will result in a new average distance, for small forces it does so in a way that does not change the variance of the distance whereas a harmonic force pollutes the variance (see e.g. 10.1021/ct300112v in a different context). A constant force could also shift the system into a different state not commensurate with the original distance, so by applying a harmonic trap, one could be keeping ones' self from exploring this, which could be important, as in the case of certain catch bond mechanisms. While I certainly wouldn't expect the authors to redo these extensive simulations, I think they could at least acknowledge this caveat, and they may be interested in considering a comparison of the two ways of applying a force in the future.

3) For the PCA analysis, I believe the authors learn separate PC vectors from different simulations and then take the dot product of those two vectors. Although this might be justified based on the simplified coordinate upon which the PCA is applied, in general, I am not a big fan of running PCA on separate data sets and then comparing the outputs, as the meaning seems opaque to me. To compare the biggest differences between many simulations, it would make more sense to me to perform PCA on all of the data combined, and see if there are certain combinations of quantities that distinguish the different simulations. Alternatively and probably better, one could perform linear discriminant analysis, which is appropriate in this case because one already knows that different simulations are in different states, and hence the LDA will directly give the linear coordinate that best distinguishes classes.

Reviewer #3 (Public Review):

This simulation study presents a valuable finding on the load-dependence (i.e., dependence on a pulling force) of the recognition of a peptide-bound major histocompatibility complex (pMHC) antigen by a T cell receptor (TCR). The evidence supporting the claims of the authors is solid, although inclusion of a larger number of simulations would have strengthened the study. The work will be of interest to computational structural biologists and immunologists.

Reviewer #1 (Public Review):

Chang et al. demonstrate through their findings that COVID-19 mRNA vaccination of hemodialysis patients produces no significant difference in antibody levels achieved across the vaccination series. They correlate the antibody responses through RNA sequencing data of dialysis patients versus healthy controls throughout the vaccination series. They also compare those with prior infection versus those who are infection naive. The antibody findings are interesting because they disagree with previous publications showing that dialysis patients have a significantly lower antibody titer level achieved from vaccination than controls. The authors posit that this may be age-related, but subject numbers in the current study are not adequately powered to make that definitive determination.

However, they find that T-cell responses may be muted in hemodialysis patients as they have lower activation of T-cell genes than healthy controls. The RNA sequencing evidence is solid. However, they lack data on a clinical correlation to T-cell responses.

Reviewer #2 (Public Review):

In HD patients, immune pathways alteration leads to higher susceptibility to infection and lower response to the COVID-19 mRNA vaccine. Therefore, it is important to understand the immune response to vaccines in ESRD patients against the COVID-19 pandemic. In this MS, the authors recruited 20 HD patients and cohort-matched controls to perform multiple experimental studies (including transcriptomic analysis, RNAseq, and Anti-Spike (trimer) IgG Titer Quantification) to investigate how immune pathways alteration in HD patients after COVID-19 mRNA vaccine injection. They demonstrate differing expression of BTMs and differing time courses of immune responses to the BTN162b2 mRNA COVID-19 vaccination in maintenance hemodialysis subjects (HD) compared to controls, which warrants further characterization of the immune dysregulation of ESRD and immune biomarkers. Overall, the study is well designed, and the result has potential clinical value and will interest nephrologists. The major concern of this study is the cohort set up. The sample sizes of recruited candidates are relatively small, and no validation cohort was designed. More importantly, between the two groups, the race distribution is uneven. For example, 10 black and 2 white HD patients were included, but accordingly, 3 black and 8 white people were recruited as controls. In such a small size of the clinical study, this kind of unevenness might cause potential issues in concluding. In addition, the control cohort also included 1 diabetes and 4 hypertension, patients. Will these existing primary diseases in controls cause noise in the data analysis because these metabolic diseases also can directly cause immune system dysfunction? In addition, there were 8 HD patients and 5 HC with a positive test of SARS-CoV-2 from 8 months to four weeks preceding vaccination. How long does the immune response last after being infected with COVID-19? Several studies have found that people infected with COVID-19 continue to produce antibodies to the virus for seven or eight months after recovery. Therefore, people with a COVID-19 history might not be suitable for this trial.

Reviewer #1 (Public Review):

This work introduces a novel framework for evaluating the performance of statistical methods that identify replay events. This is challenging because hippocampal replay is a latent cognitive process, where the ground truth is inaccessible, so methods cannot be evaluated against a known answer. The framework consists of two elements:<br /> 1. A replay sequence p-value, evaluated against shuffled permutations of the data, such as radon line fitting, rank-order correlation, or weighted correlation. This element determines how trajectory-like the spiking representation is. The p-value threshold for all accepted replay events is adjusted based on an empirical shuffled distribution to control for the false discovery rate.<br /> 2. A trajectory discriminability score, also evaluated against shuffled permutations of the data. In this case, there are two different possible spatial environments that can be replayed, so the method compares the log odds of track 1 vs. track 2.

The authors then use this framework (accepted number of replay events and trajectory discriminability) to study the performance of replay identification methods. They conclude that sharp wave ripple power is not a necessary criterion for identifying replay event candidates during awake run behavior if you have high multiunit activity, a higher number of permutations is better for identifying replay events, linear Bayesian decoding methods outperform rank-order correlation, and there is no evidence for pre-play.

The authors tackle a difficult and important problem for those studying hippocampal replay (and indeed all latent cognitive processes in the brain) with spiking data: how do we understand how well our methods are doing when the ground truth is inaccessible? Additionally, systematically studying how the variety of methods for identifying replay perform, is important for understanding the sometimes contradictory conclusions from replay papers. It helps consolidate the field around particular methods, leading to better reproducibility in the future. The authors' framework is also simple to implement and understand and the code has been provided, making it accessible to other neuroscientists. Testing for track discriminability, as well as the sequentiality of the replay event, is a sensible additional data point to eliminate "spurious" replay events.

However, there are some concerns with the framework as well. The novelty of the framework is questionable as it consists of a log odds measure previously used in two prior papers (Carey et al. 2019 and the authors' own Tirole & Huelin Gorriz, et al., 2022) and a multiple comparisons correction, albeit a unique empirical multiple comparisons correction based on shuffled data.

With respect to the log odds measure itself, as presented, it is reliant on having only two options to test between, limiting its general applicability. Even in the data used for the paper, there are sometimes three tracks, which could influence the conclusions of the paper about the validity of replay methods. This also highlights a weakness of the method in that it assumes that the true model (spatial track environment) is present in the set of options being tested. Furthermore, the log odds measure itself is sensitive to the defined ripple or multiunit start and end times, because it marginalizes over both position and time, so any inclusion of place cells that fire for the animal's stationary position could influence the discriminability of the track. Multiple track representations during a candidate replay event would also limit track discriminability. Finally, the authors call this measure "trajectory discriminability", which seems a misnomer as the time and position information are integrated out, so there is no notion of trajectory.

The authors also fail to make the connection with the control of the false discovery rate via false positives on empirical shuffles with existing multiple comparison corrections that control for false discovery rates (such as the Benjamini and Hochberg procedure or Storey's q-value). Additionally, the particular type of shuffle used will influence the empirically determined p-value, making the procedure dependent on the defined null distribution. Shuffling the data is also considerably more computationally intensive than the existing multiple comparison corrections.

Overall, the authors make interesting conclusions with respect to hippocampal replay methods, but the utility of the method is limited in scope because of its reliance on having exactly two comparisons and having to specify the null distribution to control for the false discovery rate. This work will be of interest to electrophysiologists studying hippocampal replay in spiking data.

Reviewer #2 (Public Review):

This study proposes to evaluate and compare different replay methods in the absence of "ground truth" using data from hippocampal recordings of rodents that were exposed to two different tracks on the same day. The study proposes to leverage the potential of Bayesian methods to decode replay and reactivation in the same events. They find that events that pass a higher threshold for replay typically yield a higher measure of reactivation. On the other hand, events from the shuffled data that pass thresholds for replay typically don't show any reactivation. While well-intentioned, I think the result is highly problematic and poorly conceived.

The work presents a lot of confusion about the nature of null hypothesis testing and the meaning of p-values. The prescription arrived at, to correct p-values by putting animals on two separate tracks and calculating a "sequence-less" measure of reactivation are impractical from an experimental point of view, and unsupportable from a statistical point of view. Much of the observations are presented as solutions for the field, but are in fact highly dependent on distinct features of the dataset at hand. The most interesting observation is that despite the existence of apparent sequences in the PRE-RUN data, no reactivation is detectable in those events, suggesting that in fact they represent spurious events. I would recommend the authors focus on this important observation and abandon the rest of the work, as it has the potential to further befuddle and promote poor statistical practices in the field.

The major issue is that the manuscript conveys much confusion about the nature of hypothesis testing and the meaning of p-values. It's worth stating here the definition of a p-value: the conditional probability of rejecting the null hypothesis given that the null hypothesis is true. Unfortunately, in places, this study appears to confound the meaning of the p-value with the probability of rejecting the null hypothesis given that the null hypothesis is NOT true-i.e. in their recordings from awake replay on different mazes. Most of their analysis is based on the observation that events that have higher reactivation scores, as reflected in the mean log odds differences, have lower p-values resulting from their replay analyses. Shuffled data, in contrast, does not show any reactivation but can still show spurious replays depending on the shuffle procedure used to create the surrogate dataset. The authors suggest using this to test different practices in replay detection. However, another important point that seems lost in this study is that the surrogate dataset that is contrasted with the actual data depends very specifically on the null hypothesis that is being tested. That is to say, each different shuffle procedure is in fact testing a different null hypothesis. Unfortunately, most studies, including this one, are not very explicit about which null hypothesis is being tested with a given resampling method, but the p-value obtained is only meaningful insofar as the null that is being tested and related assumptions are clearly understood. From a statistical point of view, it makes no sense to adjust the p-value obtained by one shuffle procedure according to the p-value obtained by a different shuffle procedure, which is what this study inappropriately proposes. Other prescriptions offered by the study are highly dataset and method dependent and discuss minutiae of event detection, such as whether or not to require power in the ripple frequency band.

Reviewer #3 (Public Review):

This study tackles a major problem with replay detection, which is that different methods can produce vastly different results. It provides compelling evidence that the source of this inconsistency is that biological data often violates assumptions of independent samples. This results in false positive rates that can vary greatly with the precise statistical assumptions of the chosen replay measure, the detection parameters, and the dataset itself. To address this issue, the authors propose to empirically estimate the false positive rate and control for it by adjusting the significance threshold. Remarkably, this reconciles the differences in replay detection methods, as the results of all the replay methods tested converge quite well (see Figure 6B). This suggests that by controlling for the false positive rate, one can get an accurate estimate of replay with any of the standard methods.

When comparing different replay detection methods, the authors use a sequence-independent log-odds difference score as a validation tool and an indirect measure of replay quality. This takes advantage of the two-track design of the experimental data, and its use here relies on the assumption that a true replay event would be associated with good (discriminable) reactivation of the environment that is being replayed. The other way replay "quality" is estimated is by the number of replay events detected once the false positive rate is taken into account. In this scheme, "better" replay is in the top right corner of Figure 6B: many detected events associated with congruent reactivation.

There are two possible ways the results from this study can be integrated into future replay research. The first, simpler, way is to take note of the empirically estimated false positive rates reported here and simply avoid the methods that result in high false positive rates (weighted correlation with a place bin shuffle or all-spike Spearman correlation with a spike-id shuffle). The second, perhaps more desirable, way is to integrate the practice of estimating the false positive rate when scoring replay and to take it into account. This is very powerful as it can be applied to any replay method with any choice of parameters and get an accurate estimate of replay.

How does one estimate the false positive rate in their dataset? The authors propose to use a cell-ID shuffle, which preserves all the firing statistics of replay events (bursts of spikes by the same cell, multi-unit fluctuations, etc.) but randomly swaps the cells' place fields, and to repeat the replay detection on this surrogate randomized dataset. Of course, there is no perfect shuffle, and it is possible that a surrogate dataset based on this particular shuffle may result in one underestimating the true false positive rate if different cell types are present (e.g. place field statistics may differ between CA1 and CA3 cells, or deep vs. superficial CA1 cells, or place cells vs. non-place cells if inclusion criteria are not strict). Moreover, it is crucial that this validation shuffle be independent of any shuffling procedure used to determine replay itself (which may not always be the case, particularly for the pre-decoding place field circular shuffle used by some of the methods here) lest the true false-positive rate be underestimated. Once the false positive rate is estimated, there are different ways one may choose to control for it: adjusting the significance threshold as the current study proposes, or directly comparing the number of events detected in the original vs surrogate data. Either way, with these caveats in mind, controlling for the false positive rate to the best of our ability is a powerful approach that the field should integrate.

Which replay detection method performed the best? If one does not control for varying false positive rates, there are two methods that resulted in strikingly high (>15%) false positive rates: these were weighted correlation with a place bin shuffle and Spearman correlation (using all spikes) with a spike-id shuffle. However, after controlling for the false positive rate (Figure 6B) all methods largely agree, including those with initially high false positive rates. There is no clear "winner" method, because there is a lot of overlap in the confidence intervals, and there also are some additional reasons for not overly interpreting small differences in the observed results between methods. The confidence intervals are likely to underestimate the true variance in the data because the resampling procedure does not involve hierarchical statistics and thus fails to account for statistical dependencies on the session and animal level. Moreover, it is possible that methods that involve shuffles similar to the cross-validation shuffle ("wcorr 2 shuffles", "wcorr 3 shuffles" both use a pre-decoding place field circular shuffle, which is very similar to the pre-decoding place field swap used in the cross-validation procedure to estimate the false positive rate) may underestimate the false positive rate and therefore inflate adjusted p-value and the proportion of significant events. We should therefore not interpret small differences in the measured values between methods, and the only clear winner and the best way to score replay is using any method after taking the empirically estimated false positive rate into account.

The authors recommend excluding low-ripple power events in sleep, because no replay was observed in events with low (0-3 z-units) ripple power specifically in sleep, but that no ripple restriction is necessary for awake events. There are problems with this conclusion. First, ripple power is not the only way to detect sharp-wave ripples (the sharp wave is very informative in detecting awake events). Second, when talking about sequence quality in awake non-ripple data, it is imperative for one to exclude theta sequences. The authors' speed threshold of 5 cm/s is not sufficient to guarantee that no theta cycles contaminate the awake replay events. Third, a direct comparison of the results with and without exclusion is lacking (selecting for the lower ripple power events is not the same as not having a threshold), so it is unclear how crucial it is to exclude the minority of the sleep events outside of ripples. The decision of whether or not to select for ripples should depend on the particular study and experimental conditions that can affect this measure (electrode placement, brain state prevalence, noise levels, etc.).

Finally, the authors address a controversial topic of de-novo preplay. With replay detection corrected for the false positive rate, none of the detection methods produce evidence of preplay sequences nor sequenceless reactivation in the tested dataset. This presents compelling evidence in favour of the view that the sequence of place fields formed on a novel track cannot be predicted by the sequential structure found in pre-task sleep.

Reviewer #1 (Public Review):

This work introduces a novel framework for evaluating the performance of statistical methods that identify replay events. This is challenging because hippocampal replay is a latent cognitive process, where the ground truth is inaccessible, so methods cannot be evaluated against a known answer. The framework consists of two elements:<br /> 1. A replay sequence p-value, evaluated against shuffled permutations of the data, such as radon line fitting, rank-order correlation, or weighted correlation. This element determines how trajectory-like the spiking representation is. The p-value threshold for all accepted replay events is adjusted based on an empirical shuffled distribution to control for the false discovery rate.<br /> 2. A trajectory discriminability score, also evaluated against shuffled permutations of the data. In this case, there are two different possible spatial environments that can be replayed, so the method compares the log odds of track 1 vs. track 2.

The authors then use this framework (accepted number of replay events and trajectory discriminability) to study the performance of replay identification methods. They conclude that sharp wave ripple power is not a necessary criterion for identifying replay event candidates during awake run behavior if you have high multiunit activity, a higher number of permutations is better for identifying replay events, linear Bayesian decoding methods outperform rank-order correlation, and there is no evidence for pre-play.

The authors tackle a difficult and important problem for those studying hippocampal replay (and indeed all latent cognitive processes in the brain) with spiking data: how do we understand how well our methods are doing when the ground truth is inaccessible? Additionally, systematically studying how the variety of methods for identifying replay perform, is important for understanding the sometimes contradictory conclusions from replay papers. It helps consolidate the field around particular methods, leading to better reproducibility in the future. The authors' framework is also simple to implement and understand and the code has been provided, making it accessible to other neuroscientists. Testing for track discriminability, as well as the sequentiality of the replay event, is a sensible additional data point to eliminate "spurious" replay events.

However, there are some concerns with the framework as well. The novelty of the framework is questionable as it consists of a log odds measure previously used in two prior papers (Carey et al. 2019 and the authors' own Tirole & Huelin Gorriz, et al., 2022) and a multiple comparisons correction, albeit a unique empirical multiple comparisons correction based on shuffled data.

With respect to the log odds measure itself, as presented, it is reliant on having only two options to test between, limiting its general applicability. Even in the data used for the paper, there are sometimes three tracks, which could influence the conclusions of the paper about the validity of replay methods. This also highlights a weakness of the method in that it assumes that the true model (spatial track environment) is present in the set of options being tested. Furthermore, the log odds measure itself is sensitive to the defined ripple or multiunit start and end times, because it marginalizes over both position and time, so any inclusion of place cells that fire for the animal's stationary position could influence the discriminability of the track. Multiple track representations during a candidate replay event would also limit track discriminability. Finally, the authors call this measure "trajectory discriminability", which seems a misnomer as the time and position information are integrated out, so there is no notion of trajectory.

The authors also fail to make the connection with the control of the false discovery rate via false positives on empirical shuffles with existing multiple comparison corrections that control for false discovery rates (such as the Benjamini and Hochberg procedure or Storey's q-value). Additionally, the particular type of shuffle used will influence the empirically determined p-value, making the procedure dependent on the defined null distribution. Shuffling the data is also considerably more computationally intensive than the existing multiple comparison corrections.

Overall, the authors make interesting conclusions with respect to hippocampal replay methods, but the utility of the method is limited in scope because of its reliance on having exactly two comparisons and having to specify the null distribution to control for the false discovery rate. This work will be of interest to electrophysiologists studying hippocampal replay in spiking data.

Reviewer #2 (Public Review):

This study proposes to evaluate and compare different replay methods in the absence of "ground truth" using data from hippocampal recordings of rodents that were exposed to two different tracks on the same day. The study proposes to leverage the potential of Bayesian methods to decode replay and reactivation in the same events. They find that events that pass a higher threshold for replay typically yield a higher measure of reactivation. On the other hand, events from the shuffled data that pass thresholds for replay typically don't show any reactivation. While well-intentioned, I think the result is highly problematic and poorly conceived.

The work presents a lot of confusion about the nature of null hypothesis testing and the meaning of p-values. The prescription arrived at, to correct p-values by putting animals on two separate tracks and calculating a "sequence-less" measure of reactivation are impractical from an experimental point of view, and unsupportable from a statistical point of view. Much of the observations are presented as solutions for the field, but are in fact highly dependent on distinct features of the dataset at hand. The most interesting observation is that despite the existence of apparent sequences in the PRE-RUN data, no reactivation is detectable in those events, suggesting that in fact they represent spurious events. I would recommend the authors focus on this important observation and abandon the rest of the work, as it has the potential to further befuddle and promote poor statistical practices in the field.

The major issue is that the manuscript conveys much confusion about the nature of hypothesis testing and the meaning of p-values. It's worth stating here the definition of a p-value: the conditional probability of rejecting the null hypothesis given that the null hypothesis is true. Unfortunately, in places, this study appears to confound the meaning of the p-value with the probability of rejecting the null hypothesis given that the null hypothesis is NOT true-i.e. in their recordings from awake replay on different mazes. Most of their analysis is based on the observation that events that have higher reactivation scores, as reflected in the mean log odds differences, have lower p-values resulting from their replay analyses. Shuffled data, in contrast, does not show any reactivation but can still show spurious replays depending on the shuffle procedure used to create the surrogate dataset. The authors suggest using this to test different practices in replay detection. However, another important point that seems lost in this study is that the surrogate dataset that is contrasted with the actual data depends very specifically on the null hypothesis that is being tested. That is to say, each different shuffle procedure is in fact testing a different null hypothesis. Unfortunately, most studies, including this one, are not very explicit about which null hypothesis is being tested with a given resampling method, but the p-value obtained is only meaningful insofar as the null that is being tested and related assumptions are clearly understood. From a statistical point of view, it makes no sense to adjust the p-value obtained by one shuffle procedure according to the p-value obtained by a different shuffle procedure, which is what this study inappropriately proposes. Other prescriptions offered by the study are highly dataset and method dependent and discuss minutiae of event detection, such as whether or not to require power in the ripple frequency band.

Reviewer #3 (Public Review):

This study tackles a major problem with replay detection, which is that different methods can produce vastly different results. It provides compelling evidence that the source of this inconsistency is that biological data often violates assumptions of independent samples. This results in false positive rates that can vary greatly with the precise statistical assumptions of the chosen replay measure, the detection parameters, and the dataset itself. To address this issue, the authors propose to empirically estimate the false positive rate and control for it by adjusting the significance threshold. Remarkably, this reconciles the differences in replay detection methods, as the results of all the replay methods tested converge quite well (see Figure 6B). This suggests that by controlling for the false positive rate, one can get an accurate estimate of replay with any of the standard methods.

When comparing different replay detection methods, the authors use a sequence-independent log-odds difference score as a validation tool and an indirect measure of replay quality. This takes advantage of the two-track design of the experimental data, and its use here relies on the assumption that a true replay event would be associated with good (discriminable) reactivation of the environment that is being replayed. The other way replay "quality" is estimated is by the number of replay events detected once the false positive rate is taken into account. In this scheme, "better" replay is in the top right corner of Figure 6B: many detected events associated with congruent reactivation.

There are two possible ways the results from this study can be integrated into future replay research. The first, simpler, way is to take note of the empirically estimated false positive rates reported here and simply avoid the methods that result in high false positive rates (weighted correlation with a place bin shuffle or all-spike Spearman correlation with a spike-id shuffle). The second, perhaps more desirable, way is to integrate the practice of estimating the false positive rate when scoring replay and to take it into account. This is very powerful as it can be applied to any replay method with any choice of parameters and get an accurate estimate of replay.

How does one estimate the false positive rate in their dataset? The authors propose to use a cell-ID shuffle, which preserves all the firing statistics of replay events (bursts of spikes by the same cell, multi-unit fluctuations, etc.) but randomly swaps the cells' place fields, and to repeat the replay detection on this surrogate randomized dataset. Of course, there is no perfect shuffle, and it is possible that a surrogate dataset based on this particular shuffle may result in one underestimating the true false positive rate if different cell types are present (e.g. place field statistics may differ between CA1 and CA3 cells, or deep vs. superficial CA1 cells, or place cells vs. non-place cells if inclusion criteria are not strict). Moreover, it is crucial that this validation shuffle be independent of any shuffling procedure used to determine replay itself (which may not always be the case, particularly for the pre-decoding place field circular shuffle used by some of the methods here) lest the true false-positive rate be underestimated. Once the false positive rate is estimated, there are different ways one may choose to control for it: adjusting the significance threshold as the current study proposes, or directly comparing the number of events detected in the original vs surrogate data. Either way, with these caveats in mind, controlling for the false positive rate to the best of our ability is a powerful approach that the field should integrate.

Which replay detection method performed the best? If one does not control for varying false positive rates, there are two methods that resulted in strikingly high (>15%) false positive rates: these were weighted correlation with a place bin shuffle and Spearman correlation (using all spikes) with a spike-id shuffle. However, after controlling for the false positive rate (Figure 6B) all methods largely agree, including those with initially high false positive rates. There is no clear "winner" method, because there is a lot of overlap in the confidence intervals, and there also are some additional reasons for not overly interpreting small differences in the observed results between methods. The confidence intervals are likely to underestimate the true variance in the data because the resampling procedure does not involve hierarchical statistics and thus fails to account for statistical dependencies on the session and animal level. Moreover, it is possible that methods that involve shuffles similar to the cross-validation shuffle ("wcorr 2 shuffles", "wcorr 3 shuffles" both use a pre-decoding place field circular shuffle, which is very similar to the pre-decoding place field swap used in the cross-validation procedure to estimate the false positive rate) may underestimate the false positive rate and therefore inflate adjusted p-value and the proportion of significant events. We should therefore not interpret small differences in the measured values between methods, and the only clear winner and the best way to score replay is using any method after taking the empirically estimated false positive rate into account.

The authors recommend excluding low-ripple power events in sleep, because no replay was observed in events with low (0-3 z-units) ripple power specifically in sleep, but that no ripple restriction is necessary for awake events. There are problems with this conclusion. First, ripple power is not the only way to detect sharp-wave ripples (the sharp wave is very informative in detecting awake events). Second, when talking about sequence quality in awake non-ripple data, it is imperative for one to exclude theta sequences. The authors' speed threshold of 5 cm/s is not sufficient to guarantee that no theta cycles contaminate the awake replay events. Third, a direct comparison of the results with and without exclusion is lacking (selecting for the lower ripple power events is not the same as not having a threshold), so it is unclear how crucial it is to exclude the minority of the sleep events outside of ripples. The decision of whether or not to select for ripples should depend on the particular study and experimental conditions that can affect this measure (electrode placement, brain state prevalence, noise levels, etc.).

Finally, the authors address a controversial topic of de-novo preplay. With replay detection corrected for the false positive rate, none of the detection methods produce evidence of preplay sequences nor sequenceless reactivation in the tested dataset. This presents compelling evidence in favour of the view that the sequence of place fields formed on a novel track cannot be predicted by the sequential structure found in pre-task sleep.

Reviewer #2 (Public Review):

Summary:

The work demonstrates that high-intensity ultrasound produces a release of extracellular vesicles from murine myotubes that is dependent on ultrasound intensity. It shows that this increase in extracellular vesicles is abolished in a nominally zero Ca2+ solution. It then shows that these vesicles reduce the mRNA levels of IL-1b and IL-6 in murine bone marrow-derived macrophages and uses a dilution technique to demonstrate that the number, but not the type of vesicles is responsible for this change in mRNA expression. It also compares the miRNA levels in constitutively-released vesicles with those released by high-intensity ultrasound.

Strengths:

The experiments are logically sequenced. It is very helpful to see assessment of the viability of the preparations.<br /> The results are presented fairly clearly and the statistical approach is described. The findings are reasonably clear and the writing is succinct.

Weaknesses:

The work is quite limited in scope and of limited novelty, largely recapitulating work from the first-named author's own recent publications.<br /> Thus, perhaps the most significant weakness of this study is that it makes claims of mechanisms, or of clinical or therapeutic relevance, that are not supported or even addressed by the study.

The aspects of the current work which are novel are hard to identify because the statement of aims is too broad and therefore encapsulates previous work. In addition, the introduction and discussion are vague and fail, for example, to mention the cell types used in the previous studies that are quoted. This means that it is not obvious from the Introduction whether the present study is at all novel.

The size of the study is quite small, with most experiments employing n = 4. This inevitably means that, for example, there is no significant effect of the lower power levels of ultrasound despite shifts in the mean values that might be of interest. Thus, the study appears underpowered. This problem is compounded by a failure to use appropriate analysis methods in the studies looking at dose-responses, where a regression analysis might be more appropriate than multiple individual t-tests / ANOVA.

The assessment of the role of Ca2+ is important but incomplete. Measurement of whole-cell Ca2+ levels is not really a substitute for measuring cytosolic Ca2+ as cell volume changes and sarcoplasmic reticulum Ca2+ changes would greatly influence the possible meaning of the findings. Furthermore, a statement that Ca2+ increase causes the vesicle release could only be supported by experiments that increase intracellular Ca2+, such as the use of a Ca2+ ionophore.

mRNA expression levels of IL-1b and IL-6 are reported. There should also be a report of a non-inflammatory mRNA to act as a control.

Reviewer #1 (Public Review):

Summary:

The authors embarked on a journey to understand the mechanisms and intensity-dependency of ultrasound (US)-induced extracellular vesicle (EV) release from myotubes and the potential anti-inflammatory effects of these EVs on macrophages. This study builds on their prior work from 2021 that initially reported US-induced EV secretion.

Strengths:

1. The finding that US-treated myotube EVs can suppress macrophage inflammatory responses is particularly intriguing, hinting at potential therapeutic avenues in inflammation modulation.

Weaknesses:

1. The exploration of output parameters for US induction appears limited, with only three different output powers (intensities) tested, thus narrowing the scope of their findings.<br /> 2. Their claim of elucidating mechanisms seems to be only partially met, with a predominant focus on the correlation between calcium responses and EV release.<br /> 3. While the intracellular calcium response is a dynamic activity, the method used to measure it could risk a loss of kinetic information.<br /> 4. The inclusion of miRNA sequencing is commendable; however, the interpretation of this data fails to draw clear conclusions, diminishing the impact of this segment.

While the authors have shown the anti-inflammatory effects of US-induced EVs on macrophages, there are gaps in the comprehensive understanding of the mechanisms underlying US-induced EV release. Certain aspects, like the calcium response and the utility of miRNA sequencing, were not fully explored to their potential. Therefore, while the study establishes some findings, it leaves other aspects only partially substantiated.

Reviewer #2 (Public Review):

The flowering plant Capsella bursa-pastoris is an allotetraploid formed from the genomes of Capsella orientalis and Capsella grandiflora. An outstanding question in the evolution of allotetraploids is the relative contribution of immediate consequences of allopolyploidization vs. long-term evolution after the event. The authors address this question by re-synthesizing the allotetraploid in the lab using the two progenitor species, and comparing its phenotypic and gene expression variation to naturally occurring C. bursa-pastoris. They find evidence primarily for long-term phenotypic evolution towards a selfing syndrome in C. bursa-pastoris, and a combination of short and long-term changes to gene expression.

The manuscript is thorough and provides lots of new insights into the mechanisms driving evolution in allopolyploids. I especially appreciated the detailed examination of different mechanisms driving gene expression variation. There are some important limitations of the experimental design related to independent evolution of the progenitor species and effects of the colchicine treatment used to induce polyploidy, but these are well-addressed in the Discussion.

Reviewer #1 (Public Review):

This study aims to determine the relative importance of the immediate effects of allopolyploidization from subsequent evolution in phenotypic traits associated with the selfing syndrome and in gene expression traits in the selfing allopolyploid Capsella bursa-pastoris and its diploid progenitors Capsella grandiflora, which is outcrossing, and Capsella orientalis, which is selfing. To do this, they compared five categories of plant: the two progenitors of the allopolyploid, hybrids resynthesized from the progenitors with a whole-genome duplication either before or after the hybridization event, and the naturally occurring allopolyploid.

Two lines of evidence were used: phenotypic data from the plants grown in a common environment, and RNAseq data from a subset of the plants.

The phenotypic data indicate that the selfing syndrome of C. bursa-pastoris likely evolved after the initial allopolyploidization event, and that pollen and seed viability recovered following the allopolyploidization event. The results are compelling but would benefit from small clarifications to the methods and statistics to account for possible positional effects in the growth chamber. Using a linear mixed model rather than a simple ANOVA would solve this problem.

The RNAseq data are used to explore overall expression patterns (using multi-dimensional scaling), patterns of differential expression (additive, dominant, or transgressive), and homeolog expression bias, and to determine the relative contributions of the original allopolyploidization event and subsequent evolution. Statistical cutoffs were used to categorize gene expression patterns, but the description and categorization of these patterns appears to have been largely qualitative, and might be strengthened by including more statistical detail in questions like whether homeologous expression bias did indeed show more variation in resynthesized and evolved allopolyploids.

The study includes evidence that homeolog expression bias (overrepresentation of an allele from one species) results in part from homeologous synapsis (uneven inheritance of chromosome segments). These deviations from patterns consistent with 2:2 inheritance of genomic regions are highly variable between individuals in resynthesized allopolyploids but appeared to be mostly consistent within (but not between) populations in natural C. bursa-pastoris. This is intriguing evidence that segregation can be an important source of variation in allopolyploids. However, it was limited by the difficulty of inferring homeologous recombination breakpoints with RNAseq data because of the scale of recombination in wild populations (rather than resynthesized allopolyploids). In future identifying such breakpoints will be an interesting direction for this and other allopolyploid systems.

This research suggests many follow-up questions. In particular, it may be possible to identify evidence about the mechanism of the original hybridization event. How frequently do unreduced gametes occur in these species, and is it likely that C. bursa-pastoris evolved via a triploid bridge? Exploring the viability, fertility, and phenotypes of triploids produced in both directions could be a valuable future direction.

Future research, or the current study, could also valuably explore what kinds of genes experienced what forms of expression evolution. A brief description of GO terms frequently represented in genes which showed strong patterns of expression evolution might be suggestive of which selective pressures led to the changes in expression in the C. bursa-pastoris lineage, and to what extent they related to adaptation to polyploidization (e.g. cell-cycle regulators), compensating for the initial pollen and seed inviability or adapting to selfing (endosperm- or pollen-specific genes), or adaptation to abiotic conditions.

Overall, this is an interesting and valuable contribution to the field's understanding of how expression evolves in interaction with hybridization and polyploidy. Particularly in combination with the team's previous study on these lines, this experimental design is effective for separating the contributions of hybridization, WGD, and evolution over time.

Update: the authors have thoughtfully and thoroughly updated the manuscript to address all the questions I raised. I appreciate the chance to review this valuable contribution to the scientific literature.

Reviewer #1 (Public Review):

In this study, Li et al., report that FBXO24 contributes to sperm development by modulating alternative mRNA splicing and MIWI degradation during spermiogenesis. The authors demonstrated that FBXO24 deficiency impairs sperm head formation, midpiece compartmentalization, and axonemal/peri-axonemal organization in mature sperm, which causes sperm motility defects and male infertility. In addition, FBXO24 interacts with various mRNA splicing factors, which causes altered splicing events in Fbxo24-null round spermatids. Interestingly, FBXO24 also modulates MIWI levels via its polyubiquitination in round spermatids. Thus, the authors address that FBXO24 modulates global mRNA levels by regulating piRNA-mediated MIWI function and splicing events in testicular haploid germ cells.

This study is performed with various experimental approaches to explore and elucidate underlying molecular mechanisms for the FBXO24-mediated sperm defects during germ cell development. Overall, the experiments were designed properly and performed well to support the authors' observation in each part. In addition, the finding in this study is useful for understanding the physiological and developmental significance of the FBXO24 in the male germ line, which can provide insight into impaired sperm development and male infertility. However, there are several concerns to be explained more in this study. In addition, some results should be revised and updated.

Reviewer #3 (Public Review):

This work is carried out by the research group led by Shuiqiao Yuan, who has a long interest in and significant contribution to the field of male germ cell development. The authors study a protein for which limited information existed prior to this work, a component of the E3 ubiquitin ligase complex, FBXO24. The authors generated the first FBXO24 KO mouse model reported in the literature using CRISPR, which they complement with HA-tagged FBXO24 transgenic model in the KO background. The authors begin their study with a very careful examination of the expression pattern of the FBXO24 gene at the level of mRNA and the HA-tagged transgene, and they provide conclusive evidence that the protein is expressed exclusively in the mouse testis and specifically in post-meiotic spermatids of stages VI to IX, which include early stages of spermatid elongation and nuclear condensation. The authors report a fully sterile phenotype for male mice, while female mice are normal. Interestingly, the testis size and the populations of spermatogenic cells in the KO mutant mice show a small (but significant) reduction compared to the WT testis. Importantly, the mature sperm from KO animals show a series of defects that were very thoroughly documented in this work by scanning and transmission electron microscopy; this data constitutes a very strong point in this paper. FBXO24 KO sperm have severe defects in the mitochondrial sheath with missing mitochondria near the annulus, and missing outer dense fibers. Collectively these defects cause abnormal bending of the flagellum and severely reduced sperm motility. Moreover, defects in nuclear condensation are observed with faint nuclear staining of elongating and elongated spermatids, and reduction of protein levels of protamine 2 combined with increased levels of histones and transition protein 1. All of the above are in line with the observed male sterility phenotype.

The authors also performed RNAseq in the KO animal, and found profound changes in the abundance of thousands of mRNAs; and changes in mRNA splicing patterns as well. The data reveal deeply affected gene expression patterns in the FBXO24 KO testis, which further supports the essential role that this factor serves in spermiogenesis. Unfortunately, a molecular explanation of what causes these changes is missing; it is still possible that they are an indirect consequence of the KO and not directly caused by the KO.

A well-reasoned narrative on if and how the absence of FBXO24 as an E3 ubiquitin ligase is responsible for the observed mRNA and protein differential expression is missing. If FBXO24-mediated ubiquitination is required for normal protein degradation during spermiogenesis, protein level increase should be the direct consequence of genuine FBXO24 targets in the KO testis. Importantly, besides the Miwi ubiquitination experiment which is performed in a heterologous and therefore may not be ideal for extracting conclusions, the possible involvement of ubiquitination was not shown for any other proteins that the authors found that interact with FBXO24. For example splicing factors SRSF2, SRSF3, SRSF9, or any of the other proteins whose levels were found to be changed (reduced, thus the change in the KO is less likely due to the absence of ubiquitination) such as ODF2, AKAP3, TSSK4, PHF7, TSSK6, and RNF8. Interestingly, the authors do observe increased amounts of histones and transition proteins, but reduced amounts of protamines, which directly shows that histone to protamine transition is indeed affected in the FBXO24 KO testis, and is in agreement with the observed less condensed nuclei of spermatozoa. Could histones and transition proteins be targets of the proposed ubiquitin ligase activity of FBXO24, and in its absence, histone replacement is abrogated? Providing experimental evidence to address this possibility would greatly expand our understanding of why FBXO24 is essential during spermiogenesis.

Regarding the results on Miwi protein and piRNAs, the following remarks can be made:

The finding that the Miwi protein is upregulated is an important point in this work, and it is in agreement with the observed increased size of the chromatoid body, where most of the Miwi protein is accumulated in round spermatids. This finding needs to be further supported and verified with experiments done in WT and KO mice. Miwi should be immunoprecipitated and Miwi ubiquitination should be detected (with WB or mass spec) in WT testis. It should be expected that Miwi ubiquitination is reduced in KO testis. The experiments that the authors performed in HEK293T cells are informative but experiments with tissue/cells normally expressing Miwi and FBXO24 are missing. With regard to piRNA expression, it is an exaggeration to call the observed increase in piRNA expression remarkable, especially since one replicate small RNA library per condition was sequenced. Although the library is constructed from total small RNA (which includes Mili-bound piRNAs as well), it does seem that the upregulated piRNAs are Miwi-bound piRNAs because the size of the upregulated piRNAs is mostly 29-32 bases. However, the direct comparison of the number of upregulated piRNAs with upregulated miRNAs is not in support of the claim that the increase in piRNA expression is higher compared to miRNAs: there are approximately a few hundred miRNAs expressed in mice, but hundreds of thousands of different piRNA sequences, so upregulation of ~10 times more piRNA species than miRNAs is a smaller proportional increase. Moreover, the observed increase in the overall piRNA levels could be just an epiphenomenon of the increased abundance of the Miwi protein; it has been documented that Piwi proteins stabilize their piRNA cargo, so most likely the increase in iRNA levels in 29-32 nt sizes is probably not a result of altered biogenesis, but increased half-life of the piRNAs as a result of Miwi upregulation. Therefore, the claim that FBXO24 is essential for piRNA biogenesis/production (lines 308, 314) is not appropriately supported.

Reviewer #2 (Public Review):

Spermatogenesis is a process of cell differentiation necessary to produce fertile spermatozoa. It consists of three parts, the last of which is called spermiogenesis, in which the size, shape, and organelle composition of the spermatids undergo significant changes that result in the formation of fully elongated spermatozoa. Defects in spermatogenesis or spermiogenesis can lead to male infertility. In this study, Li et al. identified FBXO24 as a highly expressed protein in human and mouse testis that is required for modulating alternative gene splicing in round spermatids through interaction with various splicing factors. They also found that deletion of FBXO24 in mice results in disorganized mitochondrial packing along the midpiece of the tail and chromatoid body architecture, which may account for the observed male sterility. The authors discovered that FBXO24 interacts with the subunits of MIWI and SCF and is required for normal piRNA biogenesis.

The major strengths of the study are the rigorous phenotypic and molecular analysis by using two complementary animal models (knock-out mouse model but also HA-tagged transgenic mouse model) to pinpoint the protein levels and localization in time and space during normal spermatogenesis and when the protein is absent.

The minor weakness of the study is inconsistent use of terminology throughout the manuscript, occasional logic-jump in their flow, and missing detailed description in methodologies used either in the text or Materials and Methods section, which can be easily rectified.

Overall, this study highlights the relevance and importance of FBXO24 in male fertility and provides a better understanding of the MIWI/piRNA pathway, mitochondrial organization, and chromatin condensation in mouse spermatozoa during spermiogenesis.

Reviewer #1 (Public Review):

Summary:<br /> This paper examines patterns of diversity and divergence in two closely related sub-species of Zea mays. While the patterns are interesting, the strength of evidence in support of the conclusions drawn from these patterns is weak overall. Most of the main conclusions are not supported by convincing analyses.

Strengths:<br /> The paper presents interesting data from sets of sympatric populations of the two sub-species, maize and teosinte. This sampling offers unique insights into the diversity and divergence between the two, as well as the geographic structure of each.

Weaknesses:<br /> There were issues with many parts of the paper, especially with the strength of conclusions that can be drawn from the analyses. I list the major issues in the order in which they appear in the paper.

1. Gene flow and demography.<br /> The f4 tests of introgression (Figure 1E) are not independent of one another. So how should we interpret these: as gene flow everywhere, or just one event in an ancestral population? More importantly, almost all the significant points involve one population (Crucero Lagunitas), which suggests that the results do not simply represent gene flow between the sub-species. There was also no signal of increased migration between sympatric pairs of populations. Overall, the evidence for gene flow presented here is not convincing. Can some kind of supporting evidence be presented?

The paper also estimates demographic histories (changes in effective population sizes) for each population, and each sub-species together. The text (lines 191-194) says that "all histories estimated a bottleneck that started approximately 10 thousand generations ago" but I do not see this. Figure 2C (not 2E, as cited in the text) shows that teosinte had declines in all populations 10,000 generations ago, but some of these declines were very minimal. Maize has a similar pattern that started more recently, but the overall species history shows no change in effective size at all. There's not a lot of signal in these figures overall.

I am also curious: how does the demographic model inferred by mushi address inbreeding and homozygosity by descent (lines 197-202)? In other words, why does a change in Ne necessarily affect inbreeding, especially when all effective population sizes are above 10,000?

2. Proportion of adaptive mutations.<br /> The paper estimates alpha, the proportion of nonsynonymous substitutions fixed by positive selection, using two different sampling schemes for polymorphism. One uses range-wide polymorphism data and one uses each of the single populations. Because the estimates using these two approaches are similar, the authors conclude that there is little local adaptation. However, this conclusion is not justified.

There is little information as to how the McDonald-Kreitman test is carried out, but it appears that polymorphism within either teosinte or maize (using either sampling scheme) is compared to fixed differences with an outgroup. These species might be Z. luxurians or Z. diploperennis, as both are mentioned as outgroups. Regardless of which is used, this sampling means that almost all the fixed differences in the MK test will be along the ancestral branch leading to the ancestor of maize or teosinte, and on the branch leading to the outgroup. Therefore, it should not be surprising that alpha does not change based on the sampling scheme, as this should barely change the number of fixed differences (no numbers are reported).

The lack of differences in results has little to do with range-wide vs restricted adaptation, and much more to do with how MK tests are constructed. Should we expect an excess of fixed amino acid differences on very short internal branches of each sub-species tree? It makes sense that there is more variation in alpha in teosinte than maize, as these branches are longer, but they all seem quite short (it is hard to know precisely, as no Fst values or similar are reported).

3. Shared and private sweeps.<br /> In order to make biological inferences from the number of shared and private sweeps, there are a number of issues that must be addressed.

One issue is false negatives and false positives. If sweeps occur but are missed, then they will appear to be less shared than they really are. Table S3 reports very high false negative rates across much of the parameter space considered, but is not mentioned in the main text. How can we make strong conclusions about the scale of local adaptation given this? Conversely, while there is information about the false positive rate provided, this information doesn't tell us whether it's higher for population-specific events. It certainly seems likely that it would be. In either case, we should be cautious saying that some sweeps are "locally restricted" if they can be missed more than 85% of the time in a second population or falsely identified more than 25% of the time in a single population.

A second, opposite, issue is shared ancestral events. Maize populations are much more closely related than teosinte (Figure 2B). Because of this, a single, completed sweep in the ancestor of all populations could much more readily show a signal in multiple descendant populations. This is consistent with the data showing more shared events (and possibly more events overall). There also appear to be some very closely (phylogenetically) related teosinte populations. What if there's selection in their shared ancestor? For instance, Los Guajes and Palmar Chico are the two most closely related populations of teosinte and have the fewest unique sweeps (Figure 4B). How do these kinds of ancestrally shared selective events fit into the framework here?

These analyses of shared sweeps are followed by an analysis of sweeps shared by sympatric pairs of teosinte and maize. Because there are not more events shared by these pairs than expected, the paper concludes that geography and local environment are not important. But wouldn't it be better to test for shared sweeps according to the geographic proximity of populations of the same sub-species? A comparison of the two sub-species does not directly address the scale of adaptation of one organism to its environment, and therefore it is hard to know what to conclude from this analysis.

4. Convergent adaptation<br /> My biggest concern involves the apparent main conclusion of the paper about the sources of "convergent adaptations". I believe the authors are misapplying the method of Lee and Coop (2017), and have not seriously considered the confounding factors of this method as applied. I am unconvinced by the conclusions that are made from these analyses.

The method of Lee and Coop (referred to as rdmc) is intended to be applied to a single locus (or very tightly linked loci) that shows adaptation to the same environmental factor in different populations. From their paper: "Geographically separated populations can convergently adapt to the same selection pressure. Convergent evolution at the level of a gene may arise via three distinct modes." However, in the current paper, we are not considering such a restricted case. Instead, genome-wide scans for sweep regions have been made, without regard to similar selection pressures or to whether events are occurring in the same gene. Instead, the method is applied to large genomic regions not associated with known phenotypes or selective pressures.

I think the larger worry here is whether we are truly considering the "same gene" in these analyses. The methods applied here attempt to find shared sweep regions, not shared genes (or mutations). Even then, there are no details that I could find as to what constitutes a shared sweep. The only relevant text (lines 802-803) describes how a single region is called: "We merged outlier regions within 50,000 Kb of one another and treated as a single sweep region." (It probably doesn't mean "50,000 kb", which would be 50 million bases.) However, no information is given about how to identify overlap between populations or sub-species, nor how likely it is that the shared target of selection would be included in anything identified as a shared sweep. Is there a way to gauge whether we are truly identifying the same target of selection in two populations?

The question then is, what does rdmc conclude if we are simply looking at a region that happened to be a sweep in two populations, but was not due to shared selection or similar genes? There is little testing of this application here, especially its accuracy. Testing in Lee and Coop (2017) is all carried out assuming the location of the selected site is known, and even then there is quite a lot of difficulty distinguishing among several of the non-neutral models. This was especially true when standing variation was only polymorphic for a short time, as is estimated here for many cases, and would be confused for migration (see Lee and Coop 2017). Furthermore, the model of Lee and Coop (2017) does not seem to consider a completed ancestral sweep that has signals that persist into current populations (see point 3 above). How would rdmc interpret such a scenario?

Overall, there simply doesn't seem to be enough testing of this method, nor are many caveats raised in relation to the strange distributions of standing variation times (bimodal) or migration rates (opposite between maize and teosinte). It is not clear what inferences can be made with confidence, and certainly the Discussion (and Abstract) makes conclusions about the spread of beneficial alleles via introgression that seem to outstrip the results.

Reviewer #2 (Public Review):

Summary:<br /> The authors sampled multiple populations of maize and teosinte across Mexico, aiming to characterise the geographic scale of local adaptation, patterns of selective sweeps, and modes of convergent evolution between populations and subspecies.

Strengths & Weaknesses:<br /> The population genomic methods are standard and appropriate, including Fst, Tajima's D, α, and selective sweep scans. The whole genome sequencing data seems high quality. However, limitations exist regarding limited sampling, potential high false-positive sweep detection rates, and weak evidence for some conclusions, like the role of migration in teosinte adaptation.

Aims & Conclusions:<br /> The results are interesting in supporting local adaptation at intermediate geographic scales, widespread convergence between populations, and standing variation/gene flow facilitating adaptation. However, more rigorous assessments of method performance would strengthen confidence. Connecting genetic patterns to phenotypic differences would also help validate associations with local adaptation.

Impact & Utility:<br /> This work provides some of the first genomic insights into local adaptation and convergence in maize and teosinte. However, the limited sampling and need for better method validation currently temper the utility and impact. Broader sampling and connecting results to phenotypes would make this a more impactful study and valuable resource. The population genomic data itself provides a helpful resource for the community.

Additional Context:<br /> Previous work has found population structure and phenotypic differences consistent with local adaptation in maize and teosinte. However, genomic insights have been lacking. This paper takes initial steps to characterise genomic patterns but is limited by sampling and validation. Additional work building on this foundation could contribute to understanding local adaptation in these agriculturally vital species.

Reviewer #2 (Public Review):

Summary:

The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

Strengths:

The study uses reliable and sharable/open data to demonstrate its findings, sharing as well the code for statistical analysis. The study provides sensitivity analysis for different scenarios of equivalence margin and alfa level, as well as for different scenarios of standard deviations for the prior of Bayes factors and different thresholds to consider. All analysis and code of the work is open and can be replicated. As well, the study demonstrates on a case-by-case basis how the different criteria can diverge, regarding one sample of a field of science: preclinical cancer biology. It also explains clearly what Bayes factors and equivalence tests are.

Weaknesses:

It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

Other comments:

- Introduction: The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

- Overall picture vs. case-by-case scenario: An interesting finding is that the authors observe that in most cases, there is no substantial evidence for either the absence or the presence of an effect, as evidenced by the equivalence tests. Thus, using both suggested criteria results in a picture similar to the one initially raised by the paper itself. The work done by the authors highlights additional criteria that can be used to further analyze replication success on a case-by-case basis, and I believe that this is where the paper's main contributions lie. Despite not changing the overall picture much, I agree that the p-value criterion by itself does not distinguish between (1) a situation where the original study had low statistical power, resulting in a highly inconclusive non-significant result that does not provide evidence for the absence of an effect and (2) a scenario where the original study was adequately powered, and a non-significant result may indeed provide some evidence for the absence of an effect when analyzed with appropriate methods. Equivalence testing and Bayesian factor approaches are valuable tools in both cases.

Regarding the 0.05 threshold, the choice of the prior distribution for the SMD under the alternative 𝐻1 is debatable, and this also applies to the equivalence margin. Sensitivity analyses, as highlighted by the authors, are helpful in these scenarios.

Reviewer #3 (Public Review):

Summary:

The paper points out that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. Also, it can not be considered a "replication success". The main point of the paper is rather obvious. It may be that both studies are underpowered, in which case their non-significance does not prove anything. The absence of evidence is not evidence of absence! On the other hand, statistical significance is a confusing concept for many, so some extra clarification is always welcome.

One might wonder if the problem that the paper addresses is really a big issue. The authors point to the "Reproducibility Project: Cancer Biology" (RPCB, Errington et al., 2021). They criticize Errington et al. because they "explicitly defined null results in both the original and the replication study as a criterion for replication success." This is true in a literal sense, but it is also a little bit uncharitable. Errington et al. assessed replication success of "null results" with respect to 5 criteria, just one of which was statistical (non-)significance.

It is very hard to decide if a replication was "successful" or not. After all, the original significant result could have been a false positive, and the original null-result a false negative. In light of these difficulties, I found the paper of Errington et al. quite balanced and thoughtful. Replication has been called "the cornerstone of science" but it turns out that it's actually very difficult to define "replication success". I find the paper of Pawel, Heyard, Micheloud, and Held to be a useful addition to the discussion.

Strengths:

This is a clearly written paper that is a useful addition to the important discussion of what constitutes a successful replication.

Weaknesses:

To me, it seems rather obvious that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. I'm not sure how often this mistake is made.

Joint Public Review:

Summary:<br /> The study "Effect of alpha-tubulin acetylation on the doublet microtubule structure" by S. Yang et al employs a multi-disciplinary approach, including cryo-electron microscopy (cryo-EM), molecular dynamics, and mass spectrometry, to investigate the impact of α-tubulin acetylation at the lysine 40 residue (αK40) on the structure and stability of doublet microtubules in cilia. The work reveals that αK40 acetylation exerts a small-scale, but significant, effect by influencing the lateral rotational angle of the microtubules, thereby affecting their stability. Additionally, the study provided an explanation of the relationship between αK40 acetylation and phosphorylation within cilia, despite that the details still remain elusive. Overall, these findings contribute to our understanding of how post-translational modifications can influence the structure, composition, stability, and functional properties of important cellular components like cilia.

Strengths:<br /> 1. Multi-Disciplinary Approach: The study employs a robust combination of cryo-electron microscopy (cryo-EM), molecular dynamics, and mass spectrometry, providing a comprehensive analysis of the subject matter.<br /> 2. Significant Findings: The paper successfully demonstrates the impact of αK40 acetylation on the lateral rotational angles between protofilaments (inter-PF angles) of doublet microtubules in cilia, thereby affecting their stability. This adds valuable insights into the role of post-translational modifications in cellular components.<br /> 3. Exploration of Acetylation-Phosphorylation Relationship: The study also delves into the relationship between αK40 acetylation and phosphorylation within cilia, contributing to a broader understanding of post-translational modifications.<br /> 4. High-quality data: The authors are cryo-EM experts in the field and the data quality presented in the manuscript is excellent.<br /> 5. Depth of analysis: The authors analyzed the effects of αK40 acetylation in excellent depth which significantly improved our understanding of this system.

Weaknesses:<br /> I have no major concerns about this paper, but would recommend that a few minor issues be addressed.

1. Lack of Statistical Details: The review points out that the paper could benefit from providing more statistical details, such as the number of particles and maps used for analysis, randomization methods, and dataset splitting for statistical analyses.<br /> 2. Questionable Conclusion Regarding MIPs: The reviewer suggests caution in the paper's conclusion that "Acetylation of αK40 does not affect tubulin and MIPs." The reviewer recommends that this conclusion be more specific or supported by additional evidence to exclude all other possibilities.<br /> 3. Need for Additional Visual Data: The reviewer recommends that an enlarged local density map along with fitted PDB models be provided in a supplementary figure, such as Figure 4.

Overall, the paper is strong in its scientific approach and findings but could benefit from additional statistical rigor and clarification of certain conclusions.

Reviewer #1 (Public Review):

Summary: The paper by McGinnis et al. uses a combination of genetic and biochemical approaches to understand how the conserved 5'-3' RNA exonuclease Xrn1 affects autophagy in response to methionine starvation in S. cerevisiae. The authors present evidence Xrn1 affects autophagy primarily via its effect on regulating TORC1 signaling. They present some evidence that Xrn1's effect on TORC1 singnaling is via its physical interaction with the SEACIT complex.

Strengths: The experiments in general for this paper are clear and have proper controls.

Weaknesses:<br /> The authors seem to try and fit the data to a simplistic model rather than embrace the complexity of the data. I will give some examples below.

1) Figure 1 clearly shows that xrn1d results in loss of tight repression of autophagy. Specifically, the 0 timepoint has increased autophagy in both the idh-GFP and ALP assays. However, it is incorrect to say that it is related in any way to methionine deprivation. The same basic pattern of regulation occurs in WT and xrn1d strains. The only difference is the "leakiness" of repression at t=0.

2) Figure 2 shows that catalytically inactive Xrn1 has the same autophagy phenotype as a deletion, indicating that Xrn1 enzymatic activity is important for function. However, it is also clear that xrn1-deletion cells expressing wt Xm1-flag do not repress autophagy as well as XRN+ cells, even though the amount of expressed protein seems similar. Does this imply the flag-tag may be a less active version of the protein? This should be discussed.

3) Figure 3 shows Xrn1-loss effects TORC signaling and that npr2-deletion inhibits autophagy. The surprising result is that a xrn1d/npr2d behaves like WT with regards to autophagy. This needs to be discussed. To me, this seems to strongly suggest that methionine repression of autophagy is occurring downstream of both xrn1 and npr2. Measuring p-S6 in the double mutant may be informative.

4) Figure 4 appears to show that even in the absence of GTR1, autophagy is repressed in rich media, active in YPL-SL, but still responds to methionine repression. This does not seem consistent with the model presented in Figure 5. Shouldn't loss of GTR1 result in repressed Torc1? The GTP and GDP-lock mutants are either all on, or all off. Why is deletion different? This needs to be explained and discussed. Also, the Figure legend does not match figures (problem after Fig4b).

5) Figure 5B shows GTR1 IP with Xrn1-FLAG. However, there are no negative controls in this experiment, so the result could be background. RNAaseA and RNA addition experiments are convincing.

6) Line 254-255. The lead sentence is simply not supported by the data. There is no evidence that Xrn1 actually affects the regulation of Gtr1/2 binding states.

7) Line 259-260. This is again overstated. Just because a mutant can be rescued by Gtr1-GTP-locked, does not say anything about RNA decay. In fact, the double mutant has extra high levels of some ATG RNA's, so I have no idea how the Gtr1 rescues.

8) Line 268-281. Your model here ignores the fact that methionine regulation takes place in the absence of both xrn1 and npr2. Therefore the model, as proposed, can't be correct.

9) Line 290-300. The slow growth rate of Xrn1 mutants may be affecting the metabolite levels. I felt that this entire paragraph was overly speculative.

Reviewer #2 (Public Review):

Summary:<br /> McGinnis and colleagues conducted a study to elucidate the precise mechanism through which SEACIT detects amino acids and regulates TORC1 signaling in yeast. In their research, the authors made a noteworthy discovery by identifying the conserved 5'-3' RNA exonuclease Xrn1 as a novel regulator of TORC1 activity, particularly in response to stress-induced autophagy. The study revealed that the impact of Xrn1 on TORC1 is contingent on its catalytic activity rather than the degradation of any specific category of mRNAs. Instead, Xrn1 plays a pivotal role in modulating the nucleotide-binding state of the Gtr1/2 complex. This modulation is crucial for the complex's interaction with and subsequent activation of TORC1.

Strengths:<br /> This study holds considerable potential as it illuminates an intriguing function of Xrn1 in nutrient sensing and growth control, expanding beyond its conventional role in RNA degradation. Furthermore, the research suggests a novel pathway through which RNA metabolism can influence methionine signaling to activate TORC1.

Weaknesses/General comments:<br /> 1) Previous work has shown that SAMTOR, upstream of mTORC1 in mammalian cells, senses methionine abundance through SAM levels (PMID: 29123071). However, this study suggests that Xrn1 senses and signals methionine to regulate mTORC1 signaling independently of SAM abundance. This finding appears to contradict the mentioned previous work. The authors should address this discrepancy. Moreover, the title of this manuscript does not seem to fit with actual findings. In the title, the authors mention that Xrn1 regulates TORC1 in response to SAM availability, but SAM levels do not seem to matter for Xrn1-dependent regulation of autophagy and TORC1.<br /> 2) This group has previously shown that the addition of methionine stimulates the synthesis of S-adenosylmethionine (SAM), which inhibits autophagy and promotes growth through the action of the methyltransferase Ppm1p, which modifies the catalytic subunit of PP2A in tune with SAM levels (PMID: 23870128). Since Xrn1 controls autophagy in a methionine-dependent manner, the authors should assess the effects of Xrn1 on SAM-dependent methylation of PP2A?<br /> 3) The authors should measure the effects of Xrn1 and TORC1 regulation on the methionine-SAM cycle activity through an isotope tracing approach, possibly by using U-13C-methionine.<br /> 4) The authors use mainly the GFP cleavage assay from Idh1-GFP to assess mitochondria degradation (or mitophagy) and generalize that autophagy is induced. Other assays should be employed more notably to assess globally non-mitochondrial specific degradation. For example, the authors could employ the Pho8∆60 assay.<br /> 5) In several blots (Panel 3D, 4D, 4B, 4F), the authors assess autophagy through GFP cleavage from Idh1-GFP but do not assess TORC1 activity in the same conditions. Showing autophagy induction and TORC1 activity on the same panels would be preferable.

Specific comments:<br /> 1) Panel 5E: As a control, the authors should use DNA instead of NMPs.<br /> 2) Panel S3B: Contrary to what is indicated in the text, this panel does not display ATG mRNA levels.<br /> 3) Panel S5K is not cited in the text. The rationale behind measuring the steady-state levels of GTP and GDP is not explained.<br /> Several panels are not subjected to statistical analysis. It is important for the authors to ensure that appropriate statistical methods are applied.

Reviewer #3 (Public Review):

Summary<br /> This study investigated the role of the exonuclease Xrn1 in regulating autophagy in response to methionine deprivation in the budding yeast (S. cerevisiae). As a model system, wild-type and xrn1-deletion cells are switched from a nutrient-rich, lactate-based media (YPL) to a synthetic, minimal, lactate media with or without re-addition of methionine. Autophagy is measured by a previously reported Idh-GFP cleavage assay, and in some cases by quantification of alkaline phosphatase activity. The authors conclude that Xrn1 suppresses autophagy in response to methionine depletion based on the results of the Idh-GFP assay. However, the alkaline phosphatase assay could potentially suggest the opposite conclusion, with xnr1 deletion blocking the induction of autophagy relative to baseline in those cells, an interpretation which is complicated by higher basal autophagy induction upon xnr1 deletion. To address the mechanism of Xrn1 regulation of autophagy, a model is presented in which Xrn1 activates Target of Rapamycin Complex 1 (TORC1), which suppresses autophagy. This regulation is proposed to occur through physical association of Xrn1 with known upstream regulators of TORC1 activity, the SEACIT/GATOR1 and Gtr/Rag complexes. However, TORC1 activity is not measured under many key experimental conditions, making it difficult to determine the accuracy of this model. If the model ultimately proves correct, this would be an important finding that establishes a new player in the critical TORC1 pathway that controls cell growth and metabolism in response to changes in nutrient availability.

Strengths<br /> Clear and highly reproducible results using the Idh-GFP cleavage assay to measure apoptosis.

Detailed characterization of the metabolic and transcriptomic effects of Xrn1 deletion through metabolomics and RNA-seq.

Use of a catalytically inactive Xrn1 mutant to demonstrate that its effects on autophagy require its catalytic activity.

Weaknesses<br /> Predominant use of a single autophagy assay (Idh-GFP cleavage), with potentially conflicting results in another assay (alkaline phosphatase activity).

TORC1 activity is not measured under many key experimental conditions.

Protein-protein interactions are studied by overexpression of tagged proteins. While this may be essential for detection, the level of overexpression relative to endogenous protein is unclear, as well as whether this recapitulates the endogenous interactions and regulation.

Results from some experiments have several possible interpretations.

Reviewer #1 (Public Review):

Summary:<br /> Cyclic Nucleotide Binding (CNB) domains are pervasive structural components involved in signaling pathways across eukaryotes and prokaryotes. Despite their similar structures, CNB domains exhibit distinct ligand-sensing capabilities. The manuscript offers a thorough and convincing investigation that clarifies numerous puzzling aspects of nucleotide binding in Trypanosoma.

Strengths:<br /> One of the strengths of this study is its multifaceted methodology, which includes a range of techniques including crystallography, ITC (Isothermal Titration Calorimetry), fluorimetry, CD (Circular Dichroism) spectroscopy, mass spectrometry, and computational analysis. This interdisciplinary approach not only enhances the depth of the investigation but also offers a robust cross-validation of the results.

Weaknesses:<br /> None noticed.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript clearly shows that Trypanosoma PKA is controlled by nucleoside analogues rather than cyclic nucleotides, which are the primary allosteric effectors of human PKA and PKG. The authors demonstrate that the inosine, guanosine, and adenosine nucleosides bind with high affinity and activate PKA in the tropical pathogens T. brucei, T. cruzi and Leishmania. The underlying determinants of nucleoside binding and selectivity are dissected by solving the crystal structure of T. cruzi PKAR(200-503) and T. brucei PKAR(199-499) bound to inosine at 1.4 Å and 2.1 Å resolution and through comparative mutational analyses. Of particular interest is the identification of a minimal subset of 2-3 residues that controls nucleoside vs. cyclic nucleotide specificity.

Strengths:<br /> The significance of this study lies not only in the structure-activity relationships revealed for important targets in several parasite pathogens but also in the understanding of CNB's evolutionary role.

Weaknesses:<br /> The main missing piece is the model for activation of the kinetoplastid PKA which remains speculative in the absence of a structure for the trypanosomatid PKA holoenzyme complex. However, this appears to be beyond the scope of this manuscript, which is already quite dense.

Reviewer #1 (Public Review):

Summary:<br /> This study aims to further resolve the history of speciation and introgression in Heliconius butterflies. The authors break the data into various partitions and test evolutionary hypotheses using the Bayesian software BPP, which is based on the multispecies coalescent model with introgression. By synthesizing these various analyses, the study pieces together an updated history of Heliconius, including a multitude of introgression events and the sharing of chromosomal inversions.

Strengths:

Full-likelihood methods for estimating introgression can be very computationally expensive, making them challenging to apply to datasets containing many species. This study provides a great example of how to apply these approaches by breaking the data down into a series of smaller inference problems and then piecing the results together. On the empirical side, it further resolves the history of a genus with a famously complex history of speciation and introgression, continuing its role as a great model system for studying the evolutionary consequences of introgression. This is highlighted by a nice Discussion section on the implications of the paper's findings for the evolution of pollen feeding.

Weaknesses:

The analyses in this study make use of a single method, BPP. The analyses are quite thorough so this is okay in my view from a methodological standpoint, but given this singularity, more attention should be paid to the weaknesses of this particular approach. Additionally, little attention is paid to comparable methods such as PhyloNet and their strengths and weaknesses in the Introduction or Discussion. BPP reduces computational burden by fixing certain aspects of the parameter space, such as the species tree topology or set of proposed introgression events. While this approach is statistically powerful, it requires users to make informed choices about which models to test, and these choices can have downstream consequences for subsequent analyses. It also might not be as applicable to systems outside of Heliconius where less previous information is available about the history of speciation and introgression. In general, it is likely that most modelling decisions made in the study are justified, but more attention should be paid to how these decisions are made and what the consequences of them could be, including alternative models.

• Co-estimating histories of speciation and introgression remains computationally challenging. To circumvent this in the study, the authors first estimate the history of speciation assuming no gene flow in BPP. While this approach should be robust to incomplete lineage sorting and gene tree estimation, it is still vulnerable to gene flow. This could result in a circular problem where gene flow causes the wrong species tree to be estimated, causing the true species tree to be estimated as a gene flow event. This is a flaw that this approach shares with summary-statistic approaches like the D-statistic, which also require an a-priori species tree. Enrichment of particular topologies on the Z chromosome helps resolve the true history in this particular case, but not all datasets will have sex chromosomes or chromosome-level assemblies to test against.

• The a-priori specification of network models necessarily means that potentially better-fitting models to the data don't get explored. Models containing introgression events are proposed here based on parsimony to explain patterns in gene tree frequencies. This is a reasonable and common assumption, but parsimony is not always the best explanation for a dataset, as we often see with phylogenetic inference. In general, there are no rigorous approaches to estimating the best-fitting number of introgression events in a dataset. Likewise, the study estimates both pulse and continuous introgression models for certain partitions, though there is no rigorous way to assess which of these describes the data better.

• Some aspects of the analyses involving inversions warrant additional consideration. Fewer loci were able to be identified in inverted regions, and such regions also often have reduced rates of recombination. I wonder if this might make inferences of the history of inverted regions vulnerable to the effects of incomplete lineage sorting, even when fitting the MSC model, due to a small # of truly genealogically independent loci. Additionally, there are several models where introgression events are proposed to explain the loss of segregating inversions in certain species. It is not clear why these scenarios should be proposed over those in which the inversion is lost simply due to drift or selection.

Reviewer #2 (Public Review):

Thawornwattana et al. reconstruct a species tree of the genus Heliconius using the full-likelihood multispecies coalescent, an exciting approach for genera with a history of extensive gene flow and introgression. With this, they obtain a species tree with H. aoede as the earliest diverging lineage, in sync with ecological and morphological characters. They also add resolution to the species relationships of the melpomene-silvaniform clade and quantify introgression events. Finally, they trace the origins of an inversion on chromosome 15 that exists as a polymorphism in H. numata, but is fixed in other species. Overall, obtaining better species tree resolutions and estimates of gene flow in groups with extensive histories of hybridization and introgression is an exciting avenue. Being able to control for ILS and get estimates between sister species are excellent perks. One overall quibble is that the paper seems to be best suited to a Heliconius audience, where past trees are easily recalled, or members of the different clades are well known.

Overall, applying approaches such as these to gain greater insight into species relationships with extensive gene flow could be of interest to many researchers.

Reviewer #3 (Public Review):

The authors use a full-likelihood multispecies coalescent (MSC) approach to identify major introgression events throughout the radiation of Heliconius butterflies, thereby improving estimates of the phylogeny. First, the authors conclude that H. aoede is the likely outgroup relative to other Heliconius species; miocene introgression into the ancestor of H. aoede makes it appear to branch later. Topologies at most loci were not concordant with this scenario, though 'aoede-early' topologies were enriched in regions of the genome where interspecific introgression is expected to be reduced: the Z chromosome and larger autosomes. The revised phylogeny is interesting because it would mean that no extant Heliconius species has reverted to a non-pollen-feeding ancestral state. Second, the authors focus on a particularly challenging clade in which ancient and ongoing gene flow is extensive, concluding that silvaniform species are not monophyletic. Building on these results, a third set of analyses investigates the origin of the P1 inversion, which harbours multiple wing patterning loci, and which is maintained as a balanced polymorphism in H. numata. The authors present data supporting a new scenario in which P1 arises in H. numata or its ancestor and is introduced to the ancestor of H. pardilinus and H. elevatus - introgression in the opposite direction to what has previously been proposed using a smaller set of taxa and different methods.

The analyses were extensive and methodologically sound. Care was taken to control for potential sources of error arising from incorrect genotype calls and the choice of a reference genome. The argument for H. aoede as the earliest-diverging Heliconius lineage was compelling, and analyses of the melpomene-silvaniform clade were thorough.

The authors have demonstrated the strengths of a full-likelihood MSC approach when reconstructing the evolutionary history of "difficult" clade. This approach, however, can quickly become intractable in large species complexes where there is extensive gene flow or significant shifts in population size. In such cases, there may be hundreds of potentially important parameters to estimate, and alternate introgression scenarios may be impossible to disentangle. This is particularly challenging in systems unlike Heliconius, where fewer data are available and there is little a priori knowledge of reproductive isolation, genome evolution, and the unique life history traits of each species.

Joint Public Review:

Summary: Two early Cambrian taxa of linguliform brachiopods are assigned to the family Eoobolidae. The taxa exhibit a columnar shell structure and the phylogenetic implications of this shell structure in relation to other early Cambrian families is discussed.

Strengths: Interesting idea regarding the evolution of shell structure.

Weaknesses: The early record of shell structures of linguliform brachiopods is incomplete and partly contradictory. The authors maintain silence regarding contradictory information throughout the article to an extent that information is cited wrongly. The article is written under the assumption that all eoobolids have a columnar shell structure. Thus, the previously claimed columnar structure of Eoobolus incipiens which has been re-illustrated in the paper is not convincing and could be interpreted in other ways.

The article needs a proper results section. The Discussion is mainly a review of published data. Other potential results are hidden in this "discussion". In addition, a more elaborate Methods section is needed in which it is explained how the data for shell thicknesses and numbers of laminae was obtained.

A critical revision of the family Eoobolidae and Lingulellotretidae including a revision of the type species of Eoobolus and Lingulellotreta is needed.

The potential evolutionary patterns that are discussed towards the end (summarized in Fig 6) are interesting but rather unconvincing as the way the data has been obtained has never been clarified. Shell thicknesses and numbers of laminae that built up the shell of several taxa are compared, but at no point it is stated where these measurements were taken. Shell thicknesses vary within a shell and also the presence of the never mentioned tertiary layer is modifying shell thicknesses. Hence, the presented data appears random and is not comparable. The obtained evolutionary patterns must be considered as dubious.

Reviewer #1 (Public Review):

Previous reports suggested an association between ceramide accumulation in skeletal muscle and disruption of insulin signaling and metabolic dysregulation. Mechanistically, however, how intracellular ceramide attenuates insulin action and reduces metabolism is not fully understood. It was suggested that insulin receptor (IR) signaling to PI3-K/AKT is inhibited by elevated intracellular ceramide. However, other studies failed to demonstrate an inhibitory effect of ceramide on PI3K/AKT. More recently, a study was published describing that intracellular localization of diacylglycerols and sphingolipids influences insulin sensitivity and mitochondrial function in human skeletal muscle (PMID: 29415895). In the present study, Diaz-Vegas and colleagues used an in vitro system to investigate this topic further and better understand how intracellular ceramide accumulation causes cellular insulin resistance and metabolic dysregulations in cultured myocytes.

The authors applied multiple methods to achieve this goal. Among these procedures are:

1. The overexpression of enzymes involved in mitochondrial ceramide synthesis and degradation;<br /> 2. Treatments of myocytes with different pharmacological tools to validate their findings;<br /> 3. Mitochondrial proteomics and lipidomics analyses.

The effects of these experimental conditions and treatment on intracellular lipids contents, mitochondrial functions, and insulin signaling in myocytes were then evaluated.

Findings:

The author's findings indicate that incubation of myocytes with palmitate increases mitochondrial ceramide and reduces the insulin-stimulated GLUT4-HA translocation to the myocyte surface without affecting AKT activation. The elevation in mitochondrial ceramide lowers the coenzyme Q levels e depletes the electron transport chain (ETC) components, impairing mitochondrial respiration. Such mitochondrial dysfunction appears to attenuate the translocation of GLUT4-HA to the plasma membrane of the L6-myotubule. Also, mitochondrial proteomic analysis revealed an association of insulin sensitivity with mitochondrial ceramide and ETC expression levels in human muscle.

Based on these findings, the authors propose a mechanism whereby the building up of ceramide inside mitochondria depletes CoQ and compromises mitochondrial respiratory complexes, raising ROS. The resulting mitochondrial dysfunction causes insulin resistance in cultured myocytes. They postulate that CoQ depletion links ceramides with insulin resistance and define the respirasome as a critical connection between ceramides and mitochondrial dysfunction.

Relevance and critiques:

This original study provides direct evidence that mitochondrial ceramide accumulation depletes CoQ and downregulates multiple ETC components in myocytes. Consequently, elevation in the levels of reactive oxygen species (ROS) and mitochondrial dysfunctions occur. The authors proposed that such mitochondrial dysregulation attenuates insulin-stimulated GLUT4 translocation to the plasma membrane of L6-myotubules. Moreover, mitochondrial ceramide accumulation does not affect insulin action on AKT activation.

Overall, this is a well-done study, showing that in obesity, elevated mitochondrial ceramide suppresses mitochondrial function and attenuates insulin action on glucose transporter GLUT4 translocation into the myocyte surface. The main conclusion is supported by the results presented. The study also applied multiple methods and described several experiments designed to test the author's central hypothesis.

Importantly, these new findings shed light on possible cellular mechanisms whereby ectopic fat deposition in skeletal muscle drives insulin resistance and metabolism dysregulation. The results demonstrating that alterations in mitochondrial ceramide are sufficient to attenuate insulin-stimulated GLUT4 trafficking in cultured myocytes are very interesting. Well-done.

Comments for further discussion and suggestions:

Although the author's results suggest that higher mitochondrial ceramide levels suppress cellular insulin sensitivity, they rely solely on a partial inhibition (i.e., 30%) of insulin-stimulated GLUT4-HA translocation in L6 myocytes. It would be critical to examine how much the increased mitochondrial ceramide would inhibit insulin-induced glucose uptake in myocytes using radiolabel deoxy-glucose.

Another important question to be addressed is whether glycogen synthesis is affected in myocytes under these experimental conditions. Results demonstrating reductions in insulin-stimulated glucose transport and glycogen synthesis in myocytes with dysfunctional mitochondria due to ceramide accumulation would further support the author's claim.

In addition, it would be critical to assess whether the increased mitochondrial ceramide and consequent lowering of energy levels affect all exocytic pathways in L6 myoblasts or just the GLUT4 trafficking. Is the secretory pathway also disrupted under these conditions?

Additional suggestions:

• Figure 1: How does increased mitochondrial ceramide affect fatty acid oxidation (FAO) in L6-myocytes? As the accumulation of mitochondrial ceramide inhibits respirasome and mitochondrial activity in vitro, can reduced FAO in vivo, due to high mitochondrial ceramide, accounts for ectopic lipid deposition in skeletal muscle of obese subjects?

• Figure 2: Although the authors show that mtSMPD5 overexpression does not affect ceramide abundance in whole cell lysate, it would be critical to examine the abundance of this lipid in other cellular membranes and organelles, particularly plasma membrane. What is the effect of mtSMPD5 overexpression on plasma membrane lipids composition? Does that affect GLUT4-containing vesicles fusion into the plasma membrane, possibly due to depletion of v-SNARE or tSNARE?

• Figure 4: One critical piece of information missing is the effect (if any) of mitochondrial ceramide accumulation on the mRNAs encoding the ETC components affected by this lipid. Although the ETC protein's lower stability may account for the effect of increased ceramide, transcriptional inhibition can't be ruled out without checking the mRNA expression levels for these ETC components.

In the revised version of their study, the authors nicely addressed all concerns previously raised. The amount of work that went into the revisions is appreciated. All weak points have been properly addressed, and the manuscript has improved substantially.

Reviewer #2 (Public Review):

Summary

The findings reported by Diaz-Vegas et al. extend those described in a previous paper from the same group establishing a role for mitochondrial CoQ depletion in the development of insulin resistance in muscle and adipose tissue (Fazakerley, 2018). In this new report, investigators sought to determine whether CoQ depletion contributes to insulin resistance caused by palmitate exposure and/or intracellular ceramide accumulation. To this end, researchers employed a widely used in vitro model of insulin resistance wherein L6 myocytes develop impaired Glut4 translocation upon exposure to palmitate (in this case, 150 uM for 16 hours). This model was combined with a variety of pharmacologic and genetic manipulations aimed at augmenting or inhibiting CoQ biosynthesis and/or ceramide biosynthesis, specifically in mitochondria. This series of experiments produced a valuable and provocative body of evidence positioning CoQ depletion downstream of mitochondrial ceramide accumulation and necessary for both palmitate- and ceramide-induced insulin resistance in L6 myocytes. Investigators concluded that mitochondrial ceramides, CoQ depletion and respiratory dysfunction are part of a core pathway leading to insulin resistance.

Strengths

The study provides exciting, first-time evidence linking palmitate-induced insulin resistance to ceramide accumulation within the mitochondria and subsequent depletion of CoQ. Ceramide accumulation specifically in mitochondria was found to be necessary and sufficient to cause insulin resistance in cultured L6 myocytes.

The in vitro experiments featured a set of mitochondrial-targeted genetic manipulations that permitted up/down-regulation of ceramide levels specifically in the mitochondrial compartment. Genetically induced mitochondrial ceramide accumulation led to CoQ depletion, which was accompanied by increased ROS production and diminution of ETC proteins and OXPHOS capacity and impaired insulin action, thereby establishing cause/effect.

Analysis of mitochondria isolated from human muscle biopsies obtained from individuals with disparate metabolic phenotypes revealed a positive correlation between complex I proteins and insulin sensitivity and a negative correlation with mitochondrial ceramide content. While it is likely that many factors contribute to these correlations, the results support the possibility that the ceramide/CoQ mechanism might be relevant to glucose control in humans.

Investigators were responsive to the reviewers' queries and critiques and performed additional experiments to bolster the interpretations and conclusions put forth in the manuscript. These included experiments to confirm that mito-targeted SMPD5 does not cause toxicity in L6 myocytes, and further studies using targeted metabolomic and lipidomic analyses to investigate the impact of ceramide depletion on CoQ levels in mice fed a high-fat diet and treated with P053 (a selective inhibitor of CerS1). The results were consistent with the in vitro findings.

Overall, these important findings offer valuable new insights into mechanisms that connect ceramides to insulin resistance and mitochondrial dysfunction, and could inform new therapeutic approaches towards improved glucose control.

Weaknesses

The mechanistic aspect of the work and conclusions put forth rely heavily on studies performed in cultured myocytes, which are highly glycolytic and generally viewed as an imperfect model for studying muscle metabolism and insulin action. Nonetheless, results from the cell culture model are generally convincing and align with the descriptive data from studies in animal models. Overall, the findings provide a strong rationale for moving this line of investigation into mouse gain/loss of function models.

One caveat of the approach taken is that exposure of cells to palmitate alone is not reflective of in vivo physiology. It would be interesting to know if similar effects on CoQ are observed when cells are exposed to a more physiological mixture of fatty acids that includes a high ratio of palmitate, but better mimics in vivo nutrition.

Reviewer #1 (Public Review):

This study identified the truncating LRRC23 is associated with the asthenozoospermia in human and demonstrated that the truncated Lrrc23 specifically disorganizes RS3 and the junctional structure between RS2 and RS3 in the sperm axoneme, which might cause sperm motility defects and male infertility. Although LRRC23 has been reported as a component of the radial spoke and is necessary for sperm motility in mice, this study provided a precise pathogenic mechanism of truncating LRRC23 in asthenozoospermia. This work is of interest to researchers working on reproduction biology. The manuscript has been revised to address prior reviewers' comments.

Reviewer #2 (Public Review):

Summary:

The present study explores the molecular function of LRRC23 in male fertility, specifically in the context of the regulation of spermiogenesis. The author initiates the investigation by identifying LRRC23 mutations as a potential cause of male sterility based on observations made in closely related individuals affected by asthenozoospermia (ASZ). To further investigate the function of LRRC23 in spermatogenesis, mutant mice expressing truncated LRRC23 proteins are created, aligning with the identified mutation site. Consequently, the findings confirm the deleterious effects of LRRC23 mutations on sperm motility in these mice while concurrently observing no significant abnormalities in the overall flagella structure. Furthermore, the study reveals LRRC23's interaction with the RS head protein RSPH9 and its active involvement in the assembly of the axonemal RS. Notably, LRRC23 mutations result in the loss of the RS3 head structure and disruption of the RS2-RS3 junction structure. Therefore, the author claimed that LRRC23 is an indispensable component of the RS3 head structure and suggests that mutations in LRRC23 underlie sterility in mice.

Strengths:

The key contribution of this article lies in confirming LRRC23's involvement in assembling the RS3 head structure in sperm flagella. This finding represents a significant advancement in understanding the complex architecture of the RS3 structural complex, building upon previous studies. Moreover, the article's topic is interesting and originates from clinical research, which holds significant implications for potential clinical applications.

Reviewer #1 (Public Review):

Summary:

Chen et al. describe the bacterial and fungal composition of cervical samples from women with/without Cesarean-section scar diverticulum (CSD) using whole metagenomic sequencing. Also, they report the metabolomic profile associated with CSD and built correlation networks at the taxonomical and taxonomic-metabolic levels to establish potential bacteria-fungi interactions. These interactions could be used, long-term, as therapeutic options to treat or prevent CSD.

After reviewing the manuscript, the authors have not integrated any of my previous recommendations into the new version of the work. Therefore, in my opinion, the limitations or weaknesses of the study remain the same.

I find it especially worrying that they do not consider the use of white controls necessary, arguing that "we considered that this study described a biomass-rich site, and the abundance of dominant species was much higher than that of the possible 'kitome', so we did not set a blank control" while describing among the most predominant species in the reproductive tract bacteria that do not colonize humans and that have been previously described as contaminants.

Lack of experimental controls can lead to artifactual results and compromise the evidence presented and the significance of the results.

Reviewer #2 (Public Review):

Summary:

Shotgun data have been analysed to obtain fungal and bacterial organisms abundance. Through their metabolic functions and through co-occurrence networks, a functional relationship between the two types of organisms can be inferred. By means of metabolomics, function-related metabolites are studied in order to deepen the fungus-bacteria synergy.

Strengths:

Data obtained in bacteria correlate with data from other authors.<br /> The study of metabolic "interactions" between fungi and bacteria is quite new.<br /> The inclusion of metabolomics data to support the results is a great contribution.

Weaknesses:

Most of them have been solved in the revision, but for the future it will be nice to integrate this data with others from 16s.

Reviewer #1 (Public Review):

The study utilizes a variety of methods, chemical and expressed probes, caged release of IP3, as well as oocytes with mutations that alter zinc availability, that provide an elegant examination of how zinc deficiency and zinc excess modulate the transient and cyclic release of calcium during egg activation. In this manuscript, the authors sought to determine if there is any interplay between zinc and calcium, two divalent cations that have been demonstrated to have important roles during fertilization. They employ agents that disrupt normal zinc homeostasis and then monitor the resulting calcium oscillations during egg activation. If zinc was made unavailable via chelation with TPEN, then the calcium oscillations halted. This occurred regardless of the activation method, which included ICSI, PLC𝛇, Acetylcholine, strontium chloride, and thimerosal. This phenotype could be rescued by introducing zinc back into the egg via an ionophore, such as zinc pyrithione; however, too much zinc pyrithione also halted calcium oscillations. Taken together, these two results demonstrate that there is a threshold level of zinc that is required for proper calcium oscillations to occur.

Furthermore, the authors sought to understand how zinc affects the IP3 receptor, IP3R1. IP3R1 is the receptor that modulates the release of calcium from the endoplasmic reticulum. The authors cited a previous study that identified zinc binding sites on IP3R1. The authors highlight that there exist no studies regarding the regulation of IP3R1 by zinc; however, such studies were cited for a similar calcium channel, the RyRs. The authors use thapsigargin to inhibit the SERCA pump, leading to calcium leak from the IP3R1. TPEN blunted the amount of calcium leaked from the ER following treatment, suggesting that zinc occupancy is necessary for IP3R1 function.

The results of these experiments support the authors conclusions that zinc is essential for the IP3R1-mediated release of calcium in an oscillatory manner during egg activation. These results provide further insight into signals necessary for proper egg activation and the ultimate success of the resulting embryo.

Reviewer #2 (Public Review):

The manuscript describes more fully the relationship between zinc fluxes and calcium oscillations during egg activation by directly manipulating the level of zinc ions inside and outside the cell with chelators and ionophores and then measuring resulting changes in Ca++ oscillations. The authors have provided solid evidence consistent with their hypothesis that zinc ions regulate Ca++ oscillations by directly modulating the gating of the IP3-R which is the main calcium channel responsible for calcium release into the cytoplasm. The authors employ well established methods of calcium measurement along with various chelators, ionophores and a wide variety of methods that cause egg activation to demonstrate that an optimal level of zinc ions are required for Ca++ oscillations to occur.

Helpfully, the authors provide a model to explain their observations in Figure 7. In the model, the increase in zinc during maturation is permissive for later IP3-R gating in response to activation. The experiments with TPEN solidly demonstrate that Zn is required because lowering free zinc, (as indicated by Fluozin staining), abrogates Ca++ oscillations. This is true regardless of the method of activation. What is not clearly described in the model or in the manuscript is whether the levels of zinc at MII are simply permissive for IP3-R gating or whether there is a more acute relationship between zinc fluxes and Ca++ oscillations. In the original paper describing the zinc spark (Kim et al., ACS Chem Biol 6:716-723), the authors show that zinc efflux very closely mirrors Ca++ oscillations suggesting a more active relationship.

The role of TRPv3 and Trpm7 in Zn homeostasis during egg activation seems to be minor. Labile zinc accumulation, as measured by fluozin-3 staining, is reduced in the dKO eggs, but is this modest decrease in labile Zn responsible for the changes in Ca release after Tg treatment? There is an increase in the amplitude of Tg-induced Ca release in dKO eggs. This argues that there is not an inhibitory effect in the dKO mice. That it takes a little longer to reach Ca peak could be due to the greater amount of Ca being released.

The effect of PyT on the apparent rise in cytoplasmic Ca++ in Figure 6 is interpreted as caused by an artifact of high Zn concentrations. However, it is not clear that 0.05 uM PyT would necessarily increase cytoplasmic Zn to the point where FURA-2 fluorescence would increase. A simpler interpretation is that PyT allows sufficient Zn to enter the cell and keeps the IP3-R channels open causing a sustained rise in cytoplasmic Ca and preventing oscillations in Ca++. This interpretation would also preclude inhibitory effects of high Zn concentrations as shown in Figure 7 which may or may not be present but are simply speculation.

Overall, this study significantly advances our understanding of egg activation and could lead to better ways of in vitro egg activation in women undergoing assisted reproduction.

Reviewer #3 (Public Review):

This study investigated the role of Zn2+ on the maintenance of Ca2+ oscillation upon fertilization. TPEN was used to reduce the level of available Zn2+ in fertilized oocytes and different inhibitors were used to pinpoint the mechanistic involvement of intracellular Zn2+ on the maintenance of Ca2+ oscillation. As also stated in the manuscript, previous studies have demonstrated the role of Zn2+ for the successful completion of meiosis/fertilization. The manuscript expands our understanding of fertilization process by describing how the level of Zn2+ regulates Ca2+ channels and stores. The manuscript is well-organized and the topic is important in early embryo development fields.

The authors added more information to the manuscript based on reviewers' comments. The quality of the manuscript has been improved and the study addresses important questions in mammalian fertilization.

Reviewer #1 (Public Review):

The study is valuable because it shows that physiologically relevant ∆9-THC concentrations have metabolic effects on early mouse embryonic cell types, which could cause developmental effects. Overall, the authors have convincing evidence showing that ∆9-THC has metabolic effects on mouse embryonic stem cells (mESCs), and that these effects persist in mESC-derived primordial germ cell-like cells even after ∆9-THC treatment has stopped. In this revised version, the authors included additional data to characterize the dose-dependence of the effects of ∆9-THC. Furthermore, they supported their finding of metabolic memory in PGCLCs by ruling out the potential alternative explanation that ∆9-THC persists in the cultured cells over the course of their experiment. This study has two significant implications: first, that ∆9-THC may alter the metabolism of early mouse embryos, and second, that mouse primordial germ cell-like cells can have a memory of previous metabolic perturbations.

The authors investigated the metabolic effects of ∆9-THC, the main psychoactive component of cannabis, on early mouse embryonic cell types. They found that ∆9-THC increases proliferation in male and female mouse embryonic stem cells (mESCs) and upregulates glycolysis. Additionally, primordial germ cell-like cells (PGCLCs) differentiated from ∆9-THC-exposed cells also show alterations to their metabolism. The study is valuable because it shows that physiologically relevant ∆9-THC concentrations have metabolic effects on cell types from the early embryo, which may cause developmental effects. Intriguingly, these effects persist in PGCLCs even after withdrawal of ∆9-THC.

The study shows that ∆9-THC increases the proliferation rate of mESCs but not mEpiLCs, without substantially affecting cell viability, except at the highest dose of 100 µM which shows toxicity (Figure 1). The dose required to cause increased proliferation was approximately 1 nM (Supplementary Figure 1), which is remarkably low. Treatment of mESCs with rimonabant (a CB1 receptor antagonist) blocks the effect of 100 nM ∆9-THC on cell proliferation, showing that the proliferative effect is mediated by CB1 receptor signaling. Similarly, treatment with 2-deoxyglucose, a glycolysis inhibitor, also blocks this proliferative effect (Figure 4G-H). Therefore, the effect of ∆9-THC depends on both CB1 signaling and glycolysis. This set of experiments strengthens the conclusions of the study by helping to elucidate the mechanism of the effects of ∆9-THC.

The study also profiles the transcriptome and metabolome of cells exposed to 100 nM ∆9-THC (Figure 4). Although the transcriptomic changes are modest overall, there is upregulation of anabolic genes, consistent with the increased proliferation rate in mESCs. Metabolomic profiling revealed a broad upregulation of metabolites in mESCs treated with 100 nM ∆9-THC. Some metabolic effects were also observed at a lower dose of 10 nM (Figure 3B).

Additionally, the study shows that ∆9-THC can influence germ cell specification. mESCs were differentiated to mEpiLCs in the presence or absence of ∆9-THC, and the mEpiLCs were subsequently differentiated to mPGCLCs. mPGCLC induction efficiency was tracked using a BV:SC dual fluorescent reporter. ∆9-THC treated cells had a moderate increase in the double positive mPGCLC population, and decrease in the double negative population. A cell tracking dye showed that mPGCLCs differentiated from ∆9-THC treated cells had undergone more divisions on average. As with the mESCs, these mPGCLCs also had altered gene expression and metabolism, consistent with an increased proliferation rate. Importantly, in the revised version, the authors supported their finding of metabolic memory in mPGCLCs by ruling out the potential alternative explanation that ∆9-THC persists in the cultured cells over the course of their experiment (Supplementary Figure 13).

Finally, the authors also observed that ∆9-THC decreases the proliferation of human ESCs (Supplementary Figure 4). These cells were in the primed pluripotent state, making them more similar to mEpiLCs than mESCs. Although this result may form the basis of follow-up experiments in a separate paper, it would be premature to conclude that the same effects will be observed in human cells as were observed in mouse cells.

Overall, this study provides good evidence for ∆9-THC having metabolic effects on mouse ESCs, and additionally shows that these effects can persist during germ cell specification. Potential effects of ∆9-THC exposure during early embryonic development are important for society to understand, and the results of this study are significant for public health.

Reviewer #2 (Public Review):

Verdikt et al. focused on the influence of Δ9-THC, the most abundant phytocannabinoid, on early embryonic processes. The authors chose an in vitro differentiation system as model, and compared the proliferation rate, metabolic status and transcriptional level in ESCs, exposure to Δ9-THC. They also evaluated the change of metabolism and transcriptome in PGCLCs derived from Δ9-THC-exposed cells. All the methods in this paper do not involve the differentiation of ESCs to lineage specific cells. So the results cannot demonstrate the impact of Δ9-THC on postimplantation developmental stages. In brief, the authors want to explore the impact of Δ9-THC on preimplantation developmental stages, but they only detected the change in ESCs and PGCLCs derived from ESCs, exposure to Δ9-THC, which showed the molecular characterization of the impact of Δ9-THC exposure on ESCs and PGCLCs.

Reviewer #1 (Public Review):

Summary:

In this paper, Steinemann et al. characterized the nature of stochastic signals underlying the trial-averaged responses observed in the lateral intraparietal cortex (LIP) of non-human primates (NHPs), while these performed the widely used random dot direction discrimination task. Ramp-up dynamics in the trial averaged LIP responses were reported in numerous papers before. However, the temporal dynamics of these signals at the single-trial level have been subject to debate. Using large-scale neuronal recordings with Neuropixels in NHPs, allows the authors to settle this debate rather compellingly. They show that drift-diffusion-like computations account well for the observed dynamics in LIP.

Strengths:

This work uses innovative technical approaches (Neuropixel recordings in behaving macaque monkeys). The authors tackle a vexing question that requires measurements of simultaneous neuronal population activity and hence leverage this advanced recording technique in a convincing way.

They use different population decoding strategies to help interpret the results.

They also compare how decoders relying on the data-driven approach using dimensionality reduction of the full neural population space compare to decoders relying on more traditional ways to categorize neurons that are based on hypotheses about their function. Intriguingly, although the functionally identified neurons are a modest fraction of the population, decoders that only rely on this fraction achieve comparable decoding performance to those relying on the full population. Moreover, decoding weights for the full population did not allow the authors to reliably identify the functionally identified subpopulation.

Weaknesses:

No major weaknesses.

Reviewer #2 (Public Review):

Steinemann, Stine, and their co-authors studied the noisy accumulation of sensory evidence during perceptual decision-making using Neuropixels recordings in awake, behaving monkeys. Previous work has largely focused on describing the neural underpinnings through which sensory evidence accumulates to inform decisions, a process which on average resembles the systematic drift of a scalar decision variable toward an evidence threshold. The additional order of magnitude in recording throughput permitted by the methodology adopted in this work offers two opportunities to extend this understanding. First, larger-scale recordings allow for the study of relationships between the population activity state and behavior without averaging across trials. The authors' observation here of covariation between the trial-to-trial fluctuations of activity and behavior (choice, reaction time) constitutes interesting new evidence for the claim that neural populations in LIP encode the behaviorally-relevant internal decision variable. Second, using Neuropixels allows the authors to sample LIP neurons with more diverse response properties (e.g. spatial RF location, motion direction selectivity), making the important question of how decision-related computations are structured in LIP amenable to study. For these reasons, the dataset collected in this study is unique and potentially quite valuable.

However, the analyses at present do not convincingly support two of the manuscript's key claims: (1) that "sophisticated analyses of the full neuronal state space" and "a simple average of Tconin neurons' yield roughly equivalent representations of the decision variable; and (2) that direction-selective units in LIP provide the samples of instantaneous evidence that these Tconin neurons integrate. Supporting claim (1) would require results from sophisticated population analyses leveraging the full neuronal state space; however, the current analyses instead focus almost exclusively on 1D projections of the data. Supporting claim (2) convincingly would require larger samples of units overlapping the motion stimulus, as well as additional control analyses.

Specific shortcomings are addressed in further detail below:

1) The key analysis-correlation between trial-by-trial activity fluctuations and behavior, presented in Figure 5-is opaque, and would be more convincing with negative controls:

To strengthen the claim that the relationship between fluctuations in (a projection of) activity and fluctuations in behavior is significant/meaningful, some evidence should be brought that this relationship is specific - e.g. do all projections of activity give rise to this relationship (or not), or what level of leverage is achieved with respect to choice/RT when the trial-by-trial correspondence with activity is broken by shuffling.

2) The choice to perform most analysis on 1D projections of population activity is not wholly appropriate for this unique type of dataset, limiting the novelty of the findings, and the interpretation of similarity between results across choices of projection appears circular:

The bulk of the analyses (Figure 2, Figure 3, part of Figure 4, Figure 5, Figure 6) operate on one of several 1D projections of simultaneously-recorded activity. Unless the embedding dimension of these datasets really does not exceed 1 (dimensionality using e.g. participation ratio in each session is not quantified), it is likely that these projections elide meaningful features of LIP population activity. Further, additional evidence/analysis would help to strengthen the authors' interpretation of the observed similarity of results across these 1D projections. For one, the rationale behind deriving Sramp was based on the ramping historically observed in Tin neurons during this task, so should be expected to resemble Tin. Second, although Tin does not comprise the majority of neurons recorded in each session, it does comprise the largest fraction of the neuron groups (e.g. Tin, Min, etc) sampled during most sessions, so SPC1 should be expected to resemble Tin more than it does the other neuron groups. Additional/control analyses will be important for strongly supporting the claim that the approximate equality between the population DV and the average of Tin units is meaningful. The analysis presented in Figure S7 is an important step toward this, demonstrating that SPC1 isn't just reflecting the activity of Tin, but would make the point more strongly with some additional analysis. Are the magnitudes of weights assigned to units in Tin larger than in the other groups of units with pre-selected response properties? What is their mean weighting magnitude, in comparison with the mean weight magnitude assigned to other groups? What is the null level of correspondence observed between weight magnitude and assignment to Tin (e.g. a negative control, where the identities of units are scrambled)?

A secondary approach could also get at this point (the small Tin group furnishes a DV very similar to the overall population DV) from a different direction: computing SPC1 using only neurons *not* in Tin, and repeating the analysis performed with the other 3 1D projections of the data currently in Figure 5. Observing similar results for this 4th projection would strengthen the evidence supporting the interpretation the authors adopt.

3) The principal components analysis normalization procedure is unclear, and potentially incorrect and misleading:

Why use the chosen normalization window (+/- 25ms around 100ms after motion stimulus onset) for standardizing activity for PCA, rather than the typical choice of mean/standard deviation of activity in the full data window? This choice would specifically squash responses for units with a strong visual response, which distorts the covariance matrix, and thus the principal components that result. This kind of departure from the standard procedure should be clearly justified: what do the principal components look like when a standard procedure is used, and why was this insufficient/incorrect/unsuitable for this setting?

4) Analysis conclusions would generally be stronger with estimates of variability and control analyses: This applies broadly to Figures 2-6.

Reviewer #3 (Public Review):

Summary:

The paper investigates which aspects of neural activity in LIP of the macaque give rise to individual decisions (specificity of choice and reaction times) in single trials, by recording simultaneously from hundreds of neurons. Using a variety of dimensionality reduction and decoding techniques, they demonstrate that a population-based drift-diffusion signal, which relies on a small subset of neurons that overlap choice targets, is responsible for the choice and reaction time variability. Analysis of direction-selective neurons in LIP and their correlation with decision-related neurons (T con in neurons ) suggests that evidence integration occurs within area LIP.

Strengths:

This is an important and interesting paper, which resolves conflicting hypotheses regarding the mechanisms that underlie decision-making in single trials. This is made possible by exploiting novel technology (Primatepixels recordings), in conjunction with state-of-the-art analyses and well-established dynamic random dot motion discrimination tasks.

Reviewer #1 (Public Review):

The study by Vengayil et al. presented a role for Ubp3 for mediating inorganic phosphate (Pi) compartmentalization in cytosol and mitochondria, which regulates metabolic flux between cytosolic glycolysis and mitochondrial processes. Although the exact function of increased Pi in mitochondria is not investigated, findings have valuable implications for understanding the metabolic interplay between glycolysis and respiration under glucose-rich conditions. They showed that UBP3 KO cells regulated decreased glycolytic flux by reducing the key Pi-dependent-glycolytic enzyme abundances, consequently increasing Pi compartmentalization to mitochondria. Increased mitochondria Pi increases oxygen consumption and mitochondrial membrane potential, indicative of increased oxidative phosphorylation. In conclusion, the authors reported that the Pi utilization by cytosolic glycolytic enzymes is a key process for mitochondrial repression under glucose conditions.

However, the main claims are only partially supported by the low number of repeats and utilizing only one strain background, which decreased the overall rigor of the study. The full-power yeast model could be utilized with testing findings in different backgrounds with increased biological repeats in many assays described in this study. In the yeast model, it has been well established that many phenotypes are genotype/strain dependent (Liti 2019, Gallone 2016, Boekout 2021, etc...). with some strains utilizing mitochondrial respiration even under high glucose conditions (Kaya 2021). It would be conclusive to test whether wild strains with increased respiration under high glucose conditions would also be characterized by increased mitochondrial Pi.

It is not described whether the drop in glycolytic flux also affects TCA cycle flux. Are there any changes in the pyruvate level? If the TCA cycle is also impaired, what drives increased mitochondrial respiration?

In addition, some of the important literature was also missed in citation and discussion. For example, in a recent study (Ouyang et al., 2022), it was reported that phosphate starvation increases mitochondrial membrane potential independent of respiration in yeast and mammalian cells, and some of the conflicting results were presented in this study.

An additional experiment with strains lacking mitochondrial DNA under phosphate-rich and restricted conditions would further strengthen the result.

Western blot control panels should include entire membrane exposure, and non-cut western blots should be submitted as supplementary.

In Figure 4, it is shown that Pi addition decreases basal OCR to the WT level. However, the Cox2 level remains significantly higher. This data is confusing as to whether mitochondrial Pi directly regulates respiration or not.

Representative images of Ubx3 KO and wild-type strains stained with CMXRos are missing.

Overall, mitochondrial copy number and mtDNA copy number should be analyzed in WT and Ubo3 KO cells as well as Pi-treated and non-treated cells, and basal OCR data should be normalized accordingly. The reported normalization against OD is not appropriate.

Reviewer #2 (Public Review):

Summary:<br /> Cells cultured in high glucose tend to repress mitochondrial biogenesis and activity, a prevailing phenotype type called Crabree effect that is observed in different cell types and cancer. Many signaling pathways have been put forward to explain this effect. Vengayil et al proposed a new mechanism involved in Ubp3/Ubp10 and phosphate that controls the glucose repression of mitochondria. The central hypothesis is that ∆ubp3 shifts the glycolysis to trehalose synthesis, therefore leading to the increase of Pi availability in the cytosol, then mitochondria receive more Pi, and therefore the glucose repression is reduced.

Strengths:<br /> The strength is that the authors used an array of different assays to test their hypothesis. Most assays were well-designed and controlled.

Weaknesses:<br /> I think the main conclusions are not strongly supported by the current dataset.

1. Although the authors discovered ∆ubp3 cells have higher Pi and mitochondrial activity than WT in high glucose, it is not known if WT cultured in different glucose concentration also change Pi that correlate with the mitochondrial activity. The focus of the research on ∆ubp3 is somewhat artificial because ∆ubp3 not only affects glycolysis and mitochondria, but many other cellular pathways are also changed. There is no idea whether culturing cells in low glucose, which de-repress the mitochondrial activity, involves Ubp3 or not. Similarly, the shift of glycolysis to trehalose synthesis is also not relevant to the WT cells cultured in a low-glucose situation.

2. The central hypothesis that Pi is the key constraint behind the glucose repression of mitochondrial biogenesis/activity is supported by the data that limiting Pi will suppress mitochondrial activity increase in these conditions (e.g., ∆ubp3). However, increasing the Pi supply failed to increase mitochondrial activity. The explanation put forward by the authors is that increased Pi supply will increase glycolysis activity, and somehow even reduce the mitochondrial Pi. I cannot understand why only the increased Pi supply in ∆ubp3, but not the increased Pi by medium supplement, can increase mitochondrial activity. The authors said "...that ubp3Δ do not increase mitochondrial Pi by merely increasing the Pi transporters, but rather by increasing available Pi pools". They showed that ∆ubp3 mitochondria had higher Pi but WT cells with medium Pi supplement showed lower Pi, it is hard to understand why the same Pi increase in the cytosol had a different outcome in mitochondrial Pi. Later on, they showed that the isolated mito exposed to higher Pi showed increased activity, so why can't increased Pi in intact cells increase mito activity? Moreover, they first showed that ∆ubp3 had a Mir1 increase in Fig3A, then showed no changes in FigS4G. It is very confusing.

3. Given that there is no degradation difference for these glycolytic enzymes in ∆ubp3, and the authors found transcriptional level changes, suggests an alternative possibility where ∆ubp3 may signal through unknown mechanisms to parallelly regulate both mitochondrial biogenesis and glycolytic enzyme expression. The increase of trehalose synthesis usually happens in cells under proteostasis stress, so it is important to rule out whether ∆ubp3 signals these metabolic changes via proteostasis dysregulation. This echoes my first point that it is unknown whether wild-type cells use a similar mechanism as ∆ubp3 cells to regulate the glucose repression of mitochondria.

4. Other major concerns:<br /> a. The authors selectively showed a few proteins in their manuscript to support their conclusion. For example, only Cox2 and Tom70 were used to illustrate mitochondrial biogenesis difference in line 97. Later on, they re-analyzed the previous MS dataset from Isasa et al 2015 and showed a few proteins in Fig3A to support their conclusion that ∆ubp3 increases mitochondrial OXPHOS proteins. However, I checked that MS dataset myself and saw that many key OXPHOS proteins do not change, for example, both ATP1 and ATP2 do not change, which encode the alpha and beta subunits of F1 ATPase. They selectively reported the proteins' change in the direction along with their hypothesis.<br /> b. The authors said they deleted ETC component Cox2 in line 111. I checked their method and table S1, I cannot figure out how they selectively deleted COX2 from mtDNA. This must be a mistake.<br /> c. They used sodium azide in a lot of assays to inhibit complex IV. However, this chemical is nonspecific and broadly affects many ATPases as well. Not sure why they do not use more specific inhibitors that are commonly used to assay OCR in seahorse.<br /> d. The authors measured cellular Pi level by grinding the entire cells to release Pi. However, this will lead to a mix of cytosolic and vacuolar Pi. Related to this caveat, the cytosol has ~50mM Pi, while only 1-2mM of these glycolysis metabolites, I am not sure why the reduction of several glycolysis enzymes will cause significant changes in cytosolic Pi levels and make Pi the limiting factor for mitochondrial respiration. One possibility is that the observed cytosolic Pi level changes were caused by the measurement issue mentioned above.<br /> e. The authors used ∆mir1 and MIR1 OE to show that Pi viability in the mitochondrial matrix is important for mitochondrial activity and biogenesis. This is not surprising as Pi is a key substrate required for OXPHOS activity. I doubt the approach of adding a control to determine whether Pi has a specific regulatory function, while other OXPHOS substrates, like ADP, O2 etc do not have the same effect.

Reviewer #1 (Public Review):

Summary:<br /> In this paper, Ruggiero, Leite, and colleagues assess the effects of early-life seizures on a large number of anatomical, physiological, behavioral, and neurochemical measures. They find that prolonged early-life seizures do not lead to obvious cell loss, but lead to astrogliosis, working memory deficits on the radial arm maze, increased startle response, decreased paired pulse inhibition, and increased hippocampal-PFC LTP. There was a U-shape relationship between LTP and cognitive deficits. There is increased theta power during the awake state in ELS animals but reduced PFC theta-gamma coupling and reduced theta HPC-PFC coherence. Theta coherence seems to be similar in ACT and REM states in ELS animals while in decreases in active relative REM in controls.

Strengths:<br /> The main strength of the paper is the number of convergent techniques used to understand how hippocampal PFC neural dynamics and behavior change after early-life seizures. The sheer scale, breadth, and reach of the experiments are praiseworthy. It is clear that the paper is a major contribution to the field as far as understanding the impact of early-life seizures. The LTP findings are robust and provide an important avenue for future study. The experiments are performed carefully and the analysis is appropriate. The paper is well-written and the figures are clear.

Weaknesses:<br /> The main weakness of the paper is the lack of causal manipulations to determine whether prevention or augmentation of any of the findings has any impact on behavior or cognition. Alternatively, if other manipulations would enhance working memory in ELS animals, it would be interesting to see the effects on any of these parameters measured in the paper. Also, I find the sections where correlations and dimensionality reduction techniques are used to compare all possible variables to each other less compelling than the rest of the paper (with the exception of the findings of U U-shaped relationship of cognition to LTP). In fact, I think these sections take away from the impact of the actual findings. Finally, the apomorphine section seemed to hang separately from the rest of the paper and did not seem to fit well.

Reviewer #2 (Public Review):

In this manuscript, the authors employ a multilevel approach to investigate the relationship between the hippocampal-prefrontal (HPC-PFC) network and long-term phenotypes resulting from early-life seizures (ELS). Their research begins by establishing an ELS rat model and conducting behavioral and neuropathological studies in adulthood. Subsequently, the manuscript delves into testing hypotheses concerning HPC-PFC network dysfunction. While the results are intriguing, my enthusiasm is tempered by concerns related to the logical flow, sample size, and the potential over-interpretation of results. Detailed comments are provided below:

Focus on Correlations: The manuscript primarily highlights correlations as the most significant findings. For instance, it demonstrates that ELS induces cognitive and sensorimotor impairments. However, it falls short of elucidating why these deficits are specifically linked to HPC-PFC synaptic plasticity/network. Furthermore, the manuscript mentions the involvement of other brain regions like the thalamus in the long-term outcomes of ELS based on immunohistochemistry data. This raises questions about the subjective nature and persuasiveness of the statistical studies presented.

Sample Size Concerns: The manuscript raises concerns about the adequacy of sample sizes in the study. The initial cohort for acute electrophysiology during ELS induction comprised only 5 rats, without a control group. Moreover, the behavioral tests involved 11 control and 14 ELS rats, but these same cohorts were used for over four different experiments. Subsequent electrophysiology and immunohistochemistry experiments used varying numbers of rats (7 to 11). Clarification is needed regarding whether these experiments utilized the same cohort and why the sample sizes differed. A power analysis should have been performed to justify sample sizes, especially given the complexity of the statistical analyses conducted.

Overinterpretation of HPC-PFC Network Dysfunction: The manuscript potentially overinterprets the role of HPC-PFC network dysfunction based on the results. Notably, cognitive deficits are described as subtle, with no evidence of learning deficits and only faint working memory impairments. However, sensorimotor deficits show promise. Consequently, it's essential to justify the emphasis on the HPC-PFC network as the primary mechanism underlying ELS-associated outcomes, especially when enhanced LTP is observed. Additionally, the manuscript seems to sideline neuropathological changes in the thalamus and the thalamus-to-PFC connection. The analysis lacks a direct assessment of the causal relationship between HPC-PFC dysfunction and ELS-associated outcomes, leaving a multitude of multilevel analyses yielding potential correlations without easily interpretable results.

Overall, while the manuscript presents intriguing findings related to the HPC-PFC network and ELS outcomes, it requires a more rigorous experimental design, a more coherent narrative linking results to hypotheses, and careful consideration of alternative interpretations based on the observed data. Addressing these concerns will enhance the manuscript's overall quality and impact.

Reviewer #1 (Public Review):

Summary:

Protein conformational changes are often critical to protein function, but obtaining structural information about conformational ensembles is a challenge. Over a number of years, the authors of the current manuscript have developed and improved an algorithm, qFit protein, that models multiple conformations into high resolution electron density maps in an automated way. The current manuscript describes the latest improvements to the program, and analyzes the performance of qFit protein in a number of test cases, including classical statistical metrics of data fit like Rfree and the gap between Rwork and Rfree, model geometry, and global and case-by-case assessment of qFit performance at different data resolution cutoffs. The authors have also updated qFit to handle cryo-EM datasets, although the analysis of its performance is more limited due to a limited number of high-resolution test cases and less standardization of deposited/processed data.

Strengths:

The strengths of the manuscript are the careful and extensive analysis of qFit's performance over a variety of metrics and a diversity of test cases, as well as the careful discussion of the limitations of qFit. This manuscript also serves as a very useful guide for users in evaluating if and when qFit should be applied during structural refinement.

Reviewer #2 (Public Review):

Summary:

The manuscript by Wankowicz et al. describes updates to qFit, an algorithm for the characterization of conformational heterogeneity of protein molecules based on X-ray diffraction of Cryo-EM data. The work provides a clear description of the algorithm used by qFit. The authors then proceed to validate the performance of qFit by comparing it to deposited X-ray entries in the PDB in the 1.2-1.5 Å resolution range as quantified by Rfree, Rwork-Rfree, detailed examination of the conformations introduced by qFit, and performance on stereochemical measures (MolProbity scores). To examine the effect of experimental resolution of X-ray diffraction data, they start from an ultra high-resolution structure (SARS-CoV2 Nsp3 macrodomain) to determine how the loss of resolution (introduced artificially) degrades the ability of qFit to correctly infer the nature and presence of alternate conformations. The authors observe a gradual loss of ability to correctly infer alternate conformations as resolution degrades past 2 Å. The authors repeat this analysis for a larger set of entries in a more automated fashion and again observe that qFit works well for structures with resolutions better than 2 Å, with a rapid loss of accuracy at lower resolution. Finally, the authors examine the performance of qFit on cryo-EM data. Despite a few prominent examples, the authors find only a handful (8) of datasets for which they can confirm a resolution better than 2.0 Å. The performance of qFit on these maps is encouraging and will be of much interest because cryo-EM maps will, presumably, continue to improve and because of the rapid increase in the availability of such data for many supramolecular biological assemblies. As the authors note, practices in cryo-EM analysis are far from uniform, hampering the development and assessment of tools like qFit.

Strengths:

qFit improves the quality of refined structures at resolutions better than 2.0 A, in terms of reflecting true conformational heterogeneity and geometry. The algorithm is well designed and does not introduce spurious or unnecessary conformational heterogeneity. I was able to install and run the program without a problem within a computing cluster environment. The paper is well written and the validation thorough.<br /> I found the section on cryo-EM particularly enlightening, both because it demonstrates the potential for discovery of conformational heterogeneity from such data by qFit, and because it clearly explains the hurdles towards this becoming common practice, including lack of uniformity in reporting resolution, and differences in map and solvent treatment.

Weaknesses:

The authors begin the results section by claiming that they made "substantial improvement" relative to the previous iteration of qFit, "both algorithmically (e.g., scoring is improved by BIC, sampling of B factors is now included) and computationally (improving the efficiency and reliability of the code)" (bottom of page 3). However, the paper does not provide a comparison to previous iterations of the software or quantitation of the effects of these specific improvements, such as whether scoring is improved by the BIC, how the application of BIC has changed since the previous paper, whether sampling of B factors helps, and whether the code faster. It would help the reader to understand what, if any, the significance of each of these improvements was.

The exclusion of structures containing ligands and multichain protein models in the validation of qFit was puzzling since both are very common in the PDB. This may convey the impression that qFit cannot handle such use cases. (Although it seems that qFit has an algorithm dedicated to modeling ligand heterogeneity and seems to be able to handle multiple chains). The paper would be more effective if it explained how a user of the software would handle scenarios with ligands and multiple chains, and why these would be excluded from analysis here.

It would be helpful to add some guidance on how/whether qFit models can be further refined afterwards in Coot, Phenix, ..., or whether these models are strictly intended as the terminal step in refinement.

Appraisal & Discussion:

Overall, the authors convincingly demonstrate that qFit provides a reliable means to detect and model conformational heterogeneity within high-resolution X-ray diffraction datasets and (based on a smaller sample) in cryo-EM density maps. This represents the state of the art in the field and will be of interest to any structural biologist or biochemist seeking to attain an understanding of the structural basis of the function of their system of interest, including potential allosteric mechanisms-an area where there are still few good solutions. That is, I expect qFit to find widespread use.

Reviewer #3 (Public Review):

Summary:

The authors address a very important issue of going beyond a single-copy model obtained by the two principal experimental methods of structural biology, macromolecular crystallography and cryo electron microscopy (cryo-EM). Such multiconformer model is based on the fact that experimental data from both these methods represent a space- and time-average of a huge number of the molecules in a sample, or even in several samples, and that the respective distributions can be multimodal. Different from structure prediction methods, this approach is strongly based on high-resolution experimental information and requires validated single-copy high-quality models as input. Overall, the results support the authors' conclusions.

In fact, the method addresses two problems which could be considered separately:

- An automation of construction of multiple conformations when they can be identified visually;<br /> - A determination of multiple conformations when their visual identification is difficult or impossible.

The first one is a known problem, when missing alternative conformations may cost a few percent in R-factors. While these conformations are relatively easy to detect and build manually, the current procedure may save significant time being quite efficient, as the test results show.

The second problem is important from the physical point of view and has been addressed first by Burling & Brunger (1994; https://doi.org/10.1002/ijch.199400022). The new procedure deals with a second-order variation in the R-factors, of about 1% or less, like placing riding hydrogen atoms, modeling density deformation or variation of the bulk solvent. In such situations, it is hard to justify model improvement. Keeping Rfree values or their marginal decreasing can be considered as a sign that the model is not overfitted data but hardly as a strong argument in favor of the model.

In general, overall targets are less appropriate for this kind of problem and local characteristics may be better indicators. Improvement of the model geometry is a good choice. Indeed, yet Cruickshank (1956; https://doi.org/10.1107/S0365110X56002059) showed that averaged density images may lead to a shortening of covalent bonds when interpreting such maps by a single model. However, a total absence of geometric outliers is not necessarily required for the structures solved at a high resolution where diffraction data should have more freedom to place the atoms where the experiments "see" them.

The key local characteristic for multi conformer models is a closeness of the model map to the experimental one. Actually, the procedure uses a kind of such measure, the Bayesian information criteria (BIC). Unfortunately, there is no information about how sharply it identifies the best model, how much it changes between the initial and final models; in overall there is not any feeling about its values. The Q-score (page 17) can be a tool for the first problem where the multiple conformations are clearly separated and not for the second problem where the contributions from neighboring conformations are merged. In addition to BIC or to even more conventional target functions such as LS or local map correlation, the extreme and mean values of the local difference maps may help to validate the models.

This method with its results is a strong argument for a need in experimental data and information they contain, differently from a pure structure prediction. At the same time, absence of strong density-based proofs may limit its impact.

Strengths:

Addressing an important problem and automatization of model construction for alternative conformations using high-resolution experimental data.

Weaknesses:

An insufficient validation of the models when no discrete alternative conformations are visible and essentially missing local real-space validation indicators.

Reviewer #1 (Public Review):

The manuscript considers a hierarchical network of neurons, of the type that can be found in the sensory cortex, and assumes that they aim to constantly predict sensory inputs that may change in time. The paper describes the dynamics of neurons and rules of synaptic plasticity that minimize the integral of prediction errors over time.

The manuscript describes and analyses the model in great detail, and presents multiple and diverse simulations illustrating the model's functioning. However, the manuscript could be made more accessible and easier to read. The paper may help to understand the organization of cortical neurons, their properties, as well as the function of their particular components (such as apical dendrites).

Reviewer #2 (Public Review):

Neuroscientists often state that we have no theory of the brain. The example of theoretical physics is often cited, where numerous and quite complex phenomena are explained by a compact mathematical description. Lagrangian and Hamiltonian pictures provide such powerful 'single equation'. These frameworks are referred to as 'energy', an elegant way to turn numerous differential equations into a single compact relationship between observable quantities (state variables like position and speed) and scaling constants (like the gravity constant or the Planck constant). Such energy-pictures have been used in theoretical neuroscience since the 1980s.

The manuscript "neuronal least-action principle for real-time learning in cortical circuits" by Walter Senn and collaborators describes a theoretical framework to link predictive coding, error-based learning, and neuronal dynamics. The central concept is that an energy function combining self-supervised and supervised objectives is optimized by realistic neuronal dynamics and learning rules when considering the state of a neuron as a mixture of the current membrane potential and its rate of change. As compared with previous energy functions in theoretical neuroscience, this theory captures a more extensive range of observations while satisfying normative constraints. Particularly, no theory had to my knowledge related to adaptive dynamics widely observed in the brain (referred to as prospective coding in the text, but is sometimes referred to as adaptive coding or redundancy reduction) with the dynamics of learning rules.

The manuscript first exposes the theory of two previously published papers by the same group on somato-dendritic error with apical and basal dendrites. These dynamics are then related to an energy function, whose optimum recovers the dynamics. The rest of the manuscript illustrates how features of this model fit either normative or observational constraints. Learning follows a combination of self-supervised learning (learning to predict the next step) and supervised learning (learning to predict an external signal). The credit assignment problem is solved by an apical-compartment projecting a set of interneurons with learning rules whose role is to align many weight matrices to avoid having to do multiplexing. An extensive method section and supplementary material expand on mathematical proofs and makes more explicit the mathematical relationship between different frameworks.

Experts would say that much of the article agglomerates previous theoretical papers by the same authors that have been published recently either in archival servers or in conference proceedings. A number of adaptations to previous theoretical results were necessary, so the present article is not easily reduced to a compendium of previous pre-prints. However, the manuscript is by no means easy to read as there are several inconsistencies and it lacks a single thread. Also, there remains a few thorny assumptions (unobserved details of the learning rules or soma-dendrites interactions), but the theory is likely going to be regarded as an important step towards a comprehensive theory of the brain.

Reviewer #1 (Public Review):

The authors bring together multiple study methods (brain recordings with EEG and behavioral coding of infant and caregiver looking, and caregiver vocal changes) to understand social processes involved in infant attention. They test different hypotheses on whether caregivers scaffold attention by structuring a child's behavior, versus whether the child's attention is guided by internal factors and caregivers then respond to infants' attentional shifts. They conclude that internal processes (as measured by brain activation preceding looking) control infants' attention, and that caregivers rapidly modify their behaviors in response to changes in infant attention.

The study is meticulously documented, with cutting-edge analytic approaches to testing alternative models; this type of work provides a careful and well-documented guide for how to conduct studies and process and analyze data for researchers in the relatively new area of neural response in infants in social contexts.

Some concerns arise around the use of terms (for example, an infant may "look" at an object, but that does not mean the infant is actually "attending); collapsing of different types of looks (to people and objects), and the averaging of data across infants that may mask some of the individual patterns.

Reviewer #2 (Public Review):

Summary:<br /> This paper acknowledges that most development occurs in social contexts, with other social partners. The authors put forth two main frameworks of how development occurs within a social interaction with a caregiver. The first is that although social interaction with mature partners is somewhat bi-directional, mature social partners exogenously influence infant behaviors and attention through "attentional scaffolding", and that in this case infant attention is reactive to caregiver behavior. The second framework posits that caregivers support and guide infant attention by contingently responding to reorientations in infant behavior, thus caregiver behaviors are reactive to infant behavior. The aim of this paper is to use moment-to-moment analysis techniques to understand the directionality of dyadic interaction. It is difficult to determine whether the authors prove their point as the results are not clearly explained as is the motivation for the chosen methods.

Strengths<br /> The question driving this study is interesting and a genuine gap in the literature. Almost all development occurs in the presence of a mature social partner. While it is known that these interactions are critical for development, the directionality of how these interactions unfold in real-time is less known.

The analyses largely seem to be appropriate for the question at hand, capturing small moment-to-moment dynamics in both infant and child behavior, and their relationships with themselves and each other. Autocorrelations and cross-correlations are powerful tools that can uncover small but meaningful patterns in data that may not be uncovered with other more discretized analyses (i.e. regression).

Weaknesses<br /> The major weakness of this paper is that the reader is assumed to understand why these results lead to their claimed findings. The authors need to describe more carefully their reasoning and justification for their analyses and what they hope to show. While a handful of experts would understand why autocorrelations and cross-correlations should be used, they are by no means basic analyses. It would also be helpful to use simulated data or even a simple figure to help the reader more easily understand what a significant result looks like versus an insignificant result.

While the overall question is interesting the introduction does not properly set up the rest of the paper. The authors spend a lot of time talking about oscillatory patterns in general but leave very little discussion to the fact they are using EEG to measure these patterns. The justification for using EEG is also not very well developed. Why did the authors single out fronto-temporal channels instead of using whole brain techniques, which are more standard in the field? This is idiosyncratic and not common.

A worrisome weakness is that the figures are not consistently formatted. The y-axes are not consistent within figures making the data difficult to compare and interpret. Labels are also not consistent and very often the text size is way too small making reading the axes difficult. This is a noticeable lack of attention to detail.

No data is provided to reproduce the figures. This does not need to include the original videos but rather the processed and de-identified data used to generate the figures. Providing the data to support reproducibility is increasingly common in the field of developmental science and the authors are greatly encouraged to do so.

Reviewer #1 (Public Review):

Many studies reported findings implying that rhizobial infection is associated with cell cycle re-entry and progression, however, our understanding has been fragmented. This study provides exciting new insights as it represents a comprehensive description of the cell cycle progression during early stages of nodulation using fluorescence markers.

To briefly summarize, the authors first monitor H3.1 / H3.3 replacement to distinguish between replicating (S phase) and non-replicating cells to show that M. truncatula cortex cells along the bacterial infection thread are non-replicating (while neighbors enter the S phase). Nuclear size measurements revealed that these non-replicative cells are in the post-replicative stage (G2) rather than in the pre-replicative G1 phase, which the authors confirm with the Plant Cell Cycle Indicator (PlaCCI) fluorescent marker to track cell cycle progression in more detail. Cortex cells in the trajectory of the infection thread did not accumulate the late G2 marker of the PlaCCI nor the G2/M marker KNOLLE, indicating that these cells indeed remain in G2. Because nuclear size measurements indicated that infected cells are polyploid, the authors used the centromere histone marker CENH3 to determine chromosome number. They find that cortex cells giving rise to the nodule primordium are endomitotic and tetraploid, probably because their cell cycle is halted at centromere separation. Although not a focus of this manuscript, the authors also use their fluorescent tools to track cell cycle progression during arbuscular mycorrhiza symbiosis. They confirm that infected cells transition from a replicating to a non-replicating state (H3.1 to H3.3) with progressing development of the arbuscules. In addition, the CENH3 marker confirms previous findings that cortex cells infected by fungi are endocycling (i.e., DNA synthesis without segregation of replicated parts). This represents an important confirmation of previous findings and contrasts with the situation during nodulation symbiosis, where chromosomes separate after replication.

In my view, the part about NF-YA1 is less strong - although I realize this is a compelling candidate to be a regulator of cell cycle progression, the experimental approaches used to address this question falls a bit short, in particular, compared to the very detailed approaches shown in the rest of the manuscript. The authors show that the transcription factor NF-YA1 regulates cell division in tobacco leaves; however, there is no experimental validation in the experimental system (nodules). All conclusions are based on a heterologous cell division system in tobacco leaves. The authors state that NF-YA1 has a nodule-specific role as a regulator of cell differentiation. I am concerned the tobacco system may not allow for adequate testing of this hypothesis. With the fluorescent tools the authors have at hand (in particular tools to detect G2/M transition, which the authors suggest is regulated by NF-YA1), it would be interesting to test what happens to cell division if NF-YA1 is over-expressed in Medicago roots?

Based on NF-YA1 expression data published previously and their results in tobacco epidermal cells, the authors hypothesize that NF-YA regulates the mitotic entry of nodule primordial cells. Given that much of the manuscript deals with earlier stages of the infection, I wonder if NF-YA1 could also have a role in regulating mitotic entry in cells adjacent to the infection thread?

In general, all microscopy images are of very high quality and support the authors' conclusions. While individually each set of fluorescent markers has its limitations, combined they constitute a powerful tool to track various stages of cell cycle progression in individual root cells during symbiosis. Overall, this is a very strong manuscript that comprehensively elucidates root cell cycle changes during microbial infection.

Reviewer #2 (Public Review):

Cell cycle control during nitrogen-fixing symbiosis is an important topic, but our understanding of the process is poor and lacks resolution, as the nodule is a complex organ with many cell types that undergo profound changes. The authors aim to define the cell cycle state of individual plant cells in the emerging nodule primordium, as a transcellular infection thread passes through the meristem to reach cells deep in the incipient nodule and releases bacteria to form symbiosomes. The authors used a number of cell cycle reporters, such as different Histone 3 variants and cyclins, to follow cell cycle progress in exquisite detail. They showed that the host cells in the path of an infection thread exhibit a cell fate distinct from their immediate neighbors: after entering the S phase similar to their neighbors, these cells exit the cell cycle and enter a special differentiated state. This is likely an important shift that allows the proper passage of the infection thread. Although definitive proof needs more investigation, they showed that a pioneering transcription factor, NF-YA1, likely represses these endoreduplicated cells from completing the cell cycle.

Reviewer #1 (Public Review):

Calcium channels are key regulators of synaptic strength and plasticity, yet how these channels are differentially utilized to enable synaptic diversity is not clear. In this manuscript, the authors use new endogenous tagging of the Drosophila CaV2 channel Cac and three auxiliary subunits to investigate distinct calcium channel functions at two motor neuron subtypes at the fly NMJ, Is and Ib. Although it is clear from previous studies that Pr is higher at Is over Ib, it is not clear why. The authors confirm these differences using postsynaptic calcium imaging combined with post-hoc Cac-TdTomato imaging. Then, through a series of confocal and super resolution imaging studies, the authors describe differences in calcium channel and active zone structure between Is and Ib motor neuron terminals, and the role of Brp and homeostatic plasticity in regulating channel abundance. Finally, the authors show that while the CaBeta subunit is present at similar levels at Is and Ib active zones, there is an interesting reduction in Stj at Is active zones. The authors conclude that these differences in active zone structure and architecture contribute to the generation of the observed heterogeneity in synaptic strength.

Overall the manuscript is well written, and the successful generation of the new endogenous Cac tags (Td-Tomato, Halo) and CaBeta, stj, and stolid genes with V5 tags will be powerful reagents for the field to enable new studies on calcium channels in synaptic structure, function, and plasticity. There are also some interesting, though not entirely unexpected, findings regarding how Brp and homeostatic plasticity modulate calcium channel abundance. However, a major concern is that the conclusions about how "molecular and organization diversity generate functional synaptic heterogeneity" are not really supported by the data presented in this study. In particular, the key fact that frames this study is that Cac levels are similar at Ib and Is active zones, but that Pr is higher at Is over Ib (which was previously known). While Pr can be influenced by myriad processes, the authors should have first assessed presynaptic calcium influx - if they had, they would have better framed the key questions in this study. As the authors reference from previous studies, calcium influx is at least two-fold higher per active zone at Is over Ib, and the authors likely know that this difference is more than sufficient to explain the difference in Pr at Is over Ib. Hence, there is no reason to invoke differences in "molecular and organization diversity" to explain the difference in Pr, and the authors offer no data to support that the differences in active zone structure at Is vs Ib are necessary for the differences in Pr. Indeed, the real question the authors should have investigated is why there are such differences in presynaptic calcium influx at Is over Ib despite having similar levels/abundance of Cac. This seems the real question, and is all that is needed to explain the Pr differences shown in Fig. 1. The other changes in active zone structure and organization at Is vs Ib may very well contribute to additional differences in Pr, but the authors have not shown this in the present study, and rely on other studies (such as calcium-SV coupling at Is vs Ib) to support an argument that is not necessitated by their data. At the end of this manuscript, the authors have found an interesting possibility that Stj levels are reduced at Is vs Ib, that might perhaps contribute to the difference in calcium influx. However, at present this remains speculative.

Overall, the authors have generated powerful reagents for the field to study calcium channels and how they are regulated, but draw conclusions about active zone structure and organization contributing to functional heterogeneity that are not strongly supported by the data presented.

Reviewer #2 (Public Review):

The authors aim to investigate how voltage-gated calcium channel number, organization, and subunit composition lead to changes in synaptic activity at tonic and phasic motor neuron terminals, or type Is and Ib motor neurons in Drosophila. These neuron subtypes generate widely different physiological outputs, and many investigations have sought to understand the molecular underpinnings responsible for these differences. Additionally, these authors explore not only static differences that exist during the third-instar larval stage of development but also use a pharmacological approach to induce homeostatic plasticity to explore how these neuronal subtypes dynamically change the structural composition and organization of key synaptic proteins contributing to physiological plasticity. The Drosophila neuromuscular junction (NMJ) is glutamatergic, the main excitatory neurotransmitter in the human brain, so these findings not only expand our understanding of the molecular and physiological mechanisms responsible for differences in motor neuron subtype activity but also contribute to our understanding of how the human brain and nervous system functions.

The authors employ state-of-the-art tools and techniques such as single-molecule localization microscopy 3D STORM and create several novel transgenic animals using CRISPR to expand the molecular tools available for exploration of synaptic biology that will be of wide interest to the field. Additionally, the authors use a robust set of experimental approaches from active zone level resolution functional imaging from live preparations to electrophysiology and immunohistochemical analyses to explore and test their hypotheses. All data appear to be robustly acquired and analyzed using appropriate methodology. The authors make important advancements to our understanding of how the different motor neuron subtypes, phasic and tonic-like, exhibit widely varying electrical output despite the neuromuscular junctions having similar ultrastructural composition in the proteins of interest, voltage gated calcium channel cacophony (cac) and the scaffold protein Bruchpilot (brp). The authors reveal the ratio of brp:cac appears to be a critical determinant of release probability (Pr), and in particular, the packing density of VGCCs and availability of brp. Importantly, the authors demonstrate a brp-dependent increase in VGCC density following acute philanthotoxin perfusion (glutamate receptor inhibitor). This VGCC increase appears to be largely responsible for the presynaptic homeostatic plasticity (PHP) observable at the Drosophila NMJ. Lastly, the authors created several novel CRISPR-tagged transgenic lines to visualize the spatial localization of VGCC subunits in Drosophila. Two of these lines, CaBV5-C and stjV5-N, express in motor neurons and in the nervous system, localize at the NMJ, and most strikingly, strongly correlate with Pr at tonic and phasic-like terminals.

The few limitations in this study could be addressed with some commentary, a few minor follow-up analyses, or experiments. The authors use a postsynaptically expressed calcium indicator (mhc-Gal4>UAS -GCaMP) to calculate Pr, yet do not explore the contribution that glutamate receptors, or other postsynaptic contributors (e.g. components of the postsynaptic density, PSD) may contribute. A previous publication exploring tonic vs phasic-like activity at the drosophila NMJ revealed a dynamic role for GluRII (Aponte-Santiago et al, 2020). Could the speed of GluR accumulation account for differences between neuron subtypes?

The observation that calcium channel density and brp:cac ratio as a critical determinant of Pr is an important one. However, it is surprising that this was not observed in previous investigations of cac intensity (of which there are many). Is this purely a technical limitation of other investigations, or are other possibilities feasible? Additionally, regarding VGCC-SV coupling, the authors conclude that this packing density increases their proximity to SVs and contributes to the steeper relationship between VGCCs and Pr at phasic type Is. Is it possible that brp or other AZ components could account for these differences. The authors possess the tools to address this directly by labeling vesicles with JanellaFluor646; a stronger signal should be present at Is boutons. Additionally, many different studies have used transmission electron microscopy to explore SVs location to AZs (t-bars) at the Drosophila NMJ.

In reference to the contradictory observations that VGCC intensity does not always correlate with, or determine Pr. Previous investigations have also observed other AZ proteins or interactors (e.g. synaptotagmin mutants) critically control release, even when the correlation between cac and release remains constant while Pr dramatically precipitates.

To confirm the observations that lower brp levels results in a significantly higher cac:brp ratio at phasic-like synapses by organizing VGCCs; this argument could be made stronger by analyzing their existing data. By selecting a population of AZs in Ib boutons that endogenously express normal cac and lower brp levels, the Pr from these should be higher than those from within that population, but comparable to Is Pr. I believe the authors should also be able to correlate the cac:brp ratio with Pr from their data set generally; to determine if a strong correlation exists beyond their observation for cac correlation.

For the philanthotoxin induced changes in cac and brp localization underlying PHP, why do the authors not show cac accumulation after PhTx on live dissected preparations (i.e. in real time)? This also be an excellent opportunity to validate their brp:cac theory. Do the authors observe a dynamic change in brp:cac after 1, or 5 minutes; do Is boutons potentiate stronger due to proportional increases in cac and brp? Also regarding PhTx-induced PHP, their observations that stj and α2δ-3are more abundant at Is synapses, suggests that they may also play a role in PhTx induced changes in cac. If either/both are overexpressed during PhTx, brp should increase while cac remains constant. These accessory proteins may determine cac incorporation at AZs.<br /> Taken together this study generates important data-driven, conceptional, and theoretical advancements in our understanding of the molecular underpinnings of different motor neurons, and our understanding of synaptic biology generally. The data are robust, thoroughly analyzed, appropriately depicted. This study not only generates novel findings but also generated novel molecular tools which will aid future investigations and investigators progress in this field.

Reviewer #1 (Public Review):

This manuscript investigates how homeostatic structural plasticity and synaptic scaling act under different levels of activity suppression and how this influences the network dynamics during growth and temporary or persistent silencing. To this end, the authors first use electrophysiology and chronic imaging to investigate the influence of different levels of AMPA-receptor blockade. A smaller level leads to reduced activity and up-regulation of synapse size and number, whereas a complete block abolished activity and decreases spine numbers. Along this line, the choice to block AMPAR is unconventional and needs to be better justified as both investigated homeostatic mechanisms are known to be AMPAR dependent.

Second, this finding is transferred into a mathematical rewiring rule, where spine number shrinks, grows, and shrinks again with increasing activity. It is shown that this rule, in contrast to other, simpler rules (grow, shrink), can grow healthy networks from scratch only if additional stimulation is provided. Continuing with these stable networks, the activity of a sub-network is increased, decreased, or silenced by modulating an external stimulation to the neurons. Whereas both activity and connectivity return to a stable state for small alteration, complete silencing leads to disconnection of the silenced network parts. Recovery from this can be achieved by restoring stimulation before the connectivity has completely decayed or by adding sufficiently fast synaptic scaling, although both cases can lead to unhealthy activity. A more systematic assessment of this interaction between scaling and homeostatic rewiring revealed a minimal timescale ratio that is needed for recovery. This is an important step towards disentangling the necessity of multiple, seemingly redundant mechanisms. Yet, in the simulations, the role of recurrent connectivity versus external inputs should be investigated in more detail in order to ensure the generality of the finding that a recovery of the activity is impossible for the presented rewiring rule without synaptic scaling.

Overall, the combination of experiments and simulations is a promising approach to investigating network self-organization. The gradual blocking of activity is especially valuable to inform mathematical models and distinguish them from alternatives. Here, the simulation results clearly demonstrate that the experimentally informed rule exhibits qualitatively different dynamics including the need for another homeostatic mechanism. However, a better connection between the simulations and experiment two would be desirable. In particular, it is unclear whether the model would actually reproduce the experiment, to which other experiments the model results relate, and which experimentally testable predictions the model makes.

In summary, this manuscript makes a valuable contribution to discerning the mathematical shape of a homeostatic structural plasticity model and understanding the necessity of synaptic scaling in the same network. Both experimental and computational methods are solid and well-described. Yet, both parts could be linked better in order to obtain conclusions with more impact and generality.

Reviewer #2 (Public Review):

This manuscript by Lu et al addresses the understudied interplay between structural and functional changes underlying homeostatic plasticity. Using hippocampal organotypic slice cultures allowing chronic imaging of dendritic spines, the authors showed that partial or complete inhibition of AMPA-type glutamate receptors differentially affects spine density, respectively leading to an increase or decrease of spines. Based on that dataset, they built a model where activity-dependent synapse formation is regulated by a biphasic rule and tested it in stimulation- or deprivation-induced homeostatic plasticity. The model matches experimental data (from the authors and the literature) quite well, and provides a framework within which functional and structural changes coexist to regulate firing rate homeostasis.

While the correlation between changes in AMPAR numbers and in spine number/size has been well characterized during Hebbian plasticity, the situation is much less clear in homeostatic plasticity due to multiple studies yielding diverging results. This manuscript adds new experimental results to the existing data and presents a valuable effort to generate a model that can explain these divergences in a unifying and satisfactory framework.

The model and its successive implantation steps are well presented along a clear thread. However, it would have benefited from having an actual timeline of structural changes throughout the three days of AMPAR inhibition, especially as their experimental model allows it. This would have provided additional information on spine dynamics (especially transient spines) and on the respective timescale of the structural and functional changes, and thus led to a better-informed model.

Additionally, the model would have been strengthened by an experimental dataset with homeostatic plasticity induced by higher activity (e.g. with bicuculline). To the best of my knowledge, there is currently no data on structural plasticity following scaling down, and it is also known that scaling up and down are mediated by different molecular pathways. The extension of the model from scaling up (in response to silencing) to scaling down (in response to increased activity) offers an interesting perspective but may be a bit of a stretch.

Finally, the authors are very specific in their definition and distinction of structural and functional homeostatic plasticity for their model. Structural plasticity is limited to spine density and functional plasticity to synaptic scaling, which allows the authors to discuss the interplay between very distinct "synapse number-based structural plasticity" and "synaptic weight-based synaptic scaling", and appears to bypass the fact that spine size regulates the space available for AMPARs at the synapse and thus synaptic weight. The authors are of course aware of the importance of changes in spine size, as they present some intriguing data showing that spine size is differentially affected by partial or complete inhibition of AMPARs and include the putative role of spine size changes in the discussion. However, spine size does not seem to be taken into account in their network simulations, which present synaptic scaling and structural plasticity as completely distinct processes. While the model still offers interesting insights into the interaction of these processes, it would have benefited from a less stringent distinction; this choice and the reasons behind it should be made more explicit in the manuscript.

Reviewer #1 (Public Review):

In the manuscript, the authors explore the mechanism by which Taenia solium larvae may contribute to human epilepsy. This is extremely important question to address because T. solium is a significant cause of epilepsy and is extremely understudied. Advances in determining how T. solium may contribute to epilepsy could have significant impact on this form of epilepsy. Excitingly, the authors convincingly show that Taenia larvae contain and release glutamate sufficient to depolarize neurons and induce recurrent excitation reminiscent of seizures. They use a combination of cutting-edge tools including electrophysiology, calcium and glutamate imaging, and biochemical approaches to demonstrate this important advance. They also show that this occurs in neurons from both mice and humans. This is relevant for pathophysiology of chronic epilepsy development. This study does not rule out other aspects of T. solium that may also contribute to epilepsy, including immunological aspects, but demonstrates a clear potential role for glutamate.

Strengths:

- The authors examine not only T. solium homogenate, but also excretory/secretory products which suggests glutamate may play a role in multiple aspects of disease progression.<br /> - The authors confirm that the human relevant pathogen also causes neuronal depolarization in human brain tissue<br /> - There is very high clinical relevance. Preventing epileptogenesis/seizures possibly with Glu-R antagonists or by more actively removing glutamate as a second possible treatment approach in addition to/replacing post-infection immune response.<br /> - Effects are consistent across multiple species (rat, mouse, human) and methodological assays (GluSnFR AND current clamp recordings AND Ca imaging)<br /> - High K content (comparable levels to high-K seizure models) of larvae could have also caused depolarization. Adequate experiments to exclude K and other suspected larvae contents (i.e. Substance P).

Weaknesses:

- Acute study is limited to studying depolarization in slices and it is unclear what is necessary/sufficient for in vivo seizure generation or epileptogenesis for chronic epilepsy.<br /> - There is likely a significant role of the immune system that is not explored here. This issue is adequately addressed in the discussion, however, and the glutamate data is considered in this context.

Discuss impact:

- Interfering with peri-larval glutamate signaling may hold promise to prevent ictogenesis and chronic epileptogenesis as this is a very understudied cause of epilepsy with unknown mechanistic etiology.<br /> Additional context for interpreting significance:<br /> - High medical need as most common adult onset epilepsy in many parts of the world.

Reviewer #2 (Public Review):

Since neurocysticercosis is associated with epilepsy, the authors wish to establish how cestode larvae affect neurons. The underlying hypothesis is that the larvae may directly excite neurons and thus favor seizure genesis.

To test this hypothesis, the authors collected biological materials from larvae (from either homogenates or excretory/secretory products), and applied them to hippocampal neurons (rats and mice) and human cortical neurons.

This constitutes a major strength of the paper, providing a direct reading of larvae's biological effects. Another strength is the combination of methods, including patch clamp, Ca, and glutamate imaging.

There are some weaknesses:

1) The main one relates to the statement: "Together, these results indicate that T. crassiceps larvae homogenate results not just in a transient depolarization of cells in the immediate vicinity of application, but can also trigger a wave of excitation that propagates through the brain slice in both space and time. This demonstrates that T. crassiceps homogenate can initiate seizure-like activity under suitable conditions."<br /> The only "evidence" of propagation is an image at two time points. It is one experiment, and there is no quantification. Either increase n's and perform a quantification, or remove such a statement.<br /> Likewise, there is no evidence of seizure genesis. A single cell recording is shown. The presence of a seizure-like event should be evaluated with field recordings.

2) Control puff experiments are lacking for Fig 1. Would puffing ACSF also produce a depolarization, and even firing, as suggested in Fig. 2D? This is needed for at least one species.

3) What is the rationale to use a Cs-based solution? Even in the presence of TTX and with blocking K channels, the depolarization may be sufficient to activate Ca channels (LVGs), which would further contribute to the depolarization. Why not perform voltage clamp recordings to directly the current?

4) Why did you use organotypic slices? Since you wish to model adult epilepsy, it would have been more relevant to use fresh slices from adult rats/mice. At least, discuss the caveat of using a network still in development in vitro.

5) Please include both the number of slices and number of cells recorded in each condition. This is the standard (the number of cells is not enough).

6) Please provide a table with the basic properties of cells (Rin, Rs, etc.). This is standard to assess the quality of the recordings.

7) Please provide a table on patient's profile. This is standard when using human material. Were these TLE cases (and "control" cortex) or epileptogenic cortex?

Globally, the authors achieved their aims. They show convincingly that larvae material can depolarize neurons, with glutamate (and aspartate) as the most likely candidates.<br /> This is important not only because it provides mechanistic insight but also potential therapeutic targets. The result is impactful, as the authors use quasi-naturalistic conditions, to assess what might happen in the human brain. The experimental design is appropriate to address the question. It can be replicated by any interested person.

Reviewer #3 (Public Review):

This paper has high significance because it addresses a prevalent parasitic infection of the nervous system, Neurocysticercosis (NCC). The infection is caused by larvae of the parasitic cestode Taenia solium It is a leading cause of epilepsy in adults worldwide

To address the effects of cestode larvae, homogenates and excretory/secretory products of larvae were added to organotypic brain slice cultures of rodents or layer 2/3 of human cortical brain slices from patients with refractory epilepsy.

A self-made pressure ejection system was used to puff larvae homogenate (20 ms puff) onto the soma of patched neurons. The mechanical force could have caused depolarizaton so a vehicle control is critical. On line 150 they appear to have used saline in this regard, and clarification would be good. Were the controls here (and aCSF elsewhere) done with the low Mg2+o aCSF like the larvae homogenates?

They found that neurons depolarized after larvae homogenate exposure and the effect was mediated by glutamate but not nicotinic receptors for acetylcholine (nAChRs), acid-sensing channels or substance P. To address nAChRs, they used 10uM mecamyline, and for ASICs 2mM amiloride which seems like a high concentration. Could the concentrations be confirmed for their selectivity? Glutamate receptor antagonists, used in combination, were 10uM CNQX, 50uM DAP5, and 2mM kynurenic acid. These concentrations are twice what most use. Please discuss. Also, it would be very interesting to know if the glutamate receptor is AMPA, Kainic acid, or NMDA. Were metabotropic antagonists ever tested? That would be logical because CNQX/DAPR/Kynurenic acid did not block all of the depolarization.

They also showed the elevated K+ in the homogenate (~11 mM) could not account for the depolarization. However, the experiment with K+ was not done in a low Mg2+o buffer (Or was it -please clarify). They also confirmed that only small molecules led to the depolarization after filtering out very large molecules. That supports the conclusion that glutamate - which is quite small - could be responsible.

It is logical to test substance P because the Intro points out prior work links the larvae and seizures by inflammation and implicates substance P. However, why focus on nAChRs and ASIC?

The depolarizations caused seizure-like events in slices. The slices were exposed to a proconvulant buffer though- low Mg2+o. This buffer can cause spontaneous seizure-like events so it is important to know what the buffer did alone.

They suggest the effects could underlie seizure generation in NCC. However, there is only one event that is seizure-like in the paper and it is just an inset. Were others similar? How frequency were they? How long?

Using Glutamate-sensing fluorescent reporters they found the larvae contain glutamate and can release it, a strength of the paper.

Fig. 4. Could an inset be added to show the effects are very fast? That would support an effect of glutamate.

Why is aspartate relatively weak and glutamate relatively effective as an agonist?

Could some of the variability in Fig 4G be due to choice of different cell types? That would be consistent with Fig 5B where only a fraction of cells in the culture showed a response to the larvae nearby.

On what basis was the ROI drawn in Fig. 5B.

Also in 5B, I don't see anything in the transmitted image. What should be seen exactly?

Human brain slices were from temporal cortex of patients with refractory epilepsy. Was the temporal cortex devoid of pathology and EEG abnormalities? This area may be quite involved in the epilepsy because refractory epilepsy that goes to surgery is often temporal lobe epilepsy. Please discuss the liitations of studying the temporal cortex of humans with epilepsy since it may be more susceptible to depolarizations of many kinds, not just larvae.

Please discuss the limitations of the cultures - they are from very young animals and cultured for 6-14 days.

Reviewer #1 (Public Review):

The manuscript describes an interesting experiment in which an animal had to judge a duration of an interval and press one of two levers depending on the duration. The Authors recorded activity of neurons in key areas of the basal ganglia (SNr and striatum), and noticed that they can be divided into 4 types.

I would like to thank the Authors for performing the analyses I suggested in my previous review - I found their results very interesting and surprising. This is a very interesting and impressive paper.

Reviewer #2 (Public Review):

In this valuable manuscript Li & Jin record from the substantial nigra and dorsal striatum to identify subpopulations of neurons with activity that reflects different dynamics during action selection, and then use optogenetics in transgenic mice to selectively inhibit or excite D1- and D2- expressing spiny projection neurons in the striatum, demonstrating a causal role for each in action selection in an opposing manner. They argue that their findings cannot be explained by current models and propose a new 'triple control' model instead, with one direct and two indirect pathways. These findings will be of broad interest to neuroscientists, but lacks some direct evidence for the proposal of the new model.

Overall there are many strengths to this manuscript including the fact that the empirical data in this manuscript is thorough and the experiments are well-designed.

Reviewer #2 (Public Review):

The manuscript by Bohl et al. is an interesting and carefully done study on the biochemical properties and mode of action of potent autonomous AAA+ disaggregase ClpL from Listeria monocytogenes. ClpL is encoded on plasmids. It shows high thermal stability and provides Listeria monocytogenes food-pathogen substantial increase in resistance to heat. The authors show that ClpL interacts with aggregated proteins through the aromatic residues present in its N-terminal domain and subsequently unfolds proteins from aggregates translocating polypeptide chains through the central pore in its oligomeric ring structure. The structure of ClpL oligomers was also investigated in the manuscript. The results suggest that mono-ring structure and not dimer or trimer of rings, observed in addition to mono-ring structures under EM, is an active species of disaggregase.

Presented experiments are conclusive and well-controlled. Several mutants were created to analyze the importance of a particular ClpL domain.

The study's strength lies in the direct comparison of ClpL biochemical properties with autonomous ClpG disaggregase present in selected Gram-negative bacteria and well-studied E. coli system consisting of ClpB disaggregase and DnaK and its cochaperones. This puts the obtained results in a broader context.

Reviewer #1 (Public Review):

Summary:<br /> This work describes the mechanism of protein disaggregation by the ClpL AAA+ protein of Listeria monocytogenes. Using several model subtrate proteins the authors first show that ClpL possesses a robust disaggregase activity that does not further require the endogenous DnaK chaperone in vitro. In addition, they found that ClpL is more thermostable than the endogenous L. monocytogenes DnaK and has the capacity to unfold tightly folded protein domains. The mechanistic basis for the robust disaggregase activity of ClpL was also dissected in vitro and in some cases, supported by in vivo data performed in chaperone-deficient E. coli strains. The data presented show that the two AAA domains, the pore-2 site and the N-terminal domain (NTD) of ClpL are critical for its disaggregase activity. Remarkably, grafting the NTD of ClpL to ClpB converted ClpB into an autonomous disaggregase, highlighting the importance of such a domain in the DnaK-independent disaggregation of proteins. The role of the ClpL NTD domain was further dissected, identifying key residues and positions necessary for aggregate recognition and disaggregation. Finally, using sets of SEC and negative staining EM experiments combined with conditional covalent linkages and disaggregation assays the authors found that ClpL shows significant structural plasticity, forming dynamic hexameric and heptameric active single rings that can further form higher assembly states via their middle domains.

Strengths:<br /> The manuscript is well-written and the experimental work is well executed. It contains a robust and complete set of in vitro data that push further our knowledge of such important disaggregases. It shows the importance of the atypical ClpL N-terminal domain in the disaggregation process as well as the structural malleability of such AAA+ proteins. More generally, this work expands our knowledge of heat resistance in bacterial pathogens.

Weaknesses:<br /> There is no specific weakness in this work, although it would have helped to have a drawing model showing how ClpL performs protein disaggregation based on their new findings. The function of the higher assembly states of ClpL remains unresolved and will need further extensive research. Similarly, it will be interesting in the future to see whether the sole function of the plasmid-encoded ClpL is to cope with general protein aggregates under heat stress.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript details the characterization of ClpL from L. monocytogenes as a potent and autonomous AAA+ disaggregase. The authors demonstrate that ClpL has potent and DnaK-independent disaggregase activity towards a variety of aggregated model substrates and that this disaggregase activity appears to be greater than that observed with the canonical DnaK/ClpB co-chaperone. Furthermore, Lm ClpL appears to have greater thermostability as compared to Lm DnaK, suggesting that ClpL-expressing cells may be able to withstand more severe heat stress conditions. Interestingly, Lm ClpP can provide thermotolerance to E. coli that have been genetically depleted of either ClpB or in cells expressing a mutant DnaK103. The authors further characterized the mechanisms by which ClpL interacts with protein aggregates, identifying that the N-terminal domain of ClpL is essential for disaggregase function. Lastly, by EM and mutagenesis analysis, the authors report that ClpL can exist in a variety of larger macromolecular complexes, including dimer or trimers of hexamers/heptamers, and they provide evidence that the N-terminal domains of ClpL prevent dimer ring formation, thus promoting an active and substrate-binding ClpL complex. Throughout this manuscript the authors compare Lm ClpL to ClpG, another potent and autonomous disaggregase found in gram-negative bacteria that have been reported on previously, demonstrating that these two enzymes share homologous activity and qualities. Taken together this report clearly establishes ClpL as a novel and autonomous disaggregase.

Strengths:<br /> The work presented in this report amounts to a significant body of novel and significant work that will be of interest to the protein chaperone community. Furthermore, by providing examples of how ClpL can provide in vivo thermotolerance to both E. coli and L. gasseri the authors have expanded the significance of this work and provided novel insight into potential mechanisms responsible for thermotolerance in food-borne pathogens.

Weaknesses:<br /> The figures are clearly depicted and easy to understand, though some of the axis labeling is a bit misleading or confusing and may warrant revision. While I do feel that the results and discussion as presented support the authors' hypothesis and overall goal of demonstrating ClpL as a novel disaggregase, interpretation of the data is hindered as no statistical tests are provided throughout the manuscript. Because of this only qualitative analysis can be made, and as such many of the concluding statements involving pairwise comparisons need to be revisited or quantitative data with stats needs to be provided. The addition of statistical analysis is critical and should not be difficult, nor do I anticipate that it will change the conclusions of this report.

Reviewer #1 (Public Review):

Summary: The manuscript offers a commendable exploration into the relationship between plasma omega-6/omega-3 fatty acid ratios and mortality outcomes.

Strengths: The chosen study design and analytical techniques align well with the research objectives, and the results resonate with existing literature.

Weaknesses: Lack of information on the selection criteria for participants; 5. The analysis of individual PUFAs is not appropriate; The definition of comorbidities is vague; The rationale of conducting the mediation analysis of blood biomarkers is not given.

Reviewer #2 (Public Review):

Summary: This study utilized a large sample from the UK Biobank which enhanced statistical robustness, employed a prospective design to establish clear temporal relationships, used objective biomarkers for assessing plasma omega-6/omega-3 ratio, and investigated various mortality causes including CVD and cancer for a holistic health understanding.

Strengths: The authors used a large sample size, employed a prospective design, and investigated various mortality.

Weaknesses: Analyzing n-3 and n-6 PUFAs separately might be less instructive. It might not be methodologically sound to treat TG, HDL, LDL, and apolipoproteins as mediators. It's imperative to exercise caution when drawing causal conclusions from the observed correlations. The manuscript might propose potential research trajectories.

Reviewer #3 (Public Review):

Summary: The authors are trying to find out whether the levels of omega-6 and omega-3 fatty acids in the blood are linked to the likelihood of dying from anything, of dying from cancer and of dying from cardiovascular disease. They use a large dataset called UK Biobank where fatty acid levels were measured in blood at the start of the study and what happened to the participants over the following years (average of 12.7 years) was followed. They find that both omega-6 AND omega-3 fatty acids were linked with less likelihood of dying from anything, from cancer and from cardiovascular disease. The effects of omega-3s were stronger. They then made a ratio of omega-6 to omega-3 fatty acids and found that as that ratio increased risk of dying also increased,. This supports the idea that omega-3s have stronger effects than omega-6s.

Strengths: This is a large study (over 85,000 participants) with a good follow up period (average 12.7 years). Using blood levels of fatty acids is superior to using estimated dietary intakes. The authors take account of many variables that could interfere with the findings (confounding variables) - they do this using statistical methods.

Weaknesses: There are several omega-6 and omega-3 fatty acids - it is not clear which ones were actually measured in this study.

Reviewer #1 (Public Review):

Summary:

Zanzibar archipelago is close to achieving malaria elimination, but despite the implementation of effective control measures, there is still a low-level seasonal malaria transmission. This could be due to the frequent importation of malaria from mainland Tanzania and Kenya, reservoirs of asymptomatic infections, and competent vectors. To investigate population structure and gene flow of P. falciparum in Zanzibar and mainland Tanzania, they used 178 samples from mainland Tanzania and 213 from Zanzibar that were previously sequenced using molecular inversion probes (MIPs) panels targeting single nucleotide polymorphisms (SNPs). They performed Principal Component Analysis (PCA) and identity by descent (IBD) analysis to assess genetic relatedness between isolates. Parasites from coastal mainland Tanzania contribute to the genetic diversity in the parasite population in Zanzibar. Despite this, there is a pattern of isolation by distance and microstructure within the archipelago, and evidence of local sharing of highly related strains sustaining malaria transmission in Zanzibar that are important targets for interventions such as mass drug administration and vector control, in addition to measures against imported malaria.

Strengths:

This study presents important samples to understand population structure and gene flow between mainland Tanzania and Zanzibar, especially from the rural Bagamoyo District, where malaria transmission persists and there is a major port of entry to Zanzibar. In addition, this study includes a larger set of SNPs, providing more robustness for analyses such as PCA and IBD. Therefore, the conclusions of this paper are well supported by data.

Weaknesses:

Some points need to be clarified:<br /> 1) SNPs in linkage disequilibrium (LD) can introduce bias in PCA and IBD analysis. Were SNPs in LD filtered out prior to these analyses?<br /> 2) Many IBD algorithms do not handle polyclonal infections well, despite an increasing number of algorithms that are able to handle polyclonal infections and multiallelic SNPs. How polyclonal samples were handled for IBD analysis?

Reviewer #2 (Public Review):

Summary:

This manuscript describes P. falciparum population structure in Zanzibar and mainland Tanzania. 282 samples were typed using molecular inversion probes. The manuscript is overall well-written and shows a clear population structure. It follows a similar manuscript published earlier this year, which typed a similar number of samples collected mostly in the same sites around the same time. The current manuscript extends this work by including a large number of samples from coastal Tanzania, and by including clinical samples, allowing for a comparison with asymptomatic samples.

The two studies made overall very similar findings, including strong small-scale population structure, related infections on Zanzibar and the mainland, near-clonal expansion on Pemba, and frequency of markers of drug resistance. Despite these similarities, the previous study is mentioned a single time in the discussion (in contrast, the previous research from the authors of the current study is more thoroughly discussed). The authors missed an opportunity here to highlight the similar findings of the two studies.

Strengths:

The overall results show a clear pattern of population structure. The finding of highly related infections detected in close proximity shows local transmission and can possibly be leveraged for targeted control.

Weaknesses:

A number of points need clarification:

It is overall quite challenging to keep track of the number of samples analyzed. I believe the number of samples used to study population structure was 282 (line 141), thus this number should be included in the abstract rather than 391. It is unclear where the number 232 on line 205 comes from, I failed to deduct this number from supplementary table 1.

Also, Table 1 and Supplementary Table 1 should be swapped. It is more important for the reader to know the number of samples included in the analysis (as given in Supplementary Table 1) than the number collected. Possibly, the two tables could be combined in a clever way.

Methods<br /> The authors took the somewhat unusual decision to apply K-means clustering to GPS coordinates to determine how to combine their data into a cluster. There is an obvious cluster on Pemba islands and three clusters on Unguja. Based on the map, I assume that one of these three clusters is mostly urban, while the other two are more rural. It would be helpful to have a bit more information about that in the methods. See also comments on maps in Figures 1 and 2 below.

Following this point, in Supplemental Figure 5 I fail to see an inflection point at K=4. If there is one, it will be so weak that it is hardly informative. I think selecting 4 clusters in Zanzibar is fine, but the justification based on this figure is unclear.

For the drug resistance loci, it is stated that "we further removed SNPs with less than 0.005 population frequency." Was the denominator for this analysis the entire population, or were Zanzibar and mainland samples assessed separately? If the latter, as for all markers <200 samples were typed per site, there could not be a meaningful way of applying this threshold. Given data were available for 200-300 samples for each marker, does this simply mean that each SNP needed to be present twice?

Discussion:<br /> I was a bit surprised to read the following statement, given Zanzibar is one of the few places that has an effective reactive case detection program in place: "Thus, directly targeting local malaria transmission, including the asymptomatic reservoir which contributes to sustained transmission (Barry et al., 2021; Sumner et al., 2021), may be an important focus for ultimately achieving malaria control in the archipelago (Björkman & Morris, 2020)." I think the current RACD program should be mentioned and referenced. A number of studies have investigated this program.

The discussion states that "In Zanzibar, we see this both within and between shehias, suggesting that parasite gene flow occurs over both short and long distances." I think the term 'long distances' should be better defined. Figure 4 shows that highly related infections rarely span beyond 20-30 km. In many epidemiological studies, this would still be considered short distances.

Lines 330-331: "Polymorphisms associated with artemisinin resistance did not appear in this population." Do you refer to background mutations here? Otherwise, the sentence seems to repeat lines 324. Please clarify.

Line 344: The opinion paper by Bousema et al. in 2012 was followed by a field trial in Kenya (Bousema et al, 2016) that found that targeting hotspots did NOT have an impact beyond the actual hotspot. This (and other) more recent finding needs to be considered when arguing for hotspot-targeted interventions in Zanzibar.

Figures and Tables:<br /> Table 2: Why not enter '0' if a mutation was not detected? 'ND' is somewhat confusing, as the prevalence is indeed 0%.

Figure 1: Panel A is very hard to read. I don't think there is a meaningful way to display a 3D-panel in 2D. Two panels showing PC1 vs. PC2 and PC1 vs. PC3 would be better. I also believe the legend 'PC2' is placed in the wrong position (along the Y-axis of panel 2).

Supplementary Figure 2B suffers from the same issue.

The maps for Figures 1 and 2 don't correspond. Assuming Kati represents cluster 4 in Figure 2, the name is put in the wrong position. If the grouping of shehias is different between the Figures, please add an explanation of why this is.

Figure 2: In the main panel, please clarify what the lines indicate (median and quartiles?). It is very difficult to see anything except the outliers. I wonder whether another way of displaying these data would be clearer. Maybe a table with medians and confidence intervals would be better (or that data could be added to the plots). The current plots might be misleading as they are dominated by outliers.

In the insert, the cluster number should not only be given as a color code but also added to the map. The current version will be impossible to read for people with color vision impairment, and it is confusing for any reader as the numbers don't appear to follow any logic (e.g. north to south).

The legend for Figure 3 is difficult to follow. I do not understand what the difference in binning was in panels A and B compared to C.

Font sizes for panel C differ, and it is not aligned with the other panels.

Why is Kusini included in Supplemental Figure 4, but not in Figure 1?

Supplemental Figures 6 and 7: What does the width of the line indicate?

What was the motivation not to put these lines on the map, as in Figure 4A? This might make it easier to interpret the data.

Reviewer #1 (Public Review):

The overall tone of the rebuttal and lack of responses on several questions was surprising. Clearly, the authors did not appreciate the phrase 'no smoking gun' and provided a lengthy repetition of the fair argument about 'ticking boxes' on the classic list of criteria. They also make repeated historical references that descriptions of neurotransmitters include many papers, typically over decades, e.g. in the case of ACh and its discovery by Sir Henry Dale. While I empathize with the authors' apparent frustration (I quote: '...accept the reality that Rome was not built in a single day and that no transmitter was proven by a one single paper') I am a bit surprised at the complete brushing away of the argument, and in fact the discussion. In the original paper, the notion of a receptor was mentioned only in a single sentence and all three reviewers brought up this rather obvious question. The historical comparisons are difficult: Of course many papers contribute to the identification of a neurotransmitter, but there is a much higher burden of proof in 2023 compared to the work by Otto Loewi and Sir Henry Dale: most, if not all, currently accepted neurotransmitter have a clear biological function at the level of the brain and animal behavior or function - and were in fact first proposed to exist based on a functional biological experiment (e.g. Loewi's heart rate change). This, and the isolation of the chemical that does the job, were clear, unquestionable 'smoking guns' a hundred years ago. Fast forward 2023: Creatine has been carefully studied by the authors to tick many of the boxes for neurotransmitters, but there is no clear role for its function in an animal. The authors show convincing effects upon K+ stimulation and electrophysiological recordings that show altered neuronal activity using the slc6a8 and agat mutants as well as Cr application - but, as has been pointed out by other reviewers, these effects are not a clear-cut demonstration of a chemical transmitter function, however many boxes are ticked. The identification of a role of a neurotransmitter for brain function and animal behavior has reasonably more advanced possibilities in 2023 than a hundred years ago - and e.g. a discussion of approaches for possible receptor candidates should be possible.

Again, I reviewed this positively and agree that a lot of cumulative data are great to be put out there and allow the discovery to be more broadly discussed and tested. But I have to note, that the authors simply respond with the 'Rome was not built in a single day' statement to my suggestions on at least 'have some lead' how to approach the question of a receptor e.g. through agonists or antagonists (while clearly stating 'I do not think the publication of this manuscript should not be made dependent' on this). Similarly, in response to reviewer 2's concerns about a missing receptor, the authors' only (may I say snarky) response is ' We have deleted this sentence, though what could mediate postsynaptic responses other than receptors?' The bullet point by reviewer 3 ' • No candidate receptor for creatine has been identified postsynaptically.' is the one point by that reviewer that is simply ignored by the authors completely. Finally, I note that my reivew question on the K stimulation issues (e.g. 35 neurons that simply did not respond at all) was: ' Response: To avoid the disadvantage of K stimulation, we also performed optogenetic experiments recently and obtained encouraging preliminary results.' No details, not data - no response really.

In sum, I find this all a bit strange and the rebuttal surprising - all three reviewers were supportive and have carefully listed points of discussion that I found all valid and thoughtful. In response, the authors selectively responded scientifically to some experimental questions, but otherwise simply rather non-scientifically dismissed questions with 'Rome was not built in a day'-type answers, or less. I my view, the authors have disregarded the review process and the effort of three supportive reviewers, which should be part of the permanent record of this paper.

Reviewer #2 (Public Review):

Bian et al studied creatine (Cr) in the context of central nervous system (CNS) function. They detected Cr in synaptic vesicles purified from mouse brains with anti-Synaptophysin using capillary electrophoresis-mass spectrometry. Cr levels in the synaptic vesicle fraction was reduced in mice lacking the Cr synthetase AGAT, or the Cr transporter SLC6A8. They provide evidence for Cr release within several minutes after treating brain slices with KCl. This KCl-induced Cr release was partially calcium dependent and was attenuated in slices obtained from AGAT and SLC6A8 mutant mice. Cr application also decreased the excitability of cortical pyramidal cells in one third of the cells tested. Finally, they provide evidence for SLC6A8-dependent Cr uptake into synaptosomes, and ATP-dependent Cr loading into synaptic vesicles. Based on these data, the authors propose that Cr may act as neurotransmitter in the CNS.

Strengths:

1. A major strength of the paper is the broad spectrum of tools used to investigate Cr.<br /> 2. The study provides evidence that Cr is present in/loaded into synaptic vesicles.

Weaknesses (resubmission):

1. There is no significant decrease in Cr content pulled down by anti-Syp in AGAT-/- mice when normalized to IgG controls. Hence, blocking AGAT activity/Cr synthesis does not affect Cr levels in the synaptic vesicle fraction, arguing against a Cr enrichment.<br /> 2. There is no difference in KCl-induced Cr release between SLC6A8-/Y and SLC6A8+/Y when normalizing the data to the respective controls. Thus, the data are not consistent with the idea that depolarization-induced Cr release requires SLC6A8.<br /> 3. The rationale of grouping the excitability data into responders and non-responders is not convincing because the threshold of 10% decrease in AP rate is arbitrary. The data do therefore not support the conclusion that Cr reduces neuronal excitability.

Reviewer #3 (Public Review):

SUMMARY:

The manuscript by Bian et al. promotes the idea that creatine is a new neurotransmitter. The authors conduct an impressive combination of mass spectrometry (Fig. 1), genetics (Figs. 2, 3, 6), biochemistry (Figs. 2, 3, 8), immunostaining (Fig. 4), electrophysiology (Figs. 5, 6, 7), and EM (Fig. 8) in order to offer support for the hypothesis that creatine is a CNS neurotransmitter.

STRENGTHS:

There are many strengths to this study.

• The combinatorial approach is a strength. There is no shortage of data in this study.<br /> • The careful consideration of specific criteria that creatine would need to meet in order to be considered a neurotransmitter is a strength.<br /> • The comparison studies that the authors have done in parallel with classical neurotransmitters is helpful.<br /> • Demonstration that creatine has inhibitory effects is another strength.<br /> • The new genetic mutations for Slc6a8 and AGAT are strengths and potentially incredibly helpful for downstream work.

WEAKNESSES:

• Some data are indirect. Even though Slc6a8 and AGAT are helpful sentinels for the presence of creatine, they are not creatine themselves. Of note, these molecules themselves are not essential for making the case that creatine is a neurotransmitter.<br /> • Regarding Slc6a8, it seems to work only as a reuptake transporter - not as a transporter into SVs. Therefore, we do not know what the transporter into the TVs is.<br /> • Puzzlingly, Slc6a8 and AGAT are in different cells, setting up the complicated model that creatine is created in one cell type and then processed as a neurotransmitter in another. This matter will likely need to be resolved in future studies.<br /> • No candidate receptor for creatine has been identified postsynaptically. This will likely need to be resolved in future studies.<br /> • Because no candidate receptor has been identified, it is important to fully consider other possibilities for roles of creatine that would explain these observations other than it being a neurotransmitter? There is some attention to this in the Discussion.

There are several criteria that define a neurotransmitter. The authors nicely delineated many criteria in their discussion, but it is worth it for readers to do the same with their own understanding of the data.

By this reviewer's understanding (and combining some textbook definitions together) a neurotransmitter: 1) must be present within the presynaptic neuron and stored in vesicles; 2) must be released by depolarization of the presynaptic terminal; 3) must require Ca2+ influx upon depolarization prior to release; 4) must bind specific receptors present on the postsynaptic cell; 5) exogenous transmitter can mimic presynaptic release; 6) there exists a mechanism of removal of the neurotransmitter from the synaptic cleft.

For a paper to claim that the published work has identified a new neurotransmitter, several of these criteria would be met - and the paper would acknowledge in the discussion which ones have not been met. For this particular paper, this reviewer finds that condition 1 is clearly met.

Conditions 2 and 3 seem to be met by electrophysiology, but there are caveats here. High KCl stimulation is a blunt instrument that will depolarize absolutely everything in the prep all at once and could result in any number of non-specific biological reactions as a result of K+ rushing into all neurons in the prep. Moreover, the results in 0 Ca2+ are puzzling. For creatine (and for the other neurotransmitters), why is there such a massive uptick in release, even when the extracellular saline is devoid of calcium?

Condition 4 is not discussed in detail at all. In the discussion, the authors elide the criterion of receptors specified by Purves by inferring that the existence of postsynaptic responses implies the existence of receptors. True, but does it specifically imply the existence of creatinergic receptors? This reviewer does not think that is necessarily the case. The authors should be appropriately circumspect and consider other modes of inhibition that are induced by activation or potentiation of other receptors (e.g., GABAergic or glycinergic).

Condition 5 may be met, because authors applied exogenous creatine and observed inhibition. However, this is tough to know without understanding the effects of endogenous release of creatine. if they were to test if the absence of creatine caused excess excitation (at putative creatinergic synapses), then that would be supportive of the same. Nicely, Ghirardini et al., 2023 study cited by the reviewers does provide support for this exact notion in pyramidal neurons.

For condition 6, the authors made a great effort with Slc6a8. This is a very tough criterion to understand or prove for many synapses and neurotransmitters.

In terms of fundamental neuroscience, the story should be impactful. There are certainly more neurotransmitters out there than currently identified and by textbook criteria, creatine seems to be one of them taking all of the data in this study and others into account.

Reviewer #1 (Public Review):

Bolumar et al. isolated and characterized EV subpopulations, apoptotic bodies (AB), Microvesicles (MV), and Exosomes (EXO), from endometrial fluid through the female menstrual cycle. By performing DNA sequencing, they found the MVs contain more specific DNA sequences than other EVs, and specifically, more mtDNA were encapsulated in MVs. They also found a reduction of mtDNA content in the human endometrium at the receptive and post-receptive period that is associated with an increase in mitophagy activity in the cells, and a higher mtDNA content in the secreted MVs was found at the same time. Last, they demonstrated that the endometrial Ishikawa cell-derived EVs could be taken by the mouse embryos and resulted in altered embryo metabolism.

This is a very interesting study and is the first one demonstrating the direct transmission of maternal mtDNA to embryos through EVs.

Reviewer #2 (Public Review):

In Bolumar, Moncayo-Arlandi et al. the authors explore whether endometrium-derived extracellular vesicles contribute DNA to embryos and therefore influence embryo metabolism and respiration. The manuscript combines techniques for isolating different populations of extracellular vesicles, DNA sequencing, embryo culture, and respiration assays performed on human endometrial samples and mouse embryos.

Vesicle isolation is technically difficult and therefore collection from human samples is commendable. Also, the influence of maternally derived DNA on the bioenergetics of embryos is unknown and therefore novel.

Reviewer #2 (Public Review):

This study investigates how genes in the Gr28 family of gustatory receptors function in the taste system of Drosophila larvae. Gr28 genes are intriguing because they have been implicated in taste as well as other functions, such as sensing temperature and ultraviolet light. This study makes several new findings. First, the authors show that four Gr28 genes are expressed in putative taste neurons, and these neurons can be largely divided into subsets that express Gr28a versus Gr28bc. The authors then demonstrate that these two neuronal subsets drive opposing behaviors (attraction versus avoidance) when activated. The avoidance-promoting neurons respond to bitter compounds and are required for bitter avoidance, and Gr28bc and Gr28ba were specifically implicated in bitter detection in these cells. Together, these findings provide insight into the complexity of taste receptor expression and function in Drosophila, even within a single receptor subfamily.

The conclusions are well-supported by the experimental data. Strengths of the paper include the use of precise genetic tools, thorough analyses of expression patterns, carefully validated behavioral assays, and well-controlled functional imaging experiments. The role of Gr28bc neurons is more thoroughly explored than that of Gr28a neurons. However, a previous study from the same lab (Mishra et al., 2018) showed that Gr28a neurons detect RNA and ribose, which are attractive to larvae. Presumably this is the attractive response that is being recapitulated upon artificial activation of Gr28a neurons.

Reviewer #1 (Public Review):

Ahn and Amrein characterize the expression of members of the Gr28 family of gustatory receptors in taste neurons in the Drosophila melanogaster larva, define the behaviorally-relevant ligands for these receptors, and use chemogenetic experiments to show, strikingly, that different neurons have opposite behavioral responses to the chemogenetic ligand. They go on to show what neurons need to be silenced to lose responses to bitters, and very nicely show what subunits of the Gr28 bitter receptors are necessary and sufficient for responses to bitters. This is a nice piece of work, rigorously carried out, that tackles the neurons and receptors that drive innate responses to tastants in Drosophila larvae.

The authors have revised the paper to address all of my recommendations. The new cartoons are extremely clear and I appreciate the more measured language when discussing the hypothetical structure and stoichiometry of the functional GR complex.

Reviewer #1 (Public Review):

Summary:<br /> The study examines the role of release site clearance in synaptic transmission during repetitive activity under physiological conditions in two types of central synapses, calyx of Held and hippocampal CA1 synapses. After the acute block of endocytosis by pharmacology, deeper synaptic depression or less facilitation was observed in two types of synapses. Acute block of CDC42 and actin polymerization, which possibly inhibits the activity of Intersectin, affected synaptic depression at the calyx synapse, but not at CA1 synapses. The data suggest an unexpected, fast role of the site clearance in counteracting synaptic depression.

Strengths:<br /> The study uses an acute block of the molecular targets with pharmacology together with precise electrophysiology. The experimental results are clear-cut and convincing. The study also examines the physiological roles of the site clearance using action potential-evoked transmission at physiological Ca and physiological temperature at mature animals. This condition has not been examined.

Weaknesses:<br /> Pharmacology may have some off-target effects, though acute manipulation should be appreciated. Although this is a hard question and difficult to address experimentally, reagents may affect synaptic vesicle mobilization to the release sites directly in addition to blocking endocytosis.

Reviewer #3 (Public Review):

General comments:

(1) While Dynasore and Pitstop-2 may impede release site clearance due to an arrest of membrane retrieval, neither Latrunculin-B nor ML-141 specifically acts on AZ scaffold proteins. Interference with actin polymerization may have a number of consequences many of which may be unrelated to release site clearance. Therefore, neither Latrunculin-B nor ML-141 can be considered suitable tools for specifically identifying the role of AZ scaffold proteins (i.e. ELKS family proteins, Piccolo, Bassoon, α-liprin, Unc13, RIM, RBP, etc) in release site clearance which was defined as one of the principal aims of this study.

(2) Initial EPSC amplitudes more than doubled in the presence of Dynasor at hippocampal SC->CA1 synapses (Figure S2). This unexpected result raises doubts about the specificity of Dynasor as a tool to selectively block SV endocytosis.

(3) In this study, the application of Dynasore and Pitstop-2 strongly decreases 100 Hz steady-state release at calyx synapses while - quite unexpectedly - strongly accelerates recovery from depression. A previous study found that genetic ablation of dynamin-1 actually enhanced 300 Hz steady-state release while only little affecting recovery from depression (Mahapatra et al., 2016). A similar scenario holds for the Latrunculin-B effects: In this study, Latrunculin-B strongly increased steady-state depression while in Babu et al. (2020), Latrunculin-B did not affect steady-state depression. In Mahapatra et al. (2016), Latrunculin-B marginally enhanced steady-state depression. The authors need to make a serious attempt to explain all these seemingly contradicting results.

(4) The experimental conditions need to be better specified. It is not clear which recordings were obtained in 1.3 mM and which (if any?) in 2 mM external Ca. It is also unclear whether 'pooled data' are presented (obtained from control recordings and from separate recordings after pre-incubation with the respective drugs), or whether the data actually represent 'before'/'after' comparisons obtained from the same synapses after washing in the respective drugs. The exact protocol of drug application (duration of application/pre-incubation?, measurements after wash-out or in the continuous presence of the drugs?) needs to be clearly described in the methods and needs to be briefly mentioned in Results and/or Figure legends.

(5) The authors compare results obtained in calyx with those obtained in SC->CA1 synapses which they considered examples for 'fast' and 'slow' synapses, respectively. There is little information given to help readers understand why these two synapse types were chosen, what the attributes 'fast' and 'slow' refer to, and how that may matter for the questions studied here. I assume the authors refer to the maximum frequency these two synapse types are able to transmit rather than to EPSC kinetics?

(6) Strong presynaptic stimuli such as those illustrated in Figures 1B and C induce massive exocytosis. The illustrated Cm increase of 2 to 2.5 pF represents a fusion of 25,000 to 30,000 SVs (assuming a single SV capacitance of 80 aF) corresponding to a 12 to 15% increase in whole terminal membrane surface (assuming a mean terminal capacitance of ~16 pF). Capacitance measurements can only be considered reliable in the absence of marked changes in series and membrane conductance. Since the data shown in Figs. 1 and 3 are central to the argumentation, illustration of the corresponding conductance traces is mandatory. Merely mentioning that the first 450 ms after stimulation were skipped during analysis is insufficient.

(7) It is essential for this study to preclude a contamination of the results with postsynaptic effects (AMPAR saturation and desensitization). AMPAR saturation limits the amplitudes of initial responses in EPSC trains and hastens the recovery from depression due to a 'ceiling effect'. AMPAR desensitization occludes paired-pulse facilitation and reduces steady-state responses during EPSC trains while accelerating the initial recovery from depression. The use of, for example, 1 mM kynurenic acid in the bath is a well-established strategy to attenuate postsynaptic effects at calyx synapses. All calyx EPSC recordings should have been performed under such conditions. Otherwise, recovery time courses and STP parameters are likely contaminated by postsynaptic effects. Since the effects of AMPAR saturation on EPSC_1 and desensitization on EPSC_ss may partially cancel each other, an unchanged relative STD in the presence of kynurenic acid is not necessarily a reliable indicator for the absence of postsynaptic effects. The use of kynurenic acid in the bath would have had the beneficial side effect of massively improving voltage-clamp conditions. For the typical values given in this MS (10 nA EPSC, 3 MOhm Rs) the expected voltage escape is ~30 mV corresponding to a change in driving force of 30 mV/80 mV=38%, i.e. initial EPSCs in trains are likely underestimated by 38%. Such large voltage escape usually results in unclamped INa(V) which was suppressed in this study by routinely including 2 mM QX-314 in the pipette solution. That approach does, however, not reduce the voltage escape.

(8) In the Results section (pages 7 and 8), the authors analyze the time course into STD during 100 Hz trains in the absence and presence of drugs. In the presence of drugs, an additional fast component is observed which is absent from control recordings. Based on this observation, the authors conclude that '... the mechanisms operate predominantly at the beginning of synaptic depression'. However, the consequences of blocking or slowing site clearing are expected to be strongly release-dependent. Assuming a probability of <20% that a fusion event occurs at a given release site, >80% of the sites cannot be affected at the arrival of the second AP even by a total arrest of site clearance simply because no fusion has yet occurred. That number decreases during a train according to (1-0.2)^n, where n is the number of the AP, such that after 10 APs, ~90% of the sites have been used and may potentially be unavailable for new rounds of release after slowing site clearance. Perhaps, the faster time course into STD in the presence of the drugs isn't related to site clearance?

(9) In the Discussion (page 10), the authors present a calculation that is supposed to explain the reduced size of the second calyx EPSC in a 100 Hz train in the presence of Dynasore or Pitstop-2. Does this calculation assume that all endocytosed SVs are immediately available for release within 10 ms? Please elaborate.

(10) It is not clear, why the bafilomycin/folimycin data is presented in Fig. S5. The data is also not mentioned in the Discussion. Either explain the purpose of these experiments or remove the data.

(11) The scheme in Figure 7 is not very helpful.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Mahapatra and Takahashi report on the physiological consequences of pharmacologically blocking either clathrin and dynamin function during compensatory endocytosis or of the cortical actin scaffold both in the calyx of Held synapse and hippocampal boutons in acute slice preparations

Strengths:<br /> Although many aspects of these pharmacological interventions have been studied in detail during the past decades, this is a nice comprehensive and comparative study, which reveals some interesting differences between a fast synapse (Calyx of Held) tuned to reliably transmit at several 100 Hz and a more slow hippocampal CA1 synapse. In particular, the authors find that acute disturbance of the synaptic actin network leads to a marked frequency-dependent enhancement of synaptic depression in the Calyx, but not in the hippocampal synapse. This striking difference between both preparations is the most interesting and novel finding.

Weaknesses:<br /> Unfortunately, however, these findings concerning the different consequences of actin depolymerization are not sufficiently discussed in comparison to the literature. My only criticism concerns the interpretation of the ML 141 and Lat B data. With respect to the Calyx data, I am missing a detailed discussion of the effects observed here in light of the different RRP subpools SRP and FRP. This is very important since Lee et al. (2012, PNAS 109 (13) E765-E774) showed earlier that disruption of actin inhibits the rapid transition of SRP SVs to the FRP at the AZ. The whole literature on this important concept is missing. Likewise, the role of actin for the replacement pool at a cerebellar synapse (Miki et al., 2016) is only mentioned in half a sentence. There is quite some evidence that actin is important both at the AZ (SRP to FRP transition, activation of replacement pool) and at the peri-active zone for compensatory endocytosis and release site clearance. Both possible underlying mechanisms (SRP to FRP transition or release site clearance) should be better dissected.

Reviewer #1 (Public Review):

Summary:

o A well-executed series of experiments that will likely be of immense interest to (a) vector-borne disease researchers and (b) gram-negative sepsis/bacteremia researchers. The study uses comparative transcriptomics to begin probing what makes Peromyscus leucopus a unique host for numerous pathogens across the tree of life. Authors responded well to concerns raised in peer review and have produced an excellent second version of the manuscript.

Strengths:

o Use of outbred M. musculus is a commendable choice for the studies here.<br /> o Use of both LPS and B. hermsii allows analysis of multiple different signaling pathways that may differ between the species.<br /> o Upload of analyzed data onto Dryad is appreciated.

Weaknesses:

o None noted beyond the authors own limitation discussion section

Reviewer #2 (Public Review):

Milovic, Duong, and Barbour investigate the inflammatory response of three species of small mammals (P. leucopus, M. musculus, and R. norvegicus) to endotoxin lipopolysaccharide (LPS) injection via genome-wide transcriptomics from blood samples. Understanding the inflammation response of P. leucopus is of importance as they are a reservoir for several pathogens. The study is a thorough, controlled, well researched analysis that will be valuable for designing and interpreting future studies. The authors discuss the limitations of the data and the potential directions. Clearly P. leucopus respond differently to the LPS exposure which is very interesting and opens the door for numerous other comparative studies.

The conclusions of the manuscript are thoughtful and supported by the data. The authors addressed my questions about mouse numbers, sex differences, and the presentation of Nos2 and Arg1 data.

Reviewer #1 (Public Review):

The manuscript by Lin, Sosnick et al investigates the functional conformational dynamics of two members of the SLC26 family of anion transporters (Prestin and SLC26A9). A key aspect of the work is that the authors use HDX-MS to convincingly identify that the folding of the unstable anion binding site is related to the fast electromechanical changes that are important for the function of Prestin. In good apparent agreement, such folding-related changes upon anion binding are absent in the related non-piezoelectric SLC26A9 that does not exhibit similar electro-motile transport. Overall, I find the work very interesting and generally well carried out - and it should be of considerable interest to researchers studying transmembrane transporters or just membrane proteins in general.

Reviewer #2 (Public Review):

In this manuscript, Xiaoxuan Lin and colleagues provide new insights into the dynamics of prestin using H/D exchange coupled with mass spectrometry. The authors aim to reveal how local changes in folding upon anion binding sustain the unique electro-transduction capabilities of prestin.

Prestin is an unusual member of the SLC26 family, that changes its cross-sectional area in the membrane upon binding of a chloride ion. In contrast to SLC26 homologs, prestin is not an anion transporter per se but requires an anion to sense voltage. Binding of Cl- at a conserved binding site located between the end of TM3 and TM10 drives the displacement of a conserved arginine (R399), that causes major conformational changes, transmitting the voltage sensing into a mechanical force exerted on the membrane.

Cryo-EM structures are available for the protein bound to various anions, including Cl-, but these structures do not explain how a conserved couple of positive (R399) and negative (the Cl- anion) charge pair transforms voltage sensitivity into mechanical changes in the membrane. To address this challenge, the authors explore local dynamics of the anion binding site and compare it with that of a "real" anion transporter SLC26A9. The authors make a convincing case that the differences in local dynamics they measure are the molecular basis for voltage sensing and its translation into electromotility.

Practically the authors make a thorough HDX-MS investigation of prestin in the presence of different anions Cl-, SO4-, salicylate as well as in the apo form, and provide insight mostly on local dynamics of the anion binding site. The experiments are well-designed and conducted and their quality and reproducibility allows for quantitative interpretation by deriving ΔΔG values of changes in dynamics at specific sites. Furthermore, the authors show by comparing the apo condition with Cl- bound condition that the absence of Cl- causes fraying of the TM3 and TM10 helices. They deduce that Cl- binding allows for directional helix structuration, leading to local structural changes that cause a rearrangement of the charge configuration at the anion binding site that lays the molecular basis for voltage sensitivity. They demonstrate based on a detailed analysis of their HDX data that such helix fraying is a specific feature of the binding site and differs from the cooperative unfolding happening elsewhere on the prestin.

However, the main question that the authors are addressing is how voltage sensitivity translates at the molecular level in the requirement for a negative-positive charge pair. The interpretation that the binding site instability observed only for prestin is a feature required for this voltage dependent is a bit speculative. Could other lines of evidence support the claim that the charge ion gap is reduced upon Cl- binding and that this leads to cross-section area expansion? An obvious option that comes to mind is MD simulations There are differences in time-scale between HDX and simulations, but the propensity for H-bond destabilization can be quantified even at short timescales. It might be that such data is already available out there but it should be explicit in the discussion. The discussion section itself is a bit narrow in scope at the moment. Discussing the data in the context of the available structures would help the non-specialist reader.

Reviewer #3 (Public Review):

Synopsis:<br /> The lack of visualizing the dynamic nature of biomolecules is a major weakness of crystallography or electron microscopy to study structure-function relationship of proteins. Such a challenge can be exemplified by the case of prestin, which shares high structural similarity to SLC26A9 anion transporter but is not an ion transporter. In this study, Lin et al aimed to use hydrogen-deuterium exchange and mass spectrometry (HDX-MS) to investigate the mobility of prestin and its response to anions. The authors exploited the nature of anion-dependent folding of this type of transporter to systematically analyze the mobility of transmembrane helices of both transporters by HDX. The authors found that the anion-binding helices engage in the stabilization of the anion-binding site. When stripped from Cl-, the site exposes to the transporter's extracellular side. More importantly, the authors narrowed down TM3 and TM10 with experimental data supporting the notion of R399's unique role in prestin's function. The results thus provide a working model of how the charged residue works in conjunction with the cooperativity of helix unfolding at the anion-binding site to drive the electromotive force of prestin.

Strengths:<br /> The use of HDX-MS to probe the dynamic nature of prestin is a major strength of this study, which provides experimental evidence revealing the global and local differences in the folding events between prestin and SLC26A9. The mass experimental data led to the identification of TM3 and TM10 as the primary contributors to the folding changes, as well as a calculation of ΔΔG of ~2.4 kcal/mol, within the thermodynamic range of the dipole between the two helices. The latter also suggests the role of R399 as previously speculated in cryo-EM structures.

This study went further to dissect the cooperativity during the folding and unfolding events on TM3, in which the authors observed a helix fraying at the anion-binding site and cooperative unfolding at the distal lipid-facing helices. This provides strong evidence of why prestin can undergo fast electromechanical rearrangement.

Weakness:<br /> The authors tried to investigate the allostery by probing the intermediate folding/unfolding states by using sulfate or salicylate in the absence of chloride. Sulfate-bound proteins appear in an apo state earlier than normal chloride binding, and salicylate treatment led to a stable TMD state with slower HDX. It is unclear from the data (Fig 4) how the allostery works without titrating chloride ions into the reaction. The sulfate or salicylate experiments seem to show two extreme folding events outside the normal chloride conditions.

TM3 and TM10 contribute to the anion-binding site together, and the authors beautifully showed the cooperativity of TM3. Does TM10 show the same cooperativity in prestin and SLC26A9? In addition, it is unclear whether the folding model at the anion-binding helices (Fig. 5B) remains the same when expressing prestin on live cells, such as thermodynamic data derived from electrophysiology studies.

The authors observed increased stability upon chloride binding at the subunit interface in the cytosol for both prestin and SLC26A9 (Fig 1). How does this similarity in the cytosolic region contribute to the differential mechanisms as seen in the TMD in both transporters? It is unclear in this version of the manuscript.

Reviewer #1 (Public Review):

This study provides compelling evidence that RAR, rather than its obligate dimerization partner RXR, is functionally limiting for chromatin binding. This manuscript provides a paradigm for how to dissect the complicated regulatory networks formed by dimerizing transcription factor families.

Dahal and colleagues use advanced SMT techniques to revisit the role of RXR in DNA-binding of the type-2 nuclear receptor (T2NR) RAR. The dominant consensus model for regulated DNA binding of T2NRs posits that they compete for a limited pool of RXR to form an obligate T2NR-RXR dimer. Using advanced SMT and proximity-assisted photoactivation technologies, Dahal et al. now test the effect of manipulating the endogenous pool size of RAR and RXR on heterodimerization and DNA-binding in live U2OS cells. Surprisingly, it turns out that RAR, rather than RXR, is functionally limiting for heterodimerization and chromatin binding. By inference, the relative pool size of various T2NRs expressed in a given cell, rather than RXR, is likely to determine chromatin binding and transcriptional output.

The conclusions of this study are well supported by the experimental results and provide unexpected novel insights into the functioning of the clinically important class of T2NR TFs. Moreover, the presented results show how the use of novel technologies can put long-standing theories on how transcription factors work upside down. This manuscript provides a paradigm for how to further dissect the complicated regulatory networks formed by T2NRs or other dimerizing TFs. I found this to be a complete story that does not require additional experimental work. However, I do have some suggestions for the authors to consider.

Reviewer #2 (Public Review):

Summary:<br /> In the manuscript "Surprising Features of Nuclear Receptor Interaction Networks Revealed by Live Cell Single Molecule Imaging", Dahal et al combine fast single molecule tracking (SMT) with proximity-assisted photoactivation (PAPA) to study the interaction between RARa and RXRa. The prevalent model in the nuclear receptor field suggests that type II nuclear receptors compete for a limiting pool of their partner RXRa. Contrary to this, the authors find that over-expression of RARa but not RXRa increases the fraction of RXRa molecules bound to chromatin, which leads them to conclude that the limiting factor is the abundance of RARa and not RXRa. The authors also perform experiments with a known RARa agonist, all trans retinoic acid (atRA) which has little effect on the bound fraction. Using PAPA, they show that chromatin binding increases upon dimerization of RARa and RXRa.

Strengths:<br /> In my view, the biggest strength of this study is the use of endogenously tagged RARa and RXRa cell lines. As the authors point out, most previous studies used either in vitro assays or over-expression. I commend the authors on the generation of single-cell clones of knock-in RARa-Halo and Halo-RXRa. The authors then carefully measure the abundance of each protein using FACS, which is very helpful when comparing across conditions. The manuscript is generally well written and figures are easy to follow. The consistent color-scheme used throughout the manuscript is very helpful.

Weaknesses:<br /> 1. Agonist treatment:<br /> The authors test the effect of all trans retinoic acid (atRA) on the bound fraction of RARa and RXRa and find that "These results are consistent with the classic model in which dimerization and chromatin binding of T2NRs are ligand independent." However, all the agonist treatments are done in media containing FBS. FBS is not chemically defined and has been found to have between 10 and 50 nM atRA (see references in PMID 32359651 for example). The addition of 1 nM or 100 nM atRA is unlikely to result in a strong effect since the medium already contains comparable or higher levels of agonist. To test their hypothesis of ligand-independent dimerization, the authors should deplete the media of atRA by growing the cells in a medium containing charcoal-stripped FBS for at least 24 hours before adding agonist.

2. Photobleaching and its effect on bound fraction measurements:<br /> The authors discard the first 500 to 1000 frames due to the high localization density in the initial frames. This will preferentially discard bound molecules that will bleach in the initial frames of the movie and lead to an over-estimation of the unbound fraction.

For experiments with over-expression of RAR-Halo and Halo-RXR, the authors state that the cells were pre-bleached and that these frames were used to calculate the mean intensity of the nuclei. When pre-bleaching, bound molecules will preferentially bleach before the diffusing population. This will again lead to an over-representation of the unbound fraction since this is the population that will remain relatively unaffected by the pre-bleaching. Indeed, the bound fraction for over-expressed RARa and RXRa is significantly lower than that for the corresponding knock in lines. To confirm whether this is a biological result, I suggest that the authors either reduce the amount of dye they use so that this pre-bleaching is not necessary or use the direct reactivation strategy they use for their PAPA experiments to eliminate the pre-bleaching step.

As for the measurement of the nuclear intensity, since the authors have access to multiple HaloTag dyes, they can saturate the HaloTagged proteins with a high concentration of JF646 or JFX650 to measure the mean intensity of the protein while still using the PA-JFX549 for SMT. Together, these will eliminate the need to pre-bleach or discard any frames.

3. Heterogeneous expression of the SNAP fusion proteins:<br /> The cell lines expressing SNAP tagged transgenes shown in Fig S6 have very heterogeneous expression of the SNAP proteins. While the bulk measurements done by Western blotting are useful, while doing single-cell experiments (especially with small numbers - ~20 - of cells), it is important to control for expression levels. Since these transgenic stable lines were not FACS sorted, it would be helpful for the reader to know the spread in the distribution of mean intensities of the SNAP proteins for the cells that the SMT data are presented for. This step is crucial while claiming the absence of an effect upon over-expression and can easily be done with a SNAPTag ligand such as SF650 using the procedure outlined for the over-expressed HaloTag proteins.

4. Definition of bound molecules:<br /> The authors state that molecules with a diffusion coefficient less than 0.15 um2/s are considered bound and those between 1-15 um2/s are considered unbound. Clarification is needed on how this threshold was determined. In previous publications using saSPT, the authors have used a cutoff of 0.1 um2/s (for example, PMID 36066004, 36322456). Do the results rely on a specific cutoff? A diffusion coefficient by itself is only a useful measure of normal diffusion. Bound molecules are unlikely to be undergoing Brownian motion, but the state array method implemented here does not seem to account for non-normal diffusive modes. How valid is this assumption here?

5. Movies:<br /> Since this is an imaging manuscript, I request the authors to provide representative movies for all the presented conditions. This is an essential component for a reader to evaluate the data and for them to benchmark their own images if they are to try to reproduce these findings.

6. Definition of an ROI:<br /> The authors state that "ROI of random size but with maximum possible area was selected to fit into the interior of the nuclei" while imaging. However, the readout speed of the Andor iXon Ultra 897 depends on the size of the defined ROI. If the ROI was variable for every movie, how do the authors ensure the same sampling rate?

Reviewer #3 (Public Review):

Summary:<br /> This study aims to investigate the stoichiometric effect between core factors and partners forming the heterodimeric transcription factor network in living cells at endogenous expression levels. Using state-of-the-art single-molecule analysis techniques, the authors tracked individual RARα and RXRα molecules labeled by HALO-tag knock-in. They discovered an asymmetric response to the overexpression of counter-partners. Specifically, the fact that an increase in RARα did not lead to an increase in RXRα chromatin binding is incompatible with the previous competitive core model. Furthermore, by using a technique that visualizes only molecules proximal to partners, they directly linked transcription factor heterodimerization to chromatin binding.

Strengths:<br /> The carefully designed experiments, from knock-in cell constructions to single-molecule imaging analysis, strengthen the evidence of the stoichiometric perturbation response of endogenous proteins. The novel finding that RXR, previously thought to be a target of competition among partners, is in excess provides new insight into key factors in dimerization network regulation. By combining the cutting-edge single-molecule imaging analysis with the technique for detecting interactions developed by the authors' group, they have directly illustrated the relationship between the physical interactions of dimeric transcription factors and chromatin binding. This has enabled interaction analysis in live cells that was challenging in single-molecule imaging, proving it is a powerful tool for studying endogenous proteins.

Weaknesses:<br /> As the authors have mentioned, they have not investigated the effects of other T2NRs or RXR isoforms. These invisible factors leave room for interpretation regarding the origin of chromatin binding of endogenous proteins (Recommendations 4). In the PAPA experiments, overexpressed factors are visualized, but changes in chromatin binding of endogenous proteins due to interactions with the overexpressed proteins have not been investigated. This might be tested by reversing the fluorescent ligands for the Sender and Receiver. Additionally, the PAPA experiments are likely to be strengthened by control experiments (Recommendations 5).

Reviewer #1 (Public Review):

Major concerns:

1. Is the direct binding of MCAK to the microtubule cap important for its in vivo function?

a. The authors claim that their "study provides mechanistic insights into understanding the end-binding mechanism of MCAK". I respectfully disagree. My concern is that the paper offers limited insights into the physiological significance of direct end-binding for MCAK activity, even in vitro. The authors estimate that in the absence of other proteins in vitro, ~95% of MCAK molecules arrive at the tip by direct binding in the presence of ~ physiological ATP concentration (1 mM). In cells, however, the major end-binding pathway may be mediated by EB, with the direct binding pathway contributing little to none. This is a reasonable concern because the apparent dissociation constant measured by the authors shows that MCAK binding to microtubules in the presence of ATP is very weak (69 uM). This concern should be addressed by 1) calculating relative contributions of direct and EB-dependent pathways based on the affinities measured in this and other published papers and estimated intracellular concentrations. Although there are many unknowns about these interactions in cells, a modeling-based analysis may be revealing. 2) the recapitulation of these pathways using purifying proteins in vitro is also feasible. Ideally, some direct evidence should be provided, e.g. based on MCAK function-separating mutants (GDP-Pi tubulin binding vs. catalytic activity at the curled protofilaments) that contribution from the direct binding of MCAK to microtubule cap in EB presence is significant.

b. As mentioned in the Discussion, preferential MCAK binding to tubulins near the MT tip may enhance MCAK targeting of terminal tubulins AFTER the MCAK has been "delivered" to the distal cap via the EB-dependent mechanism. This is a different targeting mechanism than the direct MCAK-binding. However, the measured binding affinity between MCAK and GMPCPP tubulins is so weak (69 uM), that this effect is also unlikely to have any impact because the binding events between MCAK and microtubule should be extremely rare. Without hard evidence, the arguments for this enhancement are very speculative.

2. The authors do not provide sufficient justification and explanation for their investigation of the effects of different nucleotides in MCAK binding affinity. A clear summary of the nucleotide-dependent function of MCAK (introduction with references to prior affinity measurements and corresponding MCAK affinities), the justifications for this investigation, and what has been learned from using different nucleotides (discussion) should be provided. My take on these results is that by far the strongest effect on microtubule wall and tip binding is achieved by adding any adenosine, whereas differences between different nucleotides are relatively minor. Was this expected? What can be learned from the apparent similarity between ATP and AMPPNP effects in some assays (Fig 1E, 4C, etc) but not others (Fig 1D,F, etc)?

3. It is not clear why the authors decided to use these specific mutant MCAK proteins to advance their arguments about the importance of direct tip binding. Both mutants are enzymatically inactive. Both show roughly similar tip interactions, with some (minor) differences. Without a clear understanding of what these mutants represent, the provided interpretations of the corresponding results are not convincing.

4. GMPCPP microtubules are used in the current study to represent normal dynamic microtubule ends, based on some published studies. However, there is no consensus in the field regarding the structure of growing vs. GMPCPP-stabilized microtubule ends, which additionally may be sensitive to specific experimental conditions (buffers, temperature, age of microtubules, etc). To strengthen the authors' argument, Taxol-stabilized microtubules should be used as a control to test if the effects are specific. Additionally, the authors should consider the possibility that stronger MCAK binding to the ends of different types of microtubules may reflect MCAK-dependent depolymerization events on a very small scale (several tubulin rows). These nano-scale changes to tubulins and the microtubule end may lead to the accumulation of small tubulin-MCAK aggregates, as is seen with other MAPs and slowly depolymerizing microtubules. These effects for MCAK may also depend on specific nucleotides, further complicating the interpretation. This possibility should be addressed because it provides a different interpretation than presented in the manuscript.

5. It would be helpful if the authors provided microtubule polymerization rates and catastrophe frequencies for assays with dynamic microtubules and MCAK in the presence of different nucleotides. The video recordings of microtubules under these conditions are already available to the authors, so it should not be difficult to provide these quantifications. They may reveal that microtubule ends are different (or not) under the examined conditions. It would also help to increase the overall credibility of this study by providing data that are easy to compare between different labs.

6. Are there other published studies that report MCAK binding affinity to microtubules? I find it quite surprising that the authors have reported the apparent dissociation constant for MCAK as 1mM. Such a high Kd value suggests no interaction under normal conditions, given that the intracellular concentrations of most proteins are orders of magnitude lower. If this information is inaccurate, it raises questions about the accuracy of other quantifications in the study.

7. Experimental and data analysis techniques are described superficially, and in some cases, only references to the prior work by others are provided. More direct evidence for these techniques and the corresponding controls should be provided.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Chen et al. investigate the localization of microtubule kinesin-13 MCAK to the microtubule ends. MCAK is a prominent microtubule depolymerase whose molecular mechanisms of action have been extensively studied by a number of labs over the last ~twenty years. Here, the authors use single-molecule approaches to investigate the precise localization of MCAK on growing microtubules and conclude that MCAK preferentially binds to a GDP-Pi-tubulin portion of the microtubule end. The conclusions are speculative and not well substantiated by the data, making the impact of the study in its current form rather limited. Specifically, greater effort should be made to define the region of MCAK binding on microtubule ends, as well as its structural characteristics. Given that MCAK has been previously shown to effectively tip-track growing microtubule ends through an established interaction with EB proteins, the physiological relevance of the present study is unclear. Finally, the manuscript does not cite or properly discuss a number of relevant literature references, the results of which should be directly compared and contrasted to those presented here.

Reviewer #3 (Public Review):

The authors revisit an old question of how MCAK goes to microtubule ends, partially answered by many groups over the years. The authors seem to have omitted the literature on MCAK in the past 10-15 years. The novelty is limited due to what has previously been done on the question. Previous work showed MCAK targets to microtubule plus-ends in cells through association with EB proteins and Kif18b (work from Wordeman, Medema, Walczak, Welburn, Akhmanova) but none of their work is cited.

It is not obvious in the paper that these in vitro studies only reveal microtubule end targeting, rather than plus end targeting. MCAK diffuses on the lattice to both ends and its conformation and association with the lattice and ends has also been addressed by other groups-not cited here. I want to particularly highlight the work from Friel's lab where they identified a CDK phosphomimetic mutant close to helix4 which reduces the end preference of MCAK. This residue is very close to the one mutated in this study and is highly relevant because it is a site that is phosphorylated in vivo. This study and the mutant produced here suggest a charge-based recognition of the end of microtubules.

Here the authors analyze this MCAK recognition of the lattice and microtubule ends, with different nucleotide states of MCAK and in the presence of different nucleotide states for the microtubule lattice. The main conclusion is that MCAK affinity for microtubules varies in the presence of different nucleotides (ATP and analogs) which was partially known already. How different nucleotide states of the microtubule lattice influence MCAK binding is novel. This information will be interesting to researchers working on the mechanism of motors and microtubules. However, there are some issues with some experiments. In the paper, the authors say they measure MCAK residency of growing end microtubules, but in the kymographs, the microtubules don't appear dynamic- in addition, in Figure 1A, MCAK is at microtubule ends and does not cause depolymerization. I would have expected to see depolymerization of the microtubule after MCAK targeting. The MCAK mutants are not well characterized. Do they still have ATPase activity? Are they folded? Can the authors also highlight T537 and discuss this?

Finally, a few experiments are done with MCAK and XMAP215, after the authors say they have demonstrated the binding sites overlap. The data supporting this statement were not obvious and the conclusions that the effect of the two molecules are additive would argue against competing binding sites. Overall, while there are some interesting quantitative measurements of MCAK on microtubules - in particular in relation to the nucleotide state of the microtubule lattice - the insights into end-recognition are modest and do not address or discuss how it might happen in cells. Often the number of events is not recorded. Histograms with large SEM bars are presented, so it is hard to get a good idea of data distribution and robustness. Figures lack annotations. This compromises therefore their quantifications and conclusions. The discussion was hard to follow and needs streamlining, as well as putting their work in the context of what is known from other groups who produced work on this in the past few years.

Reviewer #1 (Public Review):

This work provides new mechanistic insights into the competitive inhibition in the mammalian P2X7 receptors using structural and functional approaches. The authors solved the structure of panda (pd) P2X7 in the presence of the classical competitive antagonists PPNDS and PPADS. They find that both drugs bind to the orthosteric site employed by the physiological agonist ATP. However, owing to the presence of a single phosphate group, they prevent movements in the flipper domain required for channel opening. The authors performed structure-based mutational analysis together with electrophysiological characterization to understand the subtype-specific binding of these drugs. It is known from previous studies that P2X1 and P2X3 are more sensitive to these drugs as compared to P2X7, hence, the residues adjacent to the ATP binding site in pdP2X7 were mutated to those present in P2X1. They observed that mutations of Q143, I214, and Q248 into lysine (hP2X1) increased the P2X7 sensitivity to PPNDS, whereas in P2X1, mutations of these lysines to alanine reduced sensitivity to PPNDS, suggesting that these key residues contribute to the subunit-specific sensitivity to these drugs. Similar experiments were done in hP2X3 to demonstrate its higher sensitivity to PPNDS. This preprint provides a useful framework for developing subtype-specific drugs for the family of P2X receptor channels, an area that is currently relatively unexplored.

The conclusions of the paper are mostly well supported, but need some clarification for the following:

1) Why was the crystallization construct of panda P2X7 used for structural studies instead of rat P2X7 with the cytoplasmic ballast which is a more complete receptor that is closely related to the human receptor? Can the authors provide a justification for this choice?

2) Was there a good reason why hP2X1 and hP2X3 currents were recorded in perforated patches, whereas pdP2X7 currents were recorded using the whole-cell configuration? It seems that the extent of rundown is less of a problem with perforated patch recordings. Can the authors comment and perhaps provide a justification? It would also be good to present data for repeated applications of ATP alone using protocols similar to those for testing antagonists so the reader can better appreciate the extent of run down with different recording configurations for the different receptors.

3) The data in Fig. S1, panel A shows multiple examples where the currents activated by ATP after removal of the antagonist are considerably smaller than the initial ATP application. Is this due to rundown or incomplete antagonist unbinding? It is interesting that this wasn't observed with hP2X1 and hP2X3 even though they have a higher affinity for the antagonist. Showing examples of rundown without antagonist application would help to distinguish these distinct phenomena and it would be good for the authors to comment on this in the text. It is also curious why a previous study on pdP2X7 did not seem to have problems with rundown (see Karasawa and Kawate. eLife, 2016).

4) The written presentation could be improved as there are many instances where the writing lacks clarity and the reader has to guess what the authors wish to communicate.

Reviewer #2 (Public Review):

Summary:<br /> P2X receptors play pivotal roles in physiological processes such as neurotransmission and inflammation, making them promising drug targets. This study, through cryo-EM and functional experiments, reveals the structural basis of the competitive inhibition of the PPNDS and PPADS on mammalian P2X7 receptors. Key findings include the identification of the orthosteric site for these antagonists, the revelation of how PPADS/PPNDS binding impedes channel-activating conformational changes, and the pinpointing of specific residues in P2X1 and P2X3 subtypes that determine their heightened sensitivity to these antagonists. These insights present a comprehensive understanding that could guide the development of improved drugs targeting P2X receptors. This work will be a valuable addition to the field.

Strengths and weaknesses:<br /> The combination of structural experiments and mutagenesis analyses offers a deeper understanding of the mechanism. While the inclusion of MD simulation is appreciated, providing more insights from the simulation might further strengthen this already compelling story.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Schmassmann et al. present a study on the immune microenvironment of grade 4 gliomas using single-cell RNA-seq data from the tumor center, periphery, and peripheral blood of patients. This manuscript is overall well written and reads easily. The approach to studying the TME at various spatial locations is innovative and interesting, and the dataset presented has the potential to become a useful resource for the community. However, the size of the dataset, notably in the context of the important inter-patient variability on key clinical information, hinders the generalizability of the results. The analysis presented by the authors seems at times somewhat shallow as compared to other studies in the literature, being almost solely based on the analysis of a single dataset with extremely limited biological validation of the observations, and some claims made by the authors do not seem appropriately backed by the data they present. While I appreciate the vast analysis effort undertaken by the authors, it seems more work is required to make the most of this interesting dataset and substantiate the conclusions.

Strengths:<br /> The authors have provided useful insights into diverse GBMs (IDH mutant and IDH wild-type) that provide a deep assessment of individual tumors with spatial information.

Weaknesses:<br /> A larger set of tumors will need to be explored before general principles of immune biology and GBM immune evasion can be uncovered. This is a descriptive study that provides some interesting new hypotheses - but these will need deeper functional exploration.

Reviewer #2 (Public Review):

Summary:<br /> Most of this paper concerns scRNA-seq data generated from glioblastoma patients, from three regions: tumor center, tumor periphery, and peripheral blood mononuclear cells. They focus on immune cells, and especially microglia and T-cells, where they look at the presence/absence/changes in different types of immune signatures. The data and analysis are sound and supportive of the conclusions they draw, though future studies with more patients and/or low-throughput validation would strengthen their evidence. This study adds to our knowledge of the immune cell environment in glioblastoma patients and its regional variation.

Strengths:<br /> A key strength of the paper lies in the novelty of the data, which simultaneously examines, at single-cell resolution, gene expression in two different tumor regions (center and periphery) along with peripheral blood. The authors provide numerous detailed and state-of-the-art analyses of this data, including gene differential expression, differential abundance of cell types, gene ontology analyses, tSNE visualizations, etc.

They focus in particular on differences in immune cell types. There are some suggestive differences in immune cell composition of center versus periphery, although the number of patients (5, one of whom is missing center data) does not allow one to draw a definitive conclusion.

They identified more definitive gene expression differences in center versus peripheral microglia -- differences that were not reflected in other cell types, and which included downregulation of a number of immune response functions. They also identified gene expression differences between two subsets of microglia, although those may partly reflect regional differences (the subsets are differentially enriched in the center versus periphery) or differential representation of different patients.

Finally, they identify differences in CD8+ T cells and NK cells in the center versus the periphery, where the latter were less activated/proliferative/cytotoxic.

Data analysis is performed to a high standard, using best-available methods and in some cases backed up with alternative approaches showing similar results.

Weaknesses:<br /> While the nature of the dataset is novel, the relatively low patient numbers (five) and patient diversity (e.g. with regard to IHD1 status) may be obscuring differences in cell type abundances or cell state between regions.

Most discoveries based on the scRNA-seq discussed in the paper remain to be validated by low-throughput methods in either the same patient samples, if material remains, or in other patients.

Reviewer #1 (Public Review):

Summary:<br /> Kwong et al. present evidence that two actin-filament based cytoskeletal structures regulate the clockwise and anticlockwise rotation of the cytoplasm. These claims are based on experiments using cells plated on micropatterned substrates (circles). Previous reports have shown that the actomyosin network that forms on the dorsal surface of a cell plated on a circle drives a rotational or swirling pattern of movement in the cytoplasm. This actin network is composed of a combination of non-contractile radial stress fibers (AKA dorsal stress fibers) which are mechanically coupled to contractile transverse actin arcs (AKA actin arcs). The authors claim that directionality of the rotation of the cytoplasm (i.e., clockwise or anticlockwise) depends on either the actin arcs or radial fibers, respectively. While this would interesting, the authors are not able to remove either actin-based network without effecting the other. This is not surprising, as it is likely that the radial fibers require the arcs to elongate them, and the arcs require the radial fibers to stop them from collapsing. As such, it is difficult to make simple interpretations such as the clockwise bias is driven by the arcs and anticlockwise bias is driven by the radial fibers.

Weaknesses:<br /> There are also multiple problems with how the data is displayed and interpreted. First, it is difficult to compare the experimental data with the controls as the authors do not include control images in several of the figures. For example, Figure 6 has images showing myosin IIA distribution, but Figure 5 has the control image. Each figure needs to show controls. Otherwise, it will be difficult for the reader to understand the differences in localization of the proteins shown. This could be accomplished by either adding different control examples or by combining figures.

It is important that the authors should label the range of gray values of the heat maps shown. It is difficult to know how these maps were created. I could not find a description in the methods, nor have previous papers laid out a standardized way of doing it. As such, the reader needs some indication as to whether the maps showing different cells were created the same and show the same range of gray levels. In general, heat maps showing the same protein should have identical gray levels. The authors already show color bars next to the heat maps indicating the range of colors used. It should be a simple fix to label the minimum (blue on the color bar) and the maximum (red on the color bar) gray levels on these color bars. The profiles of actin shown in Figure 3 and Figure 3- figure supplement 3 were useful for interpretating the distribution of actin filaments. Why did not the authors show the same for the myosin IIa distributions?<br /> Line 189 "This absence of radial fibers is unexpected". The authors should clarify what they mean by this statement. The claim that the cell in Figure 3B has reduced radial stress fiber is not supported by the data shown. Every actin structure in this cell is reduced compared to the cell on the larger micropattern in Figure 3A. It is unclear if the radial stress fibers are reduced more than the arcs. Are the authors referring to radial fiber elongation?<br /> The choice of the small molecule inhibitors used in this study is difficult to understand, and their results are also confusing. For example, sequestering G actin with Latrunculin A is a complicated experiment. The authors use a relatively low concentration (50 nM) and show that actin filament-based structures are reduced and there are more in the center of the cell than in controls (Figure 3E). What was the logic of choosing this concentration? Using a small molecule that binds the barbed end (e.g., cytochalasin) could conceivably be used to selectively remove longer actin filaments, which the radial fibers have compared to the lamellipodia and the transverse arcs. The authors should articulate how the actin cytoskeleton is being changed by latruculin treatment and the impact on chirality. Is it just that the radial stress fibers are not elongating? There seems to be more radial stress fibers than in controls, rather than an absence of radial stress fibers. Similar problems arise from the other small molecules as well. LPA has more effects than simply activating RhoA. Additionally, many of the quantifiable effects of LPA treatment are apparent only after the cells are serum starved, which does not seem to be the case here. Furthermore, inhibiting ROCK with, Y-27632, effects myosin light chain phosphorylation and is not specific to myosin IIA. Are the two other myosin II paralogs expressed in these cells (myosin IIB and myosin IIC)? If so, the authors' statements about this experiment should refer to myosin II not myosin IIa. None of the uses of the small molecules above have supporting data using a different experimental method. For example, backing up the LPA experiment by perturbing RhoA tho.<br /> The use of SMIFH2 as a "formin inhibitor" is also problematic. SMIFH2 also inhibits myosin II contractility, making interpreting its effects on cells difficult to impossible. The authors present data of mDia2 knockdown, which would be a good control for this SMIFH2. However, the authors claim that mDia2 "typically nucleates tropomyosin-decorated actin filaments, which recruit myosin II and anneal endwise with α-actinin- crosslinked actin filaments." There is no reference to this statement and the authors own data shows that both arcs and radial fibers are reduced by mDia2 knockdown. Overall, the formin data does not support the conclusions the authors report.<br /> The data in Figure 7 does not support the conclusion that myosin IIa is exclusively on top of the cell. There are clear ventral stress fibers in A (actin) that have myosin IIa localization. The authors simply chose to not draw a line over them to create a height profile.

Reviewer #2 (Public Review):

Summary:<br /> Chirality of cells, organs, and organisms can stem from the chiral asymmetry of proteins and polymers at a much smaller lengthscale. The intrinsic chirality of actin filaments (F-actin) is implicated in the chiral arrangement and movement of cellular structures including F-actin-based bundles and the nucleus. It is unknown how opposite chiralities can be observed when the chirality of F-actin is invariant. Kwong, Chen, and co-authors explored this problem by studying chiral cell-scale structures in adherent mammalian cultured cells. They controlled the size of adhesive patches, and examined chirality at different timepoints. They made various molecular perturbations and used several quantitative assays. They showed that forces exerted by antiparallel actomyosin bundles on parallel radial bundles are responsible for the chirality of the actomyosin network at the cell scale.

Strengths:<br /> Whereas previously, most effort has been put into understanding radial bundles, this study makes an important distinction that transverse or circumferential bundles are made of antiparallel actomyosin arrays. A minor point that was nice for the paper to make is that between the co-existing chirality of nuclear rotation and radial bundle tilt, it is the F-actin driving nuclear rotation and not the other way around. The paper is clearly written.

Weaknesses:<br /> The paper could benefit from grammatical editing.

Reviewer #1 (Public Review):

Schmit et al. analyze and compare different strategies for the allocation of funding for insecticide-treated nets (ITNs) to reduce the global burden of malaria. They use previously published models of Plasmodium falciparum and Plasmodium vivax malaria transmission to quantify the effect of ITN distribution on clinical malaria numbers and the population at risk. The impact of different resource allocation strategies on the reduction of malaria cases or a combination of malaria cases and achieving pre-elimination is considered to determine the optimal strategy to allocate global resources to achieve malaria eradication.

Strengths:

Schmit et al. use previously published models and optimization for a rigorous analysis and comparison of the global impact of different funding allocation strategies for ITN distribution. This provides evidence of the effect of three different approaches: the prioritization of high-transmission settings to reduce the disease burden, the prioritization of low-transmission settings to "shrink the malaria map", and a resource allocation proportional to the disease burden.

Weaknesses:

The analysis and optimization which provide the evidence for the conclusions and are thus the central part of this manuscript necessitate some simplifying assumptions which may have important practical implications for the allocation of resources to reduce the malaria burden. For example, seasonality, mosquito species-specific properties, stochasticity in low transmission settings, and changing population sizes were not included. Other challenges to the reduction or elimination of malaria such as resistance of parasites and mosquitoes or the spread of different mosquito species as well as other beneficial interventions such as indoor residual spraying, seasonal malaria chemoprevention, vaccinations, combinations of different interventions, or setting-specific interventions were also not included. Schmit et al. clearly state these limitations throughout their manuscript.

This work considers different ITN distribution strategies, other interventions are not considered. It also provides a global perspective but an analysis of the specific local setting (as also noted by Schmit et al.) and different interventions as well as combinations of interventions should also be taken into account for any decisions. Nonetheless, the rigorous analysis supports the authors' conclusions and provides evidence that supports the prioritization of funding of ITNs for settings with high Plasmodium falciparum transmission. Overall, this work may contribute to making evidence-based decisions regarding the optimal prioritization of funding and resources to achieve a reduction in the malaria burden.

Reviewer #2 (Public Review):

Summary:

In this article, the authors discuss an optimal resource allocation strategy to best allocate funding in maximising malaria eradication efforts. Though achieving elimination by only using insecticide-treated bed nets (ITNs) is not the best practice, and countries utilise different interventions simultaneously, this analysis could be relevant in allocating funding for the global malaria elimination effort. To analyse and compare the impact of ITNs on P. falciparum and P. vivax cases and the total populations at risk, the authors use two previously published models (for P. falciparum and P. vivax).

Strengths:

The authors use models for both P. falciparum and P. vivax to analyse the impact of different strategies for allocating ITNs and provide the best strategies for funding to minimise malaria burden across different transmission settings. Using previously published models that account for various malaria aspects, including demography, heterogeneity in bite exposure, immunity, variation in hypnozoite across bites (P. vivax), mosquito larval dynamics, etc., gives a solid foundation for the analysis performed here.

Weaknesses:

Though the objective of the study is to identify the best setting to allocate funding to eradicate malaria, the authors use prevalence estimates (P. falciparum and P. vivax) based on the year 2000 as the baseline. Given their reasoning behind this choice, the analysis would be more relevant or useful if the proposed strategy were compared to the current Global Technical Strategy for Malaria (GTS 2016-2030). That is, using estimates based on around the year 2016.

In settings where both P. falciparum and P. vivax are co-endemic, using models that do not account for the interplay between the species, especially regarding immunity, somewhat underplays the overall disease dynamics. Furthermore, assuming the transmission within each setting (very low, low, moderate, high) is homogenous is also a weakness as there is heterogeneity in transmission intensity, bite exposure, etc, within each setting.

Reviewer #1 (Public Review):

Summary: The authors investigated the function of Microrchidia (MORC) proteins in the human malaria parasite Plasmodium falciparum. Recognizing MORC's implication in DNA compaction and gene silencing across diverse species, the study aimed to explore the influence of PfMORC on transcriptional regulation, life cycle progression and survival of the malaria parasite. Depletion of PfMORC leads to the collapse of heterochromatin and thus to the killing of the parasite. The potential regulatory role of PfMORC in the survival of the parasite suggests that it may be central to the development of new antimalarial strategies.

Strengths: The application of the cutting-edge CRISPR/Cas9 genome editing tool, combined with other molecular and genomic approaches, provides a robust methodology. Comprehensive ChIP-seq experiments indicate PfMORC's interaction with sub-telomeric areas and genes tied to antigenic variation, suggesting its pivotal role in stage transition. The incorporation of Hi-C studies is noteworthy, enabling the visualization of changes in chromatin conformation in response to PfMORC knockdown.

Weaknesses: Although disruption of PfMORC affects chromatin architecture and stage-specific gene expression, determining a direct cause-effect relationship requires further investigation. Furthermore, while numerous interacting partners have been identified, their validation is critical and understanding their role in directing MORC to its targets or in influencing the chromatin compaction activities of MORC is essential for further clarification. In addition, the authors should adjust their conclusions in the manuscript to more accurately represent the multifaceted functions of MORC in the parasite.

Reviewer #2 (Public Review):

Summary: This paper, titled "Regulation of Chromatin Accessibility and Transcriptional Repression by PfMORC Protein in Plasmodium falciparum," delves into the PfMORC protein's role during the intra-erythrocytic cycle of the malaria parasite, P. falciparum. Le Roch et al. examined PfMORC's interactions with proteins, its genomic distribution in different parasite life stages (rings, trophozoites, schizonts), and the transcriptome's response to PfMORC depletion. They conducted a chromatin conformation capture on PfMORC-depleted parasites and observed significant alterations. Furthermore, they demonstrated that PfMORC depletion is lethal to the parasite.

Strengths: This study significantly advances our understanding of PfMORC's role in establishing heterochromatin. The direct consequences of the PfMORC depletion are addressed using chromatin conformation capture.

Weaknesses: The study only partially addressed the direct effects of PfMORC depletion on other heterochromatin markers.

Reviewer #1 (Public Review):

Anderson, Henikoff and Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila.

Reviewer #2 (Public Review):

Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila. The experiments and analyses were well done, by a combination of the latest and appropriate methods. They include appropriate numbers of replicates. Results were parsed by comparing them among wildtype and two mutant with different arrest stages in spermatogenesis, as well as in FACS-sorted spermatocytes. The authors profiled larval wing discs as reference-somatic cells, allowing focus on features associated with germ cells; comparisons to testis somatic cells provided further specificity. Results were further refined by categorizing genes of interest based on available single nucleus RNA seq expression profiles. The authors acknowledge that the paper's interpretations are based on subtractive logic using the mutants, but comment that more precise ways of staging would not have yielded sufficient sample for their methods.

The authors documented differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome with little or none on the X, which is intriguing because uH2A is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. All of these are new, interesting, and important. Also importantly, the authors' data provide molecular details consistent with lack of MSCI, and lack of dosage compensation of the X chromosome in Drosophila spermatocytes.

Reviewer #1 (Public Review):

Suarez-Freire et al. analyzed here the function of the exocyst complex in the secretion of the glue proteins by the salivary glands of the Drosophila larva. This is a widely used, genetically accessible system in which the formation, maturation and precisely timed exocytosis of the glue secretory granules can be beautifully imaged. Using RNAi, the authors show that all units of the exocyst complex are required for exocytosis. They show that not just granule fusion with the plasma membrane is affected (canonical role), but also, with different penetrance, that glue protein is retained in the ER, secretory granules fail to fuse homo-typically or fail to acquire maturation features. The authors document these phenotypes and postulate specific roles for the exocyst in these additional processes to explain them: exocyst as an ER-Golgi tether and exocyst as a granule-granule tether. However, the evidence for these highly novel, potentially interesting roles would need to be more compelling to support direct involvement. For instance, the localization of exocyst to Golgi or to granule-granule contact sites does not seem substantial. Instead, it is possible that defects in Golgi traffic and granule homotypic fusion are not due to direct involvement of the exocyst in these processes, but secondary to a defect in canonical exocyst roles at the plasma membrane. A block in the last step of glue exocytosis could perhaps propagate backward in the secretory pathway to disrupt Golgi complexes or cause poor cellular health due to loss of cell polarity or autophagy. In the absence of stronger evidence for these other exocyst roles, I would suggest focusing the study on the canonical role (interesting, as it was previously reported that Drosophila exocyst had no function in the salivary gland and limited function elsewhere [DOI: 10.1034/j.1600-0854.2002.31206.x]), and leave the alternative roles for discussion and deeper study in the future.

Reviewer #2 (Public Review):

The manuscript from Wappner and Melani labs claims a novel for the exocyst subunits in multiple aspects of secretory granule exocytosis. This an intriguing paper that suggests multiple roles of the exocyst in granule maturation and fusion with roles at the ER/Golgi interface, TGN, and granule homotypic fusion.

A key strength is the breadth of the assays and study of all 8 exocyst subunits in a powerful model system (fly larvae). Many of the assays are quantitated and roles of the exocyst in early phases of granule biogenesis have not been ascribed.

However there are several weaknesses, both in terms of experimental controls, concrete statements about the granules (better resolution), and making a clear conceptual framework.

Namely, why do KD of different exocysts have different effects on presumed granule formation? Why does just overexpression of a single subunit (Sec15) induce granule fusion? While the paper is fascinating, the major comments need to be addressed to really be able to make better sense of this work, which at present is hard to disentangle direct vs. secondary effects, especially as much of the TGN seems to be altered in the KDs. The authors conveniently ascribe many of the results to the holocomplex, but their own data (Fig. 4 and Fig. 6) are at odds with this.

Major Comments:

1. Resolution not sufficient. Identification of "mature secretory granules" (MSG) in Fig. 3 is based on low-resolution images in which the MSG are not clearly seen (see control in Fig. 3A) and rather appear as a diffuse haze, and not as clear granules. There may be granules here, but as shown it is not clear. Thus it would be helpful to acquire images at higher resolution (at the diffraction limit, or higher) to see and count the MSG. (Note: the authors are not clear on which objective was used. The 20x/0.8 NA or 63x/1.4 NA? Maybe the air objective as the resolution appears poor). They need to prove that the diffuse Sgs3-GFP haze is indeed due to MSG. Related it is unclear what are the granule structures that correspond to Immature secretory granules (ISG) and cells with mesh-like structures (MLS)? Similarly, Sgs3 images of KD of 8 exocyst subunits were interpreted to be identical, in Fig. 4, but the resolution is poor.

2. Explanation of variability of exocyst KD on the appearance of MSG. What is remarkable is a highly variable effect of different subunit KD on the percentage of cells with MLS (Fig. 4C). Controls = 100 %, Exo70=~75% (at 19 deg), Sec3 = ~30%, Sec10 = 0%, Exo84 = 100% ... This is interesting for the functional exocyst is an octameric holocomples, thus why the huge subunit variability in the phenotypes? The trivial explanation is either: i) variable exocyst subunit KD (not shown) or ii) variability between experiments (no error bars are shown). Both should be addressed by quantification of the KD of different proteins and secondly by replicating the experiments. If their data holds up then the underlying mechanism here needs to be considered. (Note: there is some precedent from the autophagy field of differential exocyst effects).

3. In the salivary glands the authors state that the exocyst is needed for Sgs3-GFP exit from the ER. First, Pearson's coefficient should be shown so as to quantitate the degree of ER localizations of all KDs. Second, there should be some rescue performed (if possible) to support specificity. Third, importantly other proteins that should traffic to the PM need to be shown to traffic normally so as to rule out a non-specific effect.

4. Golgi: It is unclear from their model (Fig. 5) why after exocyst KD of Sec15 the cis-Golgi is more preserved than the TGN, which appears as large vacuoles. This is not quantitated and not shown for the 8 subunits.

5. Acute/Chronic control: It would be nice to acutely block the exocyst so as to better distinguish if the effects observed are primary or secondary effects (e.g. on a recycling pathway).

6. Higher Resolution imaging (EM or super-resolution) - this would be nice to better understand the morphological interpretations.

7. Granule homotypic fusion. Strangely over-expression of just one subunit, Sec15-GFP, made giant secretory granules (SG) that were over 8 microns big! Why is that, especially if normally the exocyst is normally a holocomplex. Was this an effect that was specific to Sec15 or all exocyst subunits? Is the Sec15 level rate limiting in these cells? It may be that a subcomplex of Sec15/10 plays earlier roles, but in any case this needs to be addressed across all (or many) of the exocyst subcomplex members.

In summary, there are clearly striking effects on secretory granule biogenesis by dysfunction of the exocyst, however right now it is hard to disentangle effects on ERGolgi traffic, loss of the TGN, and a problem in maturation or fusion of granules. It is also confusing if the entire exocyst holocomplex or subcomplex plays a key role.

Reviewer #3 (Public Review):

Freire and co-authors examine the role of the exocyst complex during the formation and secretion of mucins from secretory granules in the larval salivary gland of Drosophila melanogaster. Using transgenic lines with a tagged Sgs3 mucin the authors KD expression of exocyst subunit members and observe a defect in secretory granules with a heterogeneity of phenotypes. By carefully controlling RNAi expression using a Gal4-based system the authors can KD exocyst subunit expression to varying degrees. The authors find that the stronger the inhibition of expression of exocyst the earlier in the secretory pathway the defect. The manuscript is well written, the model system is physiological, and the techniques are innovative.

My major concern is that the evidence underlying the fundamental claim of the manuscript that "the exocyst complex participates" in multiple secretory processes lacks direct evidence. It is clear from multiple lines of evidence, which are discussed by the authors, that exocyst is essential for an array of exocytic events. The fundamental concern is that loss of homeostasis on the plasma membrane proteome and lipidome might have severe pleiotropic effects on the cell. Indeed exocyst is essential, even in tissue culture conditions, and loss is lethal. Therefore, is an alternative explanation not that they are observing varying degrees of pleiotropic defect on the secretory pathway? Perhaps the authors have more evidence that exocyst is important for homeotypic fusion of the SGs, as supported by the localisation of Sec15 on the fusion sites.

The second question that I think is important to address is, what exactly do the varying RNAi levels correspond to in terms of experiments, and have these been validated? Due to the fundamental claim being that the severity of the phenotype being correlated with the level of KD, I think validation of this model is absolutely essential.

Reviewer #1 (Public Review):

Summary:

There is a long-believed dogma in the malaria field; a mosquito infected with a single oocyst is equally infectious to humans as another mosquito with many oocysts. This belief has been used for goal setting (and modeling) of malaria transmission-blocking interventions. While recent studies using rodent malaria suggest that the dogma may not be true, there was no such study with human P. falciparum parasites. In this study, the numbers of oocysts and sporozoite in the mosquitoes and the number of expelled sporozoites into artificial skin from the infected mosquito was quantified individually. There was a significant correlation between sporozoite burden in the mosquitoes and expelled sporozoites. In addition, this study showed that highly infected mosquitoes expelled sporozoites sooner.

Strengths:

• The study was conducted using two different parasite-mosquito combinations; one was lab-adapted parasites with Anopheles stephensi and the other was parasites, which were circulated in infected patients, with An. coluzzii. Both combinations showed statistically significant correlations between sporozoite burden in mosquitoes and the number of expelled sporozoites.

• Usually, this type of study has been done in group bases (e.g., count oocysts and sporozoites at different time points using different mosquitoes from the same group). However, this study determined the numbers in individual bases after multiple optimization and validation of the approach. This individual approach significantly increases the power of correlation analysis.

Weaknesses:

• In a natural setting, most mosquitoes have less than 5 oocysts. Thus, the conclusion is more convincing if the authors perform additional analysis for the key correlations (Fig 3C and 4D) excluding mosquitoes with very high total sporozoite load (e.g., more than 5-oocyst equivalent load).

• As written as the second limitation of the study, this study did not investigate whether all expelled sporozoites were equally infectious. For example, Day 9 expelled sporozoites may be less infectious than Day 11 sporozoites, or expelled sporozoites from high-burden mosquitoes may be less infectious because they experience low nutrient conditions in a mosquito. Ideally, it is nice to test the infectivity by ex vivo assays, such as hepatocyte invasion assay, and gliding assay at least for salivary sporozoites. But are there any preceding studies where the infectivity of sporozoites from different conditions was evaluated? Citing such studies would strengthen the argument.

• Since correlation analyses are the main points of this paper, it is important to show 95%CI of Spearman rank coefficient (not only p-value). By doing so, readers will understand the strengths/weaknesses of the correlations. The p-value only shows whether the observed correlation is significantly different from no correlation or not. In other words, if there are many data points, the p-value could be very small even if the correlation is weak.

Reviewer #2 (Public Review):

Summary:

The malaria parasite Plasmodium develops into oocysts and sporozoites inside Anopheles mosquitoes, in a process called sporogony. Sporozoites invade the insect salivary glands in order to be transmitted during a blood meal. An important question regarding malaria transmission is whether all mosquitoes harboring Plasmodium parasites are equally infectious. In this paper, the authors investigated the progression of P. falciparum sporozoite development in Anopheles mosquitoes, using a sensitive qPCR method to quantify sporozoites and an artificial skin system to probe for parasite expelling. They assessed the association between oocyst burden, salivary gland infection intensity, and sporozoites expelled.

The data show that higher sporozoite loads are associated with earlier colonization of salivary glands and a higher prevalence of sporozoite-positive salivary glands and that higher salivary gland sporozoite burdens are associated with higher numbers of expelled sporozoites. Intriguingly, there is no clear association between salivary gland burdens and the prevalence of expelling, suggesting that most infections reach a sufficient threshold to allow parasite expelling during a mosquito bite. This important observation suggests that low-density gametocyte carriers, although less likely to infect mosquitoes, could nevertheless contribute to malaria transmission.

Strengths:

The paper is well written and the work is well conducted. The authors used two experimental models, one using cultured P. falciparum gametocytes and An. stephensi mosquitoes, and the other one using natural gametocyte infections in a field setup with An. coluzzii mosquitoes. Both studies gave similar results, reinforcing the validity of the observations. Parasite quantification relies on a robust and sensitive qPCR method, and parasite expelling was assessed using an innovative experimental setup based on artificial skin.

Weaknesses:

There is no clear association between the prevalence of sporozoite expelling and the parasite burden. However, high total sporozoite burdens are associated with earlier and more efficient colonization of the salivary glands, and higher salivary gland burdens are associated with higher numbers of expelled sporozoites. While these observations suggest that highly infected mosquitoes could transmit/expel parasites earlier, this is not directly addressed in the study. In addition, whether all expelled sporozoites are equally infectious is unknown. The central question, i.e. whether all infected mosquitoes are equally infectious, therefore remains open.

Reviewer #3 (Public Review):

Summary:

This study uses a state-of-the-art artificial skin assay to determine the quantity of P. falciparum sporozoites expelled during feeding using mosquito infection (by standardised membrane feeding assay SMFA) using both cultured gametocytes and natural infection. Sporozoite densities in salivary glands and expelled into the skin are quantified using a well-validated molecular assay. These studies show clear positive correlations between mosquito infection levels (as determined by oocyst numbers), sporozoite numbers in salivary glands, and sporozoites expelled during feeding. This indicates potentially significant heterogeneity in infectiousness between mosquitoes with different infection loads and thus challenges the often-made assumption that all infected mosquitoes are equally infectious.

Strengths:

Very rigorously designed studies using very well validated, state-of-the-art methods for studying malaria infections in the mosquito and quantifying load of expelled sporozoites. This resulted in very high-quality data that was well-analyzed and presented. Both sources of gametocytes (cultures vs. natural infection) show consistent results further strengthening the quality of the results obtained.

Weaknesses:

As is generally the case when using SMFAs, the mosquito infections levels are often relatively high compared to wild-caught mosquitoes (e.g. Bombard et al 2020 IJP: median 3-4 ), and the strength of the observed correlations between oocyst sheet and salivary gland sporozoite load even more so between salivary gland sporozoite load and expelled sporozoite number may be dominated by results from mosquitoes with infection levels rarely observed in wild-caught mosquitoes. This could result in an overestimation of the importance of these well-observed positive relationships under natural transmission conditions.

The results obtained from these excellently designed and executed studies very well supported their conclusion - with a slight caveat regarding their application to natural transmission scenarios

This work very convincingly highlights the potential for significant heterogeneity in the infectiousness between individual P. falciparum-infected mosquitoes. Such heterogeneity needs to be further investigated and if again confirmed taken into account both when modelling malaria transmission and when evaluating the importance of low-density infections in sustaining malaria transmission.

Reviewer #4 (Public Review):

The study compares the number of sporozoites expelled by mosquitoes with different Plasmodium infection burden. To my knowledge this is the first report comparing the number of expelled P. falciparum sporozoites and their relation to oocyst burden (intact and ruptured) and residual sporozoites in salivary glands. The study provides important evidence on malaria transmission biology although conclusions cannot be drawn on direct impact on transmission.

Although there is some evidence from malaria challenge studies that the burden of sporozoites injected into a host is directly correlated with the likelihood of infection, this has been done using experimental infection models which administer sporozoites intravenously. It is unclear whether the same correlation occurs with natural infections and what the actual threshold for infection may be. Host immunity and other host related factors also play a critical role in transmission and need to be taken into consideration; these have not been mentioned by the authors. This is of particular importance as host immunity is decreasing with reduction in transmission intensity.

The natural infections reported in the study were not natural as the authors described. Gametocyte enrichment was done to attain high oocyst infection numbers. Studying natural infections would have been better without the enrichment step. The infected mosquitoes have much larger infection burden than what occurs in the wild.<br /> Nevertheless, the findings support the same results as in the experiments conducted in the Netherlands and therefore are of interest. I suggest the authors change the wording. Rather than calling these "natural" infections, they could be called, for example, "experimental infections with wild parasite strains".

I do not believe the study results generate sufficient evidence to conclude that lower infection burden in mosquitoes is likely to result in changes to transmission potential in the field. In study limitations section, the authors say "In addition, our quantification of sporozoite inoculum size is informative for comparisons between groups of high and low-infected mosquitoes but does not provide conclusive evidence on the likelihood of achieving secondary infections. Given striking differences in sporozoite burden between different Plasmodium species - low sporozoite densities appear considerably more common in mosquitoes infected with P. yoelli and P. Berghei the association between sporozoite inoculum and the likelihood of achieving secondary infections may be best examined in controlled human infection studies. However, in the abstract conclusion the authors state "Whilst sporozoite expelling was regularly observed from mosquitoes with low infection burdens, our findings indicate that mosquito infection burden is associated with the number of expelled sporozoites and may need to be considered in estimations of transmission potential." Kindly consider ending the sentence at "expelled sporozoites." Future studies on CHMI can be recommended as a conclusion if authors feel fit.