I really liked the Oral History project that was used in the HIST 150 class at JMU. I enjoyed listening to some of the stories and reminded me of NPR's Story Corps. I can see using something like this in my Population Health Determinants Class to capture student reflections from their service-learning experiences.

I’m thinking about how open pedagogy connects really naturally with some of the things I already do in my classes. In Population Health Determinants, for example, there’s a service-learning component where students engage with local organizations to understand social determinants of health. I can see opportunities for students to create open educational materials or community resources from those experiences—something that lives beyond the course and benefits others.

Similarly, in U.S. and Global Health Care Systems, my students do a podcast project comparing different countries’ health systems. That assignment already emphasizes collaboration and knowledge sharing, but I’d like to take it further by having them publish their work openly so future students (or even community members) can learn from it.

Validity: This article uses both data and reasoning to support the claim. It gives numerous examples and statistics of how AI betters firms. Each piece of evidence is brought back to the claim that AI is maximizing innovation and creativity.

Soundness: The evidence this article uses is true and relavant. I know it's true because they provide data and statistics from an analysis that support the claim. This evidence connects to the claim that AI increases innovation, which is a prime aspect of the thesis.

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In order to obtain a buffer, the complete neutralization of either the acid or the base must be avoided. Thus weak acids are used (and my guess no strong bases as well) because the complete dissociation of its ions would prevent the suspension of the pH.

Why is it tending so much towards yes (before becoming uncertain)? Maybe the model tends to favor positive responses, as mentioned earlier being the case for another model. But I hypothesized there to be relation hallucinations with the yes and no flipped compared to the Figure. Since the plot is averaged, are those cases so rare that they do not get represented after averaging anymore?

Why does it become uncertain only once the last layers are reached? They call it sharp change in Figure 8b.

Should be "previous", right?

That assumes that the token that has high probability in the intermediate layer (e.g. yes in Figure 7) is the correct answer.

XII Regio

this needs to be verified.

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Coordinate with production accounting team for seamless claims

how?

This needs to be double-checked as well.

This amount isn’t correct. We need to find a way to get the exact or a near-exact figure for that.

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eLife Assessment

This important study addresses a topic that is frequently discussed in the literature but is under-assessed, namely correlations among genome size, repeat content, and pathogenicity in fungi. Contrary to previous assertions, the authors found that repeat content is not associated with pathogenicity. Rather, pathogenic lifestyle was found to be better explained by the number of protein-coding genes, with other genomic features associated with insect association status. The results are considered solid, although there remain concerns about potential biases stemming from the underlying data quality of the analyzed genomes.

Reviewer #1 (Public review):

Summary:

The manuscript "Lifestyles shape genome size and gene content in fungal pathogens" by Fijarczyk et al. presents a comprehensive analyses of a large dataset of fungal genomes to investigate what genomic features correlate with pathogenicity and insect associations. The authors focus on a single class of fungi, due to the diversity of life styles and availability of genomes. They analyze a set of 12 genomic features for correlations with either pathogenicity or insect association and find that, contrary to previous assertions, repeat content does not associate with pathogenicity. They discover that the number of protein coding genes, including total size of non-repetitive DNA does correlate with pathogenicity. However, unique features are associated to insect associations. This work represents an important contribution to the attempts to understand what features of genomic architecture impact the evolution of pathogenicity in fungi.

Strengths:

The statistical methods appear to be properly employed and analyses thoroughly conducted. The size of the dataset is impressive and likely makes the conclusions robust. The manuscript is well written and the information, while dense, is generally presented in a clear manner.

Weaknesses:

My main concerns all involve the genomic data, how they were annotated, and the biases this could impart to the downstream analyses. The three main features I'm concerned with are sequencing technology, gene annotation, and repeat annotation. The authors have done an excellent investigation into these issues, but these show concerning trends, and my concerns are not as assuaged as the authors.

The collection of genomes is diverse and includes assemblies generated from multiple sequencing technologies including both short- and long-read technologies. From the number of scaffolds its clear that the quality of the assemblies varies dramatically, even within categories of long- and short-read. This is going to impact many of the values important for this study, as the authors show.

I have considerable worries that the gene annotation methods could impart biases that significantly effect the main conclusions. Only 5 reference training sets were used for the Sordariomycetes and these are unequally distributed across the phylogeny. Augusts obviously performed less than ideally, as the authors observe in their extended analysis. While the authors are not concerned about phylogenetic distance from the training species, due to prevailing trends, I am not as convinced. In figure S12, the Augustus features appear to have considerably more variation in values for the H2 set and possible the microascales. It is unclear how this would effect the conclusions in this study.

Unfortunately, the genomes available from NCBI will vary greatly in the quality of their repeat masking. While some will have been masked using custom libraries generated with software like Repeatmodeler, others will probably have been masked with public databases like repbase. As public databases are again biased towards certain species (Fusarium is well represented in repbase for example), this could have significant impacts on estimating repeat content. Additionally, even custom libraries can be problematic as some software (like RepeatModeler) will included multicopy host genes leading to bona fide genes being masked if proper filtering is not employed. A more consistent repeat masking pipeline would add to the robustness of the conclusions. The authors show that there is a significant bias in their set.

To a lesser degree I wonder what impact the use of representative genomes for a species has on the analyses. Some species vary greatly in genome size, repeat content and architecture among strains. I understand that it is difficult to address in this type of analysis, but it could be discussed.

Reviewer #2 (Public review):

Summary:

In this paper, the authors report on the genomic correlates of the transition to the pathogenic lifestyle in Sordariomycetes. The pathogenic lifestyle was found to be better explained by the number of genes, and in particular effectors and tRNAs, but this was modulated by the type of interacting host (insect or not insect) and the ability to be vectored by insects.

Strengths:

The main strengths of this study lie in (i) the size of the dataset, and the potentially high number of lifestyle transitions in Sordariomycetes, (ii) the quality of the analyses and the quality of the presentation of the results, (iii) the importance of the authors' findings.

Weaknesses:

The weakness is a common issue in most comparative genomics studies in fungi, but it remains important and valid to highlight it. Defining lifestyles is complex because many fungi go through different lifestyles during their life cycles (for instance, symbiotic phases interspersed with saprotrophic phases). In many fungi, the lifestyle referenced in the literature is merely the sampling substrate (such as wood or dung), which does not necessarily mean that this substrate is a key part of the life cycle. The authors discuss this issue, but they do not eliminate the underlying uncertainties.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review):

Summary:

The manuscript "Lifestyles shape genome size and gene content in fungal pathogens" by Fijarczyk et al. presents a comprehensive analysis of a large dataset of fungal genomes to investigate what genomic features correlate with pathogenicity and insect associations. The authors focus on a single class of fungi, due to the diversity of lifestyles and availability of genomes. They analyze a set of 12 genomic features for correlations with either pathogenicity or insect association and find that, contrary to previous assertions, repeat content does not associate with pathogenicity. They discover that the number of proteincoding genes, including the total size of non-repetitive DNA does correlate with pathogenicity. However, unique features are associated with insect associations. This work represents an important contribution to the attempts to understand what features of genomic architecture impact the evolution of pathogenicity in fungi.

Strengths:

The statistical methods appear to be properly employed and analyses thoroughly conducted. The manuscript is well written and the information, while dense, is generally presented in a clear manner.

Weaknesses:

My main concerns all involve the genomic data, how they were annotated, and the biases this could impart to the downstream analyses. The three main features I'm concerned with are sequencing technology, gene annotation, and repeat annotation.

We thank the reviewer for all the comments. We are aware that the genome assemblies are of heterogeneous quality since they come from many sources. The goal of this study was to make the best use of the existing assemblies, with the assumption that noise introduced by the heterogeneity of sequencing methods should be overcome by the robustness of evolutionary trends and the breadth and number of analyzed assemblies. Therefore, at worst, we would expect a decrease in the power to detect existing trends. It is important to note that the only way to confidently remove all potential biases would be to sequence and analyze all species in the same way; this would require a complete study and is beyond the scope of the work presented here. Nevertheless some biases could affect the results in a negative way, eg. is if they affect fungal lifestyles differently. We therefore made an attempt to explore the impact of sequencing technology, gene and repeat annotation approach among genomes of different fungal lifestyles. Details are described in Supplementary Results and below. Overall, even though the assembly size and annotations conducted with Augustus can sometimes vary compared to annotations from other resources, such as JGI Mycocosm, we do not observe a bias associated with fungal lifestyles. Comparison of annotations conducted with Augustus and JGI Mycocosm dataset revealed variation in gene-related features that reflect biological differences rather than issues with annotation.  

The collection of genomes is diverse and includes assemblies generated from multiple sequencing technologies including both short- and long-read technologies. Not only has the impact of the sequencing method not been evaluated, but the technology is not even listed in Table S1. From the number of scaffolds it is clear that the quality of the assemblies varies dramatically. This is going to impact many of the values important for this study, including genome size, repeat content, and gene number.

We have now added sequencing technology in Table S1 as it was reported in NCBI. We evaluated the impact of long-read (Nanopore, PacBio, Sanger) vs short-read assemblies in Supplementary Results. In short, the proportion of different lifestyles (pathogenic vs. nonpathogenic, IA vs non-IA) were the same for short- and long-read assemblies. Indeed, longread assemblies were longer, had a higher fraction of repeats and less genes on average, but the differences between pathogenic vs. non-pathogenic (or IA vs non-IA) species were in the same direction for two sequencing technologies and in line with our results. There were some discrepancies, eg. mean intron length was longer for pathogens with long-read assemblies, but slightly shorter on average for short-read assemblies (and to lesser extent GC and pseudo tRNA count), which could explain weaker or mixed results in our study for these features.

Additionally, since some filtering was employed for small contigs, this could also bias the results.

The reason behind setting the lower contig length threshold was the fact that assemblies submitted to NCBI have varying lower-length thresholds. This is because assemblers do not output contigs above a certain length, and this threshold can be manipulated by the user. Setting a common min contig length was meant to remove this variation, knowing that any length cut-off will have a larger effect on short-read based assemblies than long-read-based assemblies. Notably, genome assemblies of corresponding species in JGI Mycocosm have a minimum contig length of 865 bp, not much lower than in our dataset. Importantly, in a response to a comment of previous reviewer, repeat content was recalculated on raw assembly lengths instead of on filtered assembly length. 

I have considerable worries that the gene annotation methods could impart biases that significantly affect the main conclusions. Only 5 reference training sets were used for the Sordariomycetes and these are unequally distributed across the phylogeny. Augusts obviously performed less than ideally, as the authors reported that it under-annotated the genomes by 10%. I suspect it will have performed worse with increasing phylogenetic distance from the reference genomes. None of the species used for training were insectassociated, except for those generated by the authors for this study. As this feature was used to split the data it could impact the results. Some major results rely explicitly on having good gene annotations, like exon length, adding to these concerns. Looking manually at Table S1 at Ophiostoma, it does seem to be a general trend that the genomes annotated with Magnaporthe grisea have shorter exons than those annotated with H294. I also wonder if many of the trends evident in Figure 5 are also the result of these biases. Clades H1 and G each contain a species used in the training and have an increase in genes for example.

We have applied 6 different reference training sets (instead of one) precisely to address the problem of increasing phylogenetic distance of annotated species. To further investigate the impact of chosen species for training, we plotted five gene features (number of genes, number of introns, intron length, exon length, fraction of genes with introns) as a function of   branch length distance from the species (or genus) used as a training set for annotation. We don’t see systematic biases across different training sets. However,  trends are very clear for clades annotated with fusarium. This set of species includes Hypocreales and Microascales, which is indeed unfortunate since Microascales is an IA group and at the same time the most distant from the fusarium genus in this set. To clarify if this trend is related to annotation bias or a biological trend, we compared gene annotations with those of Mycocosm, between Hypocreales Fusarium species, Hypocreales non-Fusarium species, and Microascales, and we observe exactly the same trends in all gene features. 

Similarly, among species that were annotated with magnaporthe_grisea, Ophiostomatales (another IA group) are among the most distant from the training set species. Here, however, another order, Diaporthales, is similarly distant, yet the two orders display different feature ranges. In terms of exon length, top 2 species in this training set include Ophiostoma, and they reach similar exon length as the Ophiostoma species annotated using H294 as a training set. In summary, it is possible that the choice of annotation species has some effect on feature values; however, in this dataset, these biases are likely mitigated by biological differences among lifestyles and clades. 

Unfortunately, the genomes available from NCBI will vary greatly in the quality of their repeat masking. While some will have been masked using custom libraries generated with software like Repeatmodeler, others will probably have been masked with public databases like repbase. As public databases are again biased towards certain species (Fusarium is well represented in repbase for example), this could have significant impacts on estimating repeat content. Additionally, even custom libraries can be problematic as some software (like RepeatModeler) will include multicopy host genes leading to bona fide genes being masked if proper filtering is not employed. A more consistent repeat masking pipeline would add to the robustness of the conclusions.

We have searched for the same species in JGI Mycocosm and were able to retrieve 58 genome assemblies with matching species, with 19 of them belonging to the same strain as in our dataset. Overall we found no differences in genome assembly length. Interestingly, repeat content was slightly higher for NCBI genome assemblies compared to JGI Mycocosm assemblies, perhaps due to masking of host multicopy genes, as the reviewer mentioned. By comparing pathogenic and non-pathogenic species for the same 19 strains, we observe that JGI Mycocosm annotates fewer repeats in pathogenic species than Augustus annotations (but trends are similar when taking into account 58 matching species). Given a small number of samples, it is hard to draw any strong conclusions; however, the differences that we see are in favor of our general results showing no (or negative) correlation of repeat content with pathogenicity. 

To a lesser degree, I wonder what impact the use of representative genomes for a species has on the analyses. Some species vary greatly in genome size, repeat content, and architecture among strains. I understand that it is difficult to address in this type of analysis, but it could be discussed.

In our case the use of protein sequences could underestimate divergence between closely related strains from the same species. We also excluded strains of the same species to avoid overrepresentation of closely related strains with similar lifestyle traits. We agree that some changes in the genome architecture can occur very rapidly, even at the species level, though analyzing emergence of eg. pathogenicity at the population level would require a slightly different approach which accounts for population-level processes. 

Reviewer #2 (Public review):

Summary:

In this paper, the authors report on the genomic correlates of the transition to the pathogenic lifestyle in Sordariomycetes. The pathogenic lifestyle was found to be better explained by the number of genes, and in particular effectors and tRNAs, but this was modulated by the type of interacting host (insect or not insect) and the ability to be vectored by insects.

Strengths:

The main strength of this study lies in the size of the dataset, and the potentially high number of lifestyle transitions in Sordariomycetes.

Weaknesses:

The main strength of the study is not the clarity of the conclusions.

(1) This is due firstly to the presentation of the hypotheses. The introduction is poorly structured and contradictory in some places. It is also incomplete since, for example, fungusinsect associations are not mentioned in the introduction even though they are explicitly considered in the analyses.

We thank the reviewer for pointing this out. We strived to address all comments and suggestions of the reviewer to clarify the message and remove the contradictions. We also added information about why we included insect-association trait in our analysis. 

(2) The lack of clarity also stems from certain biases that are challenging to control in microbial comparative genomics. Indeed, defining lifestyles is complicated because many fungi exhibit different lifestyles throughout their life cycles (for instance, symbiotic phases interspersed with saprotrophic phases). In numerous fungi, the lifestyle referenced in the literature is merely the sampling substrate (such as wood or dung), which doesn't mean that this substrate is a crucial aspect of the life cycle. This issue is discussed by the authors, but they do not eliminate the underlying uncertainties.

We agree with the reviewer that lack of certainty in the lifestyle or range of possible lifestyles of studied species is a weakness in this analysis. We are limited by the information available in the literature. We hope that our study will increase interest in collecting such data in the future.

Reviewer #3 (Public review):

Summary:

This important study combines comparative genomics with other validation methods to identify the factors that mediate genome size evolution in Sordariomycetes fungi and their relationship with lifestyle. The study provides insights into genome architecture traits in this Ascomycete group, finding that, rather than transposons, the size of their genomes is often influenced by gene gain and loss. With an excellent dataset and robust statistical support, this work contributes valuable insights into genome size evolution in Sordariomycetes, a topic of interest to both the biological and bioinformatics communities.

Strengths:

This study is complete and well-structured.

Bioinformatics analysis is always backed by good sampling and statistical methods. Also, the graphic part is intuitive and complementary to the text.

Weaknesses:

The work is great in general, I just had issues with the Figure 1B interpretation.

I struggled a bit to find the correspondence between this sentence: "Most genomic features were correlated with genome size and with each other, with the strongest positive correlation observed between the size of the assembly excluding repeats and the number of genes (Figure 1B)." and the Figure 1B. Perhaps highlighting the key p values in the figure could help.

We thank the reviewer for pointing out this sentence. Perhaps the misunderstanding comes from the fact that in this sentence one variable is missing. The correct version should be “Most genomic features were correlated with genome size and with each other, with the strongest positive correlation observed between the genome size, the genome size excluding repeats and the number of genes (Figure 1B)”. Also, the variable names now correspond better to those shown on the figure.

Reviewer #1 (Recommendations for the authors):

The authors have clearly done a lot of good work, and I think this study is worthwhile. I understand that my concerns about the underlying data could necessitate rerunning the entire analysis with better gene models, but there may be another option. JGI has a fairly standard pipeline for gene and repeat annotation. Their gene predictions are based on RNA data from the sequenced strain and should be quite good in general. One could either compare the annotations from this manuscript to those in mycocosm for genomes that are identical and see if there are systematic biases, or rerun some analyses on a subset of genomes from mycocosm. Indeed, it's possible that the large dataset used here compensates for the above concerns, but without some attempt to evaluate these issues, it's difficult to have confidence in the results.

We very appreciate the positive reception of our manuscript. Following the reviewer’s comments we have investigated gene annotations in comparison with those of JGI Mycocosm, even though only 58 species were matching and only 19 of them were from the same strain. This dataset is not representative of the Sordariomycetes diversity (most species come from one clade), therefore will not reflect the results we obtained in this study. To note, the reason for not choosing JGI Mycocosm in the first place, was the poor representation of the insect-associated species, which we found key in this study. In general, we found that assembly lengths were nearly identical, number of genes was higher, and the repeat content was lower for the JGI Mycocosm dataset. When comparing different lifestyles (in particular pathogens vs. non-pathogens), we found the same differences for our and JGI Mycocosm annotations, with one exception being the repeat content. In the small subset (19 same-strain assemblies), our dataset showed the same level of repeats between the two lifestyles, whereas JGI Mycocosm showed lower repeat content for pathogens (but notably for all 58 species, the trend was same for our and JGI Mycocosm annotations). None of these observations are in conflict with our results where we find no or negative association of repeat content with pathogens. 

The figures are very information-dense. While I accept that this is somewhat of a necessity for presenting this type of study, if the authors could summarize the important information in easier-to-interpret plots, that could help improve readability.

We put a lot of effort into showing these complicated results in as approachable manner as possible. Given that other reviewers find them intuitive we decided to keep most of them as they are. To add more clarification, we added one supplementary figure showing distributions of genomic traits across lifestyles. Moreover, in Figure 5, a phylogenetic tree was added with position of selected clades, as well as a scatterplot showing distributions of mean values for genome size and number of genes for those clades. If the reviewer has any specific suggestions on what to improve and in which figure, we’re happy to consider it. 

Reviewer #2 (Recommendations for the authors):

I have no major comments on the analyses, which have already been extensively revised. My major criticism is the presentation of the background, which is very insufficient to understand the importance or relevance of the results presented fully.

Lines are not numbered, unfortunately, which will not help the reading of my review.

(1) The introduction could better present the background and hypotheses:

(a) After reading the introduction, I still didn't have a clear understanding of the specific 'genome features' the study focuses on. The introduction fails to clearly outline the current knowledge about the genetic basis of the pathogenic lifestyle: What is known, what remains unknown, what constitutes a correlation, and what has been demonstrated? This lack of clarity makes reading difficult.

We thank the reviewer for pointing this out. We have now included in the introduction a list of genomic traits we focus on. We also tried to be more precise about demonstrated pathogenic traits and other correlated traits in the introduction. 

(b) Page 3. « Various features of the genome have been implicated in the evolution of the pathogenic lifestyle. » The cited studies did not genuinely link genome features to lifestyle, so the authors can't use « implicated in » - correlation does not imply causation.

This sentence also somehow contradicts the one at the end of the paragraph: « we still have limited knowledge of which genomic features are specific to pathogenic lifestyle

We thank the reviewer for this comment. We added a phrase “correlated with or implicated in” and changed the last sentence of the paragraph into “Yet we still have limited knowledge of how important and frequent different genomic processes are in the evolution of pathogenicity across phylogenetically distinct groups of fungi and whether we can use genomic signatures left by some of these processes as predictors of pathogenic state.”.

(c) Page 3: « Fungal pathogen genomes, and in particular fungal plant pathogen genomes have been often linked to large sizes with expansions of TEs, and a unique presence of a compartmentalized genome with fast and slow evolving regions or chromosomes » Do the authors really need to say « often »? Do they really know how often?

We removed “often”.

(d) Such accessory genomic compartments were shown to facilitate the fast evolution of effectors (Dong, Raffaele, and Kamoun 2015) ». The cited paper doesn't « show » that genomic compartments facilitate the fast evolution of effectors. It's just an observation that there might be a correlation. It's an opinion piece, not a research manuscript.

We changed the sentence to “Such accessory genomic compartments could facilitate the fast evolution of effectors”.

(e) even though such architecture can facilitate pathogen evolution, it is currently recognized more as a side effect of a species evolutionary history rather than a pathogenicity related trait ». This sentence somehow contradicts the following one: « Such accessory genomic compartments were shown to facilitate the fast evolution of effectors".

Here we wanted to point out that even though accessory genome compartments and TE expansions can facilitate pathogen evolution the origin of such architecture is not linked to pathogenicity. We reformulated the sentence to “Even though such architecture can facilitate pathogen evolution, it is currently recognized that its origin is more likely a side effect of a species evolutionary history rather than being caused by pathogenicity”.

(f) As the number of genes is strongly correlated with fungal genome size (Stajich 2017), such expansions could be a major contributor to fungal genome size. » This sentence suggests that pathogens might have bigger genomes because they have more effectors. This is contradictory to the sentence right after « At the end of the spectrum are the endoparasites Microsporidia, which have among the smallest known fungal genomes ».

The authors state that pathogens have bigger genomes and then they take an example of a pathogen that has a minimal genome. I know it's probably because they lost genes following the transition to endoparasitism and not related to their capacity to cause disease. I just want to point out that their writing could be more precise. I invite authors to think of young scholars who are new to the field of fungal evolutionary genomics.

We thank the reviewer for prompting us to clarify the text. We rewrote this short extract as follows “Notably, not all pathogenic species experience genome or gene expansions, or show compartmentalized genome architecture. While gene family expansions are important for some pathogens, the contrary can be observed in others, such as Microsporidia. Due to transition to obligatory intracellular lifestyle these fungi show signatures of strong genome contractions and reduced gene repertoire (Katinka et al. 2001) without compromising their ability to induce disease in the host. This raises questions about universal genomic mechanisms of transition to pathogenic state.”

(g) I find it strange that the authors do not cite - and do not present the major results of two other studies that use the same type of approach and ask the same type of question in Sordariomycetes, although not focusing on pathogenicity:

Hensen et al.: https://pubmed.ncbi.nlm.nih.gov/37820761/

Shen et al.: https://pubmed.ncbi.nlm.nih.gov/33148650/

We thank the reviewer for pointing out this omission. We now added more information in the introduction to highlight the importance of the phylogenetic context in studying genome evolution as demonstrated by these studies. The following part was added to introduction:  “Other phylogenomic studies investigating a wide range of Ascomycete species, while not explicitly focusing on the neutral evolution hypothesis, have found strong phylogenetic signals in genome evolution, reflected in distinct genome characteristics (e.g., genome size, gene number, intron number, repeat content) across lineages or families (Shen et al. 2020; Hensen et al. 2023). Variation in genome size has been shown to correlate with the activity of the repeat-induced point mutation (RIP) mechanism (Hensen et al. 2023; Badet and Croll 2025), by which repeated DNA is targeted and mutated. RIP can potentially lead to a slower rate of emergence of new genes via duplication (Galagan et al. 2003), and hinder TE proliferation limiting genome size expansion (Badet and Croll 2025). Variation in genome dynamics across lineages has also been suggested to result from environmental context and lifestyle strategies (Shen et al. 2020), with Saccharomycotina yeast fungi showing reductive genome evolution and Pezizomycotina filamentous fungi exhibiting frequent gene family expansions. Given the strong impact of phylogenetic membership,  demographic history (Ne) and host-specific adaptations of pathogens on their genomes, we reasoned that further examination of genomic sequences in groups of species with various lifestyles can generate predictions regarding the architecture of pathogenic genomes.”

(h) Genome defense mechanisms against repeated elements, such as RIP, are not mentioned while they could have a major impact on genome size (Hensen et al cited above; Badet and Croll https://www.biorxiv.org/content/10.1101/2025.01.10.632494v1.full).

This citation is added in the text above.

(i) Should the reader assume that the genome features to be examined are those mentioned in the first paragraph or those in the penultimate one?

In the last paragraph of the introduction we included the complete list of investigated genomic traits.

(j) The insect-associated lifestyle is mentioned only in the research questions on page 4, but not earlier in the introduction. Why should we care about insect-associated fungi?

We apologize for this omission. We added a sentence explaining how neutral evolution hypotheses can explain patterns of genome evolution in endoparasites and species with specialized vectors (traits present in insect-associated species) and added a sentence in the last paragraph that this is the reason why we have selected this trait for analysis.  

(2) Why use concatenation to infer phylogeny?

(a) Kapli et al. https://pubmed.ncbi.nlm.nih.gov/32424311/ « Analyses of both simulated and empirical data suggest that full likelihood methods are superior to the approximate coalescent methods and to concatenation »

(b) It also seems that a homogeneous model was used, and not a partitioned model, while the latter are more powerful. Why?

We thank the reviewer for the comment. When we were reconstructing the phylogenetic tree  we were not aware of the publication and we followed common practices from literature for phylogenetic tree reconstruction even though currently they are not regarded as most optimal. In fact, in the first round of submission, we have included both concatenation as well as a multispecies coalescent method based on 1000 busco sequences and a concatenation method with different partitions for 250 busco sequences. All three methods produced similar topologies. Since the results were concordant, we chose to omit these analyses from the manuscript to streamline the presentation and focus on the most important results.

(3) Other comments:

Is there a table listing lifestyles?

Yes, lifestyles (pathogenicity and insect-association) are listed in Supplementary Table S1. 

(4) Summary:

(a) seemingly similar pathogens »: meaning unclear; on what basis are they similar? why « seemingly »?

We removed “seemingly” from the sentence.

(b) Page 4: what's the difference between genome feature and genome trait?

There is no difference. We apologize for the confusion. We changed “feature” to “trait” whenever it refers to the specific 13 genomic traits analyzed in this study.

(c) Page 22: Braker, not Breaker

corrected

What do the authors mean when they write that genes were predicted with Augustus and Braker? Do they mean that the two sets of gene models were combined? Gene counts are based on Augustus (P24): why not Braker?

We only meant here that gene annotation was performed using Braker pipeline, which uses a particular version of Augustus. We corrected the sentence.

(d) Figure 2B and 2C:

'Undetermined sign' or 'Positive/Negative' would be better than « YES » or it's just impossible to understand the figure without reading the legend.

We changed “YES” to “UNDETERMINED SIGN” as suggested by the reviewer.

This sentence captures the essence of the transactional model by showing how communication is a collaborative, continuous process where meaning is co-created rather than simply transmitted

this sentence underscores how personal and cultural differences shape interpretation, showing that effective communication depends on understanding others’ perspectives and shared experiences

This highlights how external or internal distractions can disrupt understanding, reminding readers that effective communication depends not only on clear messages but also on managing barriers that alter meaning

self awareness occurs after communication failure

2 pgs

4+ pgs

4+ pgs

modes of practical expertise

moveable mudbanks

experience,. moving shore, colonial prehistory, design artifact

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Test

check version

Discussion

suggested a new parameter

highlights the federal principle of the ability for groups to easily secede if they want to. in the case of Yugoslavia is was a part of the full constitutent unit of the USSR were able to break away and break even further into independent states. In the case of succession it begins when the regional gov balme their central counterpart for whatever ails them; this contributes to intergovernmental politics of division

details the accounts were multi-national federations have collapsed or have failed to be durably democratic all around the world.

understanding the term and relevance of "multination/pluri-national" or "ethno-federal" federations instability. mentions Yugoslavia's disintegration during its transition to democracy. (which the authors argues is crucial for the stability of multinational federations, alongside the choices of no democracy and no single state)

argues that multinational federations cna succeed under certain conditions and the arguments against are greatly exagerated, based on majoritarian bias, spurious arguments, and misleading comparisons.

fucking agree!

Forma de Governo - República Federativa do Brasil

eLife Assessment

This valuable study uses a sophisticated array of techniques to investigate the mechanisms through which the chordotonal receptors in the locust ear (Müller's organ) sense auditory signals. Ultrastructural reconstruction of the sensory organ provides convincing evidence of the organization of the scolopidial structure that wraps the sensory neuron cilium. However, the recordings of sound-evoked motion and electrophysiological activity from the chordotonal sensory neurons provide incomplete evidence for the proposed axial stretch model of mechanotransduction.

Reviewer #1 (Public review):

Chaiyasitdhi et al. set out to investigate the detailed ultrastructure of the scolopidia in the locust Müller's organ, the geometry of the forces delivered to these scolopidia during natural stimulation, and the direction of forces that are most effective at eliciting transduction currents. To study the ultrastructure, they used the FIB-SEM technique, to study the geometry of natural stimulation, they used OCT vibrometry and high-speed light microscopy, and to study transduction currents, they used patch clamp physiology.

Strengths:

I believe that the ultrastructural description of the locust scolopidium is excellent and the first of its kind in any insect system. In particular, the finding of the bend in the dendritic cilium and the position of the ciliary dilation are interesting, and it would be interesting to see whether these are common features within the huge diversity of insect chordotonal organs.

I believe the use of OCT to measure organ movements is a significant strength of this paper; however, using ex vivo preparations undermines any conclusions drawn about the system's in vivo mechanics.

The choice of Group III scolopidia is also good. Research on the mechanics of locust tympana has shown that travelling waves are formed on the tympanum and waves of different frequencies show highest amplitudes at different positions on the tympanum, and therefore also on different groups of scolopidia within the Müller's organ (Windmill et al, 2005; 2008, and Malkin et al, 2013). The lowest frequency modal waves (F0) observed by Windmill et al 2008 were at about 4.4 kHz, which are slightly higher than the ~3 kHz frequencies studied in this paper but do show large deflections where these group III scolopidia attach at the styliform body (Windmill et al, 2005).

This should be mentioned in the paper since the electrophysiology justification to use group III neurons is less convincing, given that Jacobs et al 1999 clearly point out that group III neurons are very variable and some of them are tuned much higher to 10 kHz, and others even higher to 20-30 kHz.

Weaknesses:

Specifically, it is understandable that the authors decided to use excised ears for the light microscopy, where Müller's organ would not be accessible in situ. However, it is very likely that excision will change the system's mechanics, especially since any tension or support to Müller's organ will be ablated. OCT enables in vivo measurements in fully undissected systems (Mhatre et al, Biorxiv, 2021) or in systems with minimal dissection where the mechanics have not been compromised (Vavakou et al, 2021). The choice to entirely dissect out the membrane is difficult to understand here.

My main concern with this paper, however, is the use of light microscopy very close to the Nyquist limit to study scolopidial motion, and the fact that the OCT data contradict and do not match the light microscopy data.

The light microscopy data is collected at ~8 kHz, and hence the Nyquist limit is ~4 kHz. It is possible to measure frequencies reliably this close to the limit, but the amplitude of motion is quite likely to be underestimated, given that the technique only provides 2 sample points per cycle at 4 kHz and approximately 2.66 sample points at 3 kHz. At that temporal resolution, the samples are much more likely to miss the peak of the wave than not, and therefore, amplitudes will be misestimated. A much more reasonable sample rate for amplitude estimation is generally about 10 samples per cycle. I do not believe the data from the microscopy is reliable for what the authors wish to use them for.

Using the light microscopy data, the authors claim that the strains experienced by the group III scolopidia at 3 kHz are greater along the AP axis than the ML axis (Figure 4). However, this is contradicted by the OCT data, which show very low strain along the AP axis (black traces) at and around 3 kHz (Figure 3c and extended data Figure 2f) and show some movement along the ML axis (red traces, same figures). The phase at low amplitudes of motion cannot be considered very reliable either, and hence phase variations at these frequencies in the OCT cannot be considered reliable indicators of AP motion; hence, I'm unclear whether the vector difference in the OCT is a reliable indicator of movement.

The OCT data are significantly more reliable as they are acquired at an appropriate sampling rate of 90 kHz. The authors do not mention what microphone they use to monitor or calibrate their sound field and phase measurements in OCT, but I presume this was done since it is the norm. Thus, the OCT data show that the movement within the Müller's organ is complex, probably traces an ellipse at some frequencies as observed in bushcrickets (Vavkou et al, 2021) and also thought to be the case in tree crickets based on the known attachment points of the TO (Mhatre et al, 2021). The OCT data shows relatively low AP motion at frequencies near 3 kHz, and higher ML motion, which contradicts the less reliable light microscopy data. Given that the locust membrane shows peaks in motion at ~4.5 kHz, ~11 kHz, and also at ~20 kHz (Windmill et al, 2008), I am surprised that the authors limited their OCT experiments and analyses to 5 kHz.

In summary for this section, I am not convinced of the conclusion drawn by the authors that group III scolopidia receive significantly higher stimulation along the AP axis in their native configuration, if indeed they were studied in the appropriate force regime (altered due to excision).

In the scolopidial patch clamp data, the authors study transduction currents in response to steady state stimulation along the AP axis and the ML axis. The responses to steady state and periodic forces may well be different, and the authors do not offer us a way to clearly relate the two and therefore, to interpret the data.

In addition, both stimulation types, along the AP axis and the ML, elicit clear transduction responses. Stimulation along the AP axis might be slightly higher, but there is over 40% variation around the mean in one case (pull: 26.22 {plus minus} 10.99 pA) and close to 80% variation in the other (push: 10.96 {plus minus} 8.59 pA). These data are indeed from a very high displacement range (2000 nm), which is very high compared to the native displacement levels, which are in the 1-10 nm range.

The factor change from sample to sample is not reported, and is small even overall. The statistical analyses of these data are not clearly reported, and I don't see the results of the overall ANOVA in the results section. I also find the dip in the reported transduction currents between 10 and 100 nm quite odd (Figure 5 j-m) and would like to know what the authors' interpretation of this behaviour is. It seems to me that those currents increase continuously linearly after ~50-100 nm and that the data below that range are in the noise. Thus, the transduction currents observed at the relevant displacement range (1-10 nm) may not actually be reliable. How were these small displacements achieved, and how closely were the actual levels monitored? Is it possible to reliably deliver 1-10 nm displacements using a micromanipulator?

What is clear, despite the difficulty in interpreting this data, is that both AP and ML stimulation evoke transduction currents, and their relative differences are small. Additionally, in Müller's organ itself, in the excised organ, the scolopidia are stimulated along both axes. Thus, in my opinion, it is not possible to say that axial stretch along the cilium is 'the key mechanical input that activates mechano-electrical transduction'.

Reviewer #2 (Public review):

Summary of strengths and weaknesses:

Using several techniques-FIB-SEM, OCT, high-speed light microscopy, and electrophysiology-Chaiyasitdhi et al. provide evidence that chordotonal receptors in the locust ear (Müller's organ) sense the stretch of the scolapale cell, primarily of its cilium. Careful measurements certainly show cell stretch, albeit with some inconsistencies regarding best frequencies and amplitudes. The weakest argument concerns the electrophysiological recordings, because the authors do not show directly that the stimulus stretches the cells. If this latter point can be clarified, then our confidence that ciliary stretch is the proximal stimulus for mechanotransduction will be increased. This conclusion will not come as a surprise for workers in the field, as the chordotonal organ is known as a stretch-receptor organ (e.g., Wikipedia). But it is a useful contribution to the field and allows the authors to suggest transduction mechanisms whereby ciliary stretch is transduced into channel opening.

Reviewer #3 (Public review):

Summary:

The paper 'A stretching mechanism evokes mechano-electrical transduction in auditory chordotonal neurons' by Chaiyasitdhi et al. presents a study that aims to address the mechanical model for scolopidia in Schistocerca gregaria Müller's organ, the basic mechanosensory units in insect chordotonal organs. The authors combine high-resolution ultrastructural analysis (FIB-SEM), sound-evoked motion tracking (OCT and high-speed light microscopy), and electrophysiological recordings of transduction currents during direct mechanical stimulation of individual scolopidia. They conclude that axial stretching along the ciliary axis is an adequate mechanical stimulus for activating mechanotransduction channels.

Strengths/Highlights:

(1) The 3D FIB-SEM reconstruction provides high resolution of scolopidial architecture, including the newly described "scolopale lid" and the full extent of the cilium.

(2) High-speed microscopy clearly demonstrates axial stretch as the dominant motion component in the auditory receptors, which confirms a long-standing question of what the actual motion of a stretch receptor is upon auditory stimulation.

(3) Patch-clamp recordings directly link mechanical stretch to transduction currents, a major advance over previous indirect models.

Weaknesses/Limitations:

(1) The text is conceptually unclear or written in an unclear manner in some places, for example, when using the proposed model to explain the sensitivity of Nanchung-Inactive in the discussion.

(2) The proposed mechanistic models (direct-stretch, stretch-compression, stretch-deformation, stretch-tilt) are compelling but remain speculative without direct molecular or biophysical validation. For example, examining whether the organ is pre-stretched and identifying the mechanical components of cells (tissues), such as the extracellular matrix and cytoskeleton, would help establish the mechanical model and strengthen the conclusion.

(3) To some extent, the weaknesses of the paper are part of its strengths and vice versa. For example, the direct push/pull and up/down stimulations are a great experimental advance to approach an answer to the question of how the underlying cellular components are deformed and how the underlying ion channels are forced. However, as the authors clearly state, neither of their stimulations can limit all forces to only one direction, and both orthogonal forces evoke responses in the neurons. The question of which of the two orthogonal forces 'causes' the response cannot be answered with these experiments and has not been answered by this manuscript. But the study has brought the field a considerable step closer to answering the question. The answer, however, might be that both longitudinal ('stretch') and perpendicular ('compression') forces act together to open the ion channels and that both dendritic extension via stretch and bending can provide forces for ion channel gating. The current paper has identified major components (longitudinal stretch components) for the neurons they analysed, but these will surely have been chosen according to their accessibility, and as such, the variety of mechanical responses in Müller's organ might be greater. In light of these considerations, the authors might acknowledge such uncertainties more clearly in their paper. The paper is an impressive methodological progress and breakthrough, but it simply does not "demonstrate that axial stretch along the cilium is the adequate stimulus or the key mechanical input that activates mechano-electrical transduction" as the authors write at the start of their discussion. They do show that axial stretch dominates for the neurons they looked at, which is important information. The same applies to the end of the discussion: The authors write, "This relative motion within the organ then drives an axial stretch of the scolopidium, which in turn evokes the mechano-electrical transduction current." Reading the manuscript, the certainty and display of confidence are not substantiated by the data provided. But they are also not necessary. The study has paved the road to answer these questions. Instead, the authors are encouraged to make suggestions on how the remaining uncertainties could be removed (and what experiments or model might be used).

Author response:

Reviewer #1 (Public review):

Chaiyasitdhi et al. set out to investigate the detailed ultrastructure of the scolopidia in the locust Müller's organ, the geometry of the forces delivered to these scolopidia during natural stimulation, and the direction of forces that are most effective at eliciting transduction currents. To study the ultrastructure, they used the FIB-SEM technique, to study the geometry of natural stimulation, they used OCT vibrometry and high-speed light microscopy, and to study transduction currents, they used patch clamp physiology.

Strengths:

I believe that the ultrastructural description of the locust scolopidium is excellent and the first of its kind in any insect system. In particular, the finding of the bend in the dendritic cilium and the position of the ciliary dilation are interesting, and it would be interesting to see whether these are common features within the huge diversity of insect chordotonal organs.

Thank you very much for your comments. We indeed plan to extend and continue our approach to exploit and understand diverse chordotonal organs in insects and crustaceans.

I believe the use of OCT to measure organ movements is a significant strength of this paper; however, using ex vivo preparations undermines any conclusions drawn about the system's in vivo mechanics.

Having re-read the manuscript, we failed to explicitly describe our ex vivo preparation of Müller’s organ including key references that detail the largely retained physiological function of Müller’s organ. We have now revised this detail in the method section:

“We used an excised locust ear preparation for all experiments, following a previously described dissection protocol [9]. In short, the tympanum, with Muller’s organ attached was left intact suspended between the cuticular rim. The cuticular rim of the tympanum was fixed into a hole in a preparation dish that allowed Muller’s organ to be submerged with extracellular saline, whilst the outside of the tympanum was dry and could be stimulated with airborne sound. This ex vivo preparation of Muller’s organ retained frequency tuning (Warren & Matheson, 2018), similar electrophysiological function as freshly dissected Muller’s organs (Hill, 1983a, 1983b; Michelsen, 1968: frequency discrimination in the locust ear by means of four groups of receptor cells), and amplitude coding (Warren & Matheson, 2018). Since Müller’s organ is backed by an air-filled trachea in vivo, the addition of saline solution in the ex vivo preparation decreased its displacements ~100 fold due to a dampening effect (Warren et al., 2020).”

And in the last section of the introduction:

“Here, we combined FIB-SEM to resolve the 3D ultrastructure of a scolopidium, OCT and high-speed microscopy to examine sound-evoked motion at both the organ and individual scolopidium levels, and direct mechanical stimulation of the scolopale cap, where the ciliary tip is anchored, whilst simultaneously recording transduction currents. Here, Muller’s organ and the tympanum was excised from the locust for physiological experiments. This ex vivo preparation of Muller’s organ retained frequency tuning, amplitude coding and electrophysiological function. This preparation also permitted the enzymatic isolation of individual scolopidia whilst recording transduction currents (Warren & Matheson, 2018).”  

To further clarify physiological differences between the in vivo and ex vivo operation of the tympanum and Müller’s organ, we will perform an additional experiment for the revised manuscript by quantifying the changes in the sound-evoked tonotopic travelling wave of the tympanum using Laser Doppler Vibrometry (LDV). This result will be added to the Supplementary Text.

The choice of Group III scolopidia is also good. Research on the mechanics of locust tympana has shown that travelling waves are formed on the tympanum and waves of different frequencies show highest amplitudes at different positions on the tympanum, and therefore also on different groups of scolopidia within the Müller's organ (Windmill et al, 2005; 2008, and Malkin et al, 2013). The lowest frequency modal waves (F0) observed by Windmill et al 2008 were at about 4.4 kHz, which are slightly higher than the ~3 kHz frequencies studied in this paper but do show large deflections where these group III scolopidia attach at the styliform body (Windmill et al, 2005).

Thank you very much. We accept that the frequencies studied in this manuscript were lower than the lowest modal wave observed by Windmill et al., 2008. Other authors, according to Jacobs et al. 1999, found broad tuning form 3.4-3.74 kHz (Michelson et al., 1971) and 2-3.5 kHz (Halex et al., 1988). We settled on tuning previously measured for Group-III neurons in the same kind of preparation as in this manuscript, which was broadly around 3 kHz (Warren & Matheson, 2018).

This should be mentioned in the paper since the electrophysiology justification to use group III neurons is less convincing, given that Jacobs et al 1999 clearly point out that group III neurons are very variable and some of them are tuned much higher to 10 kHz, and others even higher to 20-30 kHz.

Looking at Fig. 7 from Jacobs et al., 1999, we indeed see that the four Group-III neurons recorded in this study are broadly tuned to 3-4 kHz. Often these tuning curves have threshold dips at higher frequencies at least 20 dB higher. We settled on the most sensitive frequency that we previously measured, and which also overlaps the most sensitive frequencies from several other studies.

Weaknesses:

Specifically, it is understandable that the authors decided to use excised ears for the light microscopy, where Müller's organ would not be accessible in situ. However, it is very likely that excision will change the system's mechanics, especially since any tension or support to Müller's organ will be ablated.

We completely understand this criticism. We have now added descriptions in the methodology and introduction (as detailed previously). In short, the tympanum was left intact suspended on the cuticle. Müller’s organ retains all (measured) physiological properties: frequency tuning, amplitude coding and electrophysiological function. To further investigate whether this excised preparation is a representative of the in vivo conditions, we plan to measure tympanal mechanics, such as the travelling wave, as part of the revisions.

OCT enables in vivo measurements in fully undissected systems (Mhatre et al, Biorxiv, 2021) or in systems with minimal dissection where the mechanics have not been compromised (Vavakou et al, 2021). The choice to entirely dissect out the membrane is difficult to understand here.

The pioneering OCT works by Mhatre et al, Biorxiv, 2021 and Vavakou et al, 2021 set the new standard of in vivo measurements in the field. We also totally agree with Reviewer#1’s view that OCT is best performed on in vivo Müller’s organ and we tried OCT imaging of Müller’s organ for several months in vivo. Although the OCT penetrates the tympanum the OCT beam does not penetrate the tracheal air sac that surrounds Müller’s organ and therefore OCT cannot be used in vivo. Please also see previous comment with regards to the intact physiological operation of Muller’s organ in the ex vivo preparation.

My main concern with this paper, however, is the use of light microscopy very close to the Nyquist limit to study scolopidial motion, and the fact that the OCT data contradict and do not match the light microscopy data. The light microscopy data is collected at ~8 kHz, and hence the Nyquist limit is ~4 kHz. It is possible to measure frequencies reliably this close to the limit, but the amplitude of motion is quite likely to be underestimated, given that the technique only provides 2 sample points per cycle at 4 kHz and approximately 2.66 sample points at 3 kHz. At that temporal resolution, the samples are much more likely to miss the peak of the wave than not, and therefore, amplitudes will be mis-estimated. A much more reasonable sample rate for amplitude estimation is generally about 10 samples per cycle. I do not believe the data from the microscopy is reliable for what the authors wish to use them for.

We understand your concern that the study of sound-evoked motion of the scolopidium using light microscopy was done near the Nyquist limit (with our average sampling rate at 8.6 ± 0.3 kHz and the Nyquist limit at 4.3 kHz). We also agree with your comment that amplitude of the motion could be underestimated at frequencies closer to the limit. However, we find that this systematic error does not change the key observation from our direct light microscopy observation that axial stretch of the scolopidium occurs around 3 kHz.

To address this concern, we plan to study the scolopidial motion within Group 1 auditory neurons, which are tuned to lower frequencies (0.5-1.5 kHz). This new set of data will allow us to obtain more data points per cycle (up to ~8.6 data points at 1 kHz). We will consider adding this result into the revised Fig. 4 or its extended data.

Regarding increasing the sampling rate, we did try to achieve higher sampling rate (> 10 kHz), however, there is a technical limitation of our camera and a trade-off between other key parameters, such as the size of the region of interest (ROI) and magnification. To increase the sampling rate, we will have to reduce the magnification or the ROI and in turn lose the spatial resolution required for quantification of the scolopidial motion or the ROI does not cover the whole scolopidial motion. The sampling rate at 8.6 ± 0.3 kHz was the best we could achieve.

Using the light microscopy data, the authors claim that the strains experienced by the group III scolopidia at 3 kHz are greater along the AP axis than the ML axis (Figure 4). However, this is contradicted by the OCT data, which show very low strain along the AP axis (black traces) at and around 3 kHz (Figure 3c and extended data Figure 2f) and show some movement along the ML axis (red traces, same figures). The phase at low amplitudes of motion cannot be considered very reliable either, and hence phase variations at these frequencies in the OCT cannot be considered reliable indicators of AP motion; hence, I'm unclear whether the vector difference in the OCT is a reliable indicator of movement.

This is our fault for not clearly explaining the orientation of the light microscopy measurement, which then leads to the reviewer’s concern about contradiction between OCT and light microscopy. Our OCT measurements was done along the Antero-Posterior (AP) and Mesio-Lateral axes (ML), while the axial stretch of the scolopidium occurs along the Dorso-Ventral (DV) axis. We recognise that the anatomical references in this manuscript can be confusing, and we tried to show the orientation of the scolopidium relative to Müller’s organ in Fig. 3b. To further clarify the orientation of our observations, we will add anatomical references in Fig. 4a and Fig. 5a. in the revised manuscript.

As stated in our result section (Line 165-167)

“Notably, we could not resolve the Group-III scolopidia along the ventro-dorsal axis—which runs parallel to the dendrite—as the OCT beam was obstructed by either the cuticle or the elevated process”

We did try to perform OCT measurement along the VD axis, but we could not resolve the scolopidial region along the scolopidial or ciliary axes because the OCT beam could not go through the thick cuticle at the edge of the tympanic membrane and the elevated process. For this reason, it is impossible for us to find an agreement or rule out any contradiction between the OCT and light microscopy since they are measuring motion along different axes. We plan to address this accessibility issue in a separate work using OCT measurements in combination with mirrors.

The OCT data are significantly more reliable as they are acquired at an appropriate sampling rate of 90 kHz. The authors do not mention what microphone they use to monitor or calibrate their sound field and phase measurements in OCT, but I presume this was done since it is the norm.

We use a condenser microphone (MK301, Microtech) and measuring amplifier (type 2610, Brüle & Kjær) for calibration. The calibration microphone was also calibrated beforehand using  a sound calibrator type 4231 from B&K.

Thus, the OCT data show that the movement within the Müller's organ is complex, probably traces an ellipse at some frequencies as observed in bushcrickets (Vavkou et al, 2021) and also thought to be the case in tree crickets based on the known attachment points of the tympanal organ (Mhatre et al, 2021). The OCT data shows relatively low AP motion at frequencies near 3 kHz, and higher ML motion, which contradicts the less reliable light microscopy data. Given that the locust membrane shows peaks in motion at ~4.5 kHz, ~11 kHz, and also at ~20 kHz (Windmill et al, 2008), I am surprised that the authors limited their OCT experiments and analyses to 5 kHz.

We found that immediately above 5 kHz the displacements reduced to undetectable magnitudes. We accept that there may be other modes of vibration at higher frequencies >10 kHz (based on Jacobs et al., 1999) that we could have detected with OCT. However, we focused our analysis on Group-III neurons at the best frequency and frequencies that we could cross-compere between our high-speed imaging system and OCT.

In summary for this section, I am not convinced of the conclusion drawn by the authors that group III scolopidia receive significantly higher stimulation along the AP axis in their native configuration, if indeed they were studied in the appropriate force regime (altered due to excision).

Again, we accept our faults for not clearly displaying the anatomical references of the scolopidial and ciliary axes in Fig. 4 and Fig. 5. We also did not clearly describe in detail that our ex vivo preparation largely retains its physiological properties. We will address the errors of our measurement near Nyquist and provide additional information from Group 1 scolopidia where we could achieve higher data points per cycle.

In the scolopidial patch clamp data, the authors study transduction currents in response to steady state stimulation along the AP axis and the ML axis. The responses to steady state and periodic forces may well be different, and the authors do not offer us a way to clearly relate the two and therefore, to interpret the data.

We will revise the Fig. 5a to clarify that the push-pull were done along the Dorso-Ventral (DV) axis and the push-pull were done along the Antero-Posterior (AP) axis. We do agree that steady-state and periodic forces may well be very different. However, valuable insight can be gained from mechanical systems when displaced outside of their normal physiological frequency (e.g. the transformative work on vertebrate hair bundle mechanics, Howard & Hudspeth, 1988). For the same reason, we believe artificial stimulation of the scolopidium gives us new and crucial information to understand scolopidial mechanics. Our main finding that stretch is the dominant stimulus should still, or at least provide strong support, that stretch is the dominant stimulus in periodical motion.

In addition, both stimulation types, along the AP axis and the ML, elicit clear transduction responses. Stimulation along the AP axis might be slightly higher, but there is over 40% variation around the mean in one case (pull: 26.22 {plus minus} 10.99 pA) and close to 80% variation in the other (push: 10.96 {plus minus} 8.59 pA). These data are indeed from a very high displacement range (2000 nm), which is very high compared to the native displacement levels, which are in the 1-10 nm range.

In this experiment, we wished to establish the upper limits (and plateau region) of displacement-transduction current response. However, even at 2000 nm we still did not see a plateau. Therefore, we believe that the strain on the scolopidium is still in the operating range even though our displacement is not. This discrepancy can be explained because the base of the scolopidium is not fixed. Therefore, the displacement imposed in our experiment is not equivalent to the strain on the cilium but a combination of pulling and stretching along the length of the dendrite. The force, however, remains along that particular axis, supporting our main finding.

Another important consideration is that the cilium is surrounded by the scolopale wall. It is assumed that the scolopale wall is far stiffer than the ciliary and will therefore limit the amount of ciliary strain.

The factor change from sample to sample is not reported and is small even overall. The statistical analyses of these data are not clearly reported, and I don't see the results of the overall ANOVA in the results section.

We reported the statistical analyses in the Fig. 5 Source Data. We will now add tables displaying these statistics in the supplementary text of the revised manuscript.

I also find the dip in the reported transduction currents between 10 and 100 nm quite odd (Figure 5 j-m) and would like to know what the authors' interpretation of this behaviour is. It seems to me that those currents increase continuously linearly after ~50-100 nm and that the data below that range are in the noise. Thus, the transduction currents observed at the relevant displacement range (1-10 nm) may not actually be reliable. How were these small displacements achieved, and how closely were the actual levels monitored? Is it possible to reliably deliver 1-10 nm displacements using a micromanipulator?

One interpretation is that the cilium has both sensitive and insensitive mechanically gated ion channels. A finding that is also supported by Effertz et al., 2012. We will add a sentence in the discussion highlighting this interpretation. We will also provide our calibration of displacement vs voltage delivered to the piezo in the Supplementary Text.

What is clear, despite the difficulty in interpreting this data, is that both AP and ML stimulation evoke transduction currents, and their relative differences are small. Additionally, in Müller's organ itself, in the excised organ, the scolopidia are stimulated along both axes. Thus, in my opinion, it is not possible to say that axial stretch along the cilium is 'the key mechanical input that activates mechano-electrical transduction'.

We confirm that the scolopidia are displaced along both. We also note that displacements of the scolopidium limited to the up-down axis will also produce a strain on the scolopidium along the push-pull axis. However, we tried to disentangle this complex motion by limiting the displacements to one axis during recordings of the transduction current. We found that displacement along the scolopidial axis generated the largest transduction currents. Even though there is large variation our statistical analysis confirmed a significant difference as stated in the result section (Line 283 – 286)

“Additionally, the transduction current evoked by pull from the resting position was larger than displacement upward, 12.17 ± 5.37 pA (N = 11, n = 11) (Tukey's procedure, p = 1.75e-03, t = -3.83) or downward 7.28 ± 9.76 pA (N = 11, n = 11) (Tukey's procedure, p = 5.10e-06, t = -4.53).”

The reason for large variation is that the discrete depolarisations (random depolarisations of unknown function and a common feature of chordotonal neurons so far recorded) have a similar magnitude to the transduction current produced by the step displacements. We will highlight these discrete depolarisations in Figure 4d and mention them in the results.

Reviewer #2 (Public review):

Summary of strengths and weaknesses:

Using several techniques-FIB-SEM, OCT, high-speed light microscopy, and electrophysiology-Chaiyasitdhi et al. provide evidence that chordotonal receptors in the locust ear (Müller's organ) sense the stretch of the scolapale cell, primarily of its cilium. Careful measurements certainly show cell stretch, albeit with some inconsistencies regarding best frequencies and amplitudes.

Thank you very much for acknowledging the strength of our study. Regarding the inconsistencies between best frequencies and amplitude, we believe that this concern largely arises from our faults for not clearly displaying the anatomical references of the scolopidial and ciliary axes in Fig. 4 and Fig. 5. As previously addressed in our response to Reviewer#1, we will add the anatomical references and revised the text to clarify the orientation of our measurements.

The weakest argument concerns the electrophysiological recordings, because the authors do not show directly that the stimulus stretches the cells. If this latter point can be clarified, then our confidence that ciliary stretch is the proximal stimulus for mechanotransduction will be increased.

We agree that the displacement is not solely stretching the scolopidium. However, the force is still constrained and acting along the push-pull axis. Due to this reason, we overestimate the displacement required to open the MET channels but stand by our conclusion that stretch is the dominant stimulus. For future work, we wish to devise a technique to mechanically clamp the base of the scolopidium and measure the more physiological relevant current-strain relationship.

This conclusion will not come as a surprise for workers in the field, as the chordotonal organ is known as a stretch-receptor organ (e.g., Wikipedia). But it is a useful contribution to the field and allows the authors to suggest transduction mechanisms whereby ciliary stretch is transduced into channel opening.

One of the goals of this manuscript is to highlight the lack of direct evidence for stretch-sensitivity of chordotonal organs, as this is assumed from their structure. More importantly the acceptance of chordotonal organs, as being stretch sensitive does not address the mechanism of how organs work. For instance, one candidate for the MET channel, NompC, is shown to be sensitive to compression (Wang et al., 2021). We find that a preconceived concept of “stretch-sensitive” mechanism, without an appreciation of scolopidium mechanics, cannot explain how NompC can be opened in chordotonal organs.

P. .E. Howse wrote in his work on ‘The Fine Structure and Functional Organisation of Chordotonal Organs’ in 1968 (Symp. Zool. Soc. Lon.) No. 23

“There is, however, a common tendency to refer to chordotonal organs in which scolopidia are contained in a connective tissue strand as “stretch receptor”. This is unfortunate in two senses, for firstly the implied function may not have been proved and secondly even if the organ responds to stretch the scolopidia may not.” then he proceeded to cite a pioneering work in the chordotonal organs of the hermit crab by R.C. Taylor (Comp. Biochem. Physiol. 1966) showing that the scolopidia may experience flexing when the connective strand are stretched.

This work represents the first efforts to investigate the problematic assumption of stretch-sensitivity of scolopidia since it was first highlighted 57 years ago.

Reviewer #3 (Public review):

Summary:

The paper 'A stretching mechanism evokes mechano-electrical transduction in auditory chordotonal neurons' by Chaiyasitdhi et al. presents a study that aims to address the mechanical model for scolopidia in Schistocerca gregaria Müller's organ, the basic mechanosensory units in insect chordotonal organs. The authors combine high-resolution ultrastructural analysis (FIB-SEM), sound-evoked motion tracking (OCT and high-speed light microscopy), and electrophysiological recordings of transduction currents during direct mechanical stimulation of individual scolopidia. They conclude that axial stretching along the ciliary axis is an adequate mechanical stimulus for activating mechanotransduction channels.

Strengths/Highlights:

(1) The 3D FIB-SEM reconstruction provides high resolution of scolopidial architecture, including the newly described "scolopale lid" and the full extent of the cilium.

(2) High-speed microscopy clearly demonstrates axial stretch as the dominant motion component in the auditory receptors, which confirms a long-standing question of what the actual motion of a stretch receptor is upon auditory stimulation.

(3) Patch-clamp recordings directly link mechanical stretch to transduction currents, a major advance over previous indirect models.

Weaknesses/Limitations:

(1) The text is conceptually unclear or written in an unclear manner in some places, for example, when using the proposed model to explain the sensitivity of Nanchung-Inactive in the discussion.

We will rephrase and make clearer the context of our findings for Nanchung-Inactive mechanism of MET in the introduction and the discussion. We will also refine and simplify unclear text overall.

(2) The proposed mechanistic models (direct-stretch, stretch-compression, stretch-deformation, stretch-tilt) are compelling but remain speculative without direct molecular or biophysical validation. For example, examining whether the organ is pre-stretched and identifying the mechanical components of cells (tissues), such as the extracellular matrix and cytoskeleton, would help establish the mechanical model and strengthen the conclusion.

We agree with the speculative nature of our four proposed hypotheses. We have, however, narrowed down from at least ten previous hypotheses (Field and Matheson, 1998). These hypotheses will enable us, and hopefully the field, to test them and more rapidly advance our understanding of how scolopidia work. We will add a section in the discussion as to the best way to experimentally test these four hypotheses (e.g pushing directly onto the cap should elicit sensitive responses for the cap-compression hypothesis).

(3) To some extent, the weaknesses of the paper are part of its strengths and vice versa. For example, the direct push/pull and up/down stimulations are a great experimental advance to approach an answer to the question of how the underlying cellular components are deformed and how the underlying ion channels are forced. However, as the authors clearly state, neither of their stimulations can limit all forces to only one direction, and both orthogonal forces evoke responses in the neurons. The question of which of the two orthogonal forces 'causes' the response cannot be answered with these experiments and has not been answered by this manuscript. But the study has brought the field a considerable step closer to answering the question. The answer, however, might be that both longitudinal ('stretch') and perpendicular ('compression') forces act together to open the ion channels and that both dendritic extension via stretch and bending can provide forces for ion channel gating.

Thank you very much for your acknowledgement of our experimental advances. We agree that this study cannot identify and localise the forces on the cilium as it is enclosed in the scolopidial unit. As previously explained, we plan to address this question in our next work by improving and expanding our experimental techniques, including modelling, to study the scolopidial mechanics based on our experiments using patch-clamp recording in combination with individual and direct manipulation the scolopidium.

The current paper has identified major components (longitudinal stretch components) for the neurons they analysed, but these will surely have been chosen according to their accessibility, and as such, the variety of mechanical responses in Müller's organ might be greater. In light of these considerations, the authors might acknowledge such uncertainties more clearly in their paper.

Our high-speed and OCT imaging confirms complex multi-dimensional displacements (and presumably forces) acting on the scolopidium. We agree that our mechanical stimulation cannot recapitulate such complex motions. But for future work we wish to extend our mechanical stimulation to three axis and also to pivot on the axis of the scolopidial cap.

The paper is an impressive methodological progress and breakthrough, but it simply does not "demonstrate that axial stretch along the cilium is the adequate stimulus or the key mechanical input that activates mechano-electrical transduction" as the authors write at the start of their discussion.

We rephrase to clarity that stretching along the “scolopidial axis”, not “along the ciliary axis” is the adequate stimulus. We cannot yet verify how this translates to forces acting on the cilium, hence the four speculative hypotheses. We will re-write the discussion to make clear that we are only interpretating the forces and displacements at the level of the cilium.

They do show that axial stretch dominates for the neurons they looked at, which is important information. The same applies to the end of the discussion: The authors write, "This relative motion within the organ then drives an axial stretch of the scolopidium, which in turn evokes the mechano-electrical transduction current." Reading the manuscript, the certainty and display of confidence are not substantiated by the data provided. But they are also not necessary. The study has paved the road to answer these questions. Instead, the authors are encouraged to make suggestions on how the remaining uncertainties could be removed (and what experiments or model might be used).

We will moderate our conclusion in the discussion, but we are confident that we have experimental repeats, and the statistical test, to support our conclusion that stretching of the scolopidium provides that largest transduction current responses (although not at the level of the cilium). As mentioned previously, we will include a section in the discussion for the best way to test the hypotheses arising from this work.

eLife Assessment

This study provides new and interesting findings that SCoR2 acts as a denitrosylase to control cardioprotective metabolic reprogramming and prevent injury following ischemia/reperfusion. The compelling evidence is supported by a novel multi-omics approach, but questions remain regarding the stability and human relevance of BDH1 as well as the sufficiency of SCoR2. Overall, the work will be of interest to cardiovascular researchers and provides valuable information to the field, though some mechanistic aspects require further clarification.

Reviewer #1 (Public review):

Summary:

This study shows a novel role for SCoR2 in regulating metabolic pathways in the heart to prevent injury following ischemia/reperfusion. It combines a new multi-omics method to determine SCoR2 mediated metabolic pathways in the heart. This paper would be of interest to cardiovascular researchers working on cardioprotective strategies following ischemic injury in the heart.

Strengths:

(1) Use of SCoR2KO mice subjected to I/R injury.

(2) Identification of multiple metabolic pathways in the heart by a novel multi-omics approach.

Comments on revisions:

Authors have addressed all concerns raised in the previous round of review. Substantial modifications have been made in response to those concerns. There are no further comments.

Reviewer #2 (Public review):

Summary:

This manuscript addresses the gap in knowledge related to the cardiac function of the S-denitrosylase SNO-CoA Reductase 2 (SCoR2; product of the Akr1a1 gene). Genetic variants in SCoR2 have been linked to cardiovascular disease, yet its exact role in heart remains unclear. This paper demonstrates that mice deficient in SCoR2 show significant protection in a myocardial infarction (MI) model. SCoR2 influenced ketolytic energy production, antioxidant levels, and polyol balance through the S-nitrosylation of crucial metabolic regulators.

Strengths:

Addresses a well-defined gap in knowledge related to the cardiac function of SNO-CoA Reductase 2. Besides the in-depth case for this specific player, the manuscripts sheds more light on the links between S-nytrosylation and metabolic reprogramming in heart.

Rigorous proof of requirement through the combination of gene knockout and in vivo myocardial ischemia/reperfusion

Identification of precise Cys residue for SNO-modification of BDH1 as SCoR2 target in cardiac ketolysis

Weaknesses:

The experiments with BDH1 stability were performed in mutant 293 cells. Was there a difference in BDH1 stability in myocardial tissue or primary cardiomyocytes from SCoR2-null vs -WT mice? Same question extends to PKM2.

In the absence of tracing experiments, the cross-sectional changes in ketolysis, glycolysis or polyol intermediates presented in Figures 4 and 5 are suggestive at best. This needs to be stressed while describing and interpreting these results.

The findings from human samples with ischemic and non-ischemic cardiomyopathy do not seem immediately or linearly in line with each other and with the model proposed from the KO mice. While the correlation holds up in the non-ischemic cardiomyopathy (increased SNO-BDH1, SNO-PKM2 with decreased SCoR2 expression), how do the Authors explain the decreased SNO-BDH1 with preserved SCoR2 expression in ischemic cardiomyopathy? This seems counterintuitive as activation of ketolysis is a quite established myocardial response to the ischemic stress. It may help the overall message clarity to focus the human data part on only NICM patients.

(partially linked to the point above) an important proof that is lacking at present is the proof of sufficiency for SCoR2 in S-Nytrosylation of targets and cardiac remodeling. Does SCoR2 overexpression in heart or isolated cardiomyocytes reduce S-nitrosylation of BDH1 and other targets, undermining heart function at baseline or under stress?

Comments on revisions:

Some of my points have been addressed. However, the points related to 1) BDH1 stability effect in cardiomyocytes; 2) human relevance of SNO-BDH1; 3) SCoR2 sufficiency remain unclear. That said, this manuscript will provide useful information to the field as such.

Reviewer #3 (Public review):

Summary:

This manuscript demonstrates that mice lacking the denitrosylase enzyme SCoR2/AKR1A1 demonstrate a robust cardioprotection resulting from reprogramming of multiple metabolic pathways, revealing<br /> widespread, coordinated metabolic regulation by SCoR2.

Strengths:

The extensive experimental evidence provided the use of the knockout model

Weaknesses:

No direct evidence for the underlying mechanism.

The mouse model used is not a tissue-specific knock-out.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review): 

Summary: 

This study shows a novel role for SCoR2 in regulating metabolic pathways in the heart to prevent injury following ischemia/reperfusion. It combines a new multi-omics method to determine SCoR2 mediated metabolic pathways in the heart. This paper would be of interest to cardiovascular researchers working on cardioprotective strategies following ischemic injury in the heart. 

Strengths:

(1) Use of SCoR2KO mice subjected to I/R injury. 

(2) Identification of multiple metabolic pathways in the heart by a novel multi-omics approach.

We thank the Reviewer for the positive review of our manuscript.

Weaknesses:

(1) Use of a global SCoR2KO mice is a limitation since the effects in the heart can be a combination of global loss of SCoR2. 

(2) Lack of a cell type specific effect. 

We agree that global KOs limit the cell type-specific mechanistic conclusions that can be drawn. Global knockouts are nonetheless informative in their own right and serve to identify phenotypes worthy of further study.

Reviewer #2 (Public review):

Summary: 

This manuscript addresses the gap in knowledge related to the cardiac function of the S-denitrosylase SNOCoA Reductase 2 (SCoR2; product of the Akr1a1 gene). Genetic variants in SCoR2 have been linked to cardiovascular disease, yet their exact role in the heart remains unclear. This paper demonstrates that mice deficient in SCoR2 show significant protection in a myocardial infarction (MI) model. SCoR2 influenced ketolytic energy production, antioxidant levels, and polyol balance through the S-nitrosylation of crucial metabolic regulators. 

Strengths: 

(1) Addresses a well-defined gap in knowledge related to the cardiac function of SNO-CoA Reductase 2. Besides the in-depth case for this specific player, the manuscript sheds more light on the links between Snitrosylation and metabolic reprogramming in the heart.

(2) Rigorous proof of requirement through the combination of gene knockout and in vivo myocardial ischemia/reperfusion. 

(3) Identification of precise Cys residue for SNO-modification of BDH1 as SCoR2 target in cardiac ketolysis 

We thank the Reviewer for their kind words.

Weaknesses: 

(1) The experiments with BDH1 stability were performed in mutant 293 cells. Was there a difference in BDH1 stability in myocardial tissue or primary cardiomyocytes from SCoR2-null vs -WT mice? The same question extends to PKM2. 

We have not assessed BDH1 stability directly in cardiomyocytes. However, S-nitrosylation increased BDH1 stability in HEK293 cells, and BDH1 expression was increased in (injured) hearts of SCoR2KO mice, together with increased SNO-BDH1. 

For PKM2, there is a wealth of published evidence from us and others that S-nitrosylation does not regulate protein stability but rather inhibits tetramerization required for full activity.  

(2) In the absence of tracing experiments, the cross-sectional changes in ketolysis, glycolysis, or polyol intermediates presented in Figures 4 and 5 are suggestive at best. This needs to be stressed while describing and interpreting these results. 

We now acknowledge this limitation in the ‘Limitations’ section of the manuscript and in edits made to the text. 

(3) The findings from human samples with ischemic and non-ischemic cardiomyopathy do not seem immediately or linearly in line with each other and with the model proposed from the KO mice. While the correlation holds up in the non-ischemic cardiomyopathy (increased SNO-BDH1, SNO-PKM2 with decreased SCoR2 expression), how do the authors explain the decreased SNO-BDH1 with preserved SCoR2 expression in ischemic cardiomyopathy? This seems counterintuitive as activation of ketolysis is a quite established myocardial response to ischemic stress. It may help the overall message clarity to focus the human data part on only NICM patients. 

We find it interesting and important that SNO-BDH1 is readily detected in human heart tissue and its level is correlated to disease state. Our findings suggest conservation of this mechanism in human heart failure. However, we caution against drawing further conclusions related to NICM or ICM. Our animal model (based on a single time point) cannot faithfully recapitulate patients with chronic heart disease or differences between NICM and ICM. 

(4) This is partially linked to the point above. An important proof that is lacking at present is the proof of sufficiency for SCoR2 in S-nitrosylation of targets and cardiac remodeling. Does SCoR2 overexpression in the heart or isolated cardiomyocytes reduce S-nitrosylation of BDH1 and other targets, undermining heart function at baseline or under stress? 

The Reviewer proposes to test the effect of SCoR2 overexpression on cardioprotection. This is an interesting experiment for future study with the following caveats. First, it presupposes that native expression of SCoR2 is insufficient to control basal steady state S-nitrosylation of SNO-BDH1 and SNO-PKM2 (this does not seem to be the case). Second, overexpressed SCoR2 may be mislocalized within cells or associated with unnatural targets. Thank you.

Reviewer #3 (Public review): 

Summary: 

This manuscript demonstrates that mice lacking the denitrosylase enzyme SCoR2/AKR1A1 demonstrate a robust cardioprotection resulting from reprogramming of multiple metabolic pathways, revealing widespread, coordinated metabolic regulation by SCoR2. 

Strengths: 

(1) The extensive experimental evidence. 

(2) The use of the knockout model. 

We thank the Reviewer for identifying strengths in our work.

Weaknesses: 

(1) The connection of direct evidence for the mechanism. 

We believe we have identified a novel mechanism for cardioprotection entailing coordinate reprogramming of multiple metabolic pathways and suggesting a widescale role for SCoR2 in metabolic regulation. This is the key message we convey. While genetic dissection of individual pathways may be worthwhile, these investigations will have their own limitations. 

(2) The mouse model used is not tissue-specific. 

Please see our response to Reviewer 1, above. 

Reviewer #1 (Recommendations for the authors):

In the study, titled "The denitrosylase SCoR2 controls cardioprotective metabolic reprogramming", Grimmett ZW et al., describe a role for SNO-CoA Reductase 2 (SCoR2) in promoting cardioprotection via metabolic reprogramming in the heart after I/R injury. Authors show that loss SCoR2 coordinates multiple metabolic pathways to limit infarct size. Overall, the hypothesis is interesting, however there are some limitations as described below: 

(1) It is unclear whether SCoR2 mice are global or cardiomyocyte specific. 

We apologize for any confusion. These are global SCoR2^-/- mice. This is now stated in the Results when first identifying the strain, as well as in the Methods.  

(2) Can the authors clarify how divergent metabolic pathways such as Ketone oxidation, glycolysis, PPP and polyol metabolism work downstream of SCoR2 to impact cardioprotection in mice with I/R. 

The metabolic pathways of ketone oxidation, glycolysis, PPP and polyols appear to converge to support ischemic cardioprotection in SCoR2^-/- mice, as depicted in the model shown in Fig. 5L. Subsequent to SNO-PKM2 blockade of flux through glycolysis (detailed in this manuscript and in Zhou et al, 2019, PMID: 30487609, as well as by others), substrates of ketolysis and glycolysis are funneled into the PPP, producing the antioxidant NADPH and energy precursor phosphocreatine, which are well-known to be cardioprotective. This occurs more readily in SCoR2^-/- mice due to elevated SNO-BDH1 (detailed in this manuscript). 

Polyols, thought to be products of the PPP carbohydrate intermediates arabinose, ribulose, xylulose (among others), have recently been shown to be harmful to cardiovascular health in humans. These polyols are uniformly downregulated in SCoR2^-/- mice. We suggest this is likely the result of S-nitrosylation of SCoR2-substrate enzymes that form polyols (SCoR2/Akr1a1 is unable to directly reduce carbohydrates to their corresponding polyols). Regulation of endogenous polyol production in humans is a new concept and the mechanisms whereby these compounds increase risk of cardiac events are a subject of active investigation. This is detailed in the final paragraph of both the Results and Discussion sections, and in Fig. 5L. 

(3) The only functional outcome of SCoR2 loss in echocardiography and measurements for apoptosis. However, it would be important to determine whether the cardioprotective effect persists. It seems cardiac function was recorded 24hours post injury and whether the benefit remains till later time point such as 2 or 4 weeks is not shown. Without this time point, loss of SCoR2 only leads to an acute increment in function. 

Loss of SCoR2 reduced post-MI mortality at 4 hr; cardiac functional changes (plus troponin, LDH, and apoptosis) were studied in surviving animals at 24 hr post-MI. Cardiac response to acute injury and to chronic injury (weeks post-MI) are not the same metabolically. This is well elucidated in the literature and exemplified by the role of PKM2, which is protective in the chronic response to MI (28 days post-MI; PMID: 32078387), but implicated in injury at shorter timepoints post-MI (PMID: 33288902, 28964797). All that said, functional changes at 2-4 weeks will be important to determine in the future, as the Reviewer indicates. 

Reviewer #2 (Recommendations for the authors): 

(1) The last paragraph of the Results section should be divided into the statement related to Table S2 in the Results section, and the rest of the paragraph should be put somewhere in the Discussion. 

Thank you for this suggestion, which we have taken. 

(2) The number of mice alive/dead should be reported in the histogram in Figure 1G. 

Done.

(3) A concise Graphical Abstract will be useful to grasp the overall logic and message of the manuscript from the beginning. 

We thank you for this suggestion and have added a graphical abstract to the manuscript.

Reviewer #3 (Recommendations for the authors): 

I would suggest having more evidence on the effect of metabolic reprogramming on which cell type. The use of a global knockout is a major limitation, and probably some in vitro experiments with shRNA knockdown in endothelial cells and fibroblasts would provide more insights. 

The reviewer suggests one direction for future study. We identify a novel mechanism for cardioprotection entailing coordinate reprogramming of multiple metabolic pathways and suggesting a widescale role for SCoR2 in metabolic regulation. This is the message we wish to convey. The role of cardiomyocytes vs contributing cell types is a thoughtful direction for future study. Thank you. 

Editor's additional comment:

The editors wish to highlight a critical issue concerning the characterization of the SCoR2−/− mice employed in this study. 

In the Methods section (page 20), the manuscript states that "SCoR2+/− mice were made by Deltagen, Inc. as described previously (33)." However, reference 33 does not describe SCoR2−/− mice; instead, it refers to other genetically modified strains, including Akr1a1+/−, eNOS−/−, and PKM2−/− mice, with no mention of a SCoR2-targeted model. 

The editors fully acknowledge that the authors may be using the term "SCoR2" as a functional synonym for Akr1a1, based on its described role as a mammalian homologue of yeast SCoR. If this is the case, such equivalence should be explicitly stated in the manuscript to prevent potential confusion. Moreover, considering that the genetic deletion of Akr1a1 (i.e., SCoR2) underlies the key mechanistic findings presented, it is essential that the manuscript include a clear and comprehensive description of the generation and validation of the mouse model used. 

We therefore ask the authors to (1) clarify the nomenclature and relationship between "SCoR2" and Akr1a1, and (2) provide full details on the generation of the knockout mice, including the targeting strategy and the genotyping procedures. This information is necessary not only to ensure transparency and reproducibility but also to allow readers to fully appreciate the biological relevance of the findings.

Thank you for identifying this inconsistency. We have adjusted the manuscript text accordingly to clearly state that SCoR2 is a functional name for the product of the Akr1a1 gene and that these SCoR2^-/- mice are the same as Akr1a1^-/- mice described in Ref 33. We have augmented the Methods text to describe the generation and genotyping of these SCoR2/Akr1a1 knockout mice.

je možné něco dělat s těmi volnými předložkami na konci řádků? je možné tam dát nějakou pevnou mezeru jako ve wordu apod.?

přeformulovat větu, aby nebyl rok a číslo hned za sebou

We can analyze key data tabs ('2022 Final S1 S2', 'Targeted % Reduction S1+2', and '2022 Final S3') and categorize companies into strategic profiles like 'beginners', 'leaders', and 'influencers'. Then we choose those who are willing to work with us and have good financial viability.

Nejednoznačný

Všude změňme na Česko

Mohli bychom u všech map ještě přidat tlačítko domů, prosím?

test de commentaires

eLife Assessment

Using high-throughput small-molecule screening, this study discloses novel modulators of the mitochondrial transcription factor A (TFAM), a key regulator of mitochondrial function. Reviewers viewed the targeting of TFAM as innovative and the study's conclusions as potentially important (especially the effects on inflammation). However, the lack of evidence for a direct effect of the compounds on TFAM activity weakens the paper's key conclusion and renders the study incomplete.

Reviewer #1 (Public review):

Summary:

The authors identify small-molecule compounds modulating the stability of the mitochondrial transcription factor A (TFAM) using a high-throughput CETSA screen and subsequent secondary assays. The identified compounds increased the protein levels of TFAM without affecting its RNA levels and led to an increase in mtDNA levels. As a read-out for dose-dependent action of the identified compounds, the authors investigated cGAS-STING and ISG activation in cellular inflammation models in the presence or absence of their compounds. The addition of TFAM modulators led to a decrease in cGAS-STING/ISG activation and decreased mtDNA release. Furthermore, beneficial effects could be determined in models of mtDNA disease (rescue of ATP rates), sclerotic fibroblasts (decreased fibrosis), and regulatory T cells (decreased activation of effector T cells). The study thus proposes novel first-in-class regulators of TFAM as a therapeutic option in conditions of mitochondrial dysfunction.

Strengths:

The authors identified TFAM as a promising target in conditions of mitochondrial dysfunction, as it is a key regulator of mitochondrial function, serving both as a transcription and packaging factor of mtDNA. Importantly, TFAM is a key regulator of mtDNA copy number, and a moderate increase in TFAM/mtDNA levels has been shown to be beneficial in a number of pathological conditions. Furthermore, mtDNA release leading to activation of inflammatory responses has been linked to a variety of pathological conditions in the last decade. Thus, the identification of small molecule modulators of TFAM that have the potential to increase mtDNA copy number and decrease inflammatory signaling is of great importance. Furthermore, the authors highlight potential applications in the field of mitochondrial disease, fibrosis, and autoimmune disease.

Weaknesses:

The central weakness of the study is the fact that the authors propose compounds as modulators or even activators of TFAM without sufficiently proving a direct effect on TFAM itself. There are no data indicating a direct effect on TFAM activity (e.g., mtDNA transcription, replication, packaging), and it is not sufficiently ruled out that other proteins (e.g., LONP1) mediate the effect. Additionally, important information on the performed screen is not provided. Thus, the data presented is currently incomplete to support the described findings. Furthermore, the introduction and discussion are lacking key references.

Reviewer #2 (Public review):

Summary:

The present paper aims to identify small molecules that could possibly affect mitochondrial DNA (mtDNA) stability, limiting cytosolic mtDNA abundance and activation of interferon signaling. The authors developed a high-throughput screen incorporating HiBiT technology to identify possible target compounds affecting mitochondrial transcription factor A (TFAM) content, a compound known to impact mtDNA stability. Cells were subsequently exposed to target compounds to investigate the impact on TNFα-stimulated interferon signaling, a process activated by cytosolic mtDNA abundance. Compound 2, an analog of arylsulfonamide, was highlighted as a possible mitochondrial transcription factor A (TFAM)-activator, and emphasized as a small molecule that could stabilize mtDNA and prevent stress-induced interferon signaling.

Strengths:

Identifying compounds that positively affect mitochondrial biology has diverse implications. The combination of high-throughput screening and assay development to connect identified compounds with cellular interferon signalling events is a strength of the current approach, and the authors should be commended for identifying compounds that broadly impact interferon signalling. The authors have incorporated diverse measurements, including TFAM content, mtDNA content, interferon signaling, and ATP content, as well as verified the necessity of TFAM in mediating the beneficial effects of the emphasized small molecule (Compound 2).

Weaknesses:

(1) While the identified compound clearly works through TFAM, Compound 2 was identified as an arylsulfonamide, which would be expected to affect voltage-gated sodium channels (e.g. PMID: 31316182). Alterations in cellular sodium content and membrane polarization could affect metabolism to indirectly influence mtDNA and TFAM content. It remains unclear if this compound directly or indirectly affects TFAM content, especially as the authors have utilized various cancer cell lines, which could have aberrant sodium channels.

(2) TFAM is nuclear encoded - if this compound directly functions to 'activate TFAM', why/how would TFAM content increase independent of nuclear transcription?

(3) While a listed strength is the incorporation of diverse readouts, this is also a weakness, as there is a lack of consistency between approaches. For instance, data is not provided to show compound 2 increases TFAM or mtDNA content following TNFα stimulation, and extrapolating between cell lines may not be appropriate. The authors are encouraged to directly report TFAM and mtDNA for target compounds 2 and 15 to support their data reported in Figure 2. Ideally, the authors would also report for compound 1 as a control.

(4) While the authors indicate compound 11 displayed the strongest effect on ISRE activity, this appears not to be identified in Figure 1B as a compound affecting TFAM content? Can the authors identify various Compounds in Figure 1B to better highlight the relationship between compounds and TFAM content?

(5) The authors suggest Compound 2 increases cellular ATP - but they are encouraged to normalize luminescence to cellular protein and OXPHOS content to better interpret this data. Additionally, the authors are encouraged to report cellular ATP content following TNFα stimulation/stress (the key emphasis of the present data) and test compound 11, which the authors have implicated as a more sensitive compound.

The discussion is really a perspective, theorizing the diverse implications of small molecule activation of TFAM. The authors are encouraged to provide a balanced discussion, including a critical evaluation of their own work, including an acknowledgement that evidence is not provided that Compound 2 directly activates TFAM or decreases mtDNA cytosolic leakage.

eLife Assessment

This study presents a useful inventory of genes that are up- and down-regulated in the mouse small intestine (duodenum and ileum) during the first postnatal month; the data were collected and analyzed using solid and validated methodology and can be used as a starting point for additional validation of specific markers and for follow-up functional studies. Some aspects of the study were incomplete, with claims being only partially supported by the data, and it is suggested that additional validation be performed. The authors attempted to correlate gene expression changes with periods of high and low NEC susceptibility, but these correlations are speculative and not supported by functional follow-up studies. Discussion of gene expression changes with NEC susceptibility would be more appropriate to include in the Discussion section and to be tempered in the results section.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors aimed to clarify the transcriptional changes across murine postnatal small intestinal development (0 days to 1 month) in both the duodenum and ileum, a period that shows morphological similarity to 20-30 week old fetal humans. This is an especially critical stage in human intestinal development, as necrotizing enterocolitis (NEC) usually manifests during these stages.

Strengths:

The authors assessed numerous timepoints between 0 days and 1 month in the postnatal mouse duodenum and ileum using bulk RNA transcriptomics of bulk-isolated tissues. Cellular deconvolution, based on relative marker expression, was used to clarify immune cell proportions in the bulk RNA sequencing data. They confirmed some transcriptional targets found in vivo primarily in mouse via qrtPCR and immunohistochemistry, but also in human fetal tissues and isolated organoids, and are of decent quality.

Weaknesses:

The overall weakness of this study, as mentioned by the authors themselves, is that the bulk transcriptomic data generated for the study were isolated from non-fractionated bulk intestinal tissue. This makes it difficult to interpret much of this data regarding cellular fractions found across developmental time. It is difficult to rationalize the approach here, as even isolation protocols of epithelial-only or mesenchyme-only tissues for bulk RNA sequencing are well established. The authors address some of these concerns using cellular deconvolution for immune cell populations, which I think might be helpful if they expanded this analysis to other cell types (mesenchyme, endothelium, glia). However, I would assume that bulk isolations across developmental time are going to be influenced primarily by the bulk of tissue-type found at each time point - primarily epithelium. But this is also confirmed by the immune transcripts becoming more apparent later in their time series, as this system becomes more established during weaning. This study might also be strengthened by comparison with data that is publicly available for early fetal stage development in humans. Comparisons between the duodenum and ileum could be strengthened by what we already know from adult data, from both epithelial- and mesenchyme-isolated fractions. The rationale of using the postnatal mouse as a comparison to NEC is also a little unclear- perhaps some of the developmental processes are similar, however, the environments are completely different. For example, even in early postnatal mouse development, you would find microbial activity and milk.

Reviewer #2 (Public review):

Summary:

This work presents a valuable resource by generating a comprehensive bulk RNA sequencing catalogue of gene expression in the mouse duodenum and ileum during the first postnatal month. The central findings of this work are based on an analysis of this dataset. Specifically, the authors characterized molecular shifts that occur as the intestine matures from an immature to an adult-like state, investigating both temporal changes and regional differences between the proximal and distal small intestine. A key objective was to identify gene expression patterns relevant to understanding the region-specific susceptibility and resistance to necrotizing enterocolitis (NEC) observed in humans during the postnatal period. They also sought to validate key findings through complementary methods and to provide comparative context with human intestinal samples. This study will provide a solid reference dataset for the community of researchers studying postnatal gastrointestinal development and diseases that arise during these stages. However, the study lacks functional validation of the interpretations.

Strengths:

(1) The inclusion of numerous time points (day 0 through 4 weeks) and comparative analyses throughout the first postnatal month.

(2) Validation of key interpretations of RNA-seq data by other methods.

(3) Linking mouse postnatal development to human premature infant development, enhancing its clinical relevance, particularly for NEC research. The inclusion of human intestinal biopsy and organoid data for comparison further strengthens this link.

(4) The investigation covers a wide array of developmental gene categories with known significance, including epithelial differentiation markers (e.g., Vil1, Muc2, Lyz1), intestinal stem cell markers (e.g., Lgr5, Olfm4, Ascl2), mesenchymal markers (e.g., Pdgfra, Vim), Wnt signaling components (e.g., Wnt3, Wnt5a, Ctnnb1), and various immune genes (e.g., defensins, T cell, B cell, ILC, macrophage markers).

Weaknesses:

(1) The primary limitation is that there is no functional validation. The study primarily focuses on the interpretation of RNA expression. This is a common limitation of transcriptomic "atlas" studies, but the functional and mechanistic relevance of these interpretations remains to be determined.

(2) The data are derived from bulk RNA-Seq of full-thickness intestinal tissue. While this approach helps capture rare cell types and both epithelial and mesenchymal components simultaneously, it does not provide cell-type-specific gene expression profiles, which might obscure important nuances. Future investigations using single-cell sequencing would be a logical follow-up.

(3) The day 4 samples were omitted due to quality issues, which might have led to missing some dynamic changes, especially given that some ISC genes show dynamic changes around day 6.

Reviewer #3 (Public review):

Summary:

This study uses bulk mRNA sequencing to profile transcriptional changes in intestinal cells during the early postnatal period in mice - a developmental window that has received relatively little attention despite its importance. This developmental stage is particularly significant because it parallels late gestation in humans, a time when premature infants are highly vulnerable to necrotizing enterocolitis (NEC). By sampling closely spaced timepoints from birth through postnatal week four, the authors generate a resource that helps define transcriptional trajectories during this phase. Although the primary focus is on murine tissue, the authors also present limited data from human fetal intestinal biopsy samples and organoids. In addition, they discuss potential links between observed gene expression changes and factors that may contribute to NEC.

Strengths:

The close temporal sampling in mice offers a detailed view of dynamic transcriptional changes across the first four weeks after birth. The authors leverage these close timepoints to perform hierarchical clustering to define relationships between developmental stages. This is a useful approach, as it highlights when transcriptional states shift most dramatically and allows for functional predictions about classes of genes that vary over time. This high-level analysis provides an effective entry point into the dataset and will be useful for future investigations. The inclusion of human fetal intestinal samples, although limited, is especially notable given the scarcity of data from late fetal timepoints. The authors are generally careful in their presentation of results, acknowledging the limitations of their approach and avoiding over-interpretation. As they note, this dataset is intended as a foundation for their lab and others, with secondary approaches required to more fully explore the biological questions raised.

Weaknesses:

One limitation of the study is the use of bulk mRNA sequencing to draw conclusions about individual cell types. It has been documented that a few genes are exclusively expressed in single cell types. For instance, markers such as Lgr5 and Olfm4 are enriched in intestinal stem cells (ISCs), but they are also expressed at lower levels in other lineages and in differentiating cells. Using these markers as proxies for specific cell populations lowers confidence in the conclusions, particularly without complementary validation to confirm cell type-specific dynamics.

Validation of the sequencing data was itself limited, relying primarily on qPCR, which measures expression at the same modality rather than providing orthogonal support. It is unclear how the authors selected the subset of genes for validation; many key genes highlighted in the sequencing data were not assessed. Moreover, the regional differences reported in Lgr5, Olfm4, and Ascl2, appearing much higher in proximal samples than in distal ones, were not recapitulated by qPCR validation of Olfm4, and this discrepancy was not addressed. Resolving such inconsistencies will be important for interpreting the dataset.

The basis for linking particular gene sets to NEC susceptibility rests largely on their spatial restriction to the distal intestine and their temporal regulation between early (day 0-14) and later (weeks 3-4) developmental stages. While this is a reasonable approach for generating hypotheses, the correlations have limited interpretive power without experimental validation, which is not provided here. Many factors beyond NEC may drive regional and temporal differences in intestinal development.

Finally, the contribution of human fetal biopsy samples is minimal. The central figure presenting these data (Figure 4A) shows immunofluorescence for LGR5, a single stem cell marker. The staining at day 35 is not convincing, and the conclusions that can be drawn are limited to confirming the localization of LGR5-positive cells to crypts as early as 26 weeks.

Navrhuju přeformulovat:

Situace je ale složitá – mladí lidé obvykle stojí na začátku své kariéry, nemají stabilní zaměstnání ani stabilní příjmy, zároveň jejich platy (zatím) nejsou tak vysoké a neměli ještě šanci si vytvořit dostatečné úspory.

eLife Assessment

This valuable study examined the roles of the posterior parietal cortex in rats performing an auditory change-detection decision task. It provided solid evidence for two subpopulations with opposing modulation patterns during decision formation and for a correspondence between neural and behavioral measures of the short timescale used for evidence evaluation.

Joint Public Review:

In this study, the authors sought to characterize the relationship between the timescales of evidence integration in an auditory change detection task and neural activity dynamics in the rat posterior parietal cortex (PPC), an area that has been implicated in the accumulation of sensory evidence. Using the state-of-the-art Neuropixel recording techniques, they identified two subpopulations of neurons whose firing rates were positively and negatively modulated by auditory clicks. The timescale of click-related response was similar to the behaviorally measured timescale for evidence evaluation. The click-related response of positively modulated neurons also depended on when the clicks were presented, which the authors hypothesized to reflect a time-dependent gain change to implement an urgency signal. Using muscimol injections to inactivate the PPC, they showed that PPC inactivation affected the rats' choices and reaction times.

There are several strengths of this study, including:

(1) Compelling evidence for short temporal integration in behavioral and neural data for this task.

(2) Well-executed and interpretable comparisons of psychophysical reverse correlation with single-trial, click-triggered neuronal analyses to relate behavior and neural activity.

(3) Inactivation experiments to test for causality.

(4) Characterization of neural subpopulations that allows for complex relationships between a brain region and behavior.

(5) Experimental evidence for an interesting way to use sensory gain change to implement urgency signals.

There are also some concerns, including:

(1) The work could be better contextualized. From a normative Bayesian perspective, the observed adaptation of timescales and gain aligns closely with optimal strategies for change detection in noisy streams: placing greater weight on recent sensory samples and lowering evidence requirements as decision urgency grows. However, the manuscript could go further in explicitly connecting the experimental findings to normative models, such as leaky accumulator or dynamic belief-updating frameworks. This would strengthen the broader impact of the work by making clear how the observed PPC dynamics instantiate computationally optimal strategies.

(2) It is unclear how the rats are performing the task, both in terms of the quality of performance (they only show hit rates, but the rats also seem to have high false alarm rates), and in terms of the underlying strategy that they seem to be using.

(3) A major conceptual weakness lies in the claim that PPC "dynamically modulates evidence evaluation in a time-adaptive manner to suit the behavioral demands of a free-response change detection task." To support this claim, it would require direct comparison of neural activity between two task demands, either in two tasks or in one task with manipulations that promote the adoption of different timescales.

(4) Some analyses of neural data are lacking or seem incomplete, without considering alternative interpretations.

(5) The muscimol inactivation results did not provide a clear interpretation about the link between PPC activity and decision performance.

Animation: carton et fils de laine entre les cartons : direction des AM en traction (normales et/ou cisaillement)

A la lecture des documents, trouver quelle est la problématique juridique majeur

La problématique est que les liens hypertexte sont soumis aux droits d'auteur. Sauf qu'il est possible d'en obtenir l'accès d'oeuvre proteger sans consentement de l'auteur. Ici c'est considerer que la communication est a l'auteur de choisir mais en soit le lien hypertexte n'est pas soumis c'est comment on la met en forme. La c'est à un large public sans restriction. Une exception à la règle pourrait être le framing.

Faire le lien avec le cours : à quelle partie du cours se rattache la thématique ?

cela renvoie aux droits d'auteur dans le cadre de la propriété intellectuelle sur les propriété littéraire et artistique.

eLife Assessment

This study presents valuable findings regardingg a rare mode of reproduction called hybridogenesis in a species pair of frogs. While parts of the study provide solid support for the claim of hybridogenesis, other parts are incomplete with certain claims being only partially supported, as alternative modes of reproduction cannot be fully ruled out.

Reviewer #1 (Public review):

Summary:

(1) Introduction Hybridogenesis involves one genome being clonally transmitted while the other is replaced by backcrossing. It results in high heterozygosity and balanced ancestry proportions in hybrids. Distinguishing it from other hybrid systems requires a combination of nuclear, mitochondrial, and population-genetic evidence. Hybridogenesis has been identified in only a few taxa (e.g., some fish, frogs, and stick insects), but no new cases have been reported in over a decade. Advancements in high-throughput sequencing now allow for the detection of high individual heterozygosity, which can indicate hybridization, but it is difficult to distinguish hybridogenesis from other similar asexual systems based solely on genome-wide data. To differentiate these systems, researchers look at several key indicators: Presence of pure-species offspring from hybrids (possible only in hybridogenesis); sex ratio (male presence in hybridogenetic systems); nuclear and mitochondrial haplotype sharing with co-distributed parental species; geographic distribution patterns, especially the lack of both parental species in hybrid populations.

(2) What the authors were trying to achieve The paper studies Quasipaa Frogs. Q. robertingeri (narrowly endemic) and Q. boulengeri (widespread), which are morphologically similar and found sympatrically in parts of China. Preliminary RAD-seq data revealed bimodal heterozygosity in Q. boulengeri samples. Some individuals had extremely high heterozygosity, consistent across loci and suggestive of F1 hybrids. These high-heterozygosity individuals had one haplotype from each species. The study investigates the high heterozygosity observed in Quasipaa frogs, particularly in individuals morphologically resembling Q. boulengeri but genetically appearing to be F1 hybrids with Q. robertingeri. The goal is to determine whether these patterns are consistent with hybridogenesis, rather than other atypical reproductive modes. The authors also suggest the hypothesis that hybridogenesis could enable range expansion of an endemic species through hybridization with a widespread relative.

(3) Methods A total of 107 individuals from 53 localities were collected for the study. This sample included 58 sexed adults-27 males and 31 females-as well as a majority of tadpoles. Of these individuals, 31 had previously determined karyotypes. DNA was extracted and sequenced. Individual heterozygosity and ancestry were estimated using bioinformatics tools. F1 hybrids were compared to one of the parental species to examine patterns of fixed heterozygous loci. Mitochondrial DNA was also extracted from sequencing data, and phylogenetic trees were constructed

(4) Results Two groups of individuals were detected based on heterozygosity: one group exhibited high heterozygosity and consisted of F1 hybrids, while the other group showed low heterozygosity, representing pure-species types. The F1 hybrids demonstrated approximately equal ancestry from Q. robertingeri and Q. boulengeri, consistently maintaining a high proportion of heterozygous loci at around 16.7%. In contrast, pure individuals had much lower heterozygosity, approximately 2.9%. F1 hybrids were found across 21 different sites, including both male and female individuals. The presence of numerous fixed heterozygous loci in F1 hybrids confirmed their hybrid origin, and these loci were absent in pure Q. boulengeri samples. F1 individuals typically carried one haplotype from each parental species. There was minimal haplotype sharing between the two pure species, but extensive sharing was observed between F1 hybrids and co-occurring pure-species individuals. In fact, F1 types shared haplotypes with local Q. boulengeri in over 90% of cases, which supports the occurrence of local backcrossing and parental contribution. In terms of mitochondrial DNA, F1 hybrids possessed mitochondrial haplotypes that clustered with Q. boulengeri and often shared these haplotypes directly. Genetic structure and phylogenetic analyses, revealed three distinct genetic clusters corresponding to F1 hybrids, Q. boulengeri, and Q. robertingeri. The F1 hybrids positioned themselves intermediate between the two pure species. Neighbor-joining trees and TreeMix analyses confirmed a strong separation between pure-species types, with F1 hybrids clustering alongside local Q. boulengeri subpopulations, indicating local formation of hybrids.

(5) Discussion In summary, the study reveals hybridogenesis (a reproductive system where hybrids clonally transmit one parental genome) in Quasipaa boulengeri and Q. robertingeri. Hybrids show high genetic heterozygosity and coexist with parental species, ruling out other reproductive modes like parthenogenesis or kleptogenesis. Evidence suggests hybridogenesis enables Q. robertingeri genomes to appear far outside their normal range, possibly aiding range expansion. Chromosomal abnormalities are linked to hybrid hybrids, supporting clonal genome transmission. The genetic divergence between parental species fits patterns seen in other hybridogenetic systems, highlighting a unique, understudied case in East Asia.

Strengths:

Overall, the authors carefully interpret their genetic data to support hybridogenesis as the reproductive mode in this system and propose that this mechanism may aid range expansion. They also appropriately acknowledge the need for further cytogenetic and ecological studies, demonstrating scientific caution. In summary, the discussion reasonably follows from the results, offering cautious interpretation where necessary.

Weaknesses:

Direct reproductive or cytological evidence is still lacking. While alternative reproductive modes are discussed and mostly ruled out logically, some require further empirical testing. The authors maintain a cautious interpretation, appropriately suggesting further research. Some outstanding questions remain.

(1) The elevated heterozygosity and presence of fixed heterozygous loci in hybrids compared to parental species strongly indicate hybridogenesis. However, alternative explanations such as repeated F1 hybridization or some form of balanced polymorphism, while less likely, are not fully excluded.

(2) The coexistence of hybrids and parental species, along with high nuclear and mitochondrial haplotype sharing between hybrids and Q. boulengeri, argues against reproductive modes like parthenogenesis, gynogenesis, or kleptogenesis. However, the assumption that hybrid sterility or multiple local hybrid origins are unlikely could be challenged if undetected local variation or cryptic reproductive strategies exist.

(3) The presence of Q. robertingeri nuclear genomes far outside their known geographic range, genetically linked to nearby populations, fits a hybridogenetic-mediated dispersal model. Although the authors dismiss human-mediated or accidental transport as explanations, these scenarios are not necessarily unlikley.

Reviewer #2 (Public review):

This study describes F1 hybrid frog lineages that use an "unusual" form of reproduction, perhaps hybridogenesis. Identifying such species is important for understanding the biodiversity of reproduction in animals, and animals that do not reproduce via "canonical" sex can be useful model systems in ecology and evolution. The conclusion of the study are based on reduced representation sequencing (RAD-seq with a de-novo assembly of loci) of 107 wild-caught individuals from 53 localities (plus 4 outgroup individuals), including 27 males, 31 females, and 49 juveniles of unknown sex. Conclusive inferences of unusual forms of reproduction typically require breeding studies and parent-offspring genotype comparisons but such information is not available (and perhaps impossible to generate) for the focal frog lineages.

(1) Conclusion 1: there are two pure species and F1 hybrids

The authors infer that there are two lineages RR and BB (corresponding to two named species), and F1 interspecific hybrids RB. This inference is based on the results presented in Figure 1 (PCA, admixture, and heterozygosity analyses) as well as analyses of fixed SNP differences between R and B. I think that this conclusion is well supported; my only comment on this part is that it would be useful to have the admixture plots & cross-validation for the 107 samples with other k values (not only k=2) as a supplemental figure. The plots in the supplemental file S1 are for the subset of 55 inds inferred to be BB only.

(2) Conclusion 2: F1 hybrids most likely reproduce via hybridogenesis

This conclusion is based on the sex ratio of hybrids and haplotype sharing between species and lineages at different, ~150 bp long loci. Parthenogenesis (including sperm-dependent parthenogenesis) is unlikely to generate males, yet sexed F1 hybrid individuals include 18 females and 10 males which prompts the exclusion of parthenogenesis in the present paper. Specific haplotype-sharing patterns are also discussed in the study and used as further support, but these arguments (and the related main and supplementary figures) are difficult to read/interpret. To clarify the arguments related to haplotype sharing and haplotype diversities, I suggest that the authors phase the R and B haplotypes from all their hybrids by using their pure (RR and BB individuals) as references. The concatenated lineage-specific haplotypes can then be used to reconstruct a single phylogenetic tree for all loci (easier to visualize and interpret that the separate haplotype networks for the loci). The authors can then draw cartoon phylogenies for what would be the expected pattern for haplotype clustering and diversity for different reproductive modes, and discuss their observed phylogenies in this regard. Similarly, the migration weights (represented in Figure 4) can then also be computed for separate haplotypes in the hybrids.

However, independently of the outcome of the phasing, it is important to note that there is no a priori reason why all F1 hybrid individuals would reproduce via the same reproductive mode. Notably, work by Barbara Mantovani and Valerio Scali on stick insects has shown that different F1 hybrid lineages involving the same parental species reproduce via hybridogenesis or parthenogenesis. I don't see how the presented data can allow excluding that some F1 hybrid frogs are parthenogenetic while others are hybridogenetic for example.

(3) Conclusion 3: Crosses between hybridogenetic RB males and hybridogenetic RB females gave rise to a new population of RR individuals outside of the RR species range (this new population would correspond to location 30 from Figure 1).

It is not entirely clear to me which data this conclusion is based on, I believe it is the combination of known species ranges for the species R (location 30 being outside of this) and the relatively low heterozygosity of RR individuals at location 30.

However, as the authors point out, the study focuses on an understudied geographic range. Isolated or rare populations of the R species may easily have been overlooked in the past, especially since the R and B species are morphologically difficult to distinguish. Furthermore, an isolated, perhaps vestigial population may also likely be inbred/feature low diversity. It seems most appropriate to discuss different (equally likely) scenarios for the RR population at location 30 rather than implying a hybridogenetic origin of RR individuals. I would also choose a title that does not directly imply this scenario but reflects the solid (not speculative) findings of the study.

Reviewer #3 (Public review):

Summary:

This work reports a new case of hybridogenetic reproduction in the frog genus Quasipaa. Only one other example of this peculiar reproductive mode is known in amphibians, and fewer than a dozen across the tree of life. Interestingly, a population of one of the parental species (Q. robertingeri) was found away from the core of its distribution, within the distribution of the hybridogens. This range expansion might have been mediated by hybridogenesis, whereby two copies of the same parental genome came together again after many generations of hybridogenesis.

Strengths:

Evidence for hybridogenesis is solid. The state of the art would be to genotype parents and offspring, but other known alternative scenarios have been considered carefully and can be ruled out convincingly. In addition, the authors are very careful in their phrasing and made sure to never overinterpret their data.

The explicit predictions under different reproductive modes (and Table 1) are a useful resource for future studies and could inspire new findings of unusual reproductive modes in other taxa.

The sampling is very impressive, with over 50 populations sampled across a very large area.

The comparison of p-distances between pairs of species involved in hybridogenesis is interesting.

Weaknesses:

The current phylogenetic reconstruction with the F1s does not enable to infer the number of origins of hybridogenesis, nor whether the population of Q. robertingeri that was found far from the core of the species' distribution indeed derives from hybridogenesis. This is because some of the signal is driven by the Q. boulengeri haplome, which is replaced every generation and therefore does not reflect the evolutionary history of the lineage.

All known reproductive modes except hybridogenesis can be excluded, but without genotyping parents and offspring, it is impossible to rule out another, yet undescribed reproductive mode.

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DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_9792

Curator: @scibot

SciCrunch record: RRID:BDSC_9792

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_1776

Curator: @scibot

SciCrunch record: RRID:BDSC_1776

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_23261

Curator: @scibot

SciCrunch record: RRID:BDSC_23261

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_52647

Curator: @scibot

SciCrunch record: RRID:BDSC_52647

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_42704

Curator: @scibot

SciCrunch record: RRID:BDSC_42704

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_9917

Curator: @scibot

SciCrunch record: RRID:BDSC_9917

What is this?

DOI: 10.1101/2025.10.09.681358

Resource: RRID:BDSC_73333

Curator: @scibot

SciCrunch record: RRID:BDSC_73333

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DOI: 10.1101/2025.10.09.681327

Resource: (CCLV Cat# CCLV-RIE 1035, RRID:CVCL_0023)

Curator: @scibot

SciCrunch record: RRID:CVCL_0023

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